bayesball

# load in Retrosheet pbp data frames
# for seasons 2011 through 2021

library(Lahman)
library(dplyr)
library(ggplot2)

# get Mike Trout's retro id from the People
# data frame in Lahman package

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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"

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# 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 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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# 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

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---
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,

bayesball

perfect <- function(d, n_innings){
  # inputs are Retrosheet play-by-play data frame d and
  # number of innings n_innings
  # output is a data frame containing all Perfect-k
  # games for that season
  
  require(dplyr)
  
  d %>% 
    mutate(PIT_ID = as.character(PIT_ID),