Article

A simple method for measuring power, force, velocity properties, and mechanical effectiveness in sprint running: Simple method to compute sprint mechanics

Authors:
To read the full-text of this research, you can request a copy directly from the authors.

Abstract

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. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

No full-text available

Request Full-text Paper PDF

To read the full-text of this research,
you can request a copy directly from the authors.

... The performance from the 5th to the 6th sprint compared with the 1 st sprint was more reduced in the hamstring group and it indicates that performance is more impaired in a situation of fatigue in the hamstring group. This agrees with a previous a study [66], which showed a larger decrease in performance in soccer players reporting former hamstring strain injury during an RSA (8 × 20 m) [66]. In this sense, other authors [67] observed a lower biceps femoris activity in the previously injured limb during the final phase of the sprint [68]. ...
... The performance from the 5th to the 6th sprint compared with the 1 st sprint was more reduced in the hamstring group and it indicates that performance is more impaired in a situation of fatigue in the hamstring group. This agrees with a previous a study [66], which showed a larger decrease in performance in soccer players reporting former hamstring strain injury during an RSA (8 × 20 m) [66]. In this sense, other authors [67] observed a lower biceps femoris activity in the previously injured limb during the final phase of the sprint [68]. ...
... Moreover, it has been shown that female soccer players with less hamstring flexibility have a higher risk of hamstring injury [47]. In contrast, and coinciding with the results obtained in this study, other authors pointed out that ballistic hamstring flexibility evaluated using the hamstring test seems to be unaffected by fatigue [66]. ...
Article
Full-text available
Sprinting is a fundamental component of the professional soccer player's ability to achieve the highest performance in the sport. The aim of this study was to analyze the influence of hamstring injury history on the neuromuscular fatigue produced by an RSA test in elite female football players. Nineteen female elite soccer players of the Second Spanish Soccer Division participated in the study. The participants were divided into: (1) a Control group who have not suffered previous muscular injuries and (2) a Hamstring group with previous hamstring injury at least one season prior to the protocol. The players performed a protocol consisting of a Repeat Sprint Ability Test (RSA) (6 × 40 m; 30 s rest), and CMJ and Hamstring tests before and after the RSA. The different variables of the study were compared between groups with a two-way ANOVA for repeated measures. The main findings from the present study were that, in subjects with previous hamstring injury, the performance was impaired compared with the control group: (1) in the initial meters of the sprint during an RSA there was a higher percentage difference between SprintTT and ideal Split in 0-10 m compared to 0-20 m in the hamstring group (p = 0.006; ES = 0.51); and in situations of high fatigue there was a higher %Dif1vs6 compared to %Dif1vs5 (percentage difference between the first sprint and fifth sprint) in the hamstring group (p = 0.005; ES = 0.54) compared with the control group. It seems that in elite female soccer players with previous hamstring injury, RSA-induced fatigue produces a greater decrease in the performance in the first 10 m of the sprint compared to the control uninjured players.
... The ratio between F H 0 and v H 0 corresponds to the athlete's mechanical F-v profile (S Fv , slope of the F-v linear relationship). 12,20 Interestingly, as for vertical jumping, 21 two athletes can present very different F-v profiles with the same maximal power capability (P H max). Among these different force production capacities, scientists, coaches or athletes wonder which one is more important (if any) for sprint running acceleration performance (mostly quantified through time to cover a given distance)? ...
... This section, associated with the first aim, is an analysis of kinematics and kinetics of the runner's body CoM during a linear sprinting acceleration starting from null velocity using a macroscopic inverse dynamics approach aiming to be the simplest possible and only focusing on the net stepaveraged horizontal component of the external force (and associated power output). 20,26 All variables presented in this section are modelled over time, without considering intra-step changes, and thus correspond to step-averaged values (over contact plus subsequent aerial times). ...
... Sprinting F-v relationship has been hitherto experimentally described by a linear regression. 8,9,20 Equation (7) shows here that, when velocity-time curve during a sprint acceleration is described by a mono-exponential function (Equation (1)), 20,27 the F-v relationships follows a 2nd order polynomial function, with a viscosity component associated with aerodynamic resistance. The Root Mean Square Error (RMSError) in F H , as well as the differences in F H 0 and v H 0, between values obtained by the 2nd order polynomial function (Equations (7), (8) and (10)) and values obtained by a linear regression fitting of the values obtained by this polynomial function, were computed on different simulated sprints characterizing individuals with different k (from 0.0025 to 0.0044 N s² m −2 kg −1 , increment step of 0.0001), v H max (from 5 to 12 m s −1 , increment step of 1) and (from 0.8 to 1.5 s, increment step of 0.1) values. ...
Article
Full-text available
The aim was to determine the respective influences of sprinting maximal power output (PHmax) and mechanical Force‐velocity (F‐v) profile (i.e. ratio between horizontal force production capacities at low and high velocities) on sprint acceleration performance. A macroscopic biomechanical model using an inverse dynamics approach applied to the athlete’s centre of mass during running acceleration was developed to express the time to cover a given distance as a mathematical function of PHmax and F‐v profile. Simulations showed that sprint acceleration performance depends mainly on PHmax, but also on the F‐v profile, with the existence of an individual optimal F‐v profile corresponding, for a given PHmax, to the best balance between force production capacities at low and high velocities. This individual optimal profile depends on PHmax and sprint distance: the lower the sprint distance, the more the optimal F‐v profile is oriented to force capabilities and vice versa. When applying this model to the data of 231 athletes from very different sports, differences between optimal and actual F‐v profile were observed and depend more on the variability in the optimal F‐v profile between sprint distances than on the interindividual variability in F‐v profiles. For a given sprint distance, acceleration performance (<30 m) mainly depends on PHmax and slightly on the difference between optimal and actual F‐v profile, the weight of each variable changing with sprint distance. Sprint acceleration performance is determined by both maximization of the horizontal power output capabilities and the optimization of the mechanical F–v profile of sprint propulsion.
... The fitness testing batteries used provide the performance values based on the vertical (jumping) and horizontal (sprinting) application of strength. Interestingly, investigations have suggested that the maximal power output (Pmax) resultant by the product between force (F0) and velocity (V0), is key for jumping and sprinting performance Samozino et al., 2016;Samozino, Rejc, Di Prampero, Belli, & Morin, 2012) and moreover, the production of horizontal force during sprinting has been identified as an injury-related factor (Mendiguchia et al., 2016(Mendiguchia et al., , 2014. However, to the best of our knowledge, no investigations have observed the mechanical variables underlying during sprinting and jumping in netball players. ...
... Validated field methods developed in recent years provide a macroscopic view about the mechanical outputs during jumping (Jiménez-Reyes, Samozino, Pareja-Blanco, et al., 2017;Samozino et al., 2012) and sprinting performance (P. Samozino et al., 2016). These approaches quantify the relationship between force-velocitypower (FVP) spectrum . ...
... The smartphone was placed on a tripod 20m from the track (frontal plane) using My Sprint, following previous recommendations (Romero-Franco et al., 2017). The best time of the three attempts was selected for the analysis of the split times (5, 10, 15 and 20m) and mechanical properties (F 0 , V 0 , P max , Sfv, RF max and D rf) Samozino et al., 2016). ...
Article
Full-text available
Netball is a collective sport characterized by intermittent high-intensity actions. Therefore, the players must develop high levels of relative bilateral and unilateral strength and power for both improve performance and also reduce injury risk. The purpose of this study was (i) to provide a reference about the mechanical outputs obtained in the vertical (jumping) and horizontal force-velocity-power (FVP) profile and (ii) observe their relationship, besides the performance in jumping and sprinting in amateur female netball players (age = 24.3 +/- 3.2 years, BM = 64.5 +/- 5 Kg, height = 172.5 +/- 6.2 cm). The variables for both FVP profiles (theoretical maximal force (F-0), theoretical maximal velocity (V-0) and theoretical maximal power output (P-max)) were measured with two scientifically validated apps for iOS (My Jump 2 and My Sprint). Our results in regards to the vertical FVP suggest that netball players have low force deficit (36.2 +/- 14.6%) and individualized training based on F-V profiling could be beneficial to address their deficit. The moderate correlations found for performance, V-0 and P-max suggest that the improvement in one of the skills (jumping or sprinting) may produce some positive adaptation to the other. However, no association was found in the force production (F-0) of the lower limbs for both FVP. Therefore, we recommend that netball players must train specifically ballistic actions in the vertical (jumping) and horizontal direction (sprinting) due to the specificity of both skills and the consequent impact of them on netball performance.
... The data file for each trial together with the body height and mass of each participant were imported to Lab-View (Version 13, National Instruments Corporation, TX, USA) software, which was used to calculate all outcome variables according to Samozino's method [18]: maximal theoretical horizontal force (F0), maximal theoretical horizontal velocity (V0), maximal theoretical horizontal power (P max ), the slope of the F-V relationship (Sfv), decrease in the ratio of horizontal to resultant force (DRF), peak ratio of horizontal to resultant force (RF peak ), and split times between 0 and 20 m (5-m, 10-m, and 20-m splits were used for further analysis). For reliability analysis, the coefficient of variation (CV) and intraclass coefficient correlation (ICC) were calculated using a custom-made spreadsheet available online [19]. The thresholds for interpreting ICC values were: 0.2 ÷ 0.49 (low), 0.5 ÷ 0.74 (moderate), 0.75 ÷ 0.89 (high), 0.90 ÷ 0.98 (very high), and > 0.99 (extremely high) [20]. ...
... Additionally, the Cohen's d effect size (ES) with 95% confidence interval was evaluated to compare sprint mechanical profiles (F0, V0, Sfv, DRF, RF peak , P max ) and sprint performance (time at 5 m, time at 10 m, time at 20 m) between skill levels. The criteria for interpreting ES values were as follows: trivial (< 0.2), small (0.2 ÷ 0.6), moderate (0.6 ÷ 1.2), and large (> 1.2) [19]. The relationship between mechanical parameters and sprint performance variables was evaluated using the Pearson correlation coefficient (level of significance was set at p < 0.05) with 95% confidence intervals. ...
... , very large (0.7 ÷ 0.9), and almost perfect (0.9 ÷ 1.0) [19]. The main interpretation of statistical analyses was based upon confidence intervals, effect sizes, and practical significance [20]. ...
Article
Full-text available
Aim: The purpose of the present study was to evaluate the relationships between sprint mechanical parameters and sprint performance among female soccer players at different skill levels. Materials and methods: Sixty-six female soccer players (age = 23.1 ± 5.1 years) performed a 30-m sprint to assess sprint performance and mechanical variables. Speed was measured by radar technology for 5, 10, 20, and 30 m and was used to calculate the theoretical maximal velocity (V0), theoretical maximal horizontal force (F0), maximal horizontal power (Pmax), decrease in the ratio of horizontal to resultant force (DRF), and p eak ratio of horizontal to resultant force (RFpeak). Results: Different force-velocity (F-V) profile parameters are determinants of sprint performance at various distances. RFpeak (r = -0.99), Pmax (r = -0.93), and F0 (r = 0.92) had the strongest associations with sprint performance at shorter (5-m) distances, while at longer (20-m) distances, V0 (r = -0.73), Pmax (r = -0.94), and RFpeak (r = -0.88) were largely associated with sprint performance. Conclusion: The results of this study show that as the skill level in female soccer players increases, an increase in maximal theoretical horizontal force during sprinting can be observed.
... These variables can be calculated through linear regression over a distance of 30 m [10]. In addition, the F-V profile in sprinting includes the percentage of the resultant force that is generated in the horizontal direction [11], with the decrease in the ratio of horizontal-to-resultant force (DRF) and the maximal ratio of horizontal-to-resultant force (RF peak ) typically used to assess mechanical effectiveness and sprint performance [12]; their use has been shown to be reliable in adolescents [13]. These components can be expressed as absolute or relative to body dimensions [9], with the latter being commonly used to control for the independent effect of body mass (BM), assuming a linear relationship between size and strength (i.e., watt·kg −1 ) [14,15]. ...
... A cross-sectional design was implemented to compare the main components of the force-velocity profile in sprint (i.e., F 0 , V 0 , P max , DRF and RF peak ) and performance variables (5, 20, and 30 m sprint time) among different maturation statuses in young soccer players, through Samozino's method [11]. These variables were then categorized according to different maturation status to assess the effect of maturity offset on the components of the sprint F-V profile. ...
... Two independent observers were asked to select the first frame in which participants' right thumb left the ground (start of the sprint) and, subsequently, the frame in which the pelvis was aligned with the 6 different markers for each of the 124 recorded sprints using the MySprint app [10]. Split time and velocity-time data were used by the MySprint app along with participants' BM and body height as inputs to calculate F 0 , V 0 , P max , RF peak , and DRF, according to Samozino's method [10,11]. ...
Article
Full-text available
The aim of the present study was to determine the influence of maturation status on the components of the sprint force-velocity (F-V) profile in young soccer players. Sixty-two male young soccer players from the same professional soccer academy took part in the present study. A cross-sectional design was implemented to compare the main components of the sprint F-V profile (i.e., maximal theoretical force [F0] velocity [V0], power [Pmax], and ratio of horizontal-to-resultant force [RFpeak], and decrease in the ratio of horizontal-to-resultant force [DRF]) and sprint performance (5-, 20- and 30-m sprint time) among participants’ maturation stages (i.e., pre-, mid- and post-peak height velocity [PHV] groups). Results show that ES of differences in 5-m sprint performance, F0 and RFpeak (i.e., strength- and acceleration-related components of the sprint F-V profile) were greater between pre- and mid-PHV groups than those between mid- and post-PHV groups (i.e., large and very large effects [1.24 ≤ ES ≤ 2.42] vs. moderate, small and zero effects [0 ≤ ES ≤ 0.69], respectively). However, ES of differences in V0 and DRF (i.e., peak speed-related components of the sprint F-V profile) were greater between mid- and post-PHV groups than those between pre- and mid-PHV groups (i.e., large effects [1.54 ≤ ES ≤ 1.92] vs. moderate effects [-0.59 ≤ ES ≤ 1], respectively). Once the strength development is achieved to a great extent from the pre- to mid-PHV groups, specific strength training methods may be considered to be used in young soccer players to improve their sprint performance.
... Spatio-temporal measurement of athlete sprint running performance is frequently used by coaches and sport scientists used to determine the horizontal force-velocity (F-v) relationship during sprint running. [7][8][9] A Stalker ATS radar device (Applied Concepts, Dallas, TX, USA), which can be used to record velocity-time data during sprint running at 46.875 Hz, is often the technology of choice to calculate the horizontal F-v relationship 10 and has been used in research with sprint, 4 rugby, 11,12 and soccer 9 athletes. The intraday reliability 9,13 and validity of the technology to measure velocity 13 and split times 14,15 have been previously confirmed. ...
... [7][8][9] A Stalker ATS radar device (Applied Concepts, Dallas, TX, USA), which can be used to record velocity-time data during sprint running at 46.875 Hz, is often the technology of choice to calculate the horizontal F-v relationship 10 and has been used in research with sprint, 4 rugby, 11,12 and soccer 9 athletes. The intraday reliability 9,13 and validity of the technology to measure velocity 13 and split times 14,15 have been previously confirmed. ...
