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TimMedia

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Update app.R
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library(shiny)
library(gt)
library(dplyr)
library(shinyjs)
library(shinyauthr)
library(httr)
library(bslib)

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")
  }
}

Beam <- download_private_csv("TimStats/CollegePriv", "College24.csv")
TMP <- download_private_csv("TimStats/CollegePriv", "TMP.csv")
TMB <- download_private_csv("TimStats/CollegePriv", "TMB.csv")

test <- Beam %>%
  select(Date,PitchofPA,Pitcher,PitcherId,PitcherThrows,PitcherTeam,Batter,BatterId,
         BatterSide,BatterTeam,Inning,`Top/Bottom`,Outs,Balls,Strikes,TaggedPitchType,
         AutoPitchType,PitchCall,TaggedHitType,KorBB,PlayResult,OutsOnPlay,RunsScored,
         RelSpeed,VertRelAngle,HorzRelAngle,SpinRate,SpinAxis,Tilt,RelHeight,RelSide,
         Extension,InducedVertBreak,HorzBreak,PlateLocHeight,PlateLocSide,VertApprAngle,
         HorzApprAngle,ExitSpeed,Angle,Direction,Distance,pfxx,pfxz,x0,z0,vx0,vy0,vz0,
         ax0,ay0,az0,Level,League,ContactPositionX,ContactPositionY,ContactPositionZ,
         SpinAxis3dTransverseAngle,SpinAxis3dLongitudinalAngle,SpinAxis3dTilt,
         SpinAxis3dSpinEfficiency,SpinAxis3dSeamOrientationRotationX,
         SpinAxis3dSeamOrientationRotationY,SpinAxis3dSeamOrientationRotationZ)
test <- test %>%
  mutate("Hit" = case_when(PlayResult %in% c("Single","Double","Triple","HomeRun") ~ TRUE,TRUE ~ FALSE),
         "CallStrike" = case_when(PitchCall %in% c("StrikeCalled") ~ TRUE, TRUE ~ FALSE),
         "Whiff" = case_when(PitchCall %in% c("StrikeSwinging") ~ TRUE, TRUE ~ FALSE),
         "CSW" = CallStrike + Whiff,
         "Contact" = case_when(PitchCall %in% c("FoulBall","FoulBallNotFieldable","InPlay") ~ TRUE, TRUE ~ FALSE),
         "GB" = case_when(TaggedHitType %in% c('GroundBall') ~ TRUE, TRUE ~ FALSE),
         "LD" = case_when(TaggedHitType %in% c('LineDrive') ~ TRUE, TRUE ~ FALSE),
         "FB" = case_when(TaggedHitType %in% c ("FlyBall") ~ TRUE, TRUE ~ FALSE),
         "PopU" = case_when(TaggedHitType %in% c ("Popup") ~ TRUE, TRUE ~ FALSE),
         "Swing" = Whiff + Contact,
         "BBE" = GB + LD + FB + PopU,
         "HardHit" = ifelse(ExitSpeed >= 95,TRUE,FALSE),
         "Ball" = case_when(PitchCall %in% c("BallCalled","BallinDirt") ~ TRUE, TRUE ~ FALSE),
         "Single" = case_when(PlayResult %in% c("Single") ~ TRUE, TRUE ~ FALSE),
         "Double" = case_when(PlayResult %in% c("Double") ~ TRUE, TRUE ~ FALSE),
         "Triple" = case_when(PlayResult %in% c("Triple") ~ TRUE, TRUE ~ FALSE),
         "HR" = case_when(PlayResult %in% c("HomeRun") ~ TRUE, TRUE ~ FALSE),
         "Sac" = case_when(PlayResult %in% c("Sacrifice") ~ TRUE, TRUE ~ FALSE),
         "HBP" = case_when(PitchCall %in% c("HitByPitch") ~ TRUE, TRUE ~ FALSE),
         "Error" = case_when(PlayResult %in% c("Error") ~ TRUE, TRUE ~ FALSE),
         "FC"= case_when(PlayResult %in% c("FieldersChoice") ~ TRUE, TRUE ~ FALSE),
         "Out" = case_when(PlayResult %in% c ("Out") ~ TRUE, TRUE ~ FALSE),
         "BIP" = Single + Double + Triple + HR + Sac + Error + Out + FC,
         "Count" = paste0(Balls,"-",Strikes),
         "BSituation" = ifelse(Balls > Strikes,"Ahead",NA),
         "BSituation" = ifelse(Balls < Strikes,"Behind",BSituation),
         "BSituation" = ifelse(Balls == Strikes,"Even",BSituation),
         "PSituation" = ifelse(Balls < Strikes,"Ahead",NA),
         "PSituation" = ifelse(Balls > Strikes,"Behind",PSituation),
         "PSituation" = ifelse(Balls == Strikes,"Even",PSituation),
         "Strikeout" = ifelse(KorBB == "Strikeout",TRUE,FALSE),
         "Walk" = ifelse(KorBB == "Walk",TRUE,FALSE),
         "Zone" = case_when(between(PlateLocSide,-.825,.825) & between(PlateLocHeight,1.45,3.45) ~ TRUE, TRUE ~ FALSE),
         "AB" = Strikeout + BIP - Sac,
         "PA" = Strikeout + BIP + Walk + HBP
  )
test <- test %>%
  left_join(TMB, by = c(BatterTeam = "team_abbr")) %>%
  left_join(TMP, by = c(PitcherTeam = "team_abbr")) %>%
  mutate(PitcherAndTeam = paste0(Pitcher," - ",PTeamName)) %>%
  mutate(BatterAndTeam = paste0(Batter," - ",BTeamName))


gt_theme_tim <- function(gt_object,...) {
  
  stopifnot(`'gt_object' must be a 'gt_tbl', have you accidentally passed raw data?` = "gt_tbl" %in% 
              class(gt_object))
  
  table_id <- subset(gt_object[['_options']], parameter == 'table_id')$value[[1]]
  
  if (is.na(table_id)) {
    table_id <- gt::random_id()
    opt_position <- which("table_id" %in% gt_object[["_options"]][["parameter"]])[[1]]
    gt_object[["_options"]][["value"]][[opt_position]] <- table_id
  }
  
