Combining historical data and bookmakers' odds in modelling football scores. (December 2018)

• Record Type: Journal Article
• Authors: Egidi, Leonardo; Pauli, Francesco; Torelli, Nicola
• Other Names: Groll Andreas guest-editor.; Manisera Marica guest-editor.; Schauberger Gunther guest-editor.; Zuccolotto Paola guest-editor.
• Is Part Of: Statistical modelling. Volume 18:Number 5/6(2018)
• Page Start: 436
• Page End: 459
• Publication Date: 2018-12
• Subjects: Bayesian Poisson model -- betting odd -- football prediction -- historical results -- model checks; Linear models (Statistics) -- Periodicals; Mathematical models -- Periodicals; Modèles linéaires (Statistique) -- Périodiques; Modèles mathématiques -- Périodiques; Modèle statistique; Modèle linéaire; Modélisation statistique; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 519.5011
• DOI: 10.1177/1471082X18798414
• Languages: English
• ISSNs: 1471-082X

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.