Prediction of Swimming Performance on the Basis of Selected Anthropometric Variables | Original Article

ABSTRACT:

Swimming is a popular sport and early starting specialization although performance and success in elite swimmers depend on various factors. Purpose of this study was to predict 50 m swimming performance on the basis of selected anthropometric variables. A total of 20 swimmers aged 18-30 years, with at least 1 year of swimming experience were chosen. They underwent measurement of height, arm span, leg length, torso length, hand length, hand breadth, foot length, foot breadth and fat percentage and finally the recording of the 50m sprint swimming time in freestyle swimming. Multiple linear regression was used as statistical technique. In results, height, torso length, hand length and hand breadth were contributory variable in model. Variable selected in the regression equation explain 74.8 of the total variability in the swimming performance which is good. Since F value for this regression model is highly significant (f=0.038), the model is reliable. At the same time, all the regression coefficients in this model are highly significant(p<0.05) and therefore, it may be interpreted that variable selected in the model, namely, height, torso length, hand length and hand breadth are appropriate in estimating the 50 m swimming performance of swimmers.