Machine Learning and Data Mining for Sports Analytics: 11th International Workshop, MLSA 2024, Vilnius, Lithuania, September 9, 2024, Revised Selected Papers
Publikation: Bücher und Anthologien › Konferenzbände und -dokumentationen › Forschung
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Cham: Springer Verlag, 2025. 119 S. (Communications in Computer and Information Science; Band 2460).
Publikation: Bücher und Anthologien › Konferenzbände und -dokumentationen › Forschung
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RIS
TY - BOOK
T1 - Machine Learning and Data Mining for Sports Analytics
T2 - 11th International Workshop on Machine Learning and Data Mining for Sports Analytics - MLSA 2024
A2 - Brefeld, Ulf
A2 - Davis, Jesse
A2 - Van Haaren, Jan
A2 - Zimmermann, Albrecht
N1 - Conference code: 11
PY - 2025
Y1 - 2025
N2 - The proceedings contain 9 papers. The special focus in this conference is on Machine Learning and Data Mining for Sports Analytics. The topics include: Large Language Models on Race Commentary: Towards Granular Data in Cycling Analytics; GraphEIV: A Framework for Estimating the Expected Immediate Value in Basketball Using Graph Neural Networks; mathematical Models for Off-Ball Scoring Prediction in Basketball; an Analysis of the Influence of Game Context on Team Playing Style; Augmented Intelligence for FIFA Predictions; transformer-Based Framework for Versatile Analysis of Events Data in Soccer; Automated Detection of Shot Events in Game Phases Using GNSS Data from a Single Team.
AB - The proceedings contain 9 papers. The special focus in this conference is on Machine Learning and Data Mining for Sports Analytics. The topics include: Large Language Models on Race Commentary: Towards Granular Data in Cycling Analytics; GraphEIV: A Framework for Estimating the Expected Immediate Value in Basketball Using Graph Neural Networks; mathematical Models for Off-Ball Scoring Prediction in Basketball; an Analysis of the Influence of Game Context on Team Playing Style; Augmented Intelligence for FIFA Predictions; transformer-Based Framework for Versatile Analysis of Events Data in Soccer; Automated Detection of Shot Events in Game Phases Using GNSS Data from a Single Team.
KW - Informatics
UR - http://www.scopus.com/inward/record.url?scp=105002007939&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-86692-0
DO - 10.1007/978-3-031-86692-0
M3 - Conference proceedings
SN - 978-3-031-86691-3
T3 - Communications in Computer and Information Science
BT - Machine Learning and Data Mining for Sports Analytics
PB - Springer Verlag
CY - Cham
Y2 - 9 September 2024 through 9 September 2024
ER -