Cover Image
Read Now

Machine Learning and Data Mining for Sports Analytics 9th International Workshop, MLSA 2022, Grenoble, France, September 19, 2022, Revised Selected Papers

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...

Full description

Bibliographic Details
Other Authors: Brefeld, Ulf (Editor), Davis, Jesse (Editor), Van Haaren, Jan (Editor), Zimmermann, Albrecht (Editor)
Format: eBook
Language:English
Published: Cham Springer Nature Switzerland 2023, 2023
Edition:1st ed. 2023
Series:Communications in Computer and Information Science
Subjects:
Computer Communication Networks
Software Engineering
Database Management System
Artificial Intelligence
Application Software
Computer Networks 
Computer And Information Systems Applications
Database Management
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
LEADER 02785nmm a2200409 u 4500
001 EB002150149
003 EBX01000000000000001288275
005 00000000000000.0
007 cr|||||||||||||||||||||
008 230301 ||| eng
020 |a 9783031275272 
100 1 |a Brefeld, Ulf  |e [editor] 
245 0 0 |a Machine Learning and Data Mining for Sports Analytics  |h Elektronische Ressource  |b 9th International Workshop, MLSA 2022, Grenoble, France, September 19, 2022, Revised Selected Papers  |c edited by Ulf Brefeld, Jesse Davis, Jan Van Haaren, Albrecht Zimmermann 
250 |a 1st ed. 2023 
260 |a Cham  |b Springer Nature Switzerland  |c 2023, 2023 
300 |a X, 127 p. 47 illus., 38 illus. in color  |b online resource 
505 0 |a 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 
653 |a Computer Communication Networks 
653 |a Software engineering 
653 |a Database Management System 
653 |a Software Engineering 
653 |a Artificial Intelligence 
653 |a Application software 
653 |a Computer networks  
653 |a Artificial intelligence 
653 |a Computer and Information Systems Applications 
653 |a Database management 
700 1 |a Davis, Jesse  |e [editor] 
700 1 |a Van Haaren, Jan  |e [editor] 
700 1 |a Zimmermann, Albrecht  |e [editor] 
041 0 7 |a eng  |2 ISO 639-2 
989 |b Springer  |a Springer eBooks 2005- 
490 0 |a Communications in Computer and Information Science 
028 5 0 |a 10.1007/978-3-031-27527-2 
856 4 0 |u https://doi.org/10.1007/978-3-031-27527-2?nosfx=y  |x Verlag  |3 Volltext 
082 0 |a 006.3 
520 |a 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 

Similar Items