... From this final exponential fit, time constant tau and horizontal maximal velocity (V Hmax ) were obtained, and then the variables of theoretical maximum velocity (V 0 ); theoretical maximum horizontal force (F 0 ), peak power (P max ), and slope of the F-v profile (S FV ; expressed relatively to body mass) were computed following the method previously proposed and validated. 8,9 Statistical analysis Means and standard deviations were calculated to represent the centrality and spread of the calculated variables. The variables calculated from the 1080 Sprint velocity-time data were compared to the variables calculated from the radar by determining the bias (mean measurement difference between the devices, 1080 Sprint -Radar) and random error (1.96 × standard deviation of the differences between the devices), and the 95% limits of agreement. ...
Article
This study established the magnitude of systematic bias and random error of horizontal force-velocity (F-v) profile variables obtained from a 1080 Sprint compared to that obtained from a Stalker ATS II radar device. Twenty high-school athletes from an American football training group completed a 30 m sprint while the two devices simultaneously measured velocity-time data. The velocity-time data were modelled by an exponential equation fitting process and then used to calculate individual F-v profiles and related variables (theoretical maximum velocity, theoretical maximum horizontal force, slope of the linear F-v profile, peak power, time constant tau, and horizontal maximal velocity). The devices were compared by determining the systematic bias and the 95% limits of agreement (random error) for all variables, both of which were expressed as percentages of the mean radar value. All bias values were within 6.32%, with the 1080 Sprint reporting higher values for tau, horizontal maximal velocity, and theoretical maximum velocity. Random error was lowest for velocity-based variables but exceeded 7% for all others, with slope of the F-v profile being greatest at ±12.3%. These results provide practitioners with the information necessary to determine if the agreement between the devices and the magnitude of random error is acceptable within the context of their specific application.
... The maximal amount of force produced by the neuromuscular system during sprinting depends on the running velocity . The mutual dependency among force, velocity, and power producing capacities of leg muscles could be well described using the inverse linear force-velocity (F-v) and the parabolic power-velocity (P-v) relationships (Morin et al., 2011(Morin et al., , 2019Samozino et al., 2016). During the sprint acceleration phase, the F-v and P-v relationships characterize the change in the athlete's maximal horizontal force and power production capabilities when the running velocity increases. ...
... During the sprint acceleration phase, the F-v and P-v relationships characterize the change in the athlete's maximal horizontal force and power production capabilities when the running velocity increases. Sprinter's theoretical maximum power output (P max ), theoretical maximum horizontal force (F 0 ), theoretical maximum horizontal velocity (V 0 ), the ratio of the total force production which directed in the horizontal direction (RF max ) and the decrease in the ratio of horizontal force as the running velocity increased (DRF), can be easily estimated using established field methods (Morin et al., 2011(Morin et al., , 2019Samozino et al., 2016). These variables are key determinant factors for sprint-acceleration performance . ...
... Whilst very recent research has offered an informative and comprehensive account on this topic by also including analysis of the maximum velocity phase (Gleadhill & Nagahara, 2021) the need to understand the interaction between performance level and mechanical qualities is key to our understanding of the individuality nature of mechanical profiles. To this end, we adopted the power-force-velocity profiling method (Morin et al., 2019;Samozino et al., 2016) alongside kinematic analysis to compare the physical, functional and performance differences between national female track and field champions and low-level female competitors. This information enriches the existing sprinting literature on female sprinting and provides a better insight into performance determinants affecting acceleration rates in female athletes. ...
Article
Full-text available
The current study examines the sprint mechanical and kinematic characteristics between national female track and field champions (NC) and lower-level female competitors (LL). Sixteen female athletes (8 National Champions, 8 Lower-level competitors) participated in this investigation. The testing procedures consisted of two maximal 30-m sprints. The velocity-time data, captured by three high-speed cameras, was used to calculate the variables of the horizontal F-v profile (theoretical maximal values of force [F0], velocity [V0], power [Pmax], the proportion of the theoretical maximal effectiveness of force application in the antero-posterior direction [RFmax], the rate of decrease in the ratio of horizontal force [DRF]) and essential kinematics characteristics. The NC female athletes showed higher values for Pmax (t = 3.26, p = 0.006), V0 (t = 6.27, p = 0.000) and RFmax (t = 2.58, p = 0.022) compared to LL female competitors. No statistical differences were observed for F0 (t = 1.027, p = 0.32) and DRF (t = 0.917, p = 0.375). Mean running velocity, step frequency and contact time were higher in all but one (0-5 m) 5-m distance intervals of the 30-m sprint. No differences were found in the mean step length, relative step length and flight time in the intervals (0-5, 5-10, 10-15, 15-20, 20-25, and 25-30 m). The faster female athletes in our study demonstrated the capacity to reach superior running velocities, develop larger horizontal forces at higher velocities, apply more effectively the force on the ground in the acceleration phase, show higher values of step frequencies and spent less time in contact with the ground than slower athletes.
... The F-v relationship of the lower limb in extension movements can be assessed by two main methodologies. The first method consists of the measurement of force and velocity at each repetition over an all-out effort using cyclic movements, such as running (Lakomy 1987;Samozino et al. 2016) or cycling (Lakomy 1986;Arsac et al. 1996). The second method requires force and velocity measurements over one ballistic extension in two to six resistive-loading conditions using acyclic movements, such as jumping (Bosco and Komi 1979;Jaric 2016) or lower limb extension on an inclined or horizontal leg press Meylan et al. 2015;Janicijevic et al. 2018). ...
... The second method requires force and velocity measurements over one ballistic extension in two to six resistive-loading conditions using acyclic movements, such as jumping (Bosco and Komi 1979;Jaric 2016) or lower limb extension on an inclined or horizontal leg press Meylan et al. 2015;Janicijevic et al. 2018). If the F-v relationships have been described over a wide range of experimental velocity values of ~20 to ~90 % of v0 in movements involving cyclic lower limb extensions Rabita et al. 2015b;Samozino et al. 2016), the range of experimental velocity used to determine the F-v relationship using acyclic movements has been shown to be more restricted, notably with a lack of data at high velocities. Indeed, in the high force-low velocity conditions (i.e. ...
... We theorized that lower limb extension performed without moving the body and with assistance would lead to substantial higher movement velocity, because the lower limb mass is about three-fold inferior than the body mass (Winter 2009) and that the spring assistance would help to overcome the remaining irreducible inertia of the lower limb. We hypothesized that the linear modelling of the F-v relationship would present a very high quality, including the extreme experimental points on the velocity end, as confirmed in cyclic lower limb movements Samozino et al. 2016;Cross et al. 2018) ...
Thesis
Le but de ce travail était d’étudier l’influence de la vitesse sur les capacités de production de force des membres inférieurs lors d’efforts intenses uniques et répétés (i.e. l’endurance de force).La première partie (Partie 1) était focalisée sur le type de modélisation pour définir la relation force-vitesse lors d’extensions maximales et acycliques des membres inférieurs. Cette première partie a apporté des éléments originaux qui supportent la linéarité de la relation force-vitesse, notamment du côté vitesse de la relation. En considérant toutes les conditions de force et de vitesse, la linéarité a été confirmée expérimentalement sur 80% du spectre total de la relation force-vitesse (i.e. de 6 à 86% de la vitesse maximale théorique), même en comparaison avec un modèle curvilinéaire.La deuxième partie (Partie 2a) avait pour but i) d’étudier l’effet de la condition de force-vitesse sur l’endurance de force (i.e. le nombre maximal de répétitions), en contrôlant l’effet de la fréquence de répétitions, et ii) de revisiter l’effet de l’intensité de l’exercice, communément exprimée relativement à la seule valeur de la puissance maximale obtenue à vitesse optimale (Pmax). Les résultats montraient que l’endurance de force était davantage affectée par l’intensité de l’exercice lorsqu’elle était quantifiée par le niveau de puissance exprimée relativement à la puissance maximale spécifique à la vitesse (Pmaxv) que lorsqu’elle était exprimée relativement à Pmax. Les résultats montraient aussi que les différences endurance de force était expliquée à 88% par Pmaxv et à 10% par la condition de force-vitesse dans laquelle cette puissance relative est développée. L’endurance de force était plus importante lorsque Pmaxv était diminuée et dans les conditions de force faible-vitesse élevée. Au-delà du nombre maximal de répétitions, les conditions de force faible-vitesse élevée permettaient de fournir un travail mécanique total plus important à un niveau de Pmaxv donné.La troisième partie (Partie 2b) visait à étudier la variabilité interindividuelle de l’effet de la condition de force-vitesse sur l’endurance de force. Suite à cette étude, il a été mis en avant que l’effet de la condition de force-vitesse sur l’endurance de force n’était pas le même chez tous les individus et notamment qu’il existe des profils d’athlètes différents : certains étant plus endurants dans des conditions de force faible-vitesse élevée ou, à l’inverse, dans des conditions de force élevée-vitesse faible. Ce profil force-vitesse-endurance individuel donne une indication sur l’orientation des capacités d’endurance vers des conditions de force faible-vitesse élevée, ou inversement. D’un point de vue pratique, ces résultats montraient qu’un individu présentant la meilleure performance d’endurance de force dans une condition de force-vitesse à un niveau de Pmaxv donné, n’était pas systématiquement le meilleur dans toutes les conditions de force-vitesse. Au-delà de dépendre de l’intensité de l’exercice, l’endurance de force dépend également de ce profil force-vitesse-endurance.Pour conclure, ce travail de thèse a confirmé que l’effet de la vitesse sur les capacités de production de force des membres inférieurs lors d’efforts uniques et maximaux était linéaire sur l’ensemble des conditions fonctionnelles de vitesse, notamment à des vitesses très élevées. Ces travaux ont également montré que lors d’efforts intenses et répétés, la condition de force-vitesse dans laquelle la puissance est développée influence l’endurance de force, indépendamment de la puissance et de la fréquence de mouvement. De plus, l’influence de cette condition de force-vitesse sur l’endurance de force n’est pas similaire chez tous les individus : chaque individu présente un profil force-vitesse-endurance qui lui est propre. Une détermination des conditions de force-vitesse-puissance semble intéressante pour évaluer et entrainer les capacités de production de force avec une approche individualiséeàchacun
... It is well understood that force generation, rate of force development and proper application of forces are vital to sprinting (Haugen et al., 2019;Hicks et al., 2020;Morin et al., 2011;Rabita et al., 2015). A recently developed macroscopic method has permitted the calculation of biomechanical variables during sprinting (Morin et al., 2019;Samozino et al., 2016). Such variables include maximal sprint speed, maximal theoretical horizontal force (F 0 ), maximal theoretical velocity (V 0 ), maximal theoretical power (P max ), maximal ratio of force (RF max ), decrease in ratio of force (D RF ) and force-velocity slope (S FV ). ...
... Collectively, these variables comprise the 'Sprint Profile' of the athlete and can be used to monitor and guide the training programof sprint reliant athletes (Hicks et al., 2020). A detailed description of the calculations used to obtain the Sprint Profile variables is found elsewhere (Morin et al., 2019;Samozino et al., 2016). A brief description of the Sprint Profile variables is provided in Table 1. ...
... Components of the Sprint Profile (Speed, F 0 , V 0 , P max , RF max , D RF and S FV ) were obtained through the MySprint mobile application following the set-up and protocols used by Romero-Franco et al. (2017). Briefly, in this computation method, basic laws of motion are applied to the centre of mass motion (Morin et al., 2019;Samozino et al., 2016). Split-time data were fitted by an exponential function. ...
Article
Full-text available
This study examined the relationship between broad jump (BJ), countermovement jump (CMJ) and light load countermovement jump (LL-CMJ) performance and sprint performance and Sprint Profile measures in athletes. Additionally, this study aimed to determine the predictive ability of jump measures on Sprint Profile components. Twenty-five athletes performed BJ, CMJ, LL-CMJ, 30-metre acceleration and 30-metre maximal speed fly-by sprints. Results revealed moderate to very large correlations between BJ, CMJ and LL-CMJ performance with acceleration sprint completion times (r = −0.423 to −0.807; p < 0.05), fly-by sprint completion times (r = −0.452 to −0.838; p < 0.05) and maximal sprint speed (r = 0.424 to 0.794; p < 0.05). Additionally, associations were observed with multiple jumping measures and components of the Sprint Profile (r = 0.431 to 0.777; p < 0.05) during acceleration sprints. Furthermore, the BJ distance was the best predictor of Sprint Profile components during acceleration sprints (R² = 0.57–0.76; p < 0.01) and maximal speed fly-by sprints (R² = 0.775; p < 0.001). The forces and the manner of force application during the BJ to propel the athlete forwards and upwards are similar to those necessary to exhibit superior sprint performance. This may be due to the rapid generation of forces and orientation of force application during both movements.
... Consequently, force-power-velocity relationships and mechanical effectiveness of force application have been recently used to analyse in sprint profiles (Morin et al., 2011;Morin & Samozino, 2015;Samozino et al., 2016). In this sense, Samozino et al. (2016) have proposed a straightforward method, convenient for field assessment, to determine theoretical maximal velocity (V0), theoretical horizontal force (F0), horizontal power (Pmax) and F-V profile (i.e., the slope of the F-V relationship; Sfv). ...
... Consequently, force-power-velocity relationships and mechanical effectiveness of force application have been recently used to analyse in sprint profiles (Morin et al., 2011;Morin & Samozino, 2015;Samozino et al., 2016). In this sense, Samozino et al. (2016) have proposed a straightforward method, convenient for field assessment, to determine theoretical maximal velocity (V0), theoretical horizontal force (F0), horizontal power (Pmax) and F-V profile (i.e., the slope of the F-V relationship; Sfv). Ratio of force (RFmax) and index of force application technique (DRF). ...
... External mechanical limits of the neuromuscular system during the specific multijoint movements was expresses by F0 and v0 that the system can develop, and with which is associated the maximal power output (Pmax) (Morin & Samozino, 2015;Samozino et al., 2016). Mechanical effectiveness in force application was assessed by DRF and RFmax during sprint running (Samozino et al., 2016). ...
... Acceleration performance depends on sprint kinetics, such as the magnitude and the orientation of the ground reaction force vector [2]. Mechanical effectiveness, i.e., the effective application of lower limb force in a horizontal direction as velocity increases, is significantly related to sprint performance [3][4][5]. High-level sprinters are able to produce greater horizontal force and impulse throughout the acceleration phase compared to lower-level sprinters [6]. ...
... The ability to apply horizontally oriented force can be determined by the force-velocity (F-v) and power-velocity (P-v) relationships [3]. The horizontal F-v profile can be easily estimated using inverse dynamics applied to the athlete's body center of mass (CM) during sprint acceleration, including theoretical maximal horizontal force (F 0 ) and velocity (v 0 ), maximal mechanical power output (P max ), the ratio of force (RF) which expresses mechanical effectiveness and D RF which describes the rate of decrease in RF as the velocity increases over the entire acceleration phase [3,7]. ...
