The purpose of this investigation was to examine the impact of load on the power-, force- and velocity-time curves during the jump squat. The analysis of these curves for the entire movement at a sampling frequency of 200–500 Hz averaged across 18 untrained male subjects is the most novel aspect of this study. Jump squat performance was assessed in a randomized fashion across five different external loads: 0, 20, 40, 60, and 80 kg (equivalent to 0 ± 0, 18 ± 4, 37 ± 8, 55 ± 12, 74 ± 15% of 1RM, respectively). The 0-kg loading condition (i.e., body mass only) was the load that maximized peak power output, displaying a significantly (p ≤ .05) greater value than the 40, 60, and 80 kg loads. The shape of the force-, power-, and velocity-time curves changed significantly as the load applied to the jump squat increased. There was a significantly greater rate of power development in the 0 kg load in comparison with all other loads examined. As the first comprehensive illustration of how the entire power-, force-, and velocity-time curves change across various loading conditions, this study provides extensive evidence that a load equaling an individuals body mass (i.e., external load = 0 kg) maximizes power output in untrained individuals during the jump squat.
Prue Cormie, Jeffrey M. McBride and Grant O. McCaulley
John J. McMahon, Paul A. Jones, Timothy J. Suchomel, Jason Lake and Paul Comfort
Perform . 2017 ; 12 ( 6 ): 803 – 811 . PubMed doi:10.1123/ijspp.2016-0467 10.1123/ijspp.2016-0467 27918658 10. Cormie P , McBride JM , McCaulley GO . Power-time, force-time, and velocity-time curve analysis during the jump squat: impact of load . J Appl Biomech . 2008 ; 24 ( 2 ): 112 – 120
Masafumi Terada, Megan Beard, Sara Carey, Kate Pfile, Brian Pietrosimone, Elizabeth Rullestad, Heather Whitaker and Phillip Gribble
calculating SampEn ( Glass et al., 2014 ). Glass et al. ( 2014 ) discussed the issues of utilizing the COP displacement signals for SampEn calculation in more detail. SampEn was then calculated for the COP velocity time series in the AP (SampEn-AP) and ML (SampEn-ML) directions with a custom MATLAB file using
Pedro Jiménez-Reyes, Amador García-Ramos, Victor Cuadrado-Peñafiel, Juan A. Párraga-Montilla, José A. Morcillo-Losa, Pierre Samozino and Jean-Benoît Morin
, subjects performed 3 maximal sprints of 40 m from a crouching position (staggered-stance) with 4 minutes of rest between successive sprints. The velocity-time data of each sprint were collected via a Stalker Acceleration Testing System (ATS) II radar device (Model: Stalker ATS II; Applied Concepts, Dallas
Jorge Carlos-Vivas, Elena Marín-Cascales, Tomás T. Freitas, Jorge Perez-Gomez and Pedro E. Alcaraz
dynamics analysis of the center of mass motion and allows for assessment of the sprinting power–force–velocity profile from only the anthropometric and spatiotemporal data obtained during 1 single sprint. 27 Raw velocity–time data, obtained from the radar device, were fitted by an exponential function and
Matt R. Cross, Matt Brughelli, Scott R. Brown, Pierre Samozino, Nicholas D. Gill, John B. Cronin and Jean-Benoît Morin
To compare mechanical properties of overground sprint running in elite rugby union and rugby league athletes.
Thirty elite rugby code (15 rugby union and 15 rugby league) athletes participated in this cross-sectional analysis. Radar was used to measure maximal overground sprint performance over 20 or 30 m (forwards and backs, respectively). In addition to time at 2, 5, 10, 20, and 30 m, velocity-time signals were analyzed to derive external horizontal force–velocity relationships with a recently validated method. From this relationship, the maximal theoretical velocity, external relative and absolute horizontal force, horizontal power, and optimal horizontal force for peak power production were determined.
While differences in maximal velocity were unclear between codes, rugby union backs produced moderately faster split times, with the most substantial differences occurring at 2 and 5 m (ES 0.95 and 0.86, respectively). In addition, rugby union backs produced moderately larger relative horizontal force, optimal force, and peak power capabilities than rugby league backs (ES 0.73−0.77). Rugby union forwards had a higher absolute force (ES 0.77) despite having ~12% more body weight than rugby league forwards.
In this elite sample, rugby union athletes typically displayed greater short-distance sprint performance, which may be linked to an ability to generate high levels of horizontal force and power. The acceleration characteristics presented in this study could be a result of the individual movement and positional demands of each code.
Kim Hébert-Losier, Kurt Jensen and Hans-Christer Holmberg
Jumping and hopping are used to measure lower-body muscle power, stiffness, and stretch-shortening-cycle utilization in sports, with several studies reporting correlations between such measures and sprinting and/or running abilities in athletes. Neither jumping and hopping nor correlations with sprinting and/or running have been examined in orienteering athletes.
The authors investigated squat jump (SJ), countermovement jump (CMJ), standing long jump (SLJ), and hopping performed by 8 elite and 8 amateur male foot-orienteering athletes (29 ± 7 y, 183 ± 5 cm, 73 ± 7 kg) and possible correlations to road, path, and forest running and sprinting performance, as well as running economy, velocity at anaerobic threshold, and peak oxygen uptake (VO2peak) from treadmill assessments.
