Sys.setenv(RETICULATE_PYTHON = "/usr/bin/python3")
library(shiny)
library(shinydashboard)
library(shinyWidgets)
library(ggplot2)
library(dplyr)
library(tidyr)
library(gt)
library(grid)
library(scales)
library(png)
library(purrr)
library(httr)
library(arrow)
library(readr)
library(reticulate)

PASSWORD <- Sys.getenv("password")

has_ggimage <- requireNamespace("ggimage", quietly = TRUE)
if (has_ggimage) library(ggimage)

repo_id <- "CoastalBaseball/AdvancePitcher"
hf_token <- Sys.getenv("Advance_Reader")
if (identical(hf_token, "")) {
  stop("HF token not found. Add a Space secret named 'Advance_Reader'.")
}

hf_cache_dir <- function() {
  # If HF persistent storage exists, use it; otherwise use a stable local cache folder
  d <- if (dir.exists("/data")) "/data/hf_cache" else "/tmp/hf_cache"
  dir.create(d, recursive = TRUE, showWarnings = FALSE)
  d
}

hf_download_file_cached <- function(repo_id, filename) {
  url <- paste0("https://huggingface.co/datasets/", repo_id, "/resolve/main/", filename)
  dest <- file.path(hf_cache_dir(), filename)
  
  if (file.exists(dest) && file.info(dest)$size > 0) return(dest)
  
  cat("Downloading", filename, "from HF...\n")
  resp <- GET(url, add_headers(Authorization = paste("Bearer", hf_token)))
  
  if (status_code(resp) != 200) {
    stop(paste0("Failed to download ", filename, " (status ", status_code(resp), ")."))
  }
  
  writeBin(content(resp, "raw"), dest)
  dest
}

download_private_csv_cached <- function(repo_id, filename) {
  path <- hf_download_file_cached(repo_id, filename)
  readr::read_csv(path, show_col_types = FALSE)
}

# Small helper: collect arrow queries to a real data.frame when you need it
collect_df <- function(x) {
  as.data.frame(dplyr::collect(x))
}

download_private_parquet <- function(repo_id, filename) {
  url <- paste0("https://huggingface.co/datasets/", repo_id, "/resolve/main/", filename)
  
  api_key <- Sys.getenv("HF_TOKEN")
  
  if (api_key == "") {
    stop("API key is not set.")
  }
  
  response <- GET(url, add_headers(Authorization = paste("Bearer", api_key)))
  
  if (status_code(response) == 200) {
    temp_file <- tempfile(fileext = ".parquet")
    
    writeBin(content(response, "raw"), temp_file)
    
    data <- read_parquet(temp_file)
    
    return(data)
  } else {
    stop(paste("Failed to download dataset. Status code:", status_code(response)))
  }
}

download_master_dataset <- function(repo_id, folder, token = Sys.getenv("HF_TOKEN")) {
  hf <- reticulate::import("huggingface_hub")
  api <- hf$HfApi()
  
  files <- api$list_repo_files(repo_id = repo_id, repo_type = "dataset", token = token)
  pq_files <- files[grepl(paste0("^", folder, "/.*\\.parquet$"), files)]
  
  if (length(pq_files) == 0) return(data.frame())
  
  all_data <- lapply(pq_files, function(f) {
    url <- paste0("https://huggingface.co/datasets/", repo_id, "/resolve/main/", f)
    resp <- httr::GET(url, httr::add_headers(Authorization = paste("Bearer", token)))
    if (httr::status_code(resp) == 200) {
      tmp <- tempfile(fileext = ".parquet")
      writeBin(httr::content(resp, as = "raw"), tmp)
      d <- arrow::read_parquet(tmp)
      file.remove(tmp)
      d
    } else NULL
  })
  
  bind_rows(Filter(Negate(is.null), all_data))
}

# ============================================================================
# LOAD TRACKMAN DATA (HF parquet) AS LAZY ARROW DATASET
# ============================================================================

cat("Loading TrackMan data from Hugging Face (lazy Arrow dataset)...\n")

parquet_path <- hf_download_file_cached(repo_id, "new_college_data25.parquet")

# TM2025 is a *lazy* Arrow Dataset (fast startup, low RAM)
TM2025 <- arrow::open_dataset(parquet_path, format = "parquet")

# tm_data stays lazy too; transformations happen in Arrow until you collect()
tm_data_lazy <- TM2025 %>%
  mutate(
    PlateLocSide = PlateLocSide / 12,
    PlateLocHeight = PlateLocHeight / 12
  )

cat("TM2025 loaded (lazy). Parquet cached at:", parquet_path, "\n")

cat("Loading merged_teams.csv...\n")
teams_data <- tryCatch({
  td <- readr::read_csv("merged_teams.csv", show_col_types = FALSE)
  # Clean up - remove rows with empty team names
  td <- td %>% dplyr::filter(!is.na(team_name) & team_name != "")
  cat("Loaded", nrow(td), "teams\n")
  td
}, error = function(e) {
  cat("WARNING: Could not load merged_teams.csv:", e$message, "\n")
  # Return empty frame with expected columns
  data.frame(
    trackman_abbr = character(),
    team_name = character(),
    team_logo = character(),
    league = character(),
    primary_color = character(),
    secondary_color = character(),
    conference_logo = character(),
    stringsAsFactors = FALSE
  )
})

#Load 2026 Data from the Master Dataset
data_2026 <- download_master_dataset("CoastalBaseball/2026MasterDataset", "pbp")

# ============================================================================
# LOAD BATTER / PITCHER HEIGHTS (small CSV)
# ============================================================================

cat("Loading batter_heights.csv from Hugging Face...\n")

pitcher_heights <- tryCatch({
  heights_df <- as.data.frame(download_private_csv_cached(repo_id, "batter_heights.csv"))
  names(heights_df) <- c("Name", "Ht")
  
  heights_df %>%
    mutate(
      Ht_clean = gsub('"', "", Ht),
      feet = suppressWarnings(as.numeric(gsub("'.*", "", Ht_clean))),
      inches = suppressWarnings(as.numeric(gsub(".*'\\s*", "", Ht_clean))),
      inches = ifelse(is.na(inches), 0, inches),
      height_inches = feet * 12 + inches
    ) %>%
    select(Name, Ht, height_inches)
}, error = function(e) {
  cat("WARNING: Could not load batter heights:", e$message, "\n")
  NULL
})

if (!is.null(pitcher_heights)) {
  cat("Loaded", nrow(pitcher_heights), "pitcher heights\n")
}

# ---- Height lookup helpers ----
get_pitcher_height <- function(name) {
  if (is.null(pitcher_heights)) return(72)
  h <- pitcher_heights %>% filter(Name == name) %>% pull(height_inches)
  if (length(h) == 0 || is.na(h[1])) return(72)
  h[1]
}

get_pitcher_height_display <- function(name) {
  if (is.null(pitcher_heights)) return("")
  row <- pitcher_heights %>% filter(Name == name)
  if (nrow(row) == 0) return("")
  row$Ht[1]
}

# ============================================================================
# COLLECT DATA FOR APP USE
# We need to collect() the lazy dataset for functions that need full data
# But we do it ONCE and keep only needed columns
# ============================================================================

cat("Collecting data with required columns only...\n")

# Define columns needed for the app
required_cols <- c(
  # Core identifiers
  "Pitcher", "Batter", "PitcherThrows", "BatterSide", "PitcherTeam", "Date", "GameUID", "GameID", "Inning",
  # Pitch info
  "TaggedPitchType", "PitchCall", "PlayResult", "KorBB", "PitchofPA", "Count",
  # Count columns
  "Balls", "Strikes", "Outs", "PAofInning", "OutsOnPlay", "RunsScored",
  # Location
  "PlateLocSide", "PlateLocHeight", "RelSide", "RelHeight", "Extension",
  # Movement & velocity
  "HorzBreak", "InducedVertBreak", "VertBreak", "RelSpeed", "SpinRate", "SpinAxis",
  # Approach angles
  "VertApprAngle", "HorzApprAngle",
  # Contact
  "ExitSpeed", "Angle", "Direction", "HitType", "Distance", "Bearing",
  # Indicators (if they exist)
  "WhiffIndicator", "SwingIndicator", "StrikeZoneIndicator",
  # Advanced metrics (if they exist)
  "stuff_plus", "woba", "wobacon"
)

# Get available columns from the lazy dataset
available_cols <- names(TM2025)
cols_to_select <- intersect(required_cols, available_cols)

cat("Selecting", length(cols_to_select), "of", length(available_cols), "columns\n")

# Collect only needed columns
tm_data <- tm_data_lazy %>%
  select(all_of(cols_to_select)) %>%
  collect_df()

cols_to_select_2026 <- intersect(required_cols, names(data_2026))
data_2026 <- data_2026 %>%
  mutate(
    PlateLocSide = PlateLocSide / 12,
    PlateLocHeight = PlateLocHeight / 12
  ) %>% 
  dplyr::select(all_of(cols_to_select_2026)) %>% 
  collect_df()

cat("Collected", nrow(tm_data), "rows and", ncol(tm_data), "columns\n")
cat("Collected", nrow(data_2026), "rows and", ncol(data_2026), "columns\n")
# Clean up lazy objects
rm(tm_data_lazy, TM2025)
gc()


# ---- SEC Benchmarks ----
sec_averages <- list(
  overall = list(
    chase = 26.2, k_rate = 26.4, bb_rate = 10, iz_whiff = 20, miss_rate = 28.9,
    fb_velo_l = 91.1, fb_velo_r = 93, strike_rate = 62.6, zone_rate = 46
  ),
  fb_sinker = list(spin = 2267, zone = 50, strike = 64.4, iz_whiff = 17.9, whiff = 22.5, chase = 23.5),
  slider    = list(velo_l = 81.6, velo_r = 83,   zone = 42, spin = 2440, strike = 61.4, iz_whiff = 22.1, whiff = 37.5, chase = 28.6),
  curveball = list(velo_l = 78.2, velo_r = 79.1, zone = 40.6, spin = 2442, strike = 57.6, iz_whiff = 22.3, whiff = 38.1, chase = 24.4),
  changeup  = list(velo_l = 81.8, velo_r = 84.1, zone = 37.1, spin = 1708, strike = 58.6, iz_whiff = 27.6, whiff = 37.7, chase = 31.2),
  cutter    = list(velo_l = 86,   velo_r = 86.8, zone = 46.9, spin = 2387, strike = 64.7, iz_whiff = 19.8, whiff = 30.4, chase = 28.9)
)

sec_extension_benchmark <- function(pt) {
  if (pt %in% c("Fastball","Four-Seam","FourSeamFastBall","Sinker","TwoSeamFastBall","Two-Seam")) return(5.83)
  if (pt %in% c("Slider","Sweeper")) return(5.54)
  if (pt %in% c("Curveball","Knuckle Curve")) return(5.47)
  if (pt %in% c("ChangeUp","Splitter")) return(5.98)
  if (pt %in% c("Cutter")) return(5.70)
  NA_real_
}

# ---- Gradient Color Function for SEC Benchmarking ----
get_gradient_color <- function(value, benchmark, metric_type = "higher_better", range_pct = 0.25) {
  if (is.na(value) || is.na(benchmark) || is.null(value) || is.null(benchmark)) return("#FFFFFF")
  if (is.nan(value) || is.infinite(value)) return("#FFFFFF")
  pal <- scales::gradient_n_pal(c("#E1463E", "white", "#00840D"))
  range_val <- benchmark * range_pct
  min_val <- benchmark - range_val
  max_val <- benchmark + range_val
  normalized <- if (metric_type == "higher_better") {
    (value - min_val) / (max_val - min_val)
  } else {
    (max_val - value) / (max_val - min_val)
  }
  normalized <- pmax(0, pmin(1, normalized))
  pal(normalized)
}

# ---- Pitch Family Classification ----
classify_pitch_family <- function(pitch_type) {
  case_when(
    pitch_type %in% c("Fastball", "Four-Seam", "Sinker", "FourSeamFastBall", 
                      "TwoSeamFastBall", "FF", "SI", "FB") ~ "FB",
    pitch_type %in% c("Cutter", "Curveball", "Slider", "Sweeper", "Slurve",
                      "CU", "SL", "FC", "SW", "KC") ~ "BB",
    pitch_type %in% c("Changeup", "ChangeUp", "Splitter", "CH", "FS") ~ "OS",
    TRUE ~ "Other"
  )
}


clean_data <- function(data) {
  
  # These columns are needed for various calculations
  if (!"Strikes" %in% names(data)) {
    cat("Adding default Strikes column...\n")
    data$Strikes <- NA_integer_
  }
  if (!"Balls" %in% names(data)) {
    cat("Adding default Balls column...\n")
    data$Balls <- NA_integer_
  }
  if (!"GameID" %in% names(data)) {
    cat("Creating GameID from GameUID...\n")
    # Use GameUID if available, otherwise create from Date+Pitcher
    if ("GameUID" %in% names(data)) {
      data$GameID <- data$GameUID
    } else if ("Date" %in% names(data)) {
      data$GameID <- paste(data$Date, data$Pitcher, sep = "_")
    } else {
      data$GameID <- seq_len(nrow(data))
    }
  }
  if (!"Count" %in% names(data)) {
    cat("Creating Count from Balls and Strikes...\n")
    data$Count <- paste0(data$Balls, "-", data$Strikes)
  }
  if (!"WhiffIndicator" %in% names(data)) {
    cat("Creating WhiffIndicator from PitchCall...\n")
    data$WhiffIndicator <- as.integer(data$PitchCall == "StrikeSwinging")
  }
  if (!"SwingIndicator" %in% names(data)) {
    cat("Creating SwingIndicator from PitchCall...\n")
    data$SwingIndicator <- as.integer(data$PitchCall %in% c("StrikeSwinging", "FoulBall", "InPlay"))
  }
  if (!"StrikeZoneIndicator" %in% names(data)) {
    cat("Creating StrikeZoneIndicator from location...\n")
    data$StrikeZoneIndicator <- as.integer(
      abs(data$PlateLocSide) <= 0.83 & 
        data$PlateLocHeight >= 1.5 & 
        data$PlateLocHeight <= 3.5
    )
  }
  
  # ---- Join pitcher heights to data if available ----
  if (!is.null(pitcher_heights)) {
    data <- data %>%
      left_join(pitcher_heights %>% select(Name, height_inches), by = c("Pitcher" = "Name")) %>%
      mutate(height_inches = ifelse(is.na(height_inches), 72, height_inches))
    cat("Joined pitcher heights to TrackMan data\n")
  } else {
    data$height_inches <- 72
  }
  
  # ---- Calculate Arm Angle using height ----
  if (!"arm_angle_savant" %in% names(data)) {
    cat("Calculating arm angles...\n")
    data <- data %>%
      mutate(
        RelSide_in    = 12 * as.numeric(RelSide),
        RelHeight_in  = 12 * as.numeric(RelHeight),
        shoulder_pos  = 0.70 * height_inches,
        Adj           = pmax(RelHeight_in - shoulder_pos, 1e-6),
        Opp           = abs(RelSide_in),
        arm_angle_deg = atan2(Opp, Adj) * 180 / pi,
        arm_angle_savant = pmin(pmax(90 - arm_angle_deg, 0), 90)
      ) %>%
      select(-RelSide_in, -RelHeight_in, -shoulder_pos, -Adj, -Opp, -arm_angle_deg)
    cat("Arm angle calculation complete\n")
  }
  
  # Verify key columns exist
  key_cols <- c("Pitcher", "Batter", "TaggedPitchType", "PlateLocSide", "PlateLocHeight",
                "RelSide", "RelHeight", "HorzBreak", "InducedVertBreak", "RelSpeed",
                "WhiffIndicator", "SwingIndicator", "StrikeZoneIndicator", "stuff_plus",
                "arm_angle_savant", "PitcherThrows", "BatterSide")
  missing_cols <- setdiff(key_cols, names(data))
  if (length(missing_cols) > 0) {
    cat("Note: Missing columns:", paste(missing_cols, collapse = ", "), "\n")
  }
  
  return(data)
  
}

tm_data <- clean_data(tm_data)
data_2026 <- clean_data(data_2026)

tm_data$Date <- as.Date(tm_data$Date)
data_2026$Date <- as.Date(data_2026$Date)

cat("tm_data is cleaned and has ", nrow(tm_data), " rows", '\n')
cat("data_2026 is cleaned and has ", nrow(data_2026), " rows")

# ============================================================================
# PITCH TYPE MATCHUP MATRIX FUNCTIONS
# ============================================================================


# Note: Matchup matrix functionality has been moved to a separate app
# to reduce memory usage

cat("Data loading complete.\n")

# ============================================================================
# PITCH COLORS - Consistent throughout app
# ============================================================================

pitch_colors <- c(
  "Fastball" = "#3465cb",
  "Four-Seam" = "#3465cb",
  "FourSeamFastBall" = "#3465cb",
  "4-Seam Fastball" = "#3465cb",
  "FF" = "#3465cb",
  "Sinker" = "#e5e501",
  "TwoSeamFastBall" = "#e5e501",
  "Two-Seam" = "#e5e501",
  "2-Seam Fastball" = "#e5e501",
  "SI" = "#e5e501",
  "Slider" = "#65aa02",
  "SL" = "#65aa02",
  "Sweeper" = "#dc4476",
  "SW" = "#dc4476",
  "Curveball" = "#d73813",
  "CB" = "#d73813",
  "Knuckle Curve" = "#d73813",
  "KC" = "#d73813",
  "ChangeUp" = "#980099",
  "Changeup" = "#980099",
  "CH" = "#980099",
  "Splitter" = "#23a999",
  "FS" = "#23a999",
  "SP" = "#23a999",
  "Cutter" = "#ff9903",
  "FC" = "#ff9903",
  "Slurve" = "#9370DB",
  "Other" = "gray50"
)

# ============================================================================
# HELPER FUNCTIONS FOR ARM ANGLE AND MOVEMENT
# ============================================================================

# Get pitcher image URL based on arm angle
get_pitcher_image_url <- function(arm_angle, is_lefty) {
  if (is_lefty) {
    if (arm_angle >= 40) {
      return("https://i.imgur.com/WYChFiq.png")
    } else if (arm_angle >= 10) {
      return("https://i.imgur.com/KeeUG6z.png")
    } else {
      return("https://i.imgur.com/HewvuXT.png")
    }
  } else {
    if (arm_angle >= 40) {
      return("https://i.imgur.com/84v0KDV.png")
    } else if (arm_angle >= 10) {
      return("https://i.imgur.com/RLlIVrc.png")
    } else {
      return("https://i.imgur.com/cjpIEME.png")
    }
  }
}

# Calculate shoulder Y position
shoulder_y_from_height <- function(height_inches = 72, shoulder_scale = 0.70) {
  (height_inches * shoulder_scale) / 12
}

# Calculate ray end point for arm angle visualization
ray_end_for_type <- function(mean_rel_side, mean_rel_height, length_units, shoulder_y) {
  dx <- abs(mean_rel_side)
  dy <- max(mean_rel_height - shoulder_y, 0)
  mag <- sqrt(dx^2 + dy^2)
  if (!is.finite(mag) || mag == 0) return(c(0, 0))
  ux <- dx / mag
  uy <- dy / mag
  x_sign <- ifelse(mean_rel_side < 0, -1, 1)
  c(x_sign * ux * length_units, uy * length_units)
}

# Build expected movement grid by release height
build_expected_movement_grid <- function(data, bin_size = 0.10) {
  if (is.null(data)) return(NULL)
  
  data %>%
    filter(!is.na(TaggedPitchType), !is.na(RelHeight),
           !is.na(HorzBreak), !is.na(InducedVertBreak),
           TaggedPitchType != "Other") %>%
    mutate(RH_bin = round(RelHeight / bin_size) * bin_size) %>%
    group_by(TaggedPitchType, RH_bin) %>%
    summarise(
      exp_hb = median(HorzBreak, na.rm = TRUE),
      exp_ivb = median(InducedVertBreak, na.rm = TRUE),
      n = n(),
      .groups = "drop"
    ) %>%
    filter(n >= 10)
}

# Final garbage collection before app starts
gc()
cat("Startup memory optimization complete\n")

# ============================================================================
# VISUALIZATION FUNCTIONS
# ============================================================================

# 1. ARM SLOT PLOT - Compact with pitcher figure and arm angle rays
create_pitcher_arm_angle_plot <- function(data, pitcher_name) {
  if (is.null(data)) {
    return(ggplot() + theme_void() + 
             annotate("text", x = 0.5, y = 0.5, label = "No data available"))
  }
  
  pitcher_data <- data %>%
    filter(Pitcher == pitcher_name, 
           !is.na(RelSide), !is.na(RelHeight),
           !is.na(TaggedPitchType), TaggedPitchType != "Other")
  
  if (nrow(pitcher_data) < 10) {
    return(ggplot() + theme_void() + 
             annotate("text", x = 0.5, y = 0.5, label = "Insufficient data"))
  }
  
  # Detect handedness
  pitcher_hand <- pitcher_data$PitcherThrows[1]
  is_lefty <- !is.na(pitcher_hand) && pitcher_hand == "Left"
  
  # Get overall arm angle
  overall_arm_angle <- mean(pitcher_data$arm_angle_savant, na.rm = TRUE)
  if (is.na(overall_arm_angle)) overall_arm_angle <- 45
  
  # Categorize arm slot type - added High 3/4
  arm_slot_category <- if (overall_arm_angle < 10) "Sidearm"
  else if (overall_arm_angle < 40) "Low 3/4"
  else if (overall_arm_angle < 47) "3/4"
  else if (overall_arm_angle < 60) "High 3/4"
  else "Overhand"
  
  # Calculate averages per pitch type for arm angle rays
  avg <- pitcher_data %>%
    filter(!is.na(arm_angle_savant)) %>%
    group_by(TaggedPitchType) %>%
    summarise(
      RelSide = mean(RelSide, na.rm = TRUE),
      RelHeight = mean(RelHeight, na.rm = TRUE),
      arm_angle = mean(arm_angle_savant, na.rm = TRUE),
      n = n(),
      .groups = "drop"
    ) %>%
    filter(n >= 5)
  
  if (nrow(avg) == 0) {
    return(ggplot() + theme_void() + 
             annotate("text", x = 0.5, y = 0.5, label = "No arm angle data"))
  }
  
  # Get pitcher image URL
  image_url <- get_pitcher_image_url(overall_arm_angle, is_lefty)
  
  # Figure positioning depends on arm angle type
  # Different figures have different poses - need to adjust x and y for each
  # Key: figures need to be LOW enough to touch the mound
  
  if (overall_arm_angle >= 47) {
    # Overhand / High 3/4 - upright figure, shift for handedness
    img_center_x <- if (is_lefty) -0.35 else 0.35
    img_center_y <- 2.20
    shoulder_y_fixed <- 4.0
    fig_size <- 0.285
  } else if (overall_arm_angle >= 40) {
    # 3/4 - slightly more shift than overhand
    img_center_x <- if (is_lefty) -0.40 else 0.40
    img_center_y <- 2.20
    shoulder_y_fixed <- 4.0
    fig_size <- 0.285
  } else if (overall_arm_angle >= 10) {
    # Low 3/4 - significant adjustment for proper alignment
    img_center_x <- if (is_lefty) -1.07 else 1.07  # More shifted for better alignment
    img_center_y <- 2.55  # Higher up
    shoulder_y_fixed <- 4.0
    fig_size <- 0.264  # Slightly taller
  } else {
    # Sidearm - dramatic lean
    img_center_x <- if (is_lefty) -0.9 else 0.9
    img_center_y <- 3.0
    shoulder_y_fixed <- 4.0
    fig_size <- 0.34
  }
  
  # Create image data frame
  img_df <- data.frame(x = img_center_x, y = img_center_y, image = image_url)
  
  # Calculate segment coordinates for arm angle rays
  # All rays originate from the fixed shoulder position
  # Catcher's view: RHP releases on catcher's left (negative X), LHP on right (positive X)
  seg <- avg %>%
    mutate(
      # Release point X: RHP arm on left side (negative), LHP arm on right side (positive)
      x_rel = if (is_lefty) abs(RelSide) else -abs(RelSide),
      y_rel = RelHeight,
      # All rays start from the same fixed shoulder point
      xs = 0,
      ys = shoulder_y_fixed,
      xe = x_rel,
      ye = y_rel
    )
  
  # Build plot with extended coordinates for wider release points
  p <- ggplot(seg) +
    # Mound/dirt rectangle - extend wider for ±4.5ft
    annotate("rect", xmin = -4.5, xmax = 4.5, ymin = 0, ymax = 0.6,
             fill = "#8B4513", alpha = 0.7) +
    # Teal background behind pitcher
    annotate("rect", xmin = -4.5, xmax = 4.5, ymin = 0.6, ymax = 4.3,
             fill = "#006F71", alpha = 0.9) +
    # Yellow stripe at top of background
    annotate("rect", xmin = -4.5, xmax = 4.5, ymin = 4.3, ymax = 4.5,
             fill = "yellow", alpha = 0.9) +
    # Rubber
    annotate("rect", xmin = -0.5, xmax = 0.5, ymin = 0.5, ymax = 0.65,
             fill = "white", color = "black", linewidth = 0.5)
  
  # Add pitcher figure - use ggimage if available, otherwise draw simple shape
  if (has_ggimage) {
    tryCatch({
      p <- p + ggimage::geom_image(
        data = img_df,
        aes(x = x, y = y, image = image),
        size = fig_size
      )
    }, error = function(e) {
      message("Could not load pitcher image: ", e$message)
      # Fallback: draw simple pitcher silhouette
      p <- p + 
        annotate("point", x = img_center_x, y = img_center_y + 1.2, size = 8, color = "gray30") +  # Head
        annotate("segment", x = img_center_x, xend = img_center_x, 
                 y = img_center_y + 0.9, yend = img_center_y - 0.3, 
                 linewidth = 3, color = "gray30")  # Body
    })
  } else {
    # Draw simple pitcher silhouette without ggimage
    p <- p + 
      annotate("point", x = img_center_x, y = img_center_y + 1.2, size = 8, color = "gray30") +
      annotate("segment", x = img_center_x, xend = img_center_x, 
               y = img_center_y + 0.9, yend = img_center_y - 0.3, 
               linewidth = 3, color = "gray30")
  }
  
  # Add shoulder point (small gray dot at fixed shoulder position)
  p <- p + annotate("point", x = 0, y = shoulder_y_fixed, color = "gray40", size = 2, shape = 16)
  
  # Add arm angle rays - THIN LINES colored by pitch type
  if (nrow(seg) > 0) {
    p <- p +
      geom_segment(
        data = seg,
        aes(x = xs, y = ys, xend = xe, yend = ye, color = TaggedPitchType),
        linewidth = 1.5, alpha = 0.9
      ) +
      # Release points - small dots with black outline
      geom_point(
        data = seg,
        aes(x = xe, y = ye, fill = TaggedPitchType),
        shape = 21, size = 3, stroke = 0.5, color = "black", alpha = 0.9
      )
  }
  
  p <- p +
    # Labels
    annotate("text", x = -3.5, y = 6.8, label = "3B", size = 2.5, fontface = "bold") +
    annotate("text", x = 3.5, y = 6.8, label = "1B", size = 2.5, fontface = "bold") +
    # Arm angle label at bottom
    annotate("label", x = 0, y = 0.15,
             label = paste0(round(overall_arm_angle, 1), "° - ", arm_slot_category),
             fill = "#e65100", color = "white", fontface = "bold", size = 2.5,
             label.padding = unit(0.15, "lines")) +
    # Scales - extended to ±4.5 for wider release points
    xlim(-4.5, 4.5) + ylim(0, 7) +
    scale_color_manual(values = pitch_colors, na.value = "gray50") +
    scale_fill_manual(values = pitch_colors, na.value = "gray50") +
    labs(title = ("Arm Angles"),
         x = "Horizontal (ft)", y = "Vertical (ft)") +
    theme_void() +
    theme(
      plot.title = element_text(size = 9, hjust = 0.5, face = "bold"),
      axis.text = element_text(size = 6),
      axis.title = element_text(size = 7),
      panel.background = element_rect(fill = "white", color = NA),
      plot.background = element_rect(fill = "white", color = NA),
      legend.position = "none",
      plot.margin = margin(2, 2, 2, 2)
    )
  
  return(p)
}

create_mini_arm_angle <- function(data, pitcher_name) {
  pitcher_data <- data %>%
    dplyr::filter(Pitcher == pitcher_name, 
                  !is.na(RelSide), !is.na(RelHeight),
                  !is.na(TaggedPitchType), TaggedPitchType != "Other")
  
  if (nrow(pitcher_data) < 10) return(ggplot() + theme_void())
  
  pitcher_hand <- pitcher_data$PitcherThrows[1]
  is_lefty <- !is.na(pitcher_hand) && pitcher_hand == "Left"
  overall_arm_angle <- mean(pitcher_data$arm_angle_savant, na.rm = TRUE)
  if (is.na(overall_arm_angle)) overall_arm_angle <- 45
  
  arm_slot_category <- if (overall_arm_angle < 10) "Side"
  else if (overall_arm_angle < 40) "L3/4"
  else if (overall_arm_angle < 47) "3/4"
  else if (overall_arm_angle < 60) "H3/4"
  else "OH"
  
  avg <- pitcher_data %>%
    dplyr::filter(!is.na(arm_angle_savant)) %>%
    dplyr::group_by(TaggedPitchType) %>%
    dplyr::summarise(
      RelSide = mean(RelSide, na.rm = TRUE),
      RelHeight = mean(RelHeight, na.rm = TRUE),
      arm_angle = mean(arm_angle_savant, na.rm = TRUE),
      n = dplyr::n(), .groups = "drop"
    ) %>%
    dplyr::filter(n >= 5)
  
  if (nrow(avg) == 0) return(ggplot() + theme_void())
  
  image_url <- get_pitcher_image_url(overall_arm_angle, is_lefty)
  shoulder_y_fixed <- 4.0
  
  if (overall_arm_angle >= 47) {
    img_center_x <- if (is_lefty) -0.35 else 0.35
    img_center_y <- 2.20; fig_size <- 0.30
  } else if (overall_arm_angle >= 40) {
    img_center_x <- if (is_lefty) -0.40 else 0.40
    img_center_y <- 2.20; fig_size <- 0.30
  } else if (overall_arm_angle >= 10) {
    img_center_x <- if (is_lefty) -1.07 else 1.07
    img_center_y <- 2.55; fig_size <- 0.27
  } else {
    img_center_x <- if (is_lefty) -0.9 else 0.9
    img_center_y <- 3.0; fig_size <- 0.34
  }
  
  img_df <- data.frame(x = img_center_x, y = img_center_y, image = image_url)
  
  seg <- avg %>%
    dplyr::mutate(
      x_rel = if (is_lefty) abs(RelSide) else -abs(RelSide),
      y_rel = RelHeight, xs = 0, ys = shoulder_y_fixed, xe = x_rel, ye = y_rel
    )
  
  p <- ggplot(seg) +
    annotate("rect", xmin = -4.5, xmax = 4.5, ymin = 0, ymax = 0.6, fill = "#8B4513", alpha = 0.7) +
    annotate("rect", xmin = -4.5, xmax = 4.5, ymin = 0.6, ymax = 4.3, fill = "#006F71", alpha = 0.9) +
    annotate("rect", xmin = -4.5, xmax = 4.5, ymin = 4.3, ymax = 4.5, fill = "yellow", alpha = 0.9) +
    annotate("rect", xmin = -0.5, xmax = 0.5, ymin = 0.5, ymax = 0.65, fill = "white", color = "black", linewidth = 0.3)
  
  if (has_ggimage) {
    tryCatch({
      p <- p + ggimage::geom_image(data = img_df, aes(x = x, y = y, image = image), size = fig_size)
    }, error = function(e) NULL)
  }
  
  p <- p + annotate("point", x = 0, y = shoulder_y_fixed, color = "gray40", size = 1, shape = 16)
  
  if (nrow(seg) > 0) {
    p <- p +
      geom_segment(data = seg, aes(x = xs, y = ys, xend = xe, yend = ye, color = TaggedPitchType),
                   linewidth = 0.8, alpha = 0.9) +
      geom_point(data = seg, aes(x = xe, y = ye, fill = TaggedPitchType),
                 shape = 21, size = 1.5, stroke = 0.3, color = "black", alpha = 0.9)
  }
  
  p <- p +
    annotate("label", x = 0, y = 0.15,
             label = paste0(round(overall_arm_angle, 1), "\u00b0 ", arm_slot_category),
             fill = "#006F71", color = "white", fontface = "bold", size = 1.8,
             label.padding = unit(0.1, "lines")) +
    xlim(-4.5, 4.5) + ylim(0, 7) +
    scale_color_manual(values = pitch_colors, na.value = "gray50") +
    scale_fill_manual(values = pitch_colors, na.value = "gray50") +
    theme_void() +
    theme(legend.position = "none", plot.margin = margin(0, 0, 0, 0),
          plot.background = element_rect(fill = "white", color = NA))
  
  return(p)
}

# 3. MOVEMENT CHART - MUCH BIGGER with expected movement diamonds
create_pitcher_movement_plot <- function(data, pitcher_name, expected_grid = NULL,
                                         show_arm_angle_rays = TRUE,
                                         show_arm_angle_annotation = TRUE,
                                         marker_style = "scaled_usage",  # "scaled_usage", "average", "none"
                                         show_individual_pitches = TRUE,
                                         show_expected_diamonds = TRUE,
                                         selected_pitch_types = NULL) {
  if (is.null(data)) {
    return(ggplot() + theme_void() + 
             annotate("text", x = 0, y = 0, label = "No data available"))
  }
  
  pitcher_data <- data %>%
    filter(Pitcher == pitcher_name,
           !is.na(HorzBreak), !is.na(InducedVertBreak),
           !is.na(TaggedPitchType), TaggedPitchType != "Other",
           !is.na(RelSpeed))
  
  # Filter by selected pitch types if provided
  if (!is.null(selected_pitch_types) && length(selected_pitch_types) > 0) {
    pitcher_data <- pitcher_data %>%
      filter(TaggedPitchType %in% selected_pitch_types)
  }
  
  if (nrow(pitcher_data) < 5) {
    return(ggplot() + theme_void() + 
             annotate("text", x = 0, y = 0, label = "Insufficient data"))
  }
  
  # Get pitcher hand
  pitcher_throws <- pitcher_data$PitcherThrows[1]
  if (is.na(pitcher_throws)) pitcher_throws <- "Right"
  is_lefty <- pitcher_throws == "Left"
  
  # Get height and calculate shoulder position
  h_in <- if ("height_inches" %in% names(pitcher_data)) {
    med_h <- median(pitcher_data$height_inches, na.rm = TRUE)
    if (is.na(med_h)) 72 else med_h
  } else 72
  shoulder_pos <- h_in * 0.70
  
  # Calculate averages by pitch type
  p_mean <- pitcher_data %>%
    group_by(TaggedPitchType) %>%
    summarize(
      HorzBreak = mean(HorzBreak, na.rm = TRUE),
      InducedVertBreak = mean(InducedVertBreak, na.rm = TRUE),
      mean_velo = round(mean(RelSpeed, na.rm = TRUE), 1),
      mean_rel_height = mean(RelHeight, na.rm = TRUE),
      mean_rel_side = mean(RelSide, na.rm = TRUE),
      mean_arm_angle = mean(arm_angle_savant, na.rm = TRUE),
      usage = n(),
      .groups = "drop"
    ) %>%
    mutate(
      usage_pct = round(usage / sum(usage) * 100, 1),
      scaled_usage = (usage - min(usage)) / max((max(usage) - min(usage)), 1) * (12 - 8) + 8,
      RH_bin = round(mean_rel_height / 0.10) * 0.10
    ) %>%
    filter(usage >= 3)
  
  # Add expected movement from grid if available
  p_mean$exp_hb <- NA_real_
  p_mean$exp_ivb <- NA_real_
  p_mean$has_expected <- FALSE
  
  if (!is.null(expected_grid) && nrow(expected_grid) > 0) {
    for (i in seq_len(nrow(p_mean))) {
      pt <- p_mean$TaggedPitchType[i]
      rh <- p_mean$RH_bin[i]
      
      match_row <- expected_grid %>%
        filter(TaggedPitchType == pt, abs(RH_bin - rh) < 0.15)
      
      if (nrow(match_row) > 0) {
        match_row <- match_row %>%
          mutate(dist = abs(RH_bin - rh)) %>%
          arrange(dist) %>%
          slice(1)
        p_mean$exp_hb[i] <- if (is_lefty) -match_row$exp_hb[1] else match_row$exp_hb[1]
        p_mean$exp_ivb[i] <- match_row$exp_ivb[1]
        p_mean$has_expected[i] <- TRUE
      }
    }
  }
  
  # Get arm angle data
  arm_angle_savant <- median(pitcher_data$arm_angle_savant, na.rm = TRUE)
  if (is.na(arm_angle_savant)) arm_angle_savant <- 45
  
  # Get arm angle category
  arm_angle_type <- if (arm_angle_savant >= 60) "Overhand"
  else if (arm_angle_savant >= 47) "High 3/4"
  else if (arm_angle_savant >= 40) "3/4"
  else if (arm_angle_savant >= 10) "Low 3/4"
  else "Sidearm"
  
  # ===== ARM ANGLE RAYS CALCULATION - FROM CENTER (0,0) OUTWARD =====
  # Rays start at origin (0,0) and extend outward based on release position
  # PITCHER'S PERSPECTIVE: RHP rays on RIGHT side, LHP rays on LEFT side
  # (opposite of batter's view arm angle visualization)
  if (show_arm_angle_rays && nrow(p_mean) > 0) {
    ray_length <- 18  # Extended ray length in chart units (inches)
    
    arm_rays <- p_mean %>%
      mutate(
        # Calculate direction from origin to release point
        # PITCHER'S PERSPECTIVE (flipped from batter's view):
        # For RHP: release is on pitcher's right (POSITIVE x)
        # For LHP: release is on pitcher's left (NEGATIVE x)
        rel_x_raw = ifelse(is_lefty, -abs(mean_rel_side), abs(mean_rel_side)),
        rel_y_raw = mean_rel_height - (shoulder_pos / 12),  # Height relative to shoulder
        
        # Normalize to unit vector
        rel_mag = sqrt(rel_x_raw^2 + rel_y_raw^2),
        rel_mag = ifelse(rel_mag == 0 | is.na(rel_mag), 1, rel_mag),
        
        # Direction components (normalized)
        dir_x = rel_x_raw / rel_mag,
        dir_y = rel_y_raw / rel_mag,
        
        # Ray start at origin (0,0) - center of chart
        ray_xs = 0,
        ray_ys = 0,
        
        # Ray end - extend outward from origin
        ray_xe = dir_x * ray_length,
        ray_ye = dir_y * ray_length
      )
  }
  
  # Create circle background - 32 inch radius
  circle_df <- data.frame(
    x = 32 * cos(seq(0, 2*pi, length.out = 100)),
    y = 32 * sin(seq(0, 2*pi, length.out = 100))
  )
  
  # Build base plot
  p <- ggplot(pitcher_data, aes(x = HorzBreak, y = InducedVertBreak)) +
    # Light teal background circle
    geom_polygon(data = circle_df, aes(x = x, y = y), fill = "#e5f3f3", color = "#e5f3f3", inherit.aes = FALSE) +
    # Grid circles - 12", 24", 32"
    geom_path(data = data.frame(x = 12 * cos(seq(0, 2*pi, length.out = 100)), 
                                y = 12 * sin(seq(0, 2*pi, length.out = 100))),
              aes(x = x, y = y), linetype = "dashed", color = "gray60", linewidth = 0.3, inherit.aes = FALSE) +
    geom_path(data = data.frame(x = 24 * cos(seq(0, 2*pi, length.out = 100)), 
                                y = 24 * sin(seq(0, 2*pi, length.out = 100))),
              aes(x = x, y = y), linetype = "dashed", color = "gray60", linewidth = 0.3, inherit.aes = FALSE) +
    geom_path(data = data.frame(x = 32 * cos(seq(0, 2*pi, length.out = 100)), 
                                y = 32 * sin(seq(0, 2*pi, length.out = 100))),
              aes(x = x, y = y), linetype = "solid", color = "gray50", linewidth = 0.5, inherit.aes = FALSE) +
    # Axis lines
    geom_segment(x = 0, y = -34, xend = 0, yend = 34, linewidth = 0.5, color = "grey55") +
    geom_segment(x = -34, y = 0, xend = 34, yend = 0, linewidth = 0.5, color = "grey55") +
    # ALL CLOCK LABELS around the circle
    annotate('text', x = 0, y = 36, label = '12', size = 4.5, fontface = "bold") +
    annotate('text', x = 18, y = 31, label = '1', size = 4, fontface = "bold") +
    annotate('text', x = 31, y = 18, label = '2', size = 4, fontface = "bold") +
    annotate('text', x = 36, y = 0, label = '3', size = 4.5, fontface = "bold") +
    annotate('text', x = 31, y = -18, label = '4', size = 4, fontface = "bold") +
    annotate('text', x = 18, y = -31, label = '5', size = 4, fontface = "bold") +
    annotate('text', x = 0, y = -36, label = '6', size = 4.5, fontface = "bold") +
    annotate('text', x = -18, y = -31, label = '7', size = 4, fontface = "bold") +
    annotate('text', x = -31, y = -18, label = '8', size = 4, fontface = "bold") +
    annotate('text', x = -36, y = 0, label = '9', size = 4.5, fontface = "bold") +
    annotate('text', x = -31, y = 18, label = '10', size = 4, fontface = "bold") +
    annotate('text', x = -18, y = 31, label = '11', size = 4, fontface = "bold") +
    # Break distance annotations
    annotate('text', x = 12, y = -2, label = '12"', size = 3, color = "gray40") +
    annotate('text', x = 24, y = -2, label = '24"', size = 3, color = "gray40") +
    annotate('text', y = 12, x = -2, label = '12"', size = 3, color = "gray40") +
    annotate('text', y = 24, x = -2, label = '24"', size = 3, color = "gray40")
  
  # ===== ADD ARM ANGLE RAYS FROM CENTER (0,0) =====
  if (show_arm_angle_rays && exists("arm_rays") && nrow(arm_rays) > 0) {
    # Add arm angle rays colored by pitch type - emanating from center
    p <- p +
      geom_segment(
        data = arm_rays,
        aes(x = ray_xs, y = ray_ys, xend = ray_xe, yend = ray_ye, color = TaggedPitchType),
        linewidth = 2, alpha = 0.85, inherit.aes = FALSE
      ) +
      # Small dots at the end of rays
      geom_point(
        data = arm_rays,
        aes(x = ray_xe, y = ray_ye, fill = TaggedPitchType),
        shape = 21, size = 3, stroke = 0.5, color = "black", alpha = 0.9, inherit.aes = FALSE
      )
  }
  
  # ===== ADD INDIVIDUAL PITCH POINTS =====
  if (show_individual_pitches) {
    p <- p + geom_point(aes(fill = TaggedPitchType), shape = 21, size = 3.5, 
                        color = "black", stroke = 0.3, alpha = 1)
  }
  
  # ===== ADD EXPECTED MOVEMENT DIAMONDS =====
  if (show_expected_diamonds) {
    exp_data <- p_mean %>% filter(has_expected == TRUE)
    if (nrow(exp_data) > 0) {
      p <- p +
        geom_point(data = exp_data,
                   aes(x = exp_hb, y = exp_ivb, fill = TaggedPitchType),
                   shape = 23, size = 7, stroke = 2, color = "black", 
                   alpha = 0.8, inherit.aes = FALSE)
    }
  }
  
  # ===== ADD MARKERS BASED ON STYLE =====
  if (marker_style == "scaled_usage") {
    # Scaled usage markers with velocity labels
    p <- p +
      geom_point(data = p_mean,
                 aes(x = HorzBreak, y = InducedVertBreak, fill = TaggedPitchType, size = scaled_usage),
                 shape = 21, color = "black", stroke = 2, alpha = 0.9, inherit.aes = FALSE) +
      geom_label(data = p_mean,
                 aes(x = HorzBreak, y = InducedVertBreak, label = mean_velo),
                 color = "black", size = 3, fontface = "bold", fill = "white", 
                 label.size = 0.3, inherit.aes = FALSE) +
      scale_size_identity()
    
  } else if (marker_style == "average") {
    # Fixed size average markers with velocity labels
    p <- p +
      geom_point(data = p_mean,
                 aes(x = HorzBreak, y = InducedVertBreak, fill = TaggedPitchType),
                 shape = 21, size = 10, color = "black", stroke = 2, alpha = 0.9, inherit.aes = FALSE) +
      geom_label(data = p_mean,
                 aes(x = HorzBreak, y = InducedVertBreak, label = mean_velo),
                 color = "black", size = 3, fontface = "bold", fill = "white", 
                 label.size = 0.3, inherit.aes = FALSE)
  }
  # If marker_style == "none", no markers are added
  
  # ===== FINISH PLOT =====
  p <- p +
    coord_fixed(xlim = c(-40, 40), ylim = c(-40, 40), clip = "off") +
    scale_fill_manual(values = pitch_colors, drop = FALSE) +
    scale_color_manual(values = pitch_colors, drop = FALSE) +
    labs(title = "Pitch Movement", x = "", y = "") +
    theme_minimal() +
    theme(
      plot.background = element_rect(fill = "white", color = NA),
      panel.background = element_blank(),
      axis.text = element_blank(),
      axis.ticks = element_blank(),
      axis.title = element_blank(),
      plot.title = element_text(hjust = 0.5, size = 16, face = "bold"),
      legend.position = "none",
      panel.grid = element_blank(),
      plot.margin = margin(20, 5, 5, 5)
    )
  