... The ability to apply horizontally oriented force can be determined by the force-velocity (F-v) and power-velocity (P-v) relationships [3]. The horizontal F-v profile can be easily estimated using inverse dynamics applied to the athlete's body center of mass (CM) during sprint acceleration, including theoretical maximal horizontal force (F 0 ) and velocity (v 0 ), maximal mechanical power output (P max ), the ratio of force (RF) which expresses mechanical effectiveness and D RF which describes the rate of decrease in RF as the velocity increases over the entire acceleration phase [3,7]. ...
Article
Full-text available
The aim of this study was to investigate the effects of heavy sled towing using a load corresponding to a 50% reduction of the individual theoretical maximal velocity (ranged 57–73% body mass) on subsequent 30 m sprint performance, velocity, mechanical variables (theoretical maximal horizontal force, theoretical maximal horizontal velocity, maximal mechanical power output, slope of the linear force–velocity relationship, maximal ratio of horizontal to total force and decrease in the ratio of horizontal to total force) and kinematics (step length and rate, contact and flight time). Twelve (n = 5 males and n = 7 females) junior running sprinters performed an exercise under two intervention conditions in random order. The experimental condition (EXP) consisted of two repetitions of 20 m resisted sprints, while in the control condition (CON), an active recovery was performed. Before (baseline) and after (post) the interventions, the 30 m sprint tests were analyzed. Participants showed faster 30 m sprint times following sled towing (p = 0.005). Running velocity was significantly higher in EXP at 5–10 m (p = 0.032), 10–15 m (p = 0.006), 15–20 m (p = 0.004), 20–25 m (p = 0.015) and 25–30 m (p = 0.014). No significant changes in sprint mechanical variables and kinematics were observed. Heavy sled towing appeared to be an effective post-activation potentiation stimulus to acutely enhance sprint acceleration performance with no effect on the athlete’s running technique.
... To test whether elastic-resisted sprint alters sprint performance of elite young soccer players, males from a professional soccer academy were tested on a 30-m sprint before and after 8 weeks of repeated sprint training with or without elastic resistance. Split times were measured on the 30-m sprint, and AP force production was calculated using a validated method based on a macroscopic inverse dynamics approach (31). ...
... Anterior-posterior force production capacities during sprinting were obtained using a validated method based on a macroscopic inverse dynamics approach applied to the players center of mass and requiring only split times (at 5, 10, 20, and 30 m) and anthropometrical input data (31). Split times were obtained by filming each sprint with MySprint app on an iPhone 7 (240 fps; Apple, Inc., Cupertino, CA), of which the validity and reliability for these measurement have been previously published (29). ...
... The theoretical maximal AP force (F 0 ) and theoretical maximal sprinting velocity until which force can be produced (V 0 ) were identified as the force-axis and velocity-axis intercepts of these linear regressions. Maximum AP power output (P max ) was calculated as F 0 3 V 0 /4 (31). The RF was calculated as the ratio of the AP component to total force applied onto the ground (31), with RF max corresponding to the highest RF value. ...
Article
Le Scouarnec, J, Samozino, P, Andrieu, B, Thubin, T, Morin, JB, and Favier, FB. Effects of repeated sprint training with progressive elastic resistance on sprint performance and anterior-posterior force production in elite young soccer players. J Strength Cond Res 36(6): 1675-1681, 2022-This study aimed to determine whether repeated sprint training with progressive high elastic resistance could improve sprint performance and anterior-posterior (AP) force production capacities of elite young soccer players. Seven elite U19 soccer players underwent 10 sessions of elastic-resisted repeated sprints on 8 weeks, whereas 8 U17 players from the same academy (control group) followed the same protocol without elastic bands. Sprint performance and mechanical parameters were recorded on a 30-m sprint before and after training. The control group did not show change for any of the measured variables. In contrast, the elastic-resisted training resulted in a significant improvement of the sprint time (-2.1 ± 1.3%; p = 0.026; Hedges' g = -0.49) and maximal velocity (Vmax; +3.9 ± 2%; p = 0.029; Hedges' g = 0.61) reached during the 30-m sprint. These enhancements were concurrent with an increase in the maximal power output related to AP force (Pmax; +4.9 ± 5.1%%; p = 0.026; Hedges' g = 0.42). Although the theoretical maximal AP force (F0) remained unchanged in both groups, there was a medium but nonsignificant increase in theoretical maximal velocity (V0; +3.7 ± 2.5%; p = 0.13; Hedges' g = 0.5) only in the elastic group. Therefore, the present results show that sprint capacity of elite young soccer players can be further improved by adding incremental resistance against runner displacement to raise the ability to produce AP force, rather at high velocity in the final phase of the acceleration.
... Recently, a new type of analysis has been added to the set of techniques available to sport biomechanists. This new mode of analysis, based on the mechanical force-velocity (F-v) profile, has offered a new layer for studying sprinting mechanics and an underlying theoretical dimension explaining the expression of movement as depicted through kinematics (Morin et al., 2019;Samozino et al., 2016). This, in turn, has facilitated a different examination level of differences in the mechanical characteristics between athletes from other sports, levels of practice and sex (Jiménez-Reyes et al., 2018;Nicholson et al., 2021;Slawinski et al., 2017;Stavridis et al., 2019;Watkins et al., 2021). ...
... Briefly, the maximal power-output capability in the horizontal direction (P max ), the theoretical maximal horizontal force production (F 0 ), the theoretical horizontal velocity capability (v 0 ), of a sprinter, and the proportion of resultant force production directed into the anteroposterior direction (RF) together with the rate of decline in RF as running velocity is increased (DRF) are estimated using established field methods (Morin et al., 2011(Morin et al., , 2019Samozino et al., 2016). These mechanical characteristics directly determine sprinter's propulsion capacities and constitute a crucial factor for athletes to reach maximal running velocities and most importantly to cover a given distance as soon as possible. ...
... Therefore, the aim of this study was to explore the mechanical and kinematic characteristics of sub-elite and recreational sprinters during the acceleration phase of a linear sprint running section. For this purpose, the force-velocity profiling method was performed (Morin et al., 2019;Samozino et al., 2016) to assess the mechanical differences between sub-elite and recreational sprinters. Such comparison with its outcomes will provide a better insight of the mechanical determinants affecting acceleration performance in male sprinters. ...
Article
Full-text available
The aim of this study was to explore the sprint mechanical and kinematic characteristics of sub-elite and recreational male sprinters during the acceleration phase of a linear sprint running section. Eighteen sprinters (nine sub-elite, nine recreational) performed two all-out 30-m sprints. Three high speed panning cameras were used to record the entire sprint distance continuously. The sprint velocity-time data of each camera were determined by temporal analysis of the video recording. These values were used to determine the variables of the horizontal F-v profile (theoretical maximal values of horizontal force [F0], velocity [v0], power [Pmax], the maximal ratio of horizontal to resultant force [RFmax], the decline in the ratio of horizontal force production as the running speed increases [DRF]) and key kinematic characteristics. Significantdifferences were observed between the groups for v0 (0.79 ± 0.24 m∙s-1, p = 0.005), Pmax (3 ± 1.17 W∙kg-1, p = 0.020) and RFmax (3.1 ± 1.2 %, p = 0.021). No statistical differences were found for F0 (0.55 ± 0.46 N∙kg-1, p = 0.25) and DRF (0.2 ± 0.5 %∙s∙m, p = 0.67). The mean running velocity and mean step rate were higher, whereas mean ground contact time was shorter in sub-elite sprinters. There were no differences in mean step length and mean flight time. The sub-elite sprinters in our study demonstrated the capacity to generate higher amounts of horizontal forces at higher running speeds, apply horizontal force to the ground more efficiently and achieve higher step rates during sprint acceleration than recreational sprinters.
... An understanding of these constructs has been shown to assist in the development of specific and individualized training programmes, optimizing adaptation and improving overall performance . The recent development of a simple field-based assessment of the mechanical profile of sprint acceleration Samozino et al., 2016) has provided coaches and practitioners with the information to design individualized training programs that was previously restricted to expensive laboratory-based settings. It is now understood that sprint acceleration performance can be improved by maximizing horizontal power output . ...
... Through derivation of the modelled velocity-time curve, instantaneous horizontal force can be estimated, which has been shown to exhibit considerable validity (standard error of the estimate [SEE] = 39.9 N ± 13.3 N, r = 0.978, p < 0.0001) when compared to the gold standard force plate method Samozino et al., 2016). In addition, through integration of the modelled horizontal force and velocity data, a range of biomechanical variables can be estimated, including horizontal power, or mechanical effectiveness of force application, providing a greater understanding of the underlying mechanical determinants of sprint acceleration performance, or the FVP profile. ...
Article
Full-text available
This study aimed to quantify the validity and reliability of load–velocity (LV) relationship of hill sprinting using a range of different hill gradients and to describe the effect of hill gradient on sprint performance. Twenty-four collegiate-level athletes performed a series of maximal sprints on either flat terrain or hills of gradients 5.2, 8.8 and 17.6%. Velocity–time curves were recorded using a radar device. LV relationships were established using the maximal velocity achieved in each sprinting condition, whilst force–velocity–power (FVP) profiles were established using only the flat terrain sprint. LV profiles were shown to be valid (R² = 0.99) and reliable (TE < 4.4%). For every 1-degree increase in slope, subjects’ velocity decreased by 1.7 ± 0.1% on average. All the slopes used represented low resistance relative to the entire LV spectrum (<25% velocity loss). Subjects who exhibited greater horizontal force output at higher velocities on flat terrain were most affected by the gradient of the hill. Hills of gradients up to 17.6% do not provide sufficient resistance to optimize power development. However, such hills could be used to develop late-stage technical ability, due to the prolonged horizontally oriented body position that occurs as subjects attempt to overcome the acceleration due to gravity.
... The inverse linear force-velocity (FV) and the parabolic powervelocity (PV) relationships are commonly used to describe the mechanical capabilities of the neuromuscular system to produce force during multiple-joint lower-limb movements such as vertical jumps or sprints (Bobbert, 2012;Cuk et al., 2014;Jaric, 2015). These relationships characterize the ability to produce force at different movement velocities and are summarized through these main mechanical parameters: the theoretical maximal force (F 0 ), the theoretical maximal velocity (V 0 ), and the maximal power output (P max ) ( Table 1) (Jiménez-Reyes et al., 2014;Samozino et al., 2008Samozino et al., , 2016Samozino et al., , 2012. The parameters derived from the FV profile (F 0 , V 0 , and P max ) depend on a myriad of morphological factors, neural mechanisms, muscular coordination, and the orientation of the momentum (i.e., vertical or horizontal direction of force application) Yamauchi et al., 2009). ...
... Inclusion Criteria: Observational (cross-sectional and cohort studies), quasiexperimental and experimental studies assessing either the vertical force-velocity profile assessed through the simple field method proposed by Samozino et al. (2008) or the horizontal force-velocity profile assessed through the simple field method proposed by Samozino et al. (2016) were included. The included studies had healthy and physically active men and women (14-45 years of age) and measured mechanical properties derived from the vertical and horizontal FV profile; and sport performance-related outcomes (such as jump height, sprint time, change of direction time, ball speed or throwing velocity). ...
Article
The aims of this systematic review were to synthetize the current evidence about (i) the force-velocity (FV) profile parameters (maximal values of force [F0], velocity (V0), and power [Pmax]) obtained from the Samozino’s method in different sports; (ii) the association of the FV profile parameters with sport performance outcomes; and (iii) the effects of specific training programmes on the FV profile parameters. PubMed, SportDiscus, Web of Science, and Medline databases were searched for articles published between October 2008 (conception of the Samozino’s method) and October 2020. Twenty-one studies (10 descriptive, 6 correlational, and 5 longitudinal) met the inclusion criteria. The main findings revealed greater F0, Pmax, and V0 values and better jump/sprint performance for high-level athletes compared to their low-level counterparts. The vertical Pmax showed the highest correlation with jump height. The horizontal F0, Pmax, and V0 were nearly perfectly correlated with 5/10-m, 10/20-m and 30/40-m sprint times, respectively. Training programmes using heavy- or light-loads specifically enhanced F0 and V0, respectively. These results suggest that the FV profile parameters discriminate between athletes of different sport disciplines and levels of practice, present significant correlations with a number of sport performance outcomes, and can be modified after short-term training programmes.
... Most importantly, the upper limit (5 m·s −1 ) of investigated speeds for which SL has been accurately derived from IMUs is rather low. During sprint acceleration, 5 m·s −1 is reached after the first few strides [10,23] and recreational athletes reach maximal speeds of about 9 m·s −1 [10]. ...
... Recently, we demonstrated that fairly accurate estimates of SL could be obtained during maximal sprint acceleration [10], but these estimates were indirectly obtained from the IMU-signals by combining the timing of the footfalls with the well-known monoexponential speed increase during sprint acceleration [23]. To the best of our knowledge, there are no publications in which SL is determined directly from the IMU signals during maximal linear sprint acceleration. ...
Article
Full-text available
Inertial measurement units (IMUs) fixed to the lower limbs have been reported to provide accurate estimates of stride lengths (SLs) during walking. Due to technical challenges, validation of such estimates in running is generally limited to speeds (well) below 5 m·s−1. However, athletes sprinting at (sub)maximal effort already surpass 5 m·s−1 after a few strides. The present study aimed to develop and validate IMU-derived SLs during maximal linear overground sprints. Recreational athletes (n = 21) completed two sets of three 35 m sprints executed at 60, 80, and 100% of subjective effort, with an IMU on the instep of each shoe. Reference SLs from start to ~30 m were obtained with a series of video cameras. SLs from IMUs were obtained by double integration of horizontal acceleration with a zero-velocity update, corrected for acceleration artefacts at touch-down of the feet. Peak sprint speeds (mean ± SD) reached at the three levels of effort were 7.02 ± 0.80, 7.65 ± 0.77, and 8.42 ± 0.85 m·s−1, respectively. Biases (±Limits of Agreement) of SLs obtained from all participants during sprints at 60, 80, and 100% effort were 0.01% (±6.33%), −0.75% (±6.39%), and −2.51% (±8.54%), respectively. In conclusion, in recreational athletes wearing IMUs tightly fixed to their shoes, stride length can be estimated with reasonable accuracy during maximal linear sprint acceleration.
... Thus, quantify the main sprint kinetics is key for a better understanding of human sprint acceleration performance (Cavagna et al. 1971; Rabita et al. 2015). These overall mechanical capabilities to produce horizontal force during sprint running is well described by the macroscopic linear force-velocity (FV) relationship (Morin et al. 2010(Morin et al. , 2019; Rabita et al. 2015;Samozino et al. 2016). The left side of the spectrum represents the force production capacity at low velocities and the right side represents the force production capacity at high velocities. ...
... From this material constraint, the idea of a simple field method based on position-time data has been recently proposed (Morin et al., 2019;Samozino et al., 2016). Using this method, mechanical outputs determined from simple kinematic data showed very good agreement to those assessed from a reference force plate system. ...