  gt_object %>%
    # cell body
    gt::tab_style(
      locations = gt::cells_body(),
      style = gt::cell_text(font = "Arial", size = px(14))
    ) %>%
    # col. headers
    gt::tab_style(
      locations = gt::cells_column_labels(),
      style = gt::cell_text(weight = 'bold', font = "Arial", size = px(14))
    ) %>%
    # group rows
    gt::tab_style(
      locations = gt::cells_row_groups(),
      style = list(
        gt::cell_text(font = "Arial", weight = 650, size = px(14), color = "#FFFDF5"),
        gt::cell_fill(color = "#000000")
      )
    ) %>%
    # footnote
    gt::tab_style(
      locations = gt::cells_footnotes(),
      style = gt::cell_text(font = "Arial", size = px(12))
    ) %>%
    # title
    gt::tab_style(
      locations = gt::cells_title('title'),
      style = gt::cell_text(weight = 'bold', font = "Arial", size = px(18))
    ) %>%
    # subtitle
    gt::tab_style(
      locations = gt::cells_title('subtitle'),
      style = gt::cell_text(font = "Arial", size = px(14))
    ) %>%
    # caption
    gt::tab_style(
      locations = gt::cells_source_notes(),
      style = gt::cell_text(font = "Arial", size = px(12))
    ) %>%
    # spanner
    gt::tab_style(
      locations = gt::cells_column_spanners(),
      style = gt::cell_text(font = "Arial", weight = 650, size = px(8))
    ) %>%
    gt::tab_options(
      data_row.padding = 1,
      table_body.hlines.color = "transparent",
      column_labels.border.top.color = 'black',
      column_labels.border.top.width = px(1),
      column_labels.border.bottom.style = 'none',
      #column_labels.background.color = "orange",
      row_group.border.top.style = "none",
      row_group.border.top.color = "black",
      row_group.border.bottom.width = px(1),
      row_group.border.bottom.color = "black",
      row_group.border.bottom.style = 'solid',
      row_group.padding = px(1.5),
      heading.align = 'center',
      heading.border.bottom.style = "none",
      table_body.border.top.style = "none",
      table_body.border.bottom.color = "white",
      table.border.bottom.style = 'none',
      table.border.top.style = 'none',
      source_notes.border.lr.style = "none",
      ...
    ) %>%
    gt::opt_row_striping()
}

user_base <- tibble::tibble(
  user = c(Sys.getenv("Username")),
  password = (c(Sys.getenv("Password"))),
  permissions = c("admin"),
  name = c("User One")
)

# Define UI for application that draws a histogram
ui <- fluidPage(
  
  tags$head(
    tags$style(
      HTML("
        .shiny-output-error { visibility: hidden; }
        .shiny-output-error:before { visibility: hidden; }
      ")
    )
  ),
  
  div(class = "pull-right", shinyauthr::logoutUI(id = "logout")),

  shinyauthr::loginUI(id = "login"),

  div(
    id = "bar",
    titlePanel("TimMedia"),
    
    sidebarLayout(
      sidebarPanel(
        uiOutput("dynamicSelect"),  # Replace selectInput with uiOutput
        dateRangeInput("date","Date Range:",start = "2024-01-01"),
        imageOutput("teamLogo", height = "150px"), 
        width = 3
      ),
      
      mainPanel(
        tabsetPanel(id = "tabs",  # Add id here
                    tabPanel("Pitcher Splits",
                             gt_output("CountFilterP"),
                             gt_output("PitchFilterP"),
                             gt_output("PitchSideFilterP"),
                             gt_output("InningFilterP"),   
                             gt_output("SideFilterP")
                    ),
                    tabPanel("Batter Splits",
                             gt_output("CountFilterB"),
                             gt_output("PitchFilterB"),
                             gt_output("PitchSideFilterB"),
                             gt_output("InningFilterB"),   
                             gt_output("SideFilterB")  
                    )
        ),
        width = 9
      )
    )
  ) %>% shinyjs::hidden()
)

# Then in the server, add these new reactive elements:
server <- function(input, output, session) {
  options(shiny.sanitize.errors = TRUE)
  
  # Add this reactive element
  playerType <- reactive({
    if(input$tabs == "Pitcher Splits") {
      list(
        choices = unique(test$PitcherAndTeam),
        selected = NULL,
        logo_column = "PTeamLogo",
        filter_column = "PitcherAndTeam"
      )
    } else {
      list(
        choices = unique(test$BatterAndTeam),
        selected = NULL,
        logo_column = "BTeamLogo",
        filter_column = "BatterAndTeam"
      )
    }
  })
  
  # Create dynamic select input
  output$dynamicSelect <- renderUI({
    selectInput("player",
                "Select Player",
                choices = playerType()$choices)
  })
  
  # Modify the team logo render
  output$teamLogo <- renderImage({
    req(input$player)
    
    selected_logo <- test %>%
      filter(!!sym(playerType()$filter_column) == input$player) %>%
      slice(1) %>%
      pull(!!sym(playerType()$logo_column))
    
    temp_file <- tempfile(fileext = ".png")
    download.file(selected_logo, temp_file, mode = "wb")
    
    list(
      src = temp_file,
      contentType = "image/png",
      width = "150px",
      height = "150px",
      alt = "Team Logo",
      deleteFile = TRUE,
      style = "display: block; margin: auto;"
    )
  }, deleteFile = TRUE)
  
  
  credentials <- shinyauthr::loginServer(
    id = "login",
    data = user_base,
    user_col = user,
    pwd_col = password,
    sodium_hashed = FALSE,
    log_out = reactive(logout_init())
  )
  
  # Logout to hide
  logout_init <- shinyauthr::logoutServer(
    id = "logout",
    active = reactive(credentials()$user_auth)
  )
  
  observe({
    if (credentials()$user_auth) {
      shinyjs::show(id = "bar")
    } else {
      shinyjs::hide(id = "bar")
    }
  })
  output$CountFilterP <- render_gt({
    t <- test %>% filter(PitcherAndTeam == input$player) %>% group_by(Count) %>% 
      filter(between(as.Date(Date),input$date[1],input$date[2])) %>%
      summarise(
        Pitches = n(),
        #BBE = sum(BBE,na.rm = TRUE),
        "Whiff%" = mean(Whiff[Swing == TRUE],na.rm = TRUE),
        "SwStr%" = mean(Whiff,na.rm = TRUE),
        "CSW%" = mean(CSW,na.rm = TRUE),
        "Zone%" = mean(Zone,na.rm = TRUE),
        "ZCon%" = mean(Contact[Zone == TRUE & Swing == TRUE],na.rm = TRUE),
        "ZSwing%" = mean(Swing[Zone == TRUE],na.rm = TRUE),
        "OCon%" = mean(Contact[Zone == FALSE & Swing == TRUE],na.rm = TRUE),
        "OSwing%" = mean(Swing[Zone == FALSE],na.rm = TRUE),
        "Avg EV" = mean(ExitSpeed[BBE == TRUE],na.rm = TRUE),
        "EV90" = quantile(ExitSpeed[BBE == TRUE],.9,na.rm = TRUE),
        "Max EV" = max(ExitSpeed[BBE == TRUE],na.rm = TRUE),
        "Max EV" = ifelse(is.infinite(`Max EV`),NA,`Max EV`),
        "GB%" = mean(GB[BBE == TRUE],na.rm = TRUE),
        "LD%" = mean(LD[BBE == TRUE],na.rm = TRUE),
        "FB%" = mean(FB[BBE == TRUE],na.rm = TRUE),
        "AVG" = round(sum(Hit,na.rm = TRUE) / sum(AB,na.rm = TRUE),digits = 3),
        "OBP" = round((sum(Hit,na.rm = TRUE) + sum(Walk,na.rm = TRUE) + sum(HBP,na.rm = TRUE))/ 
                        sum(PA,na.rm = TRUE),digits = 3),
        "SLG" = (round(sum(Single,na.rm = TRUE) + sum(Double,na.rm = TRUE) * 2 + 
                         sum(Triple,na.rm = TRUE) * 3 + sum(HR,na.rm = TRUE)))/sum(AB,na.rm = TRUE))%>%
      ungroup() 
      
