Predicting the future performance of soccer players

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

Authors

We propose a multitask, regression-based approach for predicting future performances of soccer players. The multitask approach allows us to simultaneously learn individual player models as offsets to a general model. We devise multitask variants of ridge regression and ε-support vector regression. Together with a hashed joint feature space, the generalized models can be optimized using standard techniques. Relevant features for the prediction are identified by a modified recursive feature elimination strategy. We report on extensive empirical results using real data from the German Bundesliga.

OriginalspracheEnglisch
ZeitschriftStatistical Analysis and Data Mining
Jahrgang9
Ausgabenummer5
Seiten (von - bis)373-382
Anzahl der Seiten10
ISSN1932-1864
DOIs
PublikationsstatusErschienen - 01.10.2016

DOI

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Forschende

  1. Tina Kaiser

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