app.R

library(shiny)
library(dplyr)
library(data.table)
library(xgboost)
library(caret)
library(shinythemes)
library(ggplot2)

# Add sample pitcher data - you'll want to replace this with your actual data
# pitcher_data <- data.frame(
#   pitcher_name = c("Pitcher A", "Pitcher A", "Pitcher B", "Pitcher B"),
#   pitch_name = c("Fastball", "Slider", "Fastball", "Curveball"),
#   velo = c(95, 85, 92, 78),
#   ivb = c(16, 2, 15, -5),
#   hb = c(6, 2, 5, -8),
#   spinrate = c(2300, 2500, 2200, 2400),
#   ext = c(6.3, 6.2, 6.5, 6.4),
#   spinaxisdiff = c(0, 5, -2, 8),
#   x0 = c(-1.5, -1.6, -1.4, -1.3),
#   z0 = c(5, 4.8, 5.2, 5.1),
#   phand = c("R", "R", "L", "L")
# )

model <- xgb.load('TimStuff2.ubj')

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)
}

scale_TimStuff <- function(raw_score, model_mean, model_sd) {
  scaled_score <- (raw_score - model_mean) / model_sd
  result <- 100 - (scaled_score * 10)
  return(result)
}

timstuff <- function(game) {
  # game <- calculate_primary(game)
  game <- game %>%
    mutate(VAA = calculate_VAA(vz0, ay, az, vy0, y0),
           SADiff = calculate_SADiff(pfxX, pfxZ, spinDirection),
           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))
  #mutate(SADiff = calculate_SADiff(pfxX, pfxZ,spinDirection))
  # 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)
}

download_private_parquet <- function(repo_id, filename) {
  library(httr)
  library(arrow)
  
  # Create the direct download URL based on your example
  url <- paste0("https://huggingface.co/datasets/", repo_id, "/resolve/main/", filename, "?download=true")
  
  # Create a temporary file
  temp_file <- tempfile(fileext = ".parquet")
  
  # Download directly to file
  response <- GET(
    url,
    add_headers(Authorization = paste("Bearer", Sys.getenv("GETCSV"))),
    write_disk(temp_file, overwrite = TRUE)
  )
  
  # Check if download was successful
  if (status_code(response) == 200) {
    tryCatch({
      # Read the parquet file
      data <- read_parquet(temp_file)
      file.remove(temp_file)
      return(data)
    }, error = function(e) {
      file.remove(temp_file)
      stop(paste("Error reading parquet file:", e$message))
    })
  } else {
    file.remove(temp_file)
    stop(paste("Failed to download file. Status code:", status_code(response)))
  }
}


MLB24T <- download_private_parquet("TimStats/StatcastDataAll", "MLB26.parquet")

MLB24T <- timstuff(MLB24T)

pitcher_data <- MLB24T %>%
  group_by(`Pitcher Name`,pitch_name,phand) %>%
  summarise(
    "start_speed" = mean(start_speed,na.rm = TRUE),
    "IVB" = mean(IVB,na.rm = TRUE),
    "HB" = mean(HB,na.rm = TRUE) ,
    "EAA" = mean(EAA,na.rm = TRUE) ,
    "x0" = mean(x0,na.rm = TRUE) ,
    "z0" = mean(z0, na.rm = TRUE) ,
    "spin_rate" = mean(spin_rate,na.rm = TRUE),
    "SADiff" = mean(SADiff,na.rm = TRUE)
  )



calculate_timstuff <- function(data) {
  data_matrix <- as.matrix(data)
  mod <- xgb.load('TimStuff2.ubj')
  prediction <- predict(mod, data_matrix)
  timstuff <- (100 - (prediction - -0.002620635) / 0.006021368 * 10)
  return(timstuff)
}

ui <- fluidPage(
  theme = shinytheme("flatly"),
  
  titlePanel("TimStuff+ Calculator"),
  
  sidebarLayout(
    sidebarPanel(
      width = 4,
      
      # Add pitcher selection
      selectInput("pitcher_select", "Select Pitcher",
                  choices = c("Custom Input", unique(pitcher_data$`Pitcher Name`))),
      
      # Add pitch type selection - will be dynamically updated based on pitcher
      conditionalPanel(
        condition = "input.pitcher_select != 'Custom Input'",
        selectInput("pitch_select", "Select Pitch Type",
                    choices = NULL)  # Will be updated in server
      ),
      
