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

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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.

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... Mechanical effectiveness RF represents the ability of the runner to direct the application of the force against the ground more horizontally (for more information see ). On the other hand, D RF is the rate of decrease in RF with increasing speed during sprint acceleration and is computed as the slope of the linear relationship between RF and velocity (Morin et al., 2012;Morin and Samozino, 2016;Samozino et al., 2016). DRF is used to describe the subject's capacity to maintain a forward horizontal orientation of the resultant ground-reaction force. ...
... We collected data of participants with PD and HC using an iPhone 6 and the MySprint App (Apple Inc., USA), through a high-speed video recording with sampling frequency of 240 Hz and at a quality of 720p. To calibrate the area of acquisition, we placed six markers at 5, 10, 15, 20, 25 and 30-m of the track, and the iPhone 6 and the MySprint App was placed at a height of 1 m over the ground and approximately 10 m the six markers (Barbalho et al., n.d.;Romero-Franco et al., 2017;Samozino et al., 2016). ...
... Data of physical qualities, mechanical effectiveness, and sprint performance were acquired during the sprint-running test with MySprint APP (Apple Inc., USA) (Romero-Franco et al., 2017;Samozino et al., 2016) for subjects with PD and HC subjects . Two videos about the sprint running are given in the Supplementary Material (S1 and S2). ...
Article
Background: High-intensity training, a still unexplored exercise for individuals with Parkinson's disease, is positively related with increased functionality and aerobic profile in healthy individuals. The aim of this work was to evaluate the feasibility, safety, and acceptance of sprint running in individuals with mild-to-moderate Parkinson's. Additionally, we compared sprint biomechanical outputs of force, velocity and power between individuals with Parkinson's disease and healthy. Methods: Physically trained subjects with Parkinson's, men, (n = 16, 64:9.01 years, stage between 1 and 3 in the Hoehn and Yahr, 16.8:7.1 at Unified Parkinson's disease Rating Scales, and control group (n = 21, 65:9.27 years) performed 20 m sprint sessions. We analyzed the self-reported satisfaction and acceptance using a self-administered questionnaire, and the sprint biomechanics and performance based on high-speed video recordings. Findings: All participants completed the tests with high feasibility, acceptability and satisfaction scores. The sprint maximal force and maximal power outputs were higher in Parkinson's disease. Conversely, control group showed higher mechanical effectiveness values. Interestingly, no difference in velocity capabilities and overall 20-m sprint performance was observed between groups, possibly explained by different mechanical strategies in both groups over the sprint accelerations. Linear regression analyses showed that physical qualities are predictors of mechanical effectiveness, and mechanical variables are important determinants of sprint performance on Parkinson's disease. Interpretation: Sprint is a feasible exercise for people with mild-to-moderate Parkinson's disease. Even though differences in physical qualities and mechanical effectiveness exist between subjects with Parkinson's disease and healthy, there is no overall substantial impact on sprint running performance.
... 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
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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 (F0), theoretical maximal velocity (V0) and theoretical maximal power output (Pmax)) 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, V0 and Pmax 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 (F0) 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.
... This is in contrast to maximal velocity running where Weyand et al. (91) showed that the magnitude of GRF production, oriented vertically over the contact phase, was the limiting factor to performance. Effectively applying lower limb force in a horizontal direction as velocity increases has been referred to as mechanical effectiveness (75). This mechanical description is underpinned by the force applied by the athlete across the acceleration effort and describes the ratio of the net horizontal component and resultant GRF across the acceleration (61). ...
... Mechanical variables such as force and velocity play a vital role in ballistic activities such as sprinting and determine overall neuromuscular performance (75). However, these variables are in a sense limiting given that the force produced and the shortening velocity of skeletal muscle are constrained by morphological factors such as fiber type, fascicle length, pennation angle, and neural mechanisms such as motor unit recruitment and intramuscular coordination (21). ...
... When starting from zero velocity, the impulse will be a combination of force applied over longer ground contacts, and as velocity increases, the time in which force can be applied reduces, therefore making quality force application at ground contact critical. Although net horizontal force determines the rate of acceleration (70,75), the impulsemomentum relationship governs the time in which force is applied; it has been shown that this factor accounts for slow or fast rates of acceleration, where shorter contact times beget the need for increased force expression. Hunter et al. (40) identified in a series of 25-m sprints that the greatest variance (61%) occurred with the horizontal impulse measured at the 16-m mark. ...
... This is in contrast to maximal velocity running where Weyand et al. (91) showed that the magnitude of GRF production, oriented vertically over the contact phase, was the limiting factor to performance. Effectively applying lower limb force in a horizontal direction as velocity increases has been referred to as mechanical effectiveness (75). This mechanical description is underpinned by the force applied by the athlete across the acceleration effort and describes the ratio of the net horizontal component and resultant GRF across the acceleration (61). ...
... Mechanical variables such as force and velocity play a vital role in ballistic activities such as sprinting and determine overall neuromuscular performance (75). However, these variables are in a sense limiting given that the force produced and the shortening velocity of skeletal muscle are constrained by morphological factors such as fiber type, fascicle length, pennation angle, and neural mechanisms such as motor unit recruitment and intramuscular coordination (21). ...
... When starting from zero velocity, the impulse will be a combination of force applied over longer ground contacts, and as velocity increases, the time in which force can be applied reduces, therefore making quality force application at ground contact critical. Although net horizontal force determines the rate of acceleration (70,75), the impulsemomentum relationship governs the time in which force is applied; it has been shown that this factor accounts for slow or fast rates of acceleration, where shorter contact times beget the need for increased force expression. Hunter et al. (40) identified in a series of 25-m sprints that the greatest variance (61%) occurred with the horizontal impulse measured at the 16-m mark. ...
... Each sprint was measured by means of a Radar device with a 46.9 Hz sampling frequency (Stalker ATS II Version 5.0.2.1, Applied Concepts, Dallas, TX, USA), which was placed on a tripod 10 meters behind the subjects at a height of 1 meter corresponding approximately to the height of subjects' center of mass [26,27]. From these speed-time measurements, a macroscopic biomechanical analysis-based on the laws of motion [28] was used to calculate the maximal horizontal external power (P max (W�kg -1 )), velocity (v 0 (m�s -1 )) and force (F 0 (N�kg -1 )) mechanical outputs during the acceleration. In addition, the ratio of force was calculated as the horizontal component of the ground reaction force divided by the resultant ground reaction force, and the maximal value of this ratio (RF max (%)) was used as an indicator of the players ability to orient the ground reaction force in the forward direction at the beginning of their acceleration. ...
... The higher the RF max , the more forward the force orientation during the early phase of acceleration. Finally, sprint performance was described via the measurement of 5 m (s) and 20 m (s) times, as derived from the fitted speed-time curves (see [28] for more details) [28]. ...
... The higher the RF max , the more forward the force orientation during the early phase of acceleration. Finally, sprint performance was described via the measurement of 5 m (s) and 20 m (s) times, as derived from the fitted speed-time curves (see [28] for more details) [28]. ...
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Aims The purpose of this study was to compare the effects of hamstring eccentric (NHE) strength training versus sprint training programmed as complements to regular soccer practice, on sprint performance and its mechanical underpinnings, as well as biceps femoris long head (BFlh) architecture. Methods In this prospective interventional control study, sprint performance, sprint mechanics and BFlh architecture variables were compared before versus after six weeks of training during the first six preseason weeks, and between three different random match-pair groups of soccer players: “Soccer group” (n = 10), “Nordic group” (n = 12) and “Sprint group” (n = 10). Results For sprint performance and mechanics, small to large pre-post improvements were reported in “Sprint group” (except maximal running velocity), whereas only trivial to small negative changes were reported in “Soccer group” and “Nordic group”. For BFlh architecture variables, “Sprint” group showed moderate increase in fascicle length compared to smaller augment for the “Nordic” group with trivial changes for “Soccer group”. Only “Nordic” group presented small increases at pennation angle. Conclusions The results suggest that sprint training was superior to NHE in order to increase BFlh fascicle length although only the sprint training was able to both provide a preventive stimulus (increase fascicle length) and at the same time improve both sprint performance and mechanics. Further studies with advanced imaging techniques are needed to confirm the validity of the findings.
... More recently, Morin and Samozino (23) have recommended the assessment of the entire force-velocity (Fv) spectrum during sprint acceleration (i.e., horizontal Fv profile) to obtain more comprehensive and meaningful information about the determinants of linear sprint performance. Due to the consistent and clear linearity of the sprint Fv relationship, the maximal capacities of the muscles to produce force (F0), velocity (v0), and power (Pmax) can be determined through the application of a linear regression model (17,30). Other variables that are also known to influence linear sprint performance can also be determined using this novel testing procedure: Fv slope (i.e., the ratio between F0 and v0), decrease in the ratio of horizontal-to-resultant force (DRF), and maximal ratio of horizontal-to-resultant force (RFpeak) (23,30). ...
... Due to the consistent and clear linearity of the sprint Fv relationship, the maximal capacities of the muscles to produce force (F0), velocity (v0), and power (Pmax) can be determined through the application of a linear regression model (17,30). Other variables that are also known to influence linear sprint performance can also be determined using this novel testing procedure: Fv slope (i.e., the ratio between F0 and v0), decrease in the ratio of horizontal-to-resultant force (DRF), and maximal ratio of horizontal-to-resultant force (RFpeak) (23,30). All the variables of the sprint Fv profile (i.e., F0, v0, Fv slope, Pmax, DRF, and RFpeak) can now be simply but accurately determined during an unloaded maximal sprint in which the athlete reaches top speed (≈ 30 meters are needed in soccer players) through the recording of either the displacement-or velocity-time data (16,29,30). ...
... Other variables that are also known to influence linear sprint performance can also be determined using this novel testing procedure: Fv slope (i.e., the ratio between F0 and v0), decrease in the ratio of horizontal-to-resultant force (DRF), and maximal ratio of horizontal-to-resultant force (RFpeak) (23,30). All the variables of the sprint Fv profile (i.e., F0, v0, Fv slope, Pmax, DRF, and RFpeak) can now be simply but accurately determined during an unloaded maximal sprint in which the athlete reaches top speed (≈ 30 meters are needed in soccer players) through the recording of either the displacement-or velocity-time data (16,29,30). ...
Article
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This study aimed to describe the seasonal changes in the sprint force-velocity (Fv) profile of professional soccer players. The sprint Fv profile of 21 male soccer players competing in the first division of the Spanish soccer league was evaluated 6 times: preseason 1 (September 2015), in-season 1 (November 2015), in-season 2 (January 2016), in-season 3 (March 2016), in-season 4 (May 2016), and preseason 2 (August 2016). No specific sprint capabilities stimuli other than those induced by soccer training were applied. The following variables were calculated from the velocity-time data recorded with a radar device during an unloaded sprint: maximal force (F0), maximal velocity (v0), Fv slope, maximal power (Pmax), decrease in the ratio of horizontal-to-resultant force (DRF), and maximal ratio of horizontal-to-resultant force (RFpeak). F0 (effect size [ES] range = 0.83–0.93), Pmax (ES range = 0.97–1.05), and RFpeak (ES range = 0.56–1.13) were higher at the in-seasons 2 and 3 compared with both preseasons (p ≤ 0.006). No significant differences were observed for v0, Fv slope, and DRF (p ≥ 0.287). These results suggest that relevant Fv profile variables may be compromised (F0 more compromised than v0) toward the end of the competitive season when specific sprint stimuli are not systematically applied.
... Recently, Samozino et al. (36) introduced a field-based method of assessing an athlete's sprint ability and the mechanical determinants associated with sprint performance (horizontal power, force, and velocity variables) (9,36). Mechanical properties (peak horizontal power, theoretical maximum horizontal force, and velocity) of an individual's force-velocity sprinting profile (F-v) were derived from equations that used split times, anthropometric, and spatiotemporal data of the athlete (equations 1-9; see Methods section) (36). ...
... Recently, Samozino et al. (36) introduced a field-based method of assessing an athlete's sprint ability and the mechanical determinants associated with sprint performance (horizontal power, force, and velocity variables) (9,36). Mechanical properties (peak horizontal power, theoretical maximum horizontal force, and velocity) of an individual's force-velocity sprinting profile (F-v) were derived from equations that used split times, anthropometric, and spatiotemporal data of the athlete (equations 1-9; see Methods section) (36). ...
