Softball Run Expectancy using Markov Chains and Simulation
Softball run expectancy using discrete Markov chains
Plots an object of S3 class "chain
"
Calculates player probabilities given players' game statistics.
Package runexp
Softball Webscraper
Softball run expectancy using multinomial random trial simulation
Player statistics and probabilities for WKU softball
Implements two methods of estimating runs scored in a softball scenario: (1) theoretical expectation using discrete Markov chains and (2) empirical distribution using multinomial random simulation. Scores are based on player-specific input probabilities (out, single, double, triple, walk, and homerun). Optional inputs include probability of attempting a steal, probability of succeeding in an attempted steal, and an indicator of whether a player is "fast" (e.g. the player could stretch home). These probabilities may be calculated from common player statistics that are publicly available on team's webpages. Scores are evaluated based on a nine-player lineup and may be used to compare lineups, evaluate base scenarios, and compare the offensive potential of individual players. Manuscript forthcoming. See Bukiet & Harold (1997) <doi:10.1287/opre.45.1.14> for implementation of discrete Markov chains.