Update app.R

app.R

@@ -1,1332 +1,511 @@
-# ============================================================================
-# COASTAL CAROLINA BASEBALL - DEFENSIVE ANALYTICS APPLICATION
-# ============================================================================
 library(shiny)
 library(DT)
-library(ggplot2)
-library(dplyr)
-library(plotly)
+library(htmltools)
 library(gt)
-library(gtExtras)
-library(shinyWidgets)
-library(tidyr)
-library(purrr)
-library(stringr)
-library(fmsb)
-# ============================================================================
-# HELPER FUNCTIONS
-# ============================================================================
-
-make_curve_segments <- function(x_start, y_start, x_end, y_end, curvature = 0.3, n = 40) {
-  if (n < 2) stop("n must be >= 2")
-  t <- seq(0, 1, length.out = n)
-  
-  cx <- (x_start + x_end) / 2 + curvature * (y_end - y_start)
-  cy <- (y_start + y_end) / 2 - curvature * (x_end - x_start)
-  
-  x <- (1 - t)^2 * x_start + 2 * (1 - t) * t * cx + t^2 * x_end
-  y <- (1 - t)^2 * y_start + 2 * (1 - t) * t * cy + t^2 * y_end
-  
-  idx_from <- seq_len(n - 1)
-  idx_to   <- seq_len(n - 1) + 1
-  
-  tibble::tibble(
-    x    = x[idx_from],
-    y    = y[idx_from],
-    xend = x[idx_to],
-    yend = y[idx_to]
-  )
-}
-
-curve1 <- make_curve_segments(89.095, 89.095, -1, 160, curvature = 0.36, n = 60)
-curve2 <- make_curve_segments(-89.095, 89.095, 1, 160, curvature = -0.36, n = 60)
-curve3 <- make_curve_segments(233.35, 233.35, -10, 410, curvature = 0.36, n = 60)
-curve4 <- make_curve_segments(-233.35, 233.35, 10, 410, curvature = -0.36, n = 60)
-
-# ============================================================================
-# SYNTHETIC DATA GENERATION
-# ============================================================================
-
-set.seed(42)
-
-# Team rosters
-cc_players <- c("Smith, John", "Johnson, Mike", "Williams, Chris", "Brown, David", 
-                "Jones, Tyler", "Garcia, Alex", "Martinez, Ryan", "Davis, Kyle",
-                "Rodriguez, Sam", "Wilson, Jake")
-
-opponent_teams <- c("Georgia Southern", "Appalachian State", "Troy", "Texas State",
-                    "South Alabama", "Arkansas State", "Louisiana", "ULM")
-
-opponent_players <- c("Thompson, Mark", "Anderson, Jake", "Taylor, Ben", "Thomas, Cole",
-                      "Jackson, Drew", "White, Nick", "Harris, Luke", "Martin, Josh",
-                      "Moore, Zach", "Lee, Grant")
-
-positions <- c("RF", "CF", "LF")
-infield_positions <- c("SS", "1B", "2B", "3B")
-
-# Generate Outfield OAA data
-generate_of_oaa_data <- function(n = 500, team = "CCU") {
-  players <- if(team == "CCU") cc_players else opponent_players
-  
-  tibble(
-    PitchUID = paste0("P", 1:n),
-    Date = sample(seq(as.Date("2025-02-14"), as.Date("2025-05-30"), by = "day"), n, replace = TRUE),
-    obs_player = sample(players[1:4], n, replace = TRUE),
-    hit_location = sample(positions, n, replace = TRUE),
-    Batter = sample(opponent_players, n, replace = TRUE),
-    Pitcher = sample(cc_players[5:8], n, replace = TRUE),
-    Inning = sample(1:9, n, replace = TRUE),
-    BatterTeam = if(team == "CCU") sample(opponent_teams, n, replace = TRUE) else "CCU",
-    PitcherTeam = if(team == "CCU") "CCU" else sample(opponent_teams, n, replace = TRUE),
-    closest_pos_dist = runif(n, 5, 120),
-    HangTime = runif(n, 2.5, 5.5),
-    x_pos = runif(n, 100, 350),
-    z_pos = runif(n, -200, 200),
-    CF_PositionAtReleaseX = runif(n, 280, 320),
-    CF_PositionAtReleaseZ = runif(n, -20, 20),
-    RF_PositionAtReleaseX = runif(n, 250, 290),
-    RF_PositionAtReleaseZ = runif(n, 80, 140),
-    LF_PositionAtReleaseX = runif(n, 250, 290),
-    LF_PositionAtReleaseZ = runif(n, -140, -80),
-    angle_from_home = runif(n, -180, 180),
-    ExitSpeed = runif(n, 70, 110),
-    Angle = runif(n, 15, 45)
-  ) %>%
-    mutate(
-      # Calculate catch probability based on distance and hang time
-      catch_prob = pmax(0, pmin(1, 1 - (closest_pos_dist / 150) + (HangTime - 3) * 0.2 + rnorm(n, 0, 0.1))),
-      # Determine success based on probability with some randomness
-      success_ind = rbinom(n, 1, pmin(0.95, pmax(0.05, catch_prob + rnorm(n, 0, 0.15)))),
-      # Calculate OAA
-      OAA = success_ind - catch_prob,
-      star_group = case_when(
-        catch_prob >= 0.90 ~ "1 Star",
-        catch_prob >= 0.70 ~ "2 Star",
-        catch_prob >= 0.50 ~ "3 Star",
-        catch_prob >= 0.25 ~ "4 Star",
-        TRUE ~ "5 Star"
-      )
-    )
-}
+library(plotly)
 
-# Generate Infield OAA data
-generate_if_oaa_data <- function(n = 400, team = "CCU") {
-  players <- if(team == "CCU") cc_players else opponent_players
-  
-  tibble(
-    PitchUID = paste0("IF", 1:n),
-    Date = sample(seq(as.Date("2025-02-14"), as.Date("2025-05-30"), by = "day"), n, replace = TRUE),
-    obs_player_name = sample(players[5:8], n, replace = TRUE),
-    obs_player = sample(infield_positions, n, replace = TRUE),
-    Batter = sample(opponent_players, n, replace = TRUE),
-    Pitcher = sample(cc_players[1:4], n, replace = TRUE),
-    Inning = sample(1:9, n, replace = TRUE),
-    BatterTeam = if(team == "CCU") sample(opponent_teams, n, replace = TRUE) else "CCU",
-    Distance = runif(n, 50, 150),
-    Bearing = runif(n, -45, 45),
-    ExitSpeed = runif(n, 60, 110),
-    Angle = runif(n, -10, 30),
-    HangTime = runif(n, 1.5, 4.0),
-    obs_player_bearing = runif(n, -45, 45),
-    obs_player_x = runif(n, 80, 130),
-    obs_player_z = runif(n, -60, 60),
-    Direction = sample(c("Pull", "Center", "Oppo"), n, replace = TRUE)
-  ) %>%
-    mutate(
-      obs_player_bearing_diff = Bearing - obs_player_bearing,
-      dist_from_lead_base = sqrt((Distance * cos(Bearing * pi/180) - 90)^2 + (Distance * sin(Bearing * pi/180))^2),
-      player_angle_rad = atan2(obs_player_z, obs_player_x),
-      # Calculate play probability
-      play_prob = pmax(0, pmin(1, 0.8 - abs(obs_player_bearing_diff) * 0.02 - Distance * 0.003 + rnorm(n, 0, 0.1))),
-      success_ind = rbinom(n, 1, pmin(0.95, pmax(0.05, play_prob + rnorm(n, 0, 0.12)))),
-      OAA = success_ind - play_prob,
-      star_group = case_when(
-        play_prob >= 0.90 ~ "1 Star",
-        play_prob >= 0.70 ~ "2 Star",
-        play_prob >= 0.50 ~ "3 Star",
-        play_prob >= 0.25 ~ "4 Star",
-        TRUE ~ "5 Star"
-      )
-    )
-}
+# ============================================================
+# PASSWORD
+# ============================================================
+PASSWORD <- Sys.getenv("password")
 
-# Generate Positioning data
-generate_positioning_data <- function(n = 800) {
-  tibble(
-    PitchUID = paste0("POS", 1:n),
-    Date = sample(seq(as.Date("2025-02-14"), as.Date("2025-05-30"), by = "day"), n, replace = TRUE),
-    PitcherTeam = sample(c("CCU", opponent_teams), n, replace = TRUE),
-    BatterTeam = sample(c("CCU", opponent_teams), n, replace = TRUE),
-    Pitcher = sample(c(cc_players, opponent_players), n, replace = TRUE),
-    Batter = sample(c(cc_players, opponent_players), n, replace = TRUE),
-    BatterSide = sample(c("Right", "Left"), n, replace = TRUE, prob = c(0.6, 0.4)),
-    PitcherThrows = sample(c("Right", "Left"), n, replace = TRUE, prob = c(0.7, 0.3)),
-    Outs = sample(0:2, n, replace = TRUE),
-    pitch_count = sample(c("0-0", "0-1", "0-2", "1-0", "1-1", "1-2", "2-0", "2-1", "2-2", "3-0", "3-1", "3-2"), n, replace = TRUE),
-    man_on_firstbase = sample(c(0, 1), n, replace = TRUE, prob = c(0.7, 0.3)),
-    man_on_secondbase = sample(c(0, 1), n, replace = TRUE, prob = c(0.8, 0.2)),
-    man_on_thirdbase = sample(c(0, 1), n, replace = TRUE, prob = c(0.9, 0.1)),
-    away_team = sample(opponent_teams, n, replace = TRUE),
-    home_score_before = sample(0:8, n, replace = TRUE),
-    away_score_before = sample(0:8, n, replace = TRUE),
-    `1B_PositionAtReleaseX` = rnorm(n, 85, 8),
-    `1B_PositionAtReleaseZ` = rnorm(n, 45, 10),
-    `2B_PositionAtReleaseX` = rnorm(n, 115, 10),
-    `2B_PositionAtReleaseZ` = rnorm(n, 35, 12),
-    `3B_PositionAtReleaseX` = rnorm(n, 85, 8),
-    `3B_PositionAtReleaseZ` = rnorm(n, -45, 10),
-    `SS_PositionAtReleaseX` = rnorm(n, 115, 10),
-    `SS_PositionAtReleaseZ` = rnorm(n, -35, 12),
-    `LF_PositionAtReleaseX` = rnorm(n, 270, 15),
-    `LF_PositionAtReleaseZ` = rnorm(n, -110, 20),
-    `CF_PositionAtReleaseX` = rnorm(n, 300, 15),
-    `CF_PositionAtReleaseZ` = rnorm(n, 0, 25),
-    `RF_PositionAtReleaseX` = rnorm(n, 270, 15),
-    `RF_PositionAtReleaseZ` = rnorm(n, 110, 20)
+# ============================================================
+# LOGIN UI
+# ============================================================
+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")
   )
-}
-
-# Generate Catcher data
-generate_catcher_data <- function(n = 1000) {
-  catchers <- c("Martinez, Ryan", "Wilson, Jake")
-  
-  tibble(
-    PitchUID = paste0("C", 1:n),
-    Date = sample(seq(as.Date("2025-02-14"), as.Date("2025-05-30"), by = "day"), n, replace = TRUE),
-    Catcher = sample(catchers, n, replace = TRUE),
-    Pitcher = sample(cc_players[1:6], n, replace = TRUE),
-    Batter = sample(opponent_players, n, replace = TRUE),
-    BatterTeam = sample(opponent_teams, n, replace = TRUE),
-    TaggedPitchType = sample(c("Fastball", "Sinker", "Slider", "Curveball", "ChangeUp", "Cutter"), n, replace = TRUE, prob = c(0.35, 0.15, 0.2, 0.12, 0.12, 0.06)),
