Update app.R

app.R

@@ -1,58 +1,568 @@
 library(shiny)
-library(bslib)
+library(DT)
+library(rsconnect)
+library(baseballr)
 library(dplyr)
+library(tidyverse)
+library(rvest)
 library(ggplot2)
+library(janitor)
+library(ggthemes)
+library(jsonlite)
+library(utils)
+library(data.table)
+library(xgboost)
+library(httr)
+library(bslib)
+library(rtabulator)
+
+download_private_csv <- function(repo_id, filename) {
+  url <- paste0("https://huggingface.co/datasets/", repo_id, "/resolve/main/", filename)
+  response <- GET(url, add_headers(Authorization = paste("Bearer", Sys.getenv("GETCSV"))))
+  
+  if (status_code(response) == 200) {
+    content <- content(response, "text")
+    con <- textConnection(content)
+    
+    # Try different read options
+    data <- read.csv(con, 
+                     header = TRUE,
+                     check.names = FALSE,  # This prevents R from modifying column names
+                     fileEncoding = "UTF-8",
+                     stringsAsFactors = FALSE)
+    close(con)
+    return(data)
+  } else {
+    stop("Failed to download dataset")
+  }
+}
+
+MLB <- download_private_csv("TimStats/StatcastDataAll", "MLB.csv")
+AAA <- download_private_csv("TimStats/StatcastDataAll", "AAA.csv")
+FSL <- download_private_csv("TimStats/StatcastDataAll", "FSL.csv")
+
+is_barrel <- function(df) {
+  df$hit_speedr <- round(df$hit_speed)
+  df <- df |>
+    mutate(barrel = ifelse((hit_speedr >= 124) &
+                             (hit_angle >= 0 & hit_angle <= 50),1,0)) |>
+    mutate(barrel = ifelse((hit_speedr == 123) &
+                             (hit_angle >= 1 & hit_angle <= 50),1,barrel)) |>
+    mutate(barrel = ifelse((hit_speedr == 122) &
+                             (hit_angle >= 2 & hit_angle <= 50),1,barrel)) |>
+    mutate(barrel = ifelse((hit_speedr == 121) &
+                             (hit_angle >= 3 & hit_angle <= 50),1,barrel)) |>
+    mutate(barrel = ifelse((hit_speedr == 120) &
+                             (hit_angle >= 4 & hit_angle <= 50),1,barrel)) |>
+    mutate(barrel = ifelse((hit_speedr == 119) &
+                             (hit_angle >= 5 & hit_angle <= 50),1,barrel)) |>
+    mutate(barrel = ifelse((hit_speedr == 118) &
+                             (hit_angle >= 6 & hit_angle <= 50),1,barrel)) |>
+    mutate(barrel = ifelse((hit_speedr == 117) &
+                             (hit_angle >= 7 & hit_angle <= 50),1,barrel)) |>
+    mutate(barrel = ifelse((hit_speedr == 116) &
+                             (hit_angle >= 8 & hit_angle <= 50),1,barrel)) |>
+    mutate(barrel = ifelse((hit_speedr == 115) &
+                             (hit_angle >= 9 & hit_angle <= 50),1,barrel)) |>
+    mutate(barrel = ifelse((hit_speedr == 114) &
+                             (hit_angle >= 10 & hit_angle <= 50),1,barrel)) |>
+    mutate(barrel = ifelse((hit_speedr == 113) &
+                             (hit_angle >= 11 & hit_angle <= 50),1,barrel)) |>
+    mutate(barrel = ifelse((hit_speedr == 112) &
+                             (hit_angle >= 12 & hit_angle <= 50),1,barrel)) |>
+    mutate(barrel = ifelse((hit_speedr == 111) &
+                             (hit_angle >= 13 & hit_angle <= 50),1,barrel)) |>
+    mutate(barrel = ifelse((hit_speedr == 110) &
+                             (hit_angle >= 14 & hit_angle <= 48),1,barrel)) |>
+    mutate(barrel = ifelse((hit_speedr == 109) &