Thesis
Full-text available
Sprinting is a key determinant of performance in soccer. The overall mechanical capabilities of this ability are well described by the macroscopic linear force-velocity (FV) and acceleration-speed (AS) relationships. This study aimed to compare FV and AS profiles computation methods in order to assess athletes’ sprint acceleration mechanical capabilities based on classic single sprint test data, and compare the linear sprint FV profile to the AS profile in-situ, based on soccer data. Ten recreational athletes were equipped with GPS units and performed two 30-m sprints followed by a 45-min soccer period. For the linear sprint test, we observed good agreement between the two methods for kinetic variables (all mean absolute bias <6.7 ± 6.51%), and a similar low inter-trial reliability (mean coefficients of variation <4.6 ± 4.36%). The AS in-situ profile in comparison with the linear FV profile showed an overall underestimation of maximal theoretical acceleration capacities (mean absolute bias of 13.65 ± 7.7%), but contrastingly allows to have a good idea of maximal theoretical running velocity capabilities of the athletes (mean absolute bias of 4.14 ± 3.68%). This pilot-study clearly showed that AS profile can be used confidently for orient training and rehabilitation, but not actually with soccer data.
... If GNSS is the chosen method, players should wear the same units to prevent interunit difference from affecting outcomes (76); however, it is advised that signal quality is checked to ensure the accuracy of data through horizontal dilution of precision and number of satellites (58). mechanical properties underpinning sprint performance using a simple model (81). Theoretical maximal velocity (V 0 ), maximal force (F 0 ), and horizontal power (Pmax) can be estimated to produce an individualized force-velocity-power profile from a player's speed time curve during a 30-to 40-m sprint (64,81). ...
... mechanical properties underpinning sprint performance using a simple model (81). Theoretical maximal velocity (V 0 ), maximal force (F 0 ), and horizontal power (Pmax) can be estimated to produce an individualized force-velocity-power profile from a player's speed time curve during a 30-to 40-m sprint (64,81). The slope of the force-velocity curve (sFV), the ratio of horizontal to vertical force (RF), and the rate of decrease in RF throughout the sprint (D RF ) are also derived from this model and are valuable in the understanding of sprint kinetics and kinematics (64). ...
Article
Soccer match play dictates that players possess well-rounded physical capacities. Therefore, player physical development plans must consider developing several fitness components simultaneously. Effective individualization of training is likely facilitated with appropriate player profiling; therefore, developing a time-efficient and informative testing battery is highly relevant for practitioners. Advances in knowledge and technology over the past decade have resulted in refinements of the testing practices used by practitioners working in professional male and female soccer. Consequently, a contemporary approach to test selection and data analysis has progressively been adopted. Furthermore, the traditional approach of using a testing battery in a single day may now be outdated for full-time players, with a flexible approach to the scheduling of testing perhaps more suitable and time efficient. Here, guidance on testing for maximal aerobic, sub-maximal aerobic, linear and change of direction speed, and stretch-shortening cycle performance (i.e., jump testing) are presented for male and female players, with emphasis on time efficient tests, while facilitating effective individualized training prescription. Normative and meaningful change data are presented to aid decision making and provide a reference point for practitioners. Finally, a time-efficient approach to scheduling fitness testing is presented, which complements daily training outcomes of a weekly periodization approach.
... Athletes with steeper FV profiles are better at generating high forces at low velocities, and vice versa [87]. Due to its simplicity and cost effectiveness, FV profiling is often applied for different movement tasks, such the vertical jump [87], sprint running [88], and bench press [89]. Nevertheless, it is also important to note that the values of the FV relationship parameters (F 0 , V 0 , and P max ) depend on the movement task. ...
... Although longer distances are needed to reach top speeds in elite athletes, the 0-30 range is sufficient to extrapolate maximal force (F 0 ) and velocity (V 0 ) capabilities. In addition to F 0 , V 0 , P max , and the slope of the FV relationship, FV profiling in sprinting allows the evaluation of the ability to produce force in the horizontal direction in the acceleration phase [88] and sprinting mechanical efficiency (i.e., maximal ratio of horizontal-to-resultant force, RF) [93]. Similar to the jumping FV relationship, there is also great variability in the values of sprinting FV parameters (regarding the gender and different sports). ...
Article
Full-text available
Traditional neuromuscular tests (e.g., jumping and sprinting tasks) are useful to assess athletic performance, but the basic outcomes (e.g., jump height, sprint time) offer only a limited amount of information, warranting a more detailed approach to performance testing. With a more analytical approach and biomechanical testing, neuromuscular function can be assessed in-depth. In this article, we review the utility of selected biomechanical variables (eccentric utilization ratio, force–velocity relationship, reactive strength index, and bilateral deficit) for monitoring sport performance and training optimization. These variables still represent a macroscopic level of analysis, but provide a more detailed insight into an individual’s neuromuscular capabilities, which can be overlooked in conventional testing. Although the aforementioned “alternative” variables are more complex in biomechanical terms, they are relatively simple to examine, with no need for additional technology other than what is already necessary for performing the conventional tests (for example, even smartphones can be used in many cases). In this review, we conclude that, with the exception of the eccentric utilization ratio, all of the selected variables have some potential for evaluating sport performance.
... Additionally, individual profiling also enables analysis of the ratio of force produced in the horizontal direction (RF%) and a theoretical maximal value of RF% (RF max ), which is a measure of the maximal mechanical effectiveness of force application in the forward direction at the sprint start. 23 Currently, individual F-v and L-v profiling can be more easily achieved using a robotic system because the actual resistance is programmable and standardized across environments. 24 Recent studies examining RST in elite athletes show a relationship between pretraining F-v profiles and how these profiles are affected by training. ...
... The raw velocity-time data and Samozino's inverse dynamics method were used to compile the F-v relationships. 23 Next, 4 progressively loaded 20-m sprints were performed to compute the participants' L-v profile. The F-v and L-v profiles were used to calculate and measure the individual training load, F 0 , P max , RF max , and v max . ...
Purpose: This study compared the effects of heavy resisted sprint training (RST) versus unresisted sprint training (UST) on sprint performance among adolescent soccer players. Methods: Twenty-four male soccer players (age: 15.7 [0.5] y; body height: 175.7 [9.4] cm; body mass: 62.5 [9.2] kg) were randomly assigned to the RST group (n = 8), the UST group (n = 10), or the control group (n = 6). The UST group performed 8 × 20 m unresisted sprints twice weekly for 4 weeks, whereas the RST group performed 5 × 20-m heavy resisted sprints with a resistance set to maximize the horizontal power output. The control group performed only ordinary soccer training and match play. Magnitude-based decision and linear regression were used to analyze the data. Results: The RST group improved sprint performances with moderate to large effect sizes (0.76–1.41) across all distances, both within and between groups (>92% beneficial effect likelihood). Conversely, there were no clear improvements in the UST and control groups. The RST evoked the largest improvements over short distances (6%–8%) and was strongly associated with increased maximum horizontal force capacities (r = .9). Players with a preintervention deficit in force capacity appeared to benefit the most from RST. Conclusions: Four weeks of heavy RST led to superior improvements in short-sprint performance compared with UST among adolescent soccer players. Heavy RST, using a load individually selected to maximize horizontal power, is therefore highly recommended as a method to improve sprint acceleration in youth athletes.
... Linear sprinting. The 30-m sprints were evaluated using the MySprint app 27 . To ensure successful performance, we followed the protocol of Samozino et al. 27 . ...
... The 30-m sprints were evaluated using the MySprint app 27 . To ensure successful performance, we followed the protocol of Samozino et al. 27 . The aim of this test was to run 30 m as fast as possible. ...
Article
Full-text available
The present study aimed to determine the influence of force–power–velocity, vertical and horizontal jumps, and repeated sprint ability on the sprinting performance of adult women soccer players. Eighteen women soccer players from one team participating in the first female national Spanish soccer league were analyzed. Fitness assessments were performed twice in a period of three months. The following assessments were made to reach the aim of the study: (1) anthropometric measures, (2) CMJ (0%, 20% and 40%), (3) hop test (dominant and nondominant leg), (4) linear sprinting at 30 m and (5) RSA test. The main evidence of this study revealed the meaningful contribution of lower-limb power (vertical and horizontal jump), maximal sprint and peak power on sprinting time performance, while stride frequency was meaningfully explained by vertical jump and maximal sprinting. In fact, positive moderate and large correlations were found between Time and CMJ, CMJ 20%, CMJ 40%, Hop Test Dominant and Non-dominant, and Pmax and MS of Force–Power–Velocity (r = − 0.73, p = 0.001; r = − 0.68, p = 0.002; r = − 0.51, p = 0.03; r = − 0.64, p = 0.004; r = − 0.57, p = 0.013; r = − 0.78, p = 0.001, and r = − 0.83, p = 0.001, respectively). In sum, peak power, maximal speed, and lower-limb power (in vertical and horizontal jumps) were significant determinants of sprinting performance (time), while vertical jump was the determinant of stride frequency. In addition, our findings suggest that potentiation and explosive vertical power could be the emphasis for sustaining the stride frequency of women soccer players, while sprinting performance should be supported by strong acceleration and maximal velocity sustained by both vertical and horizontal force and concentric and eccentric strength and power.
... However, to have an accurate understanding of acceleration, speed, and sprint ability, it is important to initiate timing in a standardized way that captures the entire sprint effort. Specifically, it is necessary to assess the initial propulsive movements that enable an athlete to build up speed (13). Throughout the scientific literature, vastly different sprint performance outcomes have been shown, despite similar cohorts being assessed (12). ...
... This suggests that this device may enable practitioners to gather a greater understanding of accelerative ability of an athlete when compared with other sprint testing methods. Recent research has emphasized the need to capture initial propulsive movements during sprinting not only to gain a better insight into an athlete's capacity but also for the calculation of horizontal force-velocity-power profiles (11,13). Contrasting the results from the Move device, substantially faster outcomes were associated with using a front-foot trigger. ...
Article
Sprint testing is commonly used to assess speed and acceleration in athletes. However, vastly different outcomes have been reported throughout the literature. These differences are likely due to the sprint timing method rather than differences in athlete ability. Consequently, this study compared different sprint starting methods on sprint time and quantified the velocity and displacement of the athlete at the moment timing is initiated. Starting in a staggered 2-point stance, 12 team sport athletes were required to accelerate 10 meters for 10 repetitions. During each repetition, 5 independent timing methods were triggered. The methods were (a) triggering a Move sensor; (b) starting 50 cm behind the line; (c) triggering a front-foot switch; (d) triggering a rear-foot switch; and (e) starting with the front foot on the line. Timing for each method was initiated at different points during the acceleration phase, and the displacement and velocity of the centroid of the pelvis at the point of timing initiation was assessed under high-speed motion capture. The Move sensor had the smallest displacement and lowest velocity at the point of timing initiation, whereas the front-foot trigger demonstrated the largest displacement and highest velocities. Trivial to very large effect size differences were observed between all methods in displacement and velocity at the point of timing initiation. Furthermore, small to very large differences in time to 5 m were found. These findings emphasize that sprint outcomes should not be compared, unless starting methods are identical. In addition, to detect real change in performance, consistent standardized protocols should be implemented.
... For each trial and each system, a 1-s moving average was used to smooth raw speed data, and the end of the sprint acceleration was identified when processed speed went down to 97.5% of the maximal sprint speed (based on the moving average) right after the start of the deceleration phase. Then, data processing of the force-velocity profiles was performed using a custom-made Excel spreadsheet and the reference procedure validated against force plate data by Samozino et al. and Morin et al. (2,3). Briefly, running speed raw data were fitted with the following mono exponential equation (Figure 1): ...
... Finally, a similarly low inter-trial variability was observed for both devices (Table 2). These results suggest that the models of GPS and linear encoder devices used in this study are both suitable for sprint acceleration force-velocity profiling following the computational approach proposed by Samozino et al. (2,3). With each device, inter-trial reliability suggests that inter-and intra-athlete comparisons are possible and reliable (for example to assess changes over time, training or detraining effects). ...
... Although the traditional assessment of sprint ability has been carried out by recording the time taken to run a given distance (i.e., 30-m sprint) (Jiménez-Reyes et al., 2020), there is an increasing interest in evaluating the players' force-velocity (Fv) profile to obtain more specific data about players' capability to produce horizontal force during the sprint (Marcote-Pequeño et al., 2019;Samozino et al., 2016). This assessment is based on the inverse and linear relationship between force and velocity . ...
... A 30-m sprint test with electronic timing and photocells (Witty System, Microgate, Bolzano, Italy) set every 5-m was used to assess the players' time in 30-m linear sprint performance and the players' Fv profile. The variables derived from the SFv profile (F0, V0, Pmax, Fvslope, RFmax, DRF and Vmax) were calculated according to Samozino et al. (2016) with the use of their specific spreadsheet . Time in the modified agility test (MAT) (Sassi et al., 2009) was used to assess the players' change of direction ability. ...
Article
This study assessed and described the Sprint Force-velocity (SFv) profile, and its validity and reliability in international cerebral palsy (CP) football players. Twenty international male CP football players (age: 26.9±7.4) performed a 30-m sprint, a vertical jump (CMJ), a change of direction (MAT), a dribbling and an intermittent endurance (Yo-YoIR1) test. The SFv profile and physical performance variables were shown according to the players’ sport class with the estimation of the effect sizes between classes. The SFv showed high reliability (ICC=0.77 to 0.99; SEM=0.89 to 8.66%). Validity for the SFv was provided by its positive correlation with the players’ sport class (r=0.53 to 0.75; p=.02 to
... Our second hypothesis that the MLS is reliable for within-and between-day testing for split times and the FVP profile was primarily supported for nine of ten variables. Despite proportional bias for VMAX, our finding is consistent with a previous study showing the mathematical model for the MySp app to have a 0.32 m•s −1 bias compared to force plate analysis [47]. ...
... Our second hypothesis that the MLS is reliable for within-and between-day testing for split times and the FVP profile was primarily supported for nine of ten variables. Despite proportional bias for V MAX , our finding is consistent with a previous study showing the mathematical model for the MySp app to have a 0.32 m·s −1 bias compared to force plate analysis [47]. ...
Article
Full-text available
This study examined the level of agreement (Pearson product-moment correlation [rP]), within- and between-day reliability (intraclass correlation coefficient [ICC]), and minimal detectable change of the MusclelabTM Laser Speed (MLS) device on sprint time and force–velocity–power profiles in Division II Collegiate athletes. Twenty-two athletes (soccer = 17, basketball = 2, volleyball = 3; 20.1 ± 1.5 y; 1.71 ± 0.11 m; 70.7 ± 12.5 kg) performed three 30-m (m) sprints on two separate occasions (seven days apart). Six time splits (5, 10, 15, 20, 25, and 30 m), horizontal force (HZT F0; N∙kg−1), peak velocity (VMAX; m∙s−1), horizontal power (HZT P0; W∙kg−1), and force–velocity slope (SFV; N·s·m−1·kg−1) were measured. Sprint data for the MLS were compared to the previously validated MySprint (MySp) app to assess for level of agreement. The MLS reported good to excellent reliability for within- and between-day trials (ICC = 0.69–0.98, ICC = 0.77–0.98, respectively). Despite a low level of agreement with HZT F0 (rP = 0.44), the MLS had moderate to excellent agreement across nine variables (rp = 0.68–0.98). Bland–Altman plots displayed significant proportional bias for VMAX (mean difference = 0.31 m∙s−1, MLS < MySp). Overall, the MLS is in agreement with the MySp app and is a reliable device for assessing sprint times, VMAX, HZT P0, and SFV. Proportional bias should be considered for VMAX when comparing the MLS to the MySp app.
