PURPOSE: To ascertain whether force-velocity-power relationships could be compiled from a battery of sled-resisted overground sprints and to clarify and compare the optimal loading conditions for maximizing power production for different athlete cohorts. METHODS: Recreational mixed-sport athletes (n = 12) and sprinters (n = 15) performed multiple trials of maximal sprints unloaded and towing a selection of sled masses (20-120% body mass [BM]). Velocity data were collected by sports radar, and kinetics at peak velocity were quantified using friction coefficients and aerodynamic drag. Individual force-velocity and power-velocity relationships were generated using linear and quadratic relationships, respectively. Mechanical and optimal loading variables were subsequently calculated and test-retest reliability assessed. RESULTS: Individual force-velocity and power-velocity relationships were accurately fitted with regression models (R2 > .977, P < .001) and were reliable (ES = 0.05-0.50, ICC = .73-.97, CV = 1.0-5.4%). The normal loading that maximized peak power was 78% ± 6% and 82% ± 8% of BM, representing a resistance of 3.37 and 3.62 N/kg at 4.19 ± 0.19 and 4.90 ± 0.18 m/s (recreational athletes and sprinters, respectively). Optimal force and normal load did not clearly differentiate between cohorts, although sprinters developed greater maximal power (17.2-26.5%, ES = 0.97-2.13, P < .02) at much greater velocities (16.9%, ES = 3.73, P < .001). CONCLUSIONS: Mechanical relationships can be accurately profiled using common sled-training equipment. Notably, the optimal loading conditions determined in this study (69-96% of BM, dependent on friction conditions) represent much greater resistance than current guidelines (~7-20% of BM). This method has potential value in quantifying individualized training parameters for optimized development of horizontal power.
PURPOSE: To ascertain whether force-velocity-power relationships could be compiled from a battery of sled-resisted overground sprints and to clarify and compare the optimal loading conditions for maximizing power production for different athlete cohorts. METHODS: Recreational mixed-sport athletes (n = 12) and sprinters (n = 15) performed multiple trials of maximal sprints unloaded and towing a selection of sled masses (20-120% body mass [BM]). Velocity data were collected by sports radar, and kinetics at peak velocity were quantified using friction coefficients and aerodynamic drag. Individual force-velocity and power-velocity relationships were generated using linear and quadratic relationships, respectively. Mechanical and optimal loading variables were subsequently calculated and test-retest reliability assessed. RESULTS: Individual force-velocity and power-velocity relationships were accurately fitted with regression models (R2 > .977, P < .001) and were reliable (ES = 0.05-0.50, ICC = .73-.97, CV = 1.0-5.4%). The normal loading that maximized peak power was 78% ± 6% and 82% ± 8% of BM, representing a resistance of 3.37 and 3.62 N/kg at 4.19 ± 0.19 and 4.90 ± 0.18 m/s (recreational athletes and sprinters, respectively). Optimal force and normal load did not clearly differentiate between cohorts, although sprinters developed greater maximal power (17.2-26.5%, ES = 0.97-2.13, P < .02) at much greater velocities (16.9%, ES = 3.73, P < .001). CONCLUSIONS: Mechanical relationships can be accurately profiled using common sled-training equipment. Notably, the optimal loading conditions determined in this study (69-96% of BM, dependent on friction conditions) represent much greater resistance than current guidelines (~7-20% of BM). This method has potential value in quantifying individualized training parameters for optimized development of horizontal power.
Keywords:
horizontal force; mechanical profiling; sprint training
Authors: Matt R Cross; Pierre Samozino; Scott R Brown; Johan Lahti; Pedro Jimenez-Reyes; Jean-Benoît Morin Journal: Sports Med Date: 2019-02 Impact factor: 11.136
Authors: Matt R Cross; Johan Lahti; Scott R Brown; Mehdi Chedati; Pedro Jimenez-Reyes; Pierre Samozino; Ola Eriksrud; Jean-Benoit Morin Journal: PLoS One Date: 2018-04-11 Impact factor: 3.240
Authors: Johan Lahti; Pedro Jiménez-Reyes; Matt R Cross; Pierre Samozino; Patrick Chassaing; Benjamin Simond-Cote; Juha Ahtiainen; Jean-Benoit Morin Journal: Sports (Basel) Date: 2020-05-25