      tt <- test %>% mutate(Count = PSituation) %>% filter(PitcherAndTeam == input$player) %>% group_by(Count) %>% 
        filter(between(as.Date(Date),input$date[1],input$date[2])) %>%
        summarise(
          Pitches = n(),
          #BBE = sum(BBE,na.rm = TRUE),
          "Whiff%" = mean(Whiff[Swing == TRUE],na.rm = TRUE),
          "SwStr%" = mean(Whiff,na.rm = TRUE),
          "CSW%" = mean(CSW,na.rm = TRUE),
          "Zone%" = mean(Zone,na.rm = TRUE),
          "ZCon%" = mean(Contact[Zone == TRUE & Swing == TRUE],na.rm = TRUE),
          "ZSwing%" = mean(Swing[Zone == TRUE],na.rm = TRUE),
          "OCon%" = mean(Contact[Zone == FALSE & Swing == TRUE],na.rm = TRUE),
          "OSwing%" = mean(Swing[Zone == FALSE],na.rm = TRUE),
          "Avg EV" = mean(ExitSpeed[BBE == TRUE],na.rm = TRUE),
          "EV90" = quantile(ExitSpeed[BBE == TRUE],.9,na.rm = TRUE),
          "Max EV" = max(ExitSpeed[BBE == TRUE],na.rm = TRUE),
          "Max EV" = ifelse(is.infinite(`Max EV`),NA,`Max EV`),
          "GB%" = mean(GB[BBE == TRUE],na.rm = TRUE),
          "LD%" = mean(LD[BBE == TRUE],na.rm = TRUE),
          "FB%" = mean(FB[BBE == TRUE],na.rm = TRUE),
          "AVG" = round(sum(Hit,na.rm = TRUE) / sum(AB,na.rm = TRUE),digits = 3),
          "OBP" = round((sum(Hit,na.rm = TRUE) + sum(Walk,na.rm = TRUE) + sum(HBP,na.rm = TRUE))/ 
                          sum(PA,na.rm = TRUE),digits = 3),
          "SLG" = (round(sum(Single,na.rm = TRUE) + sum(Double,na.rm = TRUE) * 2 + 
                           sum(Triple,na.rm = TRUE) * 3 + sum(HR,na.rm = TRUE)))/sum(AB,na.rm = TRUE)) %>%
        ungroup()
      
