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Machine learning and data mining for sports analytics : 9th international workshop, MLSA 2022, Grenoble, France, September 19, 2022, revised selected papers / edited by Ulf Brefeld, Jesse Davis, Jan Van Haaren, Albrecht Zimmermann

Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Communications in computer and information science ; 1783Publisher: Cham : Springer Nature Switzerland, 2023Publisher: Cham : Imprint: Springer, 2023Description: 1 Online-Ressource (135 Seiten)ISBN:
  • 9783031275272
Subject(s): Additional physical formats: 9783031275265 | 9783031275289 | Erscheint auch als: 9783031275265 Druck-Ausgabe | Erscheint auch als: 9783031275289 Druck-AusgabeDDC classification:
  • 006.3 23
DOI: DOI: 10.1007/978-3-031-27527-2Online resources: Summary: Football -- Towards expected counter - Using comprehensible features to predict counterattacks -- Shot analysis in different levels of German football using Expected Goals -- Analyzing passing sequences for the prediction of goal-scoring opportunities -- Let’s penetrate the defense: A machine learning model for prediction and valuation of penetrative passes -- Evaluation of creating scoring opportunities for teammates in soccer via trajectory prediction -- Cost-efficient and bias-robust sports player tracking by integrating GPS and video -- Racket sports -- Predicting tennis serve directions with machine learning -- Discovering and visualizing tactics in table tennis games based on subgroup discovery -- Cycling -- Athlete monitoring in professional road cycling using similarity search on time series data.Summary: This book constitutes the refereed proceedings of the 9th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2022, held in Grenoble, France, during September 19, 2022. The 10 full papers included in this book were carefully reviewed and selected from 18 submissions. They were organized in topical sections as follows: Football, Racket sports, Cycling.PPN: PPN: 1837692823Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-SCS | ZDB-2-SXCS | BSZ-2-SN-Auswahl
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