Machine Learning and Data Mining for Sports Analytics

9th International Workshop, MLSA 2022, Grenoble, France, September 19, 2022, Revised Selected Papers
1. Auflage 2023
ISBN: 978-3-031-27526-5
Verlag: Springer Nature Switzerland

Buch, Englisch, Band 1783, 127 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 224 g

Reihe: Communications in Computer and Information Science

This book constitutes the refereed proceedings of the 9th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2022, held in Grenoble, France, during September 19, 2022. 
The 10 full papers included in this book were carefully reviewed and selected from 18 submissions. They were organized in topical sections as follows: Football, Racket sports, Cycling.

Zielgruppe

Research

Autoren/Hrsg.

Brefeld, Ulf

Zimmermann, Albrecht

Davis, Jesse

Haaren, Jan van

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

Football.- Towards expected counter - Using comprehensible features to predict counterattacks.- Shot analysis in different levels of German football using Expected Goals.- Analyzing passing sequences for the prediction of goal-scoring opportunities.- Let’s penetrate the defense: A machine learning model for prediction and valuation of penetrative passes.- Evaluation of creating scoring opportunities for teammates in soccer via trajectory prediction.- Cost-efficient and bias-robust sports player tracking by integrating GPS and video.- Racket sports.- Predicting tennis serve directions with machine learning.- Discovering and visualizing tactics in table tennis games based on subgroup discovery.- Cycling.- Athlete monitoring in professional road cycling using similarity search on time series data.