+                             (hit_angle >= 15 & hit_angle <= 46),1,barrel)) |>
+    mutate(barrel = ifelse((hit_speedr == 108) &
+                             (hit_angle >= 16 & hit_angle <= 45),1,barrel)) |>
+    mutate(barrel = ifelse((hit_speedr == 107) &
+                             (hit_angle >= 17 & hit_angle <= 43),1,barrel)) |>
+    mutate(barrel = ifelse((hit_speedr == 106) &
+                             (hit_angle >= 18 & hit_angle <= 42),1,barrel)) |>
+    mutate(barrel = ifelse((hit_speedr == 105) &
+                             (hit_angle >= 19 & hit_angle <= 40),1,barrel)) |>
+    mutate(barrel = ifelse((hit_speedr == 104) &
+                             (hit_angle >= 20 & hit_angle <= 39),1,barrel)) |>
+    mutate(barrel = ifelse((hit_speedr == 103) &
+                             (hit_angle >= 21 & hit_angle <= 37),1,barrel)) |>
+    mutate(barrel = ifelse((hit_speedr == 102) &
+                             (hit_angle >= 22 & hit_angle <= 36),1,barrel)) |>
+    mutate(barrel = ifelse((hit_speedr == 101) &
+                             (hit_angle >= 23 & hit_angle <= 34),1,barrel)) |>
+    mutate(barrel = ifelse((hit_speedr == 100) &
+                             (hit_angle >= 24 & hit_angle <= 33),1,barrel)) |>
+    mutate(barrel = ifelse((hit_speedr == 99) &
+                             (hit_angle >= 25 & hit_angle <= 31),1,barrel)) |>
+    mutate(barrel = ifelse((hit_speedr == 98) &
+                             (hit_angle >= 26 & hit_angle <= 30),1,barrel)) |>
+    select(-hit_speedr)
+  return(df)
+}
+
+VAA <- function(milbtotal){
+  milbtotal <- milbtotal |>
+    mutate(vaa = -atan((vz0+(az*(-sqrt((vy0*vy0)-(2*ay*(y0-(17/12))))-vy0)/
+                               ay))/(-sqrt((vy0*vy0)-(2*ay*(y0-(17/12))))))*(180/pi))
+} 
+
+calculate_EAA <- function(extension) {
+  extension / 6.3
+}
+
+calculate_SADiff <- function(pfxX, pfxZ, spinDirection) {
+  inSA <- atan2(pfxZ, pfxX) * 180/pi + 90
+  inSA <- ifelse(inSA < 0, inSA + 360, inSA)
+  SADiff <- spinDirection - inSA
+  SADiff <- ifelse(SADiff > 180, SADiff - 360, SADiff)
+  SADiff <- ifelse(SADiff < -180, SADiff + 360, SADiff)
+  return(SADiff)
+}
+
+calculate_VAA <- function(vz0, ay, az, vy0, y0) {
+  -atan((vz0+(az*(-sqrt((vy0*vy0)-(2*ay*(y0-(17/12))))-vy0)/
+                ay))/(-sqrt((vy0*vy0)-(2*ay*(y0-(17/12))))))*(180/pi)
+}
+
+calculate_timstuff <- function(game) {
+  # game <- calculate_primary(game)
+  game <- game %>%
+    mutate(
+      #VAA = calculate_VAA(vz0, ay, az, vy0, y0),
+           EAA = calculate_EAA(extension),
+           SADiff = calculate_SADiff(pfxX, pfxZ, spinDirection),
+           #team_fielding_id = ifelse(description %in% c("Called Strike", "Swinging Strike", "Swinging Strike (Blocked)"), 1, 0),
+          # swing = ifelse(description %in% c("Foul", "Foul Pitchout", "In play, no out", "In play, out(s)", "In play, run(s)", "Swinging Strike", "Swinging Strike (Blocked)", "Foul Tip"), 1, 0),
+           #is_strike_swinging = ifelse(is_strike_swinging, 1, 0),
+           #Pitch = pitch_name,
+           ishandL = ifelse(phand == "L",1,0))
+  # game <- calculate_primary(game)
+  
+  feature_vars <- c("ishandL","start_speed", "IVB", "HB", "EAA", "x0", "z0", "spin_rate","SADiff")
+  complete_rows <- complete.cases(game[, feature_vars])
+  game_complete <- game[complete_rows, ]
