Predicting Pass Receiver In Football Using Distance Based Features

Yann Dauxais 1 Clément Gautrais 2
2 LACODAM - Large Scale Collaborative Data Mining
Inria Rennes – Bretagne Atlantique , IRISA_D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE
Abstract : This paper presents our approach to the football pass prediction challenge of the Machine Learning and Data Mining for Sport Analytics workshop at ECML/PKDD 2018. Our solution uses distance based features to predict the receiver of a pass. We show that our model is able to improve prediction results obtained on a similar dataset. One particularity of our approach is the use of failed passes to improve the predictions.
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Yann Dauxais, Clément Gautrais. Predicting Pass Receiver In Football Using Distance Based Features. MLSA 2018 - 5th Workshop on Machine Learning and Data Mining for Sports Analytic of ECML/PKDD, Sep 2018, Dublin, Ireland. pp.1-7. ⟨hal-01912616⟩

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