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Machine Learning and Data Mining for Sports Analytics de Ulf Brefeld

Machine Learning and Data Mining for Sports Analytics: Lecture Notes in Computer Science, cartea 11330

Editat de Ulf Brefeld, Jesse Davis, Jan van Haaren, Albrecht Zimmermann
en Limba Engleză Paperback – 7 apr 2019
This book constitutes the refereed post-conference proceedings of the 5th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2018, colocated with ECML/PKDD 2018, in Dublin, Ireland, in September 2018.

The 12 full papers presented together with 4 challenge papers were carefully reviewed and selected from 24 submissions. The papers present a variety of topics, covering the team sports American football, basketball, ice hockey, and soccer, as well as the individual sports cycling and martial arts. In addition, four challenge papers are included, reporting on how to predict pass receivers in soccer. 
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Specificații

ISBN-13: 9783030172732
ISBN-10: 3030172732
Pagini: 192
Ilustrații: X, 179 p. 57 illus., 41 illus. in color.
Dimensiuni: 155 x 235 x 11 mm
Greutate: 0.3 kg
Ediția:1st ed. 2019
Editura: Springer
Colecția Lecture Notes in Computer Science
Seria Lecture Notes in Computer Science

Locul publicării:Cham, Switzerland

Cuprins

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.

Descriere

Descriere de la o altă ediție sau format:
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.