Journal article
Evaluating a computer based skills acquisition trainer to classify badminton players
Journal of Sports Science and Medicine, Vol.10(3), pp.528-533
2011
Abstract
The aim of the present study was to compare the statistical ability of both neural networks and discriminant function analysis on the newly developed SATB program. Using these statistical tools, we identified the accuracy of the SATB in classifying badminton players into different skill level groups. Forty-one participants, classified as advanced, intermediate, or beginner skilled level, participated in this study. Results indicated neural networks are more effective in predicting group membership, and displayed higher predictive validity when compared to discriminant analysis. Using these outcomes, in conjunction with the physiological and biomechanical variables of the participants, we assessed the authenticity and accuracy of the SATB and commented on the overall effectiveness of the visual based training approach to training badminton athletes.
Details
- Title
- Evaluating a computer based skills acquisition trainer to classify badminton players
- Authors
- M V Huynh (Author) - RMIT UniversityAnthony Bedford (Author) - RMIT University
- Publication details
- Journal of Sports Science and Medicine, Vol.10(3), pp.528-533
- Publisher
- Journal of Sports Science and Medicine
- Date published
- 2011
- ISSN
- 1303-2968; 1303-2968
- Organisation Unit
- University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering; School of Health and Behavioural Sciences - Legacy
- Language
- English
- Record Identifier
- 99451467002621
- Output Type
- Journal article
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