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pro vyhledávání: '"Hvattum, Lars"'
Autor:
Groll, Andreas, Hvattum, Lars M., Ley, Christophe, Sternemann, Jonas, Schauberger, Gunther, Zeileis, Achim
In this work, three fundamentally different machine learning models are combined to create a new, joint model for forecasting the UEFA EURO 2024. Therefore, a generalized linear model, a random forest model, and a extreme gradient boosting model are
Externí odkaz:
http://arxiv.org/abs/2410.09068
Autor:
Groll, Andreas, Hvattum, Lars Magnus, Ley, Christophe, Popp, Franziska, Schauberger, Gunther, Van Eetvelde, Hans, Zeileis, Achim
Three state-of-the-art statistical ranking methods for forecasting football matches are combined with several other predictors in a hybrid machine learning model. Namely an ability estimate for every team based on historic matches; an ability estimat
Externí odkaz:
http://arxiv.org/abs/2106.05799
The COVID-19 pandemic has left its marks in the sports world, forcing the full-stop of all sports-related activities in the first half of 2020. Football leagues were suddenly stopped and each country was hesitating between a relaunch of the competiti
Externí odkaz:
http://arxiv.org/abs/2101.10597
Publikováno v:
In EURO Journal on Transportation and Logistics 2024 13
Akademický článek
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Publikováno v:
In Maritime Transport Research December 2023 5
Composing a team of professional players is among the most crucial decisions in association football. Nevertheless, transfer market decisions are often based on myopic objectives and are questionable from a financial point of view. This paper introdu
Externí odkaz:
http://arxiv.org/abs/1911.04689
Publikováno v:
In Computers and Operations Research July 2023 155