Update app.R

app.R

@@ -1,4 +1,3 @@
-# app.R
 library(shiny)
 library(dplyr)
 library(ggplot2)
@@ -1025,378 +1024,6 @@ create_pitcher_game_line <- function(game_data) {
     )
 }
 
-# =====================================================================
-# ==================  ADVANCED PITCHER REPORT CODE  ===================
-# =====================================================================
-
-# Color palettes for heatmap tables
-make_color_fn <- function(min_val, max_val) {
-  function(x) {
-    normalized <- (x - min_val) / (max_val - min_val)
-    normalized <- pmax(0, pmin(1, normalized))
-    rgb(colorRamp(c("#648FFF", "#FFFFFF", "#FFB000"))(normalized), maxColorValue = 255)
-  }
-}
-
-make_color_fn_reverse <- function(min_val, max_val) {
-  function(x) {
-    normalized <- (x - min_val) / (max_val - min_val)
-    normalized <- pmax(0, pmin(1, normalized))
-    rgb(colorRamp(c("#FFB000", "#FFFFFF", "#648FFF"))(normalized), maxColorValue = 255)
-  }
-}
-
-# Enhanced pitcher summary table with color coding
-create_advanced_pitcher_summary <- function(data, player_name) {
-  pitcher_data <- data %>% filter(Pitcher == player_name)
-  
-  # Calculate comprehensive statistics
-  summary_stats <- pitcher_data %>%
-    summarise(
-      BF = n_distinct(paste(Inning, Batter, PAofInning)),
-      P = n(),
-      K = sum(KorBB == "Strikeout", na.rm = TRUE),
-      BB = sum(WalkIndicator, na.rm = TRUE),
-      H = sum(PlayResult %in% c('Single','Double','Triple','HomeRun'), na.rm = TRUE),
-      XBH = sum(PlayResult %in% c('Double','Triple','HomeRun'), na.rm = TRUE),
-      HR = sum(PlayResult == 'HomeRun', na.rm = TRUE),
-      HBP = sum(HBPIndicator, na.rm = TRUE),
-      `Strike%` = 100 * sum(!PitchCall %in% c("BallCalled", "HitByPitch", "BallinDirt", "BallIntentional")) / n(),
-      `CSW%` = 100 * sum(PitchCall %in% c("StrikeCalled", "StrikeSwinging")) / n(),
-      `Whiff%` = 100 * sum(WhiffIndicator, na.rm = TRUE) / sum(SwingIndicator, na.rm = TRUE),
-      `Chase%` = 100 * sum(Chaseindicator, na.rm = TRUE) / sum(SwingIndicator == 1 & StrikeZoneIndicator == 0, na.rm = TRUE),
-      `Zone%` = 100 * sum(StrikeZoneIndicator, na.rm = TRUE) / n(),
-      `In-Zone Whiff%` = 100 * sum(Zwhiffind, na.rm = TRUE) / sum(Zswing, na.rm = TRUE),
-      .groups = "drop"
-    )
-  
-  return(summary_stats)
-}
-
-# Pitch characteristics table with movement and location metrics
-create_advanced_pitch_characteristics <- function(data, player_name) {
-  pitcher_data <- data %>% 
-    filter(Pitcher == player_name, !is.na(TaggedPitchType), TaggedPitchType != "Other")
-  
-  pitch_stats <- pitcher_data %>%
-    group_by(Pitch = TaggedPitchType) %>%
-    summarise(
-      Count = n(),
-      `Usage%` = 100 * n() / nrow(pitcher_data),
-      `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),
-      `Max Spin` = round(max(SpinRate, na.rm = TRUE), 0),
-      `Avg IVB` = round(mean(InducedVertBreak, na.rm = TRUE), 1),
-      `Avg HB` = round(mean(HorzBreak, na.rm = TRUE), 1),
-      `hRel` = round(mean(RelSide, na.rm = TRUE), 1),
-      `vRel` = round(mean(RelHeight, na.rm = TRUE), 1),
-      `Ext` = round(mean(Extension, na.rm = TRUE), 1),
-      `Strike%` = 100 * sum(!PitchCall %in% c("BallCalled", "BallinDirt", "BallIntentional")) / n(),