... Recently, Samozino et al. (36) introduced a field-based method of assessing an athlete's sprint ability and the mechanical determinants associated with sprint performance (horizontal power, force, and velocity variables) (9,36). Mechanical properties (peak horizontal power, theoretical maximum horizontal force, and velocity) of an individual's force-velocity sprinting profile (F-v) were derived from equations that used split times, anthropometric, and spatiotemporal data of the athlete (equations 1-9; see Methods section) (36). This approach was found to be highly valid (p , 0.001, r 5 0.826-0.978) ...
Article
Morris, CG, Weber, JA, and Netto, KJ. Relationship between mechanical effectiveness in sprint running and force-velocity characteristics of a countermovement jump in Australian rules football athletes. J Strength Cond Res XX(X): 000-000, 2020-This study evaluated the mechanical determinants of 40-m sprint performance in elite Australian Rules Football (ARF) athletes and identified variables of countermovement jumps (CMJs) that related to the sprint. Fourteen elite male ARF athletes (age = 22.7 ± 3.6 years; height = 1.88 ± 0.08 m; mass = 88.2 ± 9.38 kg) completed two 40-m sprints and 3 CMJs. Sprint mechanics were calculated using inverse dynamic methods from sprint times, anthropometric and spatiotemporal data, whereas CMJ variables were obtained from in-ground force plates. Associations between sprint mechanics, sprint performance, and CMJ variables were identified using Pearson's correlation coefficient. A p-value of <0.036 was considered statistically significant for all analyses after performing Bonferroni correction adjustment. Relative peak running power was significantly correlated (p < 0.036, r = -0.781 to -0.983) with sprint split times across all distances (5-40 m). Relative maximum horizontal force significantly correlated with acceleration performance (0-20 m, p < 0.036, r = -0.887 to -0.989). Maximum running velocity was significantly correlated (p < 0.036, r = -0.714 to -0.970) with sprint times across 20-40 m. Relative peak force in the CMJ was significantly associated (p < 0.036, r = -0.589 to -0.630) with sprint kinetics (power and horizontal force) and 5-20-m sprint times. Jump height and concentric time in the CMJ were significantly (p < 0.036) correlated with sprint time at 20 m (r = -0.550 and r = 0.546), respectively. These results indicate emphasis should be placed on training protocols that improve relative peak power, particularly in time-constrained environments such as team sports, focusing on maximal force production or maximal running velocity ability. Furthermore, associations between CMJ variables and sprint performance provide practitioners with an approach to assess sprint performance in-season, monitor training adaptations and further individualize training interventions, without requiring maximal sprint testing.
... The development of simple field tests to evaluate an athlete's physical capacities (i.e. force, velocity, power generated at the centre of mass by their entire neuromuscular system) (Jaric, 2015;Samozino, Morin, Hintzy, & Belli, 2008;Samozino, Rabita, & Dorel, 2016) have identified mechanical determinants of human performance during functional motor tasks, such as jumping or running sprint (Morin & Samozino, 2016;Rabita, Dorel, & Slawinski, 2015). By applying this approach on skating sprint performance, our research group demonstrated that forward skating velocity follows a mono-exponential velocity-time function that allows practitioners to infer force input to skating velocity (Perez, Guilhem, & Brocherie, 2019). ...
... The aim of this study was therefore to investigate the correlations between elite female ice hockey players' mechanical capacities determined in offand on-ice conditions. We hypothesised that (i) a higher P max and a lower D RF during forward skating sprint would enhance performance as observed in running sprint (Rabita et al., 2015;Samozino et al., 2016) and (ii) the magnitude of correlations for the mechanical variables would be task-dependenti.e. stronger relationships between running and skating sprint tasks than between jumping and skating sprint tasksmainly due to similar accelerative phases and horizontal contribution to performance. ...
... All biomechanical variables (i.e. F 0 , V 0 , P max , RF, D RF and S FV ) were modelled from the centre of mass of the player using the method proposed by Samozino et al. (2016). The V htime curve has been shown to systematically follows a mono-exponential function: ...
Article
This study aimed to investigate the correlations between players’ mechanical capacities determined during off- and on-ice tests. Whole body force-velocity relationships were assessed in elite female ice hockey players (n = 17) during jumping [squat jump (SJ) height], running (5 m and 30 m) and skating (5 m and 40 m) sprint tasks. Mechanical capacities estimates include relative maximal theoretical force (F0rel), velocity (V0), power (Pmaxrel), slope of the linear relationship between force relative to body mass and velocity (SFVrel), maximal horizontal component of the ground reaction force to the corresponding resultant force (RFmax) and minimal rate of decrease of this ratio (DRF). On-ice mechanical capacities (F0rel, Pmaxrel, RFmax and DRF) largely-to-very largely correlated with 40-m skating split time (r ranging from 0.82 for DRF to -0.91 for Pmaxrel; p<0.001). Performance variables (SJ height, 30-m running and 40-m forward skating split time) and Pmaxrel demonstrated the largest associations between jumping, running and skating tasks (r ranging from -0.81 for 30-m sprint running time to 0.92 for SJ height; p<0.001). Small (V0, SFVrel, DRF and force-velocity deficit) to very large (Pmaxrel) correlations (r ranging from 0.58 to 0.72; p<0.05) were obtained between mechanical variables inferred from off- and on-ice force-velocity tests. The capacity to generate high amounts of horizontal power and effective horizontal force during the first steps on the ice is paramount for forward skating sprint performance. Mechanical capacities determined during forward skating sprint could be considered in ice hockey testing to identify fitness and/or technique training requirements.
... This reinforces the suggestion that acceleration is a key parameter to maximize performance in such races. Coaches commonly state that the speed over and between barriers is the most important factor to determine an athlete's outcome when considering the hurdling race as an adapted sprint as many coaches (1,6,26), so "fast sprinting allows for fast hurdling" (23). ...
... Athletes thus have to develop the ability to accelerate their body mass forward during a sprint, which is related to the ability to produce and apply a high amount of impulse onto the ground (21). A simple method for measuring force, velocity, and power during sprint acceleration has recently been proposed, highlighting that the mechanical ability to generate force under a range of velocities can be measured and expressed in the force-velocity (F-V) relationship (23). ...
... The outcomes of the F-V profile-maximal theoretical force (F 0 ), maximal theoretical velocity (V 0 ), F-V slope, and maximal power (P max )-can be used to implement individualized training programs (18,22). The assessment of the F-V profile in sprinting makes it possible to determine the mechanical effectiveness in force application-that is, the percentage of the resultant force that is produced in the horizontal direction (23). The decrease in the ratio of the horizontal-to-resultant force (DRF) AU3 and the maximal ratio of horizontal-to-resultant force (RFpeak) are the 2 variables most commonly used to assess mechanical effectiveness, and they have been found to be correlated with sprint performance (15). ...
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Short hurdling races are sprint races in which athletes must also clear 10 hurdles. Assessing the force-velocity (F-V) profile in sprinting has been found useful for implementing individualized training programs and determining the mechanical effectiveness in force application. This study therefore compared the sprint mechanical F-V profile between flat and hurdle conditions to distinguish which mechanical capacity (i.e., maximum force [F0], maximum velocity [V0], or maximum power [Pmax]) is required to optimize performance in hurdling races. Twenty-two athletes (10 men and 12 women, aged: 22.4 6 3.6 years old) competing at the national and elite performance levels conducted 2 maximal sprints of 40min both flat and hurdle conditions. F0, V0, FVslope, Pmax, and decrease and maximal ratio of horizontal force (DRF and RFpeak, respectively) were assessed for each condition. A higher F0 (effect size [ES]51.69) and a lower V0 (ES52.08), DRF (ES5 3.15) and RFpeak (ES51.31) were found in the hurdle condition than in the flat condition. No significant differences were observed between conditions for Pmax (ES5 0.01). These results support the potential of using the F-V profile to monitor sprint mechanics to optimize specific and individualized sprint training programs for hurdlers and sprinters. Coaches of hurdlers should thus consider implementing in their training routines exercises that were found to be effective on the development of F0, such as heavy load resisted sprints.
... All data were collected using Stalker ATS system software (Model: Stalker ATS II Version 5.0.2.1, Applied Concepts, Dallas, TX, USA) supplied by the radar device manufacturer. The general mechanical ability to produce horizontal external force during sprint-running is portrayed by the linear forcevelocity (F-v) relationship (13,14). The mechanical capabilities of the lower limbs were characterised by the variables: theoretical maximum velocity (V0); theoretical maximum force (F0) and peak power production (Pmax) (15). ...
... The methods of obtaining these variables have been validated in previous research during maximal sprint-running. (13,16) A high level of reliability (coefficient of variation V0 1.11% Pmax 1.87%, F0 2.93%) for inter-individual comparisons was found for each variable during over the ground sprint-running. (13). ...
... (13,16) A high level of reliability (coefficient of variation V0 1.11% Pmax 1.87%, F0 2.93%) for inter-individual comparisons was found for each variable during over the ground sprint-running. (13). ...
Article
The aim of this study was to investigate the load effects of thigh attached wearable resistance (WR) on linear and angular kinematics and linear kinetics during sprint-running. Fourteen recreational active subjects performed a series of maximal sprints with and without WR of 1, 2, and 3% body mass (BM) in a randomised order. Sprints were performed on a non-motorised treadmill which collected velocity, and linear step kinematics and kinetics. Angular kinematics of the thigh were collected from an inertial measurement unit attached to the left thigh. Trivial decreases were found in peak velocity with all WR loads (-0.9 to -.2.4%, effect size [ES] 0.09-0.17, p > 0.05). The WR conditions resulted in significantly decreased average step frequency (-2.0% to -3.0%, ES 0.35-0.44, p < 0.05) with loads of ≥ 2% BM, whereas average step length was statistically unchanged (1.9-2.8%, ES 0.20-0.33). Average angular displacement was significantly decreased (-7.0% to -10.3%, ES 0.88-1.10, p 0.00-0.03) with loads of ≥ 2% BM. Average angular flexion velocity (-10.2%, ES 1.07, p 0.02) and extension velocity (-12.0%, ES 0.85, p 0.01) were significantly decreased with 3% BM. Trivial to small ES changes (p > 0.05) were found in the linear kinetic measures of interest. Thigh WR provides a sprint-specific rotational form of resistance resulting in greater changes to angular kinematics than linear properties of sprint-running. For practitioners who wish to target thigh angular kinematics and step frequency without decreasing step length, thigh WR of ≥ 2% BM offers a sprint-specific resistance training tool
... The mechanical properties of sprinting including maximal theoretical velocity (V0), force (F0) values, its corresponding maximal power output (Pmax), maximal ratio of force (RFmax) and rate of decrease in RF (DRF), were obtained using a validated method from speed-time data. 11,12 All data is presented as mean and standard deviation. To compare the differences in split times and mechanical properties, Cohen's d effect sizes with 95% compatibility intervals (CI) were used with the follow thresholds applied: 0.0-0.2, ...
... Our results also suggest that player's peak velocity was lower during the preseason period when compared to the in-season assessments, indicative of a reduction the horizontal force applied at higher speeds. 11 Such findings are likely due to impaired muscle activation, neural adjustments (e.g. neural drive), altered muscle contractility and a reduction in fast twitch fibre cross-sectional area that occur with detraining. ...
... Interestingly, the unclear change in DRF suggests the difference in mechanical effectiveness with increasing speed was similar between sessions. 11 For the first time, we report a large degree of variability in the change in F0 and V0, which might reflect differences in timecourses responses of the skeletal muscle to detraining (i.e. cross-sectional area, fibres type, loss of muscle mass) and muscle performance losses. ...
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Objective: To determine the change in mechanical properties of sprinting performance across an 8-week off-season period in professional rugby league players. Design: Repeated measures Methods: Twenty-six professional rugby league players from a single rugby league team competing in Super League completed two assessments of linear sprint performance during final week of the season and second week of preseason. Linear split times were used to model the horizontal force-velocity profile and determine theoretical maximal force (F0), velocity (V0) and power (Pmax). Results: Our result indicated moderate-to-large increases in split times at each distance across the off-season period (ES = 0.86 to 1.24; most likely), indicative of a reduced sprinting ability. Furthermore, small reductions in F0 (ES -0.34 to -0.57; likely to very likely) were observed, whilst the reduction in V0 (ES = -0.81; most likely) and Pmax (ES = -0.62 to -1.03; most likely) were considered moderate in magnitude. Conclusions: An 8-week off-season period elicited negative changes in linear sprint times and the horizontal force-velocity profile of professional rugby league players. Such findings might have implications for preseason training loads and therefore, the off-season period requires careful consideration by practitioners and clinicians with regards to content and monitoring.