  # ===== ADD ARM ANGLE ANNOTATION AT TOP =====
  if (show_arm_angle_annotation) {
    p <- p + annotate("text", x = 0, y = 43, 
                      label = paste0(round(arm_angle_savant, 0), "° Arm Angle - ", arm_angle_type),
                      size = 5, color = "#731209", fontface = "bold")
  }
  
  return(p)
}

# 4. COUNT USAGE PIE CHARTS
create_count_usage_pies <- function(data, pitcher_name) {
  if (is.null(data)) {
    return(ggplot() + theme_void() + annotate("text", x = 0.5, y = 0.5, label = "No data"))
  }
  
  df <- data %>%
    filter(Pitcher == pitcher_name, TaggedPitchType != "Other") %>%
    group_by(TaggedPitchType) %>%
    mutate(n = 100 * n() / nrow(data %>% filter(Pitcher == pitcher_name))) %>%
    filter(n >= 2) %>%
    ungroup()
  
  if (nrow(df) == 0) {
    return(
      ggplot() +
        annotate("text", x = 0, y = 0, label = "No count data\navailable for this pitcher", size = 4) +
        theme_void()
    )
  }
  
  plot_df <- df %>%
    mutate(
      count = case_when(
        Balls == 0 & Strikes == 0 ~ "1P",
        Strikes == 2 ~ "2K",
        Balls == 3 & Strikes == 2 ~ "Full",
        Balls > Strikes ~ "Behind",
        TRUE ~ "Even"
      ),
      BatterSide = ifelse(BatterSide == "Right", "Vs Right", "Vs Left")
    ) %>%
    filter(count %in% c("1P", "Even", "Behind", "2K", "Full")) %>%
    group_by(count, BatterSide) %>%
    mutate(total_count = n()) %>%
    group_by(count, TaggedPitchType, BatterSide) %>%
    summarise(n = n(), total = first(total_count), .groups = "drop") %>%
    mutate(
      percentage = n / total * 100,
      pct_label = ifelse(percentage >= 5, scales::percent(percentage / 100, accuracy = 1), "")
    ) %>%
    arrange(desc(percentage))
  
  # Set factor order for counts
  plot_df$count <- factor(plot_df$count, levels = c("1P", "Even", "Behind", "2K", "Full"))
  
  p <- ggplot(plot_df, aes(x = "", y = percentage, fill = TaggedPitchType)) +
    geom_bar(width = 1, stat = "identity", color = "white", linewidth = 0.3) +
    geom_text(aes(label = pct_label),
              position = position_stack(vjust = 0.5),
              size = 2.5, fontface = "bold") +
    coord_polar("y", start = 0) +
    facet_grid(BatterSide ~ count, labeller = label_value) +
    scale_fill_manual(values = pitch_colors, drop = FALSE) +
    labs(title = ("Pitch Usage by Count"), fill = "Pitch Type") +
    theme_void() +
    theme(
      plot.title = element_text(hjust = 0.5, size = 11, face = "bold"),
      strip.text = element_text(size = 9, face = "bold"),
      legend.position = "none",  # Remove legend to give more room for notes
      plot.background = element_rect(fill = "white", color = NA),
      panel.background = element_rect(fill = "white", color = NA)
    )
  
  return(p)
}

# 5. PITCH CHARACTERISTICS GT TABLE WITH SEC BENCHMARKING
create_pitch_characteristics_gt <- function(data, pitcher_name) {
  if (is.null(data)) {
    return(gt::gt(data.frame(Message = "No data available")))
  }
  
  pitcher_data <- data %>%
    filter(Pitcher == pitcher_name,
           !is.na(TaggedPitchType), TaggedPitchType != "Other")
  
  if (nrow(pitcher_data) < 10) {
    return(gt::gt(data.frame(Message = "Insufficient data")))
  }
  
  # Get pitcher hand for velo benchmarks
  pitcher_hand <- if (nrow(pitcher_data) > 0 && "PitcherThrows" %in% names(pitcher_data)) {
    h <- pitcher_data$PitcherThrows[1]
    if (is.na(h)) "Right" else h
  } else "Right"
  
  total_pitches <- nrow(pitcher_data)
  
  # Check which columns exist
  has_stuff_plus <- "stuff_plus" %in% names(pitcher_data)
  has_vaa <- "VertApprAngle" %in% names(pitcher_data)
  has_haa <- "HorzApprAngle" %in% names(pitcher_data)
  
  pitch_stats <- pitcher_data %>%
    group_by(Pitch = TaggedPitchType) %>%
    summarise(
      Count = n(),
      `Usage%` = round(100 * n() / total_pitches, 1),
      `Avg Velo` = round(mean(RelSpeed, na.rm = TRUE), 1),
      `Max Velo` = round(max(RelSpeed, na.rm = TRUE), 1),
      `Avg Spin` = round(mean(SpinRate, na.rm = TRUE), 0),
      `Avg IVB` = round(mean(InducedVertBreak, na.rm = TRUE), 1),
      `Avg HB` = round(mean(HorzBreak, na.rm = TRUE), 1),
      VAA = if (has_vaa) round(mean(VertApprAngle, na.rm = TRUE), 1) else NA_real_,
      HAA = if (has_haa) round(mean(HorzApprAngle, na.rm = TRUE), 1) else NA_real_,
      hRel = round(mean(RelSide, na.rm = TRUE), 2),
      vRel = round(mean(RelHeight, na.rm = TRUE), 2),
      Ext = round(mean(Extension, na.rm = TRUE), 2),
      # Calculate Strike% directly from PitchCall
      `Strike%` = round(100 * mean(!PitchCall %in% c("BallCalled", "BallinDirt", "BallIntentional"), na.rm = TRUE), 1),
      # Calculate Whiff% directly from PitchCall
      n_swings = sum(PitchCall %in% c("StrikeSwinging", "FoulBall", "FoulBallNotFieldable", "FoulBallFieldable", "InPlay"), na.rm = TRUE),
      n_whiffs = sum(PitchCall == "StrikeSwinging", na.rm = TRUE),
      `Whiff%` = ifelse(n_swings > 0, round(100 * n_whiffs / n_swings, 1), 0),
      # Calculate Zone% directly from PlateLocSide/Height
      `Zone%` = round(100 * mean(PlateLocSide >= -0.83 & PlateLocSide <= 0.83 &
                                   PlateLocHeight >= 1.5 & PlateLocHeight <= 3.5, na.rm = TRUE), 1),
      `Stuff+` = if (has_stuff_plus) round(mean(stuff_plus, na.rm = TRUE), 0) else NA_real_,
      .groups = "drop"
    ) %>%
    select(-n_swings, -n_whiffs) %>%
    filter(Count >= 5) %>%
    arrange(desc(`Usage%`))
  
  num_rows <- nrow(pitch_stats)
  
  if (num_rows == 0) {
    return(gt::gt(data.frame(Message = "No pitch data found")))
  }
  
  # Build GT table
  gt_tbl <- pitch_stats %>%
    gt::gt() %>%
    gt::tab_header(title = gt::md("**Pitch Characteristics (vs SEC Benchmarks)**")) %>%
    gt::cols_align(align = "center", columns = everything()) %>%
    gt::cols_align(align = "left", columns = "Pitch") %>%
    gt::sub_missing(missing_text = "-") %>%
    gt::tab_options(
      table.font.size = gt::px(11),
      data_row.padding = gt::px(4),
      column_labels.font.weight = "bold",
      heading.title.font.size = gt::px(14)
    )
  
  # Apply SEC benchmark coloring row by row
  for (i in seq_len(num_rows)) {
    pt <- pitch_stats$Pitch[i]
    
    # Get SEC reference for this pitch type
    sec_ref <- if (pt %in% c("Fastball", "Four-Seam", "FourSeamFastBall", "Sinker", "Two-Seam", "TwoSeamFastBall")) {
      sec_averages$fb_sinker
    } else if (pt == "Cutter") {
      sec_averages$cutter
    } else if (pt %in% c("Slider", "Sweeper")) {
      sec_averages$slider
    } else if (pt %in% c("Curveball", "Knuckle Curve")) {
      sec_averages$curveball
    } else if (pt %in% c("ChangeUp", "Splitter")) {
      sec_averages$changeup
    } else NULL
    
    if (!is.null(sec_ref)) {
      # Velocity benchmark
      velo_bench <- NA_real_
      if (pt %in% c("Fastball", "Four-Seam", "FourSeamFastBall", "Sinker", "Two-Seam", "TwoSeamFastBall")) {
        velo_bench <- if (pitcher_hand == "Left") sec_averages$overall$fb_velo_l else sec_averages$overall$fb_velo_r
      } else {
        vb_l <- sec_ref$velo_l
        vb_r <- sec_ref$velo_r
        if (!is.null(vb_l) && !is.null(vb_r)) {
          velo_bench <- if (pitcher_hand == "Left") vb_l else vb_r
        }
      }
      
      # Apply colors
      if (!is.na(velo_bench)) {
        avg_velo_color <- get_gradient_color(pitch_stats$`Avg Velo`[i], velo_bench, "higher_better", 0.05)
        max_velo_color <- get_gradient_color(pitch_stats$`Max Velo`[i], velo_bench, "higher_better", 0.05)
        
        gt_tbl <- gt_tbl %>%
          gt::tab_style(style = list(gt::cell_fill(color = avg_velo_color)),
                        locations = gt::cells_body(columns = "Avg Velo", rows = i)) %>%
          gt::tab_style(style = list(gt::cell_fill(color = max_velo_color)),
                        locations = gt::cells_body(columns = "Max Velo", rows = i))
      }
      
      # Spin
      if (!is.null(sec_ref$spin)) {
        spin_color <- get_gradient_color(pitch_stats$`Avg Spin`[i], sec_ref$spin, "higher_better", 0.20)
        gt_tbl <- gt_tbl %>%
          gt::tab_style(style = list(gt::cell_fill(color = spin_color)),
                        locations = gt::cells_body(columns = "Avg Spin", rows = i))
      }
      
      # Strike%
      if (!is.null(sec_ref$strike)) {
        strike_color <- get_gradient_color(pitch_stats$`Strike%`[i], sec_ref$strike, "higher_better", 0.15)
        gt_tbl <- gt_tbl %>%
          gt::tab_style(style = list(gt::cell_fill(color = strike_color)),
                        locations = gt::cells_body(columns = "Strike%", rows = i))
      }
      
      # Whiff%
      if (!is.null(sec_ref$whiff)) {
        whiff_color <- get_gradient_color(pitch_stats$`Whiff%`[i], sec_ref$whiff, "higher_better", 0.30)
        gt_tbl <- gt_tbl %>%
          gt::tab_style(style = list(gt::cell_fill(color = whiff_color)),
                        locations = gt::cells_body(columns = "Whiff%", rows = i))
      }
      
      # Zone%
      if (!is.null(sec_ref$zone)) {
        zone_color <- get_gradient_color(pitch_stats$`Zone%`[i], sec_ref$zone, "higher_better", 0.20)
        gt_tbl <- gt_tbl %>%
          gt::tab_style(style = list(gt::cell_fill(color = zone_color)),
                        locations = gt::cells_body(columns = "Zone%", rows = i))
      }
    }
    
    # Extension benchmark
    ext_bench <- sec_extension_benchmark(pt)
    if (!is.na(ext_bench)) {
      ext_color <- get_gradient_color(pitch_stats$Ext[i], ext_bench, "higher_better", 0.08)
      gt_tbl <- gt_tbl %>%
        gt::tab_style(style = list(gt::cell_fill(color = ext_color)),
                      locations = gt::cells_body(columns = "Ext", rows = i))
    }
    
    # Stuff+ (benchmark = 100)
    if ("Stuff+" %in% names(pitch_stats)) {
      stuff_val <- pitch_stats$`Stuff+`[i]
      if (!is.na(stuff_val) && is.finite(stuff_val)) {
        stuff_color <- get_gradient_color(stuff_val, 100, "higher_better", 0.20)
        gt_tbl <- gt_tbl %>%
          gt::tab_style(style = list(gt::cell_fill(color = stuff_color)),
                        locations = gt::cells_body(columns = "Stuff+", rows = i))
      }
    }
    
    # Color pitch name column
    pitch_col <- if (pt %in% names(pitch_colors)) pitch_colors[[pt]] else "#A9A9A9"
    gt_tbl <- gt_tbl %>%
      gt::tab_style(
        style = list(gt::cell_fill(color = pitch_col), gt::cell_text(weight = "bold")),
        locations = gt::cells_body(columns = "Pitch", rows = i)
      )
  }
  
  return(gt_tbl)
}

# ---- RV/100 Calculation ----
weights_vec <- c(
  "Ball" = -0.0892681735045099,
  "Called Strike" = 0.121194020810818,
  "Double" = -0.859369443968486,
  "Field Out" = 0.327827741132251,
  "Foul Ball" = 0.0709399019613328,
  "HBP" = -0.423817625210998,
  "Home Run" = -1.42174059796598,
  "Single" = -0.556264454815573,
  "Triple" = -1.09689513374671,
  "Whiff" = 0.174095217814355,
  "NA" = 0.0110712767697598
)

map_dre_event <- function(PitchCall, PlayResult) {
  dplyr::case_when(
    PitchCall %in% c("BallCalled", "BallinDirt") ~ "Ball",
    PitchCall == "StrikeCalled" ~ "Called Strike",
    PitchCall == "StrikeSwinging" ~ "Whiff",
    PitchCall %in% c("FoulBall", "FoulBallNotFieldable", "FoulBallFieldable") ~ "Foul Ball",
    PitchCall == "HitByPitch" ~ "HBP",
    PitchCall == "InPlay" & PlayResult == "Single" ~ "Single",
    PitchCall == "InPlay" & PlayResult == "Double" ~ "Double",
    PitchCall == "InPlay" & PlayResult == "Triple" ~ "Triple",
    PitchCall == "InPlay" & PlayResult == "HomeRun" ~ "Home Run",
    PitchCall == "InPlay" & PlayResult %in% c("Out", "FieldersChoice", "Error") ~ "Field Out",
    TRUE ~ "NA"
  )
}

calculate_rv100 <- function(df) {
  df %>%
    mutate(
      dre_event = map_dre_event(PitchCall, PlayResult),
      rv_pitcher = as.numeric(weights_vec[dre_event]),
      rv_pitcher = ifelse(is.na(rv_pitcher), weights_vec["NA"], rv_pitcher),
      hitter_rv = -rv_pitcher
    )
}


# 6. LOCATION HEATMAPS BY RESULT
create_location_by_result_faceted <- function(data, pitcher_name, pitch_group, batter_side) {
  if (is.null(data)) {
    return(ggplot() + theme_void())
  }
  
  # Fastballs: 4-seam, 2-seam, sinker
  fb_pitches <- c("Fastball", "Sinker", "FourSeamFastBall", "TwoSeamFastBall", 
                  "Four-Seam", "Two-Seam")
  
  # Offspeed/Breaking: slider, cutter, curveball, sweeper, changeup, splitter
  os_pitches <- c("Slider", "Cutter", "Curveball", "Sweeper", "Slurve", 
                  "ChangeUp", "Changeup", "Splitter", "Knuckle Curve")
  
  selected_pitches <- switch(pitch_group,
                             "Fastballs" = fb_pitches,
                             "FB" = fb_pitches,
                             "Offspeed" = os_pitches,
                             "OS" = os_pitches,
                             "Breaking" = os_pitches,
                             fb_pitches)
  
  df <- data %>%
    filter(Pitcher == pitcher_name,
           TaggedPitchType %in% selected_pitches,
           BatterSide == batter_side,
           !is.na(PlateLocSide), !is.na(PlateLocHeight))
  
  if (nrow(df) < 10) {
    return(ggplot() + theme_void() + 
             annotate("text", x = 0, y = 2.5, label = "Low n", size = 3))
  }
  
  df <- df %>%
    mutate(
      is_whiff = PitchCall == "StrikeSwinging",
      is_ball = PitchCall %in% c("BallCalled", "BallinDirt"),
      is_strike = PitchCall == "StrikeCalled",
      is_hard_hit = !is.na(ExitSpeed) & ExitSpeed >= 95,
      is_2strike = Strikes == 2
    )
  
  result_types <- c("Whiffs", "Balls Called", "Strikes Called", "Hard Hits (95+)", "2 Strikes")
  
  plot_data <- bind_rows(
    df %>% filter(is_whiff) %>% mutate(result_type = "Whiffs"),
    df %>% filter(is_ball) %>% mutate(result_type = "Balls Called"),
    df %>% filter(is_strike) %>% mutate(result_type = "Strikes Called"),
    df %>% filter(is_hard_hit) %>% mutate(result_type = "Hard Hits (95+)"),
    df %>% filter(is_2strike) %>% mutate(result_type = "2 Strikes")
  ) %>%
    mutate(result_type = factor(result_type, levels = result_types))
  
  if (nrow(plot_data) < 5) {
    return(ggplot() + theme_void() + 
             annotate("text", x = 0, y = 2.5, label = "Low n", size = 3))
  }
  
  sz_data <- data.frame(
    xmin = -0.83, xmax = 0.83,
    ymin = 1.5, ymax = 3.5
  )
  
  p <- ggplot(plot_data, aes(x = PlateLocSide, y = PlateLocHeight)) +
    stat_density_2d(aes(fill = after_stat(density)), 
                    geom = "raster", contour = FALSE, 
                    h = c(0.4, 0.4), n = 50) +
    scale_fill_gradient(low = "white", high = "#D73027", na.value = "white") +
    geom_rect(data = sz_data, aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax),
              inherit.aes = FALSE, fill = NA, color = "black", linewidth = 0.8) +
    facet_wrap(~result_type, nrow = 1) +
    coord_fixed(xlim = c(-1.5, 1.5), ylim = c(0.5, 4.5)) +
    theme_minimal() +
    theme(
      legend.position = "none",
      strip.text = element_text(size = 8, face = "bold"),
      axis.text = element_blank(),
      axis.title = element_blank(),
      panel.grid = element_blank(),
      plot.background = element_rect(fill = "white", color = NA)
    )
  
  return(p)
}

# ============================================================================
# COMPREHENSIVE PITCHER PDF REPORT FUNCTIONS
# ============================================================================

# SEC Benchmarks for coloring
sec_benchmarks <- list(
  era = 4.75,
  fip = 4.22,
  whip = 1.37,
  k_pct = 26,
  bb_pct = 10,
  ba_against = 0.244,
  slg_against = 0.396,
  fb_strike = 64,
  bb_strike = 60,
  os_strike = 59,
  zone_pct = 45.9,
  whiff_pct = 28.9,
  strike_pct = 62.6
)

# Color function for stats (green = good, red = bad)
get_stat_color <- function(value, benchmark, higher_is_better = TRUE, range_pct = 0.25) {
  if (is.na(value) || is.na(benchmark)) return("#FFFFFF")
  if (is.nan(value) || is.infinite(value)) return("#FFFFFF")
  
  pal <- scales::gradient_n_pal(c("#E1463E", "white", "#00840D"))
  range_val <- benchmark * range_pct
  min_val <- benchmark - range_val
  max_val <- benchmark + range_val
  
  if (higher_is_better) {
    normalized <- (value - min_val) / (max_val - min_val)
  } else {
    normalized <- (max_val - value) / (max_val - min_val)
  }
  normalized <- pmax(0, pmin(1, normalized))
  pal(normalized)
}

# Process pitcher indicators for advanced stats
process_pitcher_indicators <- function(df) {
  df %>%
    mutate(
      OutsOnPlay = case_when(
        PlayResult == "Out" ~ 1,
        PlayResult == "FieldersChoice" ~ 1,
        PlayResult == "Sacrifice" ~ 1,
        PlayResult == "SacrificeFly" ~ 1,
        KorBB == "Strikeout" ~ 1,
        grepl("DoublePlay", PlayResult, ignore.case = TRUE) ~ 2,
        TRUE ~ 0
      ),
      # Note: is_hit and is_ab already exist in the dataset
      total_bases = case_when(
        PlayResult == "Single" ~ 1,
        PlayResult == "Double" ~ 2,
        PlayResult == "Triple" ~ 3,
        PlayResult == "HomeRun" ~ 4,
        TRUE ~ 0
      ),
      is_k = as.integer(KorBB == "Strikeout"),
      is_walk = as.integer(KorBB == "Walk"),
      is_hbp = as.integer(PitchCall == "HitByPitch"),
      is_put_away = as.integer(KorBB == "Strikeout" & Strikes == 2),
      in_zone = as.integer(PlateLocSide >= -0.83 & PlateLocSide <= 0.83 &
                             PlateLocHeight >= 1.5 & PlateLocHeight <= 3.5),
      is_swing = as.integer(PitchCall %in% c("StrikeSwinging", "FoulBall", 
                                             "FoulBallNotFieldable", "FoulBallFieldable", "InPlay")),
      is_whiff = as.integer(PitchCall == "StrikeSwinging"),
      is_strike = as.integer(!PitchCall %in% c("BallCalled", "BallinDirt", "BallIntentional")),
      pitch_family = case_when(
        TaggedPitchType %in% c("Fastball", "Four-Seam", "FourSeamFastBall", "Sinker", "TwoSeamFastBall", "Two-Seam") ~ "FB",
        TaggedPitchType %in% c("Slider", "Curveball", "Cutter", "Sweeper", "Slurve", "Knuckle Curve") ~ "BB",
        TaggedPitchType %in% c("ChangeUp", "Changeup", "Splitter") ~ "OS",
        TRUE ~ "Other"
      )
    )
}

# Calculate comprehensive pitcher stats
calculate_advanced_pitcher_stats <- function(data, pitcher_name) {
  df <- data %>% 
    filter(Pitcher == pitcher_name) %>%
    process_pitcher_indicators()
  
  if (nrow(df) < 20) return(NULL)
  
  # Get PA-level data
  pa_data <- df %>%
    filter(!is.na(KorBB) | PlayResult %in% c("Single", "Double", "Triple", "HomeRun", "Out", 
                                             "FieldersChoice", "Error") | PitchCall == "HitByPitch") %>%
    group_by(GameID, Inning, PAofInning) %>%
    slice_tail(n = 1) %>%
    ungroup()
  
  # Basic counting stats - FIXED IP calculation
  total_outs <- sum(df$OutsOnPlay, na.rm = TRUE)
  full_innings <- floor(total_outs / 3)
  partial_outs <- total_outs %% 3
  # IP format: X.0, X.1, or X.2 only (not X.3+)
  ip_display <- full_innings + partial_outs / 10
  # Actual innings for rate calculations
  ip_actual <- total_outs / 3
  
  n_games <- n_distinct(df$GameID)
  n_pitches <- nrow(df)
  
  # Most recent outing
  recent_game <- df %>% 
    filter(GameID == max(GameID, na.rm = TRUE))
  recent_pitches <- nrow(recent_game)
  
  # Get last 3 outings with dates and pitch counts
  game_summary <- df %>%
    group_by(GameID, Date) %>%
    summarise(pitches = n(), .groups = "drop") %>%
    arrange(desc(Date)) %>%
    head(3)
  
  last_3_outings <- if (nrow(game_summary) > 0) {
    paste(sapply(1:nrow(game_summary), function(i) {
      date_val <- game_summary$Date[i]
      date_str <- tryCatch({
        if (inherits(date_val, "Date") || inherits(date_val, "POSIXt")) {
          format(date_val, "%m/%d")
        } else if (is.character(date_val) || is.numeric(date_val)) {
          format(as.Date(date_val), "%m/%d")
        } else {
          "?"
        }
      }, error = function(e) "?")
      paste0(game_summary$pitches[i], " (", date_str, ")")
    }), collapse = ", ")
  } else {
    "-"
  }
  
  # PA-based stats
  n_pa <- nrow(pa_data)
  n_k <- sum(pa_data$is_k, na.rm = TRUE)
  n_bb <- sum(pa_data$is_walk, na.rm = TRUE)
  n_hbp <- sum(pa_data$is_hbp, na.rm = TRUE)
  n_hr <- sum(pa_data$PlayResult == "HomeRun", na.rm = TRUE)
  
  # Runs (from RunsScored column if available)
  n_runs <- if ("RunsScored" %in% names(df)) sum(df$RunsScored, na.rm = TRUE) else n_hr
  
  # Split stats - calculate BA and SLG from PlayResult
  vs_lhh <- pa_data %>% filter(BatterSide == "Left")
  vs_rhh <- pa_data %>% filter(BatterSide == "Right")
  
  # Calculate hits and ABs from PlayResult (don't rely on pre-existing columns)
  calculate_ba_slg <- function(pa_df) {
    if (nrow(pa_df) == 0) return(list(ba = NA, slg = NA))
    
    # Hits: Single, Double, Triple, HomeRun
    hits <- sum(pa_df$PlayResult %in% c("Single", "Double", "Triple", "HomeRun"), na.rm = TRUE)
    
    # At-bats: exclude walks and HBP
    ab <- sum(pa_df$PlayResult %in% c("Single", "Double", "Triple", "HomeRun", "Out", "FieldersChoice", "Error") |
                pa_df$KorBB == "Strikeout", na.rm = TRUE)
    
    # Total bases
    tb <- sum(pa_df$PlayResult == "Single", na.rm = TRUE) +
      2 * sum(pa_df$PlayResult == "Double", na.rm = TRUE) +
      3 * sum(pa_df$PlayResult == "Triple", na.rm = TRUE) +
      4 * sum(pa_df$PlayResult == "HomeRun", na.rm = TRUE)
    
    ba <- if (ab > 0) hits / ab else NA
    slg <- if (ab > 0) tb / ab else NA
    
    list(ba = ba, slg = slg, hits = hits, ab = ab, tb = tb)
  }
  
  lhh_stats <- calculate_ba_slg(vs_lhh)
  rhh_stats <- calculate_ba_slg(vs_rhh)
  
  ba_vs_l <- lhh_stats$ba
  ba_vs_r <- rhh_stats$ba
  slg_vs_l <- lhh_stats$slg
  slg_vs_r <- rhh_stats$slg
  
  # Total hits for WHIP
  all_stats <- calculate_ba_slg(pa_data)
  n_hits <- all_stats$hits
  
  # Pitch-level stats
  n_swings <- sum(df$is_swing, na.rm = TRUE)
  n_whiffs <- sum(df$is_whiff, na.rm = TRUE)
  n_strikes <- sum(df$is_strike, na.rm = TRUE)
  n_in_zone <- sum(df$in_zone, na.rm = TRUE)
  
  # By pitch family
  fb_data <- df %>% filter(pitch_family == "FB")
  bb_data <- df %>% filter(pitch_family == "BB")
  os_data <- df %>% filter(pitch_family == "OS")
  
  fb_strike_pct <- if (nrow(fb_data) > 0) 100 * sum(fb_data$is_strike, na.rm = TRUE) / nrow(fb_data) else NA
  bb_strike_pct <- if (nrow(bb_data) > 0) 100 * sum(bb_data$is_strike, na.rm = TRUE) / nrow(bb_data) else NA
  os_strike_pct <- if (nrow(os_data) > 0) 100 * sum(os_data$is_strike, na.rm = TRUE) / nrow(os_data) else NA
  
  # Calculate rates
  k_pct <- if (n_pa > 0) 100 * n_k / n_pa else 0
  bb_pct <- if (n_pa > 0) 100 * n_bb / n_pa else 0
  whiff_pct <- if (n_swings > 0) 100 * n_whiffs / n_swings else 0
  zone_pct <- if (n_pitches > 0) 100 * n_in_zone / n_pitches else 0
  strike_pct <- if (n_pitches > 0) 100 * n_strikes / n_pitches else 0
  
  # RA9 (not ERA - can't determine earned runs from TrackMan), WHIP, FIP
  ra9 <- if (ip_actual > 0) 9 * n_runs / ip_actual else NA
  whip <- if (ip_actual > 0) (n_bb + n_hits) / ip_actual else NA
  
  # FIP with correct constant (4.08) and formula
  fip_constant <- 4.08
  fip <- if (ip_actual > 0) ((13 * n_hr + 3 * (n_bb + n_hbp) - 2 * n_k) / ip_actual) + fip_constant else NA
  
  # Avg IP per outing (using display format)
  avg_outs_per_game <- if (n_games > 0) total_outs / n_games else 0
  avg_ip_full <- floor(avg_outs_per_game / 3)
  avg_ip_partial <- round(avg_outs_per_game %% 3) / 10
  avg_ip_display <- avg_ip_full + avg_ip_partial
  
  avg_pitches <- if (n_games > 0) n_pitches / n_games else 0
  
  list(
    ip = ip_display,
    n_games = n_games,
    avg_ip = avg_ip_display,
    avg_pitches = round(avg_pitches, 0),
    recent_pitches = recent_pitches,
    last_3_outings = last_3_outings,
    ra9 = round(ra9, 2),
    whip = round(whip, 2),
    fip = round(fip, 2),
    k_pct = round(k_pct, 1),
    bb_pct = round(bb_pct, 1),
    ba_vs_l = round(ba_vs_l, 3),
    ba_vs_r = round(ba_vs_r, 3),
    slg_vs_l = round(slg_vs_l, 3),
    slg_vs_r = round(slg_vs_r, 3),
    whiff_pct = round(whiff_pct, 1),
    zone_pct = round(zone_pct, 1),
    strike_pct = round(strike_pct, 1),
    fb_strike_pct = round(fb_strike_pct, 1),
    bb_strike_pct = round(bb_strike_pct, 1),
    os_strike_pct = round(os_strike_pct, 1),
    pitcher_hand = df$PitcherThrows[1]
  )
}

# Create sequencing matrix
create_sequencing_matrix <- function(data, pitcher_name, batter_side = NULL) {
  df <- data %>%
    filter(Pitcher == pitcher_name, !is.na(TaggedPitchType), TaggedPitchType != "Other")
  
  if (!is.null(batter_side)) {
    df <- df %>% filter(BatterSide == batter_side)
  }
  
  if (nrow(df) < 50) {
    return(ggplot() + theme_void() + annotate("text", x = 0.5, y = 0.5, label = "Low n"))
  }
  
  # Create previous pitch column
  df <- df %>%
    arrange(GameID, Inning, PAofInning, PitchofPA) %>%
    group_by(GameID, Inning, PAofInning) %>%
    mutate(prev_pitch = lag(TaggedPitchType)) %>%
    ungroup() %>%
    filter(!is.na(prev_pitch))
  
  # Calculate transition matrix
  trans_matrix <- df %>%
    count(prev_pitch, TaggedPitchType) %>%
    group_by(prev_pitch) %>%
    mutate(pct = round(100 * n / sum(n), 0)) %>%
    ungroup()
  
  title_suffix <- if (!is.null(batter_side)) paste0(" vs ", batter_side, "HH") else ""
  
  ggplot(trans_matrix, aes(x = TaggedPitchType, y = prev_pitch, fill = pct)) +
    geom_tile(color = "white") +
    geom_text(aes(label = paste0(pct, "%")), size = 2.5) +
    scale_fill_gradient(low = "white", high = "#2c7bb6", name = "%") +
    labs(title = paste0("Pitch Sequencing", title_suffix),
         x = "Current Pitch", y = "Previous Pitch") +
    theme_minimal() +
    theme(
      plot.title = element_text(size = 10, face = "bold", hjust = 0.5),
      axis.text.x = element_text(angle = 45, hjust = 1, size = 7),
      axis.text.y = element_text(size = 7),
      legend.position = "none"
    )
}

# Create spray chart for hits against - SECTOR VERSION
create_hits_spray_chart <- function(data, pitcher_name, batter_side) {
  df <- data %>%
    filter(Pitcher == pitcher_name,
           BatterSide == batter_side,
           PitchCall == "InPlay",
           !is.na(Bearing), !is.na(Distance)) %>%
    mutate(
      Bearing2 = Bearing * pi / 180,
      x = Distance * sin(Bearing2),
      y = Distance * cos(Bearing2)
    )
  
  if (nrow(df) < 5) {
    return(ggplot() + theme_void() + 
             annotate("text", x = 0, y = 200, label = paste0("Low n vs ", batter_side, "HH"), size = 3))
  }
  
  # 5 angle sectors from -45 to +45
  angle_breaks_deg <- seq(-45, 45, length.out = 6)
  angle_breaks_rad <- angle_breaks_deg * pi / 180
  
  df <- df %>%
    mutate(
      angle_sector = case_when(
        Bearing >= angle_breaks_deg[1] & Bearing < angle_breaks_deg[2] ~ 1L,
        Bearing >= angle_breaks_deg[2] & Bearing < angle_breaks_deg[3] ~ 2L,
        Bearing >= angle_breaks_deg[3] & Bearing < angle_breaks_deg[4] ~ 3L,
        Bearing >= angle_breaks_deg[4] & Bearing < angle_breaks_deg[5] ~ 4L,
        Bearing >= angle_breaks_deg[5] & Bearing <= angle_breaks_deg[6] ~ 5L,
        TRUE ~ NA_integer_
      ),
      dist_sector = case_when(
        Distance < 150 ~ 1L,
        Distance >= 150 ~ 2L,
        TRUE ~ NA_integer_
      )
    ) %>%
    filter(!is.na(angle_sector), !is.na(dist_sector))
  
  if (nrow(df) == 0) {
    return(ggplot() + theme_void() + 
             annotate("text", x = 0, y = 200, label = paste0("No BIP vs ", batter_side, "HH"), size = 3))
  }
  
  total_bip <- nrow(df)
  
  # Sector stats
  sector_stats <- df %>%
    group_by(angle_sector, dist_sector) %>%
    summarise(count = n(), .groups = "drop") %>%
    mutate(pct = round(100 * count / total_bip))
  
  # Create sector polygons
  create_sector <- function(r_inner, r_outer, theta_start, theta_end, n = 40) {
    theta_seq <- seq(theta_start, theta_end, length.out = n)
    inner_x <- r_inner * sin(theta_seq)
    inner_y <- r_inner * cos(theta_seq)
    outer_x <- r_outer * sin(rev(theta_seq))
    outer_y <- r_outer * cos(rev(theta_seq))
    data.frame(x = c(inner_x, outer_x), y = c(inner_y, outer_y))
  }
  
  dist_breaks <- c(0, 150, 400)
  
  sectors <- list()
  sector_id <- 1
  for (i in 1:5) {
    for (j in 1:2) {
      poly <- create_sector(
        dist_breaks[j], dist_breaks[j + 1],
        angle_breaks_rad[i], angle_breaks_rad[i + 1]
      )
      poly$sector_id <- sector_id
      poly$angle_idx <- i
      poly$dist_idx <- j
      sectors[[sector_id]] <- poly
      sector_id <- sector_id + 1
    }
  }
  
  sector_df <- bind_rows(sectors)
  
  # Sector centers & merge stats
  sector_centers <- sector_df %>%
    group_by(sector_id, angle_idx, dist_idx) %>%
    summarise(cx = mean(x), cy = mean(y), .groups = "drop") %>%
    left_join(
      sector_stats %>% rename(angle_idx = angle_sector, dist_idx = dist_sector),
      by = c("angle_idx", "dist_idx")
    )
  
  sector_df <- sector_df %>%
    left_join(sector_centers %>% select(sector_id, pct, count), by = "sector_id")
  
  # Plot
  ggplot() +
    geom_polygon(
      data = sector_df,
      aes(x = x, y = y, group = sector_id, fill = pct),
      color = "black", linewidth = 0.3
    ) +
    geom_text(
      data = sector_centers %>% filter(!is.na(pct) & pct > 0),
      aes(x = cx, y = cy, label = paste0(pct, "%")),
      size = 2.5, fontface = "bold"
    ) +
    # Foul lines
    annotate("segment", x = 0, y = 0, xend = 247.487, yend = 247.487, color = "black", linewidth = 0.5) +
    annotate("segment", x = 0, y = 0, xend = -247.487, yend = 247.487, color = "black", linewidth = 0.5) +
    annotate("text", x = 200, y = 350, label = paste("BIP:", total_bip), size = 2.5, hjust = 0, fontface = "bold") +
    scale_fill_gradientn(
      colors = c("white", "#e5fbe5", "#90EE90", "#66c266", "#228B22", "#145a14", "#006400"),
      values = scales::rescale(c(0, 3, 5, 10, 15, 20, 25)),
      limits = c(0, NA),
      na.value = "white",
      name = "% BIP"
    ) +
    coord_fixed(xlim = c(-280, 280), ylim = c(-20, 380)) +
    labs(title = paste0("vs ", batter_side, "HH")) +
    theme_void() +
    theme(
      legend.position = "none",
      plot.title = element_text(hjust = 0.5, size = 8, face = "bold")
    )
}


create_pitch_group_heatmap <- function(data, pitcher_name, pitch_group, metric_type, batter_side = NULL) {
  
  # ---- pitch groups ----
  fb_pitches <- c("Fastball", "Sinker", "FourSeamFastBall", "TwoSeamFastBall", "Four-Seam", "Two-Seam")
  bb_pitches <- c("Slider", "Curveball", "Cutter", "Sweeper", "Slurve", "Knuckle Curve")
  os_pitches <- c("ChangeUp", "Changeup", "Splitter")
  all_pitches <- c(fb_pitches, bb_pitches, os_pitches)
  
  selected_pitches <- switch(
    pitch_group,
    "FB"  = fb_pitches,
    "BB"  = bb_pitches,
    "OS"  = os_pitches,
    "All" = all_pitches,
    fb_pitches
  )
  
  df <- data %>%
    dplyr::filter(
      Pitcher == pitcher_name,
      TaggedPitchType %in% selected_pitches,
      !is.na(PlateLocSide), !is.na(PlateLocHeight)
    )
  
  if (!is.null(batter_side) && batter_side != "All") {
    df <- df %>% dplyr::filter(BatterSide == batter_side)
  }
  
  # ---- filter by metric ----
  if (metric_type %in% c("Whiff", "Whf")) {
    df <- df %>% dplyr::filter(PitchCall == "StrikeSwinging")
  } else if (metric_type %in% c("Damage", "Dmg")) {
    df <- df %>% dplyr::filter(!is.na(ExitSpeed), ExitSpeed >= 95)
  }
  
  # ---- base strike zone (ALWAYS drawn) ----
  base_zone <- ggplot() +
    annotate("rect", xmin = -0.83, xmax = 0.83, ymin = 1.5, ymax = 3.5,
             fill = NA, color = "black", linewidth = 0.8) +
    annotate("path",
             x = c(-0.708, 0.708, 0.708, 0, -0.708, -0.708),
             y = c(0.15, 0.15, 0.3, 0.5, 0.3, 0.15),
             color = "black", linewidth = 0.6) +
    coord_fixed(xlim = c(-2, 2), ylim = c(0, 4.5)) +
    theme_void() +
    theme(
      legend.position = "none",
      plot.title = element_blank(),
      plot.margin = margin(2, 2, 2, 2)
    )
  
  # ---- if NO pitches: blank zone only ----
  if (nrow(df) == 0) return(base_zone)
  
  # ---- small N: show pitch locations (no density) ----
  if (nrow(df) < 5) {
    return(
      base_zone +
        geom_point(data = df, aes(x = PlateLocSide, y = PlateLocHeight), alpha = 0.85, size = 0.9)
    )
  }
  
  # ---- enough N: density + (optional) points ----
  base_zone +
    stat_density_2d(
      data = df,
      aes(x = PlateLocSide, y = PlateLocHeight, fill = after_stat(density)),
      geom = "raster", contour = FALSE
    ) +
    scale_fill_gradientn(colours = c("white", "blue", "#FF9999", "red", "darkred"), guide = "none") +
    geom_point(data = df, aes(x = PlateLocSide, y = PlateLocHeight), alpha = 0.25, size = 0.6)
}


# Enhanced pitch characteristics with velocity range, putaway%, release point
create_enhanced_pitch_characteristics <- function(data, pitcher_name) {
  df <- data %>%
    dplyr::filter(Pitcher == pitcher_name, !is.na(TaggedPitchType), TaggedPitchType != "Other") %>%
    process_pitcher_indicators()
  
  if (nrow(df) < 10) return(NULL)
  
  total_pitches <- nrow(df)
  pitcher_hand  <- df$PitcherThrows[1]
  
  has_stuff_plus <- "stuff_plus" %in% names(df)
  has_vaa        <- "VertApprAngle" %in% names(df)
  
  # wobacon with any case
  wobacon_col <- names(df)[tolower(names(df)) == "wobacon"]
  has_wobacon <- length(wobacon_col) > 0
  if (has_wobacon) wobacon_col <- wobacon_col[1]
  
  # woba column (overall wOBA, not just on contact)
  woba_col <- names(df)[tolower(names(df)) == "woba"]
  has_woba <- length(woba_col) > 0
  if (has_woba) woba_col <- woba_col[1]
  
  # safe helper for whiff% with denominator
  whiff_pct_safe <- function(swing, whiff) {
    ifelse(swing > 0, round(100 * whiff / swing, 1), 0)
  }
  
  pitch_stats <- df %>%
    dplyr::group_by(Pitch = TaggedPitchType) %>%
    dplyr::summarise(
      Count = dplyr::n(),
      `Usage%` = round(100 * dplyr::n() / total_pitches, 1),
      
      AvgVelo = round(mean(RelSpeed, na.rm = TRUE), 1),
      MaxVelo = round(max(RelSpeed, na.rm = TRUE), 1),
      
      # Velo range (10th-90th percentile)
      VeloRng = paste0(round(stats::quantile(RelSpeed, 0.10, na.rm = TRUE), 0), "-",
                       round(stats::quantile(RelSpeed, 0.90, na.rm = TRUE), 0)),
      
      Spin = round(mean(SpinRate, na.rm = TRUE), 0),
      IVB  = round(mean(InducedVertBreak, na.rm = TRUE), 1),
      HB   = round(mean(HorzBreak, na.rm = TRUE), 1),
      VAA  = if (has_vaa) round(mean(VertApprAngle, na.rm = TRUE), 2) else NA_real_,
      Ext  = round(mean(Extension, na.rm = TRUE), 2),
      
      hRel = round(mean(RelSide, na.rm = TRUE), 2),
      vRel = round(mean(RelHeight, na.rm = TRUE), 2),
      
      `Strike%`  = round(100 * sum(is_strike, na.rm = TRUE) / dplyr::n(), 1),
      `Whiff%`   = whiff_pct_safe(sum(is_swing, na.rm = TRUE), sum(is_whiff, na.rm = TRUE)),
      `Zone%`    = round(100 * sum(in_zone, na.rm = TRUE) / dplyr::n(), 1),
      `Putaway%` = ifelse(sum(Strikes == 2, na.rm = TRUE) > 0,
                          round(100 * sum(is_put_away, na.rm = TRUE) / sum(Strikes == 2, na.rm = TRUE), 1), 0),
      
      # Whiff% split by batter side (uses swings as denominator within side)
      `Whiff% vL` = whiff_pct_safe(
        sum(is_swing[BatterSide == "Left"],  na.rm = TRUE),
        sum(is_whiff[BatterSide == "Left"],  na.rm = TRUE)
      ),
      `Whiff% vR` = whiff_pct_safe(
        sum(is_swing[BatterSide == "Right"], na.rm = TRUE),
        sum(is_whiff[BatterSide == "Right"], na.rm = TRUE)
      ),
      
      AvgEV = round(mean(ExitSpeed[PitchCall == "InPlay"], na.rm = TRUE), 1),
      
      # overall wOBAcon (in-play only)
      wOBAcon_val = if (has_wobacon) {
        round(mean(.data[[wobacon_col]][PitchCall == "InPlay"], na.rm = TRUE), 3)
      } else NA_real_,
      
      # wOBA overall and splits (all pitches, not just in-play)
      wOBA_val = if("woba" %in% names(.data)) round(mean(woba, na.rm = TRUE), 3) else NA_real_,
      wOBA_vL_val = if (has_woba) {
        round(mean(.data[[woba_col]][BatterSide == "Left"], na.rm = TRUE), 3)
      } else NA_real_,
      wOBA_vR_val = if (has_woba) {
        round(mean(.data[[woba_col]][BatterSide == "Right"], na.rm = TRUE), 3)
      } else NA_real_,
      
      `Stuff+` = if (has_stuff_plus) round(mean(stuff_plus, na.rm = TRUE), 0) else NA_real_,
      
      Notes = "",
      .groups = "drop"
    ) %>%
    dplyr::rename(
      wOBAcon     = wOBAcon_val,
      wOBA        = wOBA_val,
      `wOBA vL`   = wOBA_vL_val,
      `wOBA vR`   = wOBA_vR_val
    ) %>%
    dplyr::filter(Count >= 5) %>%
    dplyr::arrange(dplyr::desc(`Usage%`))
  
  # Totals row
  totals <- df %>%
    dplyr::summarise(
      Pitch = "TOTAL",
      Count = dplyr::n(),
      `Usage%` = 100,
      
      AvgVelo = round(mean(RelSpeed, na.rm = TRUE), 1),
      MaxVelo = round(max(RelSpeed, na.rm = TRUE), 1),
      VeloRng = "-",
      
      Spin = round(mean(SpinRate, na.rm = TRUE), 0),
      IVB  = round(mean(InducedVertBreak, na.rm = TRUE), 1),
      HB   = round(mean(HorzBreak, na.rm = TRUE), 1),
      VAA  = if (has_vaa) round(mean(VertApprAngle, na.rm = TRUE), 2) else NA_real_,
      Ext  = round(mean(Extension, na.rm = TRUE), 2),
      
      hRel = round(mean(RelSide, na.rm = TRUE), 2),
      vRel = round(mean(RelHeight, na.rm = TRUE), 2),
      
      `Strike%`  = round(100 * sum(is_strike, na.rm = TRUE) / dplyr::n(), 1),
      `Whiff%`   = whiff_pct_safe(sum(is_swing, na.rm = TRUE), sum(is_whiff, na.rm = TRUE)),
      `Zone%`    = round(100 * sum(in_zone, na.rm = TRUE) / dplyr::n(), 1),
      `Putaway%` = ifelse(sum(Strikes == 2, na.rm = TRUE) > 0,
                          round(100 * sum(is_put_away, na.rm = TRUE) / sum(Strikes == 2, na.rm = TRUE), 1), 0),
      
      # totals splits
      `Whiff% vL` = whiff_pct_safe(
        sum(is_swing[BatterSide == "Left"], na.rm = TRUE),
        sum(is_whiff[BatterSide == "Left"], na.rm = TRUE)
      ),
      `Whiff% vR` = whiff_pct_safe(
        sum(is_swing[BatterSide == "Right"], na.rm = TRUE),
        sum(is_whiff[BatterSide == "Right"], na.rm = TRUE)
      ),
      
      AvgEV = round(mean(ExitSpeed[PitchCall == "InPlay"], na.rm = TRUE), 1),
      
      wOBAcon = if (has_wobacon) round(mean(.data[[wobacon_col]][PitchCall == "InPlay"], na.rm = TRUE), 3) else NA_real_,
      
      # wOBA overall and splits for totals
      wOBA = if (has_woba) round(mean(.data[[woba_col]], na.rm = TRUE), 3) else NA_real_,
      `wOBA vL` = if (has_woba) round(mean(.data[[woba_col]][BatterSide == "Left"], na.rm = TRUE), 3) else NA_real_,
      `wOBA vR` = if (has_woba) round(mean(.data[[woba_col]][BatterSide == "Right"], na.rm = TRUE), 3) else NA_real_,
      
