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JOURNAL
OF
SPORTS SCIENCE &
MEDICINE
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Research
article
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EVALUATING A COMPUTER BASED SKILLS ACQUISITION TRAINER TO CLASSIFY BADMINTON PLAYERS |
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Minh Vu Huynh 
and Anthony Bedford |
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RMIT University, Melbourne, Australia |
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© Journal of Sports Science and Medicine (2011) 10, 528 - 533 |
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| 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. Key words: Skills acquisition, badminton, neural networks, discriminant analysis. |
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