... In 2016, proposed a novel method to assess the mechanics variable during the sprint running in the field sport including soccer called "Force-Velocity relationship profile". This simple method could compute sprint acceleration kinetics from the running time-velocity curve in the basic of macroscopic model, which has been validated for measuring mechanical effectiveness based on an inverse dynamic approach (Samozino, Rabita et al. 2016, Morin, Samozino et al. 2019) ( Figure 2-1). ...
... The main sprint mechanical Force-Velocity profile include maximal acceleration (Acc), maximal theoretical force (F0), maximal theoretical velocity (V0), maximal power (Pmax), decrease in the ratio of horizontal-to-resultant force (DRF), the slope of the linear Force-Velocity relationship (F-V slope) and maximal ratio of horizontal-to-resultant force (RFmax) (Samozino, Rabita et al. 2016). Based on this method, the sprint velocity-time curve (v(t)) was fitted by a mono-exponential function using least-squares regression: ...
Thesis
The main objective of this thesis was to determine the influence of hamstring and quadriceps neuromuscular capacities on explosive performance and the risk of lower limb injuries in soccer players. The first study of this thesis examined the relationship between the isokinetic force capacity of the knee muscles and the deceleration performance in professional female soccer players. The results revealed the importance of the eccentric force of the knee extensors contributing to the production of braking force during the linear deceleration test. The second study of this thesis was interested in the influence of the direction of jump on the dynamic postural stability during an unipodal landing and the importance of the hamstring / quadriceps co-activation in the stabilization capacity of the legs unipodal supports. The main finding is that the dominant leg showed better dynamic postural stability during the jump landing, associated with higher H / Q co-activation in the first milliseconds of the contact phase. The third study of this thesis explores the influence of fatigue generated by maximal isokinetic contractions on the capacity for rapid strength of the hamstrings and quadriceps in footballers. The results showed that the functional and conventional ratios measured during the preseason testing are not sensitive to fatigue. In contrast, the rapid hamstring / quadriceps torque ratio is more affected by fatigue. In summary, this work has shown that the evaluation of the explosive strength and fatigability capacities of the extensor and flexor muscles of the knee on an isokinetic ergometer remains a central subject for the improvement of explosive performance and the reduction of the risk of injury in the soccer player and footballer. In addition, the results of this work show the value of systematically associating the analysis of the EMG signal with the evaluation of the isokinetic force capacities, sprint performance and stability of the supports in male and female soccer players.
... Ice hockey is a highly complex team invasion sport that involves skating, stick and puck handling, and physical contact and collisions. Horizontal force, in addition to power, and acceleration during forward skating are key determinants of ice hockey performance (Samozino et al., 2016). Horizontal force-velocity (HFV) profiling estimates the horizontal force produced by an athlete while performing a linear sprint by combining kinematic metrics, providing valuable insight on athlete power expression which can subsequently be applied in training (Jimenez-Reyes et al., 2018). ...
... Following a standardized warm up, participants completed three 50-meter skating sprints. The instantaneous velocity, collected using a radar gun (Stalker II, Texas US), was used to determine participant HFV metrics (maximal velocity, tau, force-velocity slope, maximum theoretical force, ratio decrease of force) using the method proposed by Samozino et al. (Samozino et al., 2016) within a custom Python script. Forty-eight hours later, participants completed a standardized lower body strength battery which included a 30 cm drop jump (DJ), countermovement jump (CMJ), loaded (75% body weight) CMJ (LCMJ), and isometric squat (IST) on portable dual force plate system (ForceDecks Lite, VALD Performance). ...
Conference Paper
Full-text available
The primary purpose of this study was to evaluate the horizontal force-velocity (HFV) profiles of female collegiate ice hockey players and compare these to metrics of muscular strength. The secondary purpose of this study was to categorize strength metrics using reduction analyses to improve the interpretation and application of these results and that of future studies. Thirteen female ice hockey players (body mass = 66.7 ± 18.0 kg; height = 171.6 ± 6.2 cm) completed three 50-meter on-ice sprints. Instantaneous velocity was measured using a radar gun in which participant HFV profile metrics (maximal velocity, tau, force-velocity slope, maximum theoretical force, ratio decrease force) were derived. Forty-eight hours later, participants completed four strength tests (drop jump, countermovement jump, loaded countermovement jump, and isometric squat) measured using a dual force plate resulting in 64 metrics of strength. A stepwise regression was employed to assess the associations between strength and HFV profile metrics. All strength metrics were entered into a principal component analysis (PCA) to support interpretation of the results. There were no significant associations between strength and HFV profile metrics. The PCA identified four clusters of strength metrics that were considered distinct strength properties in this population. This study presents a robust method for evaluating skating HFV profiles and strength metrics in ice hockey players and should be used in future studies to contribute to this body of literature.
... The raw instantaneous velocity-time data was collected used to derive sprint acceleration force, velocity and power characteristics, and sprint times (5m -30m 164 splits) in a commercially available custom-made Microsoft Excel spreadsheet with the average of two 165 maximal sprint trials from each subject was used for statistical analysis. This method provides an almost 166 perfect fitting of velocity-time data (R 2 > 0.996) and showed low absolute bias (1.88 -8.04%) when 167 compared to the gold standard force platform method for all sprint acceleration force, velocity and 168 power characteristics (22,28). The high agreement between methods provides evidence that the 169 estimation of overground sprint kinetics using instantaneous velocity-time data is a valid and reliable 170 approach to assess sprint acceleration characteristics. ...
Article
Full-text available
This study assessed the effect of heavy resisted sled-pull training on sprint times, and force, velocity, and power characteristics in junior Australian football players. Twenty-six athletes completed a six-week resisted sled-pull training intervention which included 10 training sessions and 1-week taper. Instantaneous velocity during two maximal 30 m sprints was recorded 1 week prior and 1 week after the intervention with a radar gun. Velocity-time data was used to derive sprint performance and force, velocity, and power characteristics. A paired t-test assessed the within-group differences between pre- and post-intervention testing. Statistical significance was accepted at p≤0.05. Hedges' G effect sizes (ES) were used to determine the magnitude of change in dependent variables. Maximum velocity (ES=1.33) and sprint times at all distances (ES range 0.80-1.41) significantly improved post heavy resisted sled-pull training. This was reflected in sprint force, velocity, and power characteristics with significant improvements in relative theoretical force (ES=0.63), theoretical velocity (ES=0.99), relative maximum power (ES=1.04), and ratio of horizontal to vertical force (ES=0.99). Despite the multi-factorial nature of training and competing physical demands associated with pre-season training, these findings imply that a short, resisted sled-pull training mesocycle may improve sprint performance and underlying force, velocity, and power characteristics in junior athletes.
... The force-velocity (FV) profiling has recently been proposed as a tool to identify the neuromuscular capabilities of athletes and to optimize the training (Jiménez-Reyes et al., 2017a). The FV relationship allows to characterize the mechanical capabilities of musculoskeletal system to produce force, power and velocity (Jaric, 2015;Samozino et al., 2016). Since the first study on the topic (Hill, 1937) it has been known that the FV relationship of individual muscles is approximately hyperbolic, while the novel studies show that FV relationship of multi-joint performance tasks is quasi-linear (Bobbert, 2012;Sánchez-Medina et al., 2014;Jaric, 2015;Sreckovic et al., 2015;Zivkovic et al., 2017). ...
Article
Full-text available
The force-velocity (FV) relationship allows the identification of the mechanical capabilities of musculoskeletal system to produce force, power and velocity. The aim of this study was to assess the associations of the mechanical variables derived from the force-velocity (FV) relationship with approach jump, linear sprint and change of direction (CoD) ability in young male volleyball players. Thirty-seven participants performed countermovement jumps with incremental loads from bodyweight to 50-100 kg (depending on the individual capabilities), 25-meter sprint with split times being recorded for the purpose of FV relationship calculation, two CoD tests (505 test and modified T-test) and approach jump. Results in this study show that approach jump performance seems to be influenced by maximal power output (r = 0.53) and horizontal force production (r = 0.51) in sprinting, as well as force capacity in jumping (r = 0.45). Only the FV variables obtained from sprinting alone contributed to explaining linear sprinting and CoD ability (r = 0.35-0.93). An interesting finding is that sprinting FV variables have similar and some even stronger correlation with approach jump performance than jumping FV variables, which needs to be considered for volleyball training optimization. Based on the results of this study it seems that parameters that refer to horizontal movement capacity are important for volleyball athletic performance. Further interventional studies are needed to check how to implement specific FV-profile-based training programs to improve specific mechanical capabilities that determine volleyball athletic performance and influence the specific physical performance of volleyball players.
... However, in their results, they remarked that for the current state of GPS devices' accuracy for speed-time measurements over a maximal sprint acceleration, it is recommended that radar, laser devices, and timing gates remain the reference methods for implementing the computation methods reported by Samozino et al. [16] . Bergamini et al. validated an adapted sensor-fusion algorithm in a trunk-mounted IMU to estimate trunk inclination and angular velocity during sprint start. ...
Article
Full-text available
In a sprint start, the athlete takes up a position with their hands just behind a line, arms vertical, feet generally placed about a shoe length apart, and the hips rising above the line of the head. Mistakes in this position influence the execution of the low-sprint start, and can drastically influence the initial running speed and acceleration achieved by the athlete. Common mistakes occur due to the misconception that athletes must also lean forward, bringing the shoulders ahead of their hands and putting pressure on them. A standard approach to identify sprint start mistakes is to use a stick or weighted string to drop down from the shoulders. The effective implementation of this approach depends on the coach's experience and remains a significant challenge. In this study, a three-dimensional motion capture system with the Vicon® Plug-in-Gait model was used to characterize the kinematic parameters that influence the execution of low-sprint start in six high-performance athletes. The main kinematic parameters are reaction time, stride length, and stride time. The obtained results demonstrate the potential utility of a three-dimensional motion capture system to assess the kinematic parameters of low-sprint start in high-performance athletes.
... The maximal sprints were measured using four pairs of photoelectrical cells (Chronojump, Barcelona, Spain) which were separated by 10 m (0 m, 10 m, 20 m and 30 m). Displacementtime data collected with the photoelectric cells were used to estimate the horizontal F-v profile of the two sprints following the field method proposed by Samozino and colleagues (Haugen et al., 2020;Samozino et al., 2016). The F-v mechanical profile is determined by the slope of the F-v relationship, representing the individual ratio between maximal force and velocity capacities (Bolger et al., 2015). ...
Article
Purpose: The aim of this study was to explore the effects of transcranial direct current stimulation (tDCS) on sprint performance and the horizontal force-velocity (F-v) profile. Method: Thirty-two healthy subjects (25 men and 7 women; age = 21.8 ± 2.4 years) completed three sessions separated by 1 week following a double-blinded crossover design. Each session consisted of two maximal sprints of 30 meters that were performed after applying ANODAL, CATHODAL or SHAM tDCS over the left dorsolateral prefrontal cortex (DLPFC) for 15 minutes at 2 mA. The 30-m time and the horizontal F-v profile variables (theoretical maximal force [F0], theoretical maximal velocity, Fv slope, maximal power [Pmax], decrease in the ratio of horizontal-to-resultant force, and maximal ratio of horizontal-to-resultant force) were compared between the tDCS conditions. Results: No significant differences between the tDCS conditions were observed for any variable (p range = 0.061 to 0.842). The magnitude of the differences was negligible for most of the comparisons (effect size [ES] < 0.20) with the only exception of Pmax and F0 which were greater for the ANODAL compared to the SHAM condition (both ES = 0.20). Conclusions: The application of tDCS over the DLPFC is not effective to increase non-fatigued sprint performance.
... It was measured with a manual radar (Stalker ATS II, Minneapolis), placed on a 2 m tripod behind the subjects initial position and at a height of 1 m, approximately corresponding to the subject's centre of mass (Prince et al., 2021). Using the data obtained by the radar in each sprint in order to establish the strength-speed relationships, the following were calculated by means of linear regression (Morin et al., 2019;Samozino et al., 2016): the horizontal force production at low speed (F0), the horizontal force production at high speed (V0), the horizontal power (Pmax), the rate of force application to sprint (RFmax), the rate of force reduction during sprint (Drf), and the maximum speed achieved (MaxSpeed). During each measurement session (M1-M2-M3-M4) on indoor athletics track, each subject performed three 30 m sprints with two-minute breaks between them and preceded by a standardised warm-up. ...
Article
The Nordic Hamstring Exercise (NHE) improves the strength of the hamstring muscles, as well as prevents and rehabilitates the injuries of said muscles. However, the eccentric demand of NHE may influence the athlete’s performance, making compliance with these programmes difficult. The aim is to analyse the acute impact on sprint performance after the passing of 24, 48, and 72 hours respectively since an NHE-based session (4 sets of 10 repetitions) had taken place. Participants were randomly divided into an experimental group (EG) (n = 12 male participants) who carried out an NHE session and a measurement of their 30 m sprint performance in each of the three subsequent days, and a control group (CG) (n = 12 male participants) who did not take part in the NHE session. The results show a significant reduction of maximum power within 24 hours (t = 3.57, d = 0.22, P < .0273) as well of the production of high speed horizontal force up to after 48 hours (t = 4.82, d = 0.22, P < .0001) in the EG. These results may suggest separating weekly NHE sessions from competition or demanding training in which sprint performance should not be affected by at least 72 hours.
... Phase 1 corresponded to the first movement made by the sprinter (determined by an increase in CoM velocity of 0.1 ms −1 ) to reach P max , Phase 2 was began at P max until V max and phase 3 began at V max until the end of the 40 m. We used the method proposed by Samozino to compute P max and the time at which it was reached Samozino et al., 2016). This simple method uses an mono-exponential model to describe the increase in velocity during the acceleration phase (Di Prampero et al., 2005) Figure 1. ...
Article
Full-text available
This study aimed to measure the contribution of each body segment to the production of total body kinetic energy (KE) during a 40-m sprint. Nine recreational sprinters performed two 40-m sprints wearing a MVN Biomech suit (Xsens). Data recorded were used to calculate total body KE, and the KE of each segment. The KE of each segment was then expressed as a percentage of the total body KE. We divided the sprint into three phases: 1 - start to maximal power (Pmax), 2 - Pmax to maximal velocity (Vmax), and 3 - Vmax to the end of the 40 m. Total body KE increased from the start to the end of the 40-m sprint (from 331.3 ± 68.4 J in phase 1 to 2378.8 ± 233.0 J in phase 3; p ≤ 0.001). The contribution of the head-trunk increased (from 39.5 ± 2.4% to 46.3 ± 1.1%; p ≤ 0.05). Contribution of the upper and lower limbs decreased over the three phases (respectively from 15.7 ± 2.5% to 10.6 ± 0.6% and from 44.8 ± 2.1% to 43.1 ± 1.5%; p ≤ 0.05). This study revealed the important contribution of the trunk to forward propulsion throughout the entire acceleration phase.