-    PitchCall = sample(c("BallCalled", "StrikeCalled", "StrikeSwinging", "InPlay", "FoulBall"), n, replace = TRUE, prob = c(0.3, 0.25, 0.15, 0.15, 0.15)),
-    PlateLocSide = rnorm(n, 0, 0.8),
-    PlateLocHeight = rnorm(n, 2.5, 0.6),
-    RelSpeed = rnorm(n, 88, 6),
-    InducedVertBreak = rnorm(n, 12, 5),
-    HorzBreak = rnorm(n, 5, 8),
-    Balls = sample(0:3, n, replace = TRUE),
-    Strikes = sample(0:2, n, replace = TRUE),
-    PopTime = ifelse(runif(n) > 0.85, runif(n, 1.85, 2.15), NA),
-    ThrowSpeed = ifelse(!is.na(PopTime), rnorm(sum(!is.na(PopTime)), 78, 4), NA),
-    ExchangeTime = ifelse(!is.na(PopTime), rnorm(sum(!is.na(PopTime)), 0.75, 0.08), NA),
-    TimeToBase = ifelse(!is.na(PopTime), PopTime - ExchangeTime, NA),
-    BasePositionZ = ifelse(!is.na(PopTime), rnorm(sum(!is.na(PopTime)), 0, 2), NA),
-    BasePositionY = ifelse(!is.na(PopTime), rnorm(sum(!is.na(PopTime)), 5, 1.5), NA),
-    Notes = ifelse(!is.na(PopTime), sample(c("2b out", "2b safe", "3b out", "3b safe"), sum(!is.na(PopTime)), replace = TRUE, prob = c(0.4, 0.3, 0.2, 0.1)), NA)
-  ) %>%
-    mutate(
-      in_zone = as.integer(PlateLocSide >= -0.83 & PlateLocSide <= 0.83 & PlateLocHeight >= 1.5 & PlateLocHeight <= 3.38),
-      is_swing = as.integer(PitchCall %in% c("StrikeSwinging", "InPlay", "FoulBall")),
-      StolenStrike = as.integer(in_zone == 0 & PitchCall == "StrikeCalled"),
-      StrikeLost = as.integer(in_zone == 1 & PitchCall == "BallCalled"),
-      frame = case_when(
-        in_zone == 1 & PitchCall == "BallCalled" ~ "Strike Lost",
-        in_zone == 0 & PitchCall == "StrikeCalled" ~ "Strike Added",
-        TRUE ~ NA_character_
-      ),
-      frame_numeric = case_when(
-        in_zone == 1 & PitchCall == "BallCalled" ~ -1,
-        in_zone == 0 & PitchCall == "StrikeCalled" ~ 1,
-        TRUE ~ NA_real_
-      ),
-      Count = paste0(Balls, "-", Strikes)
-    )
-}
-
+)
 
+# ============================================================
+# MAIN APP UI
+# ============================================================
+app_ui <- fluidPage(
+  tags$head(
+    tags$style(HTML("
+      body, table, .gt_table { font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Helvetica, Arial, sans-serif; }
+      .app-header { display:flex; justify-content:space-between; align-items:center; padding:20px 40px; background:#ffffff; border-bottom:3px solid darkcyan; margin-bottom:20px; }
+      .header-logo-left, .header-logo-right { width:120px; height:auto; }
+      .header-logo-center { max-width:400px; height:auto; }
+      @media (max-width:768px){
+        .app-header{ flex-direction:column; padding:15px 20px; }
+        .header-logo-left, .header-logo-right { width:80px; }
+        .header-logo-center { max-width:250px; margin:10px 0; }
+      }
+      .nav-tabs{ border:none !important; border-radius:50px; padding:6px 12px; margin:20px auto 0; 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; -webkit-overflow-scrolling:touch; display:flex; justify-content:center; align-items:center; flex-wrap:wrap; gap:6px; }
+      .nav-tabs::-webkit-scrollbar{ height:0; }
+      .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:14.5px; padding:10px 22px; white-space:nowrap; letter-spacing:.2px; 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), inset 0 -2px 6px rgba(0,0,0,.2);
+        border:1px solid rgba(255,255,255,.3) !important; }
+      .nav-tabs>li>a:focus{ outline:3px solid rgba(205,133,63,.6); outline-offset:2px; }
+      .tab-content{ background:linear-gradient(135deg, rgba(255,255,255,.95), rgba(248,249,250,.95)); border-radius:20px; padding:25px; margin-top:14px; box-shadow:0 15px 40px rgba(0,139,139,.1); backdrop-filter:blur(15px); 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 { background:#ffffff; border-radius:12px; border:1px solid rgba(0,139,139,.15); box-shadow:0 6px 18px rgba(0,0,0,.06); }
+      .control-label{ font-weight:700; color:#0a6a6a; }
+      .selectize-input, .form-control{ border-radius:10px; border:1px solid rgba(0,139,139,.35); }
+      .datatables, .dataTables_wrapper .dataTables_filter input{ border-radius:10px; }
+      .gt_table{ border-radius:12px; overflow:hidden; border:1px solid rgba(0,139,139,.15); }
+      .placeholder-box { background: #f8fafa; border: 2px dashed rgba(0,139,139,.25); border-radius: 12px;
+        padding: 60px 20px; text-align: center; color: #8aacac; font-size: 16px; font-weight: 600; margin: 10px 0; }
+      .section-header { color: darkcyan; border-bottom: 2px solid peru; padding-bottom: 6px; margin-bottom: 16px; }
+    "))
+  ),
 
-# Initialize datasets
-OAA_DF <- generate_of_oaa_data(500, "CCU")
-IF_OAA <- generate_if_oaa_data(400, "CCU")
-OPP_OAA_DF <- generate_of_oaa_data(500, "OPP")
-OPP_IF_OAA <- generate_if_oaa_data(400, "OPP")
-def_pos_data <- generate_positioning_data(800)
-catcher_data <- generate_catcher_data(1000)
+  # ---- Header ----
+  div(class = "app-header",
+      tags$img(src = "https://i.imgur.com/7vx5Ci8.png", class = "header-logo-left", alt = "Logo Left"),
+      tags$img(src = "https://i.imgur.com/Sq0CZ0F.png", class = "header-logo-center", alt = "Main Logo"),
+      tags$img(src = "https://i.imgur.com/VbrN5WV.png", class = "header-logo-right", alt = "Logo Right")
+  ),
 
-# ============================================================================
-# VISUALIZATION FUNCTIONS
-# ============================================================================
+  # ---- Tabs ----
+  tabsetPanel(
+    id = "tabs",
 
-# Star graph for outfielders
-star_graph <- function(player, position, data = OAA_DF) {
-  if (position %in% c("RF", "CF", "LF")) {
-    player_data <- data %>% 
-      filter(obs_player == player) %>% 
-      filter(hit_location == position)
-  } else {
-    player_data <- data %>% 
-      filter(obs_player == player) %>% 
-      mutate(hit_location = "All")
-  }
-  
-  if (nrow(player_data) == 0) {
-    return(ggplotly(ggplot() + theme_void() + ggtitle("No data available")))
-  }
-  
-  OAA <- round(sum(player_data$OAA, na.rm = TRUE), 1)
-  n_plays <- nrow(player_data)
-  expected_success <- round(sum(player_data$catch_prob, na.rm = TRUE), 1)
-  actual_success <- sum(player_data$success_ind, na.rm = TRUE)
-  
-  p <- ggplot(data, aes(closest_pos_dist, HangTime)) + 
-    stat_summary_2d(aes(z = catch_prob), fun = mean, bins = 51) +
-    scale_fill_gradientn(
-      colors = c("white", "#ffffb2", "#feb24c", "#fc4e2a", "#800026"),
-      limits = c(0, 1),
-      breaks = c(0.01, 0.25, 0.5, 0.7, 0.9, 1),
-      labels = c("5 Star", "4 Star", "3 Star", "2 Star", "1 Star", " "),
-      name = "Catch Rating",
-      guide = guide_colorbar(barheight = unit(5, "in"))
-    ) +
-    scale_x_continuous("Distance to Ball (ft)", limits = c(0, 140), breaks = seq(0, 140, by = 20)) +
-    scale_y_continuous("Hang Time (sec)", limits = c(2, 6)) +
-    theme_classic() +
-    ggtitle(paste0(player, " - ", position, " (", OAA, " OAA)")) +
-    theme(
-      legend.position = "right",
-      plot.title = element_text(hjust = .5, size = 20),
-      legend.title = element_blank(),
-      panel.grid.minor = element_blank(),
-      axis.title = element_text(size = 12),
-      axis.text = element_text(size = 10)
-    )
-  
-  point_colors <- ifelse(player_data$success_ind == 1, "green4", "white")
-  
-  p_interactive <- suppressWarnings({
-    ggplotly(p, tooltip = NULL) %>%
-      add_trace(
-        data = player_data,
-        x = ~closest_pos_dist,
-        y = ~HangTime,
-        type = "scatter",
-        mode = "markers",
-        color = I(point_colors),
-        marker = list(size = 10, line = list(color = "black", width = 1)),
-        text = ~paste0(
-          "Date: ", Date, "<br>",
-          "Batter: ", Batter, "<br>", 
-          "Pitcher: ", Pitcher, "<br>",
-          "Inning: ", Inning, "<br>",
-          "Opportunity Time: ", round(HangTime, 2), " sec<br>",
-          "Distance Needed: ", round(closest_pos_dist, 1), " ft<br>",
-          "Catch Probability: ", round(100 * catch_prob, 1), "%<br>",
-          star_group
-        ),
-        hoverinfo = "text"
-      ) %>%
-      layout(
-        hovermode = "closest",
-        title = list(
-          text = paste0(player, " - ", position,
-                        "<br><sup>OAA: ", OAA, " | Plays: ", n_plays,
-                        " | Expected Catches: ", expected_success, " | Actual Catches: ", actual_success, "</sup>"),
-          font = list(size = 18)
+    # =============================================
+    # TAB 1: Outfield OAA
+    # =============================================
+    tabPanel("Outfield OAA",
+      sidebarLayout(
+        sidebarPanel(
+          width = 3,
+          selectInput("of_player", "Player:", choices = NULL),
+          hr(),
+          checkboxGroupInput("of_year_select", "Year:",
+                             choices = c("2025", "2026"),
+                             selected = c("2025", "2026")),
+          hr(),
+          selectInput("of_position", "Position:",
+                      choices = c("LF", "CF", "RF", "ALL"),
+                      selected = "CF")
         ),
-        margin = list(t = 80)
+        mainPanel(
+          width = 9,
+          h4("Star Graph (Catch Difficulty)", class = "section-header"),
+          div(class = "placeholder-box", "Star Graph \u2014 plotly scatter on catch probability grid"),
+          hr(),
