Machine Learning and Data Mining for Sports Analytics

7th International Workshop, MLSA 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14¿18, 2020, Proceedings
Herausgegeben:Brefeld, Ulf; Davis, Jesse; Van Haaren, Jan; Zimmermann, Albrecht

• Broschiertes Buch

Produktbeschreibung

This book constitutes the refereed post-conference proceedings of the 7th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2020, colocated with ECML/PKDD 2020, in Ghent, Belgium, in September 2020. Due to the COVID-19 pandemic the conference was held online.
The 11 papers presented were carefully reviewed and selected from 22 submissions. The papers present a variety of topics within the area of sports analytics, including tactical analysis, outcome predictions, data acquisition, performance optimization, and player evaluation.

Produktdetails

• Communications in Computer and Information Science 1324
• Verlag: Springer / Springer International Publishing / Springer, Berlin
• Artikelnr. des Verlages: 978-3-030-64911-1
• 1st ed. 2020
• Seitenzahl: 152
• Erscheinungstermin: 10. Dezember 2020
• Englisch
• Abmessung: 235mm x 155mm x 9mm
• Gewicht: 242g
• ISBN-13: 9783030649111
• ISBN-10: 3030649113
• Artikelnr.: 60465463

Inhaltsangabe

Routine Inspection: A playbook for corner kicks.- How data availability aects the ability to learngood xG models.- Low-cost optical tracking of soccer players.- An Autoencoder Based Approach to SimulateSports Games.- Physical performance optimization in football.- Predicting Player Trajectoriesin Shot Situations in Soccer.- Stats Aren't Everything: Learning Strengths andWeaknesses of Cricket Players.- Prediction of tiers in the rankingof ice hockey players.- A Machine Learning Approach for Road CyclingRace Performance Prediction.- Mining Marathon Training Data to GenerateUseful User Proles.- Learning from partially labeled sequences forbehavioral signal annotation.