+  game_na <- game[!complete_rows,]
+  game_na$TimStuff <- NA
+  
+  rhp <- game_complete
+  
+  # rhp <- game_complete[game_complete$ishandL == 0]
+  # 
+  # lhp$TimStuff <- scale_TimStuff(predict(model, as.matrix(cbind(lhp$ishandL,lhp$start_speed, lhp$IVB, lhp$HB, lhp$EAA, lhp$x0, lhp$z0, lhp$spin_rate, lhp$SADiff,lhp$primary_speed,lhp$primary_IVB,lhp$primary_HB))), -0.00249975,  0.007566558)
+  
+  rhp$TimStuff <- scale_TimStuff(predict(model, as.matrix(cbind(rhp$ishandL,rhp$start_speed, rhp$IVB, rhp$HB, rhp$EAA, rhp$x0, rhp$z0, rhp$spin_rate, rhp$SADiff))),   -0.002620635,   0.006021368)
+  
+  game_complete <- rbind(rhp,game_na)
+  return(game_complete)
+}
+
+scale_TimStuff <- function(raw_score, model_mean, model_sd) {
+  scaled_score <- (raw_score - model_mean) / model_sd
+  result <- 100 - (scaled_score * 10)
+  return(result)
+}
+
+model <- xgb.load('TimStuff2.model')
+#######
 
-df <- readr::read_csv("penguins.csv")
-# Find subset of columns that are suitable for scatter plot
-df_num <- df |> select(where(is.numeric), -Year)
+Swing <- function(milbtotal){
+  milbtotal <- milbtotal %>%
+    mutate(swing = ifelse(description == "Foul" |
+                            description == "Foul Pitchout" |
+                            description == "In play, no out" |
+                            description == "In play, out(s)" | 
+                            description == "In play, run(s)" | 
+                            description == "Swinging Strike" | 
+                            description == "swinging Strike (Blocked)" |
+                            description == "Foul Tip",1,0))
+}
+
+addChecks <- function(df){
+  df <- is_barrel(df)
+  df %>% mutate(
+    InPlayCheck = case_when(description %in% c('In play, run(s)','In play, out(s)','In play, no out') ~ TRUE, TRUE ~ FALSE),
+    SwingCheck = case_when(description %in% c('Foul','Foul Bunt','Foul Pitchout','Foul Tip',
+                                         'In play, run(s)','In play, out(s)','In play, no out',
+                                         'Swinging Strike','Swinging Strike (Blocked)',
+                                         'Missed Bunt') ~ TRUE, TRUE ~ FALSE),
+    ConCheck = case_when(description %in% c('In play, run(s)','In play, out(s)','In play, no out',
+                                           'Foul','Foul Bunt','Foul Pitchout') ~ TRUE, TRUE ~ FALSE),
+    WhiffCheck = case_when(description %in% c('Swinging Strike','Swinging Strike (Blocked)',
+                                         'Missed Bunt','Foul Tip') ~ TRUE, TRUE ~ FALSE),
+    CalledStrikeCheck = case_when(description %in% c('Called Strike') ~ TRUE, TRUE ~ FALSE),
+    CSWCheck = case_when(description %in% c('Swinging Strike','Swinging Strike (Blocked)',
+                                            'Missed Bunt','Foul Tip','Called Strike') ~ TRUE, TRUE ~ FALSE),
+    StrikeCheck = case_when(description %in% c('Called Strike','Foul','Foul Bunt','Foul Pitchout',
+                                               'Foul Tip','In play, no out','In play, out(s)',
+                                               'In play, run(s)','Missed Bunt','Pitchout',
+                                               'Swinging Stike','Swinging Strike (Blocked)') ~ TRUE, TRUE ~ FALSE),
+    BallCheck = case_when(description %in% c('Ball','Ball In Dirt','Hit By Pitch') ~ TRUE, TRUE ~ FALSE),
