Simulating a basketball match with a homogeneous Markov model and forecasting the outcome

Erik Štrumbelj and Petar Vračar

International Journal of Forecasting, 2012, vol. 28, issue 2, 532-542

Abstract: We used a possession-based Markov model to model the progression of a basketball match. The model’s transition matrix was estimated directly from NBA play-by-play data and indirectly from the teams’ summary statistics. We evaluated both this approach and other commonly used forecasting approaches: logit regression of the outcome, a latent strength rating method, and bookmaker odds. We found that the Markov model approach is appropriate for modelling a basketball match and produces forecasts of a quality comparable to that of other statistical approaches, while giving more insight into basketball. Consistent with previous studies, bookmaker odds were the best probabilistic forecasts.

Keywords: Sports forecasting; Probability forecasting; Monte Carlo; Simulation; National Basketball Association (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:28:y:2012:i:2:p:532-542

DOI: 10.1016/j.ijforecast.2011.01.004

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