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Dry-land strength training is a common component of swimming programs; however, its efficacy is contentious. A common criticism of dry-land strength training for swimming is a lack of specificity. An understanding of movement patterns in swimming can enable dry-land strength training programs to be developed to elicit adaptations that transfer to improvements in swimming performance. This study aimed to quantify the range and velocity of hip roll, shoulder roll, and torso twist (produced by differences in the relative angle between shoulder roll and hip roll) in front crawl at different swimming speeds. Longitudinal torso kinematics was compared between sprint and 400-m pace front crawl using 3D kinematics of 13 elite Scottish front crawl specialists. The range (sprint: 78.1°; 400 m: 61.3°) and velocity of torso twist (sprint: 166.3°·s; 400 m: 96.9°·s) were greater at sprint than 400-m pace. These differences were attributed to reductions in hip roll (sprint: 36.8°; 400 m: 49.9°) without corresponding reductions in shoulder roll (sprint: 97.7°; 400 m: 101.6°) when subjects swam faster. Shoulder roll velocity (sprint: 190.9°·s; 400 m: 139.2°·s) and hip roll velocity (sprint: 75.5°·s; 400 m: 69.1°·s) were greater at sprint than 400-m pace due to a higher stroke frequency at sprint pace (sprint: 0.95 strokes·s; 400 m: 0.70 strokes·s). These findings imply that torques acting to rotate the upper torso and the lower torso are greater at sprint than 400-m pace. Dry-land strength training specificity can be improved by designing exercises that challenge the torso muscles to reproduce the torques required to generate the longitudinal kinematics in front crawl. [ABSTRACT FROM AUTHOR]

Active drag force in swimming can be calculated from a function of five different variables: swim velocity, tow velocity, belt force, power output and exponent of velocity. The accuracy of the drag force value is dependent on the accuracy of each variable, and on the contribution of each variable to drag estimation. To calculate uncertainty in drag value, first the derivatives of the active drag equation with respect to each variable were obtained. Second, these were multiplied by the uncertainty of that variable. Twelve national age and open level swimmers were recruited to complete four free swimming and five active drag trials. The uncertainties for the free and the tow swim velocities, and for the belt force, contributed approximately 5–6% and 2–3% error, respectively, in calculation of drag. The result of the uncertainty of the velocity exponent (1.8–2.6) indicated a contribution of about 6% error in active drag. The contribution of unequal power output showed that if a power changed 7.5% between conditions, it would lead to about 30% error in calculated drag. Consequently, if a swimmer did not maintain constant power output between conditions, there would be substantial errors in the calculation of active drag. [ABSTRACT FROM AUTHOR]

The reliability of active drag values was examined using a method that compared free swim speed with measurements taken by towing swimmers slightly faster than their maximum swim speed, while allowing their intra-stroke speed fluctuations. Twelve national age and open level swimmers were tested on two alternate days (Day 1 and Day 2). All participants completed four maximum swim speed, three passive drag and five active drag trials on each of the days. The reliability was determined using within-participant intra-class correlation coefficients (ICC) within each day and between the days. The ICCs for Day 1 and Day 2 were 0.82 and 0.85, respectively, while the comparison of the mean active drag values between days was 0.93. The data showed that the assisted towing method (ATM) with fluctuating speed was only moderately reliable within a single test. However, this method was more reliable when using the average value of active drag from both days (ICC = 0.93). This study identified that the ATM method with fluctuating speed had moderate reliability within-participant trials on values in a single day but high reliability for the average active drag values across different days. [ABSTRACT FROM AUTHOR]