Predicting performance using critical swimming speed in young swimmers - Zacca, R.; Castro, F. (Biomechanics and Medicine in Swimming XI - Abstracts, 2010)
INTRODUCTION: Predicting performance by a two-parameter model has been applied to marathon runners, rowers and cyclists, but there is still a gap on research in swimming. Therefore, the aim of the present study was to compare the actual performances in 200 m, 400 m, 800 m and 1500 m with the performance predicted by critical swimming speed (CSS) of a two-parameter mathematical model with different distances combinations in young swimmers. METHODS: Eleven young swimmers (Age: 14.3 ± 0.5 years) of national competitive level have joined the study. Maximal free-style swimming trials were conducted for the distances of 200, 400, 800 and 1500 meters (randomized order). Each distance was predicted by all the possible combinations of two distances to compose the linear regression equation between distance and time values. The level of agreement between the actual performance and the predicted performance obtained by three possible combinations for each distance was identified using Bland and Altman analysis. RESULTS: Predict performance in young swimmers through CSS by a two-parameter model in training condition lead to inaccurate values despite the good level of agreement of some combinations of distance, since any difference in the performance value may represent a victory or a defeat in swimming events. (best level of agreement for 200m = bias 9.9s, limits -10.4 to 30.3s (400-1500m); 400m = bias 7.1s; limits -22 to 7.8s 200-800m); 800m = bias 1.9s, limits -27 to 30.9s (400-1500m); 1500m bias 7.5s; limits -64.6 to 79.7s (200-800m)). DISCUSSION: Interesting results were obtained with adults engaged in competition situation. However, predicting performance by CSS in training situation does not seem to be accurate for young swimmers, probably because it is not possible to provide motivation similar to the competition situation. Competitive experience may also have influenced this result. Despite the limitations related to predict the CSS from the mathematical model of two parameters, as used in the present study, we can observed that this is still the easiest way to predict the CSS.