A generative Markov model for bowling scores

VanDerwerken Douglas () and Kenter Franklin
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VanDerwerken Douglas: Department of Mathematics, US Naval Academy, Annapolis, MD 21402-5000, USA
Kenter Franklin: Department of Mathematics, US Naval Academy, Annapolis, MD 21402-5000, USA

Journal of Quantitative Analysis in Sports, 2018, vol. 14, issue 4, 213-226

Abstract: We create a data-driven Markov model for generating 10-pin bowling scores from the Professional Bowlers Association. The model incorporates insights from the hot hand literature and makes use of Bayesian shrinkage. For realistic sample sizes, the proposed approach is superior to modeling via the empirical distribution. Investigation of player-specific model components allows for a richer comparison of players than is possible using raw game scores alone. An additional feature of the model is that it can be used for in-game prediction.

Keywords: Bayesian hierarchical model; bowling; hot hand; Markov model (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1515/jqas-2017-0081

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