We present a model for predicting the outcome of the 2016 European Football championship in France from June 10 to July 10. It is similar to our model for the 2014 World Cup.
Using historical performance data for each team – most importantly the Elo rating system originally devised to rank chess players – we estimate a set of probabilities that a particular team will reach a particular round, up to and including the championship. We also provide a modal “most likely” case for how the tournament will unfold (although “most likely” does not mean “likely”).
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The model says that France has a 23% probability of winning the trophy, followed by Germany at 20, Spain at 14%, and England at 11%. Although Germany has the highest Elo rating, France is slightly favored because of its home advantage.
After each day of play, we will re-run the model using updated historical performance data in order to generate new probabilities and a new modal forecast.
How much faith should we have in these predictions?
On the plus side, our approach carefully considers the stochastic nature of the tournament using statistical methods. Also, the predictions are not far from bookmakers’ odds. On the minus side, the environment is “stochastic” indeed, i.e., football is quite an unpredictable game!
That charming unpredictability was on full display two years ago, when our model failed to anticipate the elimination of heavyweights Spain and Italy in the group stage and gave Brazil a 48% probability of winning the trophy.
More encouragingly, it identified three of the four semi-finalists before the start of the tournament, and the fully updated version predicted the winner of every match in the knockout stage except for the 7-1 semifinal between Germany and Brazil.
Key Insights of the report - The Econometrician’s Take on Euro 2016
