International Journal on Advanced Science, Engineering and Information Technology, Vol. 7 (2017) No. 1, pages: 100-105, DOI:10.18517/ijaseit.7.1.1145

Unsupervised Pattern Recognition of Physical Fitness Related Performance Parameters among Terengganu Youth Female Field Hockey Players

Razali M. R., Alias N., Maliki A. B. H. M., Musa R. M., Kosni L. A., Juahir H.

Abstract

This study aims to identify the most significant physical fitness parameters among youth female Terengganu field hockey players. Multivariate methods of unsupervised pattern recognition of principal component analysis (PCA) and descriptive statistic were used to determine the most significant physical fitness related performance parameters on 42 Terengganu youth female field hockey players. The first PC’s projected high factor loading in BMI (0.86) and predicted VO2max (-0.82) as the most significant parameters indicating the requirements of body composition in this sport. The second PC’s displayed high factor loading in 1-minute sit up (0.89) and 20-meter speed (-0.84) highlighting the need for core muscle strength. The third PC’s demonstrated high factor loading in V-sit and reach (0.71) and maximum push up (0.82) recognising the importance of upper muscle strength in the sport. The results from the current study revealed that certain physical fitness components are seemed to be more pronounced in the performance of the game by the Terengganu female youth hockey players. The study has indicated that body composition, core muscle strength and upper muscle strength are the most outstanding physical fitness variables possess by the players for the enactment of the game compared to other fitness parameters. Highlighting the physical fitness performance related parameters might help to evaluate the strength and weakness of the players on the relevant parameters which could prompt to the adjustment of the training programme for the inclusive improvement of the players.

Keywords:

physical fitness parameters; body composition; field hockey; unsupervised pattern recognition

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