      test <- rbind(tt,t)
      test %>%
      gt() %>% 
      gt_theme_tim() %>%
      fmt_number(columns = `Avg EV`:`Max EV`,decimals = 1) %>%
      cols_width(Count:Pitches ~ px(70),
                 everything() ~ px(85)) %>%
      cols_align(align = "center") %>%
      fmt_number(columns = AVG:SLG,decimals = 3) %>%
      fmt_percent(columns = ends_with("%")) %>%
      sub_missing() %>%
      #gt_theme_savant() %>% 
      opt_interactive(
        use_compact_mode = TRUE,
        use_pagination = FALSE
      )
  })
  output$PitchFilterP <- render_gt({
    test %>% 
      filter(PitcherAndTeam == input$player) %>%
      filter(between(as.Date(Date),input$date[1],input$date[2])) %>%
      group_by(AutoPitchType) %>%
      summarise(
        Pitches = n(),
        # BBE = sum(BBE,na.rm = TRUE),
        "Usage%" = n() / nrow(.),  # Added Usage% calculation
        "Swings" = sum(Swing,na.rm = TRUE),
        "Whiff%" = mean(Whiff[Swing == TRUE],na.rm = TRUE),
        "SwStr%" = mean(Whiff,na.rm = TRUE),
        "CSW%" = mean(CSW, na.rm = TRUE),
        "Zone%" = mean(Zone, na.rm = TRUE),
        "ZCon%" = mean(Contact[Zone == TRUE & Swing == TRUE], na.rm = TRUE),
        "ZSwing%" = mean(Swing[Zone == TRUE], na.rm = TRUE),
        "OCon%" = mean(Contact[Zone == FALSE & Swing == TRUE], na.rm = TRUE),
        "OSwing%" = mean(Swing[Zone == FALSE], na.rm = TRUE),
        "Avg EV" = mean(ExitSpeed[BBE == TRUE], na.rm = TRUE),
        "EV90" = quantile(ExitSpeed[BBE == TRUE], .9, na.rm = TRUE),
        "Max EV" = max(ExitSpeed[BBE == TRUE], na.rm = TRUE),
        "Max EV" = ifelse(is.infinite(`Max EV`), NA, `Max EV`),
        "GB%" = mean(GB[BBE == TRUE], na.rm = TRUE),
        "LD%" = mean(LD[BBE == TRUE], na.rm = TRUE),
        "FB%" = mean(FB[BBE == TRUE], na.rm = TRUE),
        "AVG" = round(sum(Hit, na.rm = TRUE) / sum(AB, na.rm = TRUE), digits = 3),
        "OBP" = round((sum(Hit, na.rm = TRUE) + sum(Walk, na.rm = TRUE) + sum(HBP, na.rm = TRUE)) / 
                        sum(PA, na.rm = TRUE), digits = 3),
        "SLG" = (round(sum(Single, na.rm = TRUE) + sum(Double, na.rm = TRUE) * 2 + 
                         sum(Triple, na.rm = TRUE) * 3 + sum(HR, na.rm = TRUE))) / sum(AB, na.rm = TRUE)
      ) %>%
      ungroup() %>% 
      arrange(desc(Pitches)) %>%
      gt() %>% 
      gt_theme_tim() %>%
      fmt_number(columns = `Avg EV`:`Max EV`, decimals = 1) %>%
      cols_label(AutoPitchType = "Type") %>%
      cols_width(
        AutoPitchType ~ px(100),
        Pitches ~ px(70),
        everything() ~ px(85)
      ) %>%
      cols_align(align = "center") %>%
      fmt_number(columns = AVG:SLG, decimals = 3) %>%
      fmt_percent(columns = ends_with("%")) %>%
      sub_missing() %>%
      opt_interactive(
        use_compact_mode = TRUE,
        use_pagination = FALSE
      )
  })
  output$PitchSideFilterP <- render_gt({
    test %>% 
      filter(PitcherAndTeam == input$player) %>% 
      filter(between(as.Date(Date),input$date[1],input$date[2])) %>%
      group_by(BatterSide) %>%
      mutate(total_side = n()) %>%
      ungroup() %>%
      group_by(AutoPitchType, BatterSide) %>%
      summarise(
        Pitches = n(),
        #BBE = sum(BBE,na.rm = TRUE),
        "Usage%" = (n() / first(total_side)),
        "Swings" = sum(Swing,na.rm = TRUE),
        "Whiff%" = mean(Whiff[Swing == TRUE],na.rm = TRUE),
        "SwStr%" = mean(Whiff,na.rm = TRUE),
        "CSW%" = mean(CSW, na.rm = TRUE),
        "Zone%" = mean(Zone, na.rm = TRUE),
        "ZCon%" = mean(Contact[Zone == TRUE & Swing == TRUE], na.rm = TRUE),
        "ZSwing%" = mean(Swing[Zone == TRUE], na.rm = TRUE),
        "OCon%" = mean(Contact[Zone == FALSE & Swing == TRUE], na.rm = TRUE),
        "OSwing%" = mean(Swing[Zone == FALSE], na.rm = TRUE),
        "Avg EV" = mean(ExitSpeed[BBE == TRUE], na.rm = TRUE),
        "EV90" = quantile(ExitSpeed[BBE == TRUE], .9, na.rm = TRUE),
        "Max EV" = max(ExitSpeed[BBE == TRUE], na.rm = TRUE),
        "Max EV" = ifelse(is.infinite(`Max EV`), NA, `Max EV`),
        "GB%" = mean(GB[BBE == TRUE], na.rm = TRUE),
        "LD%" = mean(LD[BBE == TRUE], na.rm = TRUE),
        "FB%" = mean(FB[BBE == TRUE], na.rm = TRUE),
        "AVG" = round(sum(Hit, na.rm = TRUE) / sum(AB, na.rm = TRUE), digits = 3),
        "OBP" = round((sum(Hit, na.rm = TRUE) + sum(Walk, na.rm = TRUE) + sum(HBP, na.rm = TRUE)) / 
                        sum(PA, na.rm = TRUE), digits = 3),
        "SLG" = (round(sum(Single, na.rm = TRUE) + sum(Double, na.rm = TRUE) * 2 + 
                         sum(Triple, na.rm = TRUE) * 3 + sum(HR, na.rm = TRUE))) / sum(AB, na.rm = TRUE)
      ) %>%
      ungroup() %>% 
      arrange(desc(BatterSide),desc(Pitches)) %>%
      gt() %>% 
      gt_theme_tim() %>%
      fmt_number(columns = `Avg EV`:`Max EV`, decimals = 1) %>%
      cols_label(AutoPitchType = "Type", BatterSide = "Side") %>%
      cols_width(
        AutoPitchType ~ px(100),
        Pitches ~ px(70),
        BatterSide ~ px(70),
        everything() ~ px(85)
      ) %>%
      cols_align(align = "center") %>%
      fmt_number(columns = AVG:SLG, decimals = 3) %>%
      fmt_percent(columns = ends_with("%")) %>%
      sub_missing() %>%
      opt_interactive(
        use_compact_mode = TRUE,
        use_pagination = FALSE
      )
  })
  output$InningFilterP <- render_gt({
    test %>% filter(PitcherAndTeam == input$player) %>% group_by(Inning) %>%
      filter(between(as.Date(Date),input$date[1],input$date[2])) %>%
      summarise(
        Pitches = n(),
        #BBE = sum(BBE,na.rm = TRUE),
        "Swings" = sum(Swing,na.rm = TRUE),