+          h4("Field Graph (Catch Locations)", class = "section-header"),
+          div(class = "placeholder-box", "Field Graph \u2014 plotly spray on field outline with catch/hit markers"),
+          gt::gt_output("of_field_graph_table"),
+          hr(),
+          h4("Directional OAA", class = "section-header"),
+          div(class = "placeholder-box", "Radar Chart \u2014 OAA by direction (Back, Left, In, Right, etc.)"),
+          gt::gt_output("of_direction_oaa_table")
+        )
       )
-  })
-  
-  return(p_interactive)
-}
-
-# Field graph for outfielders
-field_graph <- function(player, position, data = OAA_DF) {
-  if (position %in% c("RF", "CF", "LF")) {
-    player_data <- data %>% 
-      filter(obs_player == player) %>% 
-      filter(hit_location == position) 
-  } else {
-    player_data <- data %>% 
-      filter(obs_player == player) %>% 
-      mutate(hit_location = "All")
-  }
-  
-  if (nrow(player_data) == 0) {
-    return(list(
-      ggplotly(ggplot() + theme_void() + ggtitle("No data available")),
-      gt(data.frame(Message = "No data")) %>% tab_header(title = "Play Success by Difficulty")
-    ))
-  }
-  
-  df_filtered <- player_data %>% 
-    mutate(
-      avg_y = mean(CF_PositionAtReleaseX, na.rm = TRUE),
-      avg_x = mean(CF_PositionAtReleaseZ, na.rm = TRUE)
-    )
-  
-  df_table <- df_filtered %>% 
-    group_by(star_group) %>% 
-    summarize(
-      OAA = round(sum(OAA, na.rm = TRUE), 1),
-      Plays = n(),
-      Successes = sum(success_ind, na.rm = TRUE),
-      .groups = "drop"
-    ) %>% 
-    mutate(`Success Rate` = paste0(Successes, "/", Plays, " (", round((Successes/Plays)*100, 1), "%)")) %>% 
-    dplyr::select(`Star Group` = star_group, `Success Rate`) %>% 
-    t() %>% as.data.frame() %>%
-    `colnames<-`(.[1,]) %>% tibble::as_tibble() %>% dplyr::slice(-1) %>%
-    mutate(OAA = round(sum(df_filtered$OAA, na.rm = TRUE), 2)) %>% 
-    dplyr::select(OAA, everything()) %>% 
-    gt::gt() %>%
-    gtExtras::gt_theme_guardian() %>%
-    gt::tab_header(title = "Play Success by Difficulty") %>%
-    gt::cols_align(align = "center", columns = gt::everything()) %>%
-    gt::sub_missing(columns = gt::everything(), missing_text = "-") %>%
-    gt::tab_options(
-      heading.background.color = "darkcyan",
-      column_labels.background.color = "darkcyan",
-      table.border.top.color = "peru",
-      table.border.bottom.color = "peru"
-    ) %>%
-    gt::tab_style(style = gt::cell_text(color = "white"), locations = gt::cells_title(groups = "title"))
-  
-  p <- ggplot() +
-    geom_segment(aes(x = 0, y = 0, xend = 318.1981, yend = 318.1981), color = "black") +
-    geom_segment(aes(x = 0, y = 0, xend = -318.1981, yend = 318.1981), color = "black") +
-    geom_segment(aes(x = 63.6396, y = 63.6396, xend = 0, yend = 127.279), color = "black") +
-    geom_segment(aes(x = -63.6396, y = 63.6396, xend = 0, yend = 127.279), color = "black") +
-    geom_segment(data = curve1, aes(x = x, y = y, xend = xend, yend = yend), size = 0.5, color = "black", lineend = "round") +
-    geom_segment(data = curve2, aes(x = x, y = y, xend = xend, yend = yend), size = 0.5, color = "black", lineend = "round") +
-    annotate("text", x = c(-155, 155), y = 135, label = "200", size = 3) +
-    annotate("text", x = c(-190, 190), y = 170, label = "250", size = 3) +
-    annotate("text", x = c(-227, 227), y = 205, label = "300", size = 3) +
-    annotate("text", x = c(-262, 262), y = 242, label = "350", size = 3) +
-    theme_void() +
-    geom_point(
-      data = df_filtered %>% mutate(is_catch = ifelse(success_ind == 1, 'Catch', "Hit")),
-      aes(x = z_pos, y = x_pos, fill = is_catch,
-          text = paste0("Date: ", Date, "<br>",
-                        "Catch Probability: ", round(100 * catch_prob, 1), "%<br>", star_group)),
-      color = "black", shape = 21, size = 2, alpha = .6
-    ) +
-    labs(title = paste0(player, " Possible Catches - ", position)) +
-    scale_fill_manual(values = c("Hit" = "white", "Catch" = "green4"), name = " ") +
-    geom_point(data = df_filtered, aes(x = avg_x, y = avg_y), fill = "red", color = "black", size = 3, shape = 21) +
-    coord_cartesian(xlim = c(-330, 330), ylim = c(0, 400)) + 
-    coord_equal()
-  
-  p <- ggplotly(p, tooltip = "text") %>% plotly::layout(hovermode = "closest")
-  
-  return(list(p, df_table))
-}
+    ),
 
-# Infield star graph
-infield_star_graph <- function(player, position, data = IF_OAA) {
-  if (position %in% c("SS", "1B", "2B", "3B")) {
-    player_data <- data %>% 
-      filter(obs_player_name == player) %>% 
-      filter(obs_player == position)
-  } else {
-    player_data <- data %>% 
-      filter(obs_player_name == player) %>% 
-      mutate(obs_player = "All")
-  }
-  
-  if (nrow(player_data) == 0) {
-    return(ggplotly(ggplot() + theme_void() + ggtitle("No data available")))
-  }
-  
-  OAA <- round(sum(player_data$OAA, na.rm = TRUE), 1)
-  n_plays <- nrow(player_data)
-  expected_success <- round(sum(player_data$play_prob, na.rm = TRUE), 1)
-  actual_success <- sum(player_data$success_ind, na.rm = TRUE)
-  
-  points_data <- player_data %>%
-    filter(play_prob > 0) %>%
-    filter(play_prob <= 0.5 | between(obs_player_bearing_diff, -12.5, 12.5))
-  
-  p <- ggplot(data, aes(obs_player_bearing_diff, play_prob)) + 
-    stat_summary_2d(aes(z = play_prob), fun = mean, bins = 15) +
-    scale_fill_gradientn(
-      colors = c("white", "#ffffb2", "#feb24c", "#fc4e2a", "#800026"),
-      limits = c(0, 1),
-      breaks = c(0.01, 0.25, 0.5, 0.7, 0.9, 1),
-      labels = c("5 Star", "4 Star", "3 Star", "2 Star", "1 Star", " "),
-      name = "Play Rating"
-    ) +
-    scale_x_continuous("Bearing Difference (degrees)", limits = c(-25, 25), breaks = seq(-25, 25, by = 12.5)) +
-    scale_y_continuous("Play Probability", limits = c(0, 1), labels = scales::percent) +
-    theme_minimal() +
-    theme(
-      legend.position = "right",
-      plot.title = element_text(hjust = 0.5, size = 18, face = "bold"),
-      panel.grid.minor = element_blank(),
-      axis.title = element_text(size = 12),
-      axis.text = element_text(size = 10)
-    )
-  
-  point_colors <- ifelse(points_data$success_ind == 1, "green4", "white")
-  
-  p_interactive <- suppressWarnings({
-    ggplotly(p, tooltip = NULL) %>%
-      add_trace(
-        data = points_data,
-        x = ~obs_player_bearing_diff,
-        y = ~play_prob,
-        type = "scatter",
-        mode = "markers",
-        color = I(point_colors),
-        marker = list(size = 10, line = list(color = "black", width = 1)),
-        text = ~paste0(
-          "Date: ", Date, "<br>",
-          "Batter: ", Batter, "<br>", 
-          "Play Probability: ", round(100 * play_prob, 1), "%<br>",
-          "Angular Distance Away: ", round(obs_player_bearing_diff, 1), "°<br>",
-          "Exit Velocity: ", round(ExitSpeed, 1), " mph<br>",
-          star_group
-        ),
-        hoverinfo = "text"
-      ) %>%
-      layout(
-        hovermode = "closest",
-        title = list(
-          text = paste0(player, " - ", position,
-                        "<br><sup>OAA: ", OAA, " | Plays: ", n_plays,
-                        " | Expected: ", expected_success, " | Actual: ", actual_success, "</sup>"),
-          font = list(size = 18)
+    # =============================================
+    # TAB 2: Infield OAA
+    # =============================================
+    tabPanel("Infield OAA",
+      sidebarLayout(
+        sidebarPanel(
+          width = 3,
+          selectInput("if_player", "Player:", choices = NULL),
+          hr(),
+          selectInput("if_position", "Position:",
+                      choices = c("SS", "2B", "3B", "1B", "ALL"),
+                      selected = "SS")
         ),
-        margin = list(t = 80)
+        mainPanel(
+          width = 9,
+          h4("Star Graph (Play Difficulty)", class = "section-header"),
+          div(class = "placeholder-box", "Infield Star Graph \u2014 bearing diff vs play probability with star ratings"),
+          hr(),
+          h4("Field Graph (Play Locations)", class = "section-header"),
+          div(class = "placeholder-box", "Infield Field Graph \u2014 batted ball locations with play made/not made markers"),
+          gt::gt_output("if_field_graph_table")
+        )
       )
-  })
-  
-  suppressWarnings(p_interactive)
-}
-
-# Infield field graph
-infield_field_graph <- function(player, position, data = IF_OAA) {
-  if (position %in% c("SS", "1B", "2B", "3B")) {
-    player_data <- data %>% 
-      filter(obs_player_name == player) %>% 
-      filter(obs_player == position)
-  } else {
-    player_data <- data %>% 
-      filter(obs_player_name == player)
-  }
-  
-  if (nrow(player_data) == 0) {
-    return(list(
-      ggplotly(ggplot() + theme_void() + ggtitle("No data available")),
-      gt(data.frame(Message = "No data")) %>% tab_header(title = "Play Success by Difficulty")
-    ))
-  }
-  
-  df_filtered <- player_data %>% 
-    mutate(
-      rad = Bearing * pi/180,
-      x_pos = Distance * cos(rad),
-      z_pos = Distance * sin(rad),
-      avg_y = mean(obs_player_x, na.rm = TRUE),
-      avg_x = mean(obs_player_z, na.rm = TRUE)
-    )
-  
-  df_table <- df_filtered %>% 
-    group_by(star_group) %>% 
-    summarize(
-      OAA = round(sum(OAA, na.rm = TRUE), 1),
-      Plays = n(),
-      Successes = sum(success_ind, na.rm = TRUE),
