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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

Publikation: Bücher und Anthologien › Konferenzbände und -dokumentationen › Forschung

Authors

  • Ulf Brefeld (Herausgeber*in)
  • Jesse Davis (Herausgeber*in)
  • Jan van Haaren (Herausgeber*in)
  • Albrecht Zimmermann (Herausgeber*in)
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 Learning and Principles and Practice of Knowledge Discovery (ECML
PKDD 2020).
Sports Analytics has been a steadily growing and rapidly evolving area over the last decade, both in US professional sports leagues and in European football leagues. The recent implementation of strict financial fair-play regulations in European football will definitely increase the importance of Sports Analytics in the coming years. In addition, there is the popularity of sports betting. The developed techniques are being used for decision support in all aspects of professional sports ...
OriginalspracheEnglisch
ErscheinungsortCham
VerlagSpringer International Publishing
Anzahl der Seiten146
ISBN (Print)978-3-030-64911-1
ISBN (elektronisch)978-3-030-64912-8
DOIs
PublikationsstatusErschienen - 2020
Veranstaltung7th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2020, colocated with ECML/PKDD 2020 - online , Ghent, Belgien
Dauer: 14.09.2020 → 18.09.2020
Konferenznummer: 7

Publikationsreihe

NameCommunications in Computer and Information Science
VerlagSpringer Nature
Band1324
ISSN (Print)1865-0929
ISSN (elektronisch)1865-0937

Weitere Publikationen dieser Person(en)

Interactive sequential generative models for team sports

Fassmeyer, D., Cordes, M. & Brefeld, U., 02.2025, in: Machine Learning. 114, 2, 15 S., 38.

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Joint Item Response Models for Manual and Automatic Scores on Open-Ended Test Items

Bengs, D., Brefeld, U., Kroehne, U. & Zehner, F., 2025, (Angenommen/Im Druck) in: Psychometrika.

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Machine Learning and Data Mining for Sports Analytics: 11th International Workshop, MLSA 2024, Vilnius, Lithuania, September 9, 2024, Revised Selected Papers

Brefeld, U. (Herausgeber*in), Davis, J. (Herausgeber*in), Van Haaren, J. (Herausgeber*in) & Zimmermann, A. (Herausgeber*in), 2025, Cham: Springer Verlag. 119 S. (Communications in Computer and Information Science; Band 2460)

Publikation: Bücher und Anthologien › Konferenzbände und -dokumentationen › Forschung

Masked autoencoder for multiagent trajectories

Rudolph, Y. & Brefeld, U., 02.2025, in: Machine Learning. 114, 2, 18 S., 44.

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The promise and challenges of computer mouse trajectories in DMHIs – A feasibility study on pre-treatment dropout predictions

Zantvoort, K., Matthiesen, J., Bjurner, P., Bendix, M., Brefeld, U., Funk, B. & Kaldo, V., 06.2025, in: Internet Interventions. 40, 7 S., 100828.

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