On the importance of the probabilistic model in identifying the most decisive games in a tournament

Francisco Corona 1 , Juan de Dios Tena Horrillo 2  and Michael Peter Wiper 1
  • 1 Universidad Carlos III de Madrid, Statistics, Getafe, Madrid, Spain
  • 2 University of Liverpool, Management School, Chatham Street, Liverpool L19 7ZH, UK, Tel.: + 44(0)1514752486
Francisco Corona, Juan de Dios Tena Horrillo and Michael Peter Wiper

Abstract

Identifying the decisive matches in international football tournaments is of great relevance for a variety of decision makers such as organizers, team coaches and/or media managers. This paper addresses this issue by analyzing the role of the statistical approach used to estimate the outcome of the game on the identification of decisive matches on international tournaments for national football teams. We extend the measure of decisiveness proposed by Geenens (2014) in order to allow us to predict or evaluate the decisive matches before, during and after a particular game on the tournament. Using information from the 2014 FIFA World Cup, our results suggest that Poisson and kernel regressions significantly outperform the forecasts of ordered probit models. Moreover, we find that although the identification of the most decisive matches is independent of the model considered, the identification of other key matches is model dependent. We also apply this methodology to identify the favorite teams and to predict the most decisive matches in 2015 Copa America before the start of the competition. Furthermore, we compare our forecast approach with respect to the original measure during the knockout stage.

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JQAS, an official journal of the American Statistical Association, publishes research on the quantitative aspects of professional and collegiate sports. Articles deal with subjects as measurements of player performance, tournament structure, and the frequency and occurrence of records. Additionally, the journal serves as an outlet for professionals in the sports world to raise issues and ask questions that relate to quantitative sports analysis.

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