        "Whiff%" = mean(Whiff[Swing == TRUE],na.rm = TRUE),
        "SwStr%" = mean(Whiff,na.rm = TRUE),
        "CSW%" = mean(CSW,na.rm = TRUE),
        "Zone%" = mean(Zone,na.rm = TRUE),
        "ZCon%" = mean(Contact[Zone == TRUE & Swing == TRUE],na.rm = TRUE),
        "ZSwing%" = mean(Swing[Zone == TRUE],na.rm = TRUE),
        "OCon%" = mean(Contact[Zone == FALSE & Swing == TRUE],na.rm = TRUE),
        "OSwing%" = mean(Swing[Zone == FALSE],na.rm = TRUE),
        "Avg EV" = mean(ExitSpeed[BBE == TRUE],na.rm = TRUE),
        "EV90" = quantile(ExitSpeed[BBE == TRUE],.9,na.rm = TRUE),
        "Max EV" = max(ExitSpeed[BBE == TRUE],na.rm = TRUE),
        "Max EV" = ifelse(is.infinite(`Max EV`),NA,`Max EV`),
        "GB%" = mean(GB[BBE == TRUE],na.rm = TRUE),
        "LD%" = mean(LD[BBE == TRUE],na.rm = TRUE),
        "FB%" = mean(FB[BBE == TRUE],na.rm = TRUE),
        "AVG" = round(sum(Hit,na.rm = TRUE) / sum(AB,na.rm = TRUE),digits = 3),
        "OBP" = round((sum(Hit,na.rm = TRUE) + sum(Walk,na.rm = TRUE) + sum(HBP,na.rm = TRUE))/ 
                        sum(PA,na.rm = TRUE),digits = 3),
        "SLG" = (round(sum(Single,na.rm = TRUE) + sum(Double,na.rm = TRUE) * 2 + 
                         sum(Triple,na.rm = TRUE) * 3 + sum(HR,na.rm = TRUE)))/sum(AB,na.rm = TRUE))%>%
      ungroup()%>% 
      gt() %>% 
      gt_theme_tim() %>%
      fmt_number(columns = `Avg EV`:`Max EV`,decimals = 1) %>%
      cols_width(Inning:Pitches ~ px(70),
                 everything() ~ px(85)) %>%
      cols_align(align = "center") %>%
      fmt_number(columns = AVG:SLG,decimals = 3) %>%
      fmt_percent(columns = ends_with("%")) %>%
      sub_missing() %>%
      #gt_theme_savant() %>% 
      opt_interactive(
        use_compact_mode = TRUE,
        use_pagination = FALSE
      )
  })
  output$SideFilterP <- render_gt({
    test1 <- test %>% filter(PitcherAndTeam == input$player) %>% group_by(BatterSide) %>%
      filter(between(as.Date(Date),input$date[1],input$date[2])) %>%
      summarise(
        Pitches = n(),
        #BBE = sum(BBE,na.rm = TRUE),
        "Swings" = sum(Swing,na.rm = TRUE),
        "Whiff%" = mean(Whiff[Swing == TRUE],na.rm = TRUE),
        "SwStr%" = mean(Whiff,na.rm = TRUE),
        "CSW%" = mean(CSW,na.rm = TRUE),
        "Zone%" = mean(Zone,na.rm = TRUE),
        "ZCon%" = mean(Contact[Zone == TRUE & Swing == TRUE],na.rm = TRUE),
        "ZSwing%" = mean(Swing[Zone == TRUE],na.rm = TRUE),
        "OCon%" = mean(Contact[Zone == FALSE & Swing == TRUE],na.rm = TRUE),
        "OSwing%" = mean(Swing[Zone == FALSE],na.rm = TRUE),
        "Avg EV" = mean(ExitSpeed[BBE == TRUE],na.rm = TRUE),
        "EV90" = quantile(ExitSpeed[BBE == TRUE],.9,na.rm = TRUE),
        "Max EV" = max(ExitSpeed[BBE == TRUE],na.rm = TRUE),
        "Max EV" = ifelse(is.infinite(`Max EV`),NA,`Max EV`),
        "GB%" = mean(GB[BBE == TRUE],na.rm = TRUE),
        "LD%" = mean(LD[BBE == TRUE],na.rm = TRUE),
        "FB%" = mean(FB[BBE == TRUE],na.rm = TRUE),
        "AVG" = round(sum(Hit,na.rm = TRUE) / sum(AB,na.rm = TRUE),digits = 3),
        "OBP" = round((sum(Hit,na.rm = TRUE) + sum(Walk,na.rm = TRUE) + sum(HBP,na.rm = TRUE))/ 
                        sum(PA,na.rm = TRUE),digits = 3),
        "SLG" = (round(sum(Single,na.rm = TRUE) + sum(Double,na.rm = TRUE) * 2 + 
                         sum(Triple,na.rm = TRUE) * 3 + sum(HR,na.rm = TRUE)))/sum(AB,na.rm = TRUE))%>%
      ungroup()
    test2 <- test %>% mutate(BatterSide = "Both") %>% filter(PitcherAndTeam == input$player) %>% group_by(BatterSide) %>%
      filter(between(as.Date(Date),input$date[1],input$date[2])) %>%
      summarise(
        Pitches = n(),
        #BBE = sum(BBE,na.rm = TRUE),
        "Swings" = sum(Swing,na.rm = TRUE),
        "Whiff%" = mean(Whiff[Swing == TRUE],na.rm = TRUE),
        "SwStr%" = mean(Whiff,na.rm = TRUE),
        "CSW%" = mean(CSW,na.rm = TRUE),
        "Zone%" = mean(Zone,na.rm = TRUE),
        "ZCon%" = mean(Contact[Zone == TRUE & Swing == TRUE],na.rm = TRUE),
        "ZSwing%" = mean(Swing[Zone == TRUE],na.rm = TRUE),
        "OCon%" = mean(Contact[Zone == FALSE & Swing == TRUE],na.rm = TRUE),
        "OSwing%" = mean(Swing[Zone == FALSE],na.rm = TRUE),
        "Avg EV" = mean(ExitSpeed[BBE == TRUE],na.rm = TRUE),
        "EV90" = quantile(ExitSpeed[BBE == TRUE],.9,na.rm = TRUE),
        "Max EV" = max(ExitSpeed[BBE == TRUE],na.rm = TRUE),
        "Max EV" = ifelse(is.infinite(`Max EV`),NA,`Max EV`),
        "GB%" = mean(GB[BBE == TRUE],na.rm = TRUE),
        "LD%" = mean(LD[BBE == TRUE],na.rm = TRUE),
        "FB%" = mean(FB[BBE == TRUE],na.rm = TRUE),
        "AVG" = round(sum(Hit,na.rm = TRUE) / sum(AB,na.rm = TRUE),digits = 3),
        "OBP" = round((sum(Hit,na.rm = TRUE) + sum(Walk,na.rm = TRUE) + sum(HBP,na.rm = TRUE))/ 
                        sum(PA,na.rm = TRUE),digits = 3),
        "SLG" = (round(sum(Single,na.rm = TRUE) + sum(Double,na.rm = TRUE) * 2 + 
                         sum(Triple,na.rm = TRUE) * 3 + sum(HR,na.rm = TRUE)))/sum(AB,na.rm = TRUE))%>%
      ungroup()
    test <- rbind(test1,test2)
    test %>%
      gt() %>% 
      gt_theme_tim() %>%
      fmt_number(columns = `Avg EV`:`Max EV`,decimals = 1) %>%
      cols_width(BatterSide:Pitches ~ px(70),
                 everything() ~ px(85)) %>%
      cols_align(align = "center") %>%
      cols_label(BatterSide = "Side") %>%
      fmt_number(columns = AVG:SLG,decimals = 3) %>%
      fmt_percent(columns = ends_with("%")) %>%
      sub_missing() %>%
      #gt_theme_savant() %>% 
      opt_interactive(
        use_compact_mode = TRUE,
        use_pagination = FALSE
      )
    
