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Borja Muniz-Pardos, Alejandro Gómez-Bruton, Ángel Matute-Llorente, Alex González-Agüero, Alba Gómez-Cabello, José A. Casajús and Germán Vicente-Rodríguez

sports science because a number of pioneering publications proposed WBV as an effective training method to increase lower-body strength (LBS) and lower-body power (LBP) and, potentially, athletic performance. 5 – 8 The influence of LBP in short-distance swimming performance is well documented. 9 – 12

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Julia Kathrin Baumgart and Øyvind Sandbakk

Purpose:

To investigate on-ice repeated-sprint and sports-specific-technique abilities and the relationships to aerobic and anaerobic off-ice capacities in world-class ice sledge hockey players.

Methods:

Twelve Norwegian national team players performed 8 repeated maximal 30-m sprints and a sports-specific-technique test while upper-body poling on ice, followed by 4 maximal upper-body strength tests and 8-s peak power and 3-min peak aerobic-capacity (VO2peak) tests while ergometer poling.

Results:

The fastest 30-m sprint time was 6.5 ± 0.4 s, the fastest initial 10-m split-time 2.9 ± 0.2 s, and the corresponding power output 212 ± 37 W. Average 30-m time during the 8 repeated sprints was 6.7 ± 0.4 s, and the sprint-time decrement was 4.3% ± 1.8%. Time to execute the sport-specific-technique test was 25.6 ± 2.7 s. Averaged 1-repetition-maximum strength of the 4 exercises correlated with the fastest 30-m sprint time (r = –.77), the fastest initial 10-m split time (r = –.72), the corresponding power output (r = .67), and the average 30-m sprint time (r = –.84) (all P < .05). Peak power of the 8-s ergometer sprint test correlated with the highest initial 10-m power (r = .83, P < .01) and the average 30-m sprint time (r = –.68, P < .05). Average 3-min ergometer power (r = –.86, P < .01) and VO2peak (r = –.67, P < .05) correlated with the sprint-time decrement. All off-ice variables except VO2peak correlated with technique-test time (r = –.58 to .73, all P < .05).

Conclusion:

Maximal strength and power are associated with the ability to sprint fast and rapid execution of a technically complex test, whereas mode-specific endurance capacity is particularly important for maintenance of sprint ability in ice sledge hockey.

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Cameron Mitchell, Rotem Cohen, Raffy Dotan, David Gabriel, Panagiota Klentrou and Bareket Falk

Previous studies in adults have demonstrated power athletes as having greater muscle force and muscle activation than nonathletes. Findings on endurance athletes are scarce and inconsistent. No comparable data on child athletes exist.

Purpose:

This study compared peak torque (Tq), peak rate of torque development (RTD), and rate of muscle activation (EMG rise, Q30), in isometric knee extension (KE) and fexion (KF), in pre- and early-pubertal power- and endurance-trained boys vs minimally active nonathletes.

Methods:

Nine gymnasts, 12 swimmers, and 18 nonathletes (7–12 y), performed fast, maximal isometric KE and KF. Values for Tq, RTD, electromechanical delay (EMD), and Q30 were calculated from averaged torque and surface EMG traces.

Results:

No group differences were observed in Tq, normalized for muscle cross-sectional area. The Tq-normalized KE RTD was highest in power athletes (6.2 ± 1.9, 4.7 ± 1.2, 5.0 ± 1.5 N·m·s–1, for power, endurance, and nonathletes, respectively), whereas no group differences were observed for KF. The KE Q30 was significantly greater in power athletes, both in absolute terms and relative to peak EMG amplitude (9.8 ± 7.0, 5.9 ± 4.2, 4.4 ± 2.2 mV·ms and 1.7 ± 0.8, 1.1 ± 0.6, 0.9 ± 0.5 (mV·ms)/(mV) for power, endurance, and nonathletes, respectively), with no group differences in KF. The KE EMD tended to be shorter (P = .07) in power athletes during KE (71.0 ± 24.1, 87.8 ± 18.0, 88.4 ± 27.8 ms, for power, endurance, and nonathletes), with no group differences in KF.

Conclusions:

Pre- and early-pubertal power athletes have enhanced rate of muscle activation in specifically trained muscles compared with controls or endurance athletes, suggesting that specific training can result in muscle activation-pattern changes before the onset of puberty.

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Kazuo Funato, Akifumi Matsuo and Tetsuo Fukunaga

In order to evaluate how mechanical power relates to athletic performance in weight lifting, specific movement power (SMP) was investigated using a newly developed dynamometer. Four simulated pull movements in weight lifting were measured: weight lifting pull (WL), second pull, back strength pull, and shoulder shrug pull. Subjects included 12 elite (EL) and 14 district (DI) level Japanese weight lifters. Athletic performance was defined as the highest total combined weight (snatch plus clean and jerk) lifted during competition. The highest SMP was observed in the WL. Force, velocity, and power relations were derived from the WL, showing higher velocity and power values in EL than DI at an identical force level. SMP in WL was found to be significantly correlated to athletic performance. SMP measured as a simulated pull movement in weight lifting employing the present dynamometer appears useful in evaluating athletic performance. Furthermore, this dynamometer provides force-velocity relationships during multiarticular explosive movements.

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Sharon A. Evans, Joan M. Eckerson, Terry J. Housh and Glen O. Johnson

This investigation examined age related differences in the muscular power of the arms in high school wrestlers. Seventy-five volunteers (M age ±SD = 16.3 ±1.2 yrs) were stratified into four age groups (≤15.00; 15.01−16.00; 16.01−17.00, and ≥17.01 yrs) corresponding approximately to the freshman through senior years of high school. Mean power (MP) and peak power (PP) were measured using an arm crank Wingate Anaerobic Test, and body composition was assessed via underwater weighing. The results indicated significant (p<0.05) group differences for absolute MP and PP as well as for relative MP and PP (covaried for body weight). No significant differences were found when MP and PP were adjusted for fat-free weight (FFW). The results suggested that the age related increases in muscular power of the arms were a function of increases in FFW across age.

