Machine Learning and Data Mining for Sports Analytics
10th International Workshop, MLSA 2023, Turin, Italy, September 18, 2023, Revised Selected Papers
Published on 26. February 2024
Book
Paperback/Softback
X, 204 pages
978-3-031-53832-2 (ISBN)
Description
This book constitutes the refereed proceedings of the 10th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2023, held in Turin, Italy, in September 2023.
The 16 full papers included in this book were carefully reviewed and selected from 31 submissions. They were organized in topical sections as follows: Football/Soccer, Basketball, Other team sports, Individual sports.
More details
Series
Edition
2024 ed.
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
7 s/w Abbildungen, 49 farbige Abbildungen
X, 204 p. 56 illus., 49 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 12 mm
Weight
335 gr
ISBN-13
978-3-031-53832-2 (9783031538322)
DOI
10.1007/978-3-031-53833-9
Schweitzer Classification
Other editions
Additional editions
Ulf Brefeld | Jesse Davis | Jan Van Haaren
Machine Learning and Data Mining for Sports Analytics
10th International Workshop, MLSA 2023, Turin, Italy, September 18, 2023, Revised Selected Papers
E-Book
02/2024
Springer
€80.24
Available for download
Content
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.