  })
  output$slashlineP <- render_gt({
    test %>%  filter(PitcherAndTeam == input$player) %>%
      filter(between(as.Date(Date),input$date[1],input$date[2])) %>%
      summarise(
        Pitches = n(),
        `1B` = sum(Single,na.rm = TRUE),
        `2B` = sum(Double,na.rm = TRUE),
        `3B` = sum(Triple,na.rm = TRUE),
        HR = sum(HR,na.rm = TRUE),
        SO = sum(Strikeout,na.rm = TRUE),
        BB = sum(Walk,na.rm = TRUE),
        Whiffs = sum(Whiff,na.rm = TRUE),
        `Hard Hits` = sum(HardHit,na.rm = TRUE)
      )%>%
      ungroup()%>% 
      gt() %>% 
      gt_theme_tim() %>%
      cols_align(align = "center") %>%
      # gt_theme_savant() %>% 
      opt_interactive(
        use_compact_mode = TRUE,
        use_pagination = FALSE
      )
  })
  
  output$CountFilterB <- render_gt({
    t <- test %>% filter(BatterAndTeam == input$player) %>% group_by(Count) %>% 
      filter(between(as.Date(Date),input$date[1],input$date[2])) %>%
      summarise(
        Pitches = n(),
        #BBE = sum(BBE,na.rm = TRUE),
        "Swings" = sum(Swing,na.rm = TRUE),
        "Whiff%" = mean(Whiff[Swing == TRUE],na.rm = TRUE),
        "SwStr%" = mean(Whiff,na.rm = TRUE),
        "CSW%" = mean(CSW,na.rm = TRUE),
        "Zone%" = mean(Zone,na.rm = TRUE),
        "ZCon%" = mean(Contact[Zone == TRUE & Swing == TRUE],na.rm = TRUE),
        "ZSwing%" = mean(Swing[Zone == TRUE],na.rm = TRUE),
        "OCon%" = mean(Contact[Zone == FALSE & Swing == TRUE],na.rm = TRUE),
        "OSwing%" = mean(Swing[Zone == FALSE],na.rm = TRUE),
        "Avg EV" = mean(ExitSpeed[BBE == TRUE],na.rm = TRUE),
        "EV90" = quantile(ExitSpeed[BBE == TRUE],.9,na.rm = TRUE),
        "Max EV" = max(ExitSpeed[BBE == TRUE],na.rm = TRUE),
        "Max EV" = ifelse(is.infinite(`Max EV`),NA,`Max EV`),
        "GB%" = mean(GB[BBE == TRUE],na.rm = TRUE),
        "LD%" = mean(LD[BBE == TRUE],na.rm = TRUE),
        "FB%" = mean(FB[BBE == TRUE],na.rm = TRUE),
        "AVG" = round(sum(Hit,na.rm = TRUE) / sum(AB,na.rm = TRUE),digits = 3),
        "OBP" = round((sum(Hit,na.rm = TRUE) + sum(Walk,na.rm = TRUE) + sum(HBP,na.rm = TRUE))/ 
                        sum(PA,na.rm = TRUE),digits = 3),
        "SLG" = (round(sum(Single,na.rm = TRUE) + sum(Double,na.rm = TRUE) * 2 + 
                         sum(Triple,na.rm = TRUE) * 3 + sum(HR,na.rm = TRUE)))/sum(AB,na.rm = TRUE))%>%
      ungroup()
    tt <- test %>% mutate(Count = BSituation) %>% filter(BatterAndTeam == input$player) %>% group_by(Count) %>% 
      filter(between(as.Date(Date),input$date[1],input$date[2])) %>%
      summarise(
        Pitches = n(),
        #BBE = sum(BBE,na.rm = TRUE),
        "Swings" = sum(Swing,na.rm = TRUE),
        "Whiff%" = mean(Whiff[Swing == TRUE],na.rm = TRUE),
        "SwStr%" = mean(Whiff,na.rm = TRUE),
        "CSW%" = mean(CSW,na.rm = TRUE),
        "Zone%" = mean(Zone,na.rm = TRUE),
        "ZCon%" = mean(Contact[Zone == TRUE & Swing == TRUE],na.rm = TRUE),
        "ZSwing%" = mean(Swing[Zone == TRUE],na.rm = TRUE),
        "OCon%" = mean(Contact[Zone == FALSE & Swing == TRUE],na.rm = TRUE),
        "OSwing%" = mean(Swing[Zone == FALSE],na.rm = TRUE),
        "Avg EV" = mean(ExitSpeed[BBE == TRUE],na.rm = TRUE),
        "EV90" = quantile(ExitSpeed[BBE == TRUE],.9,na.rm = TRUE),
        "Max EV" = max(ExitSpeed[BBE == TRUE],na.rm = TRUE),
        "Max EV" = ifelse(is.infinite(`Max EV`),NA,`Max EV`),
        "GB%" = mean(GB[BBE == TRUE],na.rm = TRUE),
        "LD%" = mean(LD[BBE == TRUE],na.rm = TRUE),
        "FB%" = mean(FB[BBE == TRUE],na.rm = TRUE),
        "AVG" = round(sum(Hit,na.rm = TRUE) / sum(AB,na.rm = TRUE),digits = 3),
        "OBP" = round((sum(Hit,na.rm = TRUE) + sum(Walk,na.rm = TRUE) + sum(HBP,na.rm = TRUE))/ 
                        sum(PA,na.rm = TRUE),digits = 3),
        "SLG" = (round(sum(Single,na.rm = TRUE) + sum(Double,na.rm = TRUE) * 2 + 
                         sum(Triple,na.rm = TRUE) * 3 + sum(HR,na.rm = TRUE)))/sum(AB,na.rm = TRUE))%>%
      ungroup()
    
