Predictive Modeling and Analysis of Hockey Using Markov Chains
Authors:
Amanda Harsy
,
Harvey Campos-Chavez
,
Will deBolt
,
Miles Mena
,
Jacob Prince
,
Alia Alramahi
,
Robert Dudzinski
,
Soren Thrawl
,
Anthony DeLegge
Abstract
Predicting the outcome of a hockey game can be challenging due to the fast paced and physical nature of the sport. In this paper, we share two versions of a continuous-time Markov process-based model that takes the certain state the home team is in at any point in the game and gives a winning probability statistic for that time. This state is based on the home team’s shot and goal differential relative to the opposing team and approximates the probability that the home team would win depending on the state they are currently in at a given time in the game.
Keywords: sports analytics, Markov Chains, hockey, predictive modeling
How to Cite:
Harsy, A., Campos-Chavez, H., deBolt, W., Mena, M., Prince, J., Alramahi, A., Dudzinski, R., Thrawl, S. & DeLegge, A., (2023) “Predictive Modeling and Analysis of Hockey Using Markov Chains”, Maths and Sports 4(1).
Rights: Mathematics and Sports
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