... An indirect method to estimate horizontal ground force generation of an athlete during the maximal sprinting performance, suitable for field tests, was recently validated against direct laboratory measurements Samozino et al., 2016). This macroscopic inverse dynamic method takes advantage of the observation that an athlete's velocity as a function of time in maximal effort sprinting can be modelled accurately using an exponential function (Di Prampero et al., 2005). ...
... Until recently, it was not known if horizontal velocity in maximal ice hockey skating can be modelled with the exponential model previously used for running Samozino et al., 2016) but a recent study by Perez et al. (2019) showed that the model could also be applied to skating. They also showed that acceptable inter-trial and test-retest reliability could be obtained for F-v profiling in ice hockey players when using a radar to measure skating velocity. ...
... The necessity to use costly devices (radar or laser) hinders the widespread use of the method by coaches. A low-cost solution is to use split times measured using a high-speed video camera capturing the movement in sagittal plane perspective and to fit an exponential model to the split time data to estimate the position of the athlete as a function of time and, subsequently, the F-v profile (Romero-Franco et al., 2017;Samozino et al., 2016). The method relies on accurate detection of the beginning of the sprint and misidentification of the correct time instant may lead to large errors in the results (Haugen et al., 2018). ...
Article
In recent years, a simple method for force–velocity (F-v) profiling, based on split times, has emerged as a potential tool to examine mechanical variables underlying running sprint performance in field conditions. In this study, the reliability and concurrent validity of F-v profiling based on split times were examined when used for ice hockey skating. It was also tested how a modification of the method, in which the start instant of the sprint is estimated based on optimisation (time shift method), affects the reliability and validity of the method. Both intra- and inter-rater reliability were markedly improved when using the time shift method (approximately 50% decrease in the standard error of measurement). Moreover, the results calculated using the time shift method highly correlated (r > 0.83 for all variables) with the results calculated from a continuously tracked movement of the athlete, which was considered here as the reference method. This study shows that a modification to the previously published simple method for F-v profiling improves intra- and inter-rater reliability of the method in ice hockey skating. The time shift method tested here can be used as a reliable tool to test a player’s physical performance characteristic underlying sprint performance in ice hockey skating.
... After block clearance, achieving and maintaining the maximal horizontal velocity are both related to the sprinter's capability to apply high amounts of power output, which depends on the capacity to produce high external forces at different running velocities [15,16]. The mutual dependency among force, velocity, and power producing capacities of leg muscles could be well described using the force-velocity (F-v) and power-velocity (P-v) relationships [15][16][17][18][19][20]. ...
... After block clearance, achieving and maintaining the maximal horizontal velocity are both related to the sprinter's capability to apply high amounts of power output, which depends on the capacity to produce high external forces at different running velocities [15,16]. The mutual dependency among force, velocity, and power producing capacities of leg muscles could be well described using the force-velocity (F-v) and power-velocity (P-v) relationships [15][16][17][18][19][20]. However, until recently, the kinetics analysis of the sprint acceleration phase was limited to specialized treadmill ergometers [21] or systems of force plates mounted along the sprint track [22]. ...
... However, until recently, the kinetics analysis of the sprint acceleration phase was limited to specialized treadmill ergometers [21] or systems of force plates mounted along the sprint track [22]. Recently, Samozino et al. [16] have proposed a simple and practical method to determine the F-v relationship in running considering only anthropometric and running split-time or velocity-time data. Samozino's method allows to obtain the sprinter's maximal power output (P max ), maximal horizontal force (F 0 ), maximal velocity (v 0 ), as well as the mechanical effectiveness of the force application onto the ground [15,16,23]. ...
Article
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1) Background: Within the current study we aimed at exploring gender-related differences and the relationship between sprint start block kinematics and kinetics and sprint acceleration force-velocity (F-v) relationship parameters (maximal force [F0], maximal velocity [v0], maximal power [Pmax] and slope) in top national-level sprinters. (2) Methods: Twenty-eight sprinters (6 females) performed 10 maximal 30-m sprints. Start block and acceleration kinematics and kinetics were collected with an instrumented sprint start block and a laser distance sensor (KiSprint system). Displacement-time data were used to determine the F-v relationship through Samozino's method. (3) Results: Start block rear foot maximal force (effect size [ES] = 1.08), rate of force development (ES = 0.90-1.33), F 0 (ES = 1.38), v 0 (ES = 1.83) and P max (ES = 1.95) were higher in males than in females (p ≤ 0.05). There were no differences in the slope, and ratio of horizontal-to-resultant force. F 0 , v 0 , and P max generally presented higher correlations with the start block kinetics (median r [range] = 0.49 [0.28, 0.78]) than with the kinematics (median r [range] = −0.27 [−0.52, 0.28]). (4) Conclusions: We confirmed that sprint block phase and sprint acceleration mechanics should be mutually assessed when analyzing sprinting performance. KiSprint system could provide more accurate information regarding mechanical pattern and technique during sprint initiation and acceleration, and potentially help create a more personalized and effective training program.
... Gold standard methods for ground reaction force measurement during sprint acceleration require instrumented treadmills or track-embedded multiple force plate systems, which is inaccessible to most athletes. For this reason, a simple field method based on position-time data and Newtonian laws of motion applied to the athlete's center of mass has been recently presented (Morin et al., 2019;Samozino et al., 2016). Due to a good ratio between overall validity and the overall reliability and simplicity of the model inputs (i.e. ...
... In other words, the AS profile represents the maximal forward acceleration capability of a player (resulting from propulsive force in the direction of running, according to Newtonian laws of motion) over the range of their running velocity spectrum. Conceptually, the information provided by the in-situ AS profile is close to the sprint forcevelocity profile explored during specific testing (linear sprint acceleration from zero to maximal running speed) (Morin et al., 2019;Samozino et al., 2016). The aim of this proof-of-concept study is to present a simple method to derive team sport players individual acceleration-speed profile from global positioning system (GPS) data collected over several training sessions. ...
... Then, after fitting, the residuals were analyzed and outlier points were removed, in order to improve the linear regression fitting and the overall accuracy of the model variables. For each individual and phase tested, this procedure eventually provided ~50 data points (52±5, range 43-63) from which the AS profile was derived using the updated linear regression model (for description of the linear modeling of sprint force-velocity profile, see (Morin et al., 2019;Rabita et al., 2015;Samozino et al., 2016)). Finally, three main variables were derived to characterize the players AS profile and potentially be the variables of interest for further studies: A 0 is the theoretical maximal acceleration (y-intercept of the AS linear relationship); S 0 is the theoretical maximal running speed (x-intercept of the AS relationship); AS slope is the slope, i.e. overall orientation of the AS profile (computed as AS slope = -A 0 / S 0 ). ...
Preprint
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Assessing football players' sprint mechanical outputs is key to the performance management process (e.g. talent identification, training, monitoring, return-to-sport). This is possible using linear sprint testing to derive force-velocity-power outputs (in laboratory or field settings), but (i) testing requires specific efforts and (ii) the movement assessed is not specific to the football playing tasks. This proof-of-concept short communication presents a method to derive the players' individual acceleration-speed (AS) profile in-situ, i.e. from global positioning system data collected over several football sessions (without running specific tests). Briefly, raw speed data collected in 16 professional male football players over several training sessions were plotted, and for each 0.2 m/s increment in speed from 3 m/s up to the individual top-speed reached, maximal acceleration output was retained to generate a linear AS profile. Results showed highly linear AS profiles for all players (all R 2 >0.984) which allowed to extrapolate the theoretical maximal speed and accelerations as the individual's sprint maximal capacities. Good reliability was observed between AS profiles determined 2 weeks apart for the players tested, and further research should focus on deepening our understanding of these methodological features. Despite the need for further explorations (e.g. comparison with conceptually close force-velocity assessments that require, isolated and not football-specific linear sprint tests), this in-situ approach is promising and allows direct assessment of team sport players within their specific acceleration-speed tasks. This opens several perspectives in the performance and injury prevention fields, in football and other team sports, and the possibility to "test players without testing them".
... The prominent model of estimating instantaneous sprint velocity (v mdl (t)) is based on the use of a Doppler radar to measure the maximum velocity in combination with the Eq. 1 (Furusawa et al., 1927;Samozino et al., 2016): ...
... For the v max , the limits of agreement (L.O.A.) for the Bland-Altman plot ranged from −1.20 to 0.89 m/s, this range being smaller than one (−1.25 to 1.64 m/s) presented in Gurchiek et al. (2018). L.O.A for the v 0 parameter varied from −1.01 to 0.67 m/s, which is similar in extent to one (−0.7 to 1.3 m/s) showed in Samozino et al. (2016). The f 0 and p max magnitudes were computed in terms of per unit mass and hence the L.O.A cannot be directly compared to the ones from . ...
Article
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Power-Force-Velocity profile obtained during a sprint test is crucial for designing personalized training and evaluating injury risks. Estimation of instantaneous velocity is requisite for developing these profiles and the predominant method for this estimation assumes it to have a first order exponential behavior. While this method remains appropriate for maximal sprints, the sprint velocity profile may not always show a first-order exponential behavior. Alternately, velocity profile has been estimated using inertial sensors, with a speed radar, or a smartphone application. Existing methods either relied on the exponential behavior or timing gates for drift removal, or estimated only the mean velocity. Thus, there is a need for a more flexible and appropriate approach, allowing for instantaneous velocity estimation during sprint tests. The proposed method aims to solve this problem using a sensor fusion approach, by combining the signals from wearable Global Navigation Satellite System (GNSS) and inertial measurement unit (IMU) sensors. We collected data from nine elite sprinters, equipped with a wearable GNSS-IMU sensor, who ran two trials each of 60 and 30/40 m sprints. We developed an algorithm using a gradient descent-based orientation filter, which simplified our model to a linear one-dimensional model, thus allowing us to use a simple Kalman filter (KF) for velocity estimation. We used two cascaded KFs, to segment the sprint data precisely, and to estimate the velocity and the sprint duration, respectively. We validated the estimated velocity and duration with speed radar and photocell data as reference. The median RMS error for the estimated velocity ranged from 6 to 8%, while that for the estimated sprint duration lied between 0.1 and −6.0%. The Bland–Altman plot showed close agreement between the estimated and the reference values of maximum velocity. Examination of fitting errors indicated a second order exponential behavior for the sprint velocity profile, unlike the first order behavior previously suggested in literature. The proposed sensor-fusion algorithm is valid to compute an accurate velocity profile with respect to the radar; it can compensate for and improve upon the accuracy of the individual IMU and GNSS velocities. This method thus enables the use of wearable sensors in the analysis of sprint test.
... This will negate the need for the combination of sleds with photocells, laser guns or radars. The distance-time or velocity-time running data can in turn be used for computation of macroscopic mechanical outputs (10) that may form basis for individual training prescription (1,9,10). ...
... The same issue is present for calculation of sprint mechanical outputs based on distance-time or speedtime data. An essential point when using the simple method proposed by Samozino et al. (10) is that the time 0 must be very close to the first rise of the force production onto the ground. This is equivalent to a setup with starts from blocks and audio signal with reaction time subtracted from the total time (5). ...
Article
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An increasing number of sprint-related studies have employed robotic devices to provide resistance while sprinting. The aim of this study was to establish within-session reliability and criterion validity of sprint times obtained from a robotic resistance device. Seventeen elite female handball players (22.9 ± 3.0 y; 176.5 ± 6.5 cm; 72.7 ± 5.5 kg; training volume 9.3 ± 0.7 hrs per week) performed two 30-m sprints under three different resistance loading conditions (50, 80 and 110 N). Sprint times (t0-5m, t5-10m, t10-15m, t15-20m, t20-30m and t0-30m) were assessed simultaneously by a 1080 Sprint robotic resistance device and a post-processing timing system. The results showed that 1080 Sprint timing was equivalent to the post-processing timing system within the limits of precision (± 0.01 s). A systematic bias of ~ 0.34 ± 0.01 s was observed for t0-5m caused by different athlete location and velocity at triggering point between the systems. Coefficient of variation was ~ 2% for t0-5 and ~ 1% for the other time intervals, while standard error of measurement ranged from 0.01 to 0.05 s, depending on distance and phase of sprint. Intraclass correlation ranged from 0.86 to 0.95. In conclusion, the present study shows that the 1080 Sprint is valid and reliable for sprint performance monitoring purposes.