-      .groups = "drop"
-    ) %>% 
-    mutate(`Success Rate` = paste0(Successes, "/", Plays, " (", round((Successes/Plays)*100, 1), "%)")) %>% 
-    dplyr::select(`Star Group` = star_group, `Success Rate`) %>% 
-    t() %>% as.data.frame() %>%
-    `colnames<-`(.[1,]) %>% dplyr::slice(-1) %>%
-    mutate(OAA = round(sum(df_filtered$OAA, na.rm = TRUE), 1)) %>% 
-    dplyr::select(OAA, everything()) %>% 
-    gt::gt() %>%
-    gtExtras::gt_theme_guardian() %>%
-    gt::tab_header(title = "Play Success by Difficulty") %>%
-    gt::cols_align(align = "center", columns = gt::everything()) %>%
-    gt::sub_missing(columns = gt::everything(), missing_text = "-") %>%
-    gt::tab_options(
-      heading.background.color = "darkcyan",
-      column_labels.background.color = "darkcyan"
-    ) %>%
-    gt::tab_style(style = gt::cell_text(color = "white"), locations = gt::cells_title(groups = "title"))
-  
-  p <- ggplot() +
-    geom_segment(aes(x = 0, y = 0, xend = 100, yend = 100), color = "black") +
-    geom_segment(aes(x = 0, y = 0, xend = -100, yend = 100), color = "black") +
-    geom_segment(aes(x = 63.6396, y = 63.6396, xend = 0, yend = 127.279), color = "black") +
-    geom_segment(aes(x = -63.6396, y = 63.6396, xend = 0, yend = 127.279), color = "black") +
-    geom_segment(data = curve1, aes(x = x, y = y, xend = xend, yend = yend), size = 0.5, color = "black") +
-    geom_segment(data = curve2, aes(x = x, y = y, xend = xend, yend = yend), size = 0.5, color = "black") +
-    theme_void() +
-    geom_point(
-      data = df_filtered %>% mutate(is_play = ifelse(success_ind == 1, 'Play Made', "Not Made")),
-      aes(x = z_pos, y = x_pos, fill = is_play,
-          text = paste0("Date: ", Date, "<br>", "Play Probability: ", round(100 * play_prob, 1), "%<br>", star_group)),
-      color = "black", shape = 21, size = 2, alpha = .6
-    ) +
-    labs(title = paste0(player, " Possible Plays - ", position)) +
-    scale_fill_manual(values = c("Not Made" = "white", "Play Made" = "green4"), name = " ") +
-    geom_point(data = df_filtered, aes(x = avg_x, y = avg_y), fill = "red", color = "black", size = 3, shape = 21) +
-    ylim(0, 160) + xlim(-120, 120) + coord_equal()
-  
-  p <- ggplotly(p, tooltip = "text") %>% plotly::layout(hovermode = "closest")
-  
-  return(list(p, df_table))
-}
-
-# Positioning heatmap
-infield_positioning_heatmap <- function(team, batter_hand = "No Filter", pitcher_hand = "No Filter",
-                                        man_on_first = "No Filter", man_on_second = "No Filter", man_on_third = "No Filter") {
-  
-  team_data <- def_pos_data %>% filter(PitcherTeam == team)
-  
-  if (batter_hand != "No Filter") team_data <- team_data %>% filter(BatterSide == batter_hand)
-  if (pitcher_hand != "No Filter") team_data <- team_data %>% filter(PitcherThrows == pitcher_hand)
-  if (man_on_first != "No Filter") team_data <- team_data %>% filter(man_on_firstbase == as.numeric(man_on_first == "Yes"))
-  if (man_on_second != "No Filter") team_data <- team_data %>% filter(man_on_secondbase == as.numeric(man_on_second == "Yes"))
-  if (man_on_third != "No Filter") team_data <- team_data %>% filter(man_on_thirdbase == as.numeric(man_on_third == "Yes"))
-  
-  n_observations <- nrow(team_data)
-  
-  if (n_observations < 10) {
-    return(ggplot() + theme_void() + ggtitle("Insufficient data for selected filters"))
-  }
-  
-  positions_long <- team_data %>%
-    pivot_longer(
-      cols = matches("^(1B|2B|3B|SS|LF|CF|RF)_PositionAtRelease[XZ]$"),
-      names_to = c("position", ".value"),
-      names_pattern = "^(.+)_PositionAtRelease([XZ])$"
-    )
-  
-  p <- ggplot() +
-    geom_hline(yintercept = seq(0, 400, by = 20), linetype = "dotted", color = "gray80", size = 0.3) +
-    geom_vline(xintercept = seq(-240, 240, by = 20), linetype = "dotted", color = "gray80", size = 0.3) +
-    geom_density_2d_filled(data = positions_long, aes(x = Z, y = X), bins = 35, alpha = 0.5) +
-    scale_fill_manual(values = colorRampPalette(c("#FFFFFF", "#FFF5F0", "#FEE0D2", "#FCBBA1",
-                                                  "#FC9272", "#FB6A4A", "#EF3B2C", "#CB181D", "#99000D"))(35)) +
-    geom_segment(aes(x = 0, y = 0, xend = 233.35, yend = 233.35), color = "black") +
-    geom_segment(aes(x = 0, y = 0, xend = -233.35, yend = 233.35), color = "black") +
-    geom_segment(aes(x = 63.6396, y = 63.6396, xend = 0, yend = 127.279), color = "black") +
-    geom_segment(aes(x = -63.6396, y = 63.6396, xend = 0, yend = 127.279), color = "black") +
-    geom_segment(data = curve1, aes(x = x, y = y, xend = xend, yend = yend), size = 0.5, color = "black") +
-    geom_segment(data = curve2, aes(x = x, y = y, xend = xend, yend = yend), size = 0.5, color = "black") +
-    geom_segment(data = curve3, aes(x = x, y = y, xend = xend, yend = yend), size = 0.5, color = "black") +
-    geom_segment(data = curve4, aes(x = x, y = y, xend = xend, yend = yend), size = 0.5, color = "black") +
-    labs(
-      title = paste0("Starting Fielder Position — ", team),
-      subtitle = paste0("Based on ", n_observations, " observations"),
-      x = "", y = ""
-    ) + 
-    ylim(0, 411) + xlim(-250, 250) + coord_equal() + 
-    theme_void() +
-    theme(
-      legend.position = "none",
-      plot.title = element_text(hjust = .5, size = 20, face = "bold"),
-      plot.subtitle = element_text(hjust = 0.5)
-    )
-  
-  return(p)
-}
-
-# ============================================================================
-# UI
-# ============================================================================
+    ),
 
-ui <- fluidPage(
-  tags$head(
-    tags$style(HTML("
-      @import url('https://fonts.googleapis.com/css2?family=Outfit:wght@300;400;500;600;700;800&display=swap');
-      
-      body { 
-        font-family: 'Outfit', sans-serif; 
-        background: linear-gradient(135deg, #f5f7fa 0%, #e4e9f2 100%);
-        color: #2c3e50;
-      }
-      
-      .app-header {
-        display: flex;
-        justify-content: center;
-        align-items: center;
-        padding: 25px 40px;
-        background: linear-gradient(135deg, #006F71 0%, #008B8B 50%, #20B2AA 100%);
-        border-bottom: 4px solid #A27752;
-        margin-bottom: 25px;
-        box-shadow: 0 8px 32px rgba(0, 111, 113, 0.3);
-      }
-      
-      .header-title {
-        color: white;
-        font-size: 2.2rem;
-        font-weight: 800;
-        text-shadow: 2px 2px 4px rgba(0,0,0,0.2);
-        letter-spacing: 1px;
-      }
-      
-      .header-subtitle {
-        color: rgba(255,255,255,0.9);
-        font-size: 1rem;
-        font-weight: 400;
-        margin-top: 5px;
-      }
-      
-      .nav-tabs {
-        border: none !important;
-        border-radius: 50px;
-        padding: 8px 16px;
-        margin: 20px auto;
-        max-width: 95%;
-        background: linear-gradient(135deg, #d4edeb 0%, #e8ddd0 50%, #d4edeb 100%);
-        box-shadow: 0 4px 20px rgba(0,139,139,.15), inset 0 2px 4px rgba(255,255,255,.7);
-        display: flex;
-        justify-content: center;
-        flex-wrap: wrap;
-        gap: 8px;
-      }
-      
-      .nav-tabs > li > a {
-        color: #006F71 !important;
-        border: none !important;
-        border-radius: 50px !important;
-        background: transparent !important;
-        font-weight: 600;
-        font-size: 15px;
-        padding: 12px 28px;
-        transition: all 0.3s ease;
-        letter-spacing: 0.3px;
-      }
-      
-      .nav-tabs > li > a:hover {
-        color: #004d4e !important;
-        background: rgba(255,255,255,0.6) !important;
-        transform: translateY(-2px);
-      }
-      
-      .nav-tabs > li.active > a,
-      .nav-tabs > li.active > a:focus,
-      .nav-tabs > li.active > a:hover {
-        background: linear-gradient(135deg, #006F71 0%, #008B8B 50%, #20B2AA 100%) !important;
-        color: #fff !important;
-        text-shadow: 0 1px 2px rgba(0,0,0,0.2);
-        box-shadow: 0 6px 20px rgba(0,139,139,0.4);
-        border: none !important;
-      }
-      
-      .tab-content {
-        background: white;
-        border-radius: 20px;
-        padding: 30px;
-        margin-top: 15px;
-        box-shadow: 0 10px 40px rgba(0,0,0,0.08);
-        border: 1px solid rgba(0,139,139,0.1);
-      }
-      
-      .well {
-        background: linear-gradient(135deg, #f8fffe 0%, #f5f5f0 100%);
-        border-radius: 15px;
-        border: 1px solid rgba(0,139,139,0.15);
-        box-shadow: 0 4px 15px rgba(0,0,0,0.05);
-        padding: 20px;
-      }
-      
-      .control-label {
-        font-weight: 600;
-        color: #006F71;
-        font-size: 13px;
-        text-transform: uppercase;
-        letter-spacing: 0.5px;
-        margin-bottom: 8px;
-      }
-      
-      .selectize-input, .form-control {
-        border-radius: 12px !important;
-        border: 2px solid rgba(0,139,139,0.25) !important;
-        padding: 10px 15px !important;
-        font-size: 14px !important;
-        transition: all 0.3s ease;
-      }
-      
-      .selectize-input:focus, .form-control:focus {
-        border-color: #006F71 !important;
-        box-shadow: 0 0 0 3px rgba(0,139,139,0.15) !important;
-      }
-      
-      .section-header {
-        font-size: 1.4rem;
-        font-weight: 700;
-        color: #006F71;
-        margin-bottom: 20px;
-        padding-bottom: 10px;