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Tom Kempton, Anita Claire Sirotic, Ermanno Rampinini and Aaron James Coutts

Purpose:

To describe the metabolic demands of rugby league match play for positional groups and compare match distances obtained from high-speed-running classifications with those derived from high metabolic power.

Methods:

Global positioning system (GPS) data were collected from 25 players from a team competing in the National Rugby League competition over 39 matches. Players were classified into positional groups (adjustables, outside backs, hit-up forwards, and wide-running forwards). The GPS devices provided instantaneous raw velocity data at 5 Hz, which were exported to a customized spreadsheet. The spreadsheet provided calculations for speed-based distances (eg, total distance; high-speed running, >14.4 km/h; and very-highspeed running, >18.1 km/h) and metabolic-power variables (eg, energy expenditure; average metabolic power; and high-power distance, >20 W/kg).

Results:

The data show that speed-based distances and metabolic power varied between positional groups, although this was largely related to differences in time spent on field. The distance covered at high running speed was lower than that obtained from high-power thresholds for all positional groups; however, the difference between the 2 methods was greatest for hit-up forwards and adjustables.

Conclusions:

Positional differences existed for all metabolic parameters, although these are at least partially related to time spent on the field. Higher-speed running may underestimate the demands of match play when compared with high-power distance—although the degree of difference between the measures varied by position. The analysis of metabolic power may complement traditional speed-based classifications and improve our understanding of the demands of rugby league match play.

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Matt R. Cross, Matt Brughelli, Scott R. Brown, Pierre Samozino, Nicholas D. Gill, John B. Cronin and Jean-Benoît Morin

Purpose:

To compare mechanical properties of overground sprint running in elite rugby union and rugby league athletes.

Methods:

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.

Results:

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.

Conclusions:

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.

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Annelies Knoppers, Barbara Bedker Meyer, Martha Ewing and Linda Forrest

Organizational power can be defined as access to and ability to mobilize resources such as supplies, support, and information (Kanter, 1977). Differences in organizational power in athletic departments can be seen as a function of sport (whether one coaches a revenue or nonrevenue sport) or of gender. This study examined the extent to which sport or gender best explained differences in the degree of organizational power that Division I college coaches hold in athletic departments. The sample consisted of 947 coaches who responded to a questionnaire that included items dealing with their access to supplies, support, and information. The results indicated that the nature of the intersection of sport and gender varied across the three dimensions of power. Consistently, however, female coaches of nonrevenue sports were most limited in their access to critical resources while male coaches of revenue sports had the most power. This led to the conclusion that an analysis on the distribution of power should examine it in the context of both gender and sport.

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S. Andy Sparks, Benjamin Dove, Craig A. Bridge, Adrian W. Midgley and Lars R. McNaughton

Power meters have traditionally been integrated into the crank set, but several manufacturers have designed new systems located elsewhere on the bike, such as inside the pedals.

Purpose:

This study aimed to determine the validity and reliability of the Keo power pedals during several laboratory cycling tasks.

Methods:

Ten active male participants (mean ± SD age 34.0 ± 10.6 y, height 1.77 ± 0.04 m, body mass 76.5 ± 10.7 kg) familiar with laboratory cycling protocols completed this study. Each participant was required to complete 2 laboratory cycling trials on an SRM ergometer (SRM, Germany) that was also fitted with the Keo power pedals (Look, France). The trials consisted of an incremental test to exhaustion followed by 10 min rest and then three 10-s sprint tests separated by 3 min of cycling at 100 W.

Results:

Over power ranges of 75 to 1147 W, the Keo power-pedal system produced typical error values of 0.40, 0.21, and 0.21 for the incremental, sprint, and combined trials, respectively, compared with the SRM. Mean differences of 21.0 and 18.6 W were observed between trials 1 and 2 with the Keo system in the incremental and combined protocols, respectively. In contrast, the SRM produced differences of 1.3 and 0.6 W for the same protocols.

Conclusions:

The power data from the Keo power pedals should be treated with some caution given the presence of mean differences between them and the SRM. Furthermore, this is exacerbated by poorer reliability than that of the SRM power meter.

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Matt R. Cross, Matt Brughelli, Pierre Samozino, Scott R. Brown and Jean-Benoit Morin

Purpose:

To ascertain whether force-velocity-power relationships could be compiled from a battery of sled-resisted overground sprints and to clarify and compare the optimal loading conditions for maximizing power production for different athlete cohorts.

Methods:

Recreational mixed-sport athletes (n = 12) and sprinters (n = 15) performed multiple trials of maximal sprints unloaded and towing a selection of sled masses (20–120% body mass [BM]). Velocity data were collected by sports radar, and kinetics at peak velocity were quantified using friction coefficients and aerodynamic drag. Individual force–velocity and power–velocity relationships were generated using linear and quadratic relationships, respectively. Mechanical and optimal loading variables were subsequently calculated and test–retest reliability assessed.

Results:

Individual force–velocity and power–velocity relationships were accurately fitted with regression models (R 2 > .977, P < .001) and were reliable (ES = 0.05–0.50, ICC = .73–.97, CV = 1.0–5.4%). The normal loading that maximized peak power was 78% ± 6% and 82% ± 8% of BM, representing a resistance of 3.37 and 3.62 N/kg at 4.19 ± 0.19 and 4.90 ± 0.18 m/s (recreational athletes and sprinters, respectively). Optimal force and normal load did not clearly differentiate between cohorts