... Of apparent interest for both the basic research and routine clinical testing should be the evaluation of the mechanical capacities of leg muscles performing a maximum effort during walking and running. So far, only P has been assessed from the F and V outputs recorded from single trials of maximum running typically performed on non-motorized treadmills [18,19] or force plate data [20]. A similar treadmill allowed Jaskolska and co-workers [21] to obtain an approximately linear F-V relationship from multiple trials performed against different resistance F. However, most of the treadmills within the clinical and research settings are the motorized ones, while the tests conducted at a lower V could be more relevant for clinical studies than the previously evaluated running tests. ...
... Specifically, the motorized treadmills are typically available within clinical and athletic training facilities, while a reach set of information can be obtained from just 2 brief trials. Note that just one maximum sprinting trial performed either on a non-motorized treadmill [19] or on force plates [20] could also provide F-V relationship of leg muscles, although not as strong as that obtained by the regression methods applied in the present study. However, the treadmill sprinting could not only be a challenging task to perform even for young and healthy subjects, but also out of question for a number of clinical populations, as well as for elderly and frail individuals. ...
Article
Background: The impact that mechanical factors might have on gait reorganization was evaluated by the relationship between muscle mechanical capacity of isolated leg muscle groups and transition speed in previous studies. However, until now there are no studies that explored the relationship between muscle mechanical properties measured in cyclic multi-joint movements and gait transition speed. Research question: What is the nature of the relationship between gait transition speed and muscle mechanical capacities measured in cyclic multi-joint movements? Methods: The sample included 18 physically active male adults, stratified by anthropometric dimensions. Individual walk-to-run (WRT) and run-to-walk transition speed (RWT) were determined using the standard incremental protocol. Mechanical capacities of leg muscles were assessed by linear force-velocity models obtained during treadmill locomotion and on bicycle-ergometer. Results: The results revealed inverse correlation between WRT and RWT and maximal force assessed on treadmill (F0; r = -0.57 and r = -0.54, respectively), as well with F0 (r = -0.65 and r = -0.58, respectively) and maximal power (Pmax; -0.66 and -0.65, respectively) collected on bicycle-ergometer. Significance: This study confirmed that mechanical muscle capacities are important physical limitation factors of transition speed, explaining over 36 % of the variance. The findings showed that a novel approach, with high biomechanical similarities with natural locomotion, revealed different results (negative correlations) in comparison to previous studies.
... Then mechanical outputs were computed using a recently established valid and reliable inverse dynamic field method based on spatiotemporal data. 22 Specifically, raw velocity-time data obtained from the radar device were fitted by an exponential function and derived to compute the net horizontal GRF. Individual linear force-velocity relationships were then extrapolated to calculate theoretical maximal force (F 0 ; CV = 1.7%), velocity (V 0 ; CV = 1.2%), 22 and the associated maximal power (P max ; Equation 1; CV = 2.6%). ...
... 22 Specifically, raw velocity-time data obtained from the radar device were fitted by an exponential function and derived to compute the net horizontal GRF. Individual linear force-velocity relationships were then extrapolated to calculate theoretical maximal force (F 0 ; CV = 1.7%), velocity (V 0 ; CV = 1.2%), 22 and the associated maximal power (P max ; Equation 1; CV = 2.6%). The mechanical effectiveness of force application was computed as the maximum ratio of force (RF max ; Equation 2) from horizontal (F H ) and vertical (F V ) GRFs, and the decrease in ratio of force (D RF ; CV = 1.6%) 23 as velocity increases. ...
Purpose: To analyze and compare the effects of 4 different resisted sprint training (RST) modalities on youth soccer players' performance after 8 weeks of training. Methods: Forty-eight youth soccer players were first randomly assigned to 4 groups and only then completed 8 weeks of RST: horizontal resisted sprint, vertical resisted sprint (VRS), combined resisted sprint, and unresisted sprint. Performance in horizontal and vertical jumps, sprint, and change of direction (COD) ability were assessed 1 week before and after the training intervention. Magnitude-based inference analysis was performed for calculating within-group pre-post differences. In addition, an analysis of covariance test was performed for between-group comparison, using the pretest values as covariates. After that, the analysis of covariance P values and the effect statistic were transformed to magnitude-based inference. Results: Within-group outcomes showed that all resisted training modalities experienced improvements in sprint (small to moderate) and COD (small to large) performance. Moreover, all groups, except unresisted sprint, enhanced the horizontal jump performance. However, only VRS improved on vertical jump. Between-group comparison outcomes revealed that only VRS improved the sprint time compared with horizontal resisted sprint (moderate) and COD performance compared with all groups (moderate to large). In addition, VRS enhanced the countermovement jump performance (small to large) compared with the other groups. Conclusions: Independent of the orientation of the resistance applied, RST is an effective training method for improving sprinting and COD performance. Nevertheless, VRS may promote greater improvements on sprint and COD ability and have a positive additional effect on countermovement jump performance and the reduction of COD deficit.
... Individual force-velocity relationships in sprinting were assessed with MySprint app [26]. This app uses the Samozino's method to determine the theoretical maximum values of force (F0), velocity (V0), and power (Pmax) in sprinting [27]. Samozino's method provides a simple method of obtaining the force-velocity relationship from the application of basic laws of motion using the running speed and the body mass of the athlete as main inputs [27]. ...
... This app uses the Samozino's method to determine the theoretical maximum values of force (F0), velocity (V0), and power (Pmax) in sprinting [27]. Samozino's method provides a simple method of obtaining the force-velocity relationship from the application of basic laws of motion using the running speed and the body mass of the athlete as main inputs [27]. From all the data obtained, the rate of force at 10 meters (RF-10M) and the split times of 5, 10, and 30 m of the best attempt were used for further analysis. ...
Article
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A study was made to initially evaluate whether the age category directly could influence anthropometric measurements, functional movement tests, linear sprint (30 m) and strength. Moreover, and as the main purpose, this study aimed to examine the relationship between the time execution and angles in different changes of direction (COD) test with the analyzed sport performance variables. A total sample of 23 basketball players (age: 17.5 ± 2.42 years; height: 184.6 ± 6.68 cm; body weight: 78.09 ± 11.9 kg). Between-groups' comparison explored the differences between basketball categories (Junior, n = 12; Senior, n = 11). The COD variables were divided by the time execution into low responders (LR) and high responders (HR) to establish comparisons between groups related to COD time execution. Pearson's correlation coefficient was used to establish correlations between different CODs and sport performance variables. The results showed a greater influence of age category upon COD performance, especially when the cutting angle was sharper (7.05% [Confidence limits (CL) 90%: 2.33; 11.99]; Quantitative chances (QC) 0/2/98), in which athletes need greater application of strength. Moreover, the sharper the angle or the larger the number of cuts made, the greater the relationship with the vertical force-velocity profile (-42.39 [CL 90%: -57.37; -22.16]; QC 100/0/0%). Thus, the usefulness of the f-v profile to implement training programs that optimize the f-v imbalance and the improvement of the COD performance in basketball players is suggested.
... Anthropometric measurements and CMJ results were collected on the morning of the study (Thursday). Body mass (BM) was measured using a Tanita Samozino's method 22,29 . ...
... Previous investigations have suggested that the initial levels of force may influence the magnitude of improvement in ballistic actions [11][12][13][14][15] ; however, these suggestions are only based on the vertical application of force. Therefore, this study may be considered novel, due to the use of vertical (CMJ) and horizontal application of force (P-F-V profile) tests 29 . Our investigation may be useful for amateur female rugby players and coaches who want to monitor changes in mechanical variables during sprinting performance to assess the effectiveness of their training. ...
Article
This study aimed to observe the effect of 8 weeks of resisted sled training (RST), with optimal loading for maximal power output production and initial levels of force, on the magnitude of improvement in sprint performance and individual sprint mechanical outputs in female amateur rugby union players. The study examined the horizontal Power-Force-Velocity profile (P-F-V profile), which provides a measure of the athlete’s individual balance between force and velocity capabilities (Sfv), theoretical maximum force (F0), theoretical maximum velocity (V0), maximum power (Pmax), the maximum ratio of force (Rfmax) and rate of decrease in ratio of force (Drf). Thirty-one participants (age=23.7 ± 3.3years, BM=69 ± 9Kg, height=167.5 ± 5.2 cm) were divided into a control group and two experimental groups; forwards (FG) and backs (BG). For 8 consecutive weeks (16 sessions), all groups performed the same training program: 2 sets of 5 × 30 m, but athletes assigned to FG and BG ran towing a resisted sled attached to their waists, with optimal loading for maximal power output production. Both FG and BG significantly improved (p≤0.05) in 5 m and 20 m sprint performance, and in the mechanical properties related to the horizontal P-F-V profile. The correlation between the initial level of horizontal strength and the magnitude of improvement in Pmax also suggests that higher levels of horizontal force may lead to greater adaptations in RST. The P-F-V profile is a useful field method for identifying the weakest mechanical variable in rugby players during sprinting and enabling the prescription of individualized training programs according to specific running performance.
... As with all methods of assessment each has its own limitations, including cost, complexity of set up, analysis and reliability. 91 , and that process has also been applied to sled pulling 49 . The advantage of this approach is that it allows determination of the load and velocity combination that optimizes power production. ...
... Each linear force-velocity relationship was then extrapolated to calculate theoretical maximum force (F0). This method has been shown to be a reliable field method to assess force-velocity profiles during over ground sprinting 91 Tables 5.1 and 5.2. respectively. ...
Thesis
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Speed is an important athletic quality and needs to be developed in young athletes, this may be best achieved using specific forms of sprint training. Resisted sled training is a sprint specific form of training widely used by coaches and practitioners. The two modes of resisted sled training that exist are sled pushing and pulling, with limited research available for pulling and little, if any, available for pushing in any population. The overarching question that guided this thesis was “what are the acute and chronic training responses to sled pushing and pulling in young athletes?” The aims of the thesis were to: review existing literature related to acute and chronic training responses to resisted sled pushing and pulling; examine the reliability, linearity, and utility of individual load-velocity profiles to prescribe training loads during sled pushing and pulling in young athletes; assess the effectiveness of unresisted and resisted sled pull and sled push training on short distance sprint performance across a wide array of individualised loads; and, provide practical programming guidelines on how to integrate resisted sled training into an athlete’s training. The main findings of this thesis were: 1) across existing literature little uniformity exists with regard to prescription of load for resisted sled training although heavier loads appeared to provide a stimulus for higher horizontal force application. Loads can be applied across different zones of training such as technical competency, speed-strength, power and strength-speed. 2) Sled pushing and pulling produce a highly linear relationship (r > 0.95) between load and velocity. The slope of the load-velocity relationship was found to be reliable (CV = 3.1%), with the loads that cause a decrement in velocity of 25, 50 and 75% also found to be reliable (CVs = <5%). However, there was large between-participant variation (95%CI) in the load that caused a given Vdec in both sled pushing and pulling. Loads of 14-21, 36-53, 71-107 and 107-160% body mass (%BM) caused a Vdec of 10, 25, 50 and 75% in sled pulling. Loads of 23-42, 45-85 and 69-131% body mass (%BM) caused a Vdec of 25, 50 and 75% in sled pushing. 3) Both forms of resisted sprint training demonstrated a clear trend for greater and more consistent improvements in sprinting force, power and performance over short distances when training with heavier sled loads (as compared to a lighter load or unresisted sprint training). Several practical applications may be offered from the findings. Due to the linearity and reliability of the load-velocity relationship, coaches are urged to prescribe individualised sled loads based on a target decrement in velocity rather than simply prescribing all athletes the same load as a set percentage of body mass. Both sled pushing and pulling were effective sprint specific modes of training to enhance overall sprint performance, with the latter found to be more sprint specific due to the use of the arms. Heavier loads during both forms of resisted sled training appeared to yield the greatest benefit to young athletes in short distance sprint performance, however a targeted approach to sled loading may influence different phases of the sprint.
