Produção Nacional
Revisado por pares
Predicting football scores via Poisson regression model: applications to the National Football League
2016; Korean Statistical Society; Volume: 23; Issue: 4 Linguagem: Inglês
10.5351/csam.2016.23.4.297
ISSN2383-4757
AutoresErlandson Ferreira Saraiva, Adriano K. Suzuki, Ciro Alexandre Olivieri Filho, Francisco Louzada,
Tópico(s)Forest ecology and management
ResumoFootball match predictions are of great interest to fans and sports press. In the last few years it has been the focus of several studies. In this paper, we propose the Poisson regression model in order to football match outcomes. We applied the proposed methodology to two national competitions: the 2012–2013 English Premier League and the 2015 Brazilian Football League. The number of goals scored by each team in a match is assumed to follow Poisson distribution, whose average reflects the strength of the attack, defense and the home team advantage. Inferences about all unknown quantities involved are made using a Bayesian approach. We calculate the probabilities of win, draw and loss for each match using a simulation procedure. Besides, also using simulation, the probability of a team qualifying for continental tournaments, being crowned champion or relegated to the second division is obtained.
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