Force-Velocity Profiles of Elite Athletes Tested on a Cycle Ergometer

Predrag R. Bozic; Bobana Berjan Bacvarevic

Predrag R. Bozic^1,2, Bobana Berjan Bacvarevic²

¹Serbian Institute of Sport and Sports Medicine, Belgrade, Serbia
²University of Montenegro, Faculty for Sport and Physical Education, Niksic, Montenegro

Force-Velocity Profiles of Elite Athletes Tested on a Cycle Ergometer

Monten. J. Sports Sci. Med. 2018, 7(1), 59-66 | DOI: 10.26773/mjssm.180308

Abstract

The present study explored the sensitivity of the force-velocity (F-V) modelling approach obtained from maximal sprints on a leg cycle ergometer to detect selective changes of the mechanical capacities of the lower body muscles associated with high-level training. Specifically, we assumed that the F-V relationship parameters, such as maximum force (F₀), velocity (V₀), power (P_M) and slope, would differ among individuals of different high-level training backgrounds. In total, 111 elite athletes divided into four groups (Combat sports, Athletic sprints, Team sports and Physically active) performed maximal sprints on a leg cycle ergometer loaded with 7%, 9%, and 11% of body weight. The findings obtained suggest an exceptionably strong and linear F-V relationship in most of the participants (r > 0.95), while higher P_M have been found in all groups of athletes compared to the Physically active group (p < 0.05). In addition, sport-specific F-V profiles have been observed in athletes that belong to distinctively different sports (i.e. higher F₀ and force-oriented slope for strength-trained Combat sports and higher V₀ for speed-trained Athletic sprints). To our knowledge, this is one of the rare studies that evaluate the F-V profiles with such a large sample of elite athletes obtained from commonly used task such as maximal sprints on a leg cycle ergometer. The results obtained support a high sensitivity of the F-V modelling approach to distinguish among elite athletes with different training histories.

Keywords

sprint cycling test, force-velocity relationship, sensitivity, linear regression, elite athletes

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