... 15,[19][20][21][22] A series of loaded vertical jumps with the loads corresponding to 0%, 10%, 20%, 30%, 40%, 50%, and 70% of the participant's body weight provides the information related to theoretical maximal force (F 0 ), theoretical maximal velocity (V 0 ), slope of the F-V relationship (F-V slope ), and theoretical maximal power (P max ). [14][15][16]18,21,23,24 These variables determine the mechanical limitations of the neuromuscular system involved in jumping performance to produce force, velocity, and power. 17 The difference between actual and optimal F-V profile for each individual represents the magnitude and direction of the imbalance between force and velocity qualities (F-V IMB ), which makes possible the individual determination of F or V deficit. ...
... 32 My Jump 2 provided information regarding the magnitude and direction of the F-V imbalance for each dancer (F-V IMB ), theoretical maximal force (F 0 ), theoretical maximal velocity (V 0 ), and theoretical maximal power (P max ), according to Samozino's method. [14][15][16]23,24 All data are presented as mean and standard deviations with IBM SPSS Statistics software version 24 (IBM, Armonk, New York, USA). Differences between the three company ranks were assessed using Kruskall Wallis test (with Mann-Whitney post hoc test) and one way ANOVA (Tukey post hoc test) according to the normal distribution of each variable presented in Tables 1 and 2, with level of significance set at p ≤ 0.05. ...
Article
Jumping ability has been identified as one of the best predictors of dance performance. The latest findings in strength and conditioning research suggest that the relationship between force and velocity mechanical capabilities, known as the force-velocity profile, is a relevant parameter for the assessment of jumping ability. In addition, previous investigations have suggested the existence of an optimal force-velocity profile for each individual that maximizes jump performance. Given the abundance of ballistic actions in ballet (e.g., jumps and changes of direction), quantification of the mechanical variables of the force-velocity profile could be beneficial for dancers as a guide to specific training regimens that can result in improvement of either maximal force or velocity capabilities. The aim of this study was to compare the mechanical variables of the force-velocity profile during jumping in different company ranks of ballet dancers. Eighty-seven female professional ballet dancers (age: 18.94 ± 1.32 years; height: 164.41 ± 8.20 cm; weight: 56.3 ± 5.86 kg) showed high force deficits (> 40%) or low force deficits (10% to 40%) regardless of their company rank. Our results suggest that dance training mainly develops velocity capabilities, and due to the high number of dramatic elevations that dance performance requires, supplemental individualized force training may be beneficial for dancers. The individualization of training programs addressed to the direction of each individual's imbalance (high force or low force) could help dancers and their teachers to improve jump height and therefore dance performance.
... Skeletal muscle power is viewed as a functional measure of muscle performance and the peak power occurs at submaximal force production. 67 The analysis at single muscle fibres level is preferred because it bypasses the effects of fibre-type transformation at the whole muscle level. Various studies show that the contractile velocity of single muscle fibres is increased, at least in short-term, to compensate for the loss of force, and to maintain power at the cellular level. ...
Article
Prolonged unloading of skeletal muscle, a common outcome of events such as spaceflight, bed rest and hindlimb unloading can result in extensive metabolic, structural and functional changes in muscle fibers. With advancement in investigations of cellular and molecular mechanisms, understanding of disuse muscle atrophy has significantly increased. However, substantial gaps exist in our understanding of the processes dictating muscle plasticity during unloading, which prevent us from developing effective interventions to combat muscle loss. This review aims to update the status of knowledge and underlying mechanisms leading to cellular and molecular changes in skeletal muscle during unloading. We have also discussed advances in the understanding of contractile dysfunction during spaceflights and in ground‐based models of muscle unloading. Additionally, we have elaborated on potential therapeutic interventions that show promising results in boosting muscle mass and strength during mechanical unloading. Finally, we have identified key gaps in our knowledge as well as possible research direction for the future.
... This is true in general for the untrained individual. In the case of sprint-trained runners [52] or cyclists [53], there is a strong tendency towards the linear form, which in these cases reflects the predominance of fast fibres, as predicted by the model. The same signature is obtained if the pedalling is done with the arms [54]. ...
Experiment Findings
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Oxygen ventilation
... Studies focusing on different maximal ballistic multi-joint movements (e.g. bench press (Garcia-Ramos et al., 2016;Rahmani et al., 2018), squat jump Giroux et al., 2014), cycling (Granier et al., 2017) and sprinting (Samozino et al., 2016) have reported that subjects' F-v profile was always linear and remained reproducible within a session and throughout different sessions under a similar physical condition of subjects. Even for a wholebody and complex movement, such as the deadlift high pull (DHP), which consists in raising a barbell from the floor to the maximum height possible in a single movement, F-v relationship was still found to be linear and reliable (R² > 0.90, p < 0.005) (Lu et al., 2017). ...
Thesis
L'explosivité musculaire, associée à la notion de puissance (i.e., produit de la force et de la vitesse), représente la capacité à produire le plus de travail possible en un temps restreint. Au cours des mouvements pluri-articulaires tels que le squat, le développé-couché ou le pédalage, la relation entre la force et la vitesse est représentée par une relation linéaire négative. Cependant, au cours de mouvements plus complexes impliquant l’'ensemble de la chaîne segmentaire tels que le soulevé de terre haut , la linéarité de cette relation force-vitesse n’'a, à notre connaissance, jamais été étudiée. D plus, au cours de protocole de fatigue, la modification du profil force-vitesse des individus est également peu étudiée. Ce travail de thèse se propose d'explorer l’'impact de la fatigue sur la relation force-vitesse lors d’'un mouvement explosif impliquant le corps entier. Dans le cadre d'une série d’études expérimentales, nous avons d'abord fait une étude pour évaluer la reproductibilité de la performance et de la relation force-vitesse lors du mouvement de soulevé de terre haut. Ensuite, nous avons comparé la différence et la corrélation entre les deux méthodes couramment utilisées, la plateforme de force et l'accéléromètre. Enfin, nous avons analysé l'impact de la fatigue sur la performance réalisée lors du mouvement de soulevé de terre haut et la relation force-vitesse.
... Each linear force-velocity relationship was then extrapolated to calculate theoretical maximum force (F 0 ). This method has been shown to be a reliable field method to assess force-velocity profiles during over ground sprinting (31). Sprint force-velocity profiles were then constructed using custom-made LabVIEW software. ...
Article
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Cahill, MJ, Oliver, JL, Cronin, JB, Clark, K, Cross, MR, Lloyd, RS, and Lee, JE. Influence of resisted sled-pull training on the sprint force-velocity profile of male high-school athletes. J Strength Cond Res XX(X): 000-000, 2020-Although resisted sled towing is a commonly used method of sprint-specific training, little uniformity exists around training guidelines for practitioners. The aim of this study was to assess the effectiveness of unresisted and resisted sled-pull training across multiple loads. Fifty-three male high-school athletes were assigned to an unresisted (n 5 12) or 1 of 3 resisted groups: light (n 5 15), moderate (n 5 14), and heavy (n 5 12) corresponding to loads of 44 6 4 %BM, 89 6 8 %BM, and 133 6 12 %BM that caused a 25, 50, and 75% velocity decrement in maximum sprint speed, respectively. All subjects performed 2 sled-pull training sessions twice weekly for 8 weeks. Split times of 5, 10, and 20 m improved across all resisted groups (d 5 0.40-1.04, p , 0.01) but did not improve with unresisted sprinting. However, the magnitude of the gains increased most within the heavy group, with the greatest improvement observed over the first 10 m (d $ 1.04). Changes in preintervention to postintervention force-velocity profiles were specific to the loading prescribed during training. Specifically, F 0 increased most in moderate to heavy groups (d 5 1.08-1.19); Vmax significantly decreased in the heavy group but increased in the unresisted group (d 5 012-0.44); whereas, Pmax increased across all resisted groups (d 5 0.39-1.03). The results of this study suggest that the greatest gains in short distance sprint performance, especially initial acceleration, are achieved using much heavier sled loads than previously studied in young athletes.
... It should be noted that the data from the method used by Cross et al. (2015) is easily collected with the use of a radar gun, and can be analysed easily in Microsoft Excel using the equations provided by Samozino et al. (2016), therefore both timing gates or the radar method could be used to assess sprint performance, although they are not interchangeable regarding split times. ...
Thesis
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The aims of the thesis were to 1) investigate the anthropometric and physical characteristics of youth academy rugby union players by age category (under 16, 18 and 21), and position (forwards and backs), and 2) to use statistical analysis methods (i.e., covariate adjustment, allometric scaling and reliability statistics) to enhance the analysis and interpretation of physical characteristic data. One-hundred and eighty-four academy rugby union players participated across 6 studies, and were assessed for anthropometric (body mass, height and sum of 8 skinfolds (∑8SF), and physical (dynamic and isometric strength, countermovement jump height and peak power, linear sprint (time, momentum, velocity, and velocity) and high-intensity running (Yo-Yo Intermittent Recovery Test Level 1 (Yo-YoIRTL1), and 30-15 Intermittent Fitness Test (30-15IFT)) characteristics. Studies 1, 2 and 3 demonstrated most physical characteristics, except sprint velocity and high-intensity running, were greater in older age categories. Physical characteristics differed by playing position with forwards greater for body mass, height, ∑8SF, countermovement jump peak power, absolute dynamic strength, absolute isometric mid-thigh pull peak force and sprint momentum; and backs greater for high-intensity running, sprint velocity and acceleration, countermovement jump height and relative strength. In study 4, covariate adjustment for body mass or height did not explain differences in most physical characteristics between-age categories. However, for 30-15IFT performance, adjustment for body mass resulted in clear differences between-age categories, suggesting body mass limits increases in 30-15IFT performance. In study 5, allometric scaling resulted in reduced but unclear differences in countermovement jump height and peak power, and isometric mid-thigh pull peak and net force; allometric scaling reduced the differences in 10 m velocity and 30-15IFT, whilst differences for Vmax remained the same between forwards and backs in the U18 age category. This II suggesting that body mass may explain some of differences between positions, but requires greater sample size to report clear findings. In study 6, linear sprint assessment was reliable (Coefficient of variation < 5%) for 10, 20, 30 and 40 m, with poor utility at detecting small improvements in performance. Despite this, using reliability statistics, 16 youth rugby union players were monitored individually across a season. Findings demonstrated improved individual performances in sprint times at 10, 20 and 40 m, which differed to the reported group-mean changes in performance. This highlights the importance of monitoring changes in performance on the individual level alongside group mean analysis. Practitioners working in youth rugby union should understand the anthropometric and physical characteristics that are greater with age,(e.g., body size, strength, power), and those that remain stable (e.g., speed and high-intensity running), whilst also acknowledging the complex interactions between anthropometric and physical characteristics. Body mass and height interact with physical characteristics, but cannot explain the differences between-age categories and positions. The use of reliability statistics to monitor changes in individual physical characteristics is recommended in practice and research.
... High-resolution force plates (sample rates typically ≥1000 Hz) allow the determination of instantaneous mechanical power as the product of instantaneous force and velocity, the latter obtained by mathematical integration of the mass-normalized net force (i.e., acceleration) signal. While force plates capable of measuring in either one or three dimensions now represent the gold standard for determining mechanical power in movements, such as jumping [29], hopping [32], and sprinting [33,34], other technologies have emerged as well. For example, portable position transducers and accelerometers capable of estimating power from acceleration and mass are becoming common for training and field-testing purposes [35,36]. ...
