3/26/2023 0 Comments Webmailer uni dortmundCombined with the extreme climatic conditions, this also increases the risk of injuries,” explains Achim Zeileis. This gives the national teams less time to prepare and the players less time to recover before and after the World Cup. The 2022 World Cup is interesting for the researchers from a scientific perspective because of the unusual date – the tournament had to be postponed to the winter months because of the extremely high temperatures in Qatar in the summer: “In addition to the widely discussed ethical problems of this World Cup, this also raises very critical sportive questions: In the winter months, all the major football leagues in Europe and South America have to interrupt their usual match schedule to accommodate the tournament. This year Zeileis’ model will be used for the second time after the EURO 2021 as part of a more comprehensive combined model developed by the teams around Andreas Groll (TU Dortmund), Gunther Schauberger (TU Munich) and Christophe Ley (University of Luxembourg), which surpassed the forecasting quality of the betting providers at the 2018 World Cup. So far, however, the predictions have been quite successful: Achim Zeileis' Innsbruck model, which is based on adjusted bookmakers odds, was able to correctly predict the EURO final in 2008, as well as the World and European champion Spain in 20. We provide probabilities, not certainties, and a probability of winning of 15 per cent also implies a probability of 85 per cent of not winning,” explains Andreas Groll. “It is in the very nature of forecasts that they can also be incorrect – otherwise football tournaments would be very boring. Of course, the tournament is far from being predetermined – this is reflected by the comparatively low winning probability of the top teams. ![]() This time, the favourite is Brazil with a probability of winning of 15 percent, followed by Argentina (11.2 per cent), the Netherlands (9.7 per cent), Germany (9.2 per cent) and France (9.1 per cent) – the full forecast can be found here. This results in probabilities for all teams advancing to the different tournament rounds and ultimately winning the Championship. With the predicted values from the researchers' model, the entire World Cup was simulated 100,000 times: match by match, following the tournament draw and all FIFA rules. Nevertheless, for scientific reasons, we have decided to use our machine learning approach, which we have used successfully at previous tournaments, to make probabilistic forecasts,” says Achim Zeileis from the Department of Statistics of the University of Innsbruck. “This time, the World Cup is overshadowed by many ethical and sportive problems that we cannot ignore. Their forecast combines several statistical models for the teams' playing strengths with information about the team structure (such as market value or number of Champions League players) as well as socio-economic factors of the country of origin (population or gross domestic product). This is what an international team of researchers consisting of Andreas Groll and Neele Hormann (both TU Dortmund), Gunther Schauberger (TU Munich), Christophe Ley (University of Luxembourg), Hans Van Eetvelde (University of Ghent) and Achim Zeileis (University of Innsbruck) has shown with the help of machine learning. The favourite this time is Brazil with a probability of winning of 15 percent. Next Sunday, 20 November, the men's football teams start the FIFA World Cup in Qatar. Open Access publishing of Master and PhD Thesis. ![]()
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