Purpose: To explore the interplay between arms-only propelling efficiency (η p), mechanical power output ( W˙tot ) and swimming speed (V); these three parameters are indeed related through the following equation V 3 = 1/kη p W˙tot (where k is the speed-specific drag; k = F/V 2); thus, the larger are η p and W˙tot the larger is V. We furthermore wanted to test the hypothesis that a multiple linear regression between W˙tot , η p and V would have a stronger correlation coefficient than a linear regression between W˙tot and V alone. Methods: To this aim we recruited 29 master swimmers (21 M/8F) who were asked to perform (1) an incremental protocol at the arm-ergometer (dry-land test) to determine W˙tot at V˙ O2max (e.g. V˙ max); (2) a maximal 200 m swim trial (with a pull buoy: arms only) during which V and η p were determined. Results: No relationship was found between W˙max and η p (not necessarily the swimmers with the largest W˙max are those with the largest η p and vice versa) whereas significant correlations were found between W˙max and V (R = 0.419, P = 0.024) and η p and V (R = 0.741, P = 0.001); a multiple linear regression indicates that about 75 % of the variability of V can be explained by the variability of W˙max and η p (R = 0.865, P < 0.001). Conclusions: These findings indicate that η p should be taken into consideration when the relationship between W˙max and V is investigated and that this allows to better explain the inter-subject variability in performance (swimming speed).
The interplay between arms-only propelling efficiency, power output and speed in master swimmers.
ZAMPARO, Paola;Peterson Silveira, Ricardo;
2014-01-01
Abstract
Purpose: To explore the interplay between arms-only propelling efficiency (η p), mechanical power output ( W˙tot ) and swimming speed (V); these three parameters are indeed related through the following equation V 3 = 1/kη p W˙tot (where k is the speed-specific drag; k = F/V 2); thus, the larger are η p and W˙tot the larger is V. We furthermore wanted to test the hypothesis that a multiple linear regression between W˙tot , η p and V would have a stronger correlation coefficient than a linear regression between W˙tot and V alone. Methods: To this aim we recruited 29 master swimmers (21 M/8F) who were asked to perform (1) an incremental protocol at the arm-ergometer (dry-land test) to determine W˙tot at V˙ O2max (e.g. V˙ max); (2) a maximal 200 m swim trial (with a pull buoy: arms only) during which V and η p were determined. Results: No relationship was found between W˙max and η p (not necessarily the swimmers with the largest W˙max are those with the largest η p and vice versa) whereas significant correlations were found between W˙max and V (R = 0.419, P = 0.024) and η p and V (R = 0.741, P = 0.001); a multiple linear regression indicates that about 75 % of the variability of V can be explained by the variability of W˙max and η p (R = 0.865, P < 0.001). Conclusions: These findings indicate that η p should be taken into consideration when the relationship between W˙max and V is investigated and that this allows to better explain the inter-subject variability in performance (swimming speed).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.