Article
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Regularly assessing anaerobic power is important for athletes from sports with an explosive strength component. Understanding the differences and overlap between different assessment methods might help coaches or smaller-scale testing facilities maximize financial and temporal resources. Therefore, this study investigated the degree to which cycling sprint and vertical jump tests are interchangeable for determining peak mechanical leg power output in strength-trained athletes. Professional skiers (n = 19) performed unloaded squat jumps (SJ) and other jump forms on a force plate and a six-second cycling sprint (6sCS) test on an ergometer on six occasions over two years. Along with cross-sectional correlations between cycling and jumping power, correlations between longitudinal percent changes and agreement between magnitude-based inferences about individual changes were assessed. Among the tested jump forms, SJ reflected 6sCS best. However, despite extremely large cross-sectional correlation coefficients (0.92) between 6sCS and SJ, and moderate (Pearson’s r = 0.32 for 6sCS with SJ over one-year time spans) to large (r = 0.68 over shorter time spans) correlation coefficients on percent changes, magnitude-based inferences agreed in only around 50% of cases. Thus, for making qualitative assessments about the development of anaerobic power over time in athletes, cycling sprint and squat jump tests are not interchangeable. Rather, we recommend employing the test form that best reflects athletes’ strength and conditioning training.
... Bridging the gap between research and practical use of power in running would bring the stunning potential of such parameter to light. The insights provided here into the validity and reliability of the different commercially available wearable sensors for spatiotemporal parameters show the emerging potential of such devices for running PW measurement given their narrow association considering theoretical approaches previously proposed [6][7][8][9]. ...
Article
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Mechanical power may act as a key indicator for physiological and mechanical changes during running. In this scoping review, we examine the current evidences about the use of power output (PW) during endurance running and the different commercially available wearable sensors to assess PW. The Boolean phrases endurance OR submaximal NOT sprint AND running OR runner AND power OR power meter, were searched in PubMed, MEDLINE, and SCOPUS. Nineteen studies were finally selected for analysis. The current evidence about critical power and both power-time and power-duration relationships in running allow to provide coaches and practitioners a new promising setting for PW quantification with the use of wearable sensors. Some studies have assessed the validity and reliability of different available wearables for both kinematics parameters and PW when running but running power meters need further research before a definitive conclusion regarding its validity and reliability.
... Force-velocity (Fv) profiling is a simple and novel approach to assess force and velocity production capabilities of athletes during ballistic tasks, such as jumping and sprinting [16,17]. It has been postulated that there is an optimal Fv profile that can be precisely determined and represents the balance between force and velocity [18]. ...
Article
This study aimed to analyze the differences in force-velocity profile and sprint, strength and jump performance according to playing position, and to examine the relationships between these fitness parameters within specific rugby playing positions. Fifty-one male rugby players (27 backs, 24 forwards) were assessed in their force-velocity profile, vertical jumps, 5 and 30 m sprint, and strength in Squat and Bench Press exercises. For a deeper understanding of positional differences, forwards were divided into front row and back five, and backs were split into outside and inside backs. Forwards showed higher body mass and height, greater sprint momentum and higher absolute strength than backs, whereas backs were faster in 5 and 30 m sprints. No significant differences were observed between outside and inside backs for any of the variables analyzed. Front row forwards were significantly heavier than back five, whereas the latter showed higher jump and sprint performance and greater maximum power values than front row. No significant differences were observed between any positions for force-velocity imbalance. No correlations were found between force-velocity imbalance and any physical performance variable regardless of playing position. Maximum power (r = 0.434 to 0.855; p < 0.05) and relative strength (r = 0.404 to 0.772; p < 0.05) were the variables that most correlate with jump and sprint performance in forwards and backs. In conclusion, clear differences exist between backs and forwards in strength and sprint performance. Although no differences were observed between specific backs positions, in contrast to the specific forwards positions that showed clear differences in all the physical performance variables. High levels of relative strength and power may be relevant in order to attain high sprinting and jumping performance.
... This equation was then integrated to calculate the distance-time curve [102]: = . ∆ −1 ...
Thesis
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The success of many team sports and track and field athletes can be in part linked with their sprint performance. Therefore, improving sprint performance has been the foci of researchers and practitioners alike. The most commonly used tools that deliver sprint-specific training stimuli are resisted towing devices (RST) (e.g. sleds). RST provides a predominantly concentric (CON) horizontal overload to the musculo-skeletal system, especially in the acceleration phase of the sprint. Perhaps an eccentric (ECC) horizontal overload may be beneficial given the benefits of ECC training; such as, injury prevention and rehabilitation, shift towards faster muscle phenotypes, hypertrophy, strength and power improvements. This resulted in the overarching research question, “Can a novel horizontal ECC towing device improve sprint performance?”. The aim of this thesis was to develop a device that would provide a horizontal ECC stimulus, evaluate the biomechanics of the device and test its effects on sprint performance. A review of existing ECC training devices found limited devices overload in the horizontal plane and none eccentrically overload the musculo-skeletal system in a sprint-specific gait. Therefore, a movement termed horizontal ECC towing (HET) was developed which involves an athlete in a sprint stance trying to move forwards but is being pulled backwards. A device termed the HET device was then developed to automate this movement. The device was powered by a 10 kW electric motor that can tow athletes at velocities up to 3.58 m/s and can tolerate forces up to 2.8 kN. Two familiarisation sessions were found to achieve movement consistency during HET. Biomechanics analysis was conducted to further understand the movement which would help inform training programme development for coaches. Since HET is a novel movement, no research existed. Thus, ECC towing was compared to its opposite, the CON towing direction (CTD). Statistical Parametric Mapping (SPM) analysis of ground reaction force (GRF) profiles found that the two directions were significantly different (p<0.05) and were applying different movement strategies to produce force. This suggested that different lower limb joints were likely responsible for CON and ECC force production. Vertical and horizontal GRFs were lower in the ECC direction (p<0.05), which may be limited by the coefficient of friction and indicated that isokinetic horizontal towing does not follow the contractile-force-velocity relationship. Power and work analysis of the lower limb joints showed that the ankle and hip joints are absorbing energy and likely dissipating it in the ECC towing direction (ETD). ETD has greater ankle and hip joint power absorption and much smaller power production. A four-week intervention of ECC and CON towing in elite female field hockey players (n=10) resulted in no improvements in split times. There is still an opportunity for practitioners and researchers to apply a unique ECC stimulus to their athletes. The intervention study had its limitations as it was based out of the lab in a practical setting. However, no tool provides a similar overload as the HET device. We recommend to those that are interested in overloading the power absorption phase of the ankle and hip joints should incorporate HET. Further research with the HET device involving a larger cohort of athletes could provide more conclusive evidence on the effects on sprint performance.
... Sprint performance (split times 0-5, 0-10, 0-20 and 0-30 m), maximal velocity and sprint mechanical output (ie, maximal theoretical horizontal force (F0)) are computed using a validated field method measured with a radar device (Stalker ATS Pro II, Applied Concepts, TX, USA) as reported previously. [37][38][39] Briefly, this computation method for F0 is based on a macroscopic inverse dynamic's analysis of the centre-of-mass motion. Raw velocity-time data wereare fitted by an exponential function. ...
Article
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Introduction Hamstring muscle injuries (HMI) continue to plague professional football. Several scientific publications have encouraged a multifactorial approach; however, no multifactorial HMI risk reduction studies have been conducted in professional football. Furthermore, individualisation of HMI management programmes has only been researched in a rehabilitation setting. Therefore, this study aims to determine if a specific multifactorial and individualised programme can reduce HMI occurrence in professional football. Methods and analysis We conducted a prospective cohort study over two seasons within the Finnish Premier League and compare the amount of HMI sustained during a control season to an intervention season. Injury data and sport exposure were collected during the two seasons (2019–2020), and a multifactorial and individualised HMI risk reduction programme was be implemented during intervention season (2020). After a hamstring screening protocol is completed, individual training was be defined for each player within several categories: lumbo-pelvic control, range of motion, posterior chain strength, sprint mechanical output and an additional non-individualised ‘training for all players’ category. Screening and respective updates to training programmes were conducted three times during the season. The outcome was to compare whether there was a significant effect of the intervention on the HMI occurrence using Cox regression analysis. Ethics and dissemination Approval for the injury and sport exposure data collection was obtained by the Saint-Etienne University Hospital Ethics Committee (request number: IORG0007394; record number IRBN322016/CHUSTE). Approval for the intervention season was obtained from the Central Finland healthcare District (request and record number: U6/2019).
... From this, the mechanical capabilities of the lower limbs were further characterised by the variables: theoretical maximal velocity (V 0 ); theoretical maximal horizontal force (F 0 ), peak power (P max ), maximal ratio of force (RF max ), and index of force application (D RF ) (Rabita et al., 2015). These mechanical profiling variables, along with sprint split times (5, 10, 20 and 30 m), maximal velocity of the measured sprint (V max ) and slope of the F-v profile (S FV ), were calculated consistent with the method previously validated (Morin, Samozino, Murata, Cross, & Nagahara, 2019;Samozino et al., 2016) with a custom-made MATLAB script (MATLAB R2019b, The Math-Works, Inc., Natick, Massachusetts, USA). The calculated data from the three trials were averaged. ...
Article
This study determined the effects of a six-week lower-limb wearable resistance training (WRT) intervention on sprint running time, velocity, and horizontal force-velocity mechanical variables. Twenty-two collegiate/semi-professional rugby athletes completed pre- and post-intervention testing of three maximal effort 30 m sprints. A radar device was used to measure sprint running velocity from which horizontal force-velocity mechanical profiling variables were calculated. All athletes completed two dedicated sprint training sessions a week for six-weeks during pre-season. The intervention (wearable resistance, WR) group completed the sessions with 1% body mass load attached to the left and right shanks (i.e. 0.50% body mass load on each limb), whilst the control group completed the same sessions unloaded. For the control group, all variables were found to detrain significantly (p ≤ 0.05) over the training period with large detraining effects (ES > 0.80) for theoretical maximal horizontal force, slope of the force-velocity profile, maximal ratio of force, index of force application, 5 m and 10 m times. For the WR group, there were no significant changes to any recorded variables (all p > 0.05) and all effects of training were trivial or small (ES < 0.50). After adjustment for baseline differences, significant between group differences were found for all variables (large effects, ES > 0.80) except theoretical maximal velocity, 30 m time, and maximal velocity. The addition of light wearable resistance to sprint training during a six-week pre-season block enables the maintenance of sprint performance and mechanical output qualities that otherwise would detrain due to inadequate training frequencies.
... New technologies have been employed to investigate more complex sprint variables beyond time to cover set distances. In recent literature, tools such as instrumented treadmills, optical measurement systems, video analysis, horizontal linear position transducers, and laser/radar guns have been utilized (Debaere, Jonkers, & Delecluse, 2013;Morin & Sève, 2011;Romero-Franco et al., 2017;Samozino et al., 2016;Townsend et al., 2017). All of these technologies have their advantages and disadvantages, but few provide the flexibility for use in the field and are not constrained by a set distance. ...
Thesis
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Athlete monitoring provides valuable insight into the balance of an athlete’s stress and adaptation from training. Many methods exist to quantify athletes’ allostatic state, with a physical performance measure a primary link to sport performance. However, little research has focused on a critical aspect of field sport performance, sprinting. Therefore, the purpose of this thesis was to investigate the utility of sprint monitoring using in-depth kinematic analysis. Training load was measured daily, as the product of session duration and rating of perceived exertion, in 32 adolescent female soccer players, comprising a U-15 and U-18 team. Measures of 7-day and 28-day cumulative training loads and 7-day to 28-day exponentially weighted moving average (EWMA) and rolling average (RA) acute to chronic workload ratios (ACWR) were calculated. Players performed a countermovement jump (CMJ) on a contact mat and a 30 m sprint bi-weekly, and completed a daily wellness questionnaire to assess training load response over 14 weeks. From the 30 m sprint, 10 and 30 m times were measured using timing gates, and maximal acceleration, maximal velocity, and time to maximal velocity were measured using a radar gun. Linear mixed models were used to assess the influence of training load on CMJ, 30 m sprint performance variables, and athlete wellness. Cumulative training load over 7 days had a likely small positive effect on 30 m sprint time (d = 0.14; 90% CL: −0.01 to 0.28), while 28-day cumulative training load had a likely small positive effect on 30 m sprint time (d = 0.14; 0.00 to 0.28), a very likely small negative effect on maximal sprint velocity (d = −0.19; −0.03 to −0.35), and a likely moderate negative effect on athlete wellness (d = −0.35; −0.02 to −0.68). EWMA and RA ACWRs had possibly small (d = 0.18; −0.14 to 0.49) and likely moderate (d = 0.33; 0.00 to 0.66) positive effects on wellness. All other relationships were unclear. Monitoring sprint performance should be considered to evaluate response to training loads, with sprint time indicative of acute and chronic loads, while maximal sprint velocity and athlete wellness were more suggestive of chronic loads.