-        border-bottom: 3px solid #A27752;
-      }
-      
-      .metric-card {
-        background: linear-gradient(135deg, #006F71 0%, #008B8B 100%);
-        border-radius: 15px;
-        padding: 20px;
-        color: white;
-        text-align: center;
-        box-shadow: 0 6px 20px rgba(0,139,139,0.3);
-        margin-bottom: 15px;
-      }
-      
-      .metric-value {
-        font-size: 2.5rem;
-        font-weight: 800;
-      }
-      
-      .metric-label {
-        font-size: 0.9rem;
-        opacity: 0.9;
-        text-transform: uppercase;
-        letter-spacing: 1px;
-      }
-      
-      .btn-primary {
-        background: linear-gradient(135deg, #006F71 0%, #008B8B 100%) !important;
-        border: none !important;
-        border-radius: 12px !important;
-        font-weight: 600 !important;
-        padding: 12px 25px !important;
-        transition: all 0.3s ease !important;
-      }
-      
-      .btn-primary:hover {
-        transform: translateY(-2px);
-        box-shadow: 0 6px 20px rgba(0,139,139,0.4) !important;
-      }
-      
-      .gt_table {
-        border-radius: 12px !important;
-        overflow: hidden;
-      }
-      
-      hr {
-        border-top: 2px solid rgba(162, 119, 82, 0.3);
-        margin: 30px 0;
-      }
-    "))
-  ),
-  
-  # Header
-  div(class = "app-header",
-      div(style = "text-align: center;",
-          div(class = "header-title", "Defensive Analytics Dashboard"),
-          div(class = "header-subtitle", "Coastal Carolina Baseball • Spring 2025")
-      )
-  ),
-  
-  # Main tabs
-  tabsetPanel(
-    id = "main_tabs",
-    
-    # ==================== TAB 1: TEAM OAA ====================
-    tabPanel(
-      "Team OAA",
-      br(),
-      fluidRow(
-        column(12, h3(class = "section-header", "Outfielder Outs Above Average"))
-      ),
-      fluidRow(
-        column(3, wellPanel(
-          selectInput("of_player", "Select Player:", choices = unique(OAA_DF$obs_player)),
-          selectInput("of_position", "Position:", choices = c("All", "RF", "CF", "LF")),
+    # =============================================
+    # TAB 3: Receiving (Catcher Framing)
+    # =============================================
+    tabPanel("Receiving",
+      sidebarLayout(
+        sidebarPanel(
+          width = 3,
+          selectInput("recv_catcher", "Catcher:", choices = NULL),
           hr(),
-          h5("Quick Stats"),
-          uiOutput("of_quick_stats")
-        )),
-        column(9,
-               plotlyOutput("of_star_graph", height = "500px"),
-               br(),
-               fluidRow(
-                 column(6, plotlyOutput("of_field_graph", height = "450px")),
-                 column(6, gt_output("of_success_table"))
-               )
+          checkboxGroupInput("recv_year", "Year:",
+                             choices = c("2025", "2026"),
+                             selected = c("2025", "2026")),
+          hr(),
+          selectInput("recv_pitcher_filter", "Pitcher:",
+                      choices = c("All"), selected = "All"),
+          hr(),
+          checkboxGroupInput("recv_pitch_type", "Pitch Type:",
+                             choices = c("Fastball", "Sinker", "Cutter", "Slider",
+                                         "Curveball", "ChangeUp", "Splitter"),
+                             selected = c("Fastball", "Sinker", "Cutter", "Slider",
+                                          "Curveball", "ChangeUp", "Splitter"),
+                             inline = FALSE),
+          hr(),
+          selectInput("recv_count_filter", "Count:",
+                      choices = c("All", "0-0", "0-1", "0-2", "1-0", "1-1", "1-2",
+                                  "2-0", "2-1", "2-2", "3-0", "3-1", "3-2"),
+                      selected = "All")
+        ),
+        mainPanel(
+          width = 9,
+          h4("Framing Heatmap (Called Strike Probability)", class = "section-header"),
+          div(class = "placeholder-box", "Strike zone heatmap \u2014 called strike added probability by location"),
+          hr(),
+          h4("Shadow Zone Performance", class = "section-header"),
+          fluidRow(
+            column(6, div(class = "placeholder-box", "Shadow zone framing rate \u2014 zone edge called strike %")),
+            column(6, div(class = "placeholder-box", "Framing runs by zone quadrant"))
+          ),
+          hr(),
+          h4("Receiving Summary", class = "section-header"),
+          gt::gt_output("recv_summary_table"),
+          hr(),
+          h4("Opponent Receiving Comparison", class = "section-header"),
+          div(class = "placeholder-box", "Opponent catcher framing stats comparison table")
         )
-      ),
-      hr(),
-      fluidRow(
-        column(12, h3(class = "section-header", "Infielder Outs Above Average"))
-      ),
-      fluidRow(
-        column(3, wellPanel(
-          selectInput("if_player", "Select Player:", choices = unique(IF_OAA$obs_player_name)),
-          selectInput("if_position", "Position:", choices = c("All", "SS", "2B", "3B", "1B"))
-        )),
-        column(9,
-               plotlyOutput("if_star_graph", height = "500px"),
-               br(),
-               fluidRow(
-                 column(6, plotlyOutput("if_field_graph", height = "400px")),
-                 column(6, gt_output("if_success_table"))
-               )
+      )
+    ),
+
+    # =============================================
+    # TAB 4: Throwing (Catcher Arm)
+    # =============================================
+    tabPanel("Throwing",
+      sidebarLayout(
+        sidebarPanel(
+          width = 3,
+          selectInput("throw_catcher", "Catcher:", choices = NULL),
+          hr(),
+          checkboxGroupInput("throw_year", "Year:",
+                             choices = c("2025", "2026"),
+                             selected = c("2025", "2026")),
+          hr(),
+          selectInput("throw_base", "Target Base:",
+                      choices = c("All", "2nd Base", "3rd Base"),
+                      selected = "All")
+        ),
+        mainPanel(
+          width = 9,
+          h4("Throwing Accuracy Map", class = "section-header"),
+          div(class = "placeholder-box", "Throw location scatter \u2014 accuracy to base with pop time labels"),
+          hr(),
+          h4("Pop Time Distribution", class = "section-header"),
+          fluidRow(
+            column(6, div(class = "placeholder-box", "Pop time histogram / density plot")),
+            column(6, div(class = "placeholder-box", "Pop time by game date trend line"))
+          ),
+          hr(),
+          h4("Throwing Summary", class = "section-header"),
+          gt::gt_output("throw_summary_table"),
+          hr(),
+          h4("Stolen Base Prevention", class = "section-header"),
+          div(class = "placeholder-box", "CS% breakdown \u2014 attempts, caught, allowed, by runner speed tier")
         )
-      ),
-      hr(),
-      fluidRow(
-        column(12, h3(class = "section-header", "Team OAA Leaderboard")),
-        column(12, DT::dataTableOutput("team_oaa_leaderboard"))
       )
     ),
-    
-    # ==================== TAB 2: OPPONENT OAA ====================
-    tabPanel(
-      "Opponent OAA",
-      br(),
-      fluidRow(
-        column(12, h3(class = "section-header", "Opponent Outfield Defense Analysis"))
-      ),
+
+    # =============================================
+    # TAB 5: Catching Leaderboard
+    # =============================================
+    tabPanel("Catching Leaderboard",
       fluidRow(
-        column(3, wellPanel(
-          selectInput("opp_team_filter", "Opponent Team:", 
-                      choices = c("All", unique(OPP_OAA_DF$PitcherTeam))),
-          selectInput("opp_of_player", "Select Player:", choices = unique(OPP_OAA_DF$obs_player)),
-          selectInput("opp_of_position", "Position:", choices = c("All", "RF", "CF", "LF"))
-        )),
+        column(3,
+          wellPanel(
+            checkboxGroupInput("clb_year", "Year:",
+                               choices = c("2025", "2026"),
+                               selected = c("2025", "2026")),
+            hr(),
+            selectInput("clb_sort_by", "Sort By:",
+                        choices = c("Total Catching Runs", "Framing Runs",
+                                    "Throwing Runs", "Blocking Runs", "Pop Time"),
+                        selected = "Total Catching Runs"),
+            hr(),
+            checkboxGroupInput("clb_columns", "Columns:",
+                               choices = c("Framing Runs", "Strike Rate Added",
+                                           "Shadow Zone %", "Pop Time (avg)",
+                                           "Pop Time (best)", "CS%", "SB Allowed",
+                                           "Throwing Runs", "Blocking Runs",
+                                           "Passed Balls", "Wild Pitches",
+                                           "Total Catching Runs"),
+                               selected = c("Framing Runs", "Pop Time (avg)",
+                                            "CS%", "Total Catching Runs"),
+                               inline = FALSE)
+          )
+        ),
         column(9,
-               plotlyOutput("opp_of_star_graph", height = "500px"),
-               br(),
-               fluidRow(
