Knowledge-assisted ranking: A visual analytic application for sports event data
- Submitting institution
-
University of the West of England, Bristol
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 914908
- Type
- D - Journal article
- DOI
-
10.1109/MCG.2015.25
- Title of journal
- IEEE Computer Graphics and Applications
- Article number
- -
- First page
- 72
- Volume
- 36
- Issue
- 3
- ISSN
- 0272-1716
- Open access status
- Out of scope for open access requirements
- Month of publication
- January
- Year of publication
- 2015
- URL
-
http://dx.doi.org/10.1109/MCG.2015.25
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
6
- Research group(s)
-
-
- Citation count
- 8
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper describes novel techniques for organising and retrieving large collections of video content to support professional sports analysts, where users can define multiple interactive regression model to capture sorting requirements, fully supported by visualization to facilitate knowledge discovery at different stages of the process. We demonstrate the approach using a rugby case study to find key instances for analyzing team and player performance. Analysts at the Welsh Rugby Union reported significant benefits of adopting this approach, and now use this as part of team training to quickly identify and study form and technique from previous matches (Rhodri Bown, WRU).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
