TY  - BOOK
AU  - Brefeld,Ulf
AU  - Davis,Jesse
AU  - Van Haaren,Jan
AU  - Zimmermann,Albrecht
ED  - SpringerLink (Online service)
TI  - 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 
T2  - Communications in Computer and Information Science,
SN  - 9783030649128
AV  - Q334-342 
PY  - 2020///
CY  - Cham
PB  - Springer International Publishing, Imprint: Springer
KW  - Artificial intelligence
KW  - Computer engineering
KW  - Computer networks 
KW  - Education
KW  - Data processing
KW  - Social sciences
KW  - Artificial Intelligence
KW  - Computer Engineering and Networks
KW  - Computers and Education
KW  - Computer Application in Social and Behavioral Sciences
KW  - Computer Communication Networks
N1  - 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
N2  - 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
UR  - https://doi.org/10.1007/978-3-030-64912-8
ER  -