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| Link zu diesem Datensatz | https://d-nb.info/1361337567 |
| Art des Inhalts | Konferenzschrift |
| Titel | Machine Learning and Data Mining for Sports Analytics : 11th International Workshop, MLSA 2024, Vilnius, Lithuania, September 9, 2024, Revised Selected Papers / edited by Ulf Brefeld, Jesse Davis, Jan Van Haaren, Albrecht Zimmermann |
| Person(en) |
Brefeld, Ulf (Herausgeber) Davis, Jesse (Herausgeber) Haaren, Jan van (Herausgeber) Zimmermann, Albrecht (Herausgeber) |
| Organisation(en) | SpringerLink (Online service) (Sonstige) |
| Ausgabe | 1st ed. 2025 |
| Verlag | Cham : Springer Nature Switzerland, Imprint: Springer |
| Zeitliche Einordnung | Erscheinungsdatum: 2025 |
| Umfang/Format | Online-Ressource, X, 119 p. 43 illus., 38 illus. in color. : online resource. |
| Andere Ausgabe(n) |
Printed edition:: ISBN: 978-3-031-86691-3 Printed edition:: ISBN: 978-3-031-86693-7 |
| Inhalt | -- Individual sports. -- Characterizing Serves in Table Tennis. -- Large Language Models on Race Commentary: Towards Granular Data in Cycling Analytics. -- Basketball. -- GraphEIV: A Framework for Estimating the Expected Immediate Value in Basketball Using Graph Neural Networks. -- Mathematical models for "off-ball" scoring prediction in basketball. -- Soccer. -- 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. -- Other team sports/e-Sports. -- Automated Detection of Shot Events in Game Phases Using GNSS Data from a Single Team. -- Team Dynamics in DotA2 through Attention Mechanism |
| Persistent Identifier |
URN: urn:nbn:de:101:1-2503260306475.982015257851 DOI: 10.1007/978-3-031-86692-0 |
| URL | https://doi.org/10.1007/978-3-031-86692-0 |
| ISBN/Einband/Preis | 978-3-031-86692-0 |
| Sprache(n) | Englisch (eng) |
| Beziehungen | Communications in Computer and Information Science ; 2460 |
| DDC-Notation | 796.346 (maschinell ermittelte DDC-Kurznotation) |
| Sachgruppe(n) | 796 Sport |
| Online-Zugriff | Archivobjekt öffnen |
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