Low-Cost Optical Tracking of Soccer Players
Sports analytics are on the rise in European football, however, due to the high cost so far only the top tier leagues and championships have had the privilege of collecting high precision data to build upon. We believe that this opportunity should be avai
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chine Learning and Data Mining for Sports Analytics 7th International Workshop, MLSA 2020 Co-located with ECML/PKDD 2020 Ghent, Belgium, September 14–18, 2020, Proceedings
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Communications in Computer and Information Science Editorial Board Members Joaquim Filipe Polytechnic Institute of Setúbal, Setúbal, Portugal Ashish Ghosh Indian Statistical Institute, Kolkata, India Raquel Oliveira Prates Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil Lizhu Zhou Tsinghua University, Beijing, China
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More information about this series at http://www.springer.com/series/7899
Ulf Brefeld Jesse Davis Jan Van Haaren Albrecht Zimmermann (Eds.) •
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Machine Learning and Data Mining for Sports Analytics 7th International Workshop, MLSA 2020 Co-located with ECML/PKDD 2020 Ghent, Belgium, September 14–18, 2020 Proceedings
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Editors Ulf Brefeld Leuphana University of Lüneburg Lüneburg, Germany
Jesse Davis Katholieke Universiteit Leuven Leuven, Belgium
Jan Van Haaren SciSports Amersfoort, The Netherlands
Albrecht Zimmermann Université de Caen Normandie Caen, France
ISSN 1865-0929 ISSN 1865-0937 (electronic) Communications in Computer and Information Science ISBN 978-3-030-64911-1 ISBN 978-3-030-64912-8 (eBook) https://doi.org/10.1007/978-3-030-64912-8 © Springer Nature Switzerland AG 2020 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Preface
The Machine Learning and Data Mining for Sports Analytics (MLSA) workshop aims to bring people from outside of the Machine Learning and Data Mining community into contact with researchers from that community who are working on Sports Analytics. The 7th edition of the workshop was co-located with the European Conference on Machine Learn
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