+    SweetSpotCheck = case_when(between(hit_angle,10,30) ~ TRUE, TRUE ~ FALSE),
+    HardHitCheck = case_when(hit_speed >= 95 ~ TRUE, TRUE ~ FALSE),
+    ZoneCheck = ifelse(zone <= 9, TRUE, FALSE),
+    Single = case_when(result == "Single" & InPlayCheck == TRUE ~ TRUE, TRUE ~ FALSE),
+    Double = case_when(result == "Double" & InPlayCheck == TRUE ~ TRUE, TRUE ~ FALSE),
+    Triple = case_when(result == "Triple" & InPlayCheck == TRUE ~ TRUE, TRUE ~ FALSE),
+    `Home Run` = case_when(result == "Home Run" & InPlayCheck == TRUE ~ TRUE, TRUE ~ FALSE),
+    WalkCheck = case_when(balls >= 4 & result == "Walk" ~ TRUE, TRUE ~ FALSE),
+    HBPCheck = case_when(description == "Hit By Pitch" & result == "Hit By Pitch" ~ TRUE, TRUE ~ FALSE),
+    StrikeoutCheck = case_when(strikes >= 3 & result %in% c("Strikeout",'Stikeout Double Play') ~ TRUE, TRUE ~ FALSE),
+    SacrificeCheck = case_when(InPlayCheck == TRUE & result %in% c('Sac Fly','Sac Bunt',
+                                                'Sac Fly Double Play','Sac Bunt Double Play') ~ TRUE, TRUE ~ FALSE),
+    IBBCheck = case_when(pitchNum == 1 & result == "Intent Walk" ~ TRUE, TRUE ~ FALSE),
+    ABCheck = StrikeoutCheck + InPlayCheck - SacrificeCheck,
+    PACheck = ABCheck + WalkCheck + HBPCheck,
+    TopZoneCheck = if_else(zone < 4,TRUE,FALSE),
+    BotZoneCheck = if_else(zone > 6 & zone < 10,TRUE,FALSE),
+    CompSwingCheck = if_else(bat_speed >= 60 & hit_speed >= 90,TRUE,FALSE),
+    CompSwingCheck = ifelse(bat_speed >= quantile(bat_speed,.1,na.rm = TRUE),1,0)
+  ) 
+}
+#' test <- addChecks(MLB) %>%   group_by(`Pitcher Name`,season,pitch_name) %>%
+#' summarise(
+#'   Pitches = n(),
+#'   'Avg Velo' = mean(start_speed,na.rm = TRUE),
+#'   'Top Velo' = max(start_speed,na.rm = TRUE),
+#'   #'TimStuff+' = mean(TimStuff,na.rm = TRUE),
+#'   'Max EV' = max(hit_speed,na.rm = TRUE),
+#'   'Avg EV' = mean(hit_speed,na.rm = TRUE),
+#'   'EV90' = quantile(hit_speed,0.9,na.rm = TRUE),
+#'   'Avg LA' = mean(hit_angle,na.rm = TRUE),
+#'   'stdevLA' = sd(hit_angle,na.rm = TRUE),
+#'   'HardHit%' = mean(HardHitCheck[InPlayCheck == TRUE],na.rm = TRUE),
+#'   'Barrel%' = mean(barrel[InPlayCheck == TRUE],na.rm = TRUE),
+#'   'Sweet Spot%' = mean(SweetSpotCheck[InPlayCheck == TRUE],na.rm = TRUE),
+#'   'xwOBA' = mean(expected_woba,na.rm = TRUE),
+#'   'xwOBACON' = mean(expected_woba[InPlayCheck == TRUE],na.rm = TRUE),
+#'   'Contact%' = mean(ConCheck[SwingCheck == TRUE],na.rm = TRUE),
+#'   'ZCon%' = mean(ConCheck[ZoneCheck == TRUE] & SwingCheck == TRUE,na.rm = TRUE),
+#'   'ZSwing%' = mean(SwingCheck[ZoneCheck == TRUE],na.rm = TRUE),
+#'   'OCon%' = mean(ConCheck[ZoneCheck == FALSE] & SwingCheck == TRUE,na.rm = TRUE),
+#'   'Chase%' = mean(SwingCheck[ZoneCheck == FALSE],na.rm = TRUE),
+#'   'SwStr%' = mean(WhiffCheck,na.rm = TRUE),
+#'   'Whiff%' = mean(WhiffCheck[SwingCheck == TRUE],na.rm = TRUE),
+#'   'Zone%' = mean(ZoneCheck,na.rm = TRUE),
+#'   'Strike%' = mean(StrikeCheck,na.rm = TRUE),
+#'   'Swing%' = mean(SwingCheck,na.rm = TRUE),
+#'   'Spin Rate' = mean(spin_rate,na.rm = TRUE),
+#'   'Extension' = mean(extension,na.rm = TRUE),
+#'   'IVB' = mean(IVB,na.rm = TRUE),
+#'   'HB' = mean(HB,na.rm = TRUE),
+#'   # 'VAA' = mean(vaa,na.rm = TRUE),
+#'   # 't3VAA' = mean(vaa[TopZoneCheck == TRUE],na.rm = TRUE),
+#'   # 'b3VAA' = mean(vaa[BotZoneCheck == TRUE],na.rm = TRUE),