-      `Whiff%` = 100 * sum(WhiffIndicator, na.rm = TRUE) / sum(SwingIndicator, na.rm = TRUE),
-      `Zone%` = 100 * sum(StrikeZoneIndicator, na.rm = TRUE) / n(),
-      `Chase%` = 100 * sum(Chaseindicator, na.rm = TRUE) / sum(SwingIndicator == 1 & StrikeZoneIndicator == 0, na.rm = TRUE),
-      .groups = "drop"
-    ) %>%
-    arrange(desc(`Usage%`))
-  
-  return(pitch_stats)
-}
-
-# Enhanced break plot with pitcher handedness
-create_advanced_break_plot <- function(data, player_name, pitch_colors) {
-  pitcher_data <- data %>% 
-    filter(Pitcher == player_name, !is.na(TaggedPitchType), TaggedPitchType != "Other",
-           !is.na(HorzBreak), !is.na(InducedVertBreak))
-  
-  if (nrow(pitcher_data) == 0) {
-    return(ggplot() + theme_void() + ggtitle("Pitch Movement") +
-             theme(plot.title = element_text(size = 14, face = "bold", hjust = 0.5)))
-  }
-  
-  # Determine pitcher handedness
-  pitcher_hand <- pitcher_data$PitcherThrows[1]
-  x_mult <- if (pitcher_hand == "Right") -1 else 1
-  
-  # Calculate pitch averages for larger markers
-  pitch_avgs <- pitcher_data %>%
-    group_by(TaggedPitchType) %>%
-    summarise(
-      HB_avg = mean(HorzBreak * x_mult, na.rm = TRUE),
-      IVB_avg = mean(InducedVertBreak, na.rm = TRUE),
-      Velo_avg = round(mean(RelSpeed, na.rm = TRUE)),
-      .groups = "drop"
-    )
-  
-  p <- ggplot() +
-    geom_hline(yintercept = 0, color = "#808080", alpha = 0.5, linetype = "dashed") +
-    geom_vline(xintercept = 0, color = "#808080", alpha = 0.5, linetype = "dashed") +
-    geom_point(data = pitcher_data, 
-               aes(x = HorzBreak * x_mult, y = InducedVertBreak, fill = TaggedPitchType),
-               shape = 21, size = 4, color = "black", stroke = 0.4, alpha = 0.85) +
-    geom_point(data = pitch_avgs,
-               aes(x = HB_avg, y = IVB_avg, fill = TaggedPitchType),
-               shape = 21, size = 8, color = "black", stroke = 0.5, alpha = 1) +
-    geom_text(data = pitch_avgs,
-              aes(x = HB_avg, y = IVB_avg, label = Velo_avg),
-              size = 4, fontface = "bold") +
-    scale_fill_manual(values = pitch_colors, name = "Pitch Type") +
-    coord_fixed(xlim = c(-25, 25), ylim = c(-25, 25)) +
-    labs(title = "Pitch Movement", 
-         x = "Horizontal Break (in)", 
-         y = "Induced Vertical Break (in)") +
-    theme_minimal(base_size = 12) +
-    theme(
-      plot.title = element_text(size = 16, face = "bold", hjust = 0.5),
-      legend.position = "none",
-      panel.grid.minor = element_blank(),
-      aspect.ratio = 1
-    )
-  
-  # Add side labels based on handedness
-  if (pitcher_hand == "Right") {
-    p <- p + 
-      annotate("text", x = -24, y = -24, label = "← Glove Side", 
-               hjust = 0, vjust = 0, size = 3, fontface = "italic",
-               color = "black") +
-      annotate("text", x = 24, y = -24, label = "Arm Side →", 
-               hjust = 1, vjust = 0, size = 3, fontface = "italic",
-               color = "black")
-  } else {
-    p <- p + 
-      annotate("text", x = 24, y = -24, label = "← Arm Side", 
-               hjust = 1, vjust = 0, size = 3, fontface = "italic",
-               color = "black") +
-      annotate("text", x = -24, y = -24, label = "Glove Side →", 
-               hjust = 0, vjust = 0, size = 3, fontface = "italic",
