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arXiv · 2207.13747

Bayesian estimation of in-game home team win probability for Division-I FBS college football

Jason T. Maddox·Ryan Sides·Jane L. Harvill
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Abstract

Maddox, et al. [9, 10] establish Bayesian methods for estimating home-team in-game win probability for college and NBA basketball. This paper introduces a Bayesian approach for estimating in-game home-team win probability for Division-I FBS college (American) football that uses expected number of remaining possessions and expected score as two predictors. Models for estimating these are presented and compared. These, along with other predictors are introduced into two Bayesian approaches for the final estimate of in-game home-team win probability. To illustrate utility, methods are applied to the 2021 Big XII Conference Football Championship game between Baylor and Oklahoma State.

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Jason T. Maddox, Ryan Sides, Jane L. Harvill. 2022-07-27. Bayesian estimation of in-game home team win probability for Division-I FBS college football. https://arxiv.org/abs/2207.13747

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