Machine Learning and Data Mining for Sports Analytics

Machine Learning and Data Mining for Sports Analytics portes grátis

Machine Learning and Data Mining for Sports Analytics

10th International Workshop, MLSA 2023, Turin, Italy, September 18, 2023, Revised Selected Papers

Davis, Jesse; Brefeld, Ulf; Zimmermann, Albrecht; Van Haaren, Jan

Springer International Publishing AG

02/2024

204

Mole

Inglês

9783031538322

15 a 20 dias

Descrição não disponível.
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.
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artificial intelligence;computer vision;data mining;sports analytics;supervised learning;machine learning;human-computer interaction;software design;software engineering;telecommunication networks;telecommunication systems;mixture models;classification trees;ensemble methods;clustering;neural networks;communication systems;software architecture