-               color = "black")
-  }
-  
-  return(p)
-}
-
-# Velocity distribution KDE plots by pitch type
-create_velocity_distribution_plot <- function(data, player_name, pitch_colors) {
-  pitcher_data <- data %>%
-    filter(Pitcher == player_name, !is.na(TaggedPitchType), TaggedPitchType != "Other",
-           !is.na(RelSpeed))
-  
-  if (nrow(pitcher_data) == 0) {
-    return(ggplot() + theme_void() + ggtitle("Velocity Distribution") +
-             theme(plot.title = element_text(size = 14, face = "bold", hjust = 0.5)))
-  }
-  
-  # Order pitch types by frequency
-  pitch_order <- pitcher_data %>%
-    count(TaggedPitchType, sort = TRUE) %>%
-    pull(TaggedPitchType)
-  
-  pitcher_data <- pitcher_data %>%
-    mutate(TaggedPitchType = factor(TaggedPitchType, levels = pitch_order))
-  
-  # Calculate means for each pitch type
-  pitch_means <- pitcher_data %>%
-    group_by(TaggedPitchType) %>%
-    summarise(mean_velo = mean(RelSpeed, na.rm = TRUE), .groups = "drop")
-  
-  ggplot(pitcher_data, aes(x = RelSpeed, fill = TaggedPitchType)) +
-    geom_density(alpha = 0.7, color = "black", size = 0.3) +
-    geom_vline(data = pitch_means, aes(xintercept = mean_velo, color = TaggedPitchType),
-               linetype = "dashed", size = 0.8) +
-    facet_wrap(~ TaggedPitchType, ncol = 1, strip.position = "left") +
-    scale_fill_manual(values = pitch_colors) +
-    scale_color_manual(values = pitch_colors) +
-    labs(title = "Velocity Distribution by Pitch Type",
-         x = "Velocity (mph)",
-         y = "") +
-    theme_minimal(base_size = 11) +
-    theme(
-      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
-      legend.position = "none",
-      strip.text.y.left = element_text(angle = 0, hjust = 1, face = "bold", size = 10),
-      strip.placement = "outside",
-      panel.grid.major.y = element_blank(),
-      panel.grid.minor = element_blank(),
-      axis.text.y = element_blank(),
-      axis.ticks.y = element_blank()
-    )
-}
-
-# Pitch locations by batter side
-create_location_by_side_plot <- function(data, player_name, batter_side, pitch_colors) {
-  pitcher_data <- data %>%
-    filter(Pitcher == player_name, BatterSide == batter_side,
-           !is.na(TaggedPitchType), TaggedPitchType != "Other",
-           !is.na(PlateLocSide), !is.na(PlateLocHeight))
-  
-  if (nrow(pitcher_data) == 0) {
-    return(ggplot() + 
-             annotate("rect", xmin = -0.83, xmax = 0.83, ymin = 1.5, ymax = 3.38,
-                      fill = NA, color = "black", size = 0.5) +
-             theme_void() + 
-             ggtitle(paste0("Locations vs ", batter_side, "HB")) +
-             theme(plot.title = element_text(size = 12, face = "bold", hjust = 0.5)))
-  }
-  
-  # Count pitches by type
-  pitch_count <- n_distinct(pitcher_data$TaggedPitchType)
-  
-  ggplot(pitcher_data, aes(x = -PlateLocSide, y = PlateLocHeight, fill = TaggedPitchType)) +
-    geom_point(alpha = 0.8, shape = 21, color = "black", stroke = 0.5, size = 4) +
-    facet_wrap(~ TaggedPitchType, ncol = pitch_count, 
-               labeller = labeller(TaggedPitchType = ~ "")) +
-    annotate("rect", xmin = -0.83, xmax = 0.83, ymin = 1.5, ymax = 3.38,
-             fill = NA, color = "black", size = 0.5) +
