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Machine Learning and Data Mining for Sports Analytics: 12th International Workshop, MLSA 2025, Porto, Portugal, September 15, 2025, Revised Selected Papers [Pehme köide]

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  • Formaat: Paperback / softback, 180 pages, kõrgus x laius: 235x155 mm, 60 Illustrations, color; 3 Illustrations, black and white
  • Sari: Communications in Computer and Information Science
  • Ilmumisaeg: 28-Jan-2026
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 3032151643
  • ISBN-13: 9783032151643
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Machine Learning and Data Mining for Sports Analytics: 12th International Workshop, MLSA 2025, Porto, Portugal, September 15, 2025, Revised Selected PapersSuurem pilt
  • Formaat: Paperback / softback, 180 pages, kõrgus x laius: 235x155 mm, 60 Illustrations, color; 3 Illustrations, black and white
  • Sari: Communications in Computer and Information Science
  • Ilmumisaeg: 28-Jan-2026
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 3032151643
  • ISBN-13: 9783032151643
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9783032151643.html
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.
.- 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.