... As sprinting is a dynamic movement which mainly requires power output production in two dimensions (horizontal and vertical), lower limb neuromuscular performance in vertical [countermovement jump (CMJ) and mean propulsive velocity (MPV) on half-back squat] and horizontal (i.e. sprinting) planes play the central role in the race (Samozino et al., 2016). For example, it has been reported that vertical jump height is strongly correlated with competitive performance in elite sprinters (Loturco et al., 2015). ...
Article
The objective of this study was to analyze the effect of mental fatigue on mean propulsive velocity (MPV), countermovement jump (CMJ), 100, and 200-m dash performance in college sprinters. A total of 16 male athletes of sprint events (100 and 200-m dash) participated in this study. Each participant underwent two baseline visits and then running under the three experimental conditions. Assessments (MPV and CMJ) occurred both before and after either smartphone use (SMA) or Stroop task (ST), or watching a documentary TV show about the Olympic Games (CON). Then, the athletes ran the simulated race (i.e. the 100 and 200-m dash). There was no condition (p > 0.05) or time effect (p > 0.05) for MPV, CMJ, 100-m, or 200-m dash performance. In conclusion, the present study results revealed no mental fatigue effect induced by SMA or ST on neuromuscular, 100-m or 200-m dash performance in male college sprinters.
... La prochaine évaluation permettra de quantifier les progrès et d'ajuster le programme si nécessaire. utilisent encore les lois de la mécanique de Newton appliquées au corps du sportif(Morin, Samozino, Murata, Cross, & Nagahara, 2019;Samozino et al., 2016), et ne nécessitent que de connaître la masse des sujets, et leurs temps de passage tous les 5 m, ou leur vitesse de course. ...
Article
Full-text available
La performance sportive est influencée par les capacités musculaires et physiques des athlètes. Les mesures de référence en laboratoire permettent d’évaluer les productions de force, vitesse, puissance dans des mouvements de saut, de sprint et de musculation, ou encore de biomécanique de la foulée de course, qui comptent parmi les déterminants biomécaniques de la performance sportive. Cependant, bien qu’historiquement développées « sur le terrain » notamment par les travaux d’Étienne-Jules Marey, ces techniques n’étaient pas accessibles au plus grand nombre de pratiquants et praticiens. Grâce au développement récent d’appareils photos et caméras haute fréquence (240 images/s) intégrés dans les smartphones et tablettes du fabricant Apple, des applications ont été inventées et validées par comparaison avec des mesures de référence. Elles utilisent des modèles biomécaniques validés par ailleurs pour calculer force, vitesse, puissance mécanique et performance en saut, lors d’une accélération en sprint, estimer la force maximale lors de mouvement de musculation ou des variables biomécaniques de la foulée de course et leur asymétrie. Le ratio coût/précision/simplicité élevé de ces applications a permis de générer des connaissances sur la performance sportive, mais également des avancées dans l’entraînement sportif qui auraient été impossibles sans la levée de ce verrou technologique.
... The 30-m sprints were evaluated using the MySprint app and in order to ensure successful performance, we followed the protocol of Samozino et al. (2016). The aim of this test was to run 30 m as fast as possible. ...
Article
This study analyzed the effects of with (WC) or without conducting a warm up on youth soccer players immediately before performing physical and cognitive tests. Fourteen youth soccer player (age 11.64 ± 0.50) participated in a counterbalanced cross-sectional study in which three conditions were tested: (a) basal lineal condition; (b) WC (immediately before the physical and cognitive tests); and (c) without WC (passive resting for 15 min between the warm-up and physical and cognitive tests). A 30-m sprint test, countermovement jump, and psychomotor vigilance task were also applied. The WC revealed significant improvements in countermovement jump (p < .05), 30-m sprint test performance (p < .05), and reaction time in psychomotor vigilance task (p < .05) in comparison to basal lineal condition and without WC. A 15-min rest after a warm-up has a meaningfully decremental effect on the physical and cognitive readiness of youth soccer players, in comparison with when they warm-up immediately before the demands are imposed.
... Phase 1 corresponded to the first movement made by the sprinter (determined by an increase in CoM velocity of 0.1 ms −1 ) to reach P max , Phase 2 was began at P max until V max and phase 3 began at V max until the end of the 40 m. We used the method proposed by Samozino to compute P max and the time at which it was reached Samozino et al., 2016). This simple method uses an mono-exponential model to describe the increase in velocity during the acceleration phase (Di Prampero et al., 2005) Figure 1. ...
... Sprint performance (split times 0-5, 0-10, 0-20, and 0-30-m), kinetic outputs and mechanical efficiency were computed pre-and post-training from the best time trial. Data was derived from a radar device (Stalker ATS Pro II, Applied Concepts, TX, USA), using a validated field method as reported previously (Haugen, Breitschädel & Samozino, 2018;Samozino et al., 2016;Morin et al., 2019). Individual linear sprint Force-Velocity (FV) profiles in the antero-posterior direction were calculated and thereafter relative theoretical maximal force (F0: N.kg −1 ), velocity (v0: m s −1 ), and maximal power (Pmax: W.kg −1 ) capabilities. ...
Thesis
Full-text available
Despite efforts to intervene, hamstring muscle injuries (HMI) continue to be one of the largest epidemiological burdens in professional football. The injury mechanism takes place dominantly during sprinting, but also other scenarios have been observed, such as overstretching actions, jumps, and change of directions. The main biomechanical roles of the hamstring muscles are functioning as an accelerator of center-of-mass (i.e., contributing to horizontal force production), and stabilizing the pelvis and knee joint. Multiple extrinsic and intrinsic risk factors have been identified, portraying the multifactorial nature of the HMI. Furthermore, these risk factors can vary substantially between players, portraying the importance of individualized approaches. However, there is a lack of multifactorial and individualized approaches assessed for validity in literature. Thus, the overarching aim of this doctoral thesis was to explore if a specific multifactorial and individualized approach can improve upon the ongoing HMI risk reduction protocols, and thus, further reduce the HMI risk in professional football players. This was done following the Team-sport Injury Prevention model (TIP model), where the target is to evaluate the current injury burden, identify possible solutions, and intervene. The thesis comprised of three themes within professional football, I) evaluating and identifying HMI risk (completed via assessing the current epidemiological HMI situation and the association between HMI injuries and a novel hamstring screening protocol), II) improving horizontal force capacity (completed via testing if maximal theoretical horizontal force (F0) can be improved via heavy resisted sprint training), and III) developing and conducting a multifactorial and individualized training for HMI risk reduction (completed via introducing and conducting a training intervention). The conclusions from theme I were that the HMI burden continues to be high (14.1 days absent per 1000 hours of football exposure), no tests from the screening protocol were associated with an increased HMI risk when including all injuries from the season (n = 17, p > 0.05), and that lower F0 was significantly associated with increased HMI risk when including injuries between test rounds one and two (~90 days, n =14, hazard ratio: 4.02 (CI95% 1.08 to 15.0), p = 0.04). For theme II, the players initial pre-season level of F0 was significantly associated with adaptation potential after 11 weeks of heavy resisted sprint training during the pre-season (r = -0.59, p < 0.05). The heavy resisted sprint load leading to a ~50% velocity loss induced the largest improvements in sprint mechanical output and sprint performance variables. For theme III, no intervention results could be presented within this document due to the Covid-19 pandemic leading to the intervention being postponed. However, a protocol paper was published, describing in detail the intervention approach that will be used outside the scope of the thesis. In future studies, larger sample size studies are needed to support the development of more advanced HMI risk reduction models. Such models may allow practitioners to identify risk on an individual level instead of a group level. Furthermore, constant development of more specific, reliable, and accessible risk assessment tests should be promoted that can be frequently tested throughout the football season. Finally, based on the results of theme II, individualization of a specific training stimulus should be promoted in team settings.
... A aptidão física específica é uma combinação de habilidade inata e adquirida que faz a diferença no desempenho dos atletas. 9 Assim, um teste de significância das diferenças foi realizado em 33 parâmetros de dois grupos de estudo a fim de eliminar os parâmetros com baixa discriminação e distinção. Porém, os parâmetros em potencial sugeridos pelos profissionais (estatura) foram deixados para a segunda seleção. ...
Article
Full-text available
Background: This study aimed to profile construct the specific fitness indices for teenage Chinese male sprinters to provide sprinting fitness assessment in teenage training. Methods: 229 comparative teenage male sprinters were recruited to participate test for the indices. T-test and Kruskal-Wallis were conducted for the first selection of fitness indices. In the second selection, principal components analysis was applied to select common factors with greater characteristic values. The chosen fitness indices were height, leg length B, (ankle circumferences/Achilles tendon length) ×100%, (thigh circumferences/leg length A) ×100%, Hemoglobin, 60m sprint time, 100m sprint time, countermovement-jump (CMJ) counter movement jump maximum velocity, CMJ flight time, CMJ maximum strength, CMJ power. Results: 13 indices were chosen for teenage Chinese male sprinters’ specific fitness with 3 general categories and 9 subcategories. Each weight of fitness indices was confirmed and made into a fitness assessment standard scale. Conclusions: Anthropometric indices indicate innate limits for athletes in structure of sprinting motion; physiological indices indicate athletes’ potential to express energy and recover in a short time; motor indices indicate athletes’ ability of maximum sprinting, reaction strength of lower extremity, power and maximum strength.
Background: The Yo-Yo Intermittent Recovery Test Level 1 (YYIR1) is often utilized to indirectly assess the cardiorespiratory fitness of team-sport athletes due to its proposed association with match-play high-speed running performance and predicted maximal oxygen uptake. No previous research has investigated the relationships between YYIR1 performances, actual oxygen uptake recorded during the YYIR1, and true all-out sprint kinetics (eg, maximal sprint speed, maximal force capacity, and maximal power output), which therefore served as the primary objective of this study. Objectives: To assess the true physiological kinetics (V˙O2 and heart-rate responses) during the YYIR1 and to evaluate the correlations between the physiological kinetics, sprint kinetics, and YYIR1 performance parameters. Methods: A total of 23 amateur male soccer players were recruited for the study (age 22.52 [2.86] y; height 1.75 [0.06] m; body mass 65.61 [8.43] kg). Each participant completed a YYIR1 and 2 all-out sprint tests. Results: Significant differences were observed between actual and predicted maximal oxygen-uptake values (Mdiff = 17.57 mL·kg-1·min-1, P < .001, r = .63). Shuttle distances showed statistically significant correlations with maximal sprint speed (r = .42, P = .044) and theoretic maximal speed (r = .44, P = .035). However, no other correlations with sprint kinetic parameters (eg, maximal force or power output) were observed. Conclusion: Practitioners should carefully consider the outcomes and utilities of the parameters derived from the YYIR1. The estimations of maximal oxygen uptake from shuttle performances as a proxy for cardiorespiratory fitness are not adequate. However, shuttle distances appear to be positively associated with all-out sprinting capacities.
Article
Full-text available
RESUMO Enqudramento-O sprint é um fator determinante para o desempenho em desportos coletivos como o futebol e o futsal. As relações força-potência-velocidade e eficácia mecânica têm sido recentemente utilizadas para analisar perfis de força-velocidade (F-V). O objetivo deste estudo era duplo: (1) quantificar os perfis biomecânicos F-V do sprint em jogadores de futebol e futsal portugueses; (2) analisar diferenças entre sexos, níveis competitivos e desportos nas variáveis em estudo. Métodos-4 jogadores de futebol (2 homens) e 4 jogadores de futsal (2 homens), com 26 ± 4,24 anos, realizaram 3 sprints máximos de 30 m a partir de uma posição de pé com 4 min de descanso entre sprints sucessivos. Foram recolhidos dados de vídeo com um Go Pro Hero (Full HD 1080p, 30 fps). O perfil de força-velocidade foi obtido com: F0 (N/kg), V0 (m/s), Pmax (W/kg), Sfv, RFmax (%), DRF (%), Vopt (m/s) e velocidade máxima (m/s). Results-Os jogadores masculinos mostraram um V0 (t =-7,12; p < 0,001, d = 5,04), Vopt (t =-2,90; p ≤ 0,05, d = 2,05) e velocidade máxima (t =-5,09; p ≤ 0,05, d = 3,60) mais alta do que nas jogadoras femininas. Não foram observadas diferenças com significado estatístico entre os níveis competitivos e o desporto. Conclusão-Estes resultados mostraram que os perfis mecânicos de sprint (F-V) são capazes de diferenciar entre jogadores masculinos e femininos de futebol e jogadores de futsal. Nenhuma diferença entre os níveis competitivos pode dever-se ao baixo nível competitivo da amostra. A investigação futura deve incluir diferentes níveis competitivos, tais como elite, subelite e recreativo. ABSTRACT Background: Sprint running is a key factor of performance for team sports as football and futsal. Force-power-velocity relationships and mechanical effectiveness have been recently used to analyse force-velocity (F-V) profiles. The aim of this study was twofold: (1) to quantify the sprint mechanical F-V profiles in Portuguese football and futsal players; (2) to analyse differences among sexes, competitive levels and sports on sprint mechanical variables in Portuguese football and futsal players.
Article
Full-text available
The aim of the study was to compare sprint mechanical parameters measured with timing gates and a laser gun. Thirty-four female team handball players (age: 17.0 ± 2.3 years, height: 1.70 ± 0.07 m, body mass: 66.7 ± 9.7 kg) performed three 30 m sprints in which the times were measured at 5, 10, 20 and 30 m with timing gates (accuracy 0.01 s) together with the distance over time by a laser gun. The main findings were that with a correction of +0.21 s (timing gates) the times and sprint mechanical properties calculated with the spreadsheet of Morin between timing gates and laser gun were not different. But when peak velocity was derived directly from the laser gun (Musclelab TM system) this was significantly higher than maximal velocity (v max), and lower than the theoretical maximal velocity (v 0) calculated with the spreadsheet. It was concluded that a correction of +0.21 s should be used to get correct mechanical properties when measuring with timing gates compared with laser gun measurements on an indoor court.