-    geom_segment(aes(x = -0.708, y = 0.15, xend = 0.708, yend = 0.15), color = "black", size = 0.5) +
-    geom_segment(aes(x = -0.708, y = 0.30, xend = -0.708, yend = 0.15), color = "black", size = 0.5) +
-    geom_segment(aes(x = 0.708, y = 0.30, xend = 0.708, yend = 0.15), color = "black", size = 0.5) +
-    geom_segment(aes(x = -0.708, y = 0.30, xend = 0.000, yend = 0.50), color = "black", size = 0.5) +
-    geom_segment(aes(x = 0.708, y = 0.30, xend = 0.000, yend = 0.50), color = "black", size = 0.5) +
-    scale_fill_manual(values = pitch_colors) +
-    scale_x_continuous(limits = c(-2, 2)) +
-    scale_y_continuous(limits = c(0, 4.5)) +
-    coord_fixed() +
-    ggtitle(paste0("Pitch Locations vs ", batter_side, "HB")) +
-    theme_void() +
-    theme(
-      plot.title = element_text(size = 12, face = "bold", hjust = 0.5),
-      legend.position = "none",
-      strip.text = element_text(size = 10, face = "bold"),
-      strip.placement = "outside"
-    )
-}
-
-# Create the comprehensive advanced pitcher PDF
-create_advanced_pitcher_pdf <- function(game_df, pitcher_name, output_file) {
-  if (length(dev.list()) > 0) try(dev.off(), silent = TRUE)
-  
-  pitch_colors <- c(
-    "Fastball" = "#FA8072", "Four-Seam" = "#FA8072", "Sinker" = "#fdae61",
-    "Slider" = "#A020F0", "Sweeper" = "magenta", "Curveball" = "#2c7bb6",
-    "ChangeUp" = "#90EE90", "Splitter" = "#90EE32", "Cutter" = "red"
-  )
-  
-  # Filter to pitcher's data
-  pitcher_df <- game_df %>% filter(Pitcher == pitcher_name)
-  if (nrow(pitcher_df) == 0) {
-    pdf(output_file, width = 11, height = 17)
-    grid.newpage()
-    grid.text("No data available for this pitcher", 
-              gp = gpar(fontsize = 16, fontface = "bold"))
-    dev.off()
-    return(output_file)
-  }
-  
-  game_day <- parse_game_day(pitcher_df)
-  
-  # Generate all components
-  summary_stats <- create_advanced_pitcher_summary(pitcher_df, pitcher_name)
-  pitch_char <- create_advanced_pitch_characteristics(pitcher_df, pitcher_name)
-  
-  break_plot <- create_advanced_break_plot(pitcher_df, pitcher_name, pitch_colors)
-  velo_plot <- create_velocity_distribution_plot(pitcher_df, pitcher_name, pitch_colors)
-  location_lhb <- create_location_by_side_plot(pitcher_df, pitcher_name, "Left", pitch_colors)
-  location_rhb <- create_location_by_side_plot(pitcher_df, pitcher_name, "Right", pitch_colors)
-  
-  # Create PDF
-  pdf(output_file, width = 11, height = 17)
-  on.exit(try(dev.off(), silent = TRUE), add = TRUE)
-  
-  grid.newpage()
-  
-  # Header
-  pushViewport(viewport(x = 0.5, y = 0.97, width = 1, height = 0.06, just = c("center", "top")))
-  grid.text(paste(pitcher_name, "- Advanced Pitcher Report -", format(game_day, "%m/%d/%y")),
-            gp = gpar(fontface = "bold", cex = 2.0, col = "#006F71"))
-  popViewport()
-  
-  # Game Summary Table
-  grid.text("Game Summary", x = 0.5, y = 0.90, 
-            gp = gpar(fontface = "bold", cex = 1.2, col = "#006F71"))
-  
-  summary_headers <- names(summary_stats)
-  summary_values <- as.numeric(summary_stats[1,])
-  summary_widths <- rep(0.06, length(summary_headers))
-  
-  x_start <- 0.5 - sum(summary_widths)/2
-  x_pos <- c(x_start, x_start + cumsum(summary_widths[-length(summary_widths)]))
-  y_top <- 0.88
-  row_h <- 0.022
-  
-  # Draw summary table