+#'   'CSW%' = mean(CSWCheck,na.rm = TRUE),
+#'   'Arm Angle' = mean(arm_angle,na.rm = TRUE),
+#'   'Bat Speed' = mean(bat_speed[CompSwingCheck ==  TRUE],na.rm = TRUE)
+#' )
+MLB_processed <- MLB %>% 
+  calculate_timstuff() %>%
+  addChecks() %>%
+  VAA() %>%
+  mutate('Pitch Name' = pitch_name) %>%
+  mutate('Season' = season) %>%
+  mutate('Level' = level) %>%
+  mutate('Pitch Type' = case_when(
+    pitch_name %in% c("Four-Seam Fastball", "Sinker", "Cutter", "Fastball") ~ "Fastball",
+    pitch_name %in% c("Slider", "Sweeper", "Slurve", "Curveball", "Screwball",
+                      "Knuckle Curve", "Slow Curve", "Eephus") ~ "Breaking",
+    pitch_name %in% c("Changeup", "Splitter", "Forkball") ~ "Offspeed",
+    TRUE ~ NA_character_  # Corrected default case
+  )) %>%
+  mutate('Batter Side' = bside) %>%
+  mutate('Pitcher Hand' = phand) %>%
+  mutate('Stadium' = venue_name) %>%
+  mutate('Batter Home/Away' = ifelse(`Batter Team` == teams_home_team_name,"Home","Away")) %>%
+  mutate('Pitcher Home/Away' = ifelse(`Pitcher Team` == teams_home_team_name,"Home","Away"))
+
+AAA_processed <- AAA %>%
+  calculate_timstuff() %>%
+  addChecks()%>%
+  VAA()%>%
+  mutate('Pitch Name' = pitch_name) %>%
+  mutate('Season' = season) %>%
+  mutate('Level' = level) %>%
+  mutate('Pitch Type' = case_when(
+    pitch_name %in% c("Four-Seam Fastball", "Sinker", "Cutter", "Fastball") ~ "Fastball",
+    pitch_name %in% c("Slider", "Sweeper", "Slurve", "Curveball", "Screwball",
+                      "Knuckle Curve", "Slow Curve", "Eephus") ~ "Breaking",
+    pitch_name %in% c("Changeup", "Splitter", "Forkball") ~ "Offspeed",
+    TRUE ~ NA_character_  # Corrected default case
+  ))
+
+FSL_processed <- FSL %>%
+  calculate_timstuff() %>%
+  addChecks()%>%
+  VAA()%>%
+  mutate('Pitch Name' = pitch_name) %>%
+  mutate('Season' = season) %>%
+  mutate('Level' = level) %>%
+  mutate('Pitch Type' = case_when(
+    pitch_name %in% c("Four-Seam Fastball", "Sinker", "Cutter", "Fastball") ~ "Fastball",
+    pitch_name %in% c("Slider", "Sweeper", "Slurve", "Curveball", "Screwball",
+                      "Knuckle Curve", "Slow Curve", "Eephus") ~ "Breaking",
+    pitch_name %in% c("Changeup", "Splitter", "Forkball") ~ "Offspeed",
+    TRUE ~ NA_character_  # Corrected default case
+  ))
 
+# Available stats for the UI
+available_stats <- c("Pitches", "Avg Velo", "Top Velo", "TimStuff", "Max EV", "Avg EV", 
+                     "EV90", "Avg LA", "stdevLA", "HardHit%", "Barrel%", "Sweet Spot%",
+                     "xwOBA", "xwOBACON", "Contact%", "ZCon%", "ZSwing%", "OCon%", 
+                     "Chase%", "SwStr%", "Whiff%", "Zone%", "Strike%", "Swing%",
+                     "Spin Rate", "Extension", "IVB", "HB", "CSW%", "Arm Angle", "Bat Speed")
+
+# Then your UI and server code
 ui <- page_sidebar(
-  theme = bs_theme(bootswatch = "minty"),
-  title = "Penguins explorer",
+  title = "MLB/AAA/FSL Statcast Data",
+  theme = bs_theme(preset = "united"),
   sidebar = sidebar(
-    varSelectInput("xvar", "X variable", df_num, selected = "Bill Length (mm)"),
-    varSelectInput("yvar", "Y variable", df_num, selected = "Bill Depth (mm)"),
-    checkboxGroupInput("species", "Filter by species",
-      choices = unique(df$Species), selected = unique(df$Species)
+    width = 300,
+    p("X: ", a("(@TimStats)", href = "https://twitter.com/timstats")),