      `Stuff+` = if (has_stuff_plus) round(mean(stuff_plus, na.rm = TRUE), 0) else NA_real_,
      Notes = ""
    )
  
  pitch_stats <- dplyr::bind_rows(pitch_stats, totals)
  
  list(stats = pitch_stats, pitcher_hand = pitcher_hand)
}

# ============================================================================
# NEW: ROLLING DATA HELPER (for individual pitcher PDF charts)
# ============================================================================
create_rolling_data_single <- function(data, pitcher_name, stat_type) {
  fb_pitches <- c("Fastball", "Sinker", "FourSeamFastBall", "TwoSeamFastBall", "Four-Seam", "Two-Seam")
  
  rolling_data <- data %>%
    filter(Pitcher == pitcher_name) %>%
    arrange(Date, GameUID, PitchofPA) %>%
    group_by(GameUID) %>%
    mutate(pitch_in_game = row_number()) %>%
    ungroup()
  
  if (stat_type == "velo") {
    raw_data <- rolling_data %>%
      filter(TaggedPitchType %in% fb_pitches, !is.na(RelSpeed)) %>%
      select(pitch_in_game, value = RelSpeed)
  } else {
    return(data.frame(pitch_num = integer(), value = numeric()))
  }
  
  if (nrow(raw_data) == 0) return(data.frame(pitch_num = integer(), value = numeric()))
  
  # Bucket by 10s: center of bucket (5, 15, 25, etc.)
  result <- raw_data %>%
    mutate(pitch_bucket = floor((pitch_in_game - 1) / 10) * 10 + 5) %>%
    group_by(pitch_num = pitch_bucket) %>%
    summarise(value = mean(value, na.rm = TRUE), n = n(), .groups = "drop") %>%
    filter(n >= 5)
  
  result
}

# NEW: Monthly FB Velo helper
create_monthly_fb_velo <- function(data, pitcher_name) {
  fb_pitches <- c("Fastball", "Sinker", "FourSeamFastBall", "TwoSeamFastBall", "Four-Seam", "Two-Seam")
  
  monthly_data <- data %>%
    filter(Pitcher == pitcher_name, TaggedPitchType %in% fb_pitches, !is.na(RelSpeed), !is.na(Date)) %>%
    mutate(
      Date = as.Date(Date),
      month_label = format(Date, "%b %Y"),
      month_date = as.Date(paste0(format(Date, "%Y-%m"), "-01"))
    ) %>%
    group_by(month_date, month_label) %>%
    summarise(avg_velo = mean(RelSpeed, na.rm = TRUE), n = n(), .groups = "drop") %>%
    filter(n >= 5) %>%
    arrange(month_date)
  
  monthly_data
}

# NEW: Time Through Order (TTO) wOBA chart
create_tto_chart <- function(data, pitcher_name) {
  has_woba <- "woba" %in% names(data)
  
  df <- data %>%
    filter(Pitcher == pitcher_name, !is.na(Batter), !is.na(Date)) %>%
    arrange(Date, GameUID, Inning, PAofInning)
  
  if (nrow(df) < 50) {
    return(ggplot() + theme_void() + annotate("text", x = 0.5, y = 0.5, label = "Insufficient data", size = 3))
  }
  
  # For each game, track how many times each batter has been faced
  tto_data <- df %>%
    group_by(GameUID, Batter) %>%
    mutate(
      # Each unique PA for this batter in this game
      pa_num_in_game = cumsum(!duplicated(paste(Inning, PAofInning)))
    ) %>%
    ungroup() %>%
    # Keep only last pitch of each PA (the PA result)
    filter(
      KorBB %in% c("Strikeout", "Walk") |
        PitchCall == "HitByPitch" |
        PitchCall == "InPlay"
    ) %>%
    group_by(GameUID, Batter) %>%
    mutate(times_faced = row_number()) %>%
    ungroup()
  
  # Calculate wOBA or a proxy by times faced
  if (has_woba) {
    tto_summary <- tto_data %>%
      group_by(times_faced) %>%
      summarise(
        avg_woba = mean(woba, na.rm = TRUE),
        n_pa = n(),
        .groups = "drop"
      ) %>%
      filter(n_pa >= 5, times_faced <= 5)
  } else {
    # Use OBP-like proxy: hits + walks + HBP / PA
    tto_summary <- tto_data %>%
      mutate(
        reached = as.integer(
          PlayResult %in% c("Single", "Double", "Triple", "HomeRun") |
            KorBB == "Walk" | PitchCall == "HitByPitch"
        )
      ) %>%
      group_by(times_faced) %>%
      summarise(
        avg_woba = mean(reached, na.rm = TRUE),
        n_pa = n(),
        .groups = "drop"
      ) %>%
      filter(n_pa >= 5, times_faced <= 5)
  }
  
  if (nrow(tto_summary) < 2) {
    return(ggplot() + theme_void() + annotate("text", x = 0.5, y = 0.5, label = "Insufficient TTO data", size = 3))
  }
  
  y_label <- if (has_woba) "wOBA" else "OBP"
  
  ggplot(tto_summary, aes(x = factor(times_faced), y = avg_woba)) +
    geom_col(fill = "#006F71", width = 0.6, alpha = 0.85) +
    geom_text(aes(label = sprintf("%.3f", avg_woba)), vjust = -0.5, size = 2.5, fontface = "bold") +
    geom_text(aes(label = paste0("n=", n_pa), y = 0), vjust = 1.5, size = 2, color = "gray50") +
    labs(
      title = paste0(y_label, " by Times Through Order"),
      x = "Times Faced", y = y_label
    ) +
    scale_y_continuous(expand = expansion(mult = c(0.15, 0.15))) +
    theme_minimal() +
    theme(
      plot.title = element_text(hjust = 0.5, face = "bold", size = 9, color = "#006F71"),
      axis.text = element_text(size = 7),
      axis.title = element_text(size = 7),
      panel.grid.minor = element_blank(),
      panel.grid.major.x = element_blank(),
      plot.margin = margin(2, 2, 2, 2)
    )
}

# NEW: Pitch count by inning (single row heatmap for one pitcher)
create_pitcher_inning_row <- function(data, pitcher_name) {
  inning_data <- data %>%
    filter(Pitcher == pitcher_name, !is.na(Inning)) %>%
    mutate(Inning = ifelse(Inning > 9, "X", as.character(Inning))) %>%
    group_by(Inning) %>%
    summarise(n = n(), .groups = "drop")
  
  all_innings <- c("1", "2", "3", "4", "5", "6", "7", "8", "9", "X")
  inning_data <- data.frame(Inning = all_innings) %>%
    left_join(inning_data, by = "Inning") %>%
    mutate(n = ifelse(is.na(n), 0, n))
  inning_data$Inning <- factor(inning_data$Inning, levels = all_innings)
  
  ggplot(inning_data, aes(x = Inning, y = 1, fill = n)) +
    geom_tile(color = "white", linewidth = 0.5) +
    geom_text(aes(label = ifelse(n > 0, n, "")), size = 2.5, fontface = "bold") +
    scale_fill_gradient2(low = "#E1463E", mid = "#FFFFCC", high = "#00840D",
                         midpoint = max(inning_data$n[inning_data$n > 0], na.rm = TRUE) / 2,
                         guide = "none") +
    scale_x_discrete(position = "top") +
    labs(x = NULL, y = NULL, title = "Pitch Count by Inning") +
    theme_void() +
    theme(
      plot.title = element_text(hjust = 0.5, face = "bold", size = 8, color = "#006F71"),
      axis.text.x = element_text(size = 6, face = "bold"),
      plot.margin = margin(2, 2, 2, 2)
    )
}

# Main PDF creation function - WITH NOTES SUPPORT
create_comprehensive_pitcher_pdf <- function(data, pitcher_name, output_file,
                                             delivery_notes = "", count_usage_notes = "",
                                             pitch_notes = list(), overall_notes = "",
                                             vs_lhh_notes = "", vs_rhh_notes = "",
                                             series_title = "", pitcher_role = "",
                                             matchup_matrix = NULL) {
  if (length(dev.list()) > 0) try(dev.off(), silent = TRUE)
  
  # Filter pitcher data
  pitcher_df <- data %>% filter(Pitcher == pitcher_name)
  if (nrow(pitcher_df) < 20) {
    pdf(output_file, width = 22, height = 28)
    grid::grid.newpage()
    grid::grid.text(paste("Insufficient data for", pitcher_name),
                    gp = grid::gpar(fontsize = 20, fontface = "bold"))
    dev.off()
    return(output_file)
  }
  
  # Get advanced stats
  stats <- calculate_advanced_pitcher_stats(data, pitcher_name)
  if (is.null(stats)) {
    pdf(output_file, width = 22, height = 28)
    grid::grid.newpage()
    grid::grid.text(paste("Could not calculate stats for", pitcher_name),
                    gp = grid::gpar(fontsize = 20, fontface = "bold"))
    dev.off()
    return(output_file)
  }
  
  # Get pitch characteristics
  pitch_result <- create_enhanced_pitch_characteristics(data, pitcher_name)
  pitch_char <- if (!is.null(pitch_result)) pitch_result$stats else NULL
  
  # Create plots
  arm_angle_plot <- tryCatch(
    create_pitcher_arm_angle_plot(data, pitcher_name),
    error = function(e) ggplot() + theme_void() + ggtitle("Arm Angle Error")
  )
  
  movement_plot <- tryCatch(
    create_pitcher_movement_plot(data, current_pitcher_reactive(), exp_movement_grid()),
    error = function(e) ggplot() + theme_void() + ggtitle("Movement Error")
  )
  
  count_plot <- tryCatch(
    create_count_usage_pies(data, pitcher_name),
    error = function(e) ggplot() + theme_void() + ggtitle("Count Usage Error")
  )
  
  seq_lhh <- tryCatch(
    create_sequencing_matrix(data, pitcher_name, "Left"),
    error = function(e) ggplot() + theme_void() + ggtitle("Seq vs LHH Error")
  )
  
  seq_rhh <- tryCatch(
    create_sequencing_matrix(data, pitcher_name, "Right"),
    error = function(e) ggplot() + theme_void() + ggtitle("Seq vs RHH Error")
  )
  
  spray_lhh <- tryCatch(
    create_hits_spray_chart(data, pitcher_name, "Left"),
    error = function(e) ggplot() + theme_void() + ggtitle("Spray LHH Error")
  )
  
  spray_rhh <- tryCatch(
    create_hits_spray_chart(data, pitcher_name, "Right"),
    error = function(e) ggplot() + theme_void() + ggtitle("Spray RHH Error")
  )
  
  # Create heatmaps
  heatmaps <- list()
  for (pg in c("FB", "BB", "OS")) {
    for (mt in c("All", "Whf", "Dmg")) {
      for (side in c("Left", "Right")) {
        key <- paste0(pg, "_", mt, "_", side)
        heatmaps[[key]] <- tryCatch(
          create_pitch_group_heatmap(data, pitcher_name, pg, mt, side),
          error = function(e) ggplot() + theme_void()
        )
      }
    }
  }
  
  # Start PDF
  pdf(output_file, width = 22, height = 28)
  on.exit(try(dev.off(), silent = TRUE), add = TRUE)
  grid::grid.newpage()
  
  # ===== HEADER =====
  # Add series title if provided
  if (nchar(series_title) > 0) {
    grid::grid.rect(x = 0.5, y = 0.995, width = 1, height = 0.012,
                    gp = grid::gpar(fill = "#1976D2", col = NA), just = c("center", "top"))
    grid::grid.text(series_title, x = 0.5, y = 0.989,
                    gp = grid::gpar(fontsize = 14, fontface = "bold", col = "white"))
  }
  
  # Pitcher name header
  header_y <- if (nchar(series_title) > 0) 0.982 else 0.985
  grid::grid.rect(x = 0.5, y = header_y, width = 1, height = 0.025,
                  gp = grid::gpar(fill = "#006F71", col = NA), just = c("center", "top"))
  
  # Get pitcher info
  pitcher_df <- data %>% filter(Pitcher == pitcher_name)
  pitcher_throws <- if (nrow(pitcher_df) > 0 && "PitcherThrows" %in% names(pitcher_df)) {
    pitcher_df$PitcherThrows[1]
  } else {
    "Right"
  }
  is_lefty <- !is.na(pitcher_throws) && pitcher_throws == "Left"
  hand_label <- if (is_lefty) "LHP" else "RHP"
  
  # Get pitcher height
  pitcher_height_str <- get_pitcher_height_display(pitcher_name)
  height_label <- if (nchar(pitcher_height_str) > 0) paste0(" | ", pitcher_height_str) else ""
  
  # Combine pitcher name with role if provided
  display_name <- if (nchar(pitcher_role) > 0) {
    paste0(pitcher_role, " - ", pitcher_name)
  } else {
    pitcher_name
  }
  
  # Name color - red for lefties
  name_color <- if (is_lefty) "#FF4444" else "white"
  
  # Draw pitcher name
  grid::grid.text(display_name, x = 0.5, y = header_y - 0.010,
                  gp = grid::gpar(fontsize = 24, fontface = "bold", col = name_color))
  
  # Draw handedness and height on right side of header
  grid::grid.text(paste0(hand_label, height_label), x = 0.95, y = header_y - 0.012,
                  gp = grid::gpar(fontsize = 12, fontface = "bold", col = "white"), just = "right")
  
  # ===== ROW 1: Basic Stats =====
  row1_y <- 0.955
  row1_labels <- c("IP", "G", "IP/G", "P/G", "Last 3 Outings")
  row1_values <- c(sprintf("%.1f", stats$ip), stats$n_games, sprintf("%.1f", stats$avg_ip),
                   stats$avg_pitches, stats$last_3_outings)
  
  n_cols1 <- length(row1_labels)
  total_width1 <- 0.70  # Wider to fit last 3 outings
  col_widths1 <- c(0.08, 0.08, 0.08, 0.08, 0.38)  # Custom widths
  start_x1 <- 0.15
  row_h <- 0.012
  
  x_pos <- start_x1
  for (i in seq_along(row1_labels)) {
    x_center <- x_pos + col_widths1[i] / 2
    grid::grid.rect(x = x_center, y = row1_y, width = col_widths1[i], height = row_h,
                    gp = grid::gpar(fill = "#006F71", col = "black", lwd = 0.5), just = c("center", "top"))
    grid::grid.text(row1_labels[i], x = x_center, y = row1_y - row_h * 0.5,
                    gp = grid::gpar(fontsize = if(i == 5) 8 else 10, fontface = "bold", col = "white"))
    grid::grid.rect(x = x_center, y = row1_y - row_h, width = col_widths1[i], height = row_h,
                    gp = grid::gpar(fill = "white", col = "black", lwd = 0.5), just = c("center", "top"))
    grid::grid.text(as.character(row1_values[i]), x = x_center, y = row1_y - row_h * 1.5,
                    gp = grid::gpar(fontsize = if(i == 5) 8 else 10))
    x_pos <- x_pos + col_widths1[i]
  }
  
  # ===== ROW 2: Advanced Stats =====
  row2_y <- 0.925
  row2_labels <- c("RA9", "FIP", "WHIP", "K%", "BB%", "BA L", "BA R", "SLG L", "SLG R")
  row2_values <- c(stats$ra9, stats$fip, stats$whip, stats$k_pct, stats$bb_pct,
                   stats$ba_vs_l, stats$ba_vs_r, stats$slg_vs_l, stats$slg_vs_r)
  row2_benchmarks <- c(sec_benchmarks$era, sec_benchmarks$fip, sec_benchmarks$whip,
                       sec_benchmarks$k_pct, sec_benchmarks$bb_pct,
                       sec_benchmarks$ba_against, sec_benchmarks$ba_against,
                       sec_benchmarks$slg_against, sec_benchmarks$slg_against)
  row2_higher_better <- c(FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE)
  
  n_cols2 <- length(row2_labels)
  total_width2 <- 0.80
  col_w2 <- total_width2 / n_cols2
  start_x2 <- 0.10
  
  for (i in seq_along(row2_labels)) {
    x_pos <- start_x2 + (i - 0.5) * col_w2
    fill_col <- get_stat_color(row2_values[i], row2_benchmarks[i], row2_higher_better[i], 0.30)
    grid::grid.rect(x = x_pos, y = row2_y, width = col_w2, height = 0.012,
                    gp = grid::gpar(fill = "#006F71", col = "black", lwd = 0.5), just = c("center", "top"))
    grid::grid.text(row2_labels[i], x = x_pos, y = row2_y - 0.006,
                    gp = grid::gpar(fontsize = 9, fontface = "bold", col = "white"))
    grid::grid.rect(x = x_pos, y = row2_y - 0.012, width = col_w2, height = 0.014,
                    gp = grid::gpar(fill = fill_col, col = "black", lwd = 0.5), just = c("center", "top"))
    val_text <- if (is.na(row2_values[i])) "-" else if (i <= 3) sprintf("%.2f", row2_values[i]) else if (i <= 5) paste0(row2_values[i], "%") else sprintf(".%03d", round(row2_values[i] * 1000))
    grid::grid.text(val_text, x = x_pos, y = row2_y - 0.019,
                    gp = grid::gpar(fontsize = 9))
  }
  
  # ===== ROW 3: Pitch-level Stats =====
  row3_y <- 0.895
  row3_labels <- c("Whiff%", "Zone%", "Strike%", "FB Strike%", "BB Strike%", "OS Strike%")
  row3_values <- c(stats$whiff_pct, stats$zone_pct, stats$strike_pct,
                   stats$fb_strike_pct, stats$bb_strike_pct, stats$os_strike_pct)
  row3_benchmarks <- c(sec_benchmarks$whiff_pct, sec_benchmarks$zone_pct, sec_benchmarks$strike_pct,
                       sec_benchmarks$fb_strike, sec_benchmarks$bb_strike, sec_benchmarks$os_strike)
  
  n_cols3 <- length(row3_labels)
  total_width3 <- 0.70
  col_w3 <- total_width3 / n_cols3
  start_x3 <- 0.15
  
  for (i in seq_along(row3_labels)) {
    x_pos <- start_x3 + (i - 0.5) * col_w3
    fill_col <- get_stat_color(row3_values[i], row3_benchmarks[i], TRUE, 0.20)
    grid::grid.rect(x = x_pos, y = row3_y, width = col_w3, height = 0.012,
                    gp = grid::gpar(fill = "#006F71", col = "black", lwd = 0.5), just = c("center", "top"))
    grid::grid.text(row3_labels[i], x = x_pos, y = row3_y - 0.006,
                    gp = grid::gpar(fontsize = 9, fontface = "bold", col = "white"))
    grid::grid.rect(x = x_pos, y = row3_y - 0.012, width = col_w3, height = 0.014,
                    gp = grid::gpar(fill = fill_col, col = "black", lwd = 0.5), just = c("center", "top"))
    val_text <- if (is.na(row3_values[i])) "-" else paste0(row3_values[i], "%")
    grid::grid.text(val_text, x = x_pos, y = row3_y - 0.019,
                    gp = grid::gpar(fontsize = 9))
  }
  
  # ===== CHARTS ROW 1: Arm Angle, Movement, Count Usage =====
  chart_row1_y <- 0.865
  chart_height1 <- 0.20
  
  # Arm angle
  grid::pushViewport(grid::viewport(x = 0.11, y = chart_row1_y, width = 0.19, height = chart_height1 * 0.80, just = c("center", "top")))
  tryCatch(print(arm_angle_plot, newpage = FALSE), error = function(e) NULL)
  grid::popViewport()
  
  # Delivery Notes box under arm angle - ALWAYS show the box
  delivery_notes_y <- chart_row1_y - chart_height1 * 0.80 - 0.005
  notes_height <- 0.045
  grid::grid.rect(x = 0.12, y = delivery_notes_y, width = 0.18, height = notes_height,
                  gp = grid::gpar(fill = "white", col = "#006F71", lwd = 1), just = c("center", "top"))
  grid::grid.text("Delivery Notes", x = 0.12, y = delivery_notes_y - 0.005,
                  gp = grid::gpar(fontsize = 8, fontface = "bold", col = "#006F71"))
  if (nchar(delivery_notes) > 0) {
    # Wrap text for notes
    wrapped_notes <- strwrap(delivery_notes, width = 30)
    for (j in seq_along(wrapped_notes)) {
      grid::grid.text(wrapped_notes[j], x = 0.11, y = delivery_notes_y - 0.015 - (j - 1) * 0.009,
                      gp = grid::gpar(fontsize = 7))
    }
  }
  
  # Movement - HUGE
  grid::pushViewport(grid::viewport(x = 0.46, y = chart_row1_y, width = 0.58, height = chart_height1 + 0.03, just = c("center", "top")))
  tryCatch(print(movement_plot, newpage = FALSE), error = function(e) NULL)
  grid::popViewport()
  
  # Count usage pies - lowered position
  grid::pushViewport(grid::viewport(x = 0.85, y = chart_row1_y - 0.02, width = 0.28, height = chart_height1 * 0.55, just = c("center", "top")))
  tryCatch(print(count_plot, newpage = FALSE), error = function(e) NULL)
  grid::popViewport()
  
  # ===== TIME THROUGH ORDER CHART (replaces pitch usage table) =====
  tto_chart <- tryCatch(
    create_tto_chart(data, pitcher_name),
    error = function(e) ggplot() + theme_void() + ggtitle("TTO Error")
  )
  
  usage_table_y <- 0.735
  usage_table_center <- 0.85
  
  pitch_df <- data %>%
    filter(Pitcher == pitcher_name, !is.na(TaggedPitchType), TaggedPitchType != "Other")
  
  main_pitches <- pitch_df %>%
    count(TaggedPitchType) %>%
    mutate(pct = n / sum(n) * 100) %>%
    filter(pct >= 3) %>%
    arrange(desc(pct)) %>%
    head(4) %>%
    pull(TaggedPitchType)
  
  # ===== TTO CHART (replaces old pitch usage table) =====
  grid::pushViewport(grid::viewport(x = usage_table_center, y = usage_table_y + 0.01, 
                                    width = 0.26, height = 0.10, just = c("center", "top")))
  tryCatch(print(tto_chart, newpage = FALSE), error = function(e) NULL)
  grid::popViewport()
  
  # ===== CHARTS ROW 2: Sequencing and Spray Charts =====
  chart_row2_y <- 0.645
  chart_height2 <- 0.11
  
  grid::pushViewport(grid::viewport(x = 0.17, y = chart_row2_y, width = 0.26, height = chart_height2, just = c("center", "top")))
  tryCatch(print(seq_lhh, newpage = FALSE), error = function(e) NULL)
  grid::popViewport()
  
  grid::pushViewport(grid::viewport(x = 0.43, y = chart_row2_y, width = 0.26, height = chart_height2, just = c("center", "top")))
  tryCatch(print(seq_rhh, newpage = FALSE), error = function(e) NULL)
  grid::popViewport()
  
  grid::pushViewport(grid::viewport(x = 0.67, y = chart_row2_y, width = 0.18, height = chart_height2, just = c("center", "top")))
  tryCatch(print(spray_lhh, newpage = FALSE), error = function(e) NULL)
  grid::popViewport()
  
  grid::pushViewport(grid::viewport(x = 0.85, y = chart_row2_y, width = 0.18, height = chart_height2, just = c("center", "top")))
  tryCatch(print(spray_rhh, newpage = FALSE), error = function(e) NULL)
  grid::popViewport()
  
  # ===== PITCH CHARACTERISTICS TABLE =====
  table_y <- 0.525
  
  if (!is.null(pitch_char) && nrow(pitch_char) > 0) {
    headers <- names(pitch_char)
    num_cols <- length(headers)
    num_rows <- min(nrow(pitch_char), 7)
    
    base_width <- 0.92 / (num_cols - 1 + 2.5)
    col_widths <- sapply(headers, function(h) {
      if (h == "Notes") base_width * 2.5 else base_width
    })
    x_starts_tbl <- 0.04 + cumsum(c(0, col_widths[-length(col_widths)]))
    row_h <- 0.016
    
    for (j in seq_along(headers)) {
      grid::grid.rect(x = x_starts_tbl[j], y = table_y, width = col_widths[j] * 0.98, height = row_h,
                      gp = grid::gpar(fill = "#006F71", col = "black", lwd = 0.5), just = c("left", "top"))
      grid::grid.text(headers[j], x = x_starts_tbl[j] + col_widths[j] * 0.49, y = table_y - row_h * 0.5,
                      gp = grid::gpar(fontsize = 8, fontface = "bold", col = "white"))
    }
    
    rate_cols <- c("Strike%", "Whiff%", "Zone%", "Putaway%")
    velo_cols <- c("AvgVelo", "MaxVelo")
    
    # SEC benchmarks by pitch type for AvgEV and wOBAcon (lower is better for pitcher)
    ev_benchmarks <- list(
      "Fastball" = 88.6, "Four-Seam" = 88.6, "FourSeamFastBall" = 88.6,
      "Sinker" = 87.9, "TwoSeamFastBall" = 87.9,
      "Slider" = 85.3, "Sweeper" = 85.5,
      "Changeup" = 85.6, "ChangeUp" = 85.6,
      "Curveball" = 85.4, "Splitter" = 85.2, "Cutter" = 86.5
    )
    wobacon_benchmarks <- list(
      "Fastball" = 0.402, "Four-Seam" = 0.402, "FourSeamFastBall" = 0.402,
      "Sinker" = 0.377, "TwoSeamFastBall" = 0.377,
      "Slider" = 0.393, "Sweeper" = 0.395,
      "Changeup" = 0.389, "ChangeUp" = 0.389,
      "Curveball" = 0.372, "Splitter" = 0.358, "Cutter" = 0.390
    )
    
    for (i in seq_len(num_rows)) {
      y_row <- table_y - i * row_h
      pitch_type <- pitch_char$Pitch[i]
      
      velo_bench <- if (pitch_type %in% c("Fastball", "Sinker", "Four-Seam", "Two-Seam")) 93 
      else if (pitch_type == "Slider") 83
      else if (pitch_type == "Curveball") 79
      else if (pitch_type %in% c("ChangeUp", "Changeup")) 84
      else if (pitch_type == "Cutter") 87
      else 85
      
      spin_bench <- if (pitch_type %in% c("Fastball", "Sinker", "Four-Seam", "Two-Seam")) 2267
      else if (pitch_type == "Slider") 2440
      else if (pitch_type == "Curveball") 2442
      else if (pitch_type %in% c("ChangeUp", "Changeup")) 1708
      else if (pitch_type == "Cutter") 2387
      else 2200
      
      ext_bench <- if (pitch_type %in% c("Fastball", "Sinker", "Four-Seam", "Two-Seam")) 5.83
      else if (pitch_type == "Slider") 5.54
      else if (pitch_type == "Curveball") 5.47
      else if (pitch_type %in% c("ChangeUp", "Changeup")) 5.98
      else if (pitch_type == "Cutter") 5.70
      else 5.60
      
      # Get SEC benchmarks for this pitch type
      ev_bench <- ev_benchmarks[[pitch_type]] %||% 86.5
      wobacon_bench <- wobacon_benchmarks[[pitch_type]] %||% 0.390
      
      for (j in seq_along(headers)) {
        val <- pitch_char[[headers[j]]][i]
        bg <- "#FFFFFF"
        
        if (headers[j] == "Pitch" && as.character(val) %in% names(pitch_colors)) {
          bg <- pitch_colors[[as.character(val)]]
        }
        if (headers[j] %in% velo_cols && is.numeric(val) && !is.na(val)) {
          bg <- get_stat_color(val, velo_bench, TRUE, 0.08)
        }
        if (headers[j] == "Spin" && is.numeric(val) && !is.na(val)) {
          bg <- get_stat_color(val, spin_bench, TRUE, 0.15)
        }
        if (headers[j] == "Ext" && is.numeric(val) && !is.na(val)) {
          bg <- get_stat_color(val, ext_bench, TRUE, 0.10)
        }
        if (headers[j] %in% rate_cols && is.numeric(val) && !is.na(val)) {
          benchmark <- switch(headers[j],
                              "Strike%" = 62,
                              "Whiff%" = 29,
                              "Zone%" = 46,
                              "Putaway%" = 25,
                              NA)
          if (!is.na(benchmark)) {
            bg <- get_stat_color(val, benchmark, TRUE, 0.25)
          }
        }
        # Whiff% vL and vR coloring - higher is better for pitcher
        if (headers[j] %in% c("Whiff% vL", "Whiff% vR") && is.numeric(val) && !is.na(val)) {
          bg <- get_stat_color(val, 29, TRUE, 0.25)  # TRUE = higher is better
        }
        # AvgEV coloring - lower is better for pitcher (inverse)
        if (headers[j] == "AvgEV" && is.numeric(val) && !is.na(val) && pitch_type != "TOTAL") {
          bg <- get_stat_color(val, ev_bench, FALSE, 0.06)  # FALSE = lower is better
        }
        # wOBAcon coloring - lower is better for pitcher (inverse)
        if (headers[j] == "wOBAcon" && is.numeric(val) && !is.na(val) && pitch_type != "TOTAL") {
          bg <- get_stat_color(val, wobacon_bench, FALSE, 0.15)  # FALSE = lower is better
        }
        # wOBA overall and splits coloring - lower is better for pitcher (inverse)
        if (headers[j] %in% c("wOBA", "wOBA vL", "wOBA vR") && is.numeric(val) && !is.na(val) && pitch_type != "TOTAL") {
          bg <- get_stat_color(val, 0.320, FALSE, 0.15)  # FALSE = lower is better, SEC avg wOBA ~0.320
        }
        if (headers[j] == "Stuff+" && is.numeric(val) && !is.na(val)) {
          bg <- get_stat_color(val, 100, TRUE, 0.15)
        }
        if (headers[j] == "Notes") {
          bg <- "#f5f5f5"
        }
        
        grid::grid.rect(x = x_starts_tbl[j], y = y_row, width = col_widths[j] * 0.98, height = row_h,
                        gp = grid::gpar(fill = bg, col = "gray70", lwd = 0.3), just = c("left", "top"))
        
        # Check for pitch-specific notes
        display_val <- if (headers[j] == "Notes" && pitch_type %in% names(pitch_notes)) {
          pitch_notes[[pitch_type]]
        } else if (headers[j] %in% c("wOBAcon", "wOBA", "wOBA vL", "wOBA vR") && is.numeric(val) && !is.na(val)) {
          # Format wOBA/wOBAcon as .XXX (e.g., .402 not 0.40)
          if (val < 1) {
            sub("^0", "", sprintf("%.3f", val))  # Remove leading zero: 0.402 -> .402
          } else {
            sprintf("%.3f", val)
          }
        } else if (is.numeric(val)) {
          if (is.na(val)) "-" else if (abs(val) < 10 && val != round(val)) sprintf("%.2f", val) else sprintf("%.1f", val)
        } else as.character(val)
        
        if (headers[j] != "Notes" || (headers[j] == "Notes" && pitch_type %in% names(pitch_notes))) {
          grid::grid.text(display_val, x = x_starts_tbl[j] + col_widths[j] * 0.49, y = y_row - row_h * 0.5,
                          gp = grid::gpar(fontsize = 7.5))
        }
      }
    }
  }
  
  # ===== HEATMAPS SECTION - Clean Layout (INCLUDES PILL STAT INDICATORS) =====
  hm_section_y <- 0.34
  
  # Section header
  grid::grid.rect(x = 0.5, y = hm_section_y + 0.032, width = 0.98, height = 0.015,
                  gp = grid::gpar(fill = "#006F71", col = NA))
  grid::grid.text("Location Analysis", x = 0.5, y = hm_section_y + 0.032,
                  gp = grid::gpar(fontsize = 10, fontface = "bold", col = "white"))
  
  # Colors for heatmaps + column pills
  hm_colors <- c("white", "blue", "#FF9999", "red", "darkred")
  fb_pill <- "#FA8072"
  bb_pill <- "#A020F0"
  os_pill <- "#228B22"
  
  # Dimensions / spacing
  hm_height   <- 0.048
  hm_width    <- 0.052
  hm_gap      <- 0.003
  pill_w      <- 0.022
  pill_h      <- 0.009
  row_pill_w  <- 0.018
  row_pill_h  <- 0.008
  
  # Even spacing for 4 main sections
  section_centers <- seq(0.16, 0.78, length.out = 4)
  sec1_center <- section_centers[1]   # vs LHH
  sec2_center <- section_centers[2]   # vs RHH
  sec3_center <- section_centers[3]   # LHH by Count
  sec4_center <- section_centers[4]   # RHH by Count
  nitro_center <- 0.93
  
  # Row y positions (3 rows)
  row_y <- c(
    hm_section_y - 0.020,
    hm_section_y - 0.020 - hm_height - hm_gap,
    hm_section_y - 0.020 - 2 * (hm_height + hm_gap)
  )
  
  # Row label pills for sections 1/2
  row_labels_1 <- c("All", "Whf", "Dmg")
  row_colors_1 <- c("#006F71", "#00840D", "#E1463E")
  
  # Row label pills for count sections 3/4
  row_labels_count <- c("1st", "Bhd", "2K")
  row_keys_count   <- c("1st", "Behind", "2K")
  row_colors_count <- c("#4169E1", "#FF8C00", "#DC143C")
  
  # Pitch groups (columns in count grids: FB/BB/OS)
  pitch_groups <- list(
    FB = c("Fastball", "Sinker", "Four-Seam", "FourSeamFastBall", "TwoSeamFastBall"),
    BB = c("Slider", "Curveball", "Sweeper", "Slurve", "Cutter"),
    OS = c("Changeup", "ChangeUp", "Splitter")
  )
  
  # ------------------------
  # Helper: pitch abbrev
  # ------------------------
  get_pt_short <- function(pt) {
    dplyr::case_when(
      pt %in% c("Fastball", "Four-Seam", "FourSeamFastBall") ~ "FB",
      pt %in% c("Sinker", "TwoSeamFastBall") ~ "SI",
      pt %in% c("Slider", "Sweeper") ~ "SL",
      pt == "Curveball" ~ "CB",
      pt %in% c("Changeup", "ChangeUp") ~ "CH",
      pt == "Splitter" ~ "SP",
      pt == "Cutter" ~ "CT",
      TRUE ~ substr(as.character(pt), 1, 2)
    )
  }
  
  # ------------------------
  # UNIFIED HEATMAP FUNCTION - Uses stat_density_2d
  # ------------------------
  create_density_heatmap <- function(data, min_pitches = 5) {
    # Base plot with zone
    base_plot <- ggplot() +
      annotate("rect", xmin = -0.8303, xmax = 0.8303, ymin = 1.5, ymax = 3.5,
               fill = NA, color = "black", linewidth = 0.5) +
      annotate("path",
               x = c(-0.708, 0.708, 0.708, 0, -0.708, -0.708),
               y = c(0.15, 0.15, 0.3, 0.5, 0.3, 0.15),
               color = "black", linewidth = 0.4) +
      coord_fixed(xlim = c(-2, 2), ylim = c(0, 4.5)) +
      theme_void() +
      theme(
        legend.position = "none",
        plot.margin = margin(0, 0, 0, 0)
      )
    
    # If no data or too few pitches, return blank zone
    if (is.null(data) || nrow(data) < min_pitches) {
      return(base_plot)
    }
    
    # Filter to valid location data
    plot_data <- data %>%
      dplyr::filter(!is.na(PlateLocSide), !is.na(PlateLocHeight))
    
    if (nrow(plot_data) < min_pitches) {
      return(base_plot)
    }
    
    # If small sample, use points instead of density
    if (nrow(plot_data) < 15) {
      p <- base_plot +
        geom_point(data = plot_data, 
                   aes(x = PlateLocSide, y = PlateLocHeight),
                   color = "red", alpha = 0.7, size = 1.5)
      return(p)
    }
    
    # Full density heatmap for larger samples
    p <- ggplot(plot_data, aes(x = PlateLocSide, y = PlateLocHeight)) +
      stat_density_2d(aes(fill = after_stat(density)), 
                      geom = "raster", 
                      contour = FALSE,
                      n = 100) +
      scale_fill_gradientn(
        colours = c("white", "blue", "#FF9999", "red", "darkred"),
        name = "Density"
      ) +
      annotate("rect", xmin = -0.8303, xmax = 0.8303, ymin = 1.5, ymax = 3.5,
               fill = NA, color = "black", linewidth = 0.5) +
      annotate("path",
               x = c(-0.708, 0.708, 0.708, 0, -0.708, -0.708),
               y = c(0.15, 0.15, 0.3, 0.5, 0.3, 0.15),
               color = "black", linewidth = 0.4) +
      coord_fixed(xlim = c(-2, 2), ylim = c(0, 4.5)) +
      theme_void() +
      theme(
        legend.position = "none",
        plot.margin = margin(0, 0, 0, 0)
      )
    
    return(p)
  }
  
  # ------------------------
  # PILL STAT INDICATORS (vL / vR)
  # ------------------------
  pill_y <- hm_section_y + 0.015
  
  # 2K putaway by side
  putaway_lhh <- pitch_df %>%
    dplyr::filter(Strikes == 2, BatterSide == "Left") %>%
    dplyr::group_by(TaggedPitchType) %>%
    dplyr::summarise(
      n_2k = dplyr::n(),
      n_putaway = sum(KorBB == "Strikeout", na.rm = TRUE),
      putaway_pct = 100 * n_putaway / n_2k,
      .groups = "drop"
    ) %>%
    dplyr::filter(n_2k >= 5) %>%
    dplyr::arrange(dplyr::desc(putaway_pct))
  
  putaway_rhh <- pitch_df %>%
    dplyr::filter(Strikes == 2, BatterSide == "Right") %>%
    dplyr::group_by(TaggedPitchType) %>%
    dplyr::summarise(
      n_2k = dplyr::n(),
      n_putaway = sum(KorBB == "Strikeout", na.rm = TRUE),
      putaway_pct = 100 * n_putaway / n_2k,
      .groups = "drop"
    ) %>%
    dplyr::filter(n_2k >= 5) %>%
    dplyr::arrange(dplyr::desc(putaway_pct))
  
  grid::grid.text("2K Out:", x = 0.10, y = pill_y, just = "left",
                  gp = grid::gpar(fontsize = 6, fontface = "bold", col = "#006F71"))
  
  if (nrow(putaway_lhh) > 0) {
    pt_short <- get_pt_short(putaway_lhh$TaggedPitchType[1])
    grid::grid.roundrect(x = 0.155, y = pill_y, width = 0.055, height = 0.010,
                         r = unit(0.3, "snpc"), gp = grid::gpar(fill = "#CD853F", col = NA))
    grid::grid.text(paste0("vL ", pt_short, " ", sprintf("%.0f%%", putaway_lhh$putaway_pct[1])),
                    x = 0.155, y = pill_y,
                    gp = grid::gpar(fontsize = 5, fontface = "bold", col = "white"))
  }
  if (nrow(putaway_rhh) > 0) {
    pt_short <- get_pt_short(putaway_rhh$TaggedPitchType[1])
    grid::grid.roundrect(x = 0.215, y = pill_y, width = 0.055, height = 0.010,
                         r = unit(0.3, "snpc"), gp = grid::gpar(fill = "#CD853F", col = NA))
    grid::grid.text(paste0("vR ", pt_short, " ", sprintf("%.0f%%", putaway_rhh$putaway_pct[1])),
                    x = 0.215, y = pill_y,
                    gp = grid::gpar(fontsize = 5, fontface = "bold", col = "white"))
  }
  
  # 1st pitch usage by side
  first_lhh <- pitch_df %>%
    dplyr::filter(PitchofPA == 1, BatterSide == "Left") %>%
    dplyr::count(TaggedPitchType, name = "n") %>%
    dplyr::mutate(pct = 100 * n / sum(n)) %>%
    dplyr::arrange(dplyr::desc(pct))
  
  first_rhh <- pitch_df %>%
    dplyr::filter(PitchofPA == 1, BatterSide == "Right") %>%
    dplyr::count(TaggedPitchType, name = "n") %>%
    dplyr::mutate(pct = 100 * n / sum(n)) %>%
    dplyr::arrange(dplyr::desc(pct))
  
  grid::grid.text("1st:", x = 0.27, y = pill_y, just = "left",
                  gp = grid::gpar(fontsize = 6, fontface = "bold", col = "#006F71"))
  
  if (nrow(first_lhh) > 0) {
    pt_short <- get_pt_short(first_lhh$TaggedPitchType[1])
    grid::grid.roundrect(x = 0.315, y = pill_y, width = 0.055, height = 0.010,
                         r = unit(0.3, "snpc"), gp = grid::gpar(fill = "#4169E1", col = NA))
    grid::grid.text(paste0("vL ", pt_short, " ", sprintf("%.0f%%", first_lhh$pct[1])),
                    x = 0.315, y = pill_y,
                    gp = grid::gpar(fontsize = 5, fontface = "bold", col = "white"))
  }
  if (nrow(first_rhh) > 0) {
    pt_short <- get_pt_short(first_rhh$TaggedPitchType[1])
    grid::grid.roundrect(x = 0.375, y = pill_y, width = 0.055, height = 0.010,
                         r = unit(0.3, "snpc"), gp = grid::gpar(fill = "#4169E1", col = NA))
    grid::grid.text(paste0("vR ", pt_short, " ", sprintf("%.0f%%", first_rhh$pct[1])),
                    x = 0.375, y = pill_y,
                    gp = grid::gpar(fontsize = 5, fontface = "bold", col = "white"))
  }
  
  # Hardest hit (avg EV) by side
  hardest_lhh <- pitch_df %>%
    dplyr::filter(PitchCall == "InPlay", !is.na(ExitSpeed), BatterSide == "Left") %>%
    dplyr::group_by(TaggedPitchType) %>%
    dplyr::summarise(avg_ev = mean(ExitSpeed, na.rm = TRUE), n_bip = dplyr::n(), .groups = "drop") %>%
    dplyr::filter(n_bip >= 3) %>%
    dplyr::arrange(dplyr::desc(avg_ev))
  
  hardest_rhh <- pitch_df %>%
    dplyr::filter(PitchCall == "InPlay", !is.na(ExitSpeed), BatterSide == "Right") %>%
    dplyr::group_by(TaggedPitchType) %>%
    dplyr::summarise(avg_ev = mean(ExitSpeed, na.rm = TRUE), n_bip = dplyr::n(), .groups = "drop") %>%
    dplyr::filter(n_bip >= 3) %>%
    dplyr::arrange(dplyr::desc(avg_ev))
  
  grid::grid.text("Hardest:", x = 0.43, y = pill_y, just = "left",
                  gp = grid::gpar(fontsize = 6, fontface = "bold", col = "#006F71"))
  
  if (nrow(hardest_lhh) > 0) {
    pt_short <- get_pt_short(hardest_lhh$TaggedPitchType[1])
    grid::grid.roundrect(x = 0.49, y = pill_y, width = 0.055, height = 0.010,
                         r = unit(0.3, "snpc"), gp = grid::gpar(fill = "#E1463E", col = NA))
    grid::grid.text(paste0("vL ", pt_short, " ", sprintf("%.0f", hardest_lhh$avg_ev[1])),
                    x = 0.49, y = pill_y,
                    gp = grid::gpar(fontsize = 5, fontface = "bold", col = "white"))
  }
  if (nrow(hardest_rhh) > 0) {
    pt_short <- get_pt_short(hardest_rhh$TaggedPitchType[1])
    grid::grid.roundrect(x = 0.55, y = pill_y, width = 0.055, height = 0.010,
                         r = unit(0.3, "snpc"), gp = grid::gpar(fill = "#E1463E", col = NA))
    grid::grid.text(paste0("vR ", pt_short, " ", sprintf("%.0f", hardest_rhh$avg_ev[1])),
                    x = 0.55, y = pill_y,
                    gp = grid::gpar(fontsize = 5, fontface = "bold", col = "white"))
  }
  
  # ------------------------
  # Helpers: section header + row pills
  # ------------------------
  draw_section_header <- function(x_center, label, label_col) {
    col_x <- c(x_center - hm_width - hm_gap, x_center, x_center + hm_width + hm_gap)
    
    grid::grid.text(label, x = x_center, y = hm_section_y - 0.002,
                    gp = grid::gpar(fontsize = 7, fontface = "bold", col = label_col))
    
    pills <- list(list(fb_pill, "FB"), list(bb_pill, "BB"), list(os_pill, "OS"))
    for (i in 1:3) {
      grid::grid.roundrect(x = col_x[i], y = hm_section_y - 0.011, width = pill_w, height = pill_h,
                           r = unit(0.3, "snpc"), gp = grid::gpar(fill = pills[[i]][[1]], col = NA))
      grid::grid.text(pills[[i]][[2]], x = col_x[i], y = hm_section_y - 0.011,
                      gp = grid::gpar(fontsize = 5.5, fontface = "bold", col = "white"))
    }
    
    col_x
  }
  
  draw_row_pills <- function(first_col_x, labels, fills) {
    for (r in 1:3) {
      x_pill <- first_col_x - hm_width/2 - 0.014
      y_pill <- row_y[r] - hm_height/2
      grid::grid.roundrect(x = x_pill, y = y_pill, width = row_pill_w, height = row_pill_h,
                           r = unit(0.3, "snpc"), gp = grid::gpar(fill = fills[r], col = NA))
      grid::grid.text(labels[r], x = x_pill, y = y_pill,
                      gp = grid::gpar(fontsize = 5, fontface = "bold", col = "white"))
    }
  }
  
  # Define all section column positions
  sec1_col_x <- draw_section_header(sec1_center, "vs LHH", "#E53935")
  sec2_col_x <- draw_section_header(sec2_center, "vs RHH", "#1E88E5")
  sec3_col_x <- draw_section_header(sec3_center, "LHH by Count", "#E53935")
  sec4_col_x <- draw_section_header(sec4_center, "RHH by Count", "#1E88E5")
  
  # Draw row pills for each section
  draw_row_pills(sec1_col_x[1], row_labels_1, row_colors_1)
  draw_row_pills(sec2_col_x[1], row_labels_1, row_colors_1)
  draw_row_pills(sec3_col_x[1], row_labels_count, row_colors_count)
  draw_row_pills(sec4_col_x[1], row_labels_count, row_colors_count)
  
  # ------------------------
  # Count filters
  # ------------------------
  count_filters <- list(
    "1st"    = function(d) dplyr::filter(d, PitchofPA == 1),
    "Behind" = function(d) dplyr::filter(d, Balls > Strikes),
    "2K"     = function(d) dplyr::filter(d, Strikes == 2)
  )
  