-  for (i in seq_along(summary_headers)) {
-    grid.rect(x = x_pos[i], y = y_top, width = summary_widths[i] * 0.985, height = row_h,
-              just = c("left", "top"), gp = gpar(fill = "#006F71", col = "black", lwd = 0.5))
-    grid.text(summary_headers[i], x = x_pos[i] + summary_widths[i] * 0.49, y = y_top - row_h * 0.5,
-              gp = gpar(col = "white", cex = 0.65, fontface = "bold"))
-    
-    grid.rect(x = x_pos[i], y = y_top - row_h, width = summary_widths[i] * 0.985, height = row_h,
-              just = c("left", "top"), gp = gpar(fill = "white", col = "black", lwd = 0.4))
-    grid.text(sprintf("%.1f", summary_values[i]), 
-              x = x_pos[i] + summary_widths[i] * 0.49, y = y_top - row_h * 1.5,
-              gp = gpar(cex = 0.65))
-  }
-  
-  # Pitch Characteristics Table
-  grid.text("Pitch Characteristics", x = 0.5, y = 0.82,
-            gp = gpar(fontface = "bold", cex = 1.2, col = "#006F71"))
-  
-  char_headers <- names(pitch_char)
-  char_widths <- c(0.10, rep(0.055, length(char_headers) - 1))
-  
-  x_start_char <- 0.5 - sum(char_widths)/2
-  x_pos_char <- c(x_start_char, x_start_char + cumsum(char_widths[-length(char_widths)]))
-  y_top_char <- 0.80
-  row_h_char <- 0.018
-  
-  # Draw pitch characteristics table header
-  for (i in seq_along(char_headers)) {
-    grid.rect(x = x_pos_char[i], y = y_top_char, width = char_widths[i] * 0.985, height = row_h_char,
-              just = c("left", "top"), gp = gpar(fill = "#006F71", col = "black", lwd = 0.5))
-    grid.text(char_headers[i], x = x_pos_char[i] + char_widths[i] * 0.49, y = y_top_char - row_h_char * 0.5,
-              gp = gpar(col = "white", cex = 0.60, fontface = "bold"))
-  }
-  
-  # Draw pitch characteristics table rows
-  for (r in 1:min(nrow(pitch_char), 6)) {
-    y_row <- y_top_char - r * row_h_char
-    for (i in seq_along(char_headers)) {
-      val <- pitch_char[[i]][r]
-      bg <- if (r %% 2 == 0) "#f7f7f7" else "white"
-      grid.rect(x = x_pos_char[i], y = y_row, width = char_widths[i] * 0.985, height = row_h_char,
-                just = c("left", "top"), gp = gpar(fill = bg, col = "grey80", lwd = 0.3))
-      display_val <- if (is.numeric(val)) sprintf("%.1f", val) else as.character(val)
-      grid.text(display_val, x = x_pos_char[i] + char_widths[i] * 0.49, y = y_row - row_h_char * 0.5,
-                gp = gpar(cex = 0.58))
-    }
-  }
-  
-  # Plot Movement (large, left)
-  pushViewport(viewport(x = 0.25, y = 0.57, width = 0.45, height = 0.24, just = c("center", "top")))
-  print(break_plot, newpage = FALSE)
-  popViewport()
-  
-  # Plot Velocity Distribution (large, right)
-  pushViewport(viewport(x = 0.75, y = 0.57, width = 0.45, height = 0.24, just = c("center", "top")))
-  print(velo_plot, newpage = FALSE)
-  popViewport()
-  
-  # Location plots
-  pushViewport(viewport(x = 0.25, y = 0.28, width = 0.45, height = 0.18, just = c("center", "top")))
-  print(location_lhb, newpage = FALSE)
-  popViewport()
-  
-  pushViewport(viewport(x = 0.75, y = 0.28, width = 0.45, height = 0.18, just = c("center", "top")))
-  print(location_rhb, newpage = FALSE)
-  popViewport()
-  
-  # Footer
-  grid.text("Data: TrackMan | Report Generated: Coastal Carolina Baseball",
-            x = 0.5, y = 0.03, gp = gpar(cex = 0.8, col = "grey50"))
-  
