Abstract

This paper tests whether the differences in rankings between individual players are good predictors for Grand Slam tennis outcomes. We estimate separate probit models for men and women using Grand Slam tennis match data from 2005 to 2008. The explanatory variables are divided into three groups: a player’s past performance, a player’s physical characteristics, and match characteristics. We estimate three alternative probit models. In the first model, all of the explanatory variables are included, whereas in the other two specifications, either the player’s physical characteristics or the player’s past performances are not considered. The accuracies of the different models are evaluated both in-sample and out-of-sample by computing Brier scores and comparing the predicted probabilities with the actual outcomes from the Grand Slam tennis matches from 2005 to 2008 and from the 2009 Australian Open. In addition, using bootstrapping techniques, we also evaluate the out-of-sample Brier scores for the 2005–2008 data.

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