runexp-package

Package runexp

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. package

Important Functions

• chain: calculates run expectancy using discrete Markov chains
• sim: estimates run expectancy using multinomial simulation
• plot.chain: S3 method for plotting chain output objects
• prob_calc: calculates player probabilities from commonly available stats
• scrape: scrapes player statistics from a given URL

Data Files

• wku_stats: player statistics for the 2013 Western Kentucky University softball team
• wku_probs: calculated player probabilities for the 2013 Western Kentucky University softball team

Examples

# see "?scrape", "?prob_calc", "?chain" and "?sim" for relevant examples

References

B. Bukiet, E. R. Harold, and J. L. Palacios, “A Markov Chain Approach to Baseball,” Operations Research 45, 14–23 (1997).

Author(s)

Annie Sauer anniees@vt.edu

Sierra Merkes smerkes@vt.edu