Predictive Factors of Elite Sprint Performance: Influences of Muscle Mechanical Properties and Functional Parameters. Issue 4 (April 2019)

• Record Type: Journal Article
• Authors: Loturco, Irineu; Kobal, Ronaldo; Kitamura, Katia; Fernandes, Victor; Moura, Neilton; Siqueira, Felipe; Cal Abad, César C.; Pereira, Lucas A.
• Is Part Of: Journal of strength and conditioning research. Volume 33:Issue 4(2019)
• Publication Date: 2019-04
• Subjects: acceleration -- power output -- Olympic athletes -- top-speed -- muscle mechanical properties; Physical education and training -- Periodicals; Weight training -- Physiological aspects -- Periodicals; Physical fitness -- Periodicals; 613.7
• DOI: 10.1519/JSC.0000000000002196
• Languages: English
• ISSNs: 1064-8011

Abstract

Abstract : Abstract: Loturco, I, Kobal, R, Kitamura, K, Fernandes, V, Moura, N, Siqueira, F, Cal Abad, CC, and Pereira, LA. Predictive factors of elite sprint performance: influences of muscle mechanical properties and functional parameters. J Strength Cond Res 33(4): 974–986, 2019—Sprint performance relies on many different mechanical and physiological factors. The purpose of this study was to identify, among a variety of strength-power exercises and tensiomyography (TMG) parameters, the best predictors of maximum running speed in elite sprinters and jumpers. To test these relationships, 19 power track and field athletes, 4 long jumpers, and 15 sprinters (men: 12; 22.3 ± 2.4 years; 75.5 ± 8.3 kg; 176.5 ± 5.6 cm; women: 7; 23.8 ± 4.2 years; 56.9 ± 5.4 kg; 167.4 ± 5.8 cm) were assessed using different intensities of TMG-derived velocity of contraction (Vc), squat and countermovement jumps, drop jump at 45 and 75 cm; and a 60-meter sprint time. In addition, the mean propulsive power (MPP) and peak power (PP) outputs were collected in the jump squat (JS) and half-squat (HS) exercises. Based on the calculations of the Vc at 40 mA, the athletes were divided (by median split analysis) into 2 groups: higher and lower Vc 40 mA groups. The magnitude-based inference method was used to compare the differences between groups. The correlations between mechanical and functional measures were determined using the Pearson's test. A multiple regression analysis was performed to predict sprint performance, using the Vc at 40 mA, jump heights, and JS and HS power outputs as independent variables. The higher Vc 40 mA group demonstrated likely better performances than the lower Vc 40 mA group in all tested variables. Large to nearly perfect significant correlations were found between sprint time, jump heights, and power outputs in both JS and HS exercises. Notably, the Vc 40 mA associated with the vertical jump height and MPP in JS explained >70% of the shared variance in sprint times. In conclusion, it was found that faster athletes performed better in strength-power tests, in both loaded and unloaded conditions, as confirmed by the strong correlations observed between speed and power measures. Lastly, the Vc also showed a marked selective influence on sprint and power capacities. These findings reinforce the notion that maximum running speed is a very complex physical capacity, which should be assessed and trained using several methods and training strategies.