Nowadays many approaches that analyze and predict the results of football matches are based on bookmakers` ratings. It is commonly accepted that the models used by the bookmakers contain a lot of expertise as the bookmakers` profits and losses depend on the performance of their models. One objective of this article is to analyze the role of bookmakers` odds together with many additional, potentially influental covariates with respect to a national team`s success at European football championships and especially to detect covariates, which are able to explain parts of the information covered by the odds. Therefore a pairwise Poisson model for the number of goals scored by national teams competing in European football championship matches is used. Moreover, the generalized linear mixed model (GLMM) approach, which is a widely used tool for modeling cluster data, allows to incorporate team-specific random effects. Two different approaches to the fitting of GLMMs incorporating variable selection are used, subset selection as well as a Lasso-type technique, including an L1-penalty term that enforces variable selection and shrinkage simultaneously. Based on the two preceeding European football championships a sparse model is obtained that is used to predict all matches of the current tournament resulting in a possible course of the European football championship (EURO) 2012.
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