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Journal of Quantitative Analysis in Sports

An official journal of the American Statistical Association

Editor-in-Chief: Steve Rigdon, PhD

CiteScore 2017: 0.67

SCImago Journal Rank (SJR) 2017: 0.290
Source Normalized Impact per Paper (SNIP) 2017: 0.853

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Volume 11, Issue 2


Volume 1 (2005)

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

Andreas Groll / Gunther Schauberger / Gerhard Tutz
Published Online: 2015-05-16 | DOI: https://doi.org/10.1515/jqas-2014-0051


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


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About the article

Corresponding author: Andreas Groll, Department of Mathematics, Ludwig-Maximilians-University, Theresienstr. 39, 80333 Munich, e-mail:

Published Online: 2015-05-16

Published in Print: 2015-06-01

Citation Information: Journal of Quantitative Analysis in Sports, Volume 11, Issue 2, Pages 97–115, ISSN (Online) 1559-0410, ISSN (Print) 2194-6388, DOI: https://doi.org/10.1515/jqas-2014-0051.

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