Machine Learning and Data Mining for Sports Analytics

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.

Contenu
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.