-  invisible(output_file)
-}
-
 create_pitcher_pitch_char <- function(game_data) {
   game_data %>%
     filter(TaggedPitchType != "Other", !is.na(TaggedPitchType)) %>%
@@ -2292,61 +1919,69 @@ server <- function(input, output, session) {
     }
   })
   
- 
-output$download_pitcher <- downloadHandler(
-  filename = function() {
-    df <- data_pitcher(); req(df, input$pitcher_name)
-    pitcher_clean <- gsub(" ", "_", input$pitcher_name)
-    date_str <- format(parse_game_day(df %>% filter(Pitcher == input$pitcher_name)), "%Y%m%d")
-    paste0(pitcher_clean, "_", date_str, "_Advanced_Pitcher_Report.pdf")
-  },
-  content = function(file) {
-    df <- data_pitcher(); req(df, input$pitcher_name)
-    withProgress(message='Generating Advanced Pitcher PDF', value=0, {
-      incProgress(.3, detail="Processing data...")
-      incProgress(.4, detail="Creating visualizations...")
-      create_advanced_pitcher_pdf(df, input$pitcher_name, file)
-      incProgress(.3, detail="Finalizing report...")
-    })
-    showNotification("✅ Advanced pitcher report generated!", type="message", duration=3)
-  },
-  contentType = "application/pdf"
-)
-
-# Update bulk download to use new function
-output$download_all_coastal_pitchers <- downloadHandler(
-  filename = function() {
-    df <- data_pitcher(); req(df)
-    paste0("Coastal_Advanced_Pitcher_Reports_", format(parse_game_day(df), "%Y%m%d"), ".zip")
-  },
-  content = function(file) {
-    df <- data_pitcher(); req(df)
-    pitchers <- df %>% dplyr::filter(PitcherTeam == "COA_CHA") %>%
-      dplyr::pull(Pitcher) %>% unique() %>% na.omit() %>% sort()
-    if (!length(pitchers)) { 
-      showNotification("No Coastal pitchers found", type="error", duration=5)
-      return(NULL)
-    }
-    withProgress(message='Generating Coastal Advanced Pitcher Reports', value=0, {
-      tmp <- tempdir(); pdfs <- character(0); total <- length(pitchers)
-      for (i in seq_along(pitchers)) {
-        ply <- pitchers[i]; incProgress(1/total, detail=paste("Report for", ply))
-        out <- file.path(tmp, paste0(gsub(" ","_",ply), "_",
-                                     format(parse_game_day(df), "%Y%m%d"),
-                                     "_Advanced_Pitcher_Report.pdf"))
-        try(create_advanced_pitcher_pdf(df, ply, out), silent = TRUE)
-        if (file.exists(out)) pdfs <- c(pdfs, out)
-      }
-      if (!length(pdfs)) {
-        showNotification("Failed to generate reports", type="error", duration=5)
+  output$download_pitcher <- downloadHandler(
+    filename = function() {
+      df <- data_pitcher(); req(df, input$pitcher_name)
+      pitcher_clean <- gsub(" ", "_", input$pitcher_name)
+      date_str <- format(parse_game_day(df %>% filter(Pitcher == input$pitcher_name)), "%Y%m%d")
+      paste0(pitcher_clean, "_", date_str, "_Pitcher_Report.pdf")
+    },
+    content = function(file) {
+      df <- data_pitcher(); req(df, input$pitcher_name)
+      pitch_colors <- c("Fastball"="#FA8072","Four-Seam"="#FA8072","Sinker"="#fdae61",
+                        "Slider"="#A020F0","Sweeper"="magenta","Curveball"="#2c7bb6",
+                        "ChangeUp"="#90EE90","Splitter"="#90EE32","Cutter"="red")
+      withProgress(message='Generating Pitcher PDF', value=0, {
+        incProgress(.3, detail="Processing data...")
