Learning predictive models for match outcomes in US sports, and using them to bet - Archive ouverte HAL
Communication Dans Un Congrès Année : 2024

Learning predictive models for match outcomes in US sports, and using them to bet

Résumé

Evaluating the accuracies of models for match outcome predictions is nice and well but in the end the real proof is in the money to be made by betting. To evaluate the question whether the models developed by us could be used easily to make money via sports betting, we evaluate three cases: NCAAB post-season, NBA season, and NFL season, and find that it is possible yet not without its pitfalls. In particular, we illustrate that high accuracy does not automatically equal high payout, by looking at the type of match-ups that are predicted correctly by different models. We then put our results to practical use by betting on matches, and find that some observed pitfalls are harder to avoid than others.

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Dates et versions

hal-04711998 , version 1 (27-09-2024)

Identifiants

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Albrecht Zimmermann. Learning predictive models for match outcomes in US sports, and using them to bet. Sports Analytics. ISACE 2024., Jul 2024, Paris, France. pp.313-327, ⟨10.1007/978-3-031-69073-0_27⟩. ⟨hal-04711998⟩
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