  # Metric filters for whiff/damage
  metric_filters <- list(
    "All"    = function(d) d,
    "Whiff"  = function(d) dplyr::filter(d, PitchCall %in% c("StrikeSwinging", "SwingingStrike")),
    "Damage" = function(d) dplyr::filter(d, PitchCall == "InPlay", ExitSpeed >= 95)
  )
  
  # ------------------------
  # SECTION 1: vs LHH (All / Whiff / Damage)
  # ------------------------
  hm_metrics <- c("All", "Whiff", "Damage")
  hm_groups  <- c("FB", "BB", "OS")
  
  for (row_idx in 1:3) {
    for (col_idx in 1:3) {
      # Filter data for this cell
      cell_data <- pitch_df %>%
        dplyr::filter(
          TaggedPitchType %in% pitch_groups[[col_idx]],
          BatterSide == "Left",
          !is.na(PlateLocSide), 
          !is.na(PlateLocHeight)
        )
      
      # Apply metric filter
      cell_data <- metric_filters[[hm_metrics[row_idx]]](cell_data)
      
      # Create heatmap
      p <- create_density_heatmap(cell_data)
      
      grid::pushViewport(grid::viewport(
        x = sec1_col_x[col_idx], y = row_y[row_idx],
        width = hm_width, height = hm_height, just = c("center", "top")
      ))
      tryCatch(print(p, newpage = FALSE), error = function(e) NULL)
      grid::popViewport()
    }
  }
  
  # ------------------------
  # SECTION 2: vs RHH (All / Whiff / Damage)
  # ------------------------
  for (row_idx in 1:3) {
    for (col_idx in 1:3) {
      # Filter data for this cell
      cell_data <- pitch_df %>%
        dplyr::filter(
          TaggedPitchType %in% pitch_groups[[col_idx]],
          BatterSide == "Right",
          !is.na(PlateLocSide), 
          !is.na(PlateLocHeight)
        )
      
      # Apply metric filter
      cell_data <- metric_filters[[hm_metrics[row_idx]]](cell_data)
      
      # Create heatmap
      p <- create_density_heatmap(cell_data)
      
      grid::pushViewport(grid::viewport(
        x = sec2_col_x[col_idx], y = row_y[row_idx],
        width = hm_width, height = hm_height, just = c("center", "top")
      ))
      tryCatch(print(p, newpage = FALSE), error = function(e) NULL)
      grid::popViewport()
    }
  }
  
  # ------------------------
  # SECTION 3: LHH by Count (1st / Behind / 2K)
  # ------------------------
  for (row_idx in 1:3) {
    for (col_idx in 1:3) {
      # Filter data for this cell
      cell_data <- pitch_df %>%
        dplyr::filter(
          TaggedPitchType %in% pitch_groups[[col_idx]],
          BatterSide == "Left",
          !is.na(PlateLocSide), 
          !is.na(PlateLocHeight)
        )
      
      # Apply count filter
      cell_data <- count_filters[[row_keys_count[row_idx]]](cell_data)
      
      # Create heatmap
      p <- create_density_heatmap(cell_data)
      
      grid::pushViewport(grid::viewport(
        x = sec3_col_x[col_idx], y = row_y[row_idx],
        width = hm_width, height = hm_height, just = c("center", "top")
      ))
      tryCatch(print(p, newpage = FALSE), error = function(e) NULL)
      grid::popViewport()
    }
  }
  
  # ------------------------
  # SECTION 4: RHH by Count (1st / Behind / 2K)
  # ------------------------
  for (row_idx in 1:3) {
    for (col_idx in 1:3) {
      # Filter data for this cell
      cell_data <- pitch_df %>%
        dplyr::filter(
          TaggedPitchType %in% pitch_groups[[col_idx]],
          BatterSide == "Right",
          !is.na(PlateLocSide), 
          !is.na(PlateLocHeight)
        )
      
      # Apply count filter
      cell_data <- count_filters[[row_keys_count[row_idx]]](cell_data)
      
      # Create heatmap
      p <- create_density_heatmap(cell_data)
      
      grid::pushViewport(grid::viewport(
        x = sec4_col_x[col_idx], y = row_y[row_idx],
        width = hm_width, height = hm_height, just = c("center", "top")
      ))
      tryCatch(print(p, newpage = FALSE), error = function(e) NULL)
      grid::popViewport()
    }
  }
  
  # ===== SECTION 5: NITRO ZONES (smaller, far right) =====
  nitro_width <- 0.055
  nitro_height <- 0.060
  
  grid::grid.text("Nitro Zones", x = nitro_center, y = hm_section_y - 0.002,
                  gp = grid::gpar(fontsize = 8, fontface = "bold", col = "#E1463E"))
  grid::grid.text("(90th %ile EV)", x = nitro_center, y = hm_section_y - 0.010,
                  gp = grid::gpar(fontsize = 7, col = "#E1463E"))
  
  nitro_y_lhh <- hm_section_y - 0.025
  nitro_y_rhh <- hm_section_y - 0.095
  
  # Labels
  grid::grid.roundrect(x = nitro_center - nitro_width/2 - 0.012, y = nitro_y_lhh - nitro_height/2,
                       width = 0.020, height = 0.008,
                       r = unit(0.3, "snpc"), gp = grid::gpar(fill = "#E53935", col = NA))
  grid::grid.text("LHH", x = nitro_center - nitro_width/2 - 0.012, y = nitro_y_lhh - nitro_height/2,
                  gp = grid::gpar(fontsize = 5, fontface = "bold", col = "white"))
  
  grid::grid.roundrect(x = nitro_center - nitro_width/2 - 0.012, y = nitro_y_rhh - nitro_height/2,
                       width = 0.020, height = 0.008,
                       r = unit(0.3, "snpc"), gp = grid::gpar(fill = "#1E88E5", col = NA))
  grid::grid.text("RHH", x = nitro_center - nitro_width/2 - 0.012, y = nitro_y_rhh - nitro_height/2,
                  gp = grid::gpar(fontsize = 5, fontface = "bold", col = "white"))
  
  for (side in c("Left", "Right")) {
    nitro_data <- pitch_df %>%
      dplyr::filter(
        BatterSide == side, 
        PitchCall == "InPlay", 
        !is.na(ExitSpeed),
        !is.na(PlateLocSide), 
        !is.na(PlateLocHeight)
      )
    
    if (nrow(nitro_data) >= 8) {
      ev_90 <- quantile(nitro_data$ExitSpeed, 0.90, na.rm = TRUE)
      nitro_pts <- nitro_data %>% dplyr::filter(ExitSpeed >= ev_90)
      
      y_pos <- if (side == "Left") nitro_y_lhh else nitro_y_rhh
      
      p <- ggplot(nitro_pts, aes(x = PlateLocSide, y = PlateLocHeight)) +
        annotate("rect", xmin = -0.83, xmax = 0.83, ymin = 1.5, ymax = 3.5, 
                 fill = "#FFF5F5", color = "black", linewidth = 0.5) +
        annotate("path", x = c(-0.708, 0.708, 0.708, 0, -0.708, -0.708),
                 y = c(0.15, 0.15, 0.3, 0.5, 0.3, 0.15), color = "black", linewidth = 0.4) +
        geom_point(aes(size = ExitSpeed), color = "#DC143C", alpha = 0.8) +
        scale_size_continuous(range = c(1.2, 3.5), guide = "none") +
        coord_fixed(xlim = c(-2, 2), ylim = c(0, 4.5)) +
        theme_void() + theme(plot.margin = margin(0,0,0,0))
      
      grid::pushViewport(grid::viewport(x = nitro_center, y = y_pos, 
                                        width = nitro_width, height = nitro_height, 
                                        just = c("center", "top")))
      tryCatch(print(p, newpage = FALSE), error = function(e) NULL)
      grid::popViewport()
    }
  }
  

  
  # ===== SECTION 5: NITRO ZONES (smaller, far right) =====
  nitro_width <- 0.055
  nitro_height <- 0.060
  
  grid::grid.text("Nitro Zones", x = nitro_center, y = hm_section_y - 0.002,
                  gp = grid::gpar(fontsize = 8, fontface = "bold", col = "#E1463E"))
  grid::grid.text("(90th %ile EV)", x = nitro_center, y = hm_section_y - 0.010,
                  gp = grid::gpar(fontsize = 7, col = "#E1463E"))
  
  nitro_y_lhh <- hm_section_y - 0.025
  nitro_y_rhh <- hm_section_y - 0.095
  
  # Labels
  grid::grid.roundrect(x = nitro_center - nitro_width/2 - 0.012, y = nitro_y_lhh - nitro_height/2,
                       width = 0.020, height = 0.008,
                       r = unit(0.3, "snpc"), gp = grid::gpar(fill = "#E53935", col = NA))
  grid::grid.text("LHH", x = nitro_center - nitro_width/2 - 0.012, y = nitro_y_lhh - nitro_height/2,
                  gp = grid::gpar(fontsize = 5, fontface = "bold", col = "white"))
  
  grid::grid.roundrect(x = nitro_center - nitro_width/2 - 0.012, y = nitro_y_rhh - nitro_height/2,
                       width = 0.020, height = 0.008,
                       r = unit(0.3, "snpc"), gp = grid::gpar(fill = "#1E88E5", col = NA))
  grid::grid.text("RHH", x = nitro_center - nitro_width/2 - 0.012, y = nitro_y_rhh - nitro_height/2,
                  gp = grid::gpar(fontsize = 5, fontface = "bold", col = "white"))
  
  for (side in c("Left", "Right")) {
    nitro_data <- pitch_df %>%
      filter(BatterSide == side, PitchCall == "InPlay", !is.na(ExitSpeed),
             !is.na(PlateLocSide), !is.na(PlateLocHeight))
    
    if (nrow(nitro_data) >= 8) {
      ev_90 <- quantile(nitro_data$ExitSpeed, 0.90, na.rm = TRUE)
      nitro_pts <- nitro_data %>% filter(ExitSpeed >= ev_90)
      
      y_pos <- if (side == "Left") nitro_y_lhh else nitro_y_rhh
      
      p <- ggplot(nitro_pts, aes(x = PlateLocSide, y = PlateLocHeight)) +
        annotate("rect", xmin = -0.83, xmax = 0.83, ymin = 1.5, ymax = 3.5, 
                 fill = "#FFF5F5", color = "black", linewidth = 0.5) +
        annotate("path", x = c(-0.708, 0.708, 0.708, 0, -0.708, -0.708),
                 y = c(0.15, 0.15, 0.3, 0.5, 0.3, 0.15), color = "black", linewidth = 0.4) +
        geom_point(aes(size = ExitSpeed), color = "#DC143C", alpha = 0.8) +
        scale_size_continuous(range = c(1.2, 3.5), guide = "none") +
        coord_fixed(xlim = c(-2, 2), ylim = c(0, 4.5)) +
        theme_void() + theme(plot.margin = margin(0,0,0,0))
      
      grid::pushViewport(grid::viewport(x = nitro_center, y = y_pos, 
                                        width = nitro_width, height = nitro_height, 
                                        just = c("center", "top")))
      tryCatch(print(p, newpage = FALSE), error = function(e) NULL)
      grid::popViewport()
    }
  }
  
  
  # Horizontal divider before charts
  grid::grid.lines(x = c(0.02, 0.98), y = c(hm_section_y - 0.185, hm_section_y - 0.185),
                   gp = grid::gpar(col = "#006F71", lwd = 1.5))
  
  
  # ===== CHARTS SECTION: Inning Row + Stacked Velo Charts =====
  charts_y <- hm_section_y - 0.20
  chart_width <- 0.45
  
  fb_pitches <- c("Fastball", "Sinker", "FourSeamFastBall", "TwoSeamFastBall", "Four-Seam", "Two-Seam")
  
  # ===== PITCH COUNT BY INNING ROW (Left, top) =====
  inning_row_plot <- tryCatch(
    create_pitcher_inning_row(data, pitcher_name),
    error = function(e) ggplot() + theme_void()
  )
  
  grid::pushViewport(grid::viewport(x = 0.27, y = charts_y, width = chart_width, height = 0.025, just = c("center", "top")))
  tryCatch(print(inning_row_plot, newpage = FALSE), error = function(e) NULL)
  grid::popViewport()
  
  # ===== PITCH USAGE BY INNING STACKED BAR (Left, below inning row) =====
  inning_data <- pitcher_df %>%
    dplyr::filter(!is.na(Inning), !is.na(TaggedPitchType), TaggedPitchType != "Other") %>%
    dplyr::mutate(Inning = ifelse(Inning > 9, "X", as.character(Inning))) %>%
    dplyr::group_by(Inning, TaggedPitchType) %>%
    dplyr::summarise(n = dplyr::n(), .groups = "drop") %>%
    dplyr::group_by(Inning) %>%
    dplyr::mutate(pct = 100 * n / sum(n)) %>%
    dplyr::ungroup()
  
  if (nrow(inning_data) > 0) {
    all_innings <- c("1", "2", "3", "4", "5", "6", "7", "8", "9", "X")
    inning_data$Inning <- factor(inning_data$Inning, levels = all_innings)
    
    inning_plot <- ggplot(inning_data, aes(x = Inning, y = pct, fill = TaggedPitchType)) +
      geom_col(position = "stack", width = 0.8) +
      scale_fill_manual(values = pitch_colors, name = NULL) +
      labs(x = NULL, y = "Usage %", title = "Pitch Usage by Inning") +
      scale_y_continuous(expand = expansion(mult = c(0, 0.02))) +
      theme_minimal() +
      theme(
        legend.position = "bottom",
        legend.key.size = unit(0.3, "cm"),
        legend.text = element_text(size = 5),
        plot.title = element_text(hjust = 0.5, face = "bold", size = 9, color = "#006F71"),
        axis.text = element_text(size = 6),
        axis.title.y = element_text(size = 6),
        panel.grid.minor = element_blank(),
        plot.margin = margin(2, 2, 2, 2)
      ) +
      guides(fill = guide_legend(nrow = 1))
    
    grid::pushViewport(grid::viewport(x = 0.27, y = charts_y - 0.028, width = chart_width, height = 0.065, just = c("center", "top")))
    tryCatch(print(inning_plot, newpage = FALSE), error = function(e) NULL)
    grid::popViewport()
  }
  
  # ===== FB VELO BY PITCH # IN GAME (Right, top) =====
  velo_by_pitch <- tryCatch(
    create_rolling_data_single(data, pitcher_name, "velo"),
    error = function(e) data.frame(pitch_num = integer(), value = numeric())
  )
  
  if (nrow(velo_by_pitch) > 0) {
    velo_pitch_plot <- ggplot(velo_by_pitch, aes(x = pitch_num, y = value)) +
      geom_line(color = "#006F71", linewidth = 1.2) +
      geom_point(color = "#006F71", size = 2) +
      geom_smooth(method = "loess", se = FALSE, color = "#E53935", linewidth = 0.8, linetype = "dashed", span = 0.75) +
      labs(x = "Pitch # in Game", y = "FB Velo (mph)", title = "FB Velo by Pitch Count") +
      scale_x_continuous(breaks = seq(0, 120, 20)) +
      theme_minimal() +
      theme(
        plot.title = element_text(hjust = 0.5, face = "bold", size = 9, color = "#006F71"),
        axis.text = element_text(size = 6),
        axis.title = element_text(size = 6),
        panel.grid.minor = element_blank(),
        plot.margin = margin(2, 2, 2, 2)
      )
    
    grid::pushViewport(grid::viewport(x = 0.73, y = charts_y, width = chart_width, height = 0.045, just = c("center", "top")))
    tryCatch(print(velo_pitch_plot, newpage = FALSE), error = function(e) NULL)
    grid::popViewport()
  }
  
  # ===== FB VELO BY MONTH (Right, bottom - stacked below pitch count velo) =====
  monthly_velo <- tryCatch(
    create_monthly_fb_velo(data, pitcher_name),
    error = function(e) data.frame(month_date = as.Date(character()), avg_velo = numeric())
  )
  
  if (nrow(monthly_velo) > 0) {
    monthly_velo_plot <- ggplot(monthly_velo, aes(x = month_date, y = avg_velo)) +
      geom_line(color = "#CD853F", linewidth = 1.2) +
      geom_point(color = "#CD853F", size = 2.5) +
      geom_text(aes(label = sprintf("%.1f", avg_velo)), vjust = -1, size = 2, fontface = "bold") +
      labs(x = NULL, y = "FB Velo (mph)", title = "Avg FB Velo by Month") +
      scale_x_date(date_labels = "%b", date_breaks = "1 month") +
      theme_minimal() +
      theme(
        plot.title = element_text(hjust = 0.5, face = "bold", size = 9, color = "#CD853F"),
        axis.text = element_text(size = 6),
        axis.title = element_text(size = 6),
        panel.grid.minor = element_blank(),
        plot.margin = margin(2, 2, 2, 2)
      )
    
    grid::pushViewport(grid::viewport(x = 0.73, y = charts_y - 0.048, width = chart_width, height = 0.045, just = c("center", "top")))
    tryCatch(print(monthly_velo_plot, newpage = FALSE), error = function(e) NULL)
    grid::popViewport()
  }
  
  # ===== MATCHUP MATRIX (if provided) =====
  if (!is.null(matchup_matrix) && !is.null(matchup_matrix$data) && nrow(matchup_matrix$data) > 0) {
    # Start new page for matchup matrix
    grid::grid.newpage()
    
    # Header
    grid::grid.rect(x = 0.5, y = 0.97, width = 1, height = 0.04,
                    gp = grid::gpar(fill = "#006F71", col = NA))
    grid::grid.text(paste0("Hitter Matchup Analysis: ", pitcher_name), x = 0.5, y = 0.97,
                    gp = grid::gpar(fontsize = 16, fontface = "bold", col = "white"))
    
    # Draw matrix table
    df <- matchup_matrix$data
    pitch_types <- matchup_matrix$pitch_types
    
    # Add notes if available
    if (!is.null(matchup_matrix$notes)) {
      for (h_name in names(matchup_matrix$notes)) {
        if (h_name %in% df$Hitter) {
          df$Notes[df$Hitter == h_name] <- matchup_matrix$notes[[h_name]]
        }
      }
    }
    
    # Table layout
    n_rows <- nrow(df)
    n_cols <- 4 + length(pitch_types) + 1  # Hitter, Hand, BA, SLG, pitch types, Notes
    
    table_top <- 0.92
    row_height <- min(0.025, 0.6 / (n_rows + 1))  # Header + data rows
    col_width <- 0.9 / n_cols
    start_x <- 0.05
    
    # Column headers
    headers <- c("Hitter", "H", "BA", "SLG", pitch_types, "Notes")
    for (j in seq_along(headers)) {
      x_pos <- start_x + (j - 0.5) * col_width
      grid::grid.rect(x = x_pos, y = table_top, width = col_width * 0.95, height = row_height,
                      gp = grid::gpar(fill = "#006F71", col = "white"))
      grid::grid.text(headers[j], x = x_pos, y = table_top,
                      gp = grid::gpar(fontsize = 8, fontface = "bold", col = "white"))
    }
    
    # Data rows
    for (i in 1:n_rows) {
      y_pos <- table_top - i * row_height
      row_bg <- if (i %% 2 == 0) "#f5f5f5" else "white"
      
      # Get row data
      hitter <- df$Hitter[i]
      hand <- df$Hand[i]
      ba <- if ("BA" %in% names(df)) df$BA[i] else "-"
      slg <- if ("SLG" %in% names(df)) df$SLG[i] else "-"
      notes <- if ("Notes" %in% names(df)) df$Notes[i] else ""
      
      row_values <- c(hitter, hand, ba, slg)
      for (pt in pitch_types) {
        rv_val <- if (pt %in% names(df)) df[[pt]][i] else "-"
        row_values <- c(row_values, rv_val)
      }
      row_values <- c(row_values, notes)
      
      for (j in seq_along(row_values)) {
        x_pos <- start_x + (j - 0.5) * col_width
        
        # Color coding for RV/100 columns
        cell_bg <- row_bg
        if (j > 4 && j <= (4 + length(pitch_types))) {
          val <- row_values[j]
          if (!is.na(val) && val != "-") {
            if (grepl("^\\+", val)) cell_bg <- "#D9EF8B"  # Positive = hitter advantage
            else if (grepl("^-", val)) cell_bg <- "#FDAE61"  # Negative = pitcher advantage
          }
        }
        
        grid::grid.rect(x = x_pos, y = y_pos, width = col_width * 0.95, height = row_height,
                        gp = grid::gpar(fill = cell_bg, col = "#ddd"))
        
        # Truncate long text
        display_text <- if (nchar(row_values[j]) > 20) paste0(substr(row_values[j], 1, 18), "...") else row_values[j]
        grid::grid.text(display_text, x = x_pos, y = y_pos,
                        gp = grid::gpar(fontsize = 7))
      }
    }
    
    # Legend
    grid::grid.text("RV/100: Green = Hitter Advantage | Orange = Pitcher Advantage | Based on similar pitches (velo/movement/spin)",
                    x = 0.5, y = table_top - (n_rows + 1.5) * row_height,
                    gp = grid::gpar(fontsize = 7, col = "gray50"))
  }
  
  # ===== FOOTER =====
  grid::grid.text("Data: TrackMan | Coastal Carolina Baseball", x = 0.5, y = 0.01,
                  gp = grid::gpar(fontsize = 8, col = "gray50"))
  
  invisible(output_file)
}

get_team_info <- function(team_name_input) {
  if (is.null(team_name_input) || team_name_input == "" || nrow(teams_data) == 0) {
    return(list(
      trackman_abbr = "",
      team_name = "",
      team_logo = "",
      league = "",
      primary_color = "#006F71",
      secondary_color = "#A27752",
      conference_logo = ""
    ))
  }
  row <- teams_data %>% dplyr::filter(team_name == team_name_input)
  if (nrow(row) == 0) {
    return(list(
      trackman_abbr = "",
      team_name = team_name_input,
      team_logo = "",
      league = "",
      primary_color = "#006F71",
      secondary_color = "#A27752",
      conference_logo = ""
    ))
  }
  list(
    trackman_abbr = row$trackman_abbr[1],
    team_name = row$team_name[1],
    team_logo = ifelse(is.na(row$team_logo[1]), "", row$team_logo[1]),
    league = ifelse(is.na(row$league[1]), "", row$league[1]),
    primary_color = ifelse(is.na(row$primary_color[1]), "#006F71", row$primary_color[1]),
    secondary_color = ifelse(is.na(row$secondary_color[1]), "#A27752", row$secondary_color[1]),
    conference_logo = ifelse(is.na(row$conference_logo[1]), "", row$conference_logo[1])
  )
}

create_condensed_pitcher_report <- function(data, pitcher_names, output_file,
                                            report_title = "Opposing Pitchers Report",
                                            pitcher_notes = list(),
                                            team_info = NULL) {
  if (length(pitcher_names) == 0) return(NULL)
  
  # ---- Extract team theming ----
  if (is.null(team_info)) {
    team_info <- list(
      team_name = "",
      team_logo = "",
      league = "",
      primary_color = "#006F71",
      secondary_color = "#A27752",
      conference_logo = "",
      record = ""
    )
  }
  
  # Team colors for theming
  tc_primary <- team_info$primary_color
  tc_secondary <- team_info$secondary_color
  
  # Validate hex colors
  is_valid_hex <- function(col) {
    grepl("^#[0-9A-Fa-f]{6}$", col)
  }
  if (!is_valid_hex(tc_primary)) tc_primary <- "#006F71"
  if (!is_valid_hex(tc_secondary)) tc_secondary <- "#A27752"
  
  # ---- Helper: gradient color (red-white-green) ----
  get_pill_color <- function(value, benchmark, higher_is_better = TRUE, range_pct = 0.25) {
    if (is.na(value) || is.na(benchmark)) return("#CCCCCC")
    range_val <- benchmark * range_pct
    min_val   <- benchmark - range_val
    max_val   <- benchmark + range_val
    normalized <- if (higher_is_better) {
      (value - min_val) / (max_val - min_val)
    } else {
      (max_val - value) / (max_val - min_val)
    }
    normalized <- pmax(0, pmin(1, normalized))
    scales::gradient_n_pal(c("#E1463E", "#FFFFFF", "#00840D"))(normalized)
  }
  
  # ---- Helper: mini pie chart ----
  create_mini_pie <- function(pitch_data) {
    if (is.null(pitch_data) || nrow(pitch_data) == 0) return(ggplot() + theme_void())
    pie_df <- pitch_data %>%
      dplyr::count(TaggedPitchType, name = "n") %>%
      dplyr::mutate(pct = 100 * n / sum(n)) %>%
      dplyr::filter(pct >= 3) %>%
      dplyr::arrange(dplyr::desc(pct)) %>%
      dplyr::mutate(pct_label = ifelse(pct >= 8, paste0(round(pct), "%"), ""))
    if (nrow(pie_df) == 0) return(ggplot() + theme_void())
    ggplot(pie_df, aes(x = "", y = pct, fill = TaggedPitchType)) +
      geom_bar(width = 1, stat = "identity", color = "white", linewidth = 0.15) +
      geom_text(aes(label = pct_label), position = position_stack(vjust = 0.5),
                size = 1.1, fontface = "bold") +
      coord_polar("y", start = 0) +
      scale_fill_manual(values = pitch_colors, drop = FALSE) +
      theme_void() + theme(legend.position = "none", plot.margin = margin(0,0,0,0))
  }
  
  # ---- Helper: condensed movement chart ----
  create_mini_movement <- function(data, pitcher_name, expected_grid = NULL) {
    pitcher_data <- data %>%
      dplyr::filter(Pitcher == pitcher_name,
                    !is.na(HorzBreak), !is.na(InducedVertBreak),
                    !is.na(TaggedPitchType), TaggedPitchType != "Other",
                    !is.na(RelSpeed)) %>%
      dplyr::mutate(
        RelSide = as.numeric(RelSide),
        RelHeight = as.numeric(RelHeight),
        HorzBreak = as.numeric(HorzBreak),
        InducedVertBreak = as.numeric(InducedVertBreak),
        RelSpeed = as.numeric(RelSpeed)
      )
    if (nrow(pitcher_data) < 5) {
      return(ggplot() + theme_void() + annotate("text", x=0, y=0, label="Low n", size=2))
    }
    pitcher_throws <- pitcher_data$PitcherThrows[1]
    if (is.na(pitcher_throws)) pitcher_throws <- "Right"
    is_lefty <- pitcher_throws == "Left"
    h_in <- if ("height_inches" %in% names(pitcher_data)) {
      med_h <- median(pitcher_data$height_inches, na.rm = TRUE)
      if (is.na(med_h)) 72 else med_h
    } else 72
    shoulder_pos <- h_in * 0.70
    
    p_mean <- pitcher_data %>%
      dplyr::group_by(TaggedPitchType) %>%
      dplyr::summarize(
        HorzBreak = mean(HorzBreak, na.rm=TRUE),
        InducedVertBreak = mean(InducedVertBreak, na.rm=TRUE),
        mean_velo = round(mean(RelSpeed, na.rm=TRUE), 1),
        mean_rel_height = mean(RelHeight, na.rm=TRUE),
        mean_rel_side = mean(RelSide, na.rm=TRUE),
        usage = dplyr::n(), .groups = "drop"
      ) %>%
      dplyr::mutate(
        scaled_usage = pmin((usage - min(usage)) / max((max(usage) - min(usage)), 1) * (5 - 3) + 3, 6),
        RH_bin = round(mean_rel_height / 0.10) * 0.10
      ) %>%
      dplyr::filter(usage >= 3)
    
    # Expected movement
    p_mean$exp_hb <- NA_real_; p_mean$exp_ivb <- NA_real_; p_mean$has_expected <- FALSE
    if (!is.null(expected_grid) && nrow(expected_grid) > 0) {
      for (i in seq_len(nrow(p_mean))) {
        match_row <- expected_grid %>%
          dplyr::filter(TaggedPitchType == p_mean$TaggedPitchType[i], abs(RH_bin - p_mean$RH_bin[i]) < 0.15)
        if (nrow(match_row) > 0) {
          match_row <- match_row %>% dplyr::mutate(dist = abs(RH_bin - p_mean$RH_bin[i])) %>%
            dplyr::arrange(dist) %>% dplyr::slice(1)
          p_mean$exp_hb[i]  <- if (is_lefty) -match_row$exp_hb[1] else match_row$exp_hb[1]
          p_mean$exp_ivb[i] <- match_row$exp_ivb[1]
          p_mean$has_expected[i] <- TRUE
        }
      }
    }
    
    arm_angle_savant <- median(pitcher_data$arm_angle_savant, na.rm = TRUE)
    if (is.na(arm_angle_savant)) arm_angle_savant <- 45
    arm_angle_type <- if (arm_angle_savant >= 60) "OH"
    else if (arm_angle_savant >= 47) "H3/4"
    else if (arm_angle_savant >= 40) "3/4"
    else if (arm_angle_savant >= 10) "L3/4"
    else "Side"
    
    # Arm angle rays
    ray_length <- 14
    arm_rays <- p_mean %>%
      dplyr::mutate(
        rel_x_raw = ifelse(is_lefty, -abs(mean_rel_side), abs(mean_rel_side)),
        rel_y_raw = mean_rel_height - (shoulder_pos / 12),
        rel_mag = pmax(sqrt(rel_x_raw^2 + rel_y_raw^2), 0.01),
        dir_x = rel_x_raw / rel_mag, dir_y = rel_y_raw / rel_mag,
        ray_xs = 0, ray_ys = 0,
        ray_xe = dir_x * ray_length, ray_ye = dir_y * ray_length
      )
    
    circle_df <- data.frame(x = 28*cos(seq(0, 2*base::pi, length.out=100)),
                            y = 28*sin(seq(0, 2*base::pi, length.out=100)))
    
    p <- ggplot(pitcher_data, aes(x = HorzBreak, y = InducedVertBreak)) +
      geom_polygon(data=circle_df, aes(x=x, y=y), fill="#e5f3f3", color="#e5f3f3", inherit.aes=FALSE) +
      geom_path(data=data.frame(x=12*cos(seq(0, 2*base::pi, length.out=100)),
                                y=12*sin(seq(0, 2*base::pi, length.out=100))),
                aes(x=x,y=y), linetype="dashed", color="gray70", linewidth=0.15, inherit.aes=FALSE) +
      geom_path(data=data.frame(x=24*cos(seq(0, 2*base::pi, length.out=100)),
                                y=24*sin(seq(0, 2*base::pi, length.out=100))),
                aes(x=x,y=y), linetype="dashed", color="gray70", linewidth=0.15, inherit.aes=FALSE) +
      geom_segment(x=0, y=-30, xend=0, yend=30, linewidth=0.2, color="grey60") +
      geom_segment(x=-30, y=0, xend=30, yend=0, linewidth=0.2, color="grey60") +
      annotate('text', x=0, y=31, label='12', size=1.8, fontface="bold") +
      annotate('text', x=31, y=0, label='3', size=1.8, fontface="bold") +
      annotate('text', x=0, y=-31, label='6', size=1.8, fontface="bold") +
      annotate('text', x=-31, y=0, label='9', size=1.8, fontface="bold") +
      annotate('text', x=12, y=-1.5, label='12"', size=1.2, color="gray50") +
      annotate('text', x=24, y=-1.5, label='24"', size=1.2, color="gray50")
    
    if (nrow(arm_rays) > 0) {
      p <- p +
        geom_segment(data=arm_rays, aes(x=ray_xs,y=ray_ys,xend=ray_xe,yend=ray_ye,color=TaggedPitchType),
                     linewidth=0.8, alpha=0.5, inherit.aes=FALSE) +
        geom_point(data=arm_rays, aes(x=ray_xe,y=ray_ye,fill=TaggedPitchType),
                   shape=21, size=0.8, stroke=0.15, color="black", alpha=0.6, inherit.aes=FALSE)
    }
    
    p <- p + geom_point(aes(fill=TaggedPitchType), shape=21, size=0.8, color="black", stroke=0.1, alpha=0.6)
    
    exp_data <- p_mean %>% dplyr::filter(has_expected == TRUE)
    if (nrow(exp_data) > 0) {
      p <- p + geom_point(data=exp_data, aes(x=exp_hb, y=exp_ivb, fill=TaggedPitchType),
                          shape=23, size=2.5, stroke=0.7, color="black", alpha=0.6, inherit.aes=FALSE)
    }
    
    p <- p +
      geom_point(data=p_mean, aes(x=HorzBreak, y=InducedVertBreak, fill=TaggedPitchType, size=scaled_usage),
                 shape=21, color="black", stroke=0.8, alpha=0.85, inherit.aes=FALSE) +
      geom_label(data=p_mean, aes(x=HorzBreak, y=InducedVertBreak, label=mean_velo),
                 color="black", size=1.2, fontface="bold", fill="white",
                 linewidth=0.1, label.padding=unit(0.06, "lines"), inherit.aes=FALSE) +
      scale_size_identity()
    
    p <- p +
      coord_fixed(xlim=c(-34, 34), ylim=c(-34, 34), clip="on") +
      scale_fill_manual(values=pitch_colors, drop=FALSE) +
      scale_color_manual(values=pitch_colors, drop=FALSE) +
      annotate("text", x=0, y=37, label=paste0(round(arm_angle_savant,0), "\u00b0 ", arm_angle_type),
               size=1.8, color=tc_primary, fontface="bold") +
      theme_void() +
      theme(plot.background=element_rect(fill="white", color=NA),
            legend.position="none", plot.margin=margin(0,0,0,0))
    return(p)
  }
  
  # ---- Helper: mini heatmap ----
  create_mini_heatmap <- function(data, min_pitches = 5) {
    base_plot <- ggplot() +
      annotate("rect", xmin=-0.83, xmax=0.83, ymin=1.5, ymax=3.5, fill=NA, color="black", linewidth=0.3) +
      annotate("path", x=c(-0.708,0.708,0.708,0,-0.708,-0.708),
               y=c(0.15,0.15,0.3,0.5,0.3,0.15), color="black", linewidth=0.25) +
      coord_fixed(xlim=c(-2,2), ylim=c(0,4.5)) +
      theme_void() + theme(legend.position="none", plot.margin=margin(0,0,0,0))
    if (is.null(data) || nrow(data) < min_pitches) return(base_plot)
    plot_data <- data %>% dplyr::filter(!is.na(PlateLocSide), !is.na(PlateLocHeight))
    if (nrow(plot_data) < min_pitches) return(base_plot)
    if (nrow(plot_data) < 15) {
      return(base_plot + geom_point(data=plot_data, aes(x=PlateLocSide, y=PlateLocHeight),
                                    color=tc_primary, alpha=0.7, size=0.6))
    }
    ggplot(plot_data, aes(x=PlateLocSide, y=PlateLocHeight)) +
      stat_density_2d(aes(fill=after_stat(density)), geom="raster", contour=FALSE, n=80) +
      scale_fill_gradientn(colours=c("white","#0551bc","#02fbff","#03ff00","#fbff00", "#ffa503","#ff1f02","#dc1100"), guide="none") +
      annotate("rect", xmin=-0.83, xmax=0.83, ymin=1.5, ymax=3.5, fill=NA, color="black", linewidth=0.3) +
      annotate("path", x=c(-0.708,0.708,0.708,0,-0.708,-0.708),
               y=c(0.15,0.15,0.3,0.5,0.3,0.15), color="black", linewidth=0.25) +
      coord_fixed(xlim=c(-2,2), ylim=c(0,4.5)) +
      theme_void() + theme(legend.position="none", plot.margin=margin(0,0,0,0))
  }
  
  # ---- Helper: mini whiff heatmap (new) ----
  create_mini_whiff_heatmap <- function(data, side, min_pitches = 5) {
    whiff_data <- data %>%
      dplyr::filter(
        BatterSide == side,
        PitchCall == "StrikeSwinging",
        !is.na(PlateLocSide),
        !is.na(PlateLocHeight)
      )
    create_mini_heatmap(whiff_data, min_pitches)
  }
  
  # ---- Helper: mini nitro zone plot ----
  create_mini_nitro <- function(pitch_data, side) {
    nitro_data <- pitch_data %>%
      dplyr::filter(
        BatterSide == side,
        PitchCall == "InPlay",
        !is.na(ExitSpeed),
        !is.na(PlateLocSide),
        !is.na(PlateLocHeight)
      )
    
    base_plot <- ggplot() +
      annotate("rect", xmin=-0.83, xmax=0.83, ymin=1.5, ymax=3.5, fill="#FFF5F5", color="black", linewidth=0.3) +
      annotate("path", x=c(-0.708,0.708,0.708,0,-0.708,-0.708),
               y=c(0.15,0.15,0.3,0.5,0.3,0.15), color="black", linewidth=0.25) +
      coord_fixed(xlim=c(-2,2), ylim=c(0,4.5)) +
      theme_void() + theme(legend.position="none", plot.margin=margin(0,0,0,0))
    
    if (nrow(nitro_data) < 8) return(base_plot)
    
    ev_90 <- quantile(nitro_data$ExitSpeed, 0.90, na.rm = TRUE)
    nitro_pts <- nitro_data %>% dplyr::filter(ExitSpeed >= ev_90)
    
    if (nrow(nitro_pts) < 2) return(base_plot)
    
    base_plot +
      geom_point(data = nitro_pts, aes(x = PlateLocSide, y = PlateLocHeight, size = ExitSpeed),
                 color = "#DC143C", alpha = 0.8) +
      scale_size_continuous(range = c(0.8, 2.5), guide = "none")
  }
  
  # ---- Helper: pitch abbreviation ----
  get_pt_short <- function(pt) {
    dplyr::case_when(
      pt %in% c("Fastball","Four-Seam","FourSeamFastBall") ~ "FB",
      pt %in% c("Sinker","TwoSeamFastBall","Two-Seam") ~ "SI",
      pt %in% c("Slider","Sweeper") ~ "SL",
      pt == "Curveball" ~ "CB",
      pt %in% c("Changeup","ChangeUp") ~ "CH",
      pt == "Splitter" ~ "SP",
      pt == "Cutter" ~ "CT",
      pt == "Slurve" ~ "SV",
      pt == "Knuckle Curve" ~ "KC",
      TRUE ~ "Ot"
    )
  }
  
  fb_pitches <- c("Fastball","Sinker","FourSeamFastBall","TwoSeamFastBall","Four-Seam","Two-Seam")
  bb_pitches <- c("Slider","Curveball","Cutter","Sweeper","Slurve","Knuckle Curve")
  os_pitches <- c("ChangeUp","Changeup","Splitter")
  
  expected_grid <- tryCatch(build_expected_movement_grid(data), error=function(e) NULL)
  
  # ---- Helper: resolve a URL to a downloadable image URL ----
  # Handles Wikipedia Commons "File:" page URLs by converting to Special:FilePath
  resolve_image_url <- function(url) {
    if (is.null(url) || is.na(url) || nchar(url) == 0) return("")
    
    # If it's a commons.wikimedia.org/wiki/File: URL, convert to Special:FilePath
    if (grepl("commons\\.wikimedia\\.org/wiki/File:", url)) {
      # Extract filename from URL like: https://commons.wikimedia.org/wiki/File:Big_Ten_Conference_logo.svg
      filename <- sub(".*wiki/File:", "", url)
      filename <- utils::URLdecode(filename)
      # Use Special:FilePath which redirects to the actual image
      # Add width parameter to get a PNG thumbnail (works even for SVGs)
      resolved <- paste0("https://commons.wikimedia.org/wiki/Special:FilePath/", 
                         utils::URLencode(filename), "?width=200")
      return(resolved)
    }
    
    # If it's already a direct upload.wikimedia.org URL, use as-is
    return(url)
  }
  
  # ---- Helper: download an image URL to a raster for grid rendering ----
  download_logo_raster <- function(url, label = "logo") {
    if (is.null(url) || nchar(url) == 0) return(NULL)
    
    resolved_url <- resolve_image_url(url)
    if (nchar(resolved_url) == 0) return(NULL)
    
    tryCatch({
      tmp_file <- tempfile(fileext = ".png")
      # Follow redirects (important for Special:FilePath)
      resp <- httr::GET(resolved_url, httr::timeout(8), httr::config(followlocation = TRUE))
      if (httr::status_code(resp) == 200) {
        content_type <- httr::headers(resp)[["content-type"]]
        raw_content <- httr::content(resp, "raw")
        writeBin(raw_content, tmp_file)
        
        # Try reading as PNG first
        raster <- tryCatch(png::readPNG(tmp_file), error = function(e) NULL)
        if (!is.null(raster)) return(raster)
        
        # If PNG failed, try JPEG
        if (requireNamespace("jpeg", quietly = TRUE)) {
          raster <- tryCatch(jpeg::readJPEG(tmp_file), error = function(e) NULL)
          if (!is.null(raster)) return(raster)
        }
        
        cat("Could not decode ", label, " image (content-type: ", content_type, ")\n")
      } else {
        cat("Failed to download ", label, " (status ", httr::status_code(resp), ")\n")
      }
      NULL
    }, error = function(e) {
      cat("Error downloading ", label, ": ", e$message, "\n")
      NULL
    })
  }
  
  # ---- Download team logo and conference logo ----
  team_logo_raster <- download_logo_raster(team_info$team_logo, "team logo")
  conf_logo_raster <- download_logo_raster(team_info$conference_logo, "conference logo")
  
  # ============================================================================
  # PORTRAIT MODE: 11 x 17 (tabloid portrait)
  # ============================================================================
  pdf(output_file, width = 11, height = 17)
  on.exit(try(dev.off(), silent = TRUE), add = TRUE)
  
  n_pitchers <- length(pitcher_names)
  pitchers_page1 <- 4
  pitchers_later  <- 5
  
  if (n_pitchers <= pitchers_page1) {
    n_pages <- 1
  } else {
    n_pages <- 1 + ceiling((n_pitchers - pitchers_page1) / pitchers_later)
  }
  
  # Safety: ensure we never skip pitchers
  pitchers_rendered <- 0
  
  for (page_num in 1:n_pages) {
    grid::grid.newpage()
    
    if (page_num == 1) {
      start_idx <- 1
      end_idx   <- min(pitchers_page1, n_pitchers)
    } else {
      start_idx <- pitchers_page1 + (page_num - 2) * pitchers_later + 1
      end_idx   <- min(start_idx + pitchers_later - 1, n_pitchers)
    }
    
    # Safety: skip if start_idx somehow exceeds total
    if (start_idx > n_pitchers) next
    end_idx <- min(end_idx, n_pitchers)
    
    page_pitchers <- pitcher_names[start_idx:end_idx]
    n_on_page <- length(page_pitchers)
    pitchers_rendered <- pitchers_rendered + n_on_page
    
    # ===== PAGE HEADER - TEAM BRANDED =====
    header_h <- 0.028
    # Primary color header bar
    grid::grid.rect(x=0.5, y=1 - header_h/2, width=1, height=header_h,
                    gp=grid::gpar(fill=tc_primary, col=NA))
    # Secondary color accent stripe at bottom of header
    grid::grid.rect(x=0.5, y=1 - header_h - 0.001, width=1, height=0.003,
                    gp=grid::gpar(fill=tc_secondary, col=NA))
    
    # Team logo - LEFT CORNER of header (bigger and more visible)
    logo_x_offset <- 0.040
    if (!is.null(team_logo_raster)) {
      tryCatch({
        grid::grid.raster(team_logo_raster,
                          x = logo_x_offset, y = 1 - header_h/2,
                          width = unit(0.035, "npc"), height = unit(header_h * 0.90, "npc"),
                          just = c("center", "center"))
        logo_x_offset <- 0.065  # shift conference logo to the right of team logo
      }, error = function(e) NULL)
    }
    
    # Conference logo - TOP LEFT, next to team logo
    if (!is.null(conf_logo_raster)) {
      tryCatch({
        grid::grid.raster(conf_logo_raster,
                          x = logo_x_offset + 0.022, y = 1 - header_h/2,
                          width = unit(0.025, "npc"), height = unit(header_h * 0.75, "npc"),
                          just = c("center", "center"))
      }, error = function(e) NULL)
    }
    
    # Title text - centered
    title_text <- if (nchar(team_info$team_name) > 0) {
      paste0(team_info$team_name, " - Opposing Pitcher Report")
    } else {
      report_title
    }
    grid::grid.text(title_text, x=0.5, y=1 - header_h * 0.35,
                    gp=grid::gpar(fontsize=11, fontface="bold", col="white"))
    
    # Record + conference subtitle text (centered)
    subtitle_parts <- c()
    if (nchar(team_info$record) > 0) subtitle_parts <- c(subtitle_parts, team_info$record)
    if (nchar(team_info$league) > 0) subtitle_parts <- c(subtitle_parts, team_info$league)
    subtitle_text <- paste(subtitle_parts, collapse = " | ")
    
    if (length(subtitle_parts) > 0) {
      grid::grid.text(subtitle_text, x=0.5, y=1 - header_h * 0.72,
                      gp=grid::gpar(fontsize=7, col="white"))
    }
    
    # Date + page number (right side)
    grid::grid.text(format(Sys.Date(), "%B %d, %Y"), x=0.92, y=1 - header_h * 0.35, just="right",
                    gp=grid::gpar(fontsize=6, col="white"))
    grid::grid.text(paste0("Page ", page_num, " of ", n_pages), x=0.92, y=1 - header_h * 0.72, just="right",
                    gp=grid::gpar(fontsize=5, col="white"))
    
    # ===== TOP CHARTS (Page 1 only) =====
    charts_bottom <- 1 - header_h - 0.004
    
    if (page_num == 1) {
      chart_section_height <- 0.22
      chart_top <- charts_bottom - 0.002
      chart_center_y <- chart_top - chart_section_height / 2
      
