Abstract
In this chapter we propose a simulation-based method for predicting football match outcomes. We adopt a Bayesian perspective, modeling the number of goals of two opposing teams as a Poisson distribution whose mean is proportional to the relative technical level of opponents. Fédération Internationale de Football Association (FIFA) ratings were taken as the measure of technical level of teams saw well as experts’ opinions on the scores of the matches were taken in account to construct the prior distributions of the parameters. Tournament simulations were performed in order to estimate probabilities of winning the tournament assuming different values for the weight attached to the experts’ information and different choices for the sequence of weights attached to the previous observed matches. The methodology is illustrated on the 2010 Football Word Cup.
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The research is partially supported by the Brazilian Government Agencies: CNPq, CAPES, and FAPESP.
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Louzada, F., Suzuki, A., Salasar, L., Ara, A., Leite, J. (2015). A Bayesian Approach to Predicting Football Match Outcomes Considering Time Effect Weight. In: Polpo, A., Louzada, F., Rifo, L., Stern, J., Lauretto, M. (eds) Interdisciplinary Bayesian Statistics. Springer Proceedings in Mathematics & Statistics, vol 118. Springer, Cham. https://doi.org/10.1007/978-3-319-12454-4_12
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DOI: https://doi.org/10.1007/978-3-319-12454-4_12
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