+    p("Data Updated To:", Sys.Date() - 1),
+    
+    card(
+      class = "mb-3",
+      selectInput("level", "Level:",
+                  c("MLB", "AAA", "FSL"),
+                  multiple = TRUE
+      ),
+      selectInput("group", "Group By:", 
+                  c("Pitcher Name", "Pitcher ID", "Pitch Name","Batter Name",
+                    "Batter ID","Season","Level","Pitch Type","Stadium",
+                    "Batter Home/Away","Pitcher Home/Away","Pitcher Team",
+                    "Batter Team"),
+                  multiple = TRUE
+      ),
+      selectInput("stats", "Select Stats:",
+                  choices = available_stats,
+                  multiple = TRUE
+      ),
+      dateRangeInput("dates", "Date Range:",
+                     start = "2024-02-23",
+                     end = "2024-09-30"
+      )
     ),
-    hr(), # Add a horizontal rule
-    checkboxInput("by_species", "Show species", TRUE),
-    checkboxInput("show_margins", "Show marginal plots", TRUE),
-    checkboxInput("smooth", "Add smoother"),
+    actionButton("add_filter", "Add Filter", class = "btn-primary mb-3"),
+    uiOutput("filter_container"),
+    hr(),
+    actionButton("update_table", "Update Table", class = "btn-success")
   ),
-  plotOutput("scatter")
+  mainPanel(
+    tabulatorOutput("table", height = "800px", width = "1600px")
+  )
 )
 
 server <- function(input, output, session) {
-  subsetted <- reactive({
-    req(input$species)
-    df |> filter(Species %in% input$species)
+  filters <- reactiveVal(list())
+  counter <- reactiveVal(0)
+  table_trigger <- reactiveVal(0)
+  last_click <- reactiveVal(0)
+  
+  available_columns <- reactive({
+    stat_cols <- setNames(
+      input$stats,
+      input$stats
+    )
+    c(stat_cols)
   })
-
-  output$scatter <- renderPlot(
-    {
-      p <- ggplot(subsetted(), aes(!!input$xvar, !!input$yvar)) +
-        theme_light() +
+  
+  removeClicks <- reactiveVal(0)
+  
+  # observeEvent(input$update_table, {
+  #   table_trigger(table_trigger() + 1)
+  # })
+  
+  processed_data <- eventReactive(input$update_table, {
+    req(input$level, input$stats, input$group)
+    
+    # Combine preprocessed data from selected levels
+    combined_data <- bind_rows(
+      if ("MLB" %in% input$level) MLB_processed,
+      if ("AAA" %in% input$level) AAA_processed,
+      if ("FSL" %in% input$level) FSL_processed
+    )
+    
+    # First group and calculate all stats
+    grouped_data <- combined_data %>%
+      group_by(across(all_of(input$group))) %>%
+      summarise(
+        Pitches = n(),
+        'Avg Velo' = mean(start_speed, na.rm = TRUE),
+        'Top Velo' = max(start_speed, na.rm = TRUE),
+        'TimStuff' = mean(TimStuff, na.rm = TRUE),
+        'Max EV' = max(hit_speed, na.rm = TRUE),
+        'Avg EV' = mean(hit_speed, na.rm = TRUE),
+        'EV90' = quantile(hit_speed, 0.9, na.rm = TRUE),
+        'Avg LA' = mean(hit_angle, na.rm = TRUE),
+        'stdevLA' = sd(hit_angle, na.rm = TRUE),
+        'HardHit%' = mean(HardHitCheck[InPlayCheck == TRUE], na.rm = TRUE) * 100,
+        'Barrel%' = mean(barrel[InPlayCheck == TRUE], na.rm = TRUE) * 100,
+        'Sweet Spot%' = mean(SweetSpotCheck[InPlayCheck == TRUE], na.rm = TRUE) * 100,
+        'xwOBA' = mean(expected_woba, na.rm = TRUE),
+        'xwOBACON' = mean(expected_woba[InPlayCheck == TRUE], na.rm = TRUE),
