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

Francisco Corona
Authors registered in the RePEc Author Service: Juan de Dios Tena

DES - Working Papers. Statistics and Econometrics. WS from Universidad Carlos III de Madrid. Departamento de Estadística

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 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.

Keywords: Decisive; game; Entropy; Poisson; model; Kernel; regression; Ordered; probit; model (search for similar items in EconPapers)
Date: 2015-06-01
New Economics Papers: this item is included in nep-for and nep-gth
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Journal Article: On the importance of the probabilistic model in identifying the most decisive games in a tournament (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:cte:wsrepe:21174

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