Prediction of major international soccer tournaments based on team-specific regularized Poisson regression: An application to the FIFA World Cup 2014

Groll Andreas (), Schauberger Gunther and Tutz Gerhard
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Groll Andreas: Department of Mathematics, Ludwig-Maximilians-University, Theresienstr. 39, 80333 Munich
Schauberger Gunther: Department of Statistics, Ludwig-Maximilians-University, Munich, Bavaria, Germany
Tutz Gerhard: Department of Statistics, Ludwig-Maximilians-University, Munich, Bavaria, Germany

Journal of Quantitative Analysis in Sports, 2015, vol. 11, issue 2, 97-115

Abstract: In this article an approach for the analysis and prediction of international soccer match results is proposed. It is based on a regularized Poisson regression model that includes various potentially influential covariates describing the national teams’ success in previous FIFA World Cups. Additionally, within the generalized linear model (GLM) framework, also differences of team-specific effects are incorporated. In order to achieve variable selection and shrinkage, we use tailored Lasso approaches. Based on preceding FIFA World Cups, two models for the prediction of the FIFA World Cup 2014 are fitted and investigated. Based on the model estimates, the FIFA World Cup 2014 is simulated repeatedly and winning probabilities are obtained for all teams. Both models favor the actual FIFA World Champion Germany.

Keywords: FIFA World Cup 2014; football; LASSO; prediction; sports tournaments; variable selection (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1515/jqas-2014-0051

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