Article
This study examined which mechanical variables derived from a vertical jump (i.e., concentric peak force [ConcPF] and eccentric peak force [EccPF], flight time [FT]: contraction time [CT], eccentric deceleration rate of force development [EccDecRFD]), linear sprint (i.e., theoretical maximal force [F0] and velocity [V0], maximal power output [Pmax], the peak ratio of the effective horizontal component [RFpeak], and the index of force application technique [DRF]) determined the change of direction (COD) performance to a great extent. Sixteen male soccer players (age: 21.8 ± 2.9 years; height: 175.94 ± 6.88 cm; weight: 73.23 ± 9.59 kg) were assessed for a countermovement jump, the horizontal force velocity (FV) profile, and the COD ZigZag test. The horizontal FV profile parameters were significantly associated with COD performance, while jump mechanical variables did not show any significant association (r = 0.08 to 0.19; p > 0.05). Specifically, F0 (r = -0.56), Pmax (r = -0.68), and RFpeak (r = -0.54) were strongly associated with COD performance. Moreover, a 1 N·kg⁻¹ increase in F0 was associated with -0.11 s to complete the ZigZag test, whereas 1 W·kg⁻¹ and 1% increase in Pmax and RFpeak were associated with -0.05 and -0.03 s, respectively, to complete the COD test. Horizontal force production during sprinting might play a key role in COD performance. Assessing the horizontal FV profile might help coaches prescribe a specific training program to maximize sprint acceleration, which might improve COD performance.
Research
Full-text available
The subject of study on which this work focuses is related to high-performance track and field, specifically sprinting. The aim is to analyse a weakness in the entity where the university internships have been carried out in order to be able to implement proposals for improvement that optimise, in this case, sport performance. To do this, a group of sprint training belonging to the Club Escuela Atletismo Majadahonda were analysed, using various techniques such as direct observation, monitoring of training sessions or informal conversations with the coach and athletes. The main weakness observed was a high training load in the form of plyometric and strength work, of which the magnitude of metabolic and mechanical stress they can cause is unknown. These aspects are of great interest, as the existence of a relationship between jumping capacity, strength production and performance in high-intensity sprints is being considered. In order to establish a proposal for improvement, a broad theoretical framework will be described in which the determining aspects of the training process on sprinting performance will be presented. Finally, a series of practical tests with their respective technological tools are presented. In addition, recommendations are established in terms of the periodisation of the tests, the programming of the protocol and of these tests throughout the season. Once the effects of the training load are known with greater accuracy, a strength training programming proposal is described, prioritising certain exercises with a greater transfer to sprint performance. By way of conclusion, we reflect on the traditional training programmes with high fatiguing volumes, dismantling this old conception through evidence of the same effects with a reduction in training.
Chapter
This chapter presents a double perspective from theory to practice contributing to the scientific-based evidence what is behind the real examples of best sprinters over the world in order to understand how best coaches train in a daily basis and elite competition context. During From theory section we will introduce from a general perspective (i) the description of a sprint from the velocity–time curve describing the different phases and (ii) the muscular implications needed to each phase characterizing the forces during the sprint. Taking all this together will help readers to understand and have a better knowledge about the adequateness of sprint training methods. During From practice section we will focus on the main sprint training methods, trying to understand how coaches could use them considering the velocity–time curve and the forces during a sprint. This section aims to cover the main parameters to take into account when designing a sprint training program independently of sport with the possibility to orient the target to acceleration or maximal velocity as described in the previous section. This second part intends to cover the very general training principles sprint coaches do have in common, and to shed light on how they differ.
Article
Full-text available
Hamstring strain injury (HSI) is a common and costly injury in many sports such as the various professional football codes. Most HSIs have been reported to occur during high intensity sprinting actions. This observation has led to the suggestion that a link between sprinting biomechanics and HSIs may exist. The aim of this literature review was to evaluate the available scientific evidence underpinning the potential link between sprinting biomechanics and HSIs. A structured search of the literature was completed followed by a risk of bias assessment. A total of eighteen studies were retrieved. Sixteen studies involved retrospective and/or prospective analyses, of which only three were judged to have a low risk of bias. Two other case studies captured data before and after an acute HSI. A range of biomechanical variables have been measured, including ground reaction forces, trunk and lower-limb joint angles, hip and knee joint moments and powers, hamstring muscle–tendon unit stretch, and surface electromyographic activity from various trunk and thigh muscles. Overall, current evidence was unable to provide a clear and nonconflicting perspective on the potential link between sprinting biomechanics and HSIs. Nevertheless, some interesting findings were revealed, which hopefully will stimulate future research on this topic.
Article
Despite increased awareness of the multifactorial nature of Hamstring Strain Injury (HSI), the role of running biomechanics remains unclear. The aim of this systematic review was to investigate whether an association exists between running biomechanics and HSI. Five databases were searched from inception to January 2021. Eligibility criteria included epidemiological studies that provide data on running biomechanics in athletes who have sustained a HSI (retrospectively or prospectively) and compared to control data. Searches yielded 4,798 articles. Twelve met the selection criteria. Biomechanical analysis differed considerably across studies, thus meta-analyses was not possible. Studies largely found either no differences or contradicting findings between running biomechanics of athletes who have sustained a HSI (retrospectively or prospectively) and controls, with the exception of lateral trunk kinematics and horizontal propulsive forces. It is important to note some concern regarding the quality of included studies, particularly sample size, increasing the risk of bias associated with results. Further research utilising validated methods of biomechanical analysis, is needed to determine if an association exists between running biomechanics and HSI. Until then, definitive conclusions cannot be drawn as to whether specific biomechanical interventions should be included in injury prevention and/or rehabilitation programmes.
Article
Full-text available
The current literature has shown how working on coordination and agility produces effects on specific aspects in team sports. The purpose of this study was to examine the effects of a ten-week coordination training program applied to soccer on different tests that evaluate speed (30 m speed test), agility (Illinois Agility Test (IAT)) and lower body strength (countermovement jump (CMJ)). Forty U16 male soccer players from two nonprofessional teams (twenty in the control group (CG) (aged = 14.70 ± 0.47, body weight = 60.15 ± 8.07 kg, height = 1.71 ± 0.06 m) and twenty in the experimental group (EG) (aged = 14.50 ± 0.51, body weight = 58.08 ± 9.78 kg, height = 1.69 ± 0.06 m)) performed a combined coordination and agility program during 10 min every training day (3 days a week) for 10 weeks. The results of this study showed that coordination training produced adaptations in the power (CMJ of EG (p = 0.001)) and agility capacities (IAT of EG (p = 0.002)) of young soccer players, but not on speed performance at longer distances (CG, p = 0.20 and EG, p = 0.09). Despite the benefits of the training program, a combination of training methods that includes power, agility, speed, and strength can enhance such improvements.
Article
Full-text available
Research has not yet provided critical information for practitioners to determine the minimal detectable change (MDC) in sprint times or force-velocity-power characteristics. Therefore, the aim of this study was to establish the interday reliability and minimal detectable change of sprint times, and sprint force-velocity-power characteristics in junior Australian Football (AF) players. Seventeen players were assessed using a radar device that recorded instantaneous velocity during three maximal 30 m sprint accelerations performed on two non-consecutive days. Sprint force, velocity, and power characteristics were derived through inverse dynamics applied to the raw velocity time data. Relative and absolute reliability was determined by calculating the intraclass correlation coefficient (ICC), coefficient of variation (CV), and MDC. Data analysis was assessed for (i) the first trial; (ii) the best trial (the fastest 30 m split time); (iii) the average of the first two trials; and (iv) the average of all three trials; from each testing session. The main findings were 1) absolute theoretical maximum force (F0), theoretical maximal velocity (V0), absolute and relative maximum power (Pmax), maximum ratio of force (RFmax), maximum velocity (Vmax), and all sprint distance times (5 to 30 m) displayed acceptable reliability (CV < 10% and ICC > 0.75); and 2) the average of two and three trials was the best method of establishing reliable sprint times and force-velocity-power characteristics between sessions. This study provides important information for practitioners to determine the minimal detectable change in sprint times and force-velocity-power characteristics that allow coaches to identify true changes in performance.
Article
Full-text available
DOREL, S., A. COUTURIER, J.-R. LACOUR, H. VANDEWALLE, C. HAUTIER, and F. HUG. Force–Velocity Relationship in Cycling Revisited: Benefit of Two-Dimensional Pedal Forces Analysis. Med. Sci. Sports Exerc., Vol. 42, No. 6, pp. 1174–1183, 2010. Purpose: Maximal cycling exercise has been widely used to describe the power–velocity characteristics of lower-limb extensor muscles. This study investigated the contribution of each functional sector (i.e., extension, flexion, and transitions sectors) on the total force produced over a complete pedaling cycle. We also examined the ratio of effective force to the total pedal force, termed index of mechanical effectiveness (IE), in explaining differences in power between subjects. Methods: Two-dimensional pedal forces and crank angles were measured during a cycling force–velocity test performed by 14 active men. Mean values of forces, power output, and IE over four functional angular sectors were assessed: top = 330-–30-, downstroke = 30-–150-, bottom = 150-–210-, and upstroke = 210-–330-. Results: Linear and quadratic force–velocity and power–velocity relationships were obtained for downstroke and upstroke. Maximal power output (Pmax) generated over these two sectors represented, respectively, 73.6% T 2.6% and 10.3% T 1.8% of Pmax assessed over the entire cycle. In the whole group, Pmax over the complete cycle was significantly related to Pmax during the downstroke and upstroke. IE significantly decreased with pedaling rate, especially in bottom and upstroke. There were significant relationships between power output and IE for top and upstroke when the pedaling rate was below or around the optimal value and in all the sectors at very high cadences. Conclusions: Although data from force–velocity test primarily characterize the muscular function involved in the downstroke phase, they also reflect the flexor muscles’ ability to actively pull on the pedal during the upstroke. IE influences the power output in the upstroke phase and near the top dead center, and IE accounts for differences in power between subjects at high pedaling rates. Key Words: MAXIMAL POWER OUTPUT, INDEX OF EFFECTIVENESS, CYCLING BIOMECHANICS, MUSCULAR FUNCTION, SPRINT CYCLING
Article
Full-text available
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 R2 of 0.892 ± 0.049 and 0.950 ± 0.023) and quadratic (mean R2 = 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.
Article
Full-text available
To estimate the energetics and biomechanics of accelerated/decelerated running on flat terrain based on its biomechanical similarity to constant speed running up/down an 'equivalent slope' dictated by the forward acceleration (a f). Time course of a f allows one to estimate: (1) energy cost of sprint running (C sr), from the known energy cost of uphill/downhill running, and (2) instantaneous (specific) mechanical accelerating power (P sp = a f × speed). In medium-level sprinters (MLS), C sr and metabolic power requirement (P met = C sr × speed) at the onset of a 100-m dash attain ≈50 J kg(-1) m(-1), as compared to ≈4 for running at constant speed, and ≈90 W kg(-1). For Bolt's current 100-m world record (9.58 s) the corresponding values attain ≈105 J kg(-1) m(-1) and ≈200 W kg(-1). This approach, as applied by Osgnach et al. (Med Sci Sports Exerc 42:170-178, 2010) to data obtained by video-analysis during soccer games, has been implemented in portable GPS devices (GPEXE(©)), thus yielding P met throughout the match. Actual O2 consumed, estimated from P met assuming a monoexponential VO2 response (Patent Pending, TV2014A000074), was close to that determined by portable metabolic carts. Peak P sp (W kg(-1)) was 17.5 and 19.6 for MLS and elite soccer players, and 30 for Bolt. The ratio of horizontal to overall ground reaction force (per kg body mass) was ≈20 % larger, and its angle of application in respect to the horizontal ≈10° smaller, for Bolt, as compared to MLS. Finally, we estimated that, on a 10 % down-sloping track Bolt could cover 100 m in 8.2 s. The above approach can yield useful information on the bioenergetics and biomechanics of accelerated/decelerated running.
Article
Full-text available
Abstract Athletes use weighted sled towing to improve sprint ability, but little is known about its biomechanics. The purpose of this study was to investigate the effect of weighted sled towing with two different loads on ground reaction force. Ten physically active men (mean ± SD: age 27.9 ± 1.9 years; stature 1.76 ± 0.06 m; body mass 80.2 ± 9.6 kg) performed 5 m sprints under three conditions; (a) unresisted, (b) towing a sled weighing 10% of body mass (10% condition) and (c) towing a sled weighing 30% of body mass (30% condition). Ground reaction force data during the second ground contact after the start were recorded and compared across the three conditions. No significant differences between the unresisted and 10% conditions were evident, whereas the 30% condition resulted in significantly greater values for the net horizontal and propulsive impulses (P < 0.05) compared with the unresisted condition due to longer contact time and more horizontal direction of force application to the ground. It is concluded that towing a sled weighing 30% of body mass requires more horizontal force application and increases the demand for horizontal impulse production. In contrast, the use of 10% body mass has minimal impact on ground reaction force.
Article
Full-text available
This study sought to lend experimental support to the theoretical influence of force-velocity (F-v) mechanical profile on jumping performance independently from the effect of maximal power output (P max ). 48 high-level athletes (soccer players, sprinters, rugby players) performed maximal squat jumps with additional loads from 0 to 100% of body mass. During each jump, mean force, velocity and power output were obtained using a simple computation method based on flight time, and then used to determine individual linear F-v relationships and P max values. Actual and optimal F-v profiles were computed for each subject to quantify mechanical F-v imbalance. A multiple regression analysis showed, with a high-adjustment quality (r²=0.931, P<0.001, SEE=0.015 m), significant contributions of P max , F-v imbalance and lower limb extension range (h PO ) to explain interindividual differences in jumping performance (P<0.001) with positive regression coefficients for P max and h PO and a negative one for F-v imbalance. This experimentally supports that ballistic performance depends, in addition to P max , on the F-v profile of lower limbs. This adds support to the actual existence of an individual optimal F-v profile that maximizes jumping performance, a F-v imbalance being associated to a lower performance. These results have potential strong applications in the field of strength and conditioning.
Article
Full-text available
The interaction between step kinematics and stance kinetics determines sprint velocity. However, the influence stance kinetics has upon effective acceleration in field sport athletes requires clarification. 25 men (age = 22.4 ± 3.2 years; mass = 82.8 ± 7.2 kilograms; height = 1.81 ± 0.07 m) completed 12 10-meter (m) sprints, 6 sprints each for kinematic and kinetic assessment. Pearson's correlations (p ≤ 0.05) examined relationships between: 0-5, 5-10, and 0-10 m velocity; step kinematics (mean step length [SL]; step frequency; contact time [CT]; flight time over each interval); and stance kinetics (relative vertical, horizontal, and resultant force and impulse; resultant force angle; ratio of horizontal to resultant force [RatF] for the first, second, and last contacts within the 10-m sprint). Relationships were found between 0-5, 5-10 and 0-10 m SL, and 0-5 and 0-10 m velocity (r = 0.397-0.535). 0-5 and 0-10 m CT correlated with 5-10 m velocity (r = -0.506 and -0.477, respectively). Last contact vertical force correlated with 5-10 m velocity (r = 0.405). Relationships were established between second and last contact vertical and resultant force, and contact time over all intervals (r = -0.398--0.569). First and second contact vertical impulse correlated with 0-5 m SL (r = 0.434 and 0.442, respectively). Subjects produced resultant force angles and RatF suitable for horizontal force production. Faster acceleration in field sport athletes involved longer steps, with shorter contact times. Greater vertical force production was linked with shorter contact times, illustrating efficient force production. Greater step lengths during acceleration were facilitated by higher vertical impulse, and appropriate horizontal force. Speed training for field sport athletes should be tailored to encourage these technique adaptations.
