Machine Learning and Data Mining for Sports Analytics
Springer International Publishing (Verlag)
978-3-031-27526-5 (ISBN)
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.
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.
Erscheinungsdatum | 27.02.2023 |
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Reihe/Serie | Communications in Computer and Information Science |
Zusatzinfo | X, 127 p. 47 illus., 38 illus. in color. |
Verlagsort | Cham |
Sprache | englisch |
Maße | 155 x 235 mm |
Gewicht | 226 g |
Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
Schlagworte | Applications • Artificial Intelligence • Computer Science • computer vision • conference proceedings • Human-Computer interaction • Informatics • machine learning • Neural networks • Research • software architecture • Software Design • Software engineering |
ISBN-10 | 3-031-27526-8 / 3031275268 |
ISBN-13 | 978-3-031-27526-5 / 9783031275265 |
Zustand | Neuware |
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