This study aimed to validate a simple field method for determining force- and power-velocity relationships and mechanical effectiveness of force application during sprint running. The proposed method, based on an inverse dynamic approach applied to the body center of mass, estimates the step-averaged ground reaction forces in runner's sagittal plane of motion during overground sprint acceleration from only anthropometric and spatiotemporal data. Force- and power-velocity relationships, the associated variables, and mechanical effectiveness were determined (a) on nine sprinters using both the proposed method and force plate measurements and (b) on six other sprinters using the proposed method during several consecutive trials to assess the inter-trial reliability. The low bias (<5%) and narrow limits of agreement between both methods for maximal horizontal force (638 ± 84 N), velocity (10.5 ± 0.74 m/s), and power output (1680 ± 280 W); for the slope of the force-velocity relationships; and for the mechanical effectiveness of force application showed high concurrent validity of the proposed method. The low standard errors of measurements between trials (<5%) highlighted the high reliability of the method. These findings support the validity of the proposed simple method, convenient for field use, to determine power, force, velocity properties, and mechanical effectiveness in sprint running.

The objective of this study was to characterize the mechanics of maximal running sprint acceleration in high-level athletes. Four elite (100-m best time 9.95-10.29 s) and five sub-elite (10.40-10.60 s) sprinters performed seven sprints in overground conditions. A single virtual 40-m sprint was reconstructed and kinetics parameters were calculated for each step using a force platform system and video analyses. Anteroposterior force (FY), power (PY), and the ratio of the horizontal force component to the resultant (total) force (RF, which reflects the orientation of the resultant ground reaction force for each support phase) were computed as a function of velocity (V). FY-V, RF-V, and PY-V relationships were well described by significant linear (mean R(2) of 0.892 ± 0.049 and 0.950 ± 0.023) and quadratic (mean R(2) = 0.732 ± 0.114) models, respectively. The current study allows a better understanding of the mechanics of the sprint acceleration notably by modeling the relationships between the forward velocity and the main mechanical key variables of the sprint. As these findings partly concern world-class sprinters tested in overground conditions, they give new insights into some aspects of the biomechanical limits of human locomotion.

Force application technique is a determinant factor of field 100-m sprint performance, which is not the case for the amount of total force subjects are able to apply onto the ground. It seems that the orientation of the total force applied onto the supporting ground during sprint acceleration is more important to performance than its amount.

High ballistic performances are determined by both maximization of the power output capabilities and optimization of the F-v mechanical profile of the lower limb neuromuscular system.

Recent studies have brought new insights into the evaluation of power-force-velocity profiles in both ballistic push-offs (eg, jumps) and sprint movements. These are major physical components of performance in many sports, and the methods the authors developed and validated are based on data that are now rather simple to obtain in field conditions (eg, body mass, jump height, sprint times, or velocity). The promising aspect of these approaches is that they allow for more individualized and accurate evaluation, monitoring, and training practices, the success of which is highly dependent on the correct collection, generation, and interpretation of athletes' mechanical outputs. The authors therefore wanted to provide a practical vade mecum to sports practitioners interested in implementing these power-force-velocity-profiling approaches. After providing a summary of theoretical and practical definitions for the main variables, the authors first detail how vertical profiling can be used to manage ballistic push-off performance, with emphasis on the concept of optimal force-velocity profile and the associated force-velocity imbalance. Furthermore, they discuss these same concepts with regard to horizontal profiling in the management of sprinting performance. These sections are illustrated by typical examples from the authors' practice. Finally, they provide a practical and operational synthesis and outline future challenges that will help further develop these approaches.

Sprint mechanics and field 100-m performances were tested in 13 subjects including 9 non-specialists, 3 French national-level sprinters and a world-class sprinter, to further study the mechanical factors associated with sprint performance. 6-s sprints performed on an instrumented treadmill allowed continuous recording of step kinematics, ground reaction forces (GRF), and belt velocity and computation of mechanical power output and linear force-velocity relationships. An index of the force application technique was computed as the slope of the linear relationship between the decrease in the ratio of horizontal-to-resultant GRF and the increase in velocity. Mechanical power output was positively correlated to mean 100-m speed (P < 0.01), as was the theoretical maximal velocity production capability (P < 0.011), whereas the theoretical maximal force production capability was not. The ability to apply the resultant force backward during acceleration was positively correlated to 100-m performance (r (s) > 0.683; P < 0.018), but the magnitude of resultant force was not (P = 0.16). Step frequency, contact and swing time were significantly correlated to acceleration and 100-m performance (positively for the former, negatively for the two latter, all P < 0.05), whereas aerial time and step length were not (all P > 0.21). Last, anthropometric data of body mass index and lower-limb-to-height ratio showed no significant correlation with 100-m performance. We concluded that the main mechanical determinants of 100-m performance were (1) a "velocity-oriented" force-velocity profile, likely explained by (2) a higher ability to apply the resultant GRF vector with a forward orientation over the acceleration, and (3) a higher step frequency resulting from a shorter contact time.

Ballistic performances are determined by both the maximal lower limb power output (Pmax) and their individual force-velocity (F-v) mechanical profile, especially the F-v imbalance (FVimb): difference between the athlete's actual and optimal profile. An optimized training should aim to increase Pmax and/or reduce FVimb. The aim of this study was to test whether an individualized training program based on the individual F-v profile would decrease subjects' individual FVimb and in turn improve vertical jump performance. FVimb was used as the reference to assign participants to different training intervention groups. Eighty four subjects were assigned to three groups: an “optimized” group divided into velocity-deficit, force-deficit, and well-balanced sub-groups based on subjects' FVimb, a “non-optimized” group for which the training program was not specifically based on FVimb and a control group. All subjects underwent a 9-week specific resistance training program. The programs were designed to reduce FVimb for the optimized groups (with specific programs for sub-groups based on individual FVimb values), while the non-optimized group followed a classical program exactly similar for all subjects. All subjects in the three optimized training sub-groups (velocity-deficit, force-deficit, and well-balanced) increased their jumping performance (12.7 ± 5.7% ES = 0.93 ± 0.09, 14.2 ± 7.3% ES = 1.00 ± 0.17, and 7.2 ± 4.5% ES = 0.70 ± 0.36, respectively) with jump height improvement for all subjects, whereas the results were much more variable and unclear in the non-optimized group. This greater change in jump height was associated with a markedly reduced FVimb for both force-deficit (57.9 ± 34.7% decrease in FVimb) and velocity-deficit (20.1 ± 4.3%) subjects, and unclear or small changes in Pmax (−0.40 ± 8.4% and +10.5 ± 5.2%, respectively). An individualized training program specifically based on FVimb (gap between the actual and optimal F-v profiles of each individual) was more efficient at improving jumping performance (i.e., unloaded squat jump height) than a traditional resistance training common to all subjects regardless of their FVimb. Although improving both FVimb and Pmax has to be considered to improve ballistic performance, the present results showed that reducing FVimb without even increasing Pmax lead to clearly beneficial jump performance changes. Thus, FVimb could be considered as a potentially useful variable for prescribing optimal resistance training to improve ballistic performance.

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