#### Introduction

Here is a brief illustration of using the WinProbability package just created on my Github site.

Install the package from Github:

library(devtools)
install_github("bayesball/WinProbability")

library(WinProbability)

#### Setup

I’m in a folder where I have a raw Retrosheet play-by-play datafile. Note that the file must be of the form allYEAR.csv where YEAR is the value input in the function.

dir()
## [1] "all2018.csv"          "roster2018.csv"       "WinProbabilities.Rmd"

#### Compute runs expectancies

The compute.runs.expectancy function:

• Reads in the raw dataset
• Computes the run expectancies and adds these to the datafile
d2018 <- compute.runs.expectancy(2018)

#### Compute win probabilities

The compute.win.probs function will

• Compute the win probabilities for all plays.
• The input is the Retrosheet play-by-play data frame with run expectancy values included
d2018 <- compute.win.probs(d2018)

#### Graph the win probabilities for a game

The graph.game function will plot the win probabilities for all plays in a specific game.

plays <- graph.game(d2018, "SLN201805190")