Loading...
Loading...

Go to the content (press return)

Identifying basketball plays from sensor data; towards a low-cost automatic extraction of advanced statistics

Author
Arbués, A.; B. Moeslund; H. Bahnsen; Benitez, R.
Type of activity
Presentation of work at congresses
Name of edition
2017 IEEE International Conference on Data Mining Workshops
Date of publication
2017
Presentation's date
2017-10-18
Book of congress proceedings
2017 IEEE International Conference on Data Mining Workshops (ICDMW)
First page
894
Last page
901
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
DOI
10.1109/ICDMW.2017.123
Repository
http://hdl.handle.net/2117/131599 Open in new window
URL
https://ieeexplore.ieee.org/document/8215757 Open in new window
Abstract
Advanced statistics have proved to be a crucial tool for basketball coaches in order to improve training skills. Indeed, the performance of the team can be further optimized by studying the behaviour of players under certain conditions. In the United States of America, companies such as STATS or Second Spectrum use a complex multi-camera setup to deliver advanced statistics to all NBA teams, but the price of this service is far beyond the budget of the vast majority of European teams. For this r...
Citation
Arbués, A. [et al.]. Identifying basketball plays from sensor data; towards a low-cost automatic extraction of advanced statistics. A: 2017 IEEE International Conference on Data Mining Workshops. "2017 IEEE International Conference on Data Mining Workshops (ICDMW)". Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 894-901.
Group of research
ANCORA - Anàlisi i control del ritme cardíac
CREB - Biomedical Engineering Research Centre

Participants

  • Arbués Sangüesa, Adrià  (author and speaker )
  • B. Moeslund, Thomas  (author and speaker )
  • H. Bahnsen, Chris  (author and speaker )
  • Benitez Iglesias, Raul  (author and speaker )