      # --- LEFT: Pitch Count Bar Chart ---
      as_of_date <- Sys.Date()
      usage_data <- data %>%
        dplyr::filter(Pitcher %in% pitcher_names) %>%
        dplyr::mutate(Date = as.Date(Date)) %>%
        dplyr::filter(Date <= as_of_date) %>%
        dplyr::group_by(Pitcher, Date) %>%
        dplyr::summarise(pitches = dplyr::n(), .groups="drop") %>%
        dplyr::group_by(Pitcher) %>%
        dplyr::summarise(
          last_1_week = sum(pitches[Date > (as_of_date - 7)], na.rm=TRUE),
          last_2_weeks = sum(pitches[Date > (as_of_date - 14)], na.rm=TRUE),
          .groups="drop"
        ) %>%
        tidyr::pivot_longer(cols=c(last_1_week, last_2_weeks), names_to="period", values_to="pitches")
      
      if (nrow(usage_data) > 0) {
        pitcher_order <- usage_data %>% dplyr::filter(period=="last_2_weeks") %>%
          dplyr::arrange(dplyr::desc(pitches)) %>% dplyr::pull(Pitcher)
        usage_data$Pitcher <- factor(usage_data$Pitcher, levels=rev(pitcher_order))
        usage_data$period <- factor(usage_data$period, levels=c("last_1_week","last_2_weeks"),
                                    labels=c("Last 1 Week","Last 2 Weeks"))
        usage_plot <- ggplot(usage_data, aes(x=pitches, y=Pitcher, fill=period)) +
          geom_col(position=position_dodge(width=0.8), width=0.7) +
          geom_text(aes(label=ifelse(pitches>0, pitches, "")),
                    position=position_dodge(width=0.8), hjust=-0.2, size=1.8, fontface="bold") +
          scale_fill_manual(values=c("Last 1 Week"=tc_primary, "Last 2 Weeks"=tc_secondary)) +
          labs(x="Pitches", y=NULL, fill=NULL) +
          theme_minimal() +
          theme(legend.position="top", legend.key.size=unit(0.25,"cm"), legend.text=element_text(size=5),
                axis.text.y=element_text(size=5, face="bold"), axis.text.x=element_text(size=4.5),
                panel.grid.major.y=element_blank(), plot.margin=margin(2,6,2,2)) +
          scale_x_continuous(expand=expansion(mult=c(0, 0.20)))
        grid::pushViewport(grid::viewport(x=0.25, y=chart_center_y, width=0.46, height=chart_section_height,
                                          just=c("center","center")))
        tryCatch(print(usage_plot, newpage=FALSE), error=function(e) NULL)
        grid::popViewport()
      }
      
      # --- RIGHT: Usage by Inning Heatmap ---
      inning_data <- data %>%
        dplyr::filter(Pitcher %in% pitcher_names, !is.na(Inning),
                      !is.na(TaggedPitchType), TaggedPitchType != "Other") %>%
        dplyr::mutate(Inning = ifelse(Inning > 9, "X", as.character(Inning))) %>%
        dplyr::group_by(Pitcher, Inning) %>%
        dplyr::summarise(n=dplyr::n(), .groups="drop")
      
      if (nrow(inning_data) > 0) {
        all_innings <- c("1","2","3","4","5","6","7","8","9","X")
        complete_grid <- expand.grid(Pitcher=pitcher_names, Inning=all_innings, stringsAsFactors=FALSE)
        inning_data <- complete_grid %>%
          dplyr::left_join(inning_data, by=c("Pitcher","Inning")) %>%
          dplyr::mutate(n = ifelse(is.na(n), 0, n))
        inning_data$Inning <- factor(inning_data$Inning, levels=all_innings)
        inning_data$Pitcher <- factor(inning_data$Pitcher, levels=rev(pitcher_names))
        
        inning_plot <- ggplot(inning_data, aes(x=Inning, y=Pitcher, fill=n)) +
          geom_tile(color="white", linewidth=0.3) +
          geom_text(aes(label=ifelse(n>0, n, "")), size=1.8, fontface="bold") +
          scale_fill_gradient2(low="red", mid="white", high="#00840D",
                               midpoint=max(inning_data$n[inning_data$n>0], na.rm=TRUE)/2, guide="none") +
          scale_x_discrete(position="top") +
          labs(x=NULL, y=NULL) +
          theme_minimal() +
          theme(axis.text.x=element_text(size=5, face="bold"), axis.text.y=element_text(size=4.5),
                panel.grid=element_blank(), plot.margin=margin(2,2,2,2))
        grid::pushViewport(grid::viewport(x=0.75, y=chart_center_y, width=0.46, height=chart_section_height,
                                          just=c("center","center")))
        tryCatch(print(inning_plot, newpage=FALSE), error=function(e) NULL)
        grid::popViewport()
      }
      
      charts_bottom <- chart_top - chart_section_height - 0.002
    }
    
    # ===== COLUMN HEADERS ROW - TEAM COLORED =====
    col_header_y <- charts_bottom - 0.001
    col_header_h <- 0.012
    grid::grid.rect(x=0.5, y=col_header_y, width=0.98, height=col_header_h,
                    gp=grid::gpar(fill=tc_secondary, col=NA), just=c("center","top"))
    hf <- grid::gpar(fontsize=5, fontface="bold", col="white")
    grid::grid.text("#/Cl",         x=0.02,  y=col_header_y - col_header_h/2, just="left", gp=hf)
    grid::grid.text("Pitcher Name", x=0.065, y=col_header_y - col_header_h/2, just="left", gp=hf)
    grid::grid.text("RA9",   x=0.165, y=col_header_y - col_header_h/2, gp=hf)
    grid::grid.text("IP",    x=0.205, y=col_header_y - col_header_h/2, gp=hf)
    grid::grid.text("FIP",   x=0.245, y=col_header_y - col_header_h/2, gp=hf)
    grid::grid.text("K%",    x=0.285, y=col_header_y - col_header_h/2, gp=hf)
    grid::grid.text("BB%",   x=0.325, y=col_header_y - col_header_h/2, gp=hf)
    grid::grid.text("Stuff+",x=0.365, y=col_header_y - col_header_h/2, gp=hf)
    grid::grid.text("Movement", x=0.46, y=col_header_y - col_header_h/2, gp=hf)
    
    # Right section sub-headers
    pie_header_gp <- grid::gpar(fontsize=4, fontface="bold", col="white")
    grid::grid.text("Overall", x=0.555, y=col_header_y - col_header_h/2, gp=pie_header_gp)
    grid::grid.text("1st",     x=0.595, y=col_header_y - col_header_h/2, gp=pie_header_gp)
    grid::grid.text("2K",      x=0.635, y=col_header_y - col_header_h/2, gp=pie_header_gp)
    
    # Heatmap headers
    hm_header_x <- c(0.680, 0.725, 0.770)
    hm_pill_colors <- c("#3465cb","#65aa02","#980099")
    hm_pill_labels <- c("FB","BB","OS")
    for (ci in 1:3) {
      grid::grid.roundrect(x=hm_header_x[ci], y=col_header_y - col_header_h/2, width=0.026, height=col_header_h*0.7,
                           r=unit(0.3,"snpc"), gp=grid::gpar(fill=hm_pill_colors[ci], col=NA))
      grid::grid.text(hm_pill_labels[ci], x=hm_header_x[ci], y=col_header_y - col_header_h/2,
                      gp=grid::gpar(fontsize=3.5, fontface="bold", col="white"))
    }
    
    # Whiff header
    grid::grid.roundrect(x=0.825, y=col_header_y - col_header_h/2, width=0.040, height=col_header_h*0.7,
                         r=unit(0.3,"snpc"), gp=grid::gpar(fill="#FF6600", col=NA))
    grid::grid.text("Whiff", x=0.825, y=col_header_y - col_header_h/2,
                    gp=grid::gpar(fontsize=3.5, fontface="bold", col="white"))
    
    # Nitro Zones header
    grid::grid.roundrect(x=0.885, y=col_header_y - col_header_h/2, width=0.040, height=col_header_h*0.7,
                         r=unit(0.3,"snpc"), gp=grid::gpar(fill="#DC143C", col=NA))
    grid::grid.text("Nitro", x=0.885, y=col_header_y - col_header_h/2,
                    gp=grid::gpar(fontsize=3.5, fontface="bold", col="white"))
    
    
    # ===== PITCHER BLOCKS =====
    footer_h <- 0.005
    available_top <- col_header_y - col_header_h
    available_bottom <- footer_h + 0.003
    available_height <- available_top - available_bottom
    max_pitchers_this_page <- if (page_num == 1) pitchers_page1 else pitchers_later
    block_height <- available_height / max_pitchers_this_page
    
    current_y <- available_top
    
    for (p_idx in seq_along(page_pitchers)) {
      pitcher_name <- page_pitchers[p_idx]
      p_data <- data %>% dplyr::filter(Pitcher == pitcher_name) %>% process_pitcher_indicators()
      if (nrow(p_data) < 10) { current_y <- current_y - block_height; next }
      stats <- calculate_advanced_pitcher_stats(data, pitcher_name)
      if (is.null(stats)) { current_y <- current_y - block_height; next }
      
      block_top <- current_y
      block_bottom <- current_y - block_height + 0.001
      block_mid <- (block_top + block_bottom) / 2
      
      bg_color <- if (p_idx %% 2 == 1) "#FFFFFF" else "#F5F5F5"
      grid::grid.rect(x=0.5, y=block_mid, width=0.98, height=block_height - 0.001,
                      gp=grid::gpar(fill=bg_color, col="#D0D0D0", lwd=0.5))
      # Vertical divider lines
      grid::grid.lines(x=c(0.40, 0.40), y=c(block_top, block_bottom), gp=grid::gpar(col="#D0D0D0", lwd=0.5))
      grid::grid.lines(x=c(0.535, 0.535), y=c(block_top, block_bottom), gp=grid::gpar(col="#D0D0D0", lwd=0.5))
      
      # ---- LEFT SECTION: Name, Stats, Arsenal WITH Stuff+/Whiff%/Strike%, 
      #      then Spray Charts, then Go/No Zones ----
      
      pitcher_num <- start_idx + p_idx - 1
      hand_color <- if (!is.null(stats$pitcher_hand) && stats$pitcher_hand == "Left") "#E53935" else "#1E88E5"
      hand_label <- if (!is.null(stats$pitcher_hand) && stats$pitcher_hand == "Left") "L" else "R"
      
      p_number <- pitcher_notes[[pitcher_name]]$number %||% as.character(pitcher_num)
      p_class  <- pitcher_notes[[pitcher_name]]$class %||% ""
      
      # Number badge - team colored
      grid::grid.rect(x=0.025, y=block_top - 0.008, width=0.023, height=0.013,
                      gp=grid::gpar(fill=tc_primary, col=NA))
      grid::grid.text(p_number, x=0.025, y=block_top - 0.008,
                      gp=grid::gpar(fontsize=7, fontface="bold", col="white"))
      # Hand badge
      grid::grid.rect(x=0.048, y=block_top - 0.008, width=0.011, height=0.011,
                      gp=grid::gpar(fill=hand_color, col=NA))
      grid::grid.text(hand_label, x=0.048, y=block_top - 0.008,
                      gp=grid::gpar(fontsize=4.5, fontface="bold", col="white"))
      # Name
      name_parts <- strsplit(pitcher_name, ", ")[[1]]
      display_name <- if (length(name_parts)==2) paste(name_parts[2], name_parts[1]) else pitcher_name
      grid::grid.text(display_name, x=0.062, y=block_top - 0.008, just="left",
                      gp=grid::gpar(fontsize=7, fontface="bold", col="#333"))
      if (nchar(p_class) > 0) {
        grid::grid.text(p_class, x=0.062, y=block_top - 0.015, just="left",
                        gp=grid::gpar(fontsize=4.5, fontface="italic", col="#666"))
      }
      
      # Stat pills - team colored headers
      stat_y <- block_top - 0.009
      stat_positions <- c(0.164, 0.204, 0.244, 0.284, 0.324, 0.364)
      stat_values <- c(
        if (!is.na(stats$ra9)) sprintf("%.1f", stats$ra9) else "-",
        if (!is.na(stats$ip)) sprintf("%.1f", stats$ip) else "-",
        if (!is.na(stats$fip)) sprintf("%.2f", stats$fip) else "-",
        if (!is.na(stats$k_pct)) paste0(round(stats$k_pct), "%") else "-",
        if (!is.na(stats$bb_pct)) paste0(sprintf("%.1f", stats$bb_pct), "%") else "-",
        "100"
      )
      stat_benchmarks <- c(4.75, 15, 4.22, 26, 10, 100)
      stat_higher <- c(FALSE, TRUE, FALSE, TRUE, FALSE, TRUE)
      stat_range <- c(0.30, 0.50, 0.30, 0.30, 0.30, 0.15)
      
      if ("stuff_plus" %in% names(p_data)) {
        sp_val <- mean(p_data$stuff_plus, na.rm=TRUE)
        if (!is.na(sp_val)) stat_values[6] <- as.character(round(sp_val))
      }
      stat_nums <- suppressWarnings(as.numeric(gsub("%", "", stat_values)))
      
      for (s_idx in seq_along(stat_positions)) {
        pill_bg <- if (!is.na(stat_nums[s_idx])) {
          get_pill_color(stat_nums[s_idx], stat_benchmarks[s_idx], stat_higher[s_idx], stat_range[s_idx])
        } else "#EEEEEE"
        grid::grid.roundrect(x=stat_positions[s_idx], y=stat_y, width=0.033, height=0.012,
                             r=unit(0.3,"snpc"), gp=grid::gpar(fill=pill_bg, col="#BBBBBB", lwd=0.3))
        grid::grid.text(stat_values[s_idx], x=stat_positions[s_idx], y=stat_y,
                        gp=grid::gpar(fontsize=5.5, fontface="bold"))
      }
      
      # ---- ARSENAL with Stuff+, Whiff%, Strike% per pitch ----
      arsenal_y <- block_top - 0.022
      pitch_summary <- p_data %>%
        dplyr::mutate(
          is_swing_ps = as.integer(PitchCall %in% c("StrikeSwinging", "FoulBall",
                                                    "FoulBallNotFieldable", "FoulBallFieldable", "InPlay")),
          is_whiff_ps = as.integer(PitchCall == "StrikeSwinging"),
          is_strike_ps = as.integer(!PitchCall %in% c("BallCalled", "BallinDirt", "BallIntentional"))
        ) %>%
        dplyr::group_by(TaggedPitchType) %>%
        dplyr::summarise(n=dplyr::n(),
                         velo_low=round(stats::quantile(RelSpeed,0.1,na.rm=TRUE),0),
                         velo_high=round(stats::quantile(RelSpeed,0.9,na.rm=TRUE),0),
                         top_velo=round(max(RelSpeed,na.rm=TRUE),0),
                         stuff_avg = if ("stuff_plus" %in% names(.data)) round(mean(stuff_plus, na.rm=TRUE),0) else NA_integer_,
                         whiff_pct = ifelse(sum(is_swing_ps, na.rm=TRUE) > 0,
                                            round(100 * sum(is_whiff_ps, na.rm=TRUE) / sum(is_swing_ps, na.rm=TRUE), 0), 0L),
                         strike_pct = round(100 * sum(is_strike_ps, na.rm=TRUE) / dplyr::n(), 0),
                         .groups="drop") %>%
        dplyr::mutate(pct=round(100*n/sum(n),0)) %>%
        dplyr::arrange(dplyr::desc(pct)) %>% head(5)
      
      pitch_col_width <- 0.076
      
      for (i in 1:min(nrow(pitch_summary), 5)) {
        pt <- pitch_summary$TaggedPitchType[i]
        px <- 0.015 + (i-1) * pitch_col_width
        pt_center_x <- px + 0.020
        pt_short <- get_pt_short(pt)
        pill_color <- pitch_colors[[pt]] %||% "gray50"
        
        # Pitch type pill
        grid::grid.roundrect(x=pt_center_x, y=arsenal_y, width=0.028, height=0.009,
                             r=unit(0.3,"snpc"), gp=grid::gpar(fill=pill_color, col=NA))
        grid::grid.text(pt_short, x=pt_center_x, y=arsenal_y,
                        gp=grid::gpar(fontsize=4.5, fontface="bold", col="white"))
        
        # Velo range
        grid::grid.text(paste0(pitch_summary$velo_low[i],"-",pitch_summary$velo_high[i]),
                        x=pt_center_x, y=arsenal_y - 0.008,
                        gp=grid::gpar(fontsize=3.8, col="#333"))
        # Top velo
        grid::grid.text(paste0("T",pitch_summary$top_velo[i]),
                        x=pt_center_x, y=arsenal_y - 0.014,
                        gp=grid::gpar(fontsize=3.8, fontface="bold", col=tc_primary))
        
        # ---- Per-pitch pills: S+, Whiff%, Strike% (vertically aligned) ----
        # All three pills centered on pt_center_x, stacked vertically
        pill_w <- 0.032
        pill_h <- 0.007
        
        # Row 1: Stuff+ (if available)
        stuff_y <- arsenal_y - 0.022
        if (!is.na(pitch_summary$stuff_avg[i])) {
          stuff_col <- get_pill_color(pitch_summary$stuff_avg[i], 100, TRUE, 0.15)
          grid::grid.roundrect(x=pt_center_x, y=stuff_y, width=pill_w, height=pill_h,
                               r=unit(0.3,"snpc"), gp=grid::gpar(fill=stuff_col, col=pill_color, lwd=0.4))
          grid::grid.text(paste0("S+", pitch_summary$stuff_avg[i]), x=pt_center_x, y=stuff_y,
                          gp=grid::gpar(fontsize=3.2, fontface="bold"))
        }
        
        # Row 2: Whiff%
        whiff_y <- arsenal_y - 0.030
        whiff_col <- get_pill_color(pitch_summary$whiff_pct[i], 29, TRUE, 0.30)
        grid::grid.roundrect(x=pt_center_x, y=whiff_y, width=pill_w, height=pill_h,
                             r=unit(0.3,"snpc"), gp=grid::gpar(fill=whiff_col, col=pill_color, lwd=0.4))
        grid::grid.text(paste0("W", pitch_summary$whiff_pct[i], "%"), x=pt_center_x, y=whiff_y,
                        gp=grid::gpar(fontsize=3.2, fontface="bold"))
        
        # Row 3: Strike%
        strike_y <- arsenal_y - 0.038
        str_col <- get_pill_color(pitch_summary$strike_pct[i], 62, TRUE, 0.20)
        grid::grid.roundrect(x=pt_center_x, y=strike_y, width=pill_w, height=pill_h,
                             r=unit(0.3,"snpc"), gp=grid::gpar(fill=str_col, col=pill_color, lwd=0.4))
        grid::grid.text(paste0("K", pitch_summary$strike_pct[i], "%"), x=pt_center_x, y=strike_y,
                        gp=grid::gpar(fontsize=3.2, fontface="bold"))
        
        # Row 4: Shape note (if provided) - in pitch color
        shape_note <- pitcher_notes[[pitcher_name]]$shape_notes[[pt]] %||% ""
        if (nchar(shape_note) > 0) {
          shape_y <- arsenal_y - 0.045
          grid::grid.roundrect(x=pt_center_x, y=shape_y, width=pill_w, height=pill_h,
                               r=unit(0.3,"snpc"), gp=grid::gpar(fill=pill_color, col=NA))
          # Truncate to fit
          display_note <- if (nchar(shape_note) > 6) paste0(substr(shape_note, 1, 5), ".") else shape_note
          grid::grid.text(display_note, x=pt_center_x, y=shape_y,
                          gp=grid::gpar(fontsize=3, fontface="bold", col="white"))
        }
      }
      
      # ---- SPRAY CHARTS (moved down to make room for expanded arsenal) ----
      spray_y_top <- arsenal_y - 0.052  # Was -0.042, now lower to clear pills+shape
      spray_h <- 0.048
      spray_w <- 0.095
      spray_center_y <- spray_y_top - spray_h / 2
      
      # vL spray chart
      spray_lhh_x <- 0.100
      spray_lhh_plot <- tryCatch(
        create_hits_spray_chart(data, pitcher_name, "Left") +
          labs(title = NULL) + theme(plot.margin = margin(0,0,0,0)),
        error = function(e) ggplot() + theme_void()
      )
      grid::grid.text("vL", x=spray_lhh_x - spray_w/2 - 0.008, y=spray_center_y,
                      gp=grid::gpar(fontsize=3.5, fontface="bold", col="#E53935"))
      grid::pushViewport(grid::viewport(x=spray_lhh_x, y=spray_center_y,
                                        width=spray_w, height=spray_h, just=c("center","center")))
      tryCatch(print(spray_lhh_plot, newpage=FALSE), error=function(e) NULL)
      grid::popViewport()
      
      # vR spray chart
      spray_rhh_x <- 0.280
      spray_rhh_plot <- tryCatch(
        create_hits_spray_chart(data, pitcher_name, "Right") +
          labs(title = NULL) + theme(plot.margin = margin(0,0,0,0)),
        error = function(e) ggplot() + theme_void()
      )
      grid::grid.text("vR", x=spray_rhh_x - spray_w/2 - 0.008, y=spray_center_y,
                      gp=grid::gpar(fontsize=3.5, fontface="bold", col="#1E88E5"))
      grid::pushViewport(grid::viewport(x=spray_rhh_x, y=spray_center_y,
                                        width=spray_w, height=spray_h, just=c("center","center")))
      tryCatch(print(spray_rhh_plot, newpage=FALSE), error=function(e) NULL)
      grid::popViewport()
      
      # ---- GO ZONES / NO ZONES (moved down below spray charts) ----
      zone_y_top <- spray_y_top - spray_h - 0.004
      zone_box_h <- 0.026
      zone_box_w <- 0.19
      
      go_zone_x <- 0.115    # Was 0.100, moved slightly left
      no_zone_x <- 0.225    # Was 0.280, moved slightly left
      zone_center_y <- zone_y_top - zone_box_h/2
      
      # Go Zones box
      grid::grid.rect(x=go_zone_x, y=zone_center_y, width=zone_box_w, height=zone_box_h,
                      gp=grid::gpar(fill="white", col="#00840D", lwd=0.8))
      grid::grid.text("Go Zones", x=go_zone_x, y=zone_y_top - 0.001,
                      gp=grid::gpar(fontsize=5.5, fontface="bold", col="#00840D"))
      
      go_rhh <- pitcher_notes[[pitcher_name]]$go_zones_rhh %||% ""
      go_lhh <- pitcher_notes[[pitcher_name]]$go_zones_lhh %||% ""
      note_y_start <- zone_y_top - 0.008
      if (nchar(go_rhh) > 0) {
        grid::grid.text(paste0("RHH: ", go_rhh), x=go_zone_x - zone_box_w/2 + 0.005,
                        y=note_y_start, just="left",
                        gp=grid::gpar(fontsize=3.5, col="#333"))
      } else {
        grid::grid.text("RHH:", x=go_zone_x - zone_box_w/2 + 0.005,
                        y=note_y_start, just="left",
                        gp=grid::gpar(fontsize=3.5, col="#999"))
      }
      if (nchar(go_lhh) > 0) {
        grid::grid.text(paste0("LHH: ", go_lhh), x=go_zone_x - zone_box_w/2 + 0.005,
                        y=note_y_start - 0.006, just="left",
                        gp=grid::gpar(fontsize=3.5, col="#333"))
      } else {
        grid::grid.text("LHH:", x=go_zone_x - zone_box_w/2 + 0.005,
                        y=note_y_start - 0.006, just="left",
                        gp=grid::gpar(fontsize=3.5, col="#999"))
      }
      
      # No Zones box
      grid::grid.rect(x=no_zone_x, y=zone_center_y, width=zone_box_w, height=zone_box_h,
                      gp=grid::gpar(fill="white", col="#E1463E", lwd=0.8))
      grid::grid.text("No Zones", x=no_zone_x, y=zone_y_top - 0.001,
                      gp=grid::gpar(fontsize=5.5, fontface="bold", col="#E1463E"))
      
      no_rhh <- pitcher_notes[[pitcher_name]]$no_zones_rhh %||% ""
      no_lhh <- pitcher_notes[[pitcher_name]]$no_zones_lhh %||% ""
      if (nchar(no_rhh) > 0) {
        grid::grid.text(paste0("RHH: ", no_rhh), x=no_zone_x - zone_box_w/2 + 0.005,
                        y=note_y_start, just="left",
                        gp=grid::gpar(fontsize=3.5, col="#333"))
      } else {
        grid::grid.text("RHH:", x=no_zone_x - zone_box_w/2 + 0.005,
                        y=note_y_start, just="left",
                        gp=grid::gpar(fontsize=3.5, col="#999"))
      }
      if (nchar(no_lhh) > 0) {
        grid::grid.text(paste0("LHH: ", no_lhh), x=no_zone_x - zone_box_w/2 + 0.005,
                        y=note_y_start - 0.006, just="left",
                        gp=grid::gpar(fontsize=3.5, col="#333"))
      } else {
        grid::grid.text("LHH:", x=no_zone_x - zone_box_w/2 + 0.005,
                        y=note_y_start - 0.006, just="left",
                        gp=grid::gpar(fontsize=3.5, col="#999"))
      }
      
      mvmt_center_x <- 0.47
      mvmt_width <- 0.12
      mvmt_height <- block_height * 0.50   # Smaller to fit arm angle below
      mvmt_center_y <- block_top - 0.005 - mvmt_height / 2  # At top of block
      
      mvmt_plot <- tryCatch(
        create_mini_movement(data, pitcher_name, expected_grid),
        error=function(e) { ggplot() + theme_void() }
      )
      
      tryCatch({
        mvmt_grob <- ggplot2::ggplotGrob(mvmt_plot)
        grid::pushViewport(grid::viewport(x=mvmt_center_x, y=mvmt_center_y,
                                          width=mvmt_width, height=mvmt_height,
                                          just=c("center","center"), clip="on"))
        grid::grid.draw(mvmt_grob)
        grid::popViewport()
      }, error=function(e) {
        grid::pushViewport(grid::viewport(x=mvmt_center_x, y=mvmt_center_y,
                                          width=mvmt_width, height=mvmt_height,
                                          just=c("center","center")))
        grid::grid.text("Mvmt Error", gp=grid::gpar(fontsize=6))
        grid::popViewport()
      })
      
      # ---- ARM ANGLE VISUALIZATION (below movement chart) ----
      arm_angle_height <- block_height * 0.38
      arm_angle_center_y <- mvmt_center_y - mvmt_height/2 - 0.003 - arm_angle_height/2
      
      arm_angle_plot <- tryCatch(
        create_mini_arm_angle(data, pitcher_name),
        error = function(e) ggplot() + theme_void()
      )
      
      grid::pushViewport(grid::viewport(x=mvmt_center_x, y=arm_angle_center_y,
                                        width=mvmt_width * 0.85, height=arm_angle_height,
                                        just=c("center","center")))
      tryCatch(print(arm_angle_plot, newpage=FALSE), error=function(e) NULL)
      grid::popViewport()
      
      # ---- RIGHT SECTION: Pies + Heatmaps + Whiff + Nitro ----
      # Notes box is now HORIZONTAL across the bottom of this section
      right_start <- 0.535
      
      # Reserve space at bottom for notes bar
      notes_bar_h <- 0.053
      right_chart_bottom <- block_bottom + notes_bar_h + 0.004
      
      # Pie charts
      pie_w <- 0.035
      pie_h <- (block_height - notes_bar_h - 0.014) / 2 * 0.55
      pie_cols <- c(0.555, 0.595, 0.635)
      pie_row1_y <- block_top - 0.006
      pie_row2_y <- block_top - 0.006 - pie_h - 0.003
      
      grid::grid.text("vL", x=0.538, y=pie_row1_y - pie_h/2,
                      gp=grid::gpar(fontsize=3.5, fontface="bold", col="#E53935"))
      grid::grid.text("vR", x=0.538, y=pie_row2_y - pie_h/2,
                      gp=grid::gpar(fontsize=3.5, fontface="bold", col="#1E88E5"))
      
      lhh_all <- p_data %>% dplyr::filter(BatterSide=="Left", !is.na(TaggedPitchType), TaggedPitchType!="Other")
      rhh_all <- p_data %>% dplyr::filter(BatterSide=="Right", !is.na(TaggedPitchType), TaggedPitchType!="Other")
      
      pie_list <- list(
        list(lhh_all, pie_cols[1], pie_row1_y-pie_h/2),
        list(lhh_all %>% dplyr::filter(PitchofPA==1), pie_cols[2], pie_row1_y-pie_h/2),
        list(lhh_all %>% dplyr::filter(Strikes==2), pie_cols[3], pie_row1_y-pie_h/2),
        list(rhh_all, pie_cols[1], pie_row2_y-pie_h/2),
        list(rhh_all %>% dplyr::filter(PitchofPA==1), pie_cols[2], pie_row2_y-pie_h/2),
        list(rhh_all %>% dplyr::filter(Strikes==2), pie_cols[3], pie_row2_y-pie_h/2)
      )
      for (pie_item in pie_list) {
        pp <- create_mini_pie(pie_item[[1]])
        grid::pushViewport(grid::viewport(x=pie_item[[2]], y=pie_item[[3]], width=pie_w, height=pie_h, just=c("center","center")))
        tryCatch(print(pp, newpage=FALSE), error=function(e) NULL)
        grid::popViewport()
      }
      
      # Location Heatmaps (FB/BB/OS)
      hm_w <- 0.038
      hm_h <- (block_height - notes_bar_h - 0.014) / 2 * 0.60
      hm_cols <- c(0.680, 0.725, 0.770)
      hm_row1_y <- block_top - 0.005
      hm_row2_y <- block_top - 0.005 - hm_h - 0.003
      
      grid::grid.text("LHH", x=0.658, y=hm_row1_y-hm_h/2,
                      gp=grid::gpar(fontsize=3, fontface="bold", col="#E53935"))
      grid::grid.text("RHH", x=0.658, y=hm_row2_y-hm_h/2,
                      gp=grid::gpar(fontsize=3, fontface="bold", col="#1E88E5"))
      
      pitch_groups_list <- list(FB=fb_pitches, BB=bb_pitches, OS=os_pitches)
      for (col_idx in 1:3) {
        for (side_idx in 1:2) {
          side <- c("Left","Right")[side_idx]
          y_pos <- c(hm_row1_y, hm_row2_y)[side_idx]
          cell_data <- p_data %>%
            dplyr::filter(TaggedPitchType %in% pitch_groups_list[[col_idx]],
                          BatterSide==side, !is.na(PlateLocSide), !is.na(PlateLocHeight))
          hm_plot <- create_mini_heatmap(cell_data)
          grid::pushViewport(grid::viewport(x=hm_cols[col_idx], y=y_pos-hm_h/2,
                                            width=hm_w, height=hm_h, just=c("center","center")))
          tryCatch(print(hm_plot, newpage=FALSE), error=function(e) NULL)
          grid::popViewport()
        }
      }
      
      # ---- WHIFF HEATMAPS ----
      whiff_x <- 0.825
      whiff_w <- 0.042
      whiff_h <- (block_height - notes_bar_h - 0.014) / 2 * 0.58
      whiff_row1_y <- block_top - 0.005
      whiff_row2_y <- block_top - 0.005 - whiff_h - 0.003
      
      grid::grid.text("L", x=whiff_x, y=whiff_row1_y + 0.003,
                      gp=grid::gpar(fontsize=2.5, fontface="bold", col="#E53935"))
      grid::grid.text("R", x=whiff_x, y=whiff_row2_y + 0.003,
                      gp=grid::gpar(fontsize=2.5, fontface="bold", col="#1E88E5"))
      
      # LHH whiff heatmap
      whiff_lhh_plot <- tryCatch(
        create_mini_whiff_heatmap(p_data, "Left"),
        error = function(e) ggplot() + theme_void()
      )
      grid::pushViewport(grid::viewport(x=whiff_x, y=whiff_row1_y - whiff_h/2,
                                        width=whiff_w, height=whiff_h, just=c("center","center")))
      tryCatch(print(whiff_lhh_plot, newpage=FALSE), error=function(e) NULL)
      grid::popViewport()
      
      # RHH whiff heatmap
      whiff_rhh_plot <- tryCatch(
        create_mini_whiff_heatmap(p_data, "Right"),
        error = function(e) ggplot() + theme_void()
      )
      grid::pushViewport(grid::viewport(x=whiff_x, y=whiff_row2_y - whiff_h/2,
                                        width=whiff_w, height=whiff_h, just=c("center","center")))
      tryCatch(print(whiff_rhh_plot, newpage=FALSE), error=function(e) NULL)
      grid::popViewport()
      
      # ---- NITRO ZONES ----
      nitro_x <- 0.885
      nitro_w <- 0.042
      nitro_h <- (block_height - notes_bar_h - 0.014) / 2 * 0.55
      nitro_row1_y <- block_top - 0.005
      nitro_row2_y <- block_top - 0.005 - nitro_h - 0.003
      
      grid::grid.text("L", x=nitro_x, y=nitro_row1_y + 0.003,
                      gp=grid::gpar(fontsize=2.5, fontface="bold", col="#E53935"))
      grid::grid.text("R", x=nitro_x, y=nitro_row2_y + 0.003,
                      gp=grid::gpar(fontsize=2.5, fontface="bold", col="#1E88E5"))
      
      nitro_lhh_plot <- tryCatch(
        create_mini_nitro(p_data, "Left"),
        error = function(e) ggplot() + theme_void()
      )
      grid::pushViewport(grid::viewport(x=nitro_x, y=nitro_row1_y - nitro_h/2,
                                        width=nitro_w, height=nitro_h, just=c("center","center")))
      tryCatch(print(nitro_lhh_plot, newpage=FALSE), error=function(e) NULL)
      grid::popViewport()
      
      nitro_rhh_plot <- tryCatch(
        create_mini_nitro(p_data, "Right"),
        error = function(e) ggplot() + theme_void()
      )
      grid::pushViewport(grid::viewport(x=nitro_x, y=nitro_row2_y - nitro_h/2,
                                        width=nitro_w, height=nitro_h, just=c("center","center")))
      tryCatch(print(nitro_rhh_plot, newpage=FALSE), error=function(e) NULL)
      grid::popViewport()
      
      # ---- PILL STATS (right of nitro zones) ----
      pill_stats_x <- 0.945
      pill_stats_top <- block_top - 0.008
      
      # Overall extension
      overall_ext <- mean(p_data$Extension, na.rm = TRUE)
      ext_str <- if (!is.na(overall_ext)) sprintf("%.1f", overall_ext) else "-"
      
      grid::grid.text("Ext", x=pill_stats_x, y=pill_stats_top,
                      gp=grid::gpar(fontsize=4, fontface="bold", col="#006F71"))
      ext_col <- get_pill_color(overall_ext, 5.80, TRUE, 0.10)
      grid::grid.roundrect(x=pill_stats_x, y=pill_stats_top - 0.010, width=0.035, height=0.012,
                           r=unit(0.3,"snpc"), gp=grid::gpar(fill=ext_col, col="#BBBBBB", lwd=0.3))
      grid::grid.text(paste0(ext_str, "ft"), x=pill_stats_x, y=pill_stats_top - 0.010,
                      gp=grid::gpar(fontsize=4.5, fontface="bold"))
      
      # wOBA vs L
      has_woba_col <- "woba" %in% names(p_data)
      woba_vl <- if (has_woba_col) mean(p_data$woba[p_data$BatterSide == "Left"], na.rm = TRUE) else NA_real_
      woba_vr <- if (has_woba_col) mean(p_data$woba[p_data$BatterSide == "Right"], na.rm = TRUE) else NA_real_
      
      grid::grid.text("wOBA vL", x=pill_stats_x, y=pill_stats_top - 0.028,
                      gp=grid::gpar(fontsize=3.5, fontface="bold", col="#E53935"))
      if (!is.na(woba_vl)) {
        woba_vl_col <- get_pill_color(woba_vl, 0.320, FALSE, 0.20)
        grid::grid.roundrect(x=pill_stats_x, y=pill_stats_top - 0.038, width=0.035, height=0.012,
                             r=unit(0.3,"snpc"), gp=grid::gpar(fill=woba_vl_col, col="#BBBBBB", lwd=0.3))
        grid::grid.text(sprintf("%.3f", woba_vl), x=pill_stats_x, y=pill_stats_top - 0.038,
                        gp=grid::gpar(fontsize=4.5, fontface="bold"))
      }
      
      # wOBA vs R
      grid::grid.text("wOBA vR", x=pill_stats_x, y=pill_stats_top - 0.055,
                      gp=grid::gpar(fontsize=3.5, fontface="bold", col="#1E88E5"))
      if (!is.na(woba_vr)) {
        woba_vr_col <- get_pill_color(woba_vr, 0.320, FALSE, 0.20)
        grid::grid.roundrect(x=pill_stats_x, y=pill_stats_top - 0.065, width=0.035, height=0.012,
                             r=unit(0.3,"snpc"), gp=grid::gpar(fill=woba_vr_col, col="#BBBBBB", lwd=0.3))
        grid::grid.text(sprintf("%.3f", woba_vr), x=pill_stats_x, y=pill_stats_top - 0.065,
                        gp=grid::gpar(fontsize=4.5, fontface="bold"))
      }
      
      notes_bar_h <- 0.050
      notes_left <- 0.560     # Shifted right (was 0.535)
      notes_right <- 0.920    # Narrower on right to leave room for pill stats
      notes_bar_w <- notes_right - notes_left
      notes_bar_center_x <- (notes_left + notes_right) / 2
      notes_bar_top <- block_bottom + notes_bar_h + 0.006
      notes_bar_center_y <- notes_bar_top - notes_bar_h / 2
      
      # Notes box with team-colored border
      grid::grid.rect(x=notes_bar_center_x, y=notes_bar_center_y,
                      width=notes_bar_w, height=notes_bar_h,
                      gp=grid::gpar(fill="white", col=tc_primary, lwd=0.8))
      
      # "Notes:" label centered at top
      grid::grid.text("Notes:", x=notes_bar_center_x, y=notes_bar_top - 0.005,
                      gp=grid::gpar(fontsize=5, fontface="bold", col=tc_primary))
      
      n_note_lines <- 6
      line_spacing_v <- (notes_bar_h - 0.010) / n_note_lines
      for (line_idx in 1:n_note_lines) {
        line_y <- notes_bar_top - 0.008 - line_idx * line_spacing_v
        grid::grid.lines(x = c(notes_left + 0.005, notes_right - 0.005),
                         y = c(line_y, line_y),
                         gp = grid::gpar(col = "#E0E0E0", lwd = 0.3))
      }
      current_y <- block_bottom
    }
    
    # Footer - team branded
    grid::grid.rect(x=0.5, y=0.001, width=1, height=0.004,
                    gp=grid::gpar(fill=tc_secondary, col=NA))
    grid::grid.text("Data: TrackMan | Coastal Carolina Baseball Analytics", x=0.5, y=0.005,
                    gp=grid::gpar(fontsize=4.5, col="gray50"))
  }
  
  invisible(output_file)
}

# 7. CALCULATE PITCHER STATS
calculate_pitcher_stats <- function(data, pitcher_name, date_range = NULL, batter_sides = NULL) {
  if (is.null(data)) return(NULL)
  
  df <- data %>% filter(Pitcher == pitcher_name)
  
  if (!is.null(date_range) && length(date_range) == 2) {
    df <- df %>% filter(Date >= date_range[1], Date <= date_range[2])
  }
  
  if (!is.null(batter_sides) && length(batter_sides) > 0) {
    df <- df %>% filter(BatterSide %in% batter_sides)
  }
  
  if (nrow(df) < 10) return(NULL)
  
  pa_ending_events <- df %>%
    filter(
      KorBB %in% c("Strikeout", "Walk") |
        PitchCall == "HitByPitch" |
        PitchCall == "InPlay"
    )
  
  n_pa <- nrow(pa_ending_events)
  n_k <- sum(pa_ending_events$KorBB == "Strikeout", na.rm = TRUE)
  n_bb <- sum(pa_ending_events$KorBB == "Walk", na.rm = TRUE)
  n_hbp <- sum(pa_ending_events$PitchCall == "HitByPitch", na.rm = TRUE)
  
  overall <- df %>%
    summarise(
      throws = first(PitcherThrows),
      n_pitches = n(),
      avg_velo = mean(RelSpeed, na.rm = TRUE),
      strike_pct = 100 * mean(PitchCall %in% c("StrikeCalled", "StrikeSwinging", "FoulBall", 
                                               "FoulBallNotFieldable", "FoulBallFieldable", "InPlay"), na.rm = TRUE),
      zone_pct = 100 * mean(PlateLocSide >= -0.83 & PlateLocSide <= 0.83 &
                              PlateLocHeight >= 1.5 & PlateLocHeight <= 3.5, na.rm = TRUE),
      whiff_pct = 100 * sum(PitchCall == "StrikeSwinging", na.rm = TRUE) / 
        max(sum(PitchCall %in% c("StrikeSwinging", "FoulBall", "FoulBallNotFieldable", 
                                 "FoulBallFieldable", "InPlay"), na.rm = TRUE), 1),
      z_whiff_pct = 100 * sum(PitchCall == "StrikeSwinging" & 
                                PlateLocSide >= -0.83 & PlateLocSide <= 0.83 &
                                PlateLocHeight >= 1.5 & PlateLocHeight <= 3.5, na.rm = TRUE) /
        max(sum(PitchCall %in% c("StrikeSwinging", "FoulBall", "FoulBallNotFieldable",
                                 "FoulBallFieldable", "InPlay") &
                  PlateLocSide >= -0.83 & PlateLocSide <= 0.83 &
                  PlateLocHeight >= 1.5 & PlateLocHeight <= 3.5, na.rm = TRUE), 1),
      chase_pct = 100 * sum(PitchCall %in% c("StrikeSwinging", "FoulBall", "FoulBallNotFieldable",
                                             "FoulBallFieldable", "InPlay") &
                              !(PlateLocSide >= -0.83 & PlateLocSide <= 0.83 &
                                  PlateLocHeight >= 1.5 & PlateLocHeight <= 3.5), na.rm = TRUE) /
        max(sum(!(PlateLocSide >= -0.83 & PlateLocSide <= 0.83 &
                    PlateLocHeight >= 1.5 & PlateLocHeight <= 3.5), na.rm = TRUE), 1)
    ) %>%
    mutate(
      k_pct = if (n_pa > 0) 100 * n_k / n_pa else 0,
      bb_pct = if (n_pa > 0) 100 * n_bb / n_pa else 0,
      bb_hbp_pct = if (n_pa > 0) 100 * (n_bb + n_hbp) / n_pa else 0,
      n_pa = n_pa
    )
  
  by_pitch <- df %>%
    filter(!is.na(TaggedPitchType), TaggedPitchType != "Other") %>%
    group_by(TaggedPitchType) %>%
    summarise(
      n = n(),
      velo_avg = mean(RelSpeed, na.rm = TRUE),
      velo_p20 = quantile(RelSpeed, 0.20, na.rm = TRUE),
      velo_p90 = quantile(RelSpeed, 0.90, na.rm = TRUE),
      .groups = "drop"
    )
  
  vs_lhh <- df %>%
    filter(BatterSide == "Left") %>%
    summarise(
      ba = sum(PlayResult %in% c("Single", "Double", "Triple", "HomeRun"), na.rm = TRUE) /
        max(sum(PlayResult %in% c("Single", "Double", "Triple", "HomeRun", "Out", "FieldersChoice") |
                  KorBB == "Strikeout", na.rm = TRUE), 1)
    )
  
  vs_rhh <- df %>%
    filter(BatterSide == "Right") %>%
    summarise(
      ba = sum(PlayResult %in% c("Single", "Double", "Triple", "HomeRun"), na.rm = TRUE) /
        max(sum(PlayResult %in% c("Single", "Double", "Triple", "HomeRun", "Out", "FieldersChoice") |
                  KorBB == "Strikeout", na.rm = TRUE), 1)
    )
  
  return(list(
    overall = overall,
    by_pitch = by_pitch,
    vs_lhh = vs_lhh,
    vs_rhh = vs_rhh
  ))
}



# ---- Get unique pitchers and hitters ----
all_pitchers_2025 <- sort(unique(tm_data$Pitcher[!is.na(tm_data$Pitcher) & tm_data$Pitcher != ""]))
all_pitchers_2026 <- sort(unique(data_2026$Pitcher[!is.na(data_2026$Pitcher) & data_2026$Pitcher != ""]))
all_pitchers_combined <- sort(unique(c(all_pitchers_2025, all_pitchers_2026)))

all_hitters_2025 <- sort(unique(tm_data$Batter[!is.na(tm_data$Batter) & tm_data$Batter != ""]))
all_hitters_2026 <- sort(unique(data_2026$Batter[!is.na(data_2026$Batter) & data_2026$Batter != ""]))
all_hitters_combined <- sort(unique(c(all_hitters_2025, all_hitters_2026)))

# Start with combined as default
all_pitchers <- all_pitchers_combined
all_hitters <- all_hitters_combined

cat("Found", length(all_pitchers_2025), "pitchers in 2025,", length(all_pitchers_2026), "in 2026,", length(all_pitchers_combined), "combined\n")
cat("Data preprocessing complete!\n\n")


# ============================================================================
# UI - MODERN TEAL/BRONZE STYLING
# ============================================================================

login_ui <- fluidPage(
  tags$style(HTML("
    body { background-color: #f0f4f8; font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif; color: #006F71; }
    .login-container { max-width: 360px; margin: 120px auto; background: #A27752; padding: 30px 25px; border-radius: 8px;
      box-shadow: 0 4px 15px #A1A1A4; text-align: center; color: white; }
    .btn-primary { background-color: #006F71 !important; border-color: #006F71 !important; color: white !important;
      font-weight: bold; width: 100%; margin-top: 10px; box-shadow: 0 2px 5px #006F71; transition: background-color 0.3s ease; }
    .btn-primary:hover { background-color: #006F71 !important; border-color: #A27752 !important; }
    .form-control { border-radius: 4px; border: 1.5px solid #006F71 !important; color: #006F71; font-weight: 600; }
  ")),
  div(class = "login-container",
      tags$img(src="https://upload.wikimedia.org/wikipedia/en/thumb/e/ef/Coastal_Carolina_Chanticleers_logo.svg/1200px-Coastal_Carolina_Chanticleers_logo.svg.png", height="150px"),
      passwordInput("password", "Password:"),
      actionButton("login", "Login"),
      textOutput("wrong_pass")
  )
)

app_ui <- fluidPage(
  tags$head(
    tags$style(HTML("
      body, table, .gt_table { font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Helvetica, Arial, sans-serif; }
      
      /* Header styling */
      .app-header { display:flex; justify-content:space-between; align-items:center; padding:15px 30px; background:#ffffff; border-bottom:3px solid darkcyan; margin-bottom:15px; }
      .header-title { font-size: 28px; font-weight: bold; color: darkcyan; }
      .header-subtitle { font-size: 14px; color: #666; }
      
