A Markov chain model for forecasting results of mixed martial arts contests

https://doi.org/10.1016/j.ijforecast.2022.01.007Get rights and content
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Abstract

In this paper, we present a new methodology for forecasting the results of mixed martial arts contests. Our approach utilises data scraped from freely available websites to estimate fighters’ skills in various key aspects of the sport. With these skill estimates, we simulate the contest as an actual fight using Markov chains, rather than predicting a binary outcome. We compare the model’s accuracy to that of the bookmakers using their historical odds and show that the model can be used as the basis of a successful betting strategy.

Keywords

Bayesian methods
Gambling
Markov chain
Mixed martial arts
Probability forecasting
Sports betting
Sports forecasting
Simulation

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