+        'Contact%' = mean(ConCheck[SwingCheck == TRUE], na.rm = TRUE) * 100,
+        'ZCon%' = mean(ConCheck[ZoneCheck == TRUE & SwingCheck == TRUE], na.rm = TRUE) * 100,
+        'ZSwing%' = mean(SwingCheck[ZoneCheck == TRUE], na.rm = TRUE) * 100,
+        'OCon%' = mean(ConCheck[ZoneCheck == FALSE & SwingCheck == TRUE], na.rm = TRUE) * 100,
+        'Chase%' = mean(SwingCheck[ZoneCheck == FALSE], na.rm = TRUE) * 100,
+        'SwStr%' = mean(WhiffCheck, na.rm = TRUE) * 100,
+        'Whiff%' = mean(WhiffCheck[SwingCheck == TRUE], na.rm = TRUE) * 100,
+        'Zone%' = mean(ZoneCheck, na.rm = TRUE) * 100,
+        'Strike%' = mean(StrikeCheck, na.rm = TRUE) * 100,
+        'Swing%' = mean(SwingCheck, na.rm = TRUE) * 100,
+        'Spin Rate' = mean(spin_rate, na.rm = TRUE),
+        'Extension' = mean(extension, na.rm = TRUE),
+        'IVB' = mean(IVB, na.rm = TRUE),
+        'HB' = mean(HB, na.rm = TRUE),
+        'VAA' = mean(vaa, na.rm = TRUE),
+        't3VAA' = mean(vaa[TopZoneCheck == TRUE], na.rm = TRUE),
+        'b3VAA' = mean(vaa[BotZoneCheck == TRUE], na.rm = TRUE),
+        'CSW%' = mean(CSWCheck, na.rm = TRUE) * 100,
+        'Arm Angle' = mean(arm_angle, na.rm = TRUE),
+        'Bat Speed' = mean(bat_speed[CompSwingCheck == TRUE], na.rm = TRUE),
+        .groups = 'drop'
+      ) %>%
+      mutate(
+        across(c('xwOBA', 'xwOBACON'), ~round(., 3)),  # wOBA metrics to 3 decimals
+        across(where(is.numeric) & !c('xwOBA', 'xwOBACON'), ~round(., 1))  # everything else to 1 decimal
+      )
+    
+    # Then apply filters to the summarized data
+    filtered_data <- grouped_data
+    current_filters <- filters()
+    
+    for (filter in current_filters) {
+      column <- input[[filter$column_id]]
+      operator <- input[[filter$operator_id]]
+      value <- input[[filter$value_id]]
+      
+      if (!is.null(column) && !is.null(operator) && !is.null(value) && value != "") {
+        filtered_data <- switch(operator,
+                                "eq" = filtered_data %>% filter(!!sym(column) == value),
+                                "like" = filtered_data %>% filter(grepl(value, !!sym(column), ignore.case = TRUE)),
+                                "gt" = filtered_data %>% filter(!!sym(column) > as.numeric(value)),
+                                "lt" = filtered_data %>% filter(!!sym(column) < as.numeric(value)),
+                                "gte" = filtered_data %>% filter(!!sym(column) >= as.numeric(value)),
+                                "lte" = filtered_data %>% filter(!!sym(column) <= as.numeric(value)),
+                                filtered_data
+        )
+      }
+    }
+    
+    # Finally select only the requested columns
+    filtered_data %>%
+      select(all_of(c(input$group, input$stats)))
+  })
+  
+  # Tabulator rendering with formatting
+  output$table <- renderTabulator({
+    req(processed_data())
+    column_defs <- c(
+      # Group columns
+      map(input$group, function(col) {
+        list(field = col, title = col, width = 175)  # reduced from 250
+      }),
+      # Stat columns
+      map(input$stats, function(col) {
         list(
-          theme(legend.position = "bottom"),
-          if (input$by_species) aes(color = Species),
-          geom_point(),
-          if (input$smooth) geom_smooth()