... The subjects performed six maximum intensity 40-meter sprints at minute 1, 25, 45, 46, 70 and 90 of the CST. The athletes were captured by a laser distance measurement system (LDM 301, Jenoptik, Jena, Germany; sampling rate, 100Hz) to compute V0, F0rel, Pmaxrel ("rel" refers to normalised to body mass) and 20-metre sprint time in accordance with Samozino et al. (2016). For V0, F0rel, Pmaxrel and 20-m sprint time paired sample t-Tests were used to detect differences from the start to the end of the game (1' to 90') as well as differences before and after half-time break (45 ' to 46 ' ). ...
Conference Paper
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The purpose of this study was to identify soccer-specific changes of mechanical properties in sprinting during a simulated soccer match. Professional soccer players (n=15) completed six sprint measurements before, during and after a simulated soccer game (i.e. Copenhagen Soccer Test). Mechanical properties (theoretical maximal sprinting velocity (V0), theoretical maximal horizontal force (F0), maximal horizontal sprinting power (Pmax) and the 20-metre sprint time were computed from continuous velocity data captured from a laser device. The results suggest that soccer-specific fatigue affects V0 more than F0. Furthermore, there is an inactivity-induced sprint performance loss because of the half-time break. However, at the end of the game, professional players can achieve similar sprint times as in the first half. These results could be useful for effective training planning and optimizing sprint performance during a match.
Thesis
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Swimming performance requires a whole body coordinated movement to elicit high propulsive forces with the majority of forces produced from the upper body musculature. The current academic literature highlights a range of dry-land resistance exercises that show moderate to strong correlations to swimming performance; however, association does not imply causation. Specificity states that adaptations are specific to the nature of the training stress applied and therefore it is important to highlight the dry-land resistance exercises improving swimming performance. The aim of this research study is to examine the specificity of dry-land resistance exercises to swimming performance. A systematic review of the impact of resistance training on front crawl swimming performance highlighted that low volume, high force, traditional resistance training programmes, showed positive improvement in swimming performance. Neuromuscular adaptations contribute to resistance training exercises improving swimming performance according to several research studies. A review of the specificity between front crawl swimming and dry-land resistance exercises using electromyography (EMG) data highlighted a series of similar prime movers (i.e. latissimus dorsi, pectoralis major, triceps brachii and deltoids) between a range of dry-land resistance exercises. A qualitative study of elite swimming strength and conditioning coaches identified the dry-land resistance exercises most commonly used and deemed most relevant by practitioners and coaches. The bench press and pull up were the two upper body dry-land resistance exercises that coaches ranked highest in terms of improving swimming performance. This prompted an investigation of the specificity of these dry-land resistance exercises to front crawl swimming using EMG data analysis. Following a series of pilot tests, 14 male national and international swimmers were recorded using 2D kinematic analysis to identify event cycles and EMG to investigate muscle activations. The specificity of front crawl swimming to bench press and pull up exercises were examined using temporal coordination , temporal muscle activation overlaps, Functional Data Analysis (FDA) Pearson pointwise correlations, Statistical Parametric Mapping (SPM) t-tests and Root Mean Square Difference (RMSD). The findings of this research show that while the key prime movers between the bench press and pull up exercises and front crawl swimming are similar, there is limited specificity. The results would also suggest that these exercises are applicable for the general preparation period but not for the specific competition period. The large variability within the data set makes findings difficult to interpret. Future research needs to focus on individual analysis of specificity, as the large variability does not make group analysis techniques representative of the high level of individual variability found within the data set. Greater specificity is required through the development of a coherent biomechanical model of specificity that describes joint angles, angular velocity, torque and muscle activations.
Thesis
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This work aimed to study the influence of velocity on lower limbs force production capabilities during single and repeated high-intensity exercises (i.e. strength-endurance). The first part of this work (Partie 1) focused on the type of modeling to draw the force-velocity relationship during acyclic ballistic lower limb extensions. This first part has brought original results that support the linearity of the force-velocity relationship, especially on the velocity end of the relationship. Considering all the force and velocity conditions explored, the linearity was confirmed experimentally over 80% of the total spectrum of the force-velocity relationship (i.e. from 6 to 86% of the theoretical maximal velocity), even in comparison to a curvilinear modeling. The second part (Partie 2a) aimed to i) investigate the effect of the force-velocity condition on strength- endurance (i.e. the maximum number of repetitions), controlling the effect of movement frequency and ii) to revisit the effect of exercise intensity, commonly expressed relatively to the maximum power obtained at optimal velocity (Pmax). The results obtained showed that strength-endurance was more affected by exercise intensity when power output was expressed relative to the maximum power specific to the velocity condition (Pmaxv) than when it was expressed relatively to Pmax. The results also showed that strength- endurance between different force-velocity-power conditions was explained at 88% by Pmaxv and at 10% by the force-velocity condition, in which this relative power is developed. Strength-endurance was greater when Pmaxv was lower and in high force-low velocity conditions. In addition to the maximum number of repetitions, the high force-low velocity conditions allowed a greater total mechanical work for a given Pmaxv. The third part (Partie 2b) aimed at studying the inter-individual variability of the effect of the force- velocity condition on strength-endurance. Following this study, it was pointed out that the effect of the force- velocity condition on strength-endurance was not the same for all individuals and in particular that exist different athlete profiles: some individuals are better in high force-low velocity conditions or in low force-high velocity conditions. This individual force-velocity-endurance profile gives an indication of the orientation of endurance capabilities toward high force-low velocity conditions, or vice versa. From a practical point of view, these results showed that an individual with the best endurance performance in a force-velocity condition and for a given Pmaxv was not always the best in all force-velocity conditions. In addition to depend on the intensity of exercise, strength-endurance also depends on this force-velocity-endurance profile. To conclude, this thesis work has confirmed that the effect of velocity on the lower limbs force production capabilities during single ballistic movements was linear over all the functional conditions of velocity, in particular at very high velocities. This work has also shown that in the context of repeated high intensity exercises, the force-velocity condition in which the power is developed influences strength-endurance independently of power output and the movement frequency. In addition, the influence of force-velocity condition on strength-endurance is not similar for all individuals: each individual is characterized by its own force-velocity-endurance profile. An accurate determination of the force-velocity-power conditions seems interesting for the evaluation and training of force production capabilities with an individualized approach.
Article
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The purpose of this study was to quantify possible differences in sprint mechanical outputs in soccer according to soccer playing standard, position, age and sex. Sprint tests of 674 male and female players were analysed. Theoretical maximal velocity (v0), horizontal force (F0), horizontal power (Pmax), force-velocity slope (SFV), ratio of force (RFmax) and index of force application technique (DRF) were calculated from anthropometric and spatiotemporal data using an inverse dynamic approach applied to the centre-of-mass movement. Players of higher standard exhibited superior F0, v0, Pmax, RFmax and DRF scores (small to large effects) than those of lower standard. Forwards displayed clearly superior values for most outputs, ahead of defenders, midfielders and goalkeepers, respectively. Male >28 y players achieved poorer v0, Pmax and RFmax than <20, 20-24 and 24-28 y players (small to moderate), while female <20 y players showed poorer values than 20-24 and >24 y players for the same measures (small). The sex differences in sprint mechanical properties ranged from small to very large. These results provide a holistic picture of the force-velocity-power profile continuum in sprinting soccer players and serve as useful background information for practitioners when diagnosing individual players and prescribing training programs.
Article
Ballistic actions are imperative in sports where performance depends on power production across a relevant range of contraction- and movement velocities. Force-velocity-power profiling provides information regarding neuromuscular capabilities and vertical performances, but knowledge regarding its associative value towards horizontal movements is scarce. Therefore, we conducted FvP profiling and analysed associations with uni-and multidirectional ballistic performance tasks in 27 international- to national-level athletes (18.9 ± 2.6 years, 182.9 ± 7.1 cm 21 and 79.2 ± 11.9 kg). Low to moderate correlations were observed between theoretical maximal power (Pmax) and horizontal acceleration- (R =-0.43), speed- (R =-0.64), sprint- (R =-0.60) and agility (R =-0.59) performances. Force-velocity imbalance (FvIMB) significantly (P ≤ 0.05) strengthened the correlations towards sprinting ability (from -0.60 to -0.74) and agility (from -0.59 to -0.68), however, both correlations remaining weaker than for jumping performances (R = 0.78- 0.86). In conclusion, FvP profiling provides information of importance for horizontal- and vertical performances with a significant positive effect of Pmax, but negative effect of FvIMB. Assessment of lower-extremity neuromuscular capabilities through FvP profiling and associated development of training programs targeting compensation of either force-or velocity deficit may benefit the ability to utilize a given power potential.
Article
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This investigation aimed to compare the maximal sprint acceleration profiles of drafted and non-drafted elite junior Australian football (AF) players. Nineteen players (10 drafted and 9 non-drafted) from an elite junior AF state team participated in this study. Instantaneous velocity was measured via radar gun during maximal 30 m sprints. The velocity-time data were analysed to derive individual force-velocity-power characteristics and sprint times. No significant differences existed between groups, however drafted players reached moderately faster maximum velocity (Hedges' g = 0.70 [-0.08; 1.48] and theoretical maximum velocity (g = 0.65 [-0.13; 1.42]) than non-drafted players indicating a superior ability to apply higher amounts of force at increasing sprinting velocity. Further, drafted players produced moderately higher absolute theoretical maximum force (g = 0.72 [-0.06; 1.50]) and absolute maximum power (g = 0.83 [0.04; 1.62]) which reflects their moderately higher body mass (g = 0.61[-0.16;1.38]). Although not significant, in this sample of elite junior AF players, those drafted into the AFL displayed greater absolute sprint acceleration characteristics and maximal velocity capabilities than their non-drafted counterparts (moderate effect size). Whether force-velocity-power characteristics can be more beneficial in differentiating sprint performance of elite junior Australian footballers compared to the traditional sprint time approach warrants further investigation with a larger sample size.
Article
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The aim of this study was to test individual adaptation kinetics to a high-resistance sprint training program designed to improve maximal horizontal power (Pmax), and compare the group and individual results of a classical “pre-post” analysis, and a “pre-peak” approach. Thirteen male and 9 female trained sprinters had their 30-m sprint performance and mechanical outputs assessed 1 week before (PRE), and one (POST, W1), 2 (W2), 3 (W3) and 4 (W4) weeks after a 10-week training block (10 repetitions of 20-m resisted sprints at the load associated to the apex of their velocity-power relationship: i.e., 90 ± 10% body mass on average (range: 75–112%). We observed clearly different outcomes on all variables for the PRE-POST vs. PRE-PEAK analyses. The PRE-PEAK analysis showed a larger (almost double) increase in Pmax (9.98 ± 5.27% on average, p < 0.01) than the PRE-POST (5.39 ± 5.87%, p < 0.01). Individual kinetics of post-training adaptations show that peak values were not captured in the POST (W1) assessment (generally observed at W3 and W4). Finally, the week of greatest Pmax output differed strongly among subjects, with most subjects (7/22) peaking at W4. In conclusion, after a 10-week high-resistance sprint training block, a classical 1-week-PRE to 1-week-POST assessment could not capture peak adaptation, which differed among athletes. Adopting a similar approach in practice or research should improve insight into the true effects of training stimuli on athletic capabilities.
