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

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. 

Summary

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. 

Product details

• Assisted by: Ulf Brefeld (Editor), Jess Davis (Editor), Jesse Davis (Editor), Jan van Haaren (Editor), Jan Van Haaren (Editor), Jan Van Haaren et al (Editor), Albrecht Zimmermann (Editor)
• Publisher: Springer, Berlin
• Languages: English
• Product format: Paperback / Softback
• Released: 01.01.2019
• EAN: 9783030172732
• ISBN: 978-3-0-3017273-2
• No. of pages: 179
• Dimensions: 154 mm x 236 mm x 12 mm
• Weight: 301 g
• Illustrations: X, 179 p. 57 illus., 41 illus. in color.
• Series: Lecture Notes in Computer Science; Lecture Notes in Artificial Intelligence
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; C, Data Mining, Artificial Intelligence, Mustererkennung, Wahrscheinlichkeitsrechnung und Statistik, Wissensbasierte Systeme, Expertensysteme, Mathematik für Informatiker, computer science, pattern recognition, Data Mining and Knowledge Discovery, Mathematical & statistical software, Automated Pattern Recognition, Maths for computer scientists, Mathematical statistics, Probability and Statistics in Computer Science, Expert systems / knowledge-based systems, Probability and statistics