+          field = col, 
+          title = col, 
+          width = 110,  # reduced from 150
+          formatter = if(col %in% c("xwOBA", "xwOBACON")) "number" else "number",
+          formatterParams = if(col %in% c("xwOBA", "xwOBACON")) {
+            list(precision = 3)
+          } else {
+            list(precision = 1)
+          }
         )
-
-      if (input$show_margins) {
-        margin_type <- if (input$by_species) "density" else "histogram"
-        p <- p |> ggExtra::ggMarginal(
-          type = margin_type, margins = "both",
-          size = 8, groupColour = input$by_species, groupFill = input$by_species
+      })
+    )
+    tabulator(processed_data(),
+              options = list(
+                selectable = TRUE,
+                layout = "fitColumns",
+                columns = column_defs
+              )
+    )
+  })
+  # Add observers for filter management and other reactive elements
+  observeEvent(input$add_filter, {
+    isolate({
+      current_counter <- counter()
+      filter_id <- paste0("filter_", current_counter)
+      
+      new_filter <- list(
+        id = filter_id,
+        column_id = paste0("column_", filter_id),
+        operator_id = paste0("operator_", filter_id),
+        value_id = paste0("value_", filter_id)
+      )
+      
+      current_filters <- filters()
+      filters(c(current_filters, list(new_filter)))
+      counter(current_counter + 1)
+    })
+  })
+  
+  observe({
+    current_filters <- filters()
+    
+    lapply(current_filters, function(filter) {
+      observeEvent(input[[paste0("remove_", filter$id)]], {
+        isolate({
+          removeClicks(removeClicks() + 1)
+          new_filters <- current_filters[sapply(current_filters, function(f) f$id != filter$id)]
+          filters(new_filters)
+        })
+      }, ignoreInit = TRUE, ignoreNULL = TRUE)
+    })
+  })
+  
+  # Filter container UI
+  output$filter_container <- renderUI({
+    removeClicks()
+    current_filters <- filters()
+    
+    lapply(current_filters, function(filter) {
+      div(
+        class = "mb-1",
+        div(
+          style = "display: flex; gap: 10px; align-items: center;",
+          selectInput(filter$column_id, "Column",
+                      choices = available_columns(),
+                      width = "200px",
+                      selected = input[[filter$column_id]]
+          ),
+          selectInput(filter$operator_id, "Stat",
+                      choices = c(
+                        "=" = "eq",
+                        "contains" = "like",
+                        ">" = "gt",
+                        "<" = "lt",
+                        ">=" = "gte",
+                        "<=" = "lte"
+                      ),
+                      width = "100px",
+                      selected = input[[filter$operator_id]]
+          ),
+          textInput(filter$value_id, "Value", 
+                    value = input[[filter$value_id]],
+                    width = "150px"
+          ),
+          actionButton(
+            paste0("remove_", filter$id),
+            icon("trash"),
+            class = "btn-danger btn-sm",
+            style = "margin-top: 22px;"
+          )
         )
-      }
-
-      p
-    },
-    res = 100
-  )
+      )
+    })
+  })
 }
 
-shinyApp(ui, server)
+# Run the application 
+shinyApp(ui = ui, server = server)