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
