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Machine Learning and Data Mining for Sports Analytics

- 5th International Workshop, MLSA 2018, Co-located with ECML/PKDD 2018, Dublin, Ireland, September 10, 2018, Proceedings

part of the Lecture Notes in Computer Science series

part of the Lecture Notes in Artificial Intelligence series

Machine Learning and Data Mining for Sports Analytics Save 15% from RPP Save 15%
About Machine Learning and Data Mining for Sports Analytics

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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  • Language:
  • English
  • ISBN:
  • 9783030172732
  • Binding:
  • Paperback
  • Pages:
  • 179
  • Published:
  • April 6, 2019
  • Edition:
  • 12019
  • Dimensions:
  • 155x235x0 mm.
  • Weight:
  • 454 g.
Delivery: 2-4 weeks
Expected delivery: December 21, 2024
Extended return policy to January 30, 2025

Description of Machine Learning and Data Mining for Sports Analytics

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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