      # Original inputs wrapped in conditional panel
      conditionalPanel(
        condition = "input.pitcher_select == 'Custom Input'",
        radioButtons("phand", "Hand", choices = c("R", "L"), inline = TRUE),
        numericInput("velo", "Velocity (mph)", value = 95, min = 70, max = 110, step = 1),
        numericInput("ivb", "Induced Vertical Break (in.) (Pitcher's Perspective)", value = 16, min = -30, max = 30, step = 0.1),
        numericInput("hb", "Horizontal Break (in.) (Pitcher's Perspective)", value = 6, min = -25, max = 25, step = 0.1),
        numericInput("spinrate", "Spin Rate (rpm)", value = 2300, min = 1000, max = 3500, step = 10),
        numericInput("ext", "Extension (ft)", value = 6.3, min = 5, max = 8, step = 0.1),
        numericInput("spinaxisdiff", "Spin Axis Difference (°)", value = 0, min = -180, max = 180, step = 1),
        numericInput("x0", "Horizontal Release Point (ft)", value = -1.5, min = -5, max = 5, step = 0.1),
        numericInput("z0", "Vertical Release Point (ft)", value = 5, min = 3, max = 8, step = 0.1)
      ),
      
      selectInput("feature_to_vary", "Select Feature to Vary:",
                  choices = c("Velocity" = "start_speed",
                              "Induced Vertical Break" = "IVB",
                              "Horizontal Break" = "HB",
                              "Spin Rate" = "spin_rate",
                              "Extension" = "EAA",
                              "Spin Axis Difference" = "SADiff",
                              "Horz. Release Point" = "x0"))
    ),
    
    mainPanel(
      width = 8,
      wellPanel(
        h3("Results"),
        verbatimTextOutput("stuff"),
        plotOutput("feature_impact", height = "400px")
      )
    )
  )
)

server <- function(input, output, session) {
  
  # Update pitch selections based on pitcher
  observe({
    if(input$pitcher_select != "Custom Input") {
      pitcher_pitches <- pitcher_data %>%
        filter(`Pitcher Name` == input$pitcher_select) %>%
        pull(pitch_name) %>%
        unique()
      
      updateSelectInput(session, "pitch_select",
                        choices = pitcher_pitches)
    }
  })
  
  # Reactive values for all inputs
  reactive_data <- reactive({
    if(input$pitcher_select == "Custom Input") {
      # Use manual inputs
      data.frame(
        ishandL = ifelse(input$phand == "L", 1, 0),
        start_speed = input$velo,
        IVB = input$ivb,
        HB = input$hb,
        EAA = input$ext / 6.3,
        x0 = input$x0,
        z0 = input$z0,
        spin_rate = input$spinrate,
        SADiff = input$spinaxisdiff
      )
    } else {
      # Use selected pitcher data
      pitch_data <- pitcher_data %>%
        filter(`Pitcher Name` == input$pitcher_select,
               pitch_name == input$pitch_select) %>%
        select(-`Pitcher Name`, -pitch_name)
      
      data.frame(
        ishandL = ifelse(pitch_data$phand == "L", 1, 0),
        start_speed = pitch_data$start_speed,
        IVB = pitch_data$IVB,
        HB = pitch_data$HB,
        EAA = pitch_data$EAA,
        x0 = pitch_data$x0,
        z0 = pitch_data$z0,
        spin_rate = pitch_data$spin_rate,
        SADiff = pitch_data$SADiff
      )
    }
  })
  
  output$stuff <- renderText({
    data <- reactive_data()
    TimStuff <- calculate_timstuff(data)
    paste("TimStuff+:", round(TimStuff, 2), "\nTimStuff+ scale is 100 is Average, 1 SD is 10")
  })
  
  feature_range <- reactive({
    ranges <- list(
      start_speed = c(70, 110),
      IVB = c(-20, 30),
      HB = c(-20, 20),
      spin_rate = c(1000, 3500),
      EAA = c(5/6.3, 8/6.3),
      SADiff = c(-180, 180),
      x0 = c(-4,4)
    )
    ranges[[input$feature_to_vary]]
  })
  
  output$feature_impact <- renderPlot({
    base_data <- reactive_data()
    
    feature_seq <- seq(feature_range()[1], feature_range()[2], length.out = 100)
    
    varied_data <- do.call(rbind, replicate(100, base_data, simplify = FALSE))
    varied_data[[input$feature_to_vary]] <- feature_seq
    timstuff <- calculate_timstuff(varied_data)
    
    plot_data <- data.frame(
      Feature = names(base_data)[which(names(base_data) == input$feature_to_vary)],
      Value = feature_seq,
      TimStuff = timstuff
    )
    
    ggplot(plot_data, aes(x = Value, y = TimStuff)) +
      geom_line(color = "blue", size = 1) +
      geom_point(aes(x = base_data[[input$feature_to_vary]], 
                     y = calculate_timstuff(base_data)),
                 color = "red", size = 3) +
      theme_minimal() +
      ylim(50,150) +
      labs(title = paste("Impact of", input$feature_to_vary, "on TimStuff"),
           x = input$feature_to_vary, y = "TimStuff") +
      theme(text = element_text(size = 14))
  })
}

shinyApp(ui = ui, server = server)