bayesball

data_work <- function(){
  require(readr)
  require(dplyr)
  require(lubridate)

  sc_2021 <- read_csv("https://raw.githubusercontent.com/bayesball/HomeRuns2021/main/statcast2021.csv")
  sc_2022 <- read_csv("https://raw.githubusercontent.com/bayesball/HomeRuns2021/main/statcast_2022.csv")
  sc_old <- read_csv("https://raw.githubusercontent.com/bayesball/HomeRuns2021/main/SC_BB_mini.csv")

  names(sc_old)[2] <- "Game_Date"

bayesball

# using Statcast data for the 2021 season

# two functions plot_xb_contour_work() and
# plot_woba_contour_work() implement the
# logistic and ordinal fitting algorithms

# ggplot2 code is used to show the barrel
# region over the (launch speed, launch angle)
# space

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# read in three packages

library(readr)
library(dplyr)
library(ggplot2)

# helper ggplot2 function 

helper_ggplot <- function(){
  theme(text=element_text(size=18)) +

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# Load in the necessary packages

library(tidyverse)
library(mgcv)
library(ggrepel)
library(gridExtra)

# Read in the statcast data for the 2018 season

d <- read_csv("../Statcastdata/statcast2018new.csv")

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# load in packages

library(readr)
library(dplyr)
library(lme4)
library(ggplot2)
library(posterior)
library(gridExtra)
library(Lahman)

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# load in packages

library(readr)
library(dplyr)
library(brms)
library(ggplot2)
library(posterior)
library(gridExtra)
library(Lahman)

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parse.retrosheet2.pbp = function(season){
# ADJUSTED FOR MAC -- function will work for WINDOWS and MAC
# download, unzip, append retrosheet data
# assume current directory has a folder download.folder
# download.folder has two subfolders unzipped and zipped
# program cwevent.exe is in unzipped folder (for windows)

download.retrosheet <- function(season){
  # get zip file from retrosheet website
  download.file(

bayesball

# preparation work for FanGraphs leaderboard data

# collected FanGraphs Leaderboard batting data
# choose Multiple Seasons (all), Split Seasons
# minimum 100 PA in each season
# download data and saved as "fgbatting.csv"

library(dplyr)
library(readr)
library(Lahman)

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library(shiny)
library(ggplot2)
library(dplyr)
library(readr)

# read in Retrosheet data for two seasons
d <- read_csv("retro_2seasons_ip.csv")

# main drawing function

bayesball

---
title: "AVG on Ground Balls"
author: "Jim Albert"
date: "11/2/2021"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE,
                      message = FALSE,