Improved component predictions of batting and pitching measures

Albert Jim ()
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Albert Jim: Department of Mathematics and Statistics, Bowling Green State University, Bowling Green, OH, 43403, USA

Journal of Quantitative Analysis in Sports, 2016, vol. 12, issue 2, 73-85

Abstract: Standard measures of batting performance such as batting average and on-base percentage can be decomposed into component rates such as strikeout rates and home run rates. The likelihood of hitting data for a group of players can be expressed as a product of likelihoods of the component probabilities and this motivates the use of Bayesian random effects models to estimate the groups of component rates. By combining the separate component rates, the aggregate predictions of batting performance for subsequent seasons improve upon standard shrinkage methods. This “separate and aggregate” approach is also illustrated for estimating on-base probabilities and fielding independent pitching (FIP) abilities of pitchers.

Keywords: Bayesian analysis; beta-binomial model; exchangeable model; shrinkage (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (2)

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DOI: 10.1515/jqas-2015-0063

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