-                 column(6, plotlyOutput("opp_of_field_graph", height = "450px")),
-                 column(6, gt_output("opp_of_success_table"))
-               )
+          h4("Catcher Leaderboard", style = "text-align: center; color: darkcyan;"),
+          div(class = "placeholder-box", "Catcher leaderboard DT table \u2014 sortable, color-coded"),
+          hr(),
+          h4("Catcher Comparison", style = "text-align: center; color: darkcyan;"),
+          div(class = "placeholder-box", "Side-by-side catcher radar or bar chart comparison")
         )
-      ),
-      hr(),
-      fluidRow(
-        column(12, h3(class = "section-header", "Opponent Infield Defense Analysis"))
-      ),
-      fluidRow(
-        column(3, wellPanel(
-          selectInput("opp_if_player", "Select Player:", choices = unique(OPP_IF_OAA$obs_player_name)),
-          selectInput("opp_if_position", "Position:", choices = c("All", "SS", "2B", "3B", "1B"))
-        )),
-        column(9,
-               plotlyOutput("opp_if_star_graph", height = "500px")
+      )
+    ),
+
+    # =============================================
+    # TAB 6: 6th Tool Fielding
+    # =============================================
+    tabPanel("6th Tool Fielding",
+      sidebarLayout(
+        sidebarPanel(
+          width = 3,
+          selectInput("st_player", "Player:", choices = NULL),
+          hr(),
+          checkboxGroupInput("st_year", "Year:",
+                             choices = c("2025", "2026"),
+                             selected = c("2025", "2026")),
+          hr(),
+          selectInput("st_position", "Position:",
+                      choices = c("All", "P", "C", "1B", "2B", "3B", "SS",
+                                  "LF", "CF", "RF"),
+                      selected = "All"),
+          hr(),
+          selectInput("st_play_type", "Play Type:",
+                      choices = c("All", "Routine", "Likely", "Even",
+                                  "Unlikely", "Remote"),
+                      selected = "All")
+        ),
+        mainPanel(
+          width = 9,
+          h4("Fielding Overview", class = "section-header"),
+          fluidRow(
+            column(4, div(class = "placeholder-box", "Fielding % gauge")),
+            column(4, div(class = "placeholder-box", "Range factor gauge")),
+            column(4, div(class = "placeholder-box", "Errors committed gauge"))
+          ),
+          hr(),
+          h4("Play Breakdown by Difficulty", class = "section-header"),
+          div(class = "placeholder-box", "Star-group table \u2014 plays made vs expected by 1\u20135 star difficulty"),
+          hr(),
+          h4("Error Log", class = "section-header"),
+          div(class = "placeholder-box", "Detailed error log \u2014 date, opponent, inning, play description"),
+          hr(),
+          h4("Positioning & First Step", class = "section-header"),
+          fluidRow(
+            column(6, div(class = "placeholder-box", "Average starting position on field diagram")),
+            column(6, div(class = "placeholder-box", "First-step quickness distribution"))
+          ),
+          hr(),
+          h4("Defensive Runs Saved Breakdown", class = "section-header"),
+          gt::gt_output("st_drs_table")
         )
-      ),
-      hr(),
-      fluidRow(
-        column(12, h3(class = "section-header", "Opponent OAA Summary")),
-        column(12, DT::dataTableOutput("opp_oaa_leaderboard"))
       )
     ),
-    
-    # ==================== TAB 3: OPPONENT POSITIONING ====================
-    tabPanel(
-      "Opponent Positioning",
-      br(),
-      fluidRow(
-        column(12, h3(class = "section-header", "Defensive Positioning Analysis"))
-      ),
-      fluidRow(
-        column(3, wellPanel(
-          selectInput("pos_team", "Select Team:", 
-                      choices = c("CCU", unique(def_pos_data$PitcherTeam[def_pos_data$PitcherTeam != "CCU"]))),
+
+    # =============================================
+    # TAB 7: Baserunning
+    # =============================================
+    tabPanel("Baserunning",
+      sidebarLayout(
+        sidebarPanel(
+          width = 3,
+          selectInput("br_player", "Player:", choices = NULL),
           hr(),
-          h5("Situational Filters", style = "font-weight: 600; color: #006F71;"),
-          selectInput("pos_batter_hand", "Batter Hand:", choices = c("No Filter", "Right", "Left")),
-          selectInput("pos_pitcher_hand", "Pitcher Hand:", choices = c("No Filter", "Right", "Left")),
+          checkboxGroupInput("br_year", "Year:",
+                             choices = c("2025", "2026"),
+                             selected = c("2025", "2026")),
           hr(),
-          h5("Baserunners", style = "font-weight: 600; color: #006F71;"),
-          selectInput("pos_first", "Runner on 1st:", choices = c("No Filter", "Yes", "No")),
-          selectInput("pos_second", "Runner on 2nd:", choices = c("No Filter", "Yes", "No")),
-          selectInput("pos_third", "Runner on 3rd:", choices = c("No Filter", "Yes", "No"))
-        )),
-        column(9,
-               plotOutput("positioning_heatmap", height = "650px")
+          selectInput("br_event_type", "Event Type:",
+                      choices = c("All", "Stolen Bases", "Extra Bases Taken",
+                                  "Advances on Fly", "Advances on Wild Pitch/PB",
+                                  "Home to First"),
+                      selected = "All")
+        ),
+        mainPanel(
+          width = 9,
+          h4("Baserunning Overview", class = "section-header"),
+          fluidRow(
+            column(3, div(class = "placeholder-box", "SB attempts")),
+            column(3, div(class = "placeholder-box", "SB success %")),
+            column(3, div(class = "placeholder-box", "Extra bases taken")),
+            column(3, div(class = "placeholder-box", "Baserunning runs"))
+          ),
+          hr(),
+          h4("Sprint Speed", class = "section-header"),
+          fluidRow(
+            column(6, div(class = "placeholder-box", "Home-to-first time distribution / trend")),
+            column(6, div(class = "placeholder-box", "Sprint speed percentile vs team / conference"))
+          ),
+          hr(),
+          h4("Stolen Base Detail", class = "section-header"),
+          div(class = "placeholder-box", "SB attempt log \u2014 date, base, pitcher, catcher, result, lead distance, jump time"),
+          hr(),
+          h4("Extra Bases Taken", class = "section-header"),
+          div(class = "placeholder-box", "Advancement opportunities vs taken \u2014 1st-to-3rd, 2nd-to-home, tag-up"),
+          hr(),
+          h4("Baserunning Runs Summary", class = "section-header"),
+          gt::gt_output("br_summary_table"),
+          hr(),
+          h4("Team Baserunning Leaderboard", class = "section-header"),
+          div(class = "placeholder-box", "Team baserunning leaderboard DT table")
         )
-      ),
-      hr(),
-      fluidRow(
-        column(12, h3(class = "section-header", "Average Positioning by Situation")),
-        column(12, gt_output("positioning_summary"))
       )
     ),
-    
-    # ==================== TAB 4: CATCHING ANALYSIS ====================
-    tabPanel(
-      "Catching Analysis",
-      br(),
+
+    # =============================================
+    # TAB 8: Team Defensive Positioning
+    # =============================================
+    tabPanel("Team Defensive Positioning",
       fluidRow(
-        column(12, h3(class = "section-header", "Catcher Framing & Throwing"))
+        column(2, selectInput("dp_team", "Team:", choices = c("Coastal Carolina"), selected = "Coastal Carolina")),
+        column(2, selectInput("dp_man_on_first", "Runner on 1st:", choices = c("No Filter", TRUE, FALSE), selected = "No Filter")),
+        column(2, selectInput("dp_man_on_second", "Runner on 2nd:", choices = c("No Filter", TRUE, FALSE), selected = "No Filter")),
+        column(2, selectInput("dp_man_on_third", "Runner on 3rd:", choices = c("No Filter", TRUE, FALSE), selected = "No Filter")),
+        column(2, selectInput("dp_batter_hand", "Bat Hand:", choices = c("No Filter", "Right", "Left"), selected = "No Filter"))
       ),
       fluidRow(
-        column(3, wellPanel(
-          selectInput("catcher_select", "Select Catcher:", choices = unique(catcher_data$Catcher)),
-          hr(),
-          h5("Framing Filters", style = "font-weight: 600; color: #006F71;"),
-          pickerInput("pitch_type_filter", "Pitch Types:",
-                      choices = unique(catcher_data$TaggedPitchType),
-                      selected = unique(catcher_data$TaggedPitchType),
-                      multiple = TRUE, options = list(`actions-box` = TRUE)),
-          numericInput("min_pitches_catcher", "Min Pitches:", value = 50, min = 1, max = 500)
-        )),
-        column(9,
-               fluidRow(
-                 column(4, div(class = "metric-card",
-                               div(class = "metric-value", textOutput("catcher_net_strikes")),
-                               div(class = "metric-label", "Net Strikes")
-                 )),
-                 column(4, div(class = "metric-card",
-                               div(class = "metric-value", textOutput("catcher_frame_rate")),
-                               div(class = "metric-label", "Frame Rate")
