Statistical Modelling 18 (5-6) (2018), 436–459
Combining historical data and bookmakers’ odds in modelling football scores
Leonardo Egidi
Dipartimento di Scienze Economiche,
Aziendali,
Matematiche e Statistiche ‘Bruno de Finetti’,
Università degli Studi di Trieste,
Via Tigor, Trieste,
Italy.
e-mail: legidi@units.it
Francesco Pauli
Dipartimento di Scienze Economiche,
Aziendali,
Matematiche e Statistiche ‘Bruno de Finetti’,
Università degli Studi di Trieste,
Via Tigor, Trieste,
Italy.
Nicola Torelli
Dipartimento di Scienze Economiche,
Aziendali,
Matematiche e Statistiche ‘Bruno de Finetti’,
Università degli Studi di Trieste,
Via Tigor, Trieste,
Italy.
Abstract:
Modelling football outcomes has gained increasing attention, in large part due to the potential for making substantial profits. Despite the strong connection existing between football models and the bookmakers’ betting odds, no authors have used the latter for improving the fit and the predictive accuracy of these models. We have developed a hierarchical Bayesian Poisson model in which the scoring rates of the teams are convex combinations of parameters estimated from historical data and the additional source of the betting odds. We apply our analysis to a nine-year dataset of the most popular European leagues in order to predict match outcomes for their tenth seasons. In this article, we provide numerical and graphical checks for our model.
Keywords:
Bayesian Poisson model; betting odd; football prediction; historical results; model checks.
Downloads:
Example data and code in
zipped archive.
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