Using Markov Chains in Predictive Modeling of Sports

Amanda Harsy (), Alyssa Hoofnagle (), Megan Vesta (), Harvey Campos-Chavez () and Will deBolt ()
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Amanda Harsy: Lewis University
Alyssa Hoofnagle: Wittenberg University
Megan Vesta: Lewis University
Harvey Campos-Chavez: Lewis University
Will deBolt: Lewis University

A chapter in Handbook of Visual, Experimental and Computational Mathematics, 2026, pp 1169-1197 from Springer

Abstract: Abstract Ranking sports teams or players can be a challenging task, and using statistics such as straight win percentage or player averages may be misleading at times. Among many mathematically inspired sports ranking systems, linear algebra methods are among the most elegant and simple. This chapter highlights several research projects which apply Markov chains in a variety of ways to predict the future results of MLB, NCAA baseball, and NHL hockey.

Keywords: Markov chains; Modeling; Sports analytics; Baseball; Hockey (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-032-16368-4_23

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DOI: 10.1007/978-3-032-16368-4_23

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