      /* Global data source filter styling */
      .data-source-filter { display: flex; align-items: center; gap: 8px; background: linear-gradient(135deg, #e0f7fa, #b2ebf2); padding: 8px 16px; border-radius: 25px; border: 2px solid darkcyan; }
      .data-source-filter label.control-label { display: none; }
      .data-source-filter .checkbox-inline { margin: 0 4px; font-weight: 700; color: #006F71; font-size: 13px; }
      .data-source-label { font-weight: 700; color: darkcyan; font-size: 13px; white-space: nowrap; }
      
      /* Tab styling */
      .nav-tabs{ border:none !important; border-radius:50px; padding:6px 12px; margin:10px auto; max-width:100%;
        background:linear-gradient(135deg, #d4edeb 0%, #e8ddd0 50%, #d4edeb 100%); box-shadow:0 4px 16px rgba(0,139,139,.12), inset 0 2px 4px rgba(255,255,255,.6);
        border:1px solid rgba(0,139,139,.2); position:relative; overflow-x:auto; display:flex; justify-content:center; align-items:center; flex-wrap:wrap; gap:6px; }
      .nav-tabs::before{ content:''; position:absolute; inset:0; pointer-events:none; border-radius:50px; background:linear-gradient(135deg, rgba(255,255,255,.4), transparent); }
      .nav-tabs>li>a{ color:darkcyan !important; border:none !important; border-radius:50px !important; background:transparent !important; font-weight:700; font-size:14px; padding:10px 20px; white-space:nowrap; transition:all .2s ease; }
      .nav-tabs>li>a:hover{ color:#006666 !important; background:rgba(255,255,255,.5) !important; transform:translateY(-1px); }
      .nav-tabs>li.active>a, .nav-tabs>li.active>a:focus, .nav-tabs>li.active>a:hover{
        background:linear-gradient(135deg,#008b8b 0%,#20b2aa 30%,#00ced1 50%,#20b2aa 70%,#008b8b 100%) !important;
        color:#fff !important; text-shadow:0 1px 2px rgba(0,0,0,.2); box-shadow:0 4px 16px rgba(0,139,139,.4), inset 0 2px 8px rgba(255,255,255,.4);
        border:1px solid rgba(255,255,255,.3) !important; }
      
      /* Tab content styling */
      .tab-content{ background:linear-gradient(135deg, rgba(255,255,255,.95), rgba(248,249,250,.95)); border-radius:20px; padding:20px; margin-top:10px; box-shadow:0 15px 40px rgba(0,139,139,.1); border:1px solid rgba(0,139,139,.1); position:relative; overflow:hidden; }
      .tab-content::before{ content:''; position:absolute; left:0; right:0; top:0; height:4px; background:linear-gradient(90deg, darkcyan, peru, darkcyan); background-size:200% 100%; animation:shimmer 3s linear infinite; }
      @keyframes shimmer { 0%{background-position:-200% 0;} 100%{background-position:200% 0;} }
      
      /* Well and box styling */
      .well { background:#ffffff; border-radius:12px; border:1px solid rgba(0,139,139,.15); box-shadow:0 6px 18px rgba(0,0,0,.06); padding: 15px; }
      .control-label{ font-weight:700; color:#0a6a6a; }
      .selectize-input, .form-control{ border-radius:10px; border:1px solid rgba(0,139,139,.35); }
      .gt_table{ border-radius:12px; overflow:hidden; border:1px solid rgba(0,139,139,.15); }
      
      /* Chart box styling */
      .chart-box { background: white; border-radius: 12px; border: 1px solid rgba(0,139,139,.2); padding: 10px; margin-bottom: 10px; box-shadow: 0 4px 12px rgba(0,0,0,.05); }
      .chart-box-title { font-weight: 700; color: darkcyan; font-size: 13px; margin-bottom: 8px; text-align: center; border-bottom: 2px solid rgba(0,139,139,.2); padding-bottom: 5px; }
      
      /* Compact chart styling */
      .compact-chart { margin: 0; padding: 0; }
      
      /* Stats header */
      .stats-header { background: linear-gradient(135deg, darkcyan, #20b2aa); color: white; padding: 12px 20px; border-radius: 12px; margin-bottom: 15px; }
      .stats-header h3 { margin: 0; font-weight: bold; }
      .stats-header p { margin: 0; opacity: 0.9; font-size: 13px; }
      
      /* Stat boxes */
      .stat-box { background: white; border-radius: 10px; padding: 10px 15px; text-align: center; border: 1px solid rgba(0,139,139,.2); box-shadow: 0 2px 8px rgba(0,0,0,.05); }
      .stat-value { font-size: 22px; font-weight: bold; color: darkcyan; }
      .stat-label { font-size: 11px; color: #666; text-transform: uppercase; }
      
      /* Notes inputs */
      .pdf-notes-input textarea { font-size: 16px !important; border-radius: 10px; border: 1px solid rgba(0,139,139,.35); }
      .pitch-notes-input textarea { font-size: 14px !important; border-radius: 10px; border: 1px solid rgba(0,139,139,.35); }
      .series-title-input input { font-size: 18px !important; font-weight: bold; }
      
      /* Button styling */
      .btn-teal { background: linear-gradient(135deg, darkcyan, #20b2aa); color: white; border: none; border-radius: 25px; padding: 10px 25px; font-weight: 600; box-shadow: 0 4px 12px rgba(0,139,139,.3); transition: all 0.2s; }
      .btn-teal:hover { transform: translateY(-2px); box-shadow: 0 6px 16px rgba(0,139,139,.4); color: white; }
      .btn-bronze { background: linear-gradient(135deg, peru, #daa520); color: white; border: none; border-radius: 25px; padding: 10px 25px; font-weight: 600; box-shadow: 0 4px 12px rgba(205,133,63,.3); }
      .btn-bronze:hover { transform: translateY(-2px); box-shadow: 0 6px 16px rgba(205,133,63,.4); color: white; }
      
      /* Input row styling */
      .input-row { background: #f8f9fa; border-radius: 12px; padding: 12px 15px; margin-bottom: 15px; border: 1px solid rgba(0,139,139,.15); }
      
      /* Movement plot customization panel */
      .mvmt-options { background: linear-gradient(135deg, #f0f7f7, #e8f4f4); padding: 12px; border-radius: 10px; margin-bottom: 10px; border: 1px solid rgba(0,139,139,.2); }
      .mvmt-options .checkbox { margin-bottom: 5px; }
      .mvmt-options label { font-size: 12px; font-weight: 600; color: #006F71; }
      
      /* Pitch type filter inline checkboxes */
      .mvmt-options .checkbox-inline { margin-right: 15px; padding: 4px 10px; border-radius: 15px; background: #f0f0f0; transition: all 0.2s; }
      .mvmt-options .checkbox-inline:hover { background: #e0e0e0; }
      .mvmt-options .checkbox-inline input[type='checkbox'] { margin-right: 5px; }
    "))
  ),
  
  # App Header with Global Data Source Filter
  div(class = "app-header",
      div(
        div(class = "header-title", "Pitcher Scouting Reports"),
        div(class = "header-subtitle", "Coastal Carolina Baseball Analytics")
      ),
      # ===== GLOBAL DATA SOURCE FILTER =====
      div(class = "data-source-filter",
          span(class = "data-source-label", "Data:"),
          checkboxGroupInput("data_source", label = NULL,
                             choices = c("2025" = "2025", "2026" = "2026"),
                             selected = c("2025", "2026"),
                             inline = TRUE),
          actionButton("refresh_data", "Refresh", icon = icon("refresh"), 
                       class = "btn-info btn-sm", style = "margin-left: 10px;")
      )
  ),
  
  # Main Content - Full Width with Tabs
  tabsetPanel(
    id = "main_tabs", type = "tabs",
    
    # ===== PITCHER REPORTS TAB (Combined) =====
    tabPanel("Pitcher Reports", value = "pitcher_reports",
             
             # Main Pitcher Selection Row - ALWAYS VISIBLE
             div(class = "input-row", style = "background: linear-gradient(135deg, #e0f7fa, #b2ebf2); padding: 15px; border-radius: 12px; margin-bottom: 15px;",
                 fluidRow(
                   column(3, 
                          selectInput("main_pitcher", "Select Pitcher:", 
                                      choices = c("Loading..." = ""), width = "100%")
                   ),
                   column(2,
                          checkboxGroupInput("batter_side_filter", "vs Batter:", 
                                             choices = c("L" = "Left", "R" = "Right"), 
                                             selected = c("Left", "Right"), inline = TRUE)
                   ),
                   column(2,
                          dateInput("date_filter_start", "From Date:", 
                                    value = NULL, width = "100%")
                   ),
                   column(2,
                          dateInput("date_filter_end", "To Date:", 
                                    value = NULL, width = "100%")
                   ),
                   column(3,
                          div(style = "padding-top: 25px;",
                              downloadButton("download_single_pdf", "Download PDF", 
                                             class = "btn-teal", style = "width: 100%;"))
                   )
                 )
             ),
             
             div(class = "chart-box",
                 div(class = "chart-box-title", style = "font-size: 14px; background: linear-gradient(90deg, darkcyan, peru); color: white; padding: 8px; margin: -10px -10px 10px -10px; border-radius: 10px 10px 0 0;",
                     "Series Scouting Report Settings (Optional - for multi-pitcher reports)"),
                 fluidRow(
                   column(3,
                          div(class = "series-title-input",
                              textInput("series_title", "Series Title:",
                                        value = "", placeholder = "e.g., ECU @ COA 3/9-3/14", width = "100%"))
                   ),
                   column(3,
                          selectInput("opponent_team", "Opponent Team:",
                                      choices = c("-- Select Team --" = ""),
                                      width = "100%")
                   ),
                   column(3,
                          textInput("opponent_record", "Opponent Record:",
                                    placeholder = "e.g., 25-10 (12-6)", width = "100%")
                   ),
                   column(3,
                          # Preview of selected team colors
                          uiOutput("team_color_preview")
                   )
                 ),
                 
                 # ---- Auto-populated Pitcher Roster ----
                 fluidRow(
                   column(12,
                          div(style = "margin-top: 10px; border-top: 1px solid #ddd; padding-top: 10px;",
                              div(style = "display: flex; align-items: center; justify-content: space-between; margin-bottom: 8px;",
                                  h5("Pitcher Roster", style = "color: darkcyan; margin: 0;"),
                                  div(style = "display: flex; gap: 8px; align-items: center;",
                                      # Manual add pitcher dropdown
                                      selectizeInput("add_pitcher_manual", NULL,
                                                     choices = NULL, multiple = FALSE,
                                                     options = list(placeholder = "Add a pitcher...",
                                                                    maxOptions = 100),
                                                     width = "250px"),
                                      actionButton("btn_add_pitcher", "Add",
                                                   style = "background: darkcyan; color: white; border: none; padding: 4px 12px; border-radius: 4px;"),
                                      actionButton("btn_clear_roster", "Clear All",
                                                   style = "background: #E53935; color: white; border: none; padding: 4px 12px; border-radius: 4px;")
                                  )
                              ),
                              # Dynamic roster table
                              uiOutput("pitcher_roster_ui"),
                              # Info text
                              div(id = "roster_info_text", style = "color: #888; font-size: 11px; font-style: italic; margin-top: 5px;",
                                  "Select an opponent team to auto-populate pitchers from 2026 data, or add pitchers manually.")
                          )
                   )
                 ),
                 
                 # ---- Existing pitcher roles section (for scouting notes) ----
                 fluidRow(
                   column(12,
                          h5("Pitcher Roles", style = "color: darkcyan; margin-bottom: 5px; margin-top: 10px;"),
                          uiOutput("pitcher_roles_ui")
                   )
                 )
             ),
             
             # Pitcher Header Stats
             div(class = "stats-header", style = "padding: 8px 15px; margin-top: 15px;",
                 fluidRow(
                   column(6, h4(textOutput("charts_pitcher_name"), style = "margin: 0;")),
                   column(6, align = "right", 
                          span(textOutput("charts_pitcher_hand"), style = "font-weight: bold;")
                   )
                 )
             ),
             
             # Stats GT Table (3 rows like PDF)
             div(class = "chart-box", style = "padding: 8px; margin-bottom: 10px;",
                 gt::gt_output("pitcher_stats_gt")
             ),
             
             # Row 1: Arm Angle + Movement Chart
             fluidRow(
               column(4,
                      div(class = "chart-box",
                          div(class = "chart-box-title", "Arm Angle"),
                          plotOutput("pdf_arm_angle_preview", height = 250)
                      ),
                      div(class = "chart-box",
                          div(class = "chart-box-title", "Delivery Notes"),
                          div(class = "pdf-notes-input",
                              textAreaInput("pdf_delivery_notes", label = NULL,
                                            placeholder = "Mechanics, tendencies, arm action...",
                                            rows = 3, width = "100%"))
                      )
               ),
               column(8,
                      div(class = "chart-box",
                          div(class = "chart-box-title", "Pitch Movement"),
                          
                          # ===== MOVEMENT PLOT CUSTOMIZATION OPTIONS =====
                          div(class = "mvmt-options",
                              fluidRow(
                                column(3,
                                       checkboxInput("mvmt_show_arm_rays", "Arm Angle Rays", value = TRUE)
                                ),
                                column(3,
                                       checkboxInput("mvmt_show_arm_annotation", "Arm Angle Label", value = TRUE)
                                ),
                                column(3,
                                       selectInput("mvmt_marker_style", "Markers:",
                                                   choices = c("Scaled by Usage" = "scaled_usage",
                                                               "Average (Fixed)" = "average",
                                                               "None" = "none"),
                                                   selected = "scaled_usage", width = "100%")
                                ),
                                column(3,
                                       checkboxInput("mvmt_show_pitches", "Individual Pitches", value = TRUE)
                                )
                              ),
                              fluidRow(
                                column(3,
                                       checkboxInput("mvmt_show_expected", "Expected Movement", value = TRUE)
                                ),
                                column(9,
                                       div(style = "font-size: 10px; color: #666; padding-top: 8px;",
                                           "Diamonds = expected movement for release height | Rays show release point by pitch type")
                                )
                              ),
                              # Pitch Type Filter Row
                              fluidRow(
                                column(12,
                                       div(style = "margin-top: 8px; padding-top: 8px; border-top: 1px solid rgba(0,139,139,.2);",
                                           tags$label("Pitch Types:", style = "font-weight: 700; color: #006F71; margin-right: 10px;"),
                                           uiOutput("mvmt_pitch_type_filter_ui", inline = TRUE)
                                       )
                                )
                              )
                          ),
                          
                          # The movement plot
                          plotOutput("pdf_movement_preview", height = "600px", width = "100%")
                      )
               )
             ),
             
             div(class = "chart-box",
                 div(class = "chart-box-title", style = "background: linear-gradient(90deg, #2E7D32, #E1463E); color: white; padding: 8px; margin: -10px -10px 10px -10px; border-radius: 10px 10px 0 0;", 
                     "Go Zones / No Zones"),
                 p(style = "color: #666; font-size: 12px; margin-bottom: 10px;", 
                   "Zone approach notes for each batter handedness (used in condensed reports)"),
                 fluidRow(
                   column(6,
                          div(style = "border: 2px solid #00840D; border-radius: 8px; padding: 10px; margin-bottom: 10px;",
                              h5("Go Zones", style = "color: #00840D; font-weight: bold; margin-top: 0;"),
                              textInput("go_zones_rhh", "RHH:", 
                                        placeholder = "e.g., Middle Away", width = "100%"),
                              textInput("go_zones_lhh", "LHH:", 
                                        placeholder = "e.g., Away", width = "100%")
                          )
                   ),
                   column(6,
                          div(style = "border: 2px solid #E1463E; border-radius: 8px; padding: 10px; margin-bottom: 10px;",
                              h5("No Zones", style = "color: #E1463E; font-weight: bold; margin-top: 0;"),
                              textInput("no_zones_rhh", "RHH:", 
                                        placeholder = "e.g., FB U/A, SL", width = "100%"),
                              textInput("no_zones_lhh", "LHH:", 
                                        placeholder = "e.g., FB U/A, SL", width = "100%")
                          )
                   )
                 )
             ),
             
             # Scouting Notes Section
             div(class = "chart-box",
                 div(class = "chart-box-title", "Scouting Notes"),
                 fluidRow(
                   column(3,
                          div(class = "pdf-notes-input",
                              textAreaInput("pdf_matchup_notes", "Matchup Notes:",
                                            placeholder = "Key matchup tendencies, game plan...",
                                            rows = 3, width = "100%"))
                   ),
                   column(3,
                          div(class = "pdf-notes-input",
                              textAreaInput("pdf_stamina_notes", "Stamina/Usage Notes:",
                                            placeholder = "Pitch count limits, fatigue patterns...",
                                            rows = 3, width = "100%"))
                   ),
                   column(3,
                          div(class = "pdf-notes-input",
                              textAreaInput("pdf_vs_lhh_notes", "vs LHH Notes:",
                                            placeholder = "Approach vs left-handed hitters...",
                                            rows = 3, width = "100%"))
                   ),
                   column(3,
                          div(class = "pdf-notes-input",
                              textAreaInput("pdf_vs_rhh_notes", "vs RHH Notes:",
                                            placeholder = "Approach vs right-handed hitters...",
                                            rows = 3, width = "100%"))
                   )
                 )
             ),
             
             # Download Buttons
             div(style = "text-align: center; margin: 20px 0;",
                 actionButton("save_pitcher_notes", "Save Notes", class = "btn-teal", style = "margin-right: 15px;"),
                 downloadButton("download_pdf_with_notes", "Download Current PDF", class = "btn-bronze", style = "margin-right: 15px;"),
                 downloadButton("download_series_zip", "Download All (ZIP)", class = "btn-teal", style = "margin-right: 15px;"),
                 downloadButton("download_condensed_report", "Condensed Report (1-Page)", class = "btn-bronze")
             ),
    ),  
    
    # ===== BULLPEN REPORT TAB =====
    tabPanel("Bullpen Report", value = "bullpen",
             
             # Header
             div(class = "stats-header", style = "background: linear-gradient(135deg, #1565C0, #42A5F5);",
                 h3("Auto Bullpen Report"),
                 p("Generate bullpen usage and role reports for upcoming series")
             ),
             
             # Settings Row
             div(class = "input-row",
                 fluidRow(
                   column(3, 
                          textInput("bullpen_title", "Report Title:", 
                                    placeholder = "e.g., Auto Bullpen Report: 2/13 - 2/16", width = "100%")),
                   column(3, 
                          selectizeInput("bullpen_pitchers", "Select Bullpen Arms:", 
                                         choices = NULL, multiple = TRUE,
                                         options = list(placeholder = "Select pitchers..."), width = "100%")),
                   column(2,
                          dateInput("bullpen_date", "As of Date:", value = Sys.Date(), width = "100%")),
                   column(2,
                          selectInput("rolling_stat1", "Rolling Chart 1:", 
                                      choices = c("Velo" = "velo", "Strike%" = "strike", "wOBA" = "woba", 
                                                  "Stuff+" = "stuff_plus"), selected = "velo", width = "100%")),
                   column(2,
                          selectInput("rolling_stat2", "Rolling Chart 2:", 
                                      choices = c("Velo" = "velo", "Strike%" = "strike", "wOBA" = "woba", 
                                                  "Stuff+" = "stuff_plus"), selected = "strike", width = "100%"))
                 ),
                 fluidRow(
                   column(12, style = "text-align: center; margin-top: 10px;",
                          downloadButton("download_bullpen_pdf", "Download Report", class = "btn-teal"))
                 )
             ),
             
             # Pitcher Roles Table
             div(class = "chart-box",
                 div(class = "chart-box-title", "Bullpen Roles & Assignments"),
                 uiOutput("bullpen_roles_table_ui")
             ),
             
             # Usage Charts Row
             fluidRow(
               column(6,
                      div(class = "chart-box",
                          div(class = "chart-box-title", "Pitch Count Usage (Last 1 Week vs Last 2 Weeks)"),
                          plotOutput("bullpen_usage_chart", height = 280)
                      )
               ),
               column(6,
                      div(class = "chart-box",
                          div(class = "chart-box-title", "Usage by Inning"),
                          plotOutput("bullpen_inning_heatmap", height = 280)
                      )
               )
             ),
             
             # Rolling Line Charts Row
             fluidRow(
               column(6,
                      div(class = "chart-box",
                          div(class = "chart-box-title", textOutput("rolling_chart1_title")),
                          plotOutput("bullpen_rolling_chart1", height = 280)
                      )
               ),
               column(6,
                      div(class = "chart-box",
                          div(class = "chart-box-title", textOutput("rolling_chart2_title")),
                          plotOutput("bullpen_rolling_chart2", height = 280)
                      )
               )
             ),
             
             # Stats Summary
             div(class = "chart-box",
                 div(class = "chart-box-title", "Bullpen Summary Stats"),
                 gt::gt_output("bullpen_summary_table")
             )
    )
  )
)

ui <- fluidPage(uiOutput("mainUI"))

# ============================================================================
# SERVER
# ============================================================================

server <- function(input, output, session) {
  
  data_2026_rv <- reactiveVal(data_2026)
  
  authed <- reactiveVal(FALSE)
  observeEvent(input$login, {
    if (!nzchar(PASSWORD)) {
      authed(TRUE)
      output$wrong_pass <- renderText("")
    } else if (identical(input$password, PASSWORD)) {
      authed(TRUE)
      output$wrong_pass <- renderText("")
    } else {
      authed(FALSE)
      output$wrong_pass <- renderText("Incorrect password.")
    }
  })
  output$mainUI <- renderUI({
    if (isTRUE(authed())) app_ui else login_ui
  })
  
  #==============
  #MAKE THE 2026 DATA REFRESHABLE
  #===============
  
  observeEvent(input$refresh_data, {
    tryCatch({
      showNotification("Refreshing data from HuggingFace...", type = "message", duration = 3)
      new_data <- download_private_parquet("CoastalBaseball/2026MasterDataset", "pbp_2026_master.parquet")
      new_data <- new_data %>%
        mutate(
          PlateLocSide = PlateLocSide / 12,
          PlateLocHeight = PlateLocHeight / 12
        ) %>%
        dplyr::select(any_of(cols_to_select)) %>%
        collect_df()
      new_data <- clean_data(new_data)
      new_data$Date <- as.Date(new_data$Date)
      data_2026_rv(new_data)
      
      all_pitchers_2026 <<- sort(unique(new_data$Pitcher[!is.na(new_data$Pitcher) & new_data$Pitcher != ""]))
      all_pitchers_combined <<- sort(unique(c(all_pitchers_2025, all_pitchers_2026)))
      
      showNotification(paste0("Data refreshed! ", nrow(new_data), " rows loaded."), type = "message")
    }, error = function(e) {
      showNotification(paste("Refresh failed:", e$message), type = "error")
    })
  })
  
  # =========================================================================
  # GLOBAL DATA SOURCE REACTIVE - the single source of truth for all data
  # =========================================================================
  
  exp_movement_grid <- reactive({
    tryCatch(
      build_expected_movement_grid(base_data()),
      error = function(e) { cat("Warning: Could not build expected movement grid -", e$message, "\n"); NULL }
    )
  })
  
  base_data <- reactive({
    sources <- input$data_source
    
    if (is.null(sources) || length(sources) == 0) {
      return(bind_rows(tm_data %>% mutate(Date = as.Date(Date)),
                       data_2026_rv() %>% mutate(Date = as.Date(Date))))
    }
    
    if (all(c("2025", "2026") %in% sources)) {
      bind_rows(tm_data %>% mutate(Date = as.Date(Date)),
                data_2026_rv() %>% mutate(Date = as.Date(Date)))
    } else if ("2025" %in% sources) {
      tm_data
    } else if ("2026" %in% sources) {
      data_2026_rv()
    } else {
      bind_rows(tm_data %>% mutate(Date = as.Date(Date)),
                data_2026_rv() %>% mutate(Date = as.Date(Date)))
    }
  })
  
  # Reactive pitcher list that updates when data source changes
  available_pitchers <- reactive({
    current_2026 <- data_2026_rv()
    sources <- input$data_source
    
    p_2025 <- sort(unique(tm_data$Pitcher[!is.na(tm_data$Pitcher) & tm_data$Pitcher != ""]))
    p_2026 <- sort(unique(current_2026$Pitcher[!is.na(current_2026$Pitcher) & current_2026$Pitcher != ""]))
    p_combined <- sort(unique(c(p_2025, p_2026)))
    
    if (is.null(sources) || length(sources) == 0) return(p_combined)
    if (all(c("2025", "2026") %in% sources)) p_combined
    else if ("2025" %in% sources) p_2025
    else if ("2026" %in% sources) p_2026
    else p_combined
  })
  
  # ===== UPDATE PITCHER DROPDOWNS WHEN DATA SOURCE CHANGES =====
  observeEvent(available_pitchers(), {
    req(authed())
    pitchers <- available_pitchers()
    req(length(pitchers) > 0)
    
    # Preserve current selection if still valid
    current_main <- input$main_pitcher
    new_main <- if (!is.null(current_main) && current_main %in% pitchers) current_main else pitchers[1]
    
    updateSelectInput(session, "main_pitcher",
                      choices = pitchers,
                      selected = new_main)
    
    updateSelectizeInput(session, "series_pitchers",
                         choices = pitchers)
    
    updateSelectizeInput(session, "bullpen_pitchers",
                         choices = pitchers)
  })
  
  # ===== UPDATE INPUTS ON FIRST AUTH =====
  observeEvent(authed(), {
    req(authed())
    pitchers <- available_pitchers()
    req(length(pitchers) > 0)
    
    cat("Updating pitcher dropdowns with", length(pitchers), "pitchers\n")
    
    updateSelectInput(session, "main_pitcher", 
                      choices = pitchers,
                      selected = pitchers[1])
    
    updateSelectizeInput(session, "series_pitchers", 
                         choices = pitchers)
    
    updateSelectizeInput(session, "bullpen_pitchers",
                         choices = pitchers)
  }, ignoreInit = TRUE, once = TRUE)
  
  
  current_pitcher_reactive <- reactive({
    req(authed())
    
    if (!is.null(input$active_pitcher) && nchar(trimws(input$active_pitcher)) > 0) {
      return(input$active_pitcher)
    }
    if (!is.null(input$main_pitcher) && nchar(trimws(input$main_pitcher)) > 0) {
      return(input$main_pitcher)
    }
    pitchers <- available_pitchers()
    if (length(pitchers) > 0) {
      return(pitchers[1])
    }
    NULL
  })
  
  
  # ===== FILTERED DATA (uses base_data instead of tm_data) =====
  filtered_data <- reactive({
    data <- base_data()
    
    batter_sides <- input$batter_side_filter
    if (!is.null(batter_sides) && length(batter_sides) > 0 && "BatterSide" %in% names(data)) {
      data <- data %>% filter(BatterSide %in% batter_sides)
    }
    
    start_date <- input$date_filter_start
    end_date <- input$date_filter_end
    
    if (!is.null(start_date) && !is.na(start_date) && "Date" %in% names(data)) {
      data <- data %>% filter(as.Date(Date) >= start_date)
    }
    if (!is.null(end_date) && !is.na(end_date) && "Date" %in% names(data)) {
      data <- data %>% filter(as.Date(Date) <= end_date)
    }
    
    data
  })
  
  # ===== UPDATE DATE FILTERS BASED ON PITCHER'S DATA =====
  observe({
    current_pitcher <- current_pitcher_reactive()
    req(current_pitcher)
    
    # NEW: Get the full dataset date range for min/max constraints
    all_dates <- base_data() %>%
      filter(!is.na(Date)) %>%
      summarise(
        global_min = min(as.Date(Date), na.rm = TRUE),
        global_max = max(as.Date(Date), na.rm = TRUE)
      )
    
    pitcher_dates <- base_data() %>%
      filter(Pitcher == current_pitcher, !is.na(Date)) %>%
      summarise(
        min_date = min(as.Date(Date), na.rm = TRUE),
        max_date = max(as.Date(Date), na.rm = TRUE)
      )
    
    if (nrow(pitcher_dates) > 0 && !is.na(pitcher_dates$min_date[1])) {
      updateDateInput(session, "date_filter_start", 
                      value = pitcher_dates$min_date[1],
                      min = all_dates$global_min[1],      
                      max = all_dates$global_max[1])    
      updateDateInput(session, "date_filter_end", 
                      value = pitcher_dates$max_date[1],
                      min = all_dates$global_min[1],     
                      max = all_dates$global_max[1])  
    }
  })
  
  
  # ===== PITCHER STATS REACTIVE =====
  pitcher_stats <- reactive({
    current_pitcher <- current_pitcher_reactive()
    req(current_pitcher)
    data <- filtered_data()
    req(data)
    req(nrow(data) > 0)
    calculate_pitcher_stats(data, current_pitcher)
  })
  
  # ===== ADVANCED STATS REACTIVE (uses base_data) =====
  advanced_stats <- reactive({
    current_pitcher <- current_pitcher_reactive()
    req(current_pitcher)
    tryCatch(
      calculate_advanced_pitcher_stats(base_data(), current_pitcher),
      error = function(e) NULL
    )
  })
  
  # ===== HEADER OUTPUTS =====
  output$current_pitcher_header <- renderText({
    current_pitcher <- current_pitcher_reactive()
    if (is.null(current_pitcher)) "Select a Pitcher" else current_pitcher
  })
  
  output$charts_pitcher_name <- renderText({
    current_pitcher <- current_pitcher_reactive()
    if (is.null(current_pitcher)) "Select a Pitcher" else current_pitcher
  })
  
  output$charts_pitcher_hand <- renderText({
    current_pitcher <- current_pitcher_reactive()
    req(current_pitcher)
    data <- filtered_data()
    pitcher_data <- data %>% filter(Pitcher == current_pitcher)
    if (nrow(pitcher_data) > 0 && "PitcherThrows" %in% names(pitcher_data)) {
      paste0(pitcher_data$PitcherThrows[1], "-Handed Pitcher")
    } else {
      ""
    }
  })
  
  observe({
    req(authed())
    if (nrow(teams_data) > 0) {
      team_choices <- c("-- Select Team --" = "", sort(teams_data$team_name))
      updateSelectInput(session, "opponent_team", choices = team_choices)
    }
  })
  
  # Add team color preview output:
  output$team_color_preview <- renderUI({
    team_name <- input$opponent_team
    if (is.null(team_name) || team_name == "") {
      return(div(style = "padding-top: 25px; color: gray; font-style: italic;",
                 "Select a team to preview colors and logos"))
    }
    
    info <- get_team_info(team_name)
    
    div(style = "display: flex; align-items: center; gap: 15px; padding-top: 10px;",
        # Team logo preview
        if (nchar(info$team_logo) > 0) {
          tags$img(src = info$team_logo, height = "40px",
                   onerror = "this.style.display='none'")
        },
        # Color swatches
        div(style = paste0("width: 30px; height: 30px; border-radius: 4px; border: 1px solid #ccc; background: ", info$primary_color, ";")),
        div(style = paste0("width: 30px; height: 30px; border-radius: 4px; border: 1px solid #ccc; background: ", info$secondary_color, ";")),
        # Info text
        div(
          div(style = "font-weight: bold; font-size: 13px;", info$team_name),
          div(style = "font-size: 11px; color: #666;",
              paste0(info$league, " | ", info$trackman_abbr))
        )
    )
  })
  
  pitcher_roster <- reactiveVal(data.frame(
    Pitcher = character(),
    Number = character(),
    Class = character(),
    Hand = character(),
    Pitches_2026 = integer(),
    stringsAsFactors = FALSE
  ))
  
  # Populate the "Add pitcher manually" dropdown with all pitchers in the data
  observe({
    req(authed())
    d <- base_data()
    if (!is.null(d) && nrow(d) > 0) {
      all_pitchers <- sort(unique(d$Pitcher[!is.na(d$Pitcher)]))
      updateSelectizeInput(session, "add_pitcher_manual",
                           choices = c("Select pitcher..." = "", all_pitchers),
                           server = TRUE)
    }
  })
  
  # AUTO-POPULATE: When opponent team changes, find their 2026 pitchers
  observeEvent(input$opponent_team, {
    team_name <- input$opponent_team
    if (is.null(team_name) || team_name == "") return()
    
    info <- get_team_info(team_name)
    if (nchar(info$trackman_abbr) == 0) {
      showNotification(paste0("Could not find TrackMan abbreviation for ", team_name),
                       type = "warning", duration = 4)
      return()
    }
    
    d <- base_data()
    if (is.null(d) || nrow(d) == 0) return()
    
    team_abbr <- info$trackman_abbr
    team_pitchers_data <- d %>%
      dplyr::filter(
        PitcherTeam == team_abbr,
        !is.na(Pitcher),
        !is.na(Date)
      ) %>%
      dplyr::mutate(Year = as.integer(format(as.Date(Date), "%Y"))) %>%
      dplyr::filter(Year == 2026)
    
    if (nrow(team_pitchers_data) == 0) {
      showNotification(paste0("No 2026 pitch data found for ", team_name, " (", team_abbr, ")"),
                       type = "warning", duration = 5)
      return()
    }
    
    roster_summary <- team_pitchers_data %>%
      dplyr::group_by(Pitcher) %>%
      dplyr::summarise(
        Pitches_2026 = dplyr::n(),
        Hand = dplyr::first(PitcherThrows[!is.na(PitcherThrows)]),
        .groups = "drop"
      ) %>%
      dplyr::arrange(dplyr::desc(Pitches_2026)) %>%
      dplyr::mutate(
        Number = "",
        Class = "",
        Hand = ifelse(is.na(Hand), "R", Hand)
      ) %>%
      dplyr::select(Pitcher, Number, Class, Hand, Pitches_2026)
    
    pitcher_roster(as.data.frame(roster_summary))
    
    showNotification(
      paste0("Found ", nrow(roster_summary), " pitchers for ", team_name, " in 2026 data"),
      type = "message", duration = 4
    )
  }, ignoreInit = TRUE)
  
  # ADD PITCHER MANUALLY
  observeEvent(input$btn_add_pitcher, {
    pitcher_to_add <- input$add_pitcher_manual
    if (is.null(pitcher_to_add) || pitcher_to_add == "") return()
    
    current <- pitcher_roster()
    
    if (pitcher_to_add %in% current$Pitcher) {
      showNotification(paste0(pitcher_to_add, " is already in the roster"), type = "warning", duration = 3)
      return()
    }
    
    d <- base_data()
    p_info <- data.frame(Pitcher = pitcher_to_add, Number = "", Class = "",
                         Hand = "R", Pitches_2026 = 0L, stringsAsFactors = FALSE)
    if (!is.null(d) && nrow(d) > 0) {
      p_data <- d %>% dplyr::filter(Pitcher == pitcher_to_add)
      if (nrow(p_data) > 0) {
        p_info$Hand <- dplyr::first(p_data$PitcherThrows[!is.na(p_data$PitcherThrows)]) %||% "R"
        p_data_2026 <- p_data %>%
          dplyr::filter(as.integer(format(as.Date(Date), "%Y")) == 2026)
        p_info$Pitches_2026 <- nrow(p_data_2026)
      }
    }
    
    pitcher_roster(rbind(current, p_info))
    updateSelectizeInput(session, "add_pitcher_manual", selected = "")
  })
  
  # CLEAR ALL PITCHERS
  observeEvent(input$btn_clear_roster, {
    pitcher_roster(data.frame(
      Pitcher = character(), Number = character(), Class = character(),
      Hand = character(), Pitches_2026 = integer(), stringsAsFactors = FALSE
    ))
  })
  
  # RENDER THE PITCHER ROSTER TABLE
  output$pitcher_roster_ui <- renderUI({
    roster <- pitcher_roster()
    
    if (nrow(roster) == 0) {
      return(div(style = "color: #999; padding: 10px; text-align: center; border: 1px dashed #ccc; border-radius: 6px;",
                 "No pitchers in roster. Select an opponent team or add pitchers manually."))
    }
    
    # Get base data to find each pitcher's pitch types
    bd <- tryCatch(base_data(), error = function(e) NULL)
    
    header <- div(style = "display: grid; grid-template-columns: 40px 50px 2fr 80px 80px 60px 60px 50px; gap: 4px; padding: 4px 0; border-bottom: 2px solid darkcyan; font-weight: bold; font-size: 12px; color: darkcyan;",
                  div(""), div("Hand"), div("Pitcher Name"), div("Number"), div("Class"), div("Pitches"), div("Order"), div("")
    )
    
    rows <- lapply(seq_len(nrow(roster)), function(i) {
      p <- roster[i, ]
      p_safe <- gsub("[^a-zA-Z0-9]", "_", p$Pitcher)
      hand_color <- if (p$Hand == "Left") "#E53935" else "#1E88E5"
      hand_label <- if (p$Hand == "Left") "LHP" else "RHP"
      
      # Get this pitcher's pitch types from the data
      pitcher_pitches <- character(0)
      if (!is.null(bd) && nrow(bd) > 0) {
        p_data <- bd %>% dplyr::filter(Pitcher == p$Pitcher, !is.na(TaggedPitchType), TaggedPitchType != "Other")
        if (nrow(p_data) > 0) {
          pitch_counts <- p_data %>%
            dplyr::count(TaggedPitchType, sort = TRUE) %>%
            dplyr::mutate(pct = 100 * n / sum(n)) %>%
            dplyr::filter(pct >= 3)
          pitcher_pitches <- pitch_counts$TaggedPitchType
        }
      }
      
      # Build per-pitch shape note inputs
      shape_inputs <- if (length(pitcher_pitches) > 0) {
        pitch_divs <- lapply(pitcher_pitches, function(pt) {
          pt_safe <- gsub("[^a-zA-Z0-9]", "_", pt)
          pt_short <- dplyr::case_when(
            pt == "Fastball" ~ "FB", pt == "Sinker" ~ "SI", pt == "Slider" ~ "SL",
            pt == "Curveball" ~ "CB", pt == "ChangeUp" ~ "CH", pt == "Cutter" ~ "CT",
            pt == "Sweeper" ~ "SW", pt == "Splitter" ~ "SP", pt == "Knuckle Curve" ~ "KC",
            pt == "FourSeamFastBall" ~ "FF", pt == "TwoSeamFastBall" ~ "2S",
            TRUE ~ substr(pt, 1, 2)
          )
          pt_color <- pitch_colors[[pt]]
          if (is.null(pt_color)) pt_color <- "#888888"
          
          div(style = "display: flex; align-items: center; gap: 4px; margin-bottom: 2px;",
              span(pt_short,
                   style = paste0("background: ", pt_color, "; color: white; padding: 1px 6px; ",
                                  "border-radius: 3px; font-size: 10px; font-weight: bold; ",
                                  "min-width: 28px; text-align: center; display: inline-block;")),
              textInput(paste0("roster_shape_", p_safe, "_", pt_safe), NULL,
                        value = "", placeholder = "1-2 words",
                        width = "110px")
          )
        })
        div(style = "display: flex; flex-wrap: wrap; gap: 2px 12px;", pitch_divs)
      } else {
        div(style = "color: #aaa; font-size: 10px; font-style: italic;", "No pitch data available")
      }
      
      tagList(
        # Main pitcher row
        div(style = paste0("display: grid; grid-template-columns: 40px 50px 2fr 80px 80px 60px 60px 50px; gap: 4px; padding: 6px 0 2px 0; align-items: center;",
                           if (i %% 2 == 0) " background: #f9f9f9;" else ""),
            div(actionButton(paste0("rm_pitcher_", i), "\u2716",
                             style = "background: transparent; color: #E53935; border: 1px solid #E53935; border-radius: 50%; width: 24px; height: 24px; padding: 0; font-size: 12px; cursor: pointer;")),
            div(span(hand_label, style = paste0("background: ", hand_color, "; color: white; padding: 2px 6px; border-radius: 3px; font-size: 10px; font-weight: bold;"))),
            div(style = "font-weight: 600; font-size: 13px;", p$Pitcher),
            div(textInput(paste0("roster_num_", p_safe), NULL, value = p$Number, placeholder = "#", width = "70px")),
            div(selectInput(paste0("roster_class_", p_safe), NULL,
                            choices = c("Class" = "", "Fr." = "Fr.", "So." = "So.", "Jr." = "Jr.", "Sr." = "Sr.", "Gr." = "Gr.", "R-Fr." = "R-Fr.", "R-So." = "R-So.", "R-Jr." = "R-Jr.", "R-Sr." = "R-Sr."),
                            selected = p$Class, width = "75px")),
            div(style = "text-align: center; font-size: 12px; color: #666;",
                if (p$Pitches_2026 > 0) as.character(p$Pitches_2026) else "-"),
            div(style = "display: flex; gap: 2px;",
                if (i > 1) actionButton(paste0("mv_up_", i), "\u25B2",
                                        style = "background: transparent; border: 1px solid #ccc; border-radius: 3px; width: 22px; height: 20px; padding: 0; font-size: 9px; cursor: pointer;"),
                if (i < nrow(roster)) actionButton(paste0("mv_down_", i), "\u25BC",
                                                   style = "background: transparent; border: 1px solid #ccc; border-radius: 3px; width: 22px; height: 20px; padding: 0; font-size: 9px; cursor: pointer;")
            ),
            div("")
        ),
        # Sub-row: Per-pitch shape notes + Go/No zones
        div(style = paste0("display: grid; grid-template-columns: 40px 1fr 1fr 1fr; gap: 8px; padding: 0 0 8px 0; border-bottom: 1px solid #eee; align-items: start;",
                           if (i %% 2 == 0) " background: #f9f9f9;" else ""),
            div(""),
            # Per-pitch shape notes
            div(style = "margin-top: -6px;",
                tags$label(style = "font-size: 10px; color: #555; font-weight: 600; margin-bottom: 2px; display: block;",
                           "\U0001F3AF Pitch Shape Notes"),
                shape_inputs
            ),
            # Go Zones
            div(style = "margin-top: -6px;",
                tags$label(style = "font-size: 10px; color: #00840D; font-weight: 600; margin-bottom: 1px; display: block;",
                           "\u2705 Go Zones"),
                textInput(paste0("roster_go_", p_safe), NULL,
                          value = "", placeholder = "RHH: mid-away, LHH: down-in",
                          width = "100%")
            ),
            # No Zones
            div(style = "margin-top: -6px;",
                tags$label(style = "font-size: 10px; color: #E1463E; font-weight: 600; margin-bottom: 1px; display: block;",
                           "\u26D4 No Zones"),
                textInput(paste0("roster_no_", p_safe), NULL,
                          value = "", placeholder = "RHH: FB up/away, LHH: SL",
                          width = "100%")
            )
        )
      )
    })
    
    n <- nrow(roster)
    for (i in seq_len(n)) {
      local({
        idx <- i
        observeEvent(input[[paste0("rm_pitcher_", idx)]], {
          current <- pitcher_roster()
          if (idx <= nrow(current)) pitcher_roster(current[-idx, , drop = FALSE])
        }, ignoreInit = TRUE, once = TRUE)
      })
    }
    for (i in 2:max(n, 2)) {
      local({
        idx <- i
        observeEvent(input[[paste0("mv_up_", idx)]], {
          current <- pitcher_roster()
          if (idx <= nrow(current) && idx > 1) {
            swap <- current[c(idx-1, idx), ]
            current[c(idx-1, idx), ] <- swap[c(2, 1), ]
            pitcher_roster(current)
          }
        }, ignoreInit = TRUE, once = TRUE)
      })
    }
    for (i in seq_len(max(n - 1, 1))) {
      local({
        idx <- i
        observeEvent(input[[paste0("mv_down_", idx)]], {
          current <- pitcher_roster()
          if (idx < nrow(current)) {
            swap <- current[c(idx, idx+1), ]
            current[c(idx, idx+1), ] <- swap[c(2, 1), ]
            pitcher_roster(current)
          }
        }, ignoreInit = TRUE, once = TRUE)
      })
    }
    
    count_text <- div(style = "display: flex; justify-content: space-between; margin-top: 6px; font-size: 11px; color: #666;",
                      span(paste0(nrow(roster), " pitcher(s) in roster")),
                      span(paste0("Pages needed: ", ceiling(nrow(roster) / 5)))
    )
    
    tagList(header, rows, count_text)
  })
  
  # Keep series_pitchers in sync with roster (backward compat)
  observe({
    roster <- pitcher_roster()
    if (nrow(roster) > 0) {
      updateSelectizeInput(session, "series_pitchers",
                           choices = roster$Pitcher,
                           selected = roster$Pitcher)
    }
  })
  