Article
Full-text available
This series of reviews focuses on the most important neuromuscular function in many sport performances, the ability to generate maximal muscular power. Part 1 focuses on the factors that affect maximal power production, while part 2, which will follow in a forthcoming edition of Sports Medicine, explores the practical application of these findings by reviewing the scientific literature relevant to the development of training programmes that most effectively enhance maximal power production. The ability of the neuromuscular system to generate maximal power is affected by a range of interrelated factors. Maximal muscular power is defined and limited by the force-velocity relationship and affected by the length-tension relationship. The ability to generate maximal power is influenced by the type of muscle action involved and, in particular, the time available to develop force, storage and utilization of elastic energy, interactions of contractile and elastic elements, potentiation of contractile and elastic filaments as well as stretch reflexes. Furthermore, maximal power production is influenced by morphological factors including fibre type contribution to whole muscle area, muscle architectural features and tendon properties as well as neural factors including motor unit recruitment, firing frequency, synchronization and inter-muscular coordination. In addition, acute changes in the muscle environment (i.e. alterations resulting from fatigue, changes in hormone milieu and muscle temperature) impact the ability to generate maximal power. Resistance training has been shown to impact each of these neuromuscular factors in quite specific ways. Therefore, an understanding of the biological basis of maximal power production is essential for developing training programmes that effectively enhance maximal power production in the human.
Article
Full-text available
This study aimed to determine the measurement error associated with estimates of velocity from a laser-based device during different phases of a maximal athletic sprint. Laser-based displacement data were obtained from 10 sprinters completing a total of 89 sprints and were fitted with a fifth-order polynomial function which was differentiated to obtain instantaneous velocity data. These velocity estimates were compared against criterion high-speed video velocities at either 1, 5, 10, 30 or 50 m using a Bland-Altman analysis to assess bias and random error. Bias was highest at 1 m (+ 0.41 m/s) and tended to decrease as the measurement distance increased, with values less than + 0.10 m/s at 30 and 50 m. Random error was more consistent between distances, and reached a minimum value (±0.11 m/s) at 10 m. Laser devices offer a potentially useful time-efficient tool for assessing between-subject or between-session performance from the mid-acceleration and maximum velocity phases (i. e., at 10 m and beyond), although only differences exceeding 0.22-0.30 m/s should be considered genuine. However, laser data should not be used during the first 5 m of a sprint, and are likely of limited use for assessing within-subject variation in performance during a single session.
Article
Full-text available
Force-velocity relationships reported in the literature for functional tasks involving a combination of joint rotations tend to be quasi-linear. The purpose of this study was to explain why they are not hyperbolic, like Hill's relationship. For this purpose, a leg press task was simulated with a musculoskeletal model of the human leg, which had stimulation of knee extensor muscles as only independent input. In the task the ankles moved linearly, away from the hips, against an imposed external force that was reduced over contractions from 95 to 5% of the maximum isometric value. Contractions started at 70% of leg length, and force and velocity values were extracted when 80% of leg length was reached. It was shown that the relationship between leg extension velocity and external force was quasi-linear, while the relationship between leg extension velocity and muscle force was hyperbolic. The discrepancy was explained by the fact that segmental dynamics canceled more and more of the muscle force as the external force was further reduced and velocity became higher. External power output peaked when the imposed external force was ∼50% of maximum, while muscle power output peaked when the imposed force was only ∼15% of maximum; in the latter case ∼70% of muscle power was buffered by the leg segments. According to the results of this study, there is no need to appeal to neural mechanisms to explain why, in leg press tasks, the force-velocity relationship is quasi-linear rather than hyperbolic.
Article
Full-text available
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.
Article
Full-text available
We investigated the changes in the technical ability of force application/orientation against the ground vs. the physical capability of total force production after a multiple-set repeated sprints series. Twelve male physical education students familiar with sprint running performed four sets of five 6-s sprints (24s of passive rest between sprints, 3min between sets). Sprints were performed from a standing start on an instrumented treadmill, allowing the computation of vertical (F(V)), net horizontal (F(H)) and total (F(Tot)) ground reaction forces for each step. Furthermore, the ratio of forces was calculated as RF=F(H)F(Tot)(-1), and the index of force application technique (D(RF)) representing the decrement in RF with increase in speed was computed as the slope of the linear RF-speed relationship. Changes between pre- (first two sprints) and post-fatigue (last two sprints) were tested using paired t-tests. Performance decreased significantly (e.g. top speed decreased by 15.7±5.4%; P<0.001), and all the mechanical variables tested significantly changed. F(H) showed the largest decrease, compared to F(V) and F(Tot). D(RF) significantly decreased (P<0.001, effect size=1.20), and the individual magnitudes of change of D(RF) were significantly more important than those of F(Tot) (19.2±20.9 vs. 5.81±5.76%, respectively; P<0.01). During a multiple-set repeated sprint series, both the total force production capability and the technical ability to apply force effectively against the ground are altered, the latter to a larger extent than the former.
Article
Full-text available
The study's purpose was to determine the respective influences of the maximal power (Pmax) and the force-velocity (F-v) mechanical profile of the lower limb neuromuscular system on performance in ballistic movements. A theoretical integrative approach was proposed to express ballistic performance as a mathematical function of Pmax and F-v profile. This equation was (i) validated from experimental data obtained on 14 subjects during lower limb ballistic inclined push-offs and (ii) simulated to quantify the respective influence of Pmax and F-v profile on performance. The bias between performances predicted and obtained from experimental measurements was 4%-7%, confirming the validity of the proposed theoretical approach. Simulations showed that ballistic performance was mostly influenced not only by Pmax but also by the balance between force and velocity capabilities as described by the F-v profile. For each individual, there is an optimal F-v profile that maximizes performance, whereas unfavorable F-v balances lead to differences in performance up to 30% for a given Pmax. This optimal F-v profile, which can be accurately determined, depends on some individual characteristics (limb extension range, Pmax) and on the afterload involved in the movement (inertia, inclination). The lower the afterload, the more the optimal F-v profile is oriented toward velocity capabilities and the greater the limitation of performance imposed by the maximal velocity of lower limb extension. 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.
Article
Full-text available
We transposed the concept of effectiveness of force application used in pedaling mechanics to calculate the ratio of forces (RF) during sprint running and tested the hypothesis that field sprint performance was related to the technical ability to produce high amounts of net positive horizontal force. This ability represents how effectively the total force developed by the lower limbs is applied onto the ground, despite increasing speed during the acceleration phase. Twelve physically active male subjects (including two sprinters) performed 8-s sprints on a recently validated instrumented treadmill, and a 100-m sprint on an athletics track. Mean vertical (FV), net horizontal (FH), and total (FTot) ground reaction forces measured at each step during the acceleration allowed computation of the RF as FH/FTot and an index of force application technique (DRF) as the slope of the RF-speed linear relationship from the start until top speed. Correlations were tested between these mechanical variables and field sprint performance variables measured by radar: mean and top 100-m speeds and 4-s distance. Significant (r > 0.731; P < 0.01) correlations were obtained between DRF and 100-m performance (mean and top speeds; 4-s distance). Further, FH was significantly correlated (P < 0.05) to field sprint performance, but FTot and FV were not. 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.
Article
Full-text available
We investigated the differences in performance between 100-m sprints performed on a sprint treadmill recently validated versus on a standard track. To date, studies comparing overground and treadmill running have mainly focused on constant and not maximal "free" running speed, and compared running kinetics and kinematics over a limited number of steps, but not overall sprint performance. Eleven male physical education students including two sprinters performed one 100-m on the treadmill and one on a standard athletics track in a randomized order, separated by 30 min. Performance data were derived in both cases from speed-time relationships measured with a radar and with the instrumented sprint treadmill, which allowed subjects to run and produce speed "freely", i.e. with no predetermined belt speed imposed. Field and treadmill typical speed-distance curves and data of maximal and mean speed, 100-m time and acceleration/deceleration time constants were compared using t tests and field-treadmill correlations were tested. All the performance parameters but time to reach top speed and deceleration time constant differed significantly, by about 20% on average, between field and treadmill (e.g. top speed of 8.84 ± 0.51 vs. 6.90 ± 0.39 m s(-1)). However, significant correlations were found (r > 0.63; P < 0.05) for all the performance parameters except time to reach top speed. Treadmill and field 100-m sprint performances are different, despite the fact that subjects could freely accelerate the belt. However, the significant correlations found make it possible to investigate and interpret inter-individual differences in field performance from treadmill measurements.
Article
Full-text available
The aim of the present study was to measure during a sprint start the joint angular velocity and the kinetic energy of the different segments in elite sprinters. This was performed using a 3D kinematic analysis of the whole body. Eight elite sprinters (10.30+/-0.14s 100 m time), equipped with 63 passive reflective markers, realised four maximal 10 m sprints start on an indoor track. An opto-electronic Motion Analysis system consisting of 12 digital cameras (250 Hz) was used to collect the 3D marker trajectories. During the pushing phase on the blocks, the 3D angular velocity vector and its norm were calculated for each joint. The kinetic energy of 16 segments of the lower and upper limbs and of the total body was calculated. The 3D kinematic analysis of the whole body demonstrated that joints such as shoulders, thoracic or hips did not reach their maximal angular velocity with a movement of flexion-extension, but with a combination of flexion-extension, abduction-adduction and internal-external rotation. The maximal kinetic energy of the total body was reached before clearing block (respectively, 537+/-59.3 J vs. 514.9+/-66.0 J; p< or =0.01). These results suggested that a better synchronization between the upper and lower limbs could increase the efficiency of pushing phase on the blocks. Besides, to understand low interindividual variances in the sprint start performance in elite athletes, a 3D complete body kinematic analysis shall be used.
Article
Full-text available
Maximal cycling exercise has been widely used to describe the power-velocity characteristics of lower-limb extensor muscles. This study investigated the contribution of each functional sector (i.e., extension, flexion, and transitions sectors) on the total force produced over a complete pedaling cycle. We also examined the ratio of effective force to the total pedal force, termed index of mechanical effectiveness (IE), in explaining differences in power between subjects. Two-dimensional pedal forces and crank angles were measured during a cycling force-velocity test performed by 14 active men. Mean values of forces, power output, and IE over four functional angular sectors were assessed: top = 330 degrees -30 degrees , downstroke = 30 degrees -150 degrees , bottom = 150 degrees -210 degrees , and upstroke = 210 degrees -330 degrees . Linear and quadratic force-velocity and power-velocity relationships were obtained for downstroke and upstroke. Maximal power output (Pmax) generated over these two sectors represented, respectively, 73.6% +/- 2.6% and 10.3% +/- 1.8% of Pmax assessed over the entire cycle. In the whole group, Pmax over the complete cycle was significantly related to Pmax during the downstroke and upstroke. IE significantly decreased with pedaling rate, especially in bottom and upstroke. There were significant relationships between power output and IE for top and upstroke when the pedaling rate was below or around the optimal value and in all the sectors at very high cadences. Although data from force-velocity test primarily characterize the muscular function involved in the downstroke phase, they also reflect the flexor muscles' ability to actively pull on the pedal during the upstroke. IE influences the power output in the upstroke phase and near the top dead center, and IE accounts for differences in power between subjects at high pedaling rates.
Article
Full-text available
Our aim was to clarify the relationship between power output and the different mechanical parameters influencing it during squat jumps, and to further use this relationship in a new computation method to evaluate power output in field conditions. Based on fundamental laws of mechanics, computations were developed to express force, velocity and power generated during one squat jump. This computation method was validated on eleven physically active men performing two maximal squat jumps. During each trial, mean force, velocity and power were calculated during push-off from both force plate measurements and the proposed computations. Differences between the two methods were not significant and lower than 3% for force, velocity and power. The validity of the computation method was also highlighted by Bland and Altman analyses and linear regressions close to the identity line (P<0.001). The low coefficients of variation between two trials demonstrated the acceptable reliability of the proposed method. The proposed computations confirmed, from a biomechanical analysis, the positive relationship between power output, body mass and jump height, hitherto only shown by means of regression-based equations. Further, these computations pointed out that power also depends on push-off vertical distance. The accuracy and reliability of the proposed theoretical computations were in line with those observed when using laboratory ergometers such as force plates. Consequently, the proposed method, solely based on three simple parameters (body mass, jump height and push-off distance), allows to accurately evaluate force, velocity and power developed by lower limbs extensor muscles during squat jumps in field conditions.
Article
Full-text available
Anaerobic tests are divided into tests measuring anaerobic power and anaerobic capacity. Anaerobic power tests include force-velocity tests, vertical jump tests, staircase tests, and cycle ergometer tests. The values of maximal anaerobic power obtained with these different protocols are different but generally well correlated. Differences between tests include factors such as whether average power or instantaneous power is measured, active muscle mass is the same in all the protocols, the legs act simultaneously or successively, maximal power is measured at the very beginning of exercise or after several seconds, inertia of the devices and body segments are taken into account. Force-velocity tests have the advantage of enabling the estimation of the force and velocity components of power, which is not possible with tests such as a staircase test, a vertical jump, the Wingate test and other long-duration cycle ergometer protocols. Maximal anaerobic capcity tests are subdivided into maximal oxygen debt test, ergometric tests (all-out tests and constant load tests), measurement of oxygen deficit during a constant load test and measurement of peak blood lactate. The measurement of the maximal oxygen debt is not valid and reliable enough to be used as an anaerobic capacity test. The aerobic metabolism involvement during anaerobic capacity tests, and the ignorance of the mechanical efficiency, limit the validity of the ergometric tests which are only based on the measurement of work. The amount of work performed during the Wingate test depends probably on glycolytic and aerobic power as well as anaerobic capacity. The fatigue index (power decrease) of the all-out tests is not reliable and depends probably on aerobic power as well as the fast-twich fibre percentage. Reliability of the constant load tests has seldom been studied and has been found to be rather low. In theory, the measure of the oxygen deficit during a constant load test is more valid than the other tests but its reliability is unknown. The validity and reliability of postexercise blood lactate as a test of maximal anaerobic capacity are probably not better than that of the current ergometric tests. The choice of an anaerobic test depends on the aims and subjects of a study and its practicability within a testing session.
Article
Full-text available
Although sprint performance undoubtedly involves muscle power, the stiffness of the leg also determines sprint performance while running at maximal velocity. Results that include both of these characteristics have not been directly obtained in previous studies on human runners. We have therefore studied the link between leg power, leg stiffness, and sprint performance. The acceleration and maximal running velocity developed by 11 subjects (age 16 +/- 1) during a 40-m sprint were measured by radar. Their leg muscle volumes were estimated anthropometrically. Leg power was measured by an ergometric treadmill test and by a hopping test. Each subject executed a maximal sprint acceleration on the treadmill equipped with force and speed transducers, from which forward power was calculated. A hopping jump test was executed at 2 Hz on a force platform. Leg stiffness was calculated using the flight and contact times of the hopping test. The treadmill forward leg power was correlated with both the initial acceleration (r = 0.80, P < 0.01) and the maximal running velocity (r = 0.73, P < 0.05) during track sprinting. The leg stiffnes