Publication type: Conference paper
Type of review: Peer review (publication)
Title: Machine learning for position detection in football
Authors: Frey, Martin
Murina, Elvis
Rohrbach, Janick
Walser, Manuel
Haas, Patrick
Dettling, Marcel
et. al: No
DOI: 10.1109/SDS.2019.00009
Proceedings: 2019 6th Swiss Conference on Data Science (SDS)
Pages: 111
Pages to: 112
Conference details: 6th Swiss Conference on Data Science (SDS), Bern, 14. Juni 2019
Issue Date: 14-Jun-2019
Publisher / Ed. Institution: IEEE
ISBN: 978-1-7281-3105-4
Language: English
Subjects: Sport analytics; Soccer; Football; Machine learning; Random forest; Gradient boosting; Deep learning; Convolutional neural network; Computer vision
Subject (DDC): 004: Computer science
Abstract: In recent years, analytics became increasingly important in sports. Newly developed, wearable tracking devices allow football players to log position and motion data during a game. These data can be exploited for enhancing the performance of individual players and entire teams. We present different machine learning approaches to predict spatial football player positions, which serve for advanced tactical analyses.
Fulltext version: Published version
License (according to publishing contract): Licence according to publishing contract
Departement: School of Engineering
Organisational Unit: Institute of Data Analysis and Process Design (IDP)
Published as part of the ZHAW project: Entwicklung von Algorithmen zur Analyse von Fussballspielern und Spielsituationen anhand von Bewegungsdaten
Appears in Collections:Publikationen School of Engineering

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