  # ===== STAT BOX OUTPUTS =====
  output$stat_pitches <- renderText({
    stats <- tryCatch(pitcher_stats(), error = function(e) NULL)
    if (!is.null(stats) && !is.null(stats$overall)) as.character(stats$overall$n_pitches) else "-"
  })
  
  output$stat_strike <- renderText({
    stats <- tryCatch(pitcher_stats(), error = function(e) NULL)
    if (!is.null(stats) && !is.null(stats$overall)) paste0(round(stats$overall$strike_pct, 1), "%") else "-"
  })
  
  output$stat_whiff <- renderText({
    adv_stats <- advanced_stats()
    if (!is.null(adv_stats)) paste0(adv_stats$whiff_pct, "%") else "-"
  })
  
  output$stat_zone <- renderText({
    adv_stats <- advanced_stats()
    if (!is.null(adv_stats)) paste0(adv_stats$zone_pct, "%") else "-"
  })
  
  output$stat_k <- renderText({
    adv_stats <- advanced_stats()
    if (!is.null(adv_stats)) paste0(adv_stats$k_pct, "%") else "-"
  })
  
  output$stat_bb <- renderText({
    adv_stats <- advanced_stats()
    if (!is.null(adv_stats)) paste0(adv_stats$bb_pct, "%") else "-"
  })
  
  output$stat_ip <- renderText({
    adv_stats <- advanced_stats()
    if (!is.null(adv_stats)) sprintf("%.1f", adv_stats$ip) else "-"
  })
  
  output$stat_games <- renderText({
    adv_stats <- advanced_stats()
    if (!is.null(adv_stats)) as.character(adv_stats$n_games) else "-"
  })
  
  output$stat_ra9 <- renderText({
    adv_stats <- advanced_stats()
    if (!is.null(adv_stats)) as.character(adv_stats$ra9) else "-"
  })
  
  output$stat_k9 <- renderText({
    adv_stats <- advanced_stats()
    if (!is.null(adv_stats) && !is.null(adv_stats$ip) && adv_stats$ip > 0) {
      as.character(round(adv_stats$k_pct * 9 / 100, 1))
    } else "-"
  })
  
  output$stat_bb9 <- renderText({
    adv_stats <- advanced_stats()
    if (!is.null(adv_stats)) {
      as.character(round(adv_stats$bb_pct * 9 / 100, 1))
    } else "-"
  })
  
  output$stat_fb_velo <- renderText({
    current_pitcher <- current_pitcher_reactive()
    req(current_pitcher)
    fb_data <- base_data() %>%
      filter(Pitcher == current_pitcher,
             TaggedPitchType %in% c("Fastball", "Four-Seam", "FourSeamFastBall", "Sinker", "Two-Seam", "TwoSeamFastBall"),
             !is.na(RelSpeed))
    if (nrow(fb_data) > 0) {
      paste0(round(mean(fb_data$RelSpeed, na.rm = TRUE), 1))
    } else "-"
  })
  
  output$stat_k_pct <- renderText({
    adv_stats <- advanced_stats()
    if (!is.null(adv_stats)) paste0(adv_stats$k_pct, "%") else "-"
  })
  
  output$stat_bb_pct <- renderText({
    adv_stats <- advanced_stats()
    if (!is.null(adv_stats)) paste0(adv_stats$bb_pct, "%") else "-"
  })
  
  output$stat_csw <- renderText({
    current_pitcher <- current_pitcher_reactive()
    req(current_pitcher)
    p_data <- base_data() %>% filter(Pitcher == current_pitcher)
    if (nrow(p_data) > 0) {
      csw <- sum(p_data$PitchCall %in% c("StrikeCalled", "StrikeSwinging"), na.rm = TRUE) / nrow(p_data) * 100
      paste0(round(csw, 1), "%")
    } else "-"
  })
  
  output$stat_fip <- renderText({
    adv_stats <- advanced_stats()
    if (!is.null(adv_stats)) as.character(adv_stats$fip) else "-"
  })
  
  output$stat_whip <- renderText({
    adv_stats <- advanced_stats()
    if (!is.null(adv_stats)) as.character(adv_stats$whip) else "-"
  })
  
  output$stat_ba_l <- renderText({
    adv_stats <- advanced_stats()
    if (!is.null(adv_stats)) as.character(adv_stats$ba_vs_l) else "-"
  })
  
  output$stat_ba_r <- renderText({
    adv_stats <- advanced_stats()
    if (!is.null(adv_stats)) as.character(adv_stats$ba_vs_r) else "-"
  })
  
  output$mvmt_pitch_type_filter_ui <- renderUI({
    current_pitcher <- if (!is.null(input$active_pitcher) && input$active_pitcher != "") {
      input$active_pitcher
    } else {
      current_pitcher_reactive()
    }
    
    if (is.null(current_pitcher) || current_pitcher == "") {
      return(span("Select a pitcher", style = "color: gray; font-style: italic;"))
    }
    
    data <- filtered_data()
    
    pitcher_pitches <- data %>%
      filter(Pitcher == current_pitcher, 
             !is.na(TaggedPitchType), 
             TaggedPitchType != "Other",
             !is.na(HorzBreak), !is.na(InducedVertBreak)) %>%
      count(TaggedPitchType) %>%
      filter(n >= 3) %>%
      arrange(desc(n))
    
    if (nrow(pitcher_pitches) == 0) {
      return(span("No pitch data", style = "color: gray;"))
    }
    
    choices <- setNames(pitcher_pitches$TaggedPitchType, 
                        paste0(pitcher_pitches$TaggedPitchType, " (", pitcher_pitches$n, ")"))
    selected <- pitcher_pitches$TaggedPitchType
    
    checkboxGroupInput("mvmt_pitch_types", 
                       label = NULL,
                       choices = choices,
                       selected = selected,
                       inline = TRUE)
  })
  
  # ===== PITCHER STATS GT TABLE =====
  output$pitcher_stats_gt <- gt::render_gt({
    adv_stats <- advanced_stats()
    if (is.null(adv_stats)) {
      return(gt::gt(data.frame(Message = "Select a pitcher")) %>%
               gt::tab_options(table.font.size = gt::px(11)))
    }
    
    combined <- data.frame(
      Stat = c("IP", "G", "IP/G", "P/G", "Last 3", "RA9", "FIP", "WHIP", "K%", "BB%", 
               "BA L", "BA R", "SLG L", "SLG R", "Whiff%", "Zone%", "Strike%", "FB Str%", "BB Str%", "OS Str%"),
      Value = c(adv_stats$ip, adv_stats$n_games, adv_stats$avg_ip, adv_stats$avg_pitches, 
                adv_stats$last_3_outings, adv_stats$ra9, adv_stats$fip, adv_stats$whip,
                paste0(adv_stats$k_pct, "%"), paste0(adv_stats$bb_pct, "%"),
                adv_stats$ba_vs_l, adv_stats$ba_vs_r, adv_stats$slg_vs_l, adv_stats$slg_vs_r,
                paste0(adv_stats$whiff_pct, "%"), paste0(adv_stats$zone_pct, "%"), 
                paste0(adv_stats$strike_pct, "%"), paste0(adv_stats$fb_strike_pct, "%"),
                paste0(adv_stats$bb_strike_pct, "%"), paste0(adv_stats$os_strike_pct, "%"))
    )
    
    wide_df <- as.data.frame(t(combined$Value))
    names(wide_df) <- combined$Stat
    
    gt::gt(wide_df) %>%
      gt::tab_style(style = list(gt::cell_fill(color = "#006F71"), gt::cell_text(color = "white", weight = "bold", size = gt::px(10))),
                    locations = gt::cells_column_labels()) %>%
      gt::cols_align(align = "center") %>%
      gt::tab_options(table.font.size = gt::px(11), data_row.padding = gt::px(8),
                      column_labels.padding = gt::px(4), table.width = gt::pct(100))
  })
  
  # ===== HEATMAP OUTPUTS (use base_data) =====
  output$hm_fb_lhh <- renderPlot({
    req(current_pitcher_reactive())
    create_pitch_group_heatmap(base_data(), current_pitcher_reactive(), "FB", "All", "Left")
  }, bg = "transparent")
  
  output$hm_fb_rhh <- renderPlot({
    req(current_pitcher_reactive())
    create_pitch_group_heatmap(base_data(), current_pitcher_reactive(), "FB", "All", "Right")
  }, bg = "transparent")
  
  output$hm_os_lhh <- renderPlot({
    req(current_pitcher_reactive())
    create_pitch_group_heatmap(base_data(), current_pitcher_reactive(), "OS", "All", "Left")
  }, bg = "transparent")
  
  output$hm_os_rhh <- renderPlot({
    req(current_pitcher_reactive())
    create_pitch_group_heatmap(base_data(), current_pitcher_reactive(), "OS", "All", "Right")
  }, bg = "transparent")
  
  # ===== FACETED HEATMAP OUTPUTS (use base_data) =====
  output$faceted_hm_fb_lhh <- renderPlot({
    req(current_pitcher_reactive())
    create_location_by_result_faceted(base_data(), current_pitcher_reactive(), "Fastballs", "Left")
  }, bg = "transparent")
  
  output$faceted_hm_fb_rhh <- renderPlot({
    req(current_pitcher_reactive())
    create_location_by_result_faceted(base_data(), current_pitcher_reactive(), "Fastballs", "Right")
  }, bg = "transparent")
  
  output$faceted_hm_os_lhh <- renderPlot({
    req(current_pitcher_reactive())
    create_location_by_result_faceted(base_data(), current_pitcher_reactive(), "Offspeed", "Left")
  }, bg = "transparent")
  
  output$faceted_hm_os_rhh <- renderPlot({
    req(current_pitcher_reactive())
    create_location_by_result_faceted(base_data(), current_pitcher_reactive(), "Offspeed", "Right")
  }, bg = "transparent")
  
  # Series pitchers dropdown
  observe({
    req(authed())
    updateSelectizeInput(session, "series_pitchers",
                         choices = available_pitchers())
  })
  
  # ===== SERIES PITCHERS SYNC =====
  observeEvent(input$series_pitchers, {
    pitchers <- input$series_pitchers
    if (!is.null(pitchers) && length(pitchers) > 0) {
      updateSelectInput(session, "active_pitcher",
                        choices = pitchers,
                        selected = pitchers[1])
    }
  })
  
  # ===== NOTES STORAGE FOR MULTIPLE PITCHERS =====
  pitcher_notes_storage <- reactiveVal(list())
  pitcher_roles <- reactiveVal(list())
  
  # Save notes for current pitcher
  observeEvent(input$save_pitcher_notes, {
    current_pitcher <- current_pitcher_reactive()
    
    if (is.null(current_pitcher) || current_pitcher == "") {
      showNotification("No pitcher selected", type = "error")
      return()
    }
    
    storage <- pitcher_notes_storage()
    
    # Get pitcher number and class from dynamic inputs
    p_safe <- gsub("[^a-zA-Z0-9]", "_", current_pitcher)
    p_number <- input[[paste0("num_", p_safe)]] %||% ""
    p_class  <- input[[paste0("class_", p_safe)]] %||% ""
    
    storage[[current_pitcher]] <- list(
      number = p_number,
      class = p_class,
      delivery_notes = input$pdf_delivery_notes,
      matchup_notes = input$pdf_matchup_notes,
      stamina_notes = input$pdf_stamina_notes,
      vs_lhh_notes = input$pdf_vs_lhh_notes,
      vs_rhh_notes = input$pdf_vs_rhh_notes,
      go_zones_rhh = input$go_zones_rhh,
      go_zones_lhh = input$go_zones_lhh,
      no_zones_rhh = input$no_zones_rhh,
      no_zones_lhh = input$no_zones_lhh,
      pitch_notes = get_dynamic_pitch_notes(),
      shape_notes = get_shape_notes()
    )
    
    pitcher_notes_storage(storage)
    showNotification(paste("Notes saved for", current_pitcher), type = "message", duration = 2)
  })
  
  
  # Helper function to get pitch notes from dynamic inputs
  get_dynamic_pitch_notes <- function() {
    notes <- list()
    current_pitcher <- current_pitcher_reactive()
    if (is.null(current_pitcher) || current_pitcher == "") return(notes)
    
    pitcher_pitches <- base_data() %>%
      filter(Pitcher == current_pitcher, !is.na(TaggedPitchType), TaggedPitchType != "Other") %>%
      count(TaggedPitchType) %>%
      filter(n >= 10) %>%
      arrange(desc(n)) %>%
      pull(TaggedPitchType)
    
    for (pt in pitcher_pitches) {
      input_id <- paste0("pdf_note_", gsub("[^a-zA-Z]", "", tolower(pt)))
      if (!is.null(input[[input_id]])) {
        notes[[pt]] <- input[[input_id]]
      }
    }
    notes
  }
  
  # Helper function to get shape notes from dynamic inputs
  get_shape_notes <- function() {
    notes <- list()
    current_pitcher <- current_pitcher_reactive()
    if (is.null(current_pitcher) || current_pitcher == "") return(notes)
    
    pitcher_pitches <- base_data() %>%
      filter(Pitcher == current_pitcher, !is.na(TaggedPitchType), TaggedPitchType != "Other") %>%
      count(TaggedPitchType) %>%
      filter(n >= 10) %>%
      arrange(desc(n)) %>%
      pull(TaggedPitchType)
    
    for (pt in pitcher_pitches) {
      input_id <- paste0("shape_note_", gsub("[^a-zA-Z]", "", tolower(pt)))
      if (!is.null(input[[input_id]])) {
        notes[[pt]] <- input[[input_id]]
      }
    }
    notes
  }
  
  # Load notes when switching pitchers
  observeEvent(input$active_pitcher, {
    current_pitcher <- input$active_pitcher
    if (is.null(current_pitcher) || current_pitcher == "") return()
    
    storage <- pitcher_notes_storage()
    
    if (current_pitcher %in% names(storage)) {
      saved <- storage[[current_pitcher]]
      updateTextAreaInput(session, "pdf_delivery_notes", value = saved$delivery_notes %||% "")
      updateTextAreaInput(session, "pdf_matchup_notes", value = saved$matchup_notes %||% "")
      updateTextAreaInput(session, "pdf_stamina_notes", value = saved$stamina_notes %||% "")
      updateTextAreaInput(session, "pdf_vs_lhh_notes", value = saved$vs_lhh_notes %||% "")
      updateTextAreaInput(session, "pdf_vs_rhh_notes", value = saved$vs_rhh_notes %||% "")
      # Load Go Zones / No Zones
      updateTextInput(session, "go_zones_rhh", value = saved$go_zones_rhh %||% "")
      updateTextInput(session, "go_zones_lhh", value = saved$go_zones_lhh %||% "")
      updateTextInput(session, "no_zones_rhh", value = saved$no_zones_rhh %||% "")
      updateTextInput(session, "no_zones_lhh", value = saved$no_zones_lhh %||% "")
    } else {
      updateTextAreaInput(session, "pdf_delivery_notes", value = "")
      updateTextAreaInput(session, "pdf_matchup_notes", value = "")
      updateTextAreaInput(session, "pdf_stamina_notes", value = "")
      updateTextAreaInput(session, "pdf_vs_lhh_notes", value = "")
      updateTextAreaInput(session, "pdf_vs_rhh_notes", value = "")
      updateTextInput(session, "go_zones_rhh", value = "")
      updateTextInput(session, "go_zones_lhh", value = "")
      updateTextInput(session, "no_zones_rhh", value = "")
      updateTextInput(session, "no_zones_lhh", value = "")
    }
  })
  
  output$pitcher_roles_ui <- renderUI({
    pitchers <- input$series_pitchers
    if (is.null(pitchers) || length(pitchers) == 0) {
      return(p("Select pitchers above to assign numbers and classes", style = "color: gray;"))
    }
    
    class_choices <- c("", "FR", "SO", "JR", "SR", "GR", "RS FR", "RS SO", "RS JR", "RS SR")
    
    # Load saved values
    storage <- pitcher_notes_storage()
    
    fluidRow(
      lapply(pitchers, function(p) {
        saved <- storage[[p]]
        saved_number <- saved$number %||% ""
        saved_class <- saved$class %||% ""
        
        p_safe <- gsub("[^a-zA-Z0-9]", "_", p)
        
        column(2,
               div(style = "border: 1px solid #ddd; border-radius: 6px; padding: 6px; margin-bottom: 5px; background: #fafafa;",
                   tags$label(substr(p, 1, 18), style = "font-size: 11px; font-weight: bold; display: block; margin-bottom: 3px; color: #333;"),
                   fluidRow(
                     column(5, 
                            textInput(paste0("num_", p_safe), label = NULL,
                                      value = saved_number,
                                      placeholder = "#",
                                      width = "100%")
                     ),
                     column(7,
                            selectInput(paste0("class_", p_safe), label = NULL,
                                        choices = class_choices,
                                        selected = saved_class,
                                        width = "100%")
                     )
                   )
               )
        )
      })
    )
  })
  
  # ===== PITCH TYPE FILTER UI =====
  output$pitch_type_filter_ui <- renderUI({
    current_pitcher <- if (!is.null(input$active_pitcher) && input$active_pitcher != "") {
      input$active_pitcher
    } else if (!is.null(input$series_pitchers) && length(input$series_pitchers) > 0) {
      input$series_pitchers[1]
    } else {
      NULL
    }
    
    if (is.null(current_pitcher)) {
      return(p("Select a pitcher to filter pitch types", style = "color: gray; font-style: italic;"))
    }
    
    pitcher_pitches <- base_data() %>%
      filter(Pitcher == current_pitcher, !is.na(TaggedPitchType), TaggedPitchType != "Other") %>%
      count(TaggedPitchType) %>%
      arrange(desc(n))
    
    if (nrow(pitcher_pitches) == 0) {
      return(p("No pitch data available", style = "color: gray;"))
    }
    
    choices <- setNames(pitcher_pitches$TaggedPitchType, 
                        paste0(pitcher_pitches$TaggedPitchType, " (", pitcher_pitches$n, ")"))
    selected <- pitcher_pitches %>% filter(n >= 10) %>% pull(TaggedPitchType)
    
    checkboxGroupInput("pitch_type_filter", NULL,
                       choices = choices,
                       selected = selected,
                       inline = TRUE)
  })
  
  # ===== DYNAMIC PITCH NOTES UI =====
  output$dynamic_pitch_notes_ui <- renderUI({
    current_pitcher <- if (!is.null(input$active_pitcher) && input$active_pitcher != "") {
      input$active_pitcher
    } else {
      current_pitcher_reactive()
    }
    
    if (is.null(current_pitcher) || current_pitcher == "") {
      return(p("Select a pitcher to see pitch-specific notes", style = "color: gray;"))
    }
    
    pitcher_pitches <- base_data() %>%
      filter(Pitcher == current_pitcher, !is.na(TaggedPitchType), TaggedPitchType != "Other") %>%
      count(TaggedPitchType) %>%
      filter(n >= 10) %>%
      arrange(desc(n)) %>%
      pull(TaggedPitchType)
    
    if (length(pitcher_pitches) == 0) {
      return(p("No pitch data available", style = "color: gray;"))
    }
    
    col_width <- max(2, floor(12 / length(pitcher_pitches)))
    
    storage <- pitcher_notes_storage()
    saved_notes <- if (current_pitcher %in% names(storage)) storage[[current_pitcher]]$pitch_notes else list()
    
    fluidRow(
      lapply(pitcher_pitches, function(pt) {
        input_id <- paste0("pdf_note_", gsub("[^a-zA-Z]", "", tolower(pt)))
        saved_value <- saved_notes[[pt]] %||% ""
        
        column(col_width,
               div(class = "pitch-notes-input",
                   textAreaInput(input_id, paste0(pt, " Notes:"),
                                 value = saved_value,
                                 placeholder = paste0(pt, " notes..."),
                                 rows = 3, width = "100%"))
        )
      })
    )
  })
  
  # ===== SHAPE NOTES UI FOR CONDENSED REPORT =====
  output$shape_notes_ui <- renderUI({
    current_pitcher <- if (!is.null(input$active_pitcher) && input$active_pitcher != "") {
      input$active_pitcher
    } else {
      current_pitcher_reactive()
    }
    
    if (is.null(current_pitcher) || current_pitcher == "") {
      return(p("Select a pitcher to add shape notes", style = "color: gray; font-style: italic;"))
    }
    
    pitcher_pitches <- base_data() %>%
      filter(Pitcher == current_pitcher, !is.na(TaggedPitchType), TaggedPitchType != "Other") %>%
      group_by(TaggedPitchType) %>%
      summarise(
        n = n(),
        velo_low = round(quantile(RelSpeed, 0.1, na.rm = TRUE), 0),
        velo_high = round(quantile(RelSpeed, 0.9, na.rm = TRUE), 0),
        .groups = "drop"
      ) %>%
      filter(n >= 10) %>%
      arrange(desc(n))
    
    if (nrow(pitcher_pitches) == 0) {
      return(p("No pitch data available", style = "color: gray;"))
    }
    
    storage <- pitcher_notes_storage()
    saved_shape_notes <- if (current_pitcher %in% names(storage)) storage[[current_pitcher]]$shape_notes else list()
    
    tagList(
      fluidRow(
        column(2, tags$strong("Pitch Type", style = "font-size: 12px;")),
        column(2, tags$strong("Velo Range", style = "font-size: 12px;")),
        column(8, tags$strong("Shape Notes", style = "font-size: 12px;"))
      ),
      hr(style = "margin: 5px 0;"),
      lapply(1:nrow(pitcher_pitches), function(i) {
        pt <- pitcher_pitches$TaggedPitchType[i]
        input_id <- paste0("shape_note_", gsub("[^a-zA-Z]", "", tolower(pt)))
        saved_value <- saved_shape_notes[[pt]] %||% ""
        pt_color <- pitch_colors[[pt]] %||% "gray50"
        
        fluidRow(
          style = "margin-bottom: 8px; padding: 5px; background: #f8f9fa; border-radius: 5px;",
          column(2, 
                 div(style = paste0("background: ", pt_color, "; color: white; padding: 4px 8px; border-radius: 4px; text-align: center; font-weight: bold; font-size: 11px;"),
                     pt)
          ),
          column(2, 
                 div(style = "padding-top: 5px; font-size: 12px; color: #333;",
                     paste0(pitcher_pitches$velo_low[i], "-", pitcher_pitches$velo_high[i], " mph"))
          ),
          column(8,
                 textInput(input_id, label = NULL, 
                           value = saved_value,
                           placeholder = paste0("e.g., RIDE, SWEEP, 12-6, FADE+SINK..."),
                           width = "100%")
          )
        )
      })
    )
  })
  
  output$pitcher_report_date <- renderText({
    format(Sys.Date(), "%B %d, %Y")
  })
  
  output$pitcher_hand_display <- renderText({
    req(current_pitcher_reactive())
    req(current_pitcher_reactive() != "")
    data <- tryCatch(filtered_data(), error = function(e) NULL)
    if (is.null(data)) return("Unknown")
    
    pitcher_data <- data %>% filter(Pitcher == current_pitcher_reactive())
    if (nrow(pitcher_data) > 0 && "PitcherThrows" %in% names(pitcher_data) && !is.na(pitcher_data$PitcherThrows[1])) {
      paste0(pitcher_data$PitcherThrows[1], "HP")
    } else {
      "Unknown"
    }
  })
  
  # ===== VALUE BOXES =====
  output$vb_pitches <- renderValueBox({
    stats <- tryCatch(pitcher_stats(), error = function(e) NULL)
    valueBox(
      if (!is.null(stats) && !is.null(stats$overall)) stats$overall$n_pitches else "-",
      "Pitches", icon = icon("baseball"), color = "teal"
    )
  })
  
  output$vb_strike_pct <- renderValueBox({
    stats <- tryCatch(pitcher_stats(), error = function(e) NULL)
    valueBox(
      if (!is.null(stats) && !is.null(stats$overall)) paste0(round(stats$overall$strike_pct, 1), "%") else "-",
      "Strike%", icon = icon("bullseye"), color = "green"
    )
  })
  
  output$vb_whiff_pct <- renderValueBox({
    stats <- tryCatch(pitcher_stats(), error = function(e) NULL)
    valueBox(
      if (!is.null(stats) && !is.null(stats$overall)) paste0(round(stats$overall$whiff_pct, 1), "%") else "-",
      "Whiff%", icon = icon("wind"), color = "orange"
    )
  })
  
  output$vb_zone_pct <- renderValueBox({
    stats <- tryCatch(pitcher_stats(), error = function(e) NULL)
    valueBox(
      if (!is.null(stats) && !is.null(stats$overall)) paste0(round(stats$overall$zone_pct, 1), "%") else "-",
      "Zone%", icon = icon("crosshairs"), color = "blue"
    )
  })
  
  output$vb_k_pct <- renderValueBox({
    stats <- tryCatch(pitcher_stats(), error = function(e) NULL)
    valueBox(
      if (!is.null(stats) && !is.null(stats$overall)) paste0(round(stats$overall$k_pct, 1), "%") else "-",
      "K%", icon = icon("k"), color = "red"
    )
  })
  
  output$vb_bb_pct <- renderValueBox({
    stats <- tryCatch(pitcher_stats(), error = function(e) NULL)
    valueBox(
      if (!is.null(stats) && !is.null(stats$overall)) paste0(round(stats$overall$bb_pct, 1), "%") else "-",
      "BB%", icon = icon("person-walking"), color = "yellow"
    )
  })
  
  # ===== MAIN REPORT PLOTS =====
  output$pitcher_report_arm_slot <- renderPlot({
    req(current_pitcher_reactive())
    req(nchar(current_pitcher_reactive()) > 0)
    data <- filtered_data()
    req(data)
    create_pitcher_arm_angle_plot(data, current_pitcher_reactive())
  }, bg = "transparent")
  
  output$pitcher_report_movement <- renderPlot({
    req(current_pitcher_reactive())
    req(nchar(current_pitcher_reactive()) > 0)
    data <- filtered_data()
    req(data)
    create_pitcher_movement_plot(data, current_pitcher_reactive(), exp_movement_grid())
  }, bg = "transparent")
  
  output$pitcher_report_count_usage <- renderPlot({
    req(current_pitcher_reactive())
    req(nchar(current_pitcher_reactive()) > 0)
    data <- filtered_data()
    req(data)
    create_count_usage_pies(data, current_pitcher_reactive())
  }, bg = "transparent")
  
  output$pitcher_report_characteristics_table <- gt::render_gt({
    req(current_pitcher_reactive())
    req(nchar(current_pitcher_reactive()) > 0)
    data <- filtered_data()
    req(data)
    create_pitch_characteristics_gt(data, current_pitcher_reactive())
  })
  
  # ===== LOCATION HEATMAPS =====
  output$pitcher_report_fb_lhh <- renderPlot({
    req(current_pitcher_reactive())
    req(nchar(current_pitcher_reactive()) > 0)
    data <- filtered_data()
    req(data)
    create_location_by_result_faceted(data, current_pitcher_reactive(), "Fastballs", "Left")
  }, bg = "transparent")
  
  output$pitcher_report_fb_rhh <- renderPlot({
    req(current_pitcher_reactive())
    req(nchar(current_pitcher_reactive()) > 0)
    data <- filtered_data()
    req(data)
    create_location_by_result_faceted(data, current_pitcher_reactive(), "Fastballs", "Right")
  }, bg = "transparent")
  
  output$pitcher_report_os_lhh <- renderPlot({
    req(current_pitcher_reactive())
    req(nchar(current_pitcher_reactive()) > 0)
    data <- filtered_data()
    req(data)
    create_location_by_result_faceted(data, current_pitcher_reactive(), "Offspeed", "Left")
  }, bg = "transparent")
  
  output$pitcher_report_os_rhh <- renderPlot({
    req(current_pitcher_reactive())
    req(nchar(current_pitcher_reactive()) > 0)
    data <- filtered_data()
    req(data)
    create_location_by_result_faceted(data, current_pitcher_reactive(), "Offspeed", "Right")
  }, bg = "transparent")
  
  
  # ===== PDF PREVIEW PLOTS =====
  output$pdf_movement_preview <- renderPlot({
    current_pitcher <- if (!is.null(input$active_pitcher) && input$active_pitcher != "") {
      input$active_pitcher
    } else {
      current_pitcher_reactive()
    }
    req(current_pitcher)
    req(nchar(current_pitcher) > 0)
    data <- filtered_data()
    req(data)
    
    show_arm_rays <- if (!is.null(input$mvmt_show_arm_rays)) input$mvmt_show_arm_rays else TRUE
    show_arm_annotation <- if (!is.null(input$mvmt_show_arm_annotation)) input$mvmt_show_arm_annotation else TRUE
    marker_style <- if (!is.null(input$mvmt_marker_style)) input$mvmt_marker_style else "scaled_usage"
    show_pitches <- if (!is.null(input$mvmt_show_pitches)) input$mvmt_show_pitches else TRUE
    show_expected <- if (!is.null(input$mvmt_show_expected)) input$mvmt_show_expected else TRUE
    selected_pitch_types <- input$mvmt_pitch_types
    
    create_pitcher_movement_plot(
      data = data, 
      pitcher_name = current_pitcher, 
      expected_grid = exp_movement_grid(),
      show_arm_angle_rays = show_arm_rays,
      show_arm_angle_annotation = show_arm_annotation,
      marker_style = marker_style,
      show_individual_pitches = show_pitches,
      show_expected_diamonds = show_expected,
      selected_pitch_types = selected_pitch_types
    )
  }, bg = "transparent")
  
  output$pdf_arm_angle_preview <- renderPlot({
    current_pitcher <- if (!is.null(input$active_pitcher) && input$active_pitcher != "") {
      input$active_pitcher
    } else {
      current_pitcher_reactive()
    }
    req(current_pitcher)
    req(nchar(current_pitcher) > 0)
    data <- filtered_data()
    req(data)
    create_pitcher_arm_angle_plot(data, current_pitcher)
  }, bg = "transparent")
  
  output$pdf_count_usage_preview <- renderPlot({
    current_pitcher <- if (!is.null(input$active_pitcher) && input$active_pitcher != "") {
      input$active_pitcher
    } else {
      current_pitcher_reactive()
    }
    req(current_pitcher)
    req(nchar(current_pitcher) > 0)
    data <- filtered_data()
    req(data)
    create_count_usage_pies(data, current_pitcher)
  }, bg = "transparent")
  
  output$pdf_pitch_characteristics_preview <- gt::render_gt({
    current_pitcher <- if (!is.null(input$active_pitcher) && input$active_pitcher != "") {
      input$active_pitcher
    } else {
      current_pitcher_reactive()
    }
    req(current_pitcher)
    req(nchar(current_pitcher) > 0)
    data <- filtered_data()
    req(data)
    create_pitch_characteristics_gt(data, current_pitcher)
  })
  
  # ===== SEQUENCING PREVIEWS =====
  output$pdf_seq_lhh_preview <- renderPlot({
    current_pitcher <- if (!is.null(input$active_pitcher) && input$active_pitcher != "") {
      input$active_pitcher
    } else {
      current_pitcher_reactive()
    }
    req(current_pitcher)
    req(nchar(current_pitcher) > 0)
    data <- filtered_data()
    req(data)
    create_sequencing_matrix(data, current_pitcher, "Left")
  }, bg = "transparent")
  
  output$pdf_seq_rhh_preview <- renderPlot({
    current_pitcher <- if (!is.null(input$active_pitcher) && input$active_pitcher != "") {
      input$active_pitcher
    } else {
      current_pitcher_reactive()
    }
    req(current_pitcher)
    req(nchar(current_pitcher) > 0)
    data <- filtered_data()
    req(data)
    create_sequencing_matrix(data, current_pitcher, "Right")
  }, bg = "transparent")
  
  # ===== HEATMAP PREVIEWS (use filtered_data) =====
  output$pdf_hm_fb_lhh <- renderPlot({
    current_pitcher <- if (!is.null(input$active_pitcher) && input$active_pitcher != "") input$active_pitcher else current_pitcher_reactive()
    req(current_pitcher)
    create_pitch_group_heatmap(filtered_data(), current_pitcher, "FB", "All", "Left")
  }, bg = "transparent")
  
  output$pdf_hm_bb_lhh <- renderPlot({
    current_pitcher <- if (!is.null(input$active_pitcher) && input$active_pitcher != "") input$active_pitcher else current_pitcher_reactive()
    req(current_pitcher)
    create_pitch_group_heatmap(filtered_data(), current_pitcher, "BB", "All", "Left")
  }, bg = "transparent")
  
  output$pdf_hm_os_lhh <- renderPlot({
    current_pitcher <- if (!is.null(input$active_pitcher) && input$active_pitcher != "") input$active_pitcher else current_pitcher_reactive()
    req(current_pitcher)
    create_pitch_group_heatmap(filtered_data(), current_pitcher, "OS", "All", "Left")
  }, bg = "transparent")
  
  output$pdf_hm_fb_rhh <- renderPlot({
    current_pitcher <- if (!is.null(input$active_pitcher) && input$active_pitcher != "") input$active_pitcher else current_pitcher_reactive()
    req(current_pitcher)
    create_pitch_group_heatmap(filtered_data(), current_pitcher, "FB", "All", "Right")
  }, bg = "transparent")
  
  output$pdf_hm_bb_rhh <- renderPlot({
    current_pitcher <- if (!is.null(input$active_pitcher) && input$active_pitcher != "") input$active_pitcher else current_pitcher_reactive()
    req(current_pitcher)
    create_pitch_group_heatmap(filtered_data(), current_pitcher, "BB", "All", "Right")
  }, bg = "transparent")
  
  output$pdf_hm_os_rhh <- renderPlot({
    current_pitcher <- if (!is.null(input$active_pitcher) && input$active_pitcher != "") input$active_pitcher else current_pitcher_reactive()
    req(current_pitcher)
    create_pitch_group_heatmap(filtered_data(), current_pitcher, "OS", "All", "Right")
  }, bg = "transparent")
  
  # ===== DAMAGE AND WHIFF HEATMAPS =====
  output$pdf_damage_lhh <- renderPlot({
    current_pitcher <- if (!is.null(input$active_pitcher) && input$active_pitcher != "") input$active_pitcher else current_pitcher_reactive()
    req(current_pitcher)
    create_pitch_group_heatmap(filtered_data(), current_pitcher, "All", "Dmg", "Left")
  }, bg = "transparent")
  
  output$pdf_damage_rhh <- renderPlot({
    current_pitcher <- if (!is.null(input$active_pitcher) && input$active_pitcher != "") input$active_pitcher else current_pitcher_reactive()
    req(current_pitcher)
    create_pitch_group_heatmap(filtered_data(), current_pitcher, "All", "Dmg", "Right")
  }, bg = "transparent")
  
  output$pdf_whiff_lhh <- renderPlot({
    current_pitcher <- if (!is.null(input$active_pitcher) && input$active_pitcher != "") input$active_pitcher else current_pitcher_reactive()
    req(current_pitcher)
    create_pitch_group_heatmap(filtered_data(), current_pitcher, "All", "Whf", "Left")
  }, bg = "transparent")
  
  output$pdf_whiff_rhh <- renderPlot({
    current_pitcher <- if (!is.null(input$active_pitcher) && input$active_pitcher != "") input$active_pitcher else current_pitcher_reactive()
    req(current_pitcher)
    create_pitch_group_heatmap(filtered_data(), current_pitcher, "All", "Whf", "Right")
  }, bg = "transparent")
  
  # ===== COUNT-BASED HEATMAPS UI =====
  output$pdf_count_heatmaps_ui <- renderUI({
    current_pitcher <- if (!is.null(input$active_pitcher) && input$active_pitcher != "") input$active_pitcher else current_pitcher_reactive()
    if (is.null(current_pitcher) || current_pitcher == "") return(NULL)
    
    pitcher_data <- base_data() %>%
      filter(Pitcher == current_pitcher, !is.na(TaggedPitchType), TaggedPitchType != "Other")
    
    if (nrow(pitcher_data) < 50) return(p("Not enough data for count heatmaps"))
    
    top_pitches <- pitcher_data %>%
      count(TaggedPitchType) %>%
      arrange(desc(n)) %>%
      head(2) %>%
      pull(TaggedPitchType)
    
    pitch_short <- sapply(top_pitches, function(p) {
      case_when(
        p %in% c("Fastball", "Four-Seam") ~ "FB",
        p == "Sinker" ~ "SI",
        p %in% c("Slider", "Sweeper") ~ "SL",
        p == "Curveball" ~ "CB",
        p %in% c("Changeup", "ChangeUp") ~ "CH",
        p == "Cutter" ~ "CT",
        TRUE ~ substr(p, 1, 2)
      )
    })
    
    tagList(
      lapply(seq_along(top_pitches), function(i) {
        pt <- top_pitches[i]
        ps <- pitch_short[i]
        fluidRow(
          column(4,
                 div(style = "text-align: center; font-size: 10px; font-weight: bold;", paste0("Ahead ", ps)),
                 plotOutput(paste0("pdf_count_hm_ahead_", i), height = 100)
          ),
          column(4,
                 div(style = "text-align: center; font-size: 10px; font-weight: bold;", paste0("Early ", ps)),
                 plotOutput(paste0("pdf_count_hm_early_", i), height = 100)
          ),
          column(4,
                 div(style = "text-align: center; font-size: 10px; font-weight: bold;", paste0("2-Strike ", ps)),
                 plotOutput(paste0("pdf_count_hm_2k_", i), height = 100)
          )
        )
      })
    )
  })
  
  # Dynamic count heatmap outputs (use base_data)
  observe({
    current_pitcher <- if (!is.null(input$active_pitcher) && input$active_pitcher != "") input$active_pitcher else current_pitcher_reactive()
    if (is.null(current_pitcher) || current_pitcher == "") return()
    
    pitcher_data <- base_data() %>%
      filter(Pitcher == current_pitcher, !is.na(TaggedPitchType), TaggedPitchType != "Other")
    
    if (nrow(pitcher_data) < 50) return()
    
    top_pitches <- pitcher_data %>%
      count(TaggedPitchType) %>%
      arrange(desc(n)) %>%
      head(2) %>%
      pull(TaggedPitchType)
    
    for (i in seq_along(top_pitches)) {
      local({
        idx <- i
        pt <- top_pitches[idx]
        
        output[[paste0("pdf_count_hm_ahead_", idx)]] <- renderPlot({
          p_data <- pitcher_data %>%
            filter(TaggedPitchType == pt,
                   (Balls == 0 & Strikes >= 1) | (Balls == 1 & Strikes == 2),
                   !is.na(PlateLocSide), !is.na(PlateLocHeight))
          
          if (nrow(p_data) < 10) {
            return(ggplot() + theme_void() + annotate("text", x = 0, y = 2, label = "Low n", size = 3))
          }
          
          ggplot(p_data, aes(x = PlateLocSide, y = PlateLocHeight)) +
            stat_density_2d(aes(fill = after_stat(density)), geom = "raster", contour = FALSE) +
            scale_fill_gradientn(colours = c("white", "blue", "#FF9999", "red", "darkred")) +
            annotate("rect", xmin = -0.83, xmax = 0.83, ymin = 1.5, ymax = 3.5, fill = NA, color = "black", linewidth = 0.6) +
            annotate("path", x = c(-0.708, 0.708, 0.708, 0, -0.708, -0.708),
                     y = c(0.15, 0.15, 0.3, 0.5, 0.3, 0.15), color = "black", linewidth = 0.5) +
            coord_fixed(xlim = c(-2, 2), ylim = c(0, 4.5)) +
            theme_void() + theme(legend.position = "none")
        }, bg = "transparent")
        
        output[[paste0("pdf_count_hm_early_", idx)]] <- renderPlot({
          p_data <- pitcher_data %>%
            filter(TaggedPitchType == pt,
                   Balls <= 1 & Strikes <= 1,
                   !is.na(PlateLocSide), !is.na(PlateLocHeight))
          
          if (nrow(p_data) < 10) {
            return(ggplot() + theme_void() + annotate("text", x = 0, y = 2, label = "Low n", size = 3))
          }
          
          ggplot(p_data, aes(x = PlateLocSide, y = PlateLocHeight)) +
            stat_density_2d(aes(fill = after_stat(density)), geom = "raster", contour = FALSE) +
            scale_fill_gradientn(colours = c("white", "blue", "#FF9999", "red", "darkred")) +
            annotate("rect", xmin = -0.83, xmax = 0.83, ymin = 1.5, ymax = 3.5, fill = NA, color = "black", linewidth = 0.6) +
            annotate("path", x = c(-0.708, 0.708, 0.708, 0, -0.708, -0.708),
                     y = c(0.15, 0.15, 0.3, 0.5, 0.3, 0.15), color = "black", linewidth = 0.5) +
            coord_fixed(xlim = c(-2, 2), ylim = c(0, 4.5)) +
            theme_void() + theme(legend.position = "none")
        }, bg = "transparent")
        
        output[[paste0("pdf_count_hm_2k_", idx)]] <- renderPlot({
          p_data <- pitcher_data %>%
            filter(TaggedPitchType == pt, Strikes == 2,
                   !is.na(PlateLocSide), !is.na(PlateLocHeight))
          
          if (nrow(p_data) < 10) {
            return(ggplot() + theme_void() + annotate("text", x = 0, y = 2, label = "Low n", size = 3))
          }
          
          ggplot(p_data, aes(x = PlateLocSide, y = PlateLocHeight)) +
            stat_density_2d(aes(fill = after_stat(density)), geom = "raster", contour = FALSE) +
            scale_fill_gradientn(colours = c("white", "blue", "#FF9999", "red", "darkred")) +
            annotate("rect", xmin = -0.83, xmax = 0.83, ymin = 1.5, ymax = 3.5, fill = NA, color = "black", linewidth = 0.6) +
            annotate("path", x = c(-0.708, 0.708, 0.708, 0, -0.708, -0.708),
                     y = c(0.15, 0.15, 0.3, 0.5, 0.3, 0.15), color = "black", linewidth = 0.5) +
            coord_fixed(xlim = c(-2, 2), ylim = c(0, 4.5)) +
            theme_void() + theme(legend.position = "none")
        }, bg = "transparent")
      })
    }
  })
  
  # ===== SINGLE PDF DOWNLOAD (uses base_data) =====
  output$download_single_pdf <- downloadHandler(
    filename = function() {
      current_pitcher <- current_pitcher_reactive()
      req(current_pitcher)
      pitcher_clean <- gsub(" ", "_", current_pitcher)
      paste0(pitcher_clean, "_Scouting_Report_", format(Sys.Date(), "%Y%m%d"), ".pdf")
    },
    content = function(file) {
      current_pitcher <- current_pitcher_reactive()
      req(current_pitcher)
      
      withProgress(message = "Generating PDF...", value = 0, {
        tryCatch({
          create_comprehensive_pitcher_pdf(base_data(), current_pitcher, file)
          incProgress(1)
        }, error = function(e) {
          showNotification(paste("Error:", e$message), type = "error")
        })
      })
    },
    contentType = "application/pdf"
  )
  
  # ===== PDF DOWNLOAD WITH NOTES (uses base_data) =====
  output$download_pdf_with_notes <- downloadHandler(
    filename = function() {
      current_pitcher <- if (!is.null(input$active_pitcher) && input$active_pitcher != "") input$active_pitcher else current_pitcher_reactive()
      req(current_pitcher)
      pitcher_clean <- gsub(" ", "_", current_pitcher)
      paste0(pitcher_clean, "_Scouting_Report_", format(Sys.Date(), "%Y%m%d"), ".pdf")
    },
    content = function(file) {
      current_pitcher <- if (!is.null(input$active_pitcher) && input$active_pitcher != "") input$active_pitcher else current_pitcher_reactive()
      req(current_pitcher)
      
      pitch_notes <- get_dynamic_pitch_notes()
      
      delivery_notes <- if (!is.null(input$pdf_delivery_notes)) input$pdf_delivery_notes else ""
      count_usage_notes <- if (!is.null(input$pdf_count_usage_notes)) input$pdf_count_usage_notes else ""
      overall_notes <- if (!is.null(input$pdf_overall_notes)) input$pdf_overall_notes else ""
      vs_lhh_notes <- if (!is.null(input$pdf_vs_lhh_notes)) input$pdf_vs_lhh_notes else ""
      vs_rhh_notes <- if (!is.null(input$pdf_vs_rhh_notes)) input$pdf_vs_rhh_notes else ""
      series_title <- if (!is.null(input$series_title)) input$series_title else ""
      
      role_input_id <- paste0("role_", gsub("[^a-zA-Z0-9]", "_", current_pitcher))
      pitcher_role <- if (!is.null(input[[role_input_id]])) input[[role_input_id]] else ""
      
      withProgress(message = 'Generating PDF with Notes', value = 0, {
        incProgress(0.2, detail = "Processing data...")
        incProgress(0.3, detail = "Creating visualizations...")
        
        create_comprehensive_pitcher_pdf(
          data = base_data(), 
          pitcher_name = current_pitcher, 
          output_file = file,
          delivery_notes = delivery_notes,
          count_usage_notes = count_usage_notes,
          pitch_notes = pitch_notes,
          overall_notes = overall_notes,
          vs_lhh_notes = vs_lhh_notes,
          vs_rhh_notes = vs_rhh_notes,
          series_title = series_title,
          pitcher_role = pitcher_role,
          matchup_matrix = NULL
        )
        
        incProgress(0.5, detail = "Finalizing report...")
      })
      
      showNotification("PDF with Notes generated!", type = "message", duration = 3)
    },
    contentType = "application/pdf"
  )
  
  # ===== SERIES ZIP DOWNLOAD (uses base_data) =====
  output$download_series_zip <- downloadHandler(
    filename = function() {
      series_title <- if (!is.null(input$series_title) && nchar(input$series_title) > 0) {
        gsub("[^a-zA-Z0-9]", "_", input$series_title)
      } else {
        "Scouting_Reports"
      }
      paste0(series_title, "_", format(Sys.Date(), "%Y%m%d"), ".zip")
    },
    content = function(file) {
      pitchers <- input$series_pitchers
      if (is.null(pitchers) || length(pitchers) == 0) {
        pitchers <- current_pitcher_reactive()
      }
      
      if (is.null(pitchers) || length(pitchers) == 0) {
        showNotification("No pitchers selected for series", type = "error")
        return(NULL)
      }
      
      series_title <- if (!is.null(input$series_title)) input$series_title else ""
      storage <- pitcher_notes_storage()
      
      temp_dir <- tempdir()
      pdf_files <- c()
      
      withProgress(message = 'Generating Series PDFs', value = 0, {
        for (i in seq_along(pitchers)) {
          pitcher <- pitchers[i]
          incProgress(1/length(pitchers), detail = paste("Creating", pitcher, "..."))
          
          if (pitcher %in% names(storage)) {
            saved <- storage[[pitcher]]
            delivery_notes <- saved$delivery_notes %||% ""
            count_usage_notes <- saved$count_usage_notes %||% ""
            overall_notes <- saved$overall_notes %||% ""
            vs_lhh_notes <- saved$vs_lhh_notes %||% ""
            vs_rhh_notes <- saved$vs_rhh_notes %||% ""
            pitch_notes <- saved$pitch_notes %||% list()
          } else {
            delivery_notes <- ""
            count_usage_notes <- ""
            overall_notes <- ""
            vs_lhh_notes <- ""
            vs_rhh_notes <- ""
            pitch_notes <- list()
          }
          
          role_input_id <- paste0("role_", gsub("[^a-zA-Z0-9]", "_", pitcher))
          pitcher_role <- if (!is.null(input[[role_input_id]])) input[[role_input_id]] else ""
          
          pitcher_clean <- gsub(" ", "_", pitcher)
          role_prefix <- if (nchar(pitcher_role) > 0) paste0(pitcher_role, "_") else ""
          pdf_filename <- file.path(temp_dir, paste0(role_prefix, pitcher_clean, "_Report.pdf"))
          
          tryCatch({
            create_comprehensive_pitcher_pdf(
              data = base_data(),
              pitcher_name = pitcher,
              output_file = pdf_filename,
              delivery_notes = delivery_notes,
              count_usage_notes = count_usage_notes,
              pitch_notes = pitch_notes,
              overall_notes = overall_notes,
              vs_lhh_notes = vs_lhh_notes,
              vs_rhh_notes = vs_rhh_notes,
              series_title = series_title,
              pitcher_role = pitcher_role
            )
            pdf_files <- c(pdf_files, pdf_filename)
          }, error = function(e) {
            showNotification(paste("Error creating PDF for", pitcher, ":", e$message), type = "warning")
          })
        }
      })
      
      if (length(pdf_files) > 0) {
        zip(file, pdf_files, flags = "-j")
        showNotification(paste("Created ZIP with", length(pdf_files), "reports"), type = "message", duration = 3)
      } else {
        showNotification("No PDFs were created", type = "error")
      }
    },
    contentType = "application/zip"
  )
  
  output$download_condensed_report <- downloadHandler(
    filename = function() {
      series_title <- if (!is.null(input$series_title) && nchar(input$series_title) > 0) {
        gsub("[^a-zA-Z0-9]", "_", input$series_title)
      } else {
        "Pitcher_Report"
      }
      paste0(series_title, "_Condensed_", format(Sys.Date(), "%Y%m%d"), ".pdf")
    },
    content = function(file) {
      roster <- pitcher_roster()
      
      if (nrow(roster) == 0) {
        showNotification("No pitchers in roster. Select an opponent team or add pitchers manually.", type = "error")
        return(NULL)
      }
      
      pitchers <- roster$Pitcher
      
      # Helper: parse "RHH: xxx, LHH: yyy" format into list(rhh, lhh)
      parse_zone_text <- function(raw_text) {
        rhh <- ""; lhh <- ""
        if (nchar(raw_text) > 0) {
          if (grepl("RHH:", raw_text, ignore.case = TRUE)) {
            rhh <- trimws(sub(".*RHH:\\s*([^,]+).*", "\\1", raw_text, ignore.case = TRUE))
          }
          if (grepl("LHH:", raw_text, ignore.case = TRUE)) {
            lhh <- trimws(sub(".*LHH:\\s*(.+)$", "\\1", raw_text, ignore.case = TRUE))
          }
          if (nchar(rhh) == 0 && nchar(lhh) == 0 && nchar(raw_text) > 0) {
            rhh <- raw_text; lhh <- raw_text
          }
        }
        list(rhh = rhh, lhh = lhh)
      }
      
