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

Buch in der Datenbank seit 2025-03-28T02:54:49+01:00 (Berlin)
Buch zuletzt gefunden am 2025-05-15T04:38:22+02:00 (Berlin)
ISBN/EAN: 9783031866920

ISBN - alternative Schreibweisen:
978-3-031-86692-0

Daten vom Verlag:

Autor/in: Ulf Brefeld; Jesse Davis; Jan Van Haaren; Albrecht Zimmermann, (ORCID: 0000000196006463; 0000000237489263; 0000000283197456)
Titel: Communications in Computer and Information Science; Machine Learning and Data Mining for Sports Analytics - 11th International Workshop, MLSA 2024, Vilnius, Lithuania, September 9, 2024, Revised Selected Papers
Verlag: Springer; Springer International Publishing
119 Seiten
Erscheinungsjahr: 2025-03-25
Cham; CH
Sprache: Englisch
64,19 € (DE)
71,00 CHF (CH)
Available
X, 119 p. 43 illus., 38 illus. in color.

EA; Nonbooks, PBS / Informatik, EDV/Informatik; Künstliche Intelligenz; Verstehen; Machine Learning; Data Mining; Sports Analytics; Supervised learning; Neural networks; Mixture models; Classification and regression trees; Ensemble methods; Clustering; Artificial Intelligence; Computer Communication Networks; Computer and Information Systems Applications; Database Management System; Software Engineering; Netzwerk-Hardware; Angewandte Informatik; Datenbanken; Software Engineering; BC

This book constitutes the refereed proceedings of the 11th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2024, held in Vilnius, Lithuania, on September 9, 2024. 

The 9 full papers presented in this volume were carefully reviewed and selected from 21 submissions. 

They are grouped into the following topics: Individual sports; Basketball; Soccer; Other team sports/e-Sports.

.- Characterizing Serves in Table Tennis.

.- 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.

.- Team Dynamics in DotA2 through Attention Mechanism.