-                 )),
-                 column(4, div(class = "metric-card",
-                               div(class = "metric-value", textOutput("catcher_avg_pop")),
-                               div(class = "metric-label", "Avg Pop Time")
-                 ))
-               ),
-               br(),
-               fluidRow(
-                 column(6, 
-                        h4("Framing Heatmap"),
-                        plotOutput("catcher_framing_heatmap", height = "500px")),
-                 column(6, 
-                        h4("Framing Points"),
-                        plotlyOutput("catcher_framing_points", height = "500px"))
-               )
-        )
+        column(2, selectInput("dp_pitcher_hand", "Pitch Hand:", choices = c("No Filter", "Right", "Left"), selected = "No Filter")),
+        column(2, selectInput("dp_scorediff", "Score Diff:", choices = c("No Filter", -4:4), selected = "No Filter")),
+        column(2, dateInput("dp_date_from", "From:", value = "2025-02-14")),
+        column(2, dateInput("dp_date_to", "To:", value = "2026-06-22")),
+        column(2, selectInput("dp_pitcher", "Pitcher:", choices = c("No Filter"), selected = "No Filter"))
       ),
-      hr(),
       fluidRow(
-        column(6,
-               h4("Throwing Accuracy Map"),
-               plotOutput("catcher_throw_map", height = "500px")),
-        column(6,
-               h4("Pop Time Distribution"),
-               plotlyOutput("catcher_pop_dist", height = "250px"),
-               h4("Throw Velocity Trend"),
-               plotlyOutput("catcher_velo_trend", height = "250px"))
+        column(2, selectInput("dp_hitter", "Batter:", choices = c("No Filter"), selected = "No Filter")),
+        column(2, selectInput("dp_count", "Count:", choices = c("No Filter"), selected = "No Filter")),
+        column(2, selectInput("dp_outs", "Outs:", choices = c("No Filter", 0, 1, 2), selected = "No Filter")),
+        column(2, selectInput("dp_opponent", "Opponent:", choices = c("No Filter"), selected = "No Filter"))
       ),
       hr(),
+      div(class = "placeholder-box", style = "min-height: 500px;",
+          "Defensive Positioning Heatmap \u2014 density contours on field diagram with median position markers")
+    ),
+
+    # =============================================
+    # TAB 9: OAA Leaderboard
+    # =============================================
+    tabPanel("OAA Leaderboard",
       fluidRow(
-        column(12, h3(class = "section-header", "Catcher Leaderboard")),
-        column(12, DT::dataTableOutput("catcher_leaderboard"))
+        column(3,
+          wellPanel(
+            checkboxGroupInput("oaa_lb_year", "Year:",
+                               choices = c("2025", "2026"),
+                               selected = c("2025", "2026")),
+            hr(),
+            selectInput("oaa_lb_group", "Position Group:",
+                        choices = c("All Positions", "Outfield (OF)",
+                                    "Infield (IF)", "By Position"),
+                        selected = "All Positions"),
+            hr(),
+            sliderInput("oaa_lb_min_plays", "Min Plays:",
+                        min = 1, max = 100, value = 10, step = 1),
+            hr(),
+            selectInput("oaa_lb_sort", "Sort By:",
+                        choices = c("Total OAA", "OAA per Play",
+                                    "Success Rate Added", "Plays Made",
+                                    "5-Star Plays"),
+                        selected = "Total OAA"),
+            hr(),
+            checkboxGroupInput("oaa_lb_columns", "Columns:",
+                               choices = c("OAA", "OAA/Play", "Plays",
+                                           "Expected Catches", "Actual Catches",
+                                           "Success Rate", "Success Rate Added",
+                                           "1-Star Made", "2-Star Made",
+                                           "3-Star Made", "4-Star Made",
+                                           "5-Star Made"),
+                               selected = c("OAA", "Plays", "Success Rate",
+                                            "Success Rate Added"),
+                               inline = FALSE)
+          )
+        ),
+        column(9,
+          h4("OAA Leaderboard", style = "text-align: center; color: darkcyan;"),
+          div(class = "placeholder-box", "OAA leaderboard DT table \u2014 sortable, color-coded by OAA value"),
+          hr(),
+          h4("OAA by Star Group", style = "text-align: center; color: darkcyan;"),
+          div(class = "placeholder-box", "Stacked bar chart \u2014 OAA contribution by difficulty tier per player"),
+          hr(),
+          h4("Team OAA Summary", style = "text-align: center; color: darkcyan;"),
+          gt::gt_output("oaa_lb_team_summary")
+        )
       )
     )
-    )
   )
+)
 
-# ============================================================================
-# SERVER
-# ============================================================================
+# ============================================================
+# ROOT UI (login gating)
+# ============================================================
+ui <- fluidPage(uiOutput("mainUI"))
 
+# ============================================================
+# SERVER
+# ============================================================
 server <- function(input, output, session) {
-  
-  # ==================== TAB 1: TEAM OAA ====================
-  
-  output$of_quick_stats <- renderUI({
-    player_data <- OAA_DF %>% filter(obs_player == input$of_player)
-    if (input$of_position != "All") {
-      player_data <- player_data %>% filter(hit_location == input$of_position)
+
+  # ---- Auth ----
+  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$wrong_pass <- renderText("Incorrect password.")
     }
-    
-    total_oaa <- round(sum(player_data$OAA, na.rm = TRUE), 1)
-    plays <- nrow(player_data)
-    success_rate <- round(mean(player_data$success_ind) * 100, 1)
-    
-    tagList(
-      div(class = "metric-card", style = "padding: 12px;",
-          div(class = "metric-value", style = "font-size: 1.8rem;", total_oaa),
-          div(class = "metric-label", "Total OAA")
-      ),
-      div(class = "metric-card", style = "padding: 12px; background: linear-gradient(135deg, #A27752 0%, #c49a6c 100%);",
-          div(class = "metric-value", style = "font-size: 1.8rem;", plays),
-          div(class = "metric-label", "Total Plays")
-      ),
-      div(class = "metric-card", style = "padding: 12px; background: linear-gradient(135deg, #2c3e50 0%, #4a6278 100%);",
-          div(class = "metric-value", style = "font-size: 1.8rem;", paste0(success_rate, "%")),
-          div(class = "metric-label", "Success Rate")
-      )
-    )
-  })
-  
-  output$of_star_graph <- renderPlotly({
-    star_graph(input$of_player, input$of_position, OAA_DF)
-  })
-  
-  of_field_results <- reactive({
-    field_graph(input$of_player, input$of_position, OAA_DF)
-  })
-  
-  output$of_field_graph <- renderPlotly({
-    of_field_results()[[1]]
-  })
-  
-  output$of_success_table <- render_gt({
-    of_field_results()[[2]]
-  })
-  
-  output$if_star_graph <- renderPlotly({
-    infield_star_graph(input$if_player, input$if_position, IF_OAA)
-  })
-  
-  if_field_results <- reactive({
-    infield_field_graph(input$if_player, input$if_position, IF_OAA)
-  })
-  
-  output$if_field_graph <- renderPlotly({
-    if_field_results()[[1]]
-  })
-  
-  output$if_success_table <- render_gt({
-    if_field_results()[[2]]
-  })
-  
-  output$team_oaa_leaderboard <- DT::renderDataTable({
-    of_summary <- OAA_DF %>%
-      group_by(Player = obs_player) %>%
-      summarise(
-        `OF OAA` = round(sum(OAA, na.rm = TRUE), 1),
-        `OF Plays` = n(),
-        `OF Success %` = round(mean(success_ind) * 100, 1),
-        .groups = "drop"
-      )
-    
-    if_summary <- IF_OAA %>%
-      group_by(Player = obs_player_name) %>%
-      summarise(
-        `IF OAA` = round(sum(OAA, na.rm = TRUE), 1),
-        `IF Plays` = n(),
-        `IF Success %` = round(mean(success_ind) * 100, 1),
-        .groups = "drop"
-      )
-    
-    full_join(of_summary, if_summary, by = "Player") %>%
-      mutate(
-        `Total OAA` = coalesce(`OF OAA`, 0) + coalesce(`IF OAA`, 0)
-      ) %>%
-      arrange(desc(`Total OAA`)) %>%
-      DT::datatable(
-        options = list(pageLength = 15, scrollX = TRUE),
-        rownames = FALSE
-      )
-  })
-  
-  # ==================== TAB 2: OPPONENT OAA ====================
-  
-  output$opp_of_star_graph <- renderPlotly({
-    star_graph(input$opp_of_player, input$opp_of_position, OPP_OAA_DF)
-  })
-  
-  opp_of_field_results <- reactive({
-    field_graph(input$opp_of_player, input$opp_of_position, OPP_OAA_DF)
-  })
-  
-  output$opp_of_field_graph <- renderPlotly({
-    opp_of_field_results()[[1]]
-  })
-  
-  output$opp_of_success_table <- render_gt({
-    opp_of_field_results()[[2]]
-  })
-  
-  output$opp_if_star_graph <- renderPlotly({
-    infield_star_graph(input$opp_if_player, input$opp_if_position, OPP_IF_OAA)
-  })
-  
-  output$opp_oaa_leaderboard <- DT::renderDataTable({
-    opp_summary <- OPP_OAA_DF %>%
-      group_by(Player = obs_player, Team = PitcherTeam) %>%
-      summarise(
-        OAA = round(sum(OAA, na.rm = TRUE), 1),
-        Plays = n(),
