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# loads in data frame d2015
# Retrosheet play-by-play data for 2015 season

load(url("http://www-math.bgsu.edu/~albert/retrosheet/pbp.2015.Rdata"))

# function will extract 1/0 data for a specific batter and a particular outcome

get_streak_data <- function(retrodata, batter, outcome){
  require(dplyr)
  require(Lahman)

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# Interesting table that presents the number of 2016 MLB players 
# from each of 50 US States.

# http://www.baseball-almanac.com/players/birthplace.php?y=2016

# Interested in mapping the data

# Use XML package to read in data

library(XML)

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get_data <- function(pitcher){
    require(Lahman)
    require(dplyr)
    get.birthyear <- function(player.id){
       playerline <- filter(Master, playerID == player.id)
       birthyear <- playerline$birthYear
       birthmonth <- playerline$birthMonth
       ifelse(birthmonth >= 7, birthyear + 1, birthyear)
     }
    names <- unlist(strsplit(pitcher, " "))

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compare_obp_trajectories <- function(players){
  require(Lahman)
  require(dplyr)
  require(LearnBayes)
  require(ggplot2)
  library(ggthemes)
  
  get_data <- function(batter, playerid=FALSE){
    get.birthyear <- function(player.id){
      playerline <- filter(Master, playerID == player.id)

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---
title: "Adjusting SLG"
author: "Jim Albert"
date: "December 17, 2016"
output:
  html_document: default
  html_notebook: default
---

```{r global_options, include=FALSE}

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# stolen base study
# look at SB and SB Attempts

# downloading Retrosheet data and computing runs values
# using two helper functions

# see https://baseballwithr.wordpress.com/2014/02/10/downloading-retrosheet-data-and-runs-expectancy/
# for specific instructions on downloading Retrosheet data

library(devtools)

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# game log data available at
# http://www.retrosheet.org/gamelogs/index.html
# csv file with headers available at
# https://github.com/maxtoki/baseball_R/blob/master/data/game_log_header.csv

# my gamelog data for the 2016 season stored in 
# data frame d

# this is some theme information that I'll using in 
# my ggplot2 plots

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platoon_dist2 <- function(pbpdata, season, data=FALSE){
  require(dplyr)
  require(ggplot2)
  require(Lahman)

  d_PA <- filter(pbpdata, BAT_EVENT_FL==TRUE)
  
  S_left <- summarize(group_by(filter(d_PA,
                              BAT_HAND_CD=="L"), BAT_ID),
                      Opp=sum(PIT_HAND_CD=="R"),

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---
title: "Is David Ortiz Clutch?"
output:
  html_document: default
  html_notebook: default
---

Read in Retrosheet data for the 2000 through the 2013 seasons.
Also read in the compute.runs function.

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model_data_simulation <- function(P_vector,
                                  mystat=sum,
                                  N=100,
                                  N_sim=10000){
  require(ggplot2)
  TH <- theme(
    plot.title = element_text(
      colour = "red",
      size = 14,
      hjust = 0.5,