      # Helper: map pitch abbreviation to full name
      pitch_abbrev_to_full <- function(abbrev) {
        dplyr::case_when(
          toupper(abbrev) %in% c("FB", "FF", "FASTBALL") ~ "Fastball",
          toupper(abbrev) %in% c("SI", "SNK", "SINKER") ~ "Sinker",
          toupper(abbrev) %in% c("SL", "SLIDER") ~ "Slider",
          toupper(abbrev) %in% c("CB", "CU", "CURVE", "CURVEBALL") ~ "Curveball",
          toupper(abbrev) %in% c("CH", "CHANGE", "CHANGEUP") ~ "ChangeUp",
          toupper(abbrev) %in% c("CT", "CUT", "FC", "CUTTER") ~ "Cutter",
          toupper(abbrev) %in% c("SW", "SWEEP", "SWEEPER") ~ "Sweeper",
          toupper(abbrev) %in% c("SP", "SPLIT", "SPLITTER") ~ "Splitter",
          toupper(abbrev) %in% c("KC", "KNUCKLE") ~ "Knuckle Curve",
          TRUE ~ abbrev
        )
      }
      
      # Get base data to find each pitcher's pitch types for per-pitch shape notes
      bd <- tryCatch(base_data(), error = function(e) NULL)
      
      withProgress(message = 'Generating Condensed Report...', value = 0, {
        pitcher_notes <- list()
        storage <- pitcher_notes_storage()
        for (i in seq_len(nrow(roster))) {
          pname <- roster$Pitcher[i]
          saved <- storage[[pname]]
          if (is.null(saved)) saved <- list()
          p_safe <- gsub("[^a-zA-Z0-9]", "_", pname)
          
          roster_num <- input[[paste0("roster_num_", p_safe)]]
          roster_class <- input[[paste0("roster_class_", p_safe)]]
          
          # Read roster-level go/no zone inputs
          roster_go_raw <- input[[paste0("roster_go_", p_safe)]] %||% ""
          roster_no_raw <- input[[paste0("roster_no_", p_safe)]] %||% ""
          go_parsed <- parse_zone_text(roster_go_raw)
          no_parsed <- parse_zone_text(roster_no_raw)
          
          # Read per-pitch shape notes from roster UI
          # Input IDs are: roster_shape_{p_safe}_{pt_safe}
          roster_shape_notes <- saved$shape_notes %||% list()
          if (!is.null(bd) && nrow(bd) > 0) {
            p_data <- bd %>% dplyr::filter(Pitcher == pname, !is.na(TaggedPitchType), TaggedPitchType != "Other")
            if (nrow(p_data) > 0) {
              pitch_types <- p_data %>%
                dplyr::count(TaggedPitchType, sort = TRUE) %>%
                dplyr::mutate(pct = 100 * n / sum(n)) %>%
                dplyr::filter(pct >= 3) %>%
                dplyr::pull(TaggedPitchType)
              
              for (pt in pitch_types) {
                pt_safe <- gsub("[^a-zA-Z0-9]", "_", pt)
                shape_val <- input[[paste0("roster_shape_", p_safe, "_", pt_safe)]] %||% ""
                if (nchar(shape_val) > 0) {
                  roster_shape_notes[[pt]] <- shape_val
                }
              }
            }
          }
          
          pitcher_notes[[pname]] <- list(
            number = roster_num %||% saved$number %||% input[[paste0("num_", p_safe)]] %||% "",
            class = roster_class %||% saved$class %||% input[[paste0("class_", p_safe)]] %||% "",
            matchup = saved$matchup_notes %||% "",
            vs_lhh = saved$vs_lhh_notes %||% "",
            vs_rhh = saved$vs_rhh_notes %||% "",
            go_zones_rhh = if (nchar(go_parsed$rhh) > 0) go_parsed$rhh else (saved$go_zones_rhh %||% ""),
            go_zones_lhh = if (nchar(go_parsed$lhh) > 0) go_parsed$lhh else (saved$go_zones_lhh %||% ""),
            no_zones_rhh = if (nchar(no_parsed$rhh) > 0) no_parsed$rhh else (saved$no_zones_rhh %||% ""),
            no_zones_lhh = if (nchar(no_parsed$lhh) > 0) no_parsed$lhh else (saved$no_zones_lhh %||% ""),
            shape_notes = roster_shape_notes
          )
          
          incProgress(0.3 / length(pitchers))
        }
        
        report_title <- if (!is.null(input$series_title) && nchar(input$series_title) > 0) {
          input$series_title
        } else {
          "Opposing Pitchers Report"
        }
        
        team_info <- NULL
        if (!is.null(input$opponent_team) && nchar(input$opponent_team) > 0) {
          team_info <- get_team_info(input$opponent_team)
          team_info$record <- input$opponent_record %||% ""
        }
        
        incProgress(0.3, detail = "Creating condensed report...")
        
        tryCatch({
          create_condensed_pitcher_report(
            data = base_data(),
            pitcher_names = pitchers,
            output_file = file,
            report_title = report_title,
            pitcher_notes = pitcher_notes,
            team_info = team_info
          )
          incProgress(0.4, detail = "Complete!")
          showNotification("Condensed report generated!", type = "message", duration = 3)
        }, error = function(e) {
          showNotification(paste("Error creating report:", e$message), type = "error")
        })
      })
    },
    contentType = "application/pdf"
  )
  
  
  # ===== PDF REPORTS TAB OUTPUTS =====
  output$pdf_pitcher_name <- renderText({
    if (is.null(current_pitcher_reactive()) || current_pitcher_reactive() == "") "None selected" else current_pitcher_reactive()
  })
  
  # Download handler for comprehensive PDF from sidebar
  output$download_comprehensive_pdf <- downloadHandler(
    filename = function() {
      req(current_pitcher_reactive())
      pitcher_clean <- gsub(" ", "_", current_pitcher_reactive())
      paste0(pitcher_clean, "_Comprehensive_Report_", format(Sys.Date(), "%Y%m%d"), ".pdf")
    },
    content = function(file) {
      req(current_pitcher_reactive())
      withProgress(message = 'Generating Comprehensive PDF', value = 0, {
        incProgress(0.2, detail = "Processing data...")
        create_comprehensive_pitcher_pdf(base_data(), current_pitcher_reactive(), file)
        incProgress(0.8, detail = "Finalizing report...")
      })
      showNotification("Comprehensive Pitcher PDF generated!", type = "message", duration = 3)
    },
    contentType = "application/pdf"
  )
  
  # Download handler for comprehensive PDF from main tab
  output$download_comprehensive_pdf_main <- downloadHandler(
    filename = function() {
      req(current_pitcher_reactive())
      pitcher_clean <- gsub(" ", "_", current_pitcher_reactive())
      paste0(pitcher_clean, "_Comprehensive_Report_", format(Sys.Date(), "%Y%m%d"), ".pdf")
    },
    content = function(file) {
      req(current_pitcher_reactive())
      withProgress(message = 'Generating Comprehensive PDF', value = 0, {
        incProgress(0.2, detail = "Processing data...")
        create_comprehensive_pitcher_pdf(base_data(), current_pitcher_reactive(), file)
        incProgress(0.8, detail = "Finalizing report...")
      })
      showNotification("Comprehensive Pitcher PDF generated!", type = "message", duration = 3)
    },
    contentType = "application/pdf"
  )
  
  # ===== BULLPEN REPORT SERVER =====
  
  observe({
    req(authed())
    updateSelectizeInput(session, "bullpen_pitchers", 
                         choices = available_pitchers(),
                         server = TRUE)
  })
  
  pitcher_colors <- c("#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", 
                      "#FFFF33", "#A65628", "#F781BF", "#999999", "#66C2A5")
  
  get_pitcher_color <- function(pitcher, pitchers) {
    idx <- which(pitchers == pitcher)
    if (length(idx) > 0) pitcher_colors[((idx - 1) %% length(pitcher_colors)) + 1]
    else "#333333"
  }
  
  # Calculate comprehensive bullpen stats (uses base_data)
  bullpen_stats_reactive <- reactive({
    req(input$bullpen_pitchers)
    pitchers <- input$bullpen_pitchers
    
    fb_pitches <- c("Fastball", "Sinker", "FourSeamFastBall", "TwoSeamFastBall", "Four-Seam", "Two-Seam")
    bb_pitches <- c("Slider", "Curveball", "Cutter", "Sweeper", "Slurve")
    os_pitches <- c("ChangeUp", "Changeup", "Splitter")
    
    cur_data <- base_data()
    
    pitch_per_game <- cur_data %>%
      filter(Pitcher %in% pitchers) %>%
      group_by(Pitcher, Date, GameUID) %>%
      summarise(game_pitches = n(), .groups = "drop") %>%
      group_by(Pitcher) %>%
      summarise(
        pitch_20 = round(quantile(game_pitches, 0.20, na.rm = TRUE), 0),
        pitch_80 = round(quantile(game_pitches, 0.80, na.rm = TRUE), 0),
        .groups = "drop"
      )
    
    fb_velo <- cur_data %>%
      filter(Pitcher %in% pitchers, TaggedPitchType %in% fb_pitches, !is.na(RelSpeed)) %>%
      group_by(Pitcher) %>%
      summarise(
        FB_velo_20 = round(quantile(RelSpeed, 0.20, na.rm = TRUE), 1),
        FB_velo_80 = round(quantile(RelSpeed, 0.80, na.rm = TRUE), 1),
        .groups = "drop"
      )
    
    woba_splits <- cur_data %>%
      filter(Pitcher %in% pitchers) %>%
      group_by(Pitcher, BatterSide) %>%
      summarise(
        woba_val = if("woba" %in% names(cur_data())) round(mean(woba, na.rm = TRUE), 3) else NA_real_,
        .groups = "drop"
      ) %>%
      pivot_wider(names_from = BatterSide, values_from = woba_val, names_prefix = "wOBA_vs_")
    
    main_stats <- cur_data %>%
      filter(Pitcher %in% pitchers) %>%
      mutate(
        is_fb = TaggedPitchType %in% fb_pitches,
        is_bb = TaggedPitchType %in% bb_pitches,
        is_os = TaggedPitchType %in% os_pitches,
        is_strike = PitchCall %in% c("StrikeCalled", "StrikeSwinging", "FoulBall", "InPlay")
      ) %>%
      group_by(Pitcher) %>%
      summarise(
        n_pitches = n(),
        FB_pct = round(100 * sum(is_fb) / n(), 1),
        BB_pct = round(100 * sum(is_bb) / n(), 1),
        OS_pct = round(100 * sum(is_os) / n(), 1),
        IP = round(sum(OutsOnPlay, na.rm = TRUE) / 3, 1),
        n_k = sum(KorBB == "Strikeout", na.rm = TRUE),
        n_bb = sum(KorBB == "Walk", na.rm = TRUE),
        n_pa = n_distinct(PAofInning),
        K_pct = round(100 * n_k / n_pa, 1),
        BB_pct_rate = round(100 * n_bb / n_pa, 1),
        Strike_pct = round(100 * sum(is_strike) / n(), 1),
        n_fb = sum(is_fb),
        n_bb_pit = sum(is_bb),
        n_os = sum(is_os),
        FB_Strike_pct = round(100 * sum(is_strike & is_fb) / max(n_fb, 1), 1),
        BB_Strike_pct = round(100 * sum(is_strike & is_bb) / max(n_bb_pit, 1), 1),
        OS_Strike_pct = round(100 * sum(is_strike & is_os) / max(n_os, 1), 1),
        .groups = "drop"
      ) %>%
      select(-n_fb, -n_bb_pit, -n_os, -n_pa, -n_k, -n_bb)
    
    stats <- main_stats %>%
      left_join(pitch_per_game, by = "Pitcher") %>%
      left_join(fb_velo, by = "Pitcher") %>%
      left_join(woba_splits, by = "Pitcher")
    
    stats$Color <- sapply(stats$Pitcher, get_pitcher_color, pitchers = pitchers)
    stats
  })
  
  # Bullpen roles table UI
  output$bullpen_roles_table_ui <- renderUI({
    req(input$bullpen_pitchers)
    pitchers <- input$bullpen_pitchers
    stats <- bullpen_stats_reactive()
    
    tagList(
      tags$table(class = "table table-bordered table-sm", style = "width: 100%; font-size: 11px;",
                 tags$thead(
                   tags$tr(
                     tags$th("Pitcher", style = "background: #006F71; color: white;"),
                     tags$th("Role", style = "background: #006F71; color: white;"),
                     tags$th("Matchup", style = "background: #006F71; color: white;"),
                     tags$th("P/G", style = "background: #006F71; color: white;"),
                     tags$th("FB Velo", style = "background: #006F71; color: white;"),
                     tags$th("Str%", style = "background: #006F71; color: white;"),
                     tags$th("FB%", style = "background: #006F71; color: white;"),
                     tags$th("BB%", style = "background: #006F71; color: white;"),
                     tags$th("OS%", style = "background: #006F71; color: white;"),
                     tags$th("wOBA vL", style = "background: #006F71; color: white;"),
                     tags$th("wOBA vR", style = "background: #006F71; color: white;"),
                     tags$th("Notes", style = "background: #006F71; color: white;")
                   )
                 ),
                 tags$tbody(
                   lapply(seq_along(pitchers), function(i) {
                     p <- pitchers[i]
                     p_stats <- stats %>% filter(Pitcher == p)
                     p_color <- get_pitcher_color(p, pitchers)
                     pitch_range <- if(nrow(p_stats) > 0) paste0(p_stats$pitch_20, "-", p_stats$pitch_80) else ""
                     fb_range <- if(nrow(p_stats) > 0) paste0(p_stats$FB_velo_20, "-", p_stats$FB_velo_80) else ""
                     strike_pct <- if(nrow(p_stats) > 0 && !is.na(p_stats$Strike_pct)) paste0(p_stats$Strike_pct, "%") else ""
                     fb_pct <- if(nrow(p_stats) > 0 && !is.na(p_stats$FB_pct)) paste0(p_stats$FB_pct, "%") else ""
                     bb_pct <- if(nrow(p_stats) > 0 && !is.na(p_stats$BB_pct)) paste0(p_stats$BB_pct, "%") else ""
                     os_pct <- if(nrow(p_stats) > 0 && !is.na(p_stats$OS_pct)) paste0(p_stats$OS_pct, "%") else ""
                     woba_vl <- if(nrow(p_stats) > 0 && "wOBA_vs_Left" %in% names(p_stats) && !is.na(p_stats$wOBA_vs_Left)) sprintf("%.3f", p_stats$wOBA_vs_Left) else ""
                     woba_vr <- if(nrow(p_stats) > 0 && "wOBA_vs_Right" %in% names(p_stats) && !is.na(p_stats$wOBA_vs_Right)) sprintf("%.3f", p_stats$wOBA_vs_Right) else ""
                     
                     tags$tr(
                       tags$td(tags$strong(p, style = paste0("color: ", p_color, ";"))),
                       tags$td(textInput(paste0("bp_role_", i), label = NULL, value = "", placeholder = "Role", width = "100%")),
                       tags$td(selectInput(paste0("bp_matchup_", i), label = NULL, choices = c("Both", "RHH", "LHH"), selected = "Both", width = "80px")),
                       tags$td(pitch_range, style = "text-align: center;"),
                       tags$td(fb_range, style = "text-align: center;"),
                       tags$td(strike_pct, style = "text-align: center;"),
                       tags$td(fb_pct, style = "text-align: center;"),
                       tags$td(bb_pct, style = "text-align: center;"),
                       tags$td(os_pct, style = "text-align: center;"),
                       tags$td(woba_vl, style = "text-align: center;"),
                       tags$td(woba_vr, style = "text-align: center;"),
                       tags$td(textInput(paste0("bp_notes_", i), label = NULL, value = "", placeholder = "Notes...", width = "100%"))
                     )
                   })
                 )
      )
    )
  })
  
  # Bullpen usage chart (uses base_data)
  output$bullpen_usage_chart <- renderPlot({
    req(input$bullpen_pitchers)
    
    as_of_date <- input$bullpen_date
    pitchers <- input$bullpen_pitchers
    
    usage_data <- base_data() %>%
      filter(Pitcher %in% pitchers) %>%
      mutate(Date = as.Date(Date)) %>%
      filter(Date <= as_of_date) %>%
      group_by(Pitcher, Date) %>%
      summarise(pitches = n(), .groups = "drop") %>%
      group_by(Pitcher) %>%
      summarise(
        last_1_week = sum(pitches[Date > (as_of_date - 7)], na.rm = TRUE),
        last_2_weeks = sum(pitches[Date > (as_of_date - 14)], na.rm = TRUE),
        .groups = "drop"
      ) %>%
      pivot_longer(cols = c(last_1_week, last_2_weeks), names_to = "period", values_to = "pitches")
    
    pitcher_order <- usage_data %>%
      filter(period == "last_2_weeks") %>%
      arrange(desc(pitches)) %>%
      pull(Pitcher)
    
    usage_data$Pitcher <- factor(usage_data$Pitcher, levels = rev(pitcher_order))
    usage_data$period <- factor(usage_data$period, levels = c("last_1_week", "last_2_weeks"),
                                labels = c("Last 1 Week", "Last 2 Weeks"))
    
    ggplot(usage_data, aes(x = pitches, y = Pitcher, fill = period)) +
      geom_col(position = position_dodge(width = 0.8), width = 0.7) +
      geom_text(aes(label = ifelse(pitches > 0, pitches, "")), 
                position = position_dodge(width = 0.8), hjust = -0.2, size = 4, fontface = "bold") +
      scale_fill_manual(values = c("Last 1 Week" = "#006F71", "Last 2 Weeks" = "#CD853F")) +
      labs(x = "Pitches", y = NULL, fill = NULL, title = "Pitch Count Usage") +
      theme_minimal() +
      theme(
        legend.position = "top",
        axis.text.y = element_text(size = 12, face = "bold"),
        plot.title = element_text(hjust = 0.5, face = "bold", color = "#006F71"),
        panel.grid.major.y = element_blank()
      ) +
      scale_x_continuous(expand = expansion(mult = c(0, 0.15)))
  })
  
  # Bullpen inning heatmap (uses base_data)
  output$bullpen_inning_heatmap <- renderPlot({
    req(input$bullpen_pitchers)
    pitchers <- input$bullpen_pitchers
    
    inning_data <- base_data() %>%
      filter(Pitcher %in% pitchers, !is.na(Inning)) %>%
      mutate(Inning = ifelse(Inning > 9, "X", as.character(Inning))) %>%
      group_by(Pitcher, Inning) %>%
      summarise(pitches = n(), .groups = "drop")
    
    all_innings <- c("1", "2", "3", "4", "5", "6", "7", "8", "9", "X")
    complete_grid <- expand.grid(Pitcher = pitchers, Inning = all_innings, stringsAsFactors = FALSE)
    
    inning_data <- complete_grid %>%
      left_join(inning_data, by = c("Pitcher", "Inning")) %>%
      mutate(pitches = ifelse(is.na(pitches), 0, pitches))
    
    inning_data$Inning <- factor(inning_data$Inning, levels = all_innings)
    inning_data$Pitcher <- factor(inning_data$Pitcher, levels = rev(pitchers))
    
    ggplot(inning_data, aes(x = Inning, y = Pitcher, fill = pitches)) +
      geom_tile(color = "white", linewidth = 0.8) +
      geom_text(aes(label = ifelse(pitches > 0, pitches, "")), size = 3.5, fontface = "bold") +
      scale_fill_gradient2(low = "#E1463E", mid = "#FFFFCC", high = "#00840D", 
                           midpoint = median(inning_data$pitches[inning_data$pitches > 0], na.rm = TRUE),
                           name = "Pitches") +
      scale_x_discrete(position = "top") +
      labs(x = NULL, y = NULL, title = "Usage by Inning") +
      theme_minimal() +
      theme(
        axis.text.x = element_text(size = 12, face = "bold"),
        axis.text.y = element_text(size = 11, face = "bold"),
        legend.position = "none",
        panel.grid = element_blank(),
        plot.title = element_text(hjust = 0.5, face = "bold", color = "#006F71")
      )
  })
  
  # Rolling chart titles
  output$rolling_chart1_title <- renderText({
    stat_names <- c("velo" = "Rolling Velocity by Pitch #", "strike" = "Rolling Strike% by Pitch #",
                    "woba" = "Rolling wOBA by Pitch #", "stuff_plus" = "Rolling Stuff+ by Pitch #")
    stat_names[input$rolling_stat1]
  })
  
  output$rolling_chart2_title <- renderText({
    stat_names <- c("velo" = "Rolling Velocity by Pitch #", "strike" = "Rolling Strike% by Pitch #",
                    "woba" = "Rolling wOBA by Pitch #", "stuff_plus" = "Rolling Stuff+ by Pitch #")
    stat_names[input$rolling_stat2]
  })
  
  # Helper function to create rolling stat data (uses base_data)
  create_rolling_data <- function(pitchers, stat_type) {
    fb_pitches <- c("Fastball", "Sinker", "FourSeamFastBall", "TwoSeamFastBall", "Four-Seam", "Two-Seam")
    
    rolling_data <- base_data() %>%
      filter(Pitcher %in% pitchers) %>%
      arrange(Pitcher, Date, GameUID, PitchofPA) %>%
      group_by(Pitcher, GameUID) %>%
      mutate(pitch_in_game = row_number()) %>%
      ungroup()
    
    if (stat_type == "velo") {
      raw_data <- rolling_data %>%
        filter(TaggedPitchType %in% fb_pitches, !is.na(RelSpeed)) %>%
        select(Pitcher, pitch_in_game, value = RelSpeed)
    } else if (stat_type == "strike") {
      raw_data <- rolling_data %>%
        mutate(value = as.numeric(PitchCall %in% c("StrikeCalled", "StrikeSwinging", "FoulBall", "InPlay")) * 100) %>%
        select(Pitcher, pitch_in_game, value)
    } else if (stat_type == "woba") {
      if ("woba" %in% names(rolling_data)) {
        raw_data <- rolling_data %>% filter(!is.na(woba)) %>% select(Pitcher, pitch_in_game, value = woba)
      } else {
        return(data.frame(Pitcher = character(), pitch_num = integer(), value = numeric()))
      }
    } else if (stat_type == "stuff_plus") {
      if ("stuff_plus" %in% names(rolling_data)) {
        raw_data <- rolling_data %>% filter(!is.na(stuff_plus)) %>% select(Pitcher, pitch_in_game, value = stuff_plus)
      } else {
        return(data.frame(Pitcher = character(), pitch_num = integer(), value = numeric()))
      }
    } else {
      return(data.frame(Pitcher = character(), pitch_num = integer(), value = numeric()))
    }
    
    if (nrow(raw_data) == 0) {
      return(data.frame(Pitcher = character(), pitch_num = integer(), value = numeric()))
    }
    
    result <- raw_data %>%
      group_by(Pitcher, pitch_num = pitch_in_game) %>%
      summarise(value = mean(value, na.rm = TRUE), n_games = n(), .groups = "drop") %>%
      filter(n_games >= 2)
    
    result
  }
  
  # Function to calculate stats by pitch count buckets (uses base_data)
  create_pitch_bucket_stats <- function(pitchers) {
    fb_pitches <- c("Fastball", "Sinker", "FourSeamFastBall", "TwoSeamFastBall", "Four-Seam", "Two-Seam")
    
    pitch_data <- base_data() %>%
      filter(Pitcher %in% pitchers) %>%
      arrange(Pitcher, Date, GameUID, PitchofPA) %>%
      group_by(Pitcher, GameUID) %>%
      mutate(pitch_in_game = row_number()) %>%
      ungroup() %>%
      mutate(
        pitch_bucket = paste0(floor((pitch_in_game - 1) / 10) * 10 + 1, "-", floor((pitch_in_game - 1) / 10) * 10 + 10),
        bucket_order = floor((pitch_in_game - 1) / 10)
      )
    
    bucket_stats <- pitch_data %>%
      group_by(Pitcher, pitch_bucket, bucket_order) %>%
      summarise(
        Pitches = n(),
        Games = n_distinct(GameUID),
        `FB Velo` = round(mean(RelSpeed[TaggedPitchType %in% fb_pitches], na.rm = TRUE), 1),
        `Strike%` = round(100 * sum(PitchCall %in% c("StrikeCalled", "StrikeSwinging", "FoulBall", "InPlay")) / n(), 1),
        `Whiff%` = round(100 * sum(PitchCall == "StrikeSwinging", na.rm = TRUE) / 
                           sum(PitchCall %in% c("StrikeSwinging", "FoulBall", "InPlay"), na.rm = TRUE), 1),
        `Zone%` = round(100 * mean(PlateLocSide >= -0.83 & PlateLocSide <= 0.83 & 
                                     PlateLocHeight >= 1.5 & PlateLocHeight <= 3.5, na.rm = TRUE), 1),
        .groups = "drop"
      ) %>%
      arrange(Pitcher, bucket_order) %>%
      select(-bucket_order)
    
    bucket_stats %>% mutate(across(where(is.numeric), ~ifelse(is.nan(.), NA, .)))
  }
  
  # Rolling chart 1
  output$bullpen_rolling_chart1 <- renderPlot({
    req(input$bullpen_pitchers)
    pitchers <- input$bullpen_pitchers
    stat_type <- input$rolling_stat1
    
    rolling_data <- create_rolling_data(pitchers, stat_type)
    
    if (is.null(rolling_data) || nrow(rolling_data) == 0) {
      return(ggplot() + theme_void() + annotate("text", x = 0.5, y = 0.5, label = "Insufficient data"))
    }
    
    max_pitch <- min(max(rolling_data$pitch_num, na.rm = TRUE), 120)
    
    ggplot(rolling_data, aes(x = pitch_num, y = value, color = Pitcher)) +
      geom_line(linewidth = 1.2, alpha = 0.8) +
      scale_color_manual(values = setNames(sapply(pitchers, get_pitcher_color, pitchers = pitchers), pitchers)) +
      labs(x = "Pitch # in Game", y = NULL) +
      scale_x_continuous(limits = c(1, max_pitch), breaks = seq(10, max_pitch, 10)) +
      theme_minimal() +
      theme(legend.position = "none", plot.title = element_text(hjust = 0.5, face = "bold", color = "#006F71"), panel.grid.minor = element_blank())
  })
  
  # Rolling chart 2
  output$bullpen_rolling_chart2 <- renderPlot({
    req(input$bullpen_pitchers)
    pitchers <- input$bullpen_pitchers
    stat_type <- input$rolling_stat2
    
    rolling_data <- create_rolling_data(pitchers, stat_type)
    
    if (is.null(rolling_data) || nrow(rolling_data) == 0) {
      return(ggplot() + theme_void() + annotate("text", x = 0.5, y = 0.5, label = "Insufficient data"))
    }
    
    max_pitch <- min(max(rolling_data$pitch_num, na.rm = TRUE), 120)
    
    ggplot(rolling_data, aes(x = pitch_num, y = value, color = Pitcher)) +
      geom_line(linewidth = 1.2, alpha = 0.8) +
      scale_color_manual(values = setNames(sapply(pitchers, get_pitcher_color, pitchers = pitchers), pitchers)) +
      labs(x = "Pitch # in Game", y = NULL) +
      scale_x_continuous(limits = c(1, max_pitch), breaks = seq(10, max_pitch, 10)) +
      theme_minimal() +
      theme(legend.position = "none", plot.title = element_text(hjust = 0.5, face = "bold", color = "#006F71"), panel.grid.minor = element_blank())
  })
  
  # Bullpen summary stats table
  output$bullpen_summary_table <- gt::render_gt({
    req(input$bullpen_pitchers)
    stats <- bullpen_stats_reactive()
    
    display_stats <- stats %>%
      select(Pitcher, FB_pct, BB_pct, OS_pct, IP, K_pct, BB_pct_rate, 
             Strike_pct, FB_Strike_pct, BB_Strike_pct, OS_Strike_pct)
    
    display_stats %>%
      gt() %>%
      tab_header(title = "Bullpen Performance Stats") %>%
      cols_label(
        Pitcher = "Pitcher", FB_pct = "FB%", BB_pct = "BB%", OS_pct = "OS%",
        IP = "IP", K_pct = "K%", BB_pct_rate = "BB%", Strike_pct = "Str%",
        FB_Strike_pct = "FB Str%", BB_Strike_pct = "BB Str%", OS_Strike_pct = "OS Str%"
      ) %>%
      tab_style(style = cell_fill(color = "#006F71"), locations = cells_column_labels()) %>%
      tab_style(style = cell_text(color = "white", weight = "bold"), locations = cells_column_labels()) %>%
      fmt_number(columns = c(FB_pct, BB_pct, OS_pct, K_pct, BB_pct_rate, Strike_pct, FB_Strike_pct, BB_Strike_pct, OS_Strike_pct), decimals = 1) %>%
      data_color(columns = K_pct, fn = scales::col_numeric(palette = c("#E1463E", "white", "#00840D"), domain = c(15, 35))) %>%
      data_color(columns = BB_pct_rate, fn = scales::col_numeric(palette = c("#00840D", "white", "#E1463E"), domain = c(5, 15))) %>%
      data_color(columns = Strike_pct, fn = scales::col_numeric(palette = c("#E1463E", "white", "#00840D"), domain = c(55, 70)))
  })
  
  # Download bullpen PDF (uses base_data)
  output$download_bullpen_pdf <- downloadHandler(
    filename = function() {
      paste0("Bullpen_Report_", format(input$bullpen_date, "%Y%m%d"), ".pdf")
    },
    content = function(file) {
      req(input$bullpen_pitchers)
      
      withProgress(message = "Generating Bullpen Report...", value = 0, {
        incProgress(0.2, detail = "Calculating stats...")
        
        pitchers <- input$bullpen_pitchers
        stats <- bullpen_stats_reactive()
        as_of_date <- input$bullpen_date
        cur_data <- base_data()
        
        pdf(file, width = 11, height = 14)
        grid::grid.newpage()
        
        # Header
        grid::grid.rect(x = 0.5, y = 0.97, width = 1, height = 0.05,
                        gp = grid::gpar(fill = "#006F71", col = NA))
        grid::grid.text(if(nchar(input$bullpen_title) > 0) input$bullpen_title else "Auto Bullpen Report", 
                        x = 0.5, y = 0.965,
                        gp = grid::gpar(fontsize = 22, fontface = "bold", col = "white"))
        grid::grid.text(paste("As of", format(as_of_date, "%m/%d/%y")), 
                        x = 0.5, y = 0.935,
                        gp = grid::gpar(fontsize = 10, col = "white"))
        
        incProgress(0.3, detail = "Drawing tables...")
        
        table_y <- 0.90
        row_h <- 0.018
        col_widths <- c(0.10, 0.10, 0.05, 0.06, 0.07, 0.05, 0.05, 0.05, 0.05, 0.06, 0.06, 0.20)
        x_starts <- cumsum(c(0.05, col_widths[-length(col_widths)]))
        headers <- c("Pitcher", "Role", "Match", "P/G", "FB Velo", "Str%", "FB%", "BB%", "OS%", "wOBA vL", "wOBA vR", "Notes")
        
        for (j in seq_along(headers)) {
          grid::grid.rect(x = x_starts[j] + col_widths[j]/2, y = table_y, 
                          width = col_widths[j], height = row_h,
                          gp = grid::gpar(fill = "#006F71", col = "black"), just = c("center", "top"))
          grid::grid.text(headers[j], x = x_starts[j] + col_widths[j]/2, y = table_y - row_h/2,
                          gp = grid::gpar(fontsize = 6, fontface = "bold", col = "white"))
        }
        
        for (i in seq_along(pitchers)) {
          p <- pitchers[i]
          p_stats <- stats %>% filter(Pitcher == p)
          p_color <- get_pitcher_color(p, pitchers)
          y_row <- table_y - i * row_h
          
          role <- input[[paste0("bp_role_", i)]] %||% ""
          matchup <- input[[paste0("bp_matchup_", i)]] %||% "Both"
          notes <- input[[paste0("bp_notes_", i)]] %||% ""
          pitch_range <- if(nrow(p_stats) > 0) paste0(p_stats$pitch_20, "-", p_stats$pitch_80) else ""
          fb_range <- if(nrow(p_stats) > 0) paste0(p_stats$FB_velo_20, "-", p_stats$FB_velo_80) else ""
          strike_pct <- if(nrow(p_stats) > 0 && !is.na(p_stats$Strike_pct)) paste0(p_stats$Strike_pct, "%") else ""
          fb_pct <- if(nrow(p_stats) > 0 && !is.na(p_stats$FB_pct)) paste0(p_stats$FB_pct, "%") else ""
          bb_pct <- if(nrow(p_stats) > 0 && !is.na(p_stats$BB_pct)) paste0(p_stats$BB_pct, "%") else ""
          os_pct <- if(nrow(p_stats) > 0 && !is.na(p_stats$OS_pct)) paste0(p_stats$OS_pct, "%") else ""
          woba_vl <- if(nrow(p_stats) > 0 && "wOBA_vs_Left" %in% names(p_stats) && !is.na(p_stats$wOBA_vs_Left)) sprintf("%.3f", p_stats$wOBA_vs_Left) else ""
          woba_vr <- if(nrow(p_stats) > 0 && "wOBA_vs_Right" %in% names(p_stats) && !is.na(p_stats$wOBA_vs_Right)) sprintf("%.3f", p_stats$wOBA_vs_Right) else ""
          
          row_vals <- c(p, role, matchup, pitch_range, fb_range, strike_pct, fb_pct, bb_pct, os_pct, woba_vl, woba_vr, notes)
          for (j in seq_along(row_vals)) {
            bg <- if (i %% 2 == 0) "#f8f9fa" else "white"
            grid::grid.rect(x = x_starts[j] + col_widths[j]/2, y = y_row, 
                            width = col_widths[j], height = row_h,
                            gp = grid::gpar(fill = bg, col = "gray70"), just = c("center", "top"))
            txt_col <- if(j == 1) p_color else "black"
            grid::grid.text(row_vals[j], x = x_starts[j] + col_widths[j]/2, y = y_row - row_h/2,
                            gp = grid::gpar(fontsize = 5.5, col = txt_col, fontface = if(j==1) "bold" else "plain"))
          }
        }
        
        incProgress(0.5, detail = "Creating charts...")
        
        chart_y <- table_y - (length(pitchers) + 2) * row_h
        
        # Usage bar chart
        usage_data <- cur_data %>%
          filter(Pitcher %in% pitchers) %>%
          mutate(Date = as.Date(Date)) %>%
          filter(Date <= as_of_date) %>%
          group_by(Pitcher, Date) %>%
          summarise(pitches = n(), .groups = "drop") %>%
          group_by(Pitcher) %>%
          summarise(
            last_1_week = sum(pitches[Date > (as_of_date - 7)], na.rm = TRUE),
            last_2_weeks = sum(pitches[Date > (as_of_date - 14)], na.rm = TRUE),
            .groups = "drop"
          ) %>%
          pivot_longer(cols = c(last_1_week, last_2_weeks), names_to = "period", values_to = "pitches")
        
        usage_data$Pitcher <- factor(usage_data$Pitcher, levels = rev(pitchers))
        usage_data$period <- factor(usage_data$period, levels = c("last_1_week", "last_2_weeks"),
                                    labels = c("Last 1 Week", "Last 2 Weeks"))
        
        usage_plot <- ggplot(usage_data, aes(x = pitches, y = Pitcher, fill = period)) +
          geom_col(position = position_dodge(width = 0.8), width = 0.7) +
          geom_text(aes(label = ifelse(pitches > 0, pitches, "")), 
                    position = position_dodge(width = 0.8), hjust = -0.2, size = 2.5) +
          scale_fill_manual(values = c("Last 1 Week" = "#006F71", "Last 2 Weeks" = "#CD853F")) +
          labs(x = "Pitches", y = NULL, fill = NULL, title = "Pitch Usage") +
          theme_minimal() +
          theme(legend.position = "top", plot.title = element_text(hjust = 0.5, face = "bold", size = 10), axis.text = element_text(size = 7))
        
        grid::pushViewport(grid::viewport(x = 0.26, y = chart_y, width = 0.42, height = 0.22, just = c("center", "top")))
        print(usage_plot, newpage = FALSE)
        grid::popViewport()
        
        # Inning heatmap
        inning_data <- cur_data %>%
          filter(Pitcher %in% pitchers, !is.na(Inning)) %>%
          mutate(Inning = ifelse(Inning > 9, "X", as.character(Inning))) %>%
          group_by(Pitcher, Inning) %>%
          summarise(pitches = n(), .groups = "drop")
        
        all_innings <- c("1", "2", "3", "4", "5", "6", "7", "8", "9", "X")
        complete_grid <- expand.grid(Pitcher = pitchers, Inning = all_innings, stringsAsFactors = FALSE)
        inning_data <- complete_grid %>%
          left_join(inning_data, by = c("Pitcher", "Inning")) %>%
          mutate(pitches = ifelse(is.na(pitches), 0, pitches))
        inning_data$Inning <- factor(inning_data$Inning, levels = all_innings)
        inning_data$Pitcher <- factor(inning_data$Pitcher, levels = rev(pitchers))
        
        inning_plot <- ggplot(inning_data, aes(x = Inning, y = Pitcher, fill = pitches)) +
          geom_tile(color = "white", linewidth = 0.5) +
          geom_text(aes(label = ifelse(pitches > 0, pitches, "")), size = 2) +
          scale_fill_gradient2(low = "#E1463E", mid = "#FFFFCC", high = "#00840D",
                               midpoint = max(inning_data$pitches)/2, guide = "none") +
          scale_x_discrete(position = "top") +
          labs(x = NULL, y = NULL, title = "Usage by Inning") +
          theme_minimal() +
          theme(plot.title = element_text(hjust = 0.5, face = "bold", size = 10), panel.grid = element_blank(), axis.text = element_text(size = 7))
        
        grid::pushViewport(grid::viewport(x = 0.74, y = chart_y, width = 0.42, height = 0.22, just = c("center", "top")))
        print(inning_plot, newpage = FALSE)
        grid::popViewport()
        
        incProgress(0.7, detail = "Creating rolling charts...")
        
        rolling_y <- chart_y - 0.25
        
        max_pitch_num <- cur_data %>%
          filter(Pitcher %in% pitchers) %>%
          group_by(Pitcher, GameUID) %>%
          summarise(max_p = n(), .groups = "drop") %>%
          summarise(max_overall = max(max_p)) %>%
          pull(max_overall)
        max_pitch_num <- min(max_pitch_num, 120)
        
        stat_names <- c("velo" = "Rolling Velocity by Pitch #", "strike" = "Rolling Strike% by Pitch #", 
                        "woba" = "Rolling wOBA by Pitch #", "stuff_plus" = "Rolling Stuff+ by Pitch #")
        
        # Rolling chart 1
        stat_type1 <- input$rolling_stat1
        rolling_data1 <- create_rolling_data(pitchers, stat_type1)
        
        if (!is.null(rolling_data1) && nrow(rolling_data1) > 0) {
          rolling_plot1 <- ggplot(rolling_data1, aes(x = pitch_num, y = value, color = Pitcher)) +
            geom_line(linewidth = 1, alpha = 0.8) +
            scale_color_manual(values = setNames(sapply(pitchers, get_pitcher_color, pitchers = pitchers), pitchers)) +
            labs(x = "Pitch # in Game", y = NULL, title = stat_names[stat_type1]) +
            scale_x_continuous(limits = c(1, max_pitch_num), breaks = seq(10, max_pitch_num, 10)) +
            theme_minimal() +
            theme(legend.position = "none", plot.title = element_text(hjust = 0.5, face = "bold", size = 10), axis.text = element_text(size = 7))
          
          grid::pushViewport(grid::viewport(x = 0.26, y = rolling_y, width = 0.42, height = 0.20, just = c("center", "top")))
          print(rolling_plot1, newpage = FALSE)
          grid::popViewport()
        }
        
        # Rolling chart 2
        stat_type2 <- input$rolling_stat2
        rolling_data2 <- create_rolling_data(pitchers, stat_type2)
        
        if (!is.null(rolling_data2) && nrow(rolling_data2) > 0) {
          rolling_plot2 <- ggplot(rolling_data2, aes(x = pitch_num, y = value, color = Pitcher)) +
            geom_line(linewidth = 1, alpha = 0.8) +
            scale_color_manual(values = setNames(sapply(pitchers, get_pitcher_color, pitchers = pitchers), pitchers)) +
            labs(x = "Pitch # in Game", y = NULL, title = stat_names[stat_type2]) +
            scale_x_continuous(limits = c(1, max_pitch_num), breaks = seq(10, max_pitch_num, 10)) +
            theme_minimal() +
            theme(legend.position = "none", plot.title = element_text(hjust = 0.5, face = "bold", size = 10), axis.text = element_text(size = 7))
          
          grid::pushViewport(grid::viewport(x = 0.74, y = rolling_y, width = 0.42, height = 0.20, just = c("center", "top")))
          print(rolling_plot2, newpage = FALSE)
          grid::popViewport()
        }
        
        incProgress(0.85, detail = "Creating pitch bucket stats table...")
        
        bucket_stats <- create_pitch_bucket_stats(pitchers)
        
        if (!is.null(bucket_stats) && nrow(bucket_stats) > 0) {
          bucket_table_y <- rolling_y - 0.23
          
          grid::grid.rect(x = 0.5, y = bucket_table_y + 0.015, width = 0.90, height = 0.018,
                          gp = grid::gpar(fill = "#006F71", col = NA))
          grid::grid.text("Stats by Pitch Count (Per Game)", x = 0.5, y = bucket_table_y + 0.015,
                          gp = grid::gpar(fontsize = 10, fontface = "bold", col = "white"))
          
          bucket_headers <- c("Pitcher", "Pitches", "Bucket", "Games", "FB Velo", "Strike%", "Whiff%", "Zone%")
          bucket_col_widths <- c(0.12, 0.06, 0.08, 0.06, 0.08, 0.08, 0.08, 0.08)
          bucket_x_starts <- cumsum(c(0.18, bucket_col_widths[-length(bucket_col_widths)]))
          bucket_row_h <- 0.014
          
          for (j in seq_along(bucket_headers)) {
            grid::grid.rect(x = bucket_x_starts[j] + bucket_col_widths[j]/2, y = bucket_table_y - 0.005, 
                            width = bucket_col_widths[j], height = bucket_row_h,
                            gp = grid::gpar(fill = "#006F71", col = "black"), just = c("center", "top"))
            grid::grid.text(bucket_headers[j], x = bucket_x_starts[j] + bucket_col_widths[j]/2, 
                            y = bucket_table_y - 0.005 - bucket_row_h/2,
                            gp = grid::gpar(fontsize = 6, fontface = "bold", col = "white"))
          }
          
          max_rows <- min(nrow(bucket_stats), 20)
          
          for (i in seq_len(max_rows)) {
            y_row <- bucket_table_y - 0.005 - i * bucket_row_h
            p <- bucket_stats$Pitcher[i]
            p_color <- get_pitcher_color(p, pitchers)
            
            row_vals <- c(
              p, as.character(bucket_stats$Pitches[i]), bucket_stats$pitch_bucket[i],
              as.character(bucket_stats$Games[i]),
              ifelse(is.na(bucket_stats$`FB Velo`[i]), "-", sprintf("%.1f", bucket_stats$`FB Velo`[i])),
              ifelse(is.na(bucket_stats$`Strike%`[i]), "-", sprintf("%.1f%%", bucket_stats$`Strike%`[i])),
              ifelse(is.na(bucket_stats$`Whiff%`[i]), "-", sprintf("%.1f%%", bucket_stats$`Whiff%`[i])),
              ifelse(is.na(bucket_stats$`Zone%`[i]), "-", sprintf("%.1f%%", bucket_stats$`Zone%`[i]))
            )
            
            for (j in seq_along(row_vals)) {
              bg <- if (i %% 2 == 0) "#f8f9fa" else "white"
              grid::grid.rect(x = bucket_x_starts[j] + bucket_col_widths[j]/2, y = y_row, 
                              width = bucket_col_widths[j], height = bucket_row_h,
                              gp = grid::gpar(fill = bg, col = "gray70"), just = c("center", "top"))
              txt_col <- if(j == 1) p_color else "black"
              grid::grid.text(row_vals[j], x = bucket_x_starts[j] + bucket_col_widths[j]/2, y = y_row - bucket_row_h/2,
                              gp = grid::gpar(fontsize = 5, col = txt_col, fontface = if(j==1) "bold" else "plain"))
            }
          }
        }
        
        dev.off()
        incProgress(1, detail = "Done!")
      })
      
      showNotification("Bullpen Report generated!", type = "message", duration = 3)
    },
    contentType = "application/pdf"
  )
}

# ============================================================================
# RUN APP
# ============================================================================

shinyApp(ui = ui, server = server)