+        incProgress(.4, detail="Creating visualizations...")
+        create_pitcher_pdf(df, input$pitcher_name, file, pitch_colors)
+        incProgress(.3, detail="Finalizing report...")
+      })
+      showNotification("✅ Pitcher report generated!", type="message", duration=3)
+    },
+    contentType = "application/pdf"
+  )
+  
+  # ---- Pitcher bulk ZIP
+  output$download_all_coastal_pitchers <- downloadHandler(
+    filename = function() {
+      df <- data_pitcher(); req(df)
+      paste0("Coastal_Pitcher_Reports_", format(parse_game_day(df), "%Y%m%d"), ".zip")
+    },
+    content = function(file) {
+      df <- data_pitcher(); req(df)
+      pitch_colors <- c(
+        "Fastball"="#FA8072","Four-Seam"="#FA8072","Sinker"="#fdae61",
+        "Slider"="#A020F0","Sweeper"="magenta","Curveball"="#2c7bb6",
+        "ChangeUp"="#90EE90","Splitter"="#90EE32","Cutter"="red"
+      )
+      pitchers <- df %>% dplyr::filter(PitcherTeam == "COA_CHA") %>%
+        dplyr::pull(Pitcher) %>% unique() %>% na.omit() %>% sort()
+      if (!length(pitchers)) { 
+        showNotification("No Coastal pitchers found", type="error", duration=5)
         return(NULL)
       }
-      zip::zip(zipfile=file, files=basename(pdfs), root=tmp); unlink(pdfs)
-    })
-    showNotification("✅ Coastal pitcher ZIP ready!", type="message", duration=5)
-  },
-  contentType = "application/zip"
-)
+      withProgress(message='Generating Coastal Pitcher Reports', value=0, {
+        tmp <- tempdir(); pdfs <- character(0); total <- length(pitchers)
+        for (i in seq_along(pitchers)) {
+          ply <- pitchers[i]; incProgress(1/total, detail=paste("Report for", ply))
+          out <- file.path(tmp, paste0(gsub(" ","_",ply), "_",
+                                       format(parse_game_day(df), "%Y%m%d"),
+                                       "_Pitcher_Report.pdf"))
+          try(create_pitcher_pdf(df, ply, out, pitch_colors), silent = TRUE)
+          if (file.exists(out)) pdfs <- c(pdfs, out)
+        }
+        if (!length(pdfs)) {
+          showNotification("Failed to generate reports", type="error", duration=5)
+          return(NULL)
+        }
+        zip::zip(zipfile=file, files=basename(pdfs), root=tmp); unlink(pdfs)
+      })
+      showNotification("✅ Coastal pitcher ZIP ready!", type="message", duration=5)
+    },
+    contentType = "application/zip"
+  )
+  
   
   output$status_message <- renderUI({
     if (input$report_type == "hitter") {