A generative model for predicting outcomes in college basketball

(Ein generatives Modell zur Ergebnisprognose im Collegebasketball)

We show that a classical model for soccer can also provide competitive results in predicting basketball outcomes. We modify the classical model in two ways in order to capture both the specific behavior of each National collegiate athletic association (NCAA) conference and different strategies of teams and conferences. Through simulated bets on six online betting houses, we show that this extension leads to better predictive performance in terms of profit we make. We compare our estimates with the probabilities predicted by the winner of the recent Kaggle competition on the 2014 NCAA tournament, and conclude that our model tends to provide results that differ more from the implicit probabilities of the betting houses and, therefore, has the potential to provide higher benefits.
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Schlagworte: Basketball männlich Leistungssport Nachwuchsleistungssport USA Kanada Wettkampf Leistung Prognose Statistik Simulation
Notationen: Naturwissenschaften und Technik Nachwuchssport Spielsportarten
DOI: 10.1515/jqas-2014-0055
Veröffentlicht in: Journal of Quantitative Analysis in Sports
Veröffentlicht: 2015
Jahrgang: 11
Heft: 1
Seiten: 39-52
Dokumentenarten: Artikel
Sprache: Englisch
Level: hoch