Article
Purpose Improvements in D′ (the fatigability constant for running) subsequent to training interventions remain elusive. High-intensity interval training (HIIT) within the severe intensity domain for short durations (< 2-min) have been theorized to improve D′. The purpose of the present study was to assess this in a group of moderately trained individuals. Methods Eighteen participants completed graded exercise testing (GXT), 40-m sprint testing and a 3-min all-out test (3MT) for running to determine key mechanistic and physiological parameters. Participants were randomly assigned into one of two groups based on intensity prescription (G140% = 140% of critical speed [CS]), or time intervals (G90-s = 90-s) to complete a twice-weekly training intervention for 6-weeks followed by re-assessment. Results No between-group differences were present either prior to or following the intervention. Substantial and meaningful improvements were detected during the post-intervention period for both groups for VO2max (G140%: + 7.60%; G90-s: + 11.67%), speed evoking VO2max (sVO2max; G140%: + 4.33%; G90-s: + 2.92%), gas exchange threshold (GET; G140%: + 12.02%; G90-s: + 20.52%), speed evoking GET (sGET; G140%: + 4.17%; G90-s: + 7.92%), CS (G140%: M = 0.62 m/s; G90-s: M = 0.46 m/s), D′ (G140%: M = − 56.34 m; G90-s: M = − 18.36 m), FI% (G140% M = − 6.75%; G90-s: M = − 4.38%) and maximal distance (G140%: M = 49.67 m; G90-s: M = 58.38 m). Conclusions The prescribed intensities and durations were insufficient to elicit improvements in D′. Improvements in D′ may be dependent on very short-duration intervals (i.e. < 60 to 90-s) at speeds exceeding 140% CS but below maximal sprint speed.
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We tested the hypothesis that the degree of adaptation to highly focused sprint training at opposite ends of the sprint Force-Velocity (FV) spectrum would be associated with initial sprint FV-profile in rugby athletes. Training-induced changes in sprint FV-profiles were computed before and after an 8-week in-season resisted or assisted sprint training protocol, including a 3-week taper. Professional male rugby players (age: 18.9 ± 1.0 years; body-height: 1.9 ± 0.0 m; body-mass: 88.3 ± 10.0 kg) were divided into two groups based on their initial sprint FV-profiles: 1) heavy sled training (RESISTED, N = 9, velocity loss 70-80%), and 2) assisted acceleration training (ASSISTED, N = 12, velocity increase 5-10%). A total of 16 athletes were able to finish all required measurements and sessions. According to the hypothesis, a significant correlation was found between initial sprint FV-profile and relative change in sprint FV-profile (RESISTED: r = -0.95, p<0.01, ASSISTED: r = -0.79, p<0.01). This study showed that initial FV-properties influence the degree of mechanical response when training at different ends of the FV-spectrum. Practitioners should consider utilizing the sprint FV-profile to improve the individual effectiveness of resisted and assisted sprint training programs in high-level rugby athletes.
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The main aim of hamstring injury rehabilitation is to facilitate that the athlete is returning to sport at highest possible performance level as fast as possible but with a minimal risk of reinjury. The characteristics and presentation of the different hamstring injury types may guide the clinician toward a specific and appropriate rehabilitation plan, including rehabilitation goals with adequate progression and loading through stepwise rehabilitation phases. This chapter summarizes the evidence for hamstring rehabilitation programs following athletic hamstring injuries. The chapter covers acute hamstring muscle injuries, complete hamstring tendon avulsion ruptures, apophyseal avulsion fractures, and proximal hamstring tendinopathies. It further provides recommendations for how to optimize the rehabilitation process for the specific hamstring injury types.
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Hamstring strain injury often results in neuromuscular performance deficits that persist beyond rehabilitation and the return to full training and competitive sport. It seems appropriate to address these deficits as a part of a sport-specific training program which primarily aims to enhance performance. Prolonged deficits in horizontal ground reaction forces in sprinting, repeat sprint performance, knee flexor eccentric strength and biceps femoris long head fascicle lengths have been observed in multiple studies of hamstring strain injury. Why such deficits persist beyond the return to sport is not known, although persistent neuromuscular inhibition of the injured muscles has been proposed. There is limited and mixed evidence for sprint running kinematic (technique) differences between previously injured and uninjured limbs or athletes, although more work in this area seems warranted. While there is some uncertainty about the optimal mix of methods for addressing the aforementioned deficits, sport-specific running programs in conjunction with continued monitoring of acceleration phase sprint performance and repeated sprint ability seem appropriate. Heavy strength training with at least some eccentrically biased exercises is also recommended to address deficits in eccentric strength and muscle fascicle lengths.
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Sprinting and speed is a fundamental skill and physical attribute crucial in seam bowlers and batters within cricket. The aim of this study was to assess differences in mechanical properties during sprinting between youth and senior international cricketers and between seam bowlers and batters. Retrospective 40 m sprint times and anthropometric measures of 56 international cricketers (19 senior seam bowlers, 7 under-19 seam bowlers, 16 senior batters, 14 under-19 batters) were used to calculate the theoretical maximal force (F 0 ), theoretical maximal velocity (V (0) ), theoretical maximal power (P max ), slope of the force-velocity relationship (F-V slope), maximal ratio of horizontal-to-resultant force (RF max ), decrease in the ratio of horizontal-to-resultant force (DRF) and optimum velocity (V opt ). There were no significant (P > 0.05) differences in sprint times nor sprint mechanical profile variables between position or age. However, there was a moderately greater F 0 (N/Kg) (ES = 0.78; 90% CI 0.19–1.34) and RF max (ES = 0.75; 90% CI 0.11–1.35) in senior seam bowlers when compared to batters. Furthermore, FV Slope (ES = 0.79; 90% CI 0.15–1.40) and DRF (ES = 0.75; 90% CI 0.11–1.35) were moderately greater in senior compared to under-19 batters. When expressed relative to body mass, it appears that senior international seam bowlers show trends towards a more force biased profile during sprinting when compared to batters. These findings will help coaches to optimise physical preparation strategies in youth and senior international cricketers.
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Aim The aim of this study was to ascertain the effect of resisted sprint training in swimming on maximal swimming velocity and performance characteristics. The aim was also to examine how maximal swimming velocity is related to maximal swim power and maximal dry-land power. Method Eighteen competitive national level swimmers (9 male and 9 female; age: 18.3 ± 2.3 years, body mass: 72 ± 8.3 kg, height: 177.2 ± 4.6 cm, mean ± SD) were recruited to this study. Subjects were assigned to either resisted sprint training (RST) or unresisted sprint training (UST). Sprint training was performed two times per week during 6 weeks as 8x15m with a 2min send-off interval. RST performed sprint training using individualized load corresponding 10% of maximum drag load (L 10), UST performed sprint training with no added resistance. A test-battery including dry-land strength assessment; maximal strength (MxS) and explosive strength (ExS), a timed 25m front-crawl swim and in-water force-velocity profiling was performed prior and following the training intervention. Maximal swim power (P max), maximum drag load (F 0), theoretical maximum velocity (v 0) and slope of force-velocity curve (S Fv) was computed though force-velocity profiling. Results No significant within group differences occurred in neither RST nor UST following the 6-week intervention period in: swimming velocity, MxS, ExS, P max , F 0 , v 0 , and S Fv. Strong correlations were found between swimming velocity and MxS (r = 0.75), ExS (r = 0.82) and P max (r = 0.92). Conclusion Resisted sprint training in swimming using L 10 did in the present study not elicit any improvements in maximal swimming velocity or examined performance characteristics. Resisted sprint training does not appear to be a superior method of improving swimming performance compared to unresisted sprint training. MxS, ExS and P max can be used as robust predictors of swim performance, however only P max was found to be casually related to swimming velocity. Acknowledgments I would like to express gratitude to my supervisor Dr. Lennart Gullstrand for guidance and feedback along the journey. Great thank you to Johan Wallberg for providing me with literature and valuable advice, also thank you to Carl Jenner for support and interesting discussions on the topic. Special thanks to Juan Alonso for supplying me with equipment and teaching me how to operate it. Thank you to Manni Svensson at 1080 Motion for showing interest in the project and to Prof. Peter Schantz for precious feedback in the finishing stages. Lastly, big thank you to all the swimmers who volunteered to participate in the project. Abbreviation Dictionary C D-hydrodynamic force coefficient ExS-dry-land explosive strength e g-gross efficiency e p-propelling efficiency F p-propulsive force F d-drag force F-v-force-velocity F 0-theoretical maximum force (maximum drag load) L 10-load corresponding 10% of maximum drag load L opt-load corresponding to maximal power output MxS-dry-land maximal strength P d-power to overcome drag (useful power) P k-power lost in giving water kinetic energy P i-power input (metabolic power) P max-maximal swim power P o-mechanical power output RST-resisted sprint training SI-stroke index SL-stroke length SR-stroke rate (stroke frequency) S Fv-slope of force-velocity curve UST-unresisted sprint training v 0-theoretical maximum velocity ∆%-delta in % (change in %)
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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.
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At the 2008 Summer Olympics in Beijing, Usain Bolt broke the world record for the 100 m sprint. Just one year later, at the 2009 World Championships in Athletics in Berlin he broke it again. A few months after Beijing, Eriksen et al. studied Bolt's performance and predicted that Bolt could have run about one-tenth of a second faster, which was confirmed in Berlin. In this paper we extend the analysis of Eriksen et al. to model Bolt's velocity time-dependence for the Beijing 2008 and Berlin 2009 records. We deduce the maximum force, the maximum power, and the total mechanical energy produced by Bolt in both races. Surprisingly, we conclude that all of these values were smaller in 2009 than in 2008.
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To determine whether the magnitude of performance improvements and the mechanisms driving adaptation to ballistic power training differ between strong and weak individuals. Twenty-four men were divided into three groups on the basis of their strength level: stronger (n = 8, one-repetition maximum-to-body mass ratio (1RM/BM) = 1.97 +/- 0.08), weaker (n = 8, 1RM/BM = 1.32 +/- 0.14), or control (n = 8, 1RM/BM = 1.37 +/- 0.13). The stronger and weaker groups trained three times per week for 10 wk. During these sessions, subjects performed maximal-effort jump squats with 0%-30% 1RM. The impact of training on athletic performance was assessed using a 2-d testing battery that involved evaluation of jump and sprint performance as well as measures of the force-velocity relationship, jumping mechanics, muscle architecture, and neural drive. Both experimental groups showed significant (P < or = 0.05) improvements in jump (stronger: peak power = 10.0 +/- 5.2 W.kg, jump height = 0.07 +/- 0.04 m; weaker: peak power = 9.1 +/- 2.3 W.kg, jump height = 0.06 +/- 0.04 m) and sprint performance after training (stronger: 40-m time = -2.2% +/- 2.0%; weaker: 40-m time = -3.6% +/- 2.3%). Effect size analyses revealed a tendency toward practically relevant differences existing between stronger and weaker individuals in the magnitude of improvements in jump performance (effect size: stronger: peak power = 1.55, jump height = 1.46; weaker: peak power = 1.03, jump height = 0.95) and especially after 5 wk of training (effect size: stronger: peak power = 1.60, jump height = 1.59; weaker: peak power = 0.95, jump height = 0.61). The mechanisms driving these improvements included significant (P < or = 0.05) changes in the force-velocity relationship, jump mechanics, and neural activation, with no changes to muscle architecture observed. The magnitude of improvements after ballistic power training was not significantly influenced by strength level. However, the training had a tendency toward eliciting a more pronounced effect on jump performance in the stronger group. The neuromuscular and biomechanical mechanisms driving performance improvements were very similar for both strong and weak individuals.
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We tested the validity of an instrumented treadmill dynamometer for measuring maximal propulsive power during sprint running, and sought to verify whether this could be done over one single sprint, as shown during sprint cycling. The treadmill dynamometer modified towards sprint use (constant motor torque) allows vertical and horizontal forces to be measured at the same location as velocity, i.e. at the foot, which is novel compared to existing methods in which power is computed as the product of belt velocity and horizontal force measured by transducers placed in the tethering system. Twelve males performed 6s sprints against default, high and low loads set from the motor torque necessary to overcome the friction due to subjects' weight on the belt (default load), and 20% higher and lower motor torque values. Horizontal ground reaction force, belt velocity, propulsive power and linear force-velocity relationships were compared between the default load condition and when taking all conditions together. Force and velocity traces and values were reproducible and consistent with the literature, and no significant difference was found between maximal power and force-velocity relationships obtained in the default load condition only vs. adding data from all conditions. The presented method allows one to measure maximal propulsive power and calculate linear force-velocity relationships from one single sprint data. The main novelties are that both force and velocity are measured at the same location, and that instantaneous values are averaged over one contact period, and not over a constant arbitrary time-window.
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In clinical measurement comparison of a new measurement technique with an established one is often needed to see whether they agree sufficiently for the new to replace the old. Such investigations are often analysed inappropriately, notably by using correlation coefficients. The use of correlation is misleading. An alternative approach, based on graphical techniques and simple calculations, is described, together with the relation between this analysis and the assessment of repeatability.