    test <- rbind(tt,t)
    test %>%
      gt() %>% 
      gt_theme_tim() %>%
      fmt_number(columns = `Avg EV`:`Max EV`,decimals = 1) %>%
      cols_width(Count:Pitches ~ px(70),
                 everything() ~ px(85)) %>%
      cols_align(align = "center") %>%
      fmt_number(columns = AVG:SLG,decimals = 3) %>%
      fmt_percent(columns = ends_with("%")) %>%
      sub_missing() %>%
      #gt_theme_savant() %>% 
      opt_interactive(
        use_compact_mode = TRUE,
        use_pagination = FALSE
      )
  })
  output$PitchFilterB <- render_gt({
    test %>% 
      filter(BatterAndTeam == input$player) %>%
      filter(between(as.Date(Date),input$date[1],input$date[2])) %>%
      group_by(AutoPitchType) %>%
      summarise(
        Pitches = n(),
        # BBE = sum(BBE,na.rm = TRUE),
        "Pitch%" = n() / nrow(.),  # Added Pitch% calculation
        "Swings" = sum(Swing,na.rm = TRUE),
        "Whiff%" = mean(Whiff[Swing == TRUE],na.rm = TRUE),
        "SwStr%" = mean(Whiff,na.rm = TRUE),
        "CSW%" = mean(CSW, na.rm = TRUE),
        "Zone%" = mean(Zone, na.rm = TRUE),
        "ZCon%" = mean(Contact[Zone == TRUE & Swing == TRUE], na.rm = TRUE),
        "ZSwing%" = mean(Swing[Zone == TRUE], na.rm = TRUE),
        "OCon%" = mean(Contact[Zone == FALSE & Swing == TRUE], na.rm = TRUE),
        "OSwing%" = mean(Swing[Zone == FALSE], na.rm = TRUE),
        "Avg EV" = mean(ExitSpeed[BBE == TRUE], na.rm = TRUE),
        "EV90" = quantile(ExitSpeed[BBE == TRUE], .9, na.rm = TRUE),
        "Max EV" = max(ExitSpeed[BBE == TRUE], na.rm = TRUE),
        "Max EV" = ifelse(is.infinite(`Max EV`), NA, `Max EV`),
        "GB%" = mean(GB[BBE == TRUE], na.rm = TRUE),
        "LD%" = mean(LD[BBE == TRUE], na.rm = TRUE),
        "FB%" = mean(FB[BBE == TRUE], na.rm = TRUE),
        "AVG" = round(sum(Hit, na.rm = TRUE) / sum(AB, na.rm = TRUE), digits = 3),
        "OBP" = round((sum(Hit, na.rm = TRUE) + sum(Walk, na.rm = TRUE) + sum(HBP, na.rm = TRUE)) / 
                        sum(PA, na.rm = TRUE), digits = 3),
        "SLG" = (round(sum(Single, na.rm = TRUE) + sum(Double, na.rm = TRUE) * 2 + 
                         sum(Triple, na.rm = TRUE) * 3 + sum(HR, na.rm = TRUE))) / sum(AB, na.rm = TRUE)
      ) %>%
      ungroup() %>% 
      arrange(desc(Pitches)) %>%
      gt() %>% 
      gt_theme_tim() %>%
      fmt_number(columns = `Avg EV`:`Max EV`, decimals = 1) %>%
      cols_label(AutoPitchType = "Type") %>%
      cols_width(
        AutoPitchType ~ px(100),
        Pitches ~ px(70),
        everything() ~ px(85)
      ) %>%
      cols_align(align = "center") %>%
      fmt_number(columns = AVG:SLG, decimals = 3) %>%
      fmt_percent(columns = ends_with("%")) %>%
      sub_missing() %>%
      opt_interactive(
        use_compact_mode = TRUE,
        use_pagination = FALSE
      )
  })
  output$PitchSideFilterB <- render_gt({
    test %>% 
      filter(BatterAndTeam == input$player) %>% 
      filter(between(as.Date(Date),input$date[1],input$date[2])) %>%
      group_by(PitcherThrows) %>%
      mutate(total_side = n()) %>%
      ungroup() %>%
      group_by(AutoPitchType, PitcherThrows) %>%
      summarise(
        Pitches = n(),
        #BBE = sum(BBE,na.rm = TRUE),
        "Pitch%" = (n() / first(total_side)),
        "Swings" = sum(Swing,na.rm = TRUE),
        "Whiff%" = mean(Whiff[Swing == TRUE],na.rm = TRUE),
        "SwStr%" = mean(Whiff,na.rm = TRUE),
        "CSW%" = mean(CSW, na.rm = TRUE),
        "Zone%" = mean(Zone, na.rm = TRUE),
        "ZCon%" = mean(Contact[Zone == TRUE & Swing == TRUE], na.rm = TRUE),
        "ZSwing%" = mean(Swing[Zone == TRUE], na.rm = TRUE),
        "OCon%" = mean(Contact[Zone == FALSE & Swing == TRUE], na.rm = TRUE),
        "OSwing%" = mean(Swing[Zone == FALSE], na.rm = TRUE),
        "Avg EV" = mean(ExitSpeed[BBE == TRUE], na.rm = TRUE),
        "EV90" = quantile(ExitSpeed[BBE == TRUE], .9, na.rm = TRUE),
        "Max EV" = max(ExitSpeed[BBE == TRUE], na.rm = TRUE),
        "Max EV" = ifelse(is.infinite(`Max EV`), NA, `Max EV`),
        "GB%" = mean(GB[BBE == TRUE], na.rm = TRUE),
        "LD%" = mean(LD[BBE == TRUE], na.rm = TRUE),
        "FB%" = mean(FB[BBE == TRUE], na.rm = TRUE),
        "AVG" = round(sum(Hit, na.rm = TRUE) / sum(AB, na.rm = TRUE), digits = 3),
        "OBP" = round((sum(Hit, na.rm = TRUE) + sum(Walk, na.rm = TRUE) + sum(HBP, na.rm = TRUE)) / 
                        sum(PA, na.rm = TRUE), digits = 3),
        "SLG" = (round(sum(Single, na.rm = TRUE) + sum(Double, na.rm = TRUE) * 2 + 
                         sum(Triple, na.rm = TRUE) * 3 + sum(HR, na.rm = TRUE))) / sum(AB, na.rm = TRUE)
      ) %>%
      ungroup() %>% 
      arrange(desc(PitcherThrows),desc(Pitches)) %>%
      gt() %>% 
      gt_theme_tim() %>%
      fmt_number(columns = `Avg EV`:`Max EV`, decimals = 1) %>%
      cols_label(AutoPitchType = "Type", PitcherThrows = "Hand") %>%
      cols_width(
        AutoPitchType ~ px(100),
        Pitches ~ px(70),
        PitcherThrows ~ px(70),
        everything() ~ px(85)
      ) %>%
      cols_align(align = "center") %>%
      fmt_number(columns = AVG:SLG, decimals = 3) %>%
      fmt_percent(columns = ends_with("%")) %>%
      sub_missing() %>%
      opt_interactive(
        use_compact_mode = TRUE,
        use_pagination = FALSE
      )
  })
  output$InningFilterB <- render_gt({
    test %>% filter(BatterAndTeam == input$player) %>% group_by(Inning) %>%
      filter(between(as.Date(Date),input$date[1],input$date[2])) %>%
      summarise(
        Pitches = n(),
        #BBE = sum(BBE,na.rm = TRUE),
        "Swings" = sum(Swing,na.rm = TRUE),
        "Whiff%" = mean(Whiff[Swing == TRUE],na.rm = TRUE),
        "SwStr%" = mean(Whiff,na.rm = TRUE),
        "CSW%" = mean(CSW,na.rm = TRUE),
        "Zone%" = mean(Zone,na.rm = TRUE),
        "ZCon%" = mean(Contact[Zone == TRUE & Swing == TRUE],na.rm = TRUE),
        "ZSwing%" = mean(Swing[Zone == TRUE],na.rm = TRUE),
        "OCon%" = mean(Contact[Zone == FALSE & Swing == TRUE],na.rm = TRUE),
        "OSwing%" = mean(Swing[Zone == FALSE],na.rm = TRUE),