During SJs and CMJs, elites demonstrated superior relative peak forces, times to peak force, and prestretch augmentation, albeit lower SJ heights and peak powers. Between-groups differences were unclear for CMJ heights, hopping stiffness, and most SLJ parameters. Large pairwise correlations were observed between relative peak and time to peak forces and sprinting velocities; time to peak forces and running velocities; and prestretch augmentation and forest-running velocities. Prestretch augmentation and time to peak forces were moderately correlated to VO2peak. Correlations between running economy and jumping or hopping were small or trivial.
Overall, the elites exhibited superior stretch-shortening-cycle utilization and rapid generation of high relative maximal forces, especially vertically. These functional measures were more closely related to sprinting and/or running abilities, indicating benefits of lower-body training in orienteering.
John J. McMahon, Shannon Murphy, Sophie J.E. Rej and Paul Comfort
Gross measures of countermovement-jump (CMJ) performance are commonly used to track maturational changes in neuromuscular function in rugby league (RL). The purpose of this study was to conduct both a gross and a more detailed temporal-phase analysis of the CMJ performances of senior and academy RL players, to provide greater insight into how neuromuscular function differs between these groups.
Twenty senior and 14 academy (under-19) male RL players performed 3 maximal-effort CMJs on a force platform, with forward dynamics subsequently employed to allow gross performance measures and entire kinetic– and kinematic–time curves to be compared between groups.
Jump height (JH), reactive strength index modified, concentric displacement, and relative concentric impulse (C-IMP) were the only gross measures that were greater for senior players (d = 0.58–0.91) than for academy players. The relative force- and displacement–time curves were similar between groups, but the relative power– and velocity–time curves were greater (d = 0.59–0.97) for the senior players at 94–96% and 89–100% of the total movement time, respectively.
The CMJ distinguished between senior and academy RL players, with seniors demonstrating greater JH through applying a larger C-IMP and thus achieving greater velocity throughout the majority of the concentric phase and at takeoff. Therefore, academy RL players should train to improve triple (ie, ankle, knee, and hip) extension velocity during the CMJ to bring their JH scores in line with those attained by senior players.
Susana M. Soares, Ricardo J. Fernandes, J. Leandro Machado, José A. Maia, Daniel J. Daly and João P. Vilas-Boas
It is essential to determine swimmers’ anaerobic potential and better plan training, understanding physiological effects of the fatigue.
To study changes in the characteristics of the intracyclic velocity variation during an all-out 50-m swim and to observe differences in speed and stroking parameters between these changes.
28 competitive swimmers performed a 50-m front-crawl all-out test while attached to a speedometer. The velocity–time (v[t]) curve off all stroke cycles was analyzed per individual using a routine that included a wavelet procedure, allowing the determination of the fatigue thresholds that divide effort in time intervals.
One or 2 fatigue thresholds were observed at individual level on the v(t) curve. In males, when 1 fatigue threshold was identified, the mean velocity and the stroke index dropped (P < .05) in the second time interval (1.7 ± 0.0 vs 1.6 ± 0.0 m/s and 3.0 ± 0.2 vs 2.8 ± 0.3 m/s, respectively). When 2 fatigue thresholds were identified, the mean velocity of the first time interval was higher than that of the third time interval (P < .05), for both male (1.7 ± 0.0 vs 1.6 ± 0.1 m/s) and female (1.5 ± 0.1 vs 1.3 ± 0.1 m/s) swimmers.
One or 2 fatigue thresholds were found in the intracyclic velocity-variation patterns. Concurrently, changes in velocity and stroke parameters were also observed between time intervals. This information could allow coaches to obtain new insights into delaying the degenerative effects of fatigue and maintain stable stroke-cycle characteristics over a 50-m event.
Jace A. Delaney, Tannath J. Scott, Heidi R. Thornton, Kyle J.M. Bennett, David Gay, Grant M. Duthie and Ben J. Dascombe
Rugby league coaches often prescribe training to replicate the demands of competition. The intensities of running drills are often monitored in comparison with absolute match-play measures. Such measures may not be sensitive enough to detect fluctuations in intensity across a match or to differentiate between positions.
To determine the position- and duration-specific running intensities of rugby league competition, using a moving-average method, for the prescription and monitoring of training.
Data from a 15-Hz global positioning system (GPS) were collected from 32 professional rugby league players across a season. The velocity–time curve was analyzed using a rolling-average method, where maximum values were calculated for 10 different durations, 1, 2, 3, 4, 5, 6, 7, 8, 9, and 10 min, for each player across each match.
There were large differences between the 1- and 2-min rolling averages and all other rolling-average durations. Smaller differences were observed for rolling averages of greater duration. Fullbacks maintained a greater velocity than outside backs and middle and edge forwards over the 1- and 2-min rolling averages (ES 0.8−1.2, P < .05). For rolling averages 3 min and greater, the running demands of the fullbacks were greater than those of the middle forwards and outside backs (ES 1.1−1.4, P < .05).
These findings suggest that the running demands of rugby league fluctuate vastly across a match. Fullbacks were the only position to exhibit a greater running intensity than any other position, and therefore training prescription should reflect this.