Bayesian hierarchical model for the prediction of football results

Gianluca Baio and Marta Blangiardo

Journal of Applied Statistics, 2010, vol. 37, issue 2, 253-264

Abstract: The problem of modelling football data has become increasingly popular in the last few years and many different models have been proposed with the aim of estimating the characteristics that bring a team to lose or win a game, or to predict the score of a particular match. We propose a Bayesian hierarchical model to fulfil both these aims and test its predictive strength based on data about the Italian Serie A 1991-1992 championship. To overcome the issue of overshrinkage produced by the Bayesian hierarchical model, we specify a more complex mixture model that results in a better fit to the observed data. We test its performance using an example of the Italian Serie A 2007-2008 championship.

Keywords: Bayesian hierarchical models; overshrinkage; football data; bivariate Poisson distribution; Poisson-log normal model (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (18)

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DOI: 10.1080/02664760802684177

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