        "Avg EV" = mean(ExitSpeed[BBE == TRUE],na.rm = TRUE),
        "EV90" = quantile(ExitSpeed[BBE == TRUE],.9,na.rm = TRUE),
        "Max EV" = max(ExitSpeed[BBE == TRUE],na.rm = TRUE),
        "Max EV" = ifelse(is.infinite(`Max EV`),NA,`Max EV`),
        "GB%" = mean(GB[BBE == TRUE],na.rm = TRUE),
        "LD%" = mean(LD[BBE == TRUE],na.rm = TRUE),
        "FB%" = mean(FB[BBE == TRUE],na.rm = TRUE),
        "AVG" = round(sum(Hit,na.rm = TRUE) / sum(AB,na.rm = TRUE),digits = 3),
        "OBP" = round((sum(Hit,na.rm = TRUE) + sum(Walk,na.rm = TRUE) + sum(HBP,na.rm = TRUE))/ 
                        sum(PA,na.rm = TRUE),digits = 3),
        "SLG" = (round(sum(Single,na.rm = TRUE) + sum(Double,na.rm = TRUE) * 2 + 
                         sum(Triple,na.rm = TRUE) * 3 + sum(HR,na.rm = TRUE)))/sum(AB,na.rm = TRUE))%>%
      ungroup()%>% 
      gt() %>% 
      gt_theme_tim() %>%
      fmt_number(columns = `Avg EV`:`Max EV`,decimals = 1) %>%
      cols_width(Inning:Pitches ~ px(70),
                 everything() ~ px(85)) %>%
      cols_align(align = "center") %>%
      fmt_number(columns = AVG:SLG,decimals = 3) %>%
      fmt_percent(columns = ends_with("%")) %>%
      sub_missing() %>%
      #gt_theme_savant() %>% 
      opt_interactive(
        use_compact_mode = TRUE,
        use_pagination = FALSE
      )
  })
  output$SideFilterB <- render_gt({
    test1 <- test %>% filter(BatterAndTeam == input$player) %>% group_by(PitcherThrows) %>%
      filter(between(as.Date(Date),input$date[1],input$date[2])) %>%
      summarise(
        Pitches = n(),
        #BBE = sum(BBE,na.rm = TRUE),
        "Swings" = sum(Swing,na.rm = TRUE),
        "Whiff%" = mean(Whiff[Swing == TRUE],na.rm = TRUE),
        "SwStr%" = mean(Whiff,na.rm = TRUE),
        "CSW%" = mean(CSW,na.rm = TRUE),
        "Zone%" = mean(Zone,na.rm = TRUE),
        "ZCon%" = mean(Contact[Zone == TRUE & Swing == TRUE],na.rm = TRUE),
        "ZSwing%" = mean(Swing[Zone == TRUE],na.rm = TRUE),
        "OCon%" = mean(Contact[Zone == FALSE & Swing == TRUE],na.rm = TRUE),
        "OSwing%" = mean(Swing[Zone == FALSE],na.rm = TRUE),
        "Avg EV" = mean(ExitSpeed[BBE == TRUE],na.rm = TRUE),
        "EV90" = quantile(ExitSpeed[BBE == TRUE],.9,na.rm = TRUE),
        "Max EV" = max(ExitSpeed[BBE == TRUE],na.rm = TRUE),
        "Max EV" = ifelse(is.infinite(`Max EV`),NA,`Max EV`),
        "GB%" = mean(GB[BBE == TRUE],na.rm = TRUE),
        "LD%" = mean(LD[BBE == TRUE],na.rm = TRUE),
        "FB%" = mean(FB[BBE == TRUE],na.rm = TRUE),
        "AVG" = round(sum(Hit,na.rm = TRUE) / sum(AB,na.rm = TRUE),digits = 3),
        "OBP" = round((sum(Hit,na.rm = TRUE) + sum(Walk,na.rm = TRUE) + sum(HBP,na.rm = TRUE))/ 
                        sum(PA,na.rm = TRUE),digits = 3),
        "SLG" = (round(sum(Single,na.rm = TRUE) + sum(Double,na.rm = TRUE) * 2 + 
                         sum(Triple,na.rm = TRUE) * 3 + sum(HR,na.rm = TRUE)))/sum(AB,na.rm = TRUE))%>%
      ungroup()
    test2 <- test %>% mutate(PitcherThrows = "Both") %>% filter(BatterAndTeam == input$player) %>% group_by(PitcherThrows) %>%
      filter(between(as.Date(Date),input$date[1],input$date[2])) %>%
      summarise(
        Pitches = n(),
        #BBE = sum(BBE,na.rm = TRUE),
        "Swings" = sum(Swing,na.rm = TRUE),
        "Whiff%" = mean(Whiff[Swing == TRUE],na.rm = TRUE),
        "SwStr%" = mean(Whiff,na.rm = TRUE),
        "CSW%" = mean(CSW,na.rm = TRUE),
        "Zone%" = mean(Zone,na.rm = TRUE),
        "ZCon%" = mean(Contact[Zone == TRUE & Swing == TRUE],na.rm = TRUE),
        "ZSwing%" = mean(Swing[Zone == TRUE],na.rm = TRUE),
        "OCon%" = mean(Contact[Zone == FALSE & Swing == TRUE],na.rm = TRUE),
        "OSwing%" = mean(Swing[Zone == FALSE],na.rm = TRUE),
        "Avg EV" = mean(ExitSpeed[BBE == TRUE],na.rm = TRUE),
        "EV90" = quantile(ExitSpeed[BBE == TRUE],.9,na.rm = TRUE),
        "Max EV" = max(ExitSpeed[BBE == TRUE],na.rm = TRUE),
        "Max EV" = ifelse(is.infinite(`Max EV`),NA,`Max EV`),
        "GB%" = mean(GB[BBE == TRUE],na.rm = TRUE),
        "LD%" = mean(LD[BBE == TRUE],na.rm = TRUE),
        "FB%" = mean(FB[BBE == TRUE],na.rm = TRUE),
        "AVG" = round(sum(Hit,na.rm = TRUE) / sum(AB,na.rm = TRUE),digits = 3),
        "OBP" = round((sum(Hit,na.rm = TRUE) + sum(Walk,na.rm = TRUE) + sum(HBP,na.rm = TRUE))/ 
                        sum(PA,na.rm = TRUE),digits = 3),
        "SLG" = (round(sum(Single,na.rm = TRUE) + sum(Double,na.rm = TRUE) * 2 + 
                         sum(Triple,na.rm = TRUE) * 3 + sum(HR,na.rm = TRUE)))/sum(AB,na.rm = TRUE))%>%
      ungroup()
    test <- rbind(test1,test2)
    test %>%
      gt() %>% 
      gt_theme_tim() %>%
      fmt_number(columns = `Avg EV`:`Max EV`,decimals = 1) %>%
      cols_width(PitcherThrows:Pitches ~ px(70),
                 everything() ~ px(85)) %>%
      cols_align(align = "center") %>%
      cols_label(PitcherThrows = "Hand") %>%
      fmt_number(columns = AVG:SLG,decimals = 3) %>%
      fmt_percent(columns = ends_with("%")) %>%
      sub_missing() %>%
      #gt_theme_savant() %>% 
      opt_interactive(
        use_compact_mode = TRUE,
        use_pagination = FALSE
      )
    
  })
  output$slashlineB <- render_gt({
    test %>%  filter(BatterAndTeam == input$player) %>%
      filter(between(as.Date(Date),input$date[1],input$date[2])) %>%
      summarise(
        Pitches = n(),
        `1B` = sum(Single,na.rm = TRUE),
        `2B` = sum(Double,na.rm = TRUE),
        `3B` = sum(Triple,na.rm = TRUE),
        HR = sum(HR,na.rm = TRUE),
        SO = sum(Strikeout,na.rm = TRUE),
        BB = sum(Walk,na.rm = TRUE),
        Whiffs = sum(Whiff,na.rm = TRUE),
        `Hard Hits` = sum(HardHit,na.rm = TRUE)
      )%>%
      ungroup()%>% 
      gt() %>% 
      gt_theme_tim() %>%
      cols_align(align = "center") %>%
      # gt_theme_savant() %>% 
      opt_interactive(
        use_compact_mode = TRUE,
        use_pagination = FALSE
      )
  })
  
  
  
}

# Run the application 
shinyApp(ui = ui, server = server)