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 VO(2max) (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).