Tech UPTechnologyScience predicts which team will win the World Cup...

Science predicts which team will win the World Cup in Russia

The ball is already rolling through the Russian stadiums, and the surprises of the opening days threaten to destroy the forecasts of coaches, journalists and fans. Neither Germany, nor Brazil, nor Argentina, nor Spain have won on their debut. Of the favorites, only France has gotten off to a good start.

Can science help us know how the tournament will end? Andreas Groll, a statistician at the Technical University of Dortmund (Germany), and his colleagues think so. They have created a method that combines machine learning (the branch of artificial intelligence that allows machines to learn) and statistics to produce a forecast.

His mathematical tool gives Spain as the most likely winner, with a 17.8% chance, but this forecast corresponds to the analysis prior to the round of 16 crosses. In the method created by Groll and his team, the structure of the competition is a key factor. As they say, in the event that Spain and Germany manage to reach the quarterfinals, their chances of winning will be almost equal, although with the Germans somewhat ahead.

How can they make a forecast?

The mixture of machine learning and statistics of these researchers is called random forests . This technique is based on a decision tree, a predictive model that works by calculating all the possible results of the events in each branch of the tree (in this case, the results of all the matches), which gives the most likely outcome of the tournament. .

The advantage of random forests is that they calculate such a large number of probabilities that an average can be drawn that guides with great precision what can happen. In this work, statisticians from the University of Dortmund ran 100,000 simulations of the tournament.

Among the variables that they included in their model, are the position that each World Cup team occupies in the FIFA ranking, the results of their previous World Cups, the characteristics of the teams (for example, the average age of their players, if they have experience in international tournaments like the Champions…) and even the gross domestic product of the participating countries.

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