Katalog der Deutschen Nationalbibliothek
Ergebnis der Suche nach: tit all "Sports data mining"
|
|
|
| Link zu diesem Datensatz | https://d-nb.info/1321649185 |
| Art des Inhalts | Konferenzschrift |
| Titel | Machine Learning and Data Mining for Sports Analytics : 10th International Workshop, MLSA 2023, Turin, Italy, September 18, 2023, 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. 2024 |
| Verlag | Cham : Springer Nature Switzerland, Imprint: Springer |
| Zeitliche Einordnung | Erscheinungsdatum: 2024 |
| Umfang/Format | Online-Ressource, X, 204 p. 56 illus., 49 illus. in color. : online resource. |
| Andere Ausgabe(n) |
Printed edition:: ISBN: 978-3-031-53832-2 Printed edition:: ISBN: 978-3-031-53834-6 |
| Inhalt | Sports Data Analytics: An Art and a Science -- Foot ball/ soccer -- ETSY: A rule-based approach to Event and Tracking data Synchronization -- Masked Autoencoder Pretraining for Event Classi cation in Elite Soccer -- Quanti cation of Turnover Danger with xCounter -- Pass Receiver and Outcome Prediction in Soccer Using Temporal -- Graph Networks -- Field Depth Matters: Comparing the Valuation of Passes in Football -- Basket ball -- Momentum matters: investigating high-pressure situations in the NBA through scoring probability -- Are Sports Awards About Sports? Using AI to Find the Answer -- The Big Three: a practical framework for designing Decision Support -- Systems in Sports and an application for basketball -- Ot her t eam sp ort s -- What data should be collected for a good handball Expected Goal model? .-Identifying Player Roles in Ice Hockey -- Position Prediction -- Boat speed prediction in SailGP -- Individual sp ort s -- Exploring Table Tennis Analytics: Domination, Expected Score and Shot Diversity -- Specialization Evaluation -- Exploiting Clustering for Sports Data Analysis: A Study of Public and Real-world Datasets |
| Persistent Identifier |
URN: urn:nbn:de:101:1-2024022603070539827393 DOI: 10.1007/978-3-031-53833-9 |
| URL | https://doi.org/10.1007/978-3-031-53833-9 |
| ISBN/Einband/Preis | 978-3-031-53833-9 |
| Sprache(n) | Englisch (eng) |
| Beziehungen | Communications in Computer and Information Science ; 2035 |
| DDC-Notation | 796.01 (maschinell ermittelte DDC-Kurznotation) |
| Sachgruppe(n) | 796 Sport |
| Online-Zugriff | Archivobjekt öffnen |

