A mixture-of-modelers approach to forecasting NCAA tournament outcomes
Predicting the outcome of a single sporting event is difficult; predicting all of the outcomes for an entire tournament is a monumental challenge. Despite the difficulties, millions of people compete each year to forecast the outcome of the NCAA men`s basketball tournament, which spans 63 games over 3 weeks. Statistical prediction of game outcomes involves a multitude of possible covariates and information sources, large performance variations from game to game, and a scarcity of detailed historical data. In this paper, we present the results of a team of modelers working together to forecast the 2014 NCAA men`s basketball tournament. We present not only the methods and data used, but also several novel ideas for post-processing statistical forecasts and decontaminating data sources. In particular, we highlight the difficulties in using publicly available data and suggest techniques for improving their relevance.
© Copyright 2015 Journal of Quantitative Analysis in Sports. de Gruyter. Kaikki oikeudet pidätetään.
Aiheet: | koripallo miespuolinen huippu-urheilu juniori huippu-urheilu USA Kanada kilpailu suorituskyky ennuste tilastot simulointi |
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Aihealueet: | tekniset ja luonnontieteet junioriurheilu urheilukilpailut |
DOI: | 10.1515/jqas-2014-0056 |
Julkaisussa: | Journal of Quantitative Analysis in Sports |
Julkaistu: |
2015
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Vuosikerta: | 11 |
Numero: | 1 |
Sivuja: | 13-27 |
Julkaisutyypit: | artikkeli |
Kieli: | englanti (kieli) |
Taso: | kehittynyt |