-        `Success %` = round(mean(success_ind) * 100, 1),
-        .groups = "drop"
-      ) %>%
-      arrange(desc(OAA))
-    
-    DT::datatable(opp_summary, options = list(pageLength = 15), rownames = FALSE)
-  })
-  
-  # ==================== TAB 3: POSITIONING ====================
-  
-  output$positioning_heatmap <- renderPlot({
-    infield_positioning_heatmap(
-      team = input$pos_team,
-      batter_hand = input$pos_batter_hand,
-      pitcher_hand = input$pos_pitcher_hand,
-      man_on_first = input$pos_first,
-      man_on_second = input$pos_second,
-      man_on_third = input$pos_third
-    )
-  })
-  
-  output$positioning_summary <- render_gt({
-    team_data <- def_pos_data %>% filter(PitcherTeam == input$pos_team)
-    
-    team_data %>%
-      summarise(
-        `Avg 1B X` = round(mean(`1B_PositionAtReleaseX`, na.rm = TRUE), 1),
-        `Avg 1B Z` = round(mean(`1B_PositionAtReleaseZ`, na.rm = TRUE), 1),
-        `Avg SS X` = round(mean(`SS_PositionAtReleaseX`, na.rm = TRUE), 1),
-        `Avg SS Z` = round(mean(`SS_PositionAtReleaseZ`, na.rm = TRUE), 1),
-        `Avg CF X` = round(mean(`CF_PositionAtReleaseX`, na.rm = TRUE), 1),
-        `Avg CF Z` = round(mean(`CF_PositionAtReleaseZ`, na.rm = TRUE), 1),
-        Observations = n()
-      ) %>%
-      gt() %>%
-      tab_header(title = paste("Average Positioning -", input$pos_team)) %>%
-      cols_align(align = "center") %>%
-      tab_options(heading.background.color = "darkcyan") %>%
-      tab_style(style = cell_text(color = "white"), locations = cells_title())
-  })
-  
-  # ==================== TAB 4: CATCHING ====================
-  
-  catcher_filtered <- reactive({
-    catcher_data %>%
-      filter(Catcher == input$catcher_select) %>%
-      filter(TaggedPitchType %in% input$pitch_type_filter)
-  })
-  
-  output$catcher_net_strikes <- renderText({
-    df <- catcher_filtered()
-    net <- sum(df$frame_numeric, na.rm = TRUE)
-    sprintf("%+d", net)
   })
-  
-  output$catcher_frame_rate <- renderText({
-    df <- catcher_filtered() %>% filter(!is.na(frame_numeric))
-    if (nrow(df) == 0) return("N/A")
-    added <- sum(df$frame_numeric == 1, na.rm = TRUE)
-    total <- sum(df$frame_numeric != 0, na.rm = TRUE)
-    if (total == 0) return("N/A")
-    paste0(round(added / total * 100, 1), "%")
+
+  output$mainUI <- renderUI({
+    if (isTRUE(authed())) app_ui else login_ui
   })
-  
-  output$catcher_avg_pop <- renderText({
-    df <- catcher_filtered() %>% filter(!is.na(PopTime))
-    if (nrow(df) == 0) return("N/A")
-    paste0(round(mean(df$PopTime, na.rm = TRUE), 2), "s")
+
+  # ---- Placeholder GT outputs ----
+  output$of_field_graph_table <- gt::render_gt({
+    gt::gt(data.frame(Note = "Connect data to populate"))
   })
-  
-  output$catcher_framing_heatmap <- renderPlot({
-    df <- catcher_filtered() %>%
-      filter(!is.na(frame), !is.na(PlateLocSide), !is.na(PlateLocHeight)) %>%
-      filter(frame %in% c("Strike Added", "Strike Lost"))
-    
-    if (nrow(df) < 10) {
-      return(ggplot() + theme_void() + ggtitle("Insufficient data"))
-    }
-    
-    ggplot(df, aes(PlateLocSide, PlateLocHeight)) +
-      stat_density_2d(aes(fill = after_stat(density)), geom = "raster", contour = FALSE, alpha = 0.8) +
-      scale_fill_gradientn(colours = c("white", "lightblue", "#FF9999", "red", "darkred")) +
-      annotate("rect", xmin = -0.83, xmax = 0.83, ymin = 1.5, ymax = 3.38, 
-               fill = NA, color = "black", linewidth = 1.5) +
-      coord_fixed() + xlim(-2, 2) + ylim(0, 4.5) +
-      facet_wrap(~frame, nrow = 1) +
-      theme_void() +
-      theme(strip.text = element_text(size = 16, face = "bold"), legend.position = "none")
+
+  output$of_direction_oaa_table <- gt::render_gt({
+    gt::gt(data.frame(Note = "Connect data to populate"))
   })
-  
-  output$catcher_framing_points <- renderPlotly({
-    df <- catcher_filtered() %>%
-      filter(!is.na(frame), !is.na(PlateLocSide), !is.na(PlateLocHeight),
-             frame %in% c("Strike Added", "Strike Lost"))
-    
-    if (nrow(df) < 10) {
-      return(ggplotly(ggplot() + theme_void()))
-    }
-    
-    pitch_colors <- c("Fastball" = "#FA8072", "Sinker" = "#fdae61", "Slider" = "#A020F0",
-                      "Curveball" = "#2c7bb6", "ChangeUp" = "#90EE90", "Cutter" = "red")
-    
-    p <- ggplot(df, aes(PlateLocSide, PlateLocHeight, color = TaggedPitchType,
-                        text = paste0("Pitch: ", TaggedPitchType, "<br>Frame: ", frame))) +
-      geom_point(alpha = 0.7, size = 2) +
-      annotate("rect", xmin = -0.83, xmax = 0.83, ymin = 1.5, ymax = 3.38, 
-               fill = NA, color = "black", linewidth = 1) +
-      coord_fixed(xlim = c(-2, 2), ylim = c(0, 4.5)) +
-      facet_wrap(~frame, nrow = 1) +
-      scale_color_manual(values = pitch_colors, na.value = "grey60") +
-      theme_minimal() +
-      theme(strip.text = element_text(face = "bold"))
-    
-    ggplotly(p, tooltip = "text")
+
+  output$if_field_graph_table <- gt::render_gt({
+    gt::gt(data.frame(Note = "Connect data to populate"))
   })
-  
-  output$catcher_throw_map <- renderPlot({
-    df <- catcher_filtered() %>%
-      filter(!is.na(Notes), Notes %in% c("2b out", "2b safe", "3b out", "3b safe"))
-    
-    if (nrow(df) == 0) {
-      return(ggplot() + theme_void() + ggtitle("No throwing data available"))
-    }
-    
-    ggplot(df) +
-      geom_polygon(data = data.frame(x = c(-10,10,10,-10), y = c(0.25,0.25,8,8)),
-                   aes(x = x, y = y), fill = '#14a6a8', color = '#14a6a8') +
-      geom_polygon(data = data.frame(x = c(-10,10,10,-10), y = c(8,8,9,9)),
-                   aes(x = x, y = y), fill = 'yellow', color = 'yellow') +
-      geom_polygon(data = data.frame(x = c(-10,10,10,-10), y = c(-2,-2,0.25,0.25)),
-                   aes(x = x, y = y), fill = 'brown', color = 'brown') +
-      geom_polygon(data = data.frame(x = c(-10,10,10,-10), y = c(-5,-5,-2,-2)),
-                   aes(x = x, y = y), fill = 'darkgreen', color = 'darkgreen') +
-      geom_polygon(data = data.frame(x = c(-1,1,1,-1), y = c(0,0,0.45,0.45)),
-                   aes(x = x, y = y), fill = 'white', color = 'black') +
-      geom_point(aes(x = BasePositionZ, y = BasePositionY, fill = Notes),
-                 color = 'white', pch = 21, size = 4) +
-      scale_fill_manual(values = c('2b safe' = 'red', '2b out' = '#339a1d',
-                                   '3b safe' = '#ff6b6b', '3b out' = '#1a5d1a')) +
-      scale_x_continuous(limits = c(-10, 10)) + 
-      scale_y_continuous(limits = c(-5, 9)) +
-      coord_fixed() +
-      theme_void() +
-      theme(legend.position = "bottom") +
-      ggtitle(paste(input$catcher_select, "- Throwing Report"))
+
+  output$recv_summary_table <- gt::render_gt({
+    gt::gt(data.frame(Note = "Connect data to populate"))
   })
-  
-  output$catcher_pop_dist <- renderPlotly({
-    df <- catcher_filtered() %>% filter(!is.na(PopTime))
-    
-    if (nrow(df) == 0) return(ggplotly(ggplot() + theme_void()))
-    
-    p <- ggplot(df, aes(PopTime)) +
-      geom_histogram(bins = 15, fill = "darkcyan", alpha = 0.7, color = "white") +
-      geom_vline(xintercept = mean(df$PopTime), color = "peru", linetype = "dashed", size = 1) +
-      labs(x = "Pop Time (s)", y = "Count") +
-      theme_minimal()
-    
-    ggplotly(p)
+
+  output$throw_summary_table <- gt::render_gt({
+    gt::gt(data.frame(Note = "Connect data to populate"))
   })
-  
-  output$catcher_velo_trend <- renderPlotly({
-    df <- catcher_filtered() %>% 
-      filter(!is.na(ThrowSpeed)) %>%
-      arrange(Date) %>%
-      mutate(throw_num = row_number())
-    
-    if (nrow(df) == 0) return(ggplotly(ggplot() + theme_void()))
-    
-    p <- ggplot(df, aes(throw_num, ThrowSpeed)) +
-      geom_point(color = "darkcyan", size = 2) +
-      geom_smooth(method = "loess", color = "peru", se = TRUE, fill = "peru", alpha = 0.3) +
-      labs(x = "Throw #", y = "Velocity (MPH)") +
-      theme_minimal()
-    
-    ggplotly(p)
+
+  output$st_drs_table <- gt::render_gt({
+    gt::gt(data.frame(Note = "Connect data to populate"))
   })
-  
-  output$catcher_leaderboard <- DT::renderDataTable({
-    catcher_data %>%
-      group_by(Catcher) %>%
-      summarise(
-        `Pitches Caught` = n(),
-        `Strikes Added` = sum(frame_numeric == 1, na.rm = TRUE),
-        `Strikes Lost` = sum(frame_numeric == -1, na.rm = TRUE),
-        `Net Strikes` = sum(frame_numeric, na.rm = TRUE),
-        `Frame Rate` = round(sum(frame_numeric == 1, na.rm = TRUE) / 
-                               max(1, sum(!is.na(frame_numeric) & frame_numeric != 0)) * 100, 1),
-        `Avg Pop Time` = round(mean(PopTime, na.rm = TRUE), 2),
-        `Avg Throw Velo` = round(mean(ThrowSpeed, na.rm = TRUE), 1),
-        .groups = "drop"
-      ) %>%
-      arrange(desc(`Net Strikes`)) %>%
-      DT::datatable(options = list(pageLength = 10), rownames = FALSE)
+
+  output$br_summary_table <- gt::render_gt({
+    gt::gt(data.frame(Note = "Connect data to populate"))
   })
-  
 
-# ============================================================================
-# RUN APP
-# ============================================================================
+  output$oaa_lb_team_summary <- gt::render_gt({
+    gt::gt(data.frame(Note = "Connect data to populate"))
+  })
+}
 
-shinyApp(ui = ui, server = server)
+shinyApp(ui, server)