Machine Learning and Data Mining for Sports Analytics

Nyhet

12th International Workshop, MLSA 2025, Porto, Portugal, September 15, 2025, Revised Selected Papers

Häftad, Engelska, 2026

AvHugo Rios-Neto,Pieter Robberechts,Maaike Van Roy,Albrecht Zimmermann,Maaike van Roy

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This book constitutes the refereed proceedings of the 12th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2025, held in Porto, Portugal, on September 15, 2025. The 11 full papers presented in this volume were carefully reviewed and selected from 24 submissions. They are grouped into the following topics: Individual sports; Soccer; Other team sports.

Produktinformation

Utgivningsdatum2026-01-28
Mått155 x 235 x 11 mm
Vikt300 g
FormatHäftad
SpråkEngelska
SerieCommunications in Computer and Information Science
Antal sidor180
FörlagSpringer Nature Switzerland AG
ISBN9783032151643

Tillhör följande kategorier

Hårdvara inom Data och it
Programvaruutveckling inom Data och it
Databaser inom Data och it
Tillämpad datateknik inom Data och it
Sportböcker inom Sport fritid och hobby
Systemvetenskap och AI inom Data och it
Artificiell intelligens inom Data och it

.- Individual Sports.- Analysis of Service Returns in Table Tennis..- Racing Beyond the Gate: Predicting Speedway Results with Expected Points (xP)..- Soccer.- Contextual Evaluation of Individual Contributions from Pressing Situations in Football..- Beyond Outcome Bias: Incorporating Action Completion Probability and Risk-Return into Soccer Evaluation Models..- Next-Event Prediction in Soccer: Assessing the Impact of Team and Player Information..- A unified spatio-temporal graph model to predict multi-agent movement..- Through the Gaps: Uncovering Tactical Line-Breaking Passes with Clustering..- Pitch-wide space evaluation for soccer transitions..- What Makes a Dribble Successful? Insights From 3D Pose Tracking Data..- Other Team Sports.- Multidimensional heterogeneity learning for field goal attempt analysis of NBA players..- Evaluating Movement Initiation Timing in Ultimate Frisbee via Temporal Counterfactuals.