Volume : 2, Issue : 8, August - 2013

Relationship Between Selected Anthropometric Measurements and Performance of Women Badminton Players

Dr. M. P. Gaur

Abstract :

The role of anthropometry as a sports science is perhaps one of the most crucial in this regard. It is essential because the physique, body composition, physical growth and one’s motor development are of fundamental importance in developing the criteria of talent relation and development in sports. Thirty Five (35) female players age ranging from 17–25 years who have participated in inter college or zonal championships in Badminton were randomly selected to act as subjects for the study. Weight, Standing Height, Sitting Height, Leg Length, Lower Leg Length, Upper Leg Length, Arm Length, Upper Arm Length, and Lower Arm Length were taken into consideration. Weighing Scale, Anthropometric Rod, Steel tape and Skin Fold Caliper were the tools used for the measurements whereas the performance of the selected Badminton players was gathered by the help of three experts out of 10. The collected data was analyzed by computing descriptive statistics followed by Pearson’s Product Moment Correlation. The results revealed that mean and SD values of Weight, Standing Height, Sitting Height, Leg Length, Lower Leg Length, Upper Leg Length, Arm Length, Upper Arm Length, and Lower Arm Length were found to be 50.48±5.28, 154.91±3.85, 79.03±6.32, 86.82±7.38, 47.80±3.82, 43.80±1.99, 59.73±4.68, 29.15±3.20 and 31.0±4.21 respectively. Whereas a significant relationship was found between Performance score and the selected variables, as the values were found to be 0.324, 0.828, 0.468, 0.481, 0.655, 0.533, 0.352 and 0.658 respectively against the tabulated value 0.296 which was significant related at 0.05 level but only upper leg length was not correlated to performance score as the value was found to be 0.178. So finally it was concluded that for better prediction of performance of women Badminton players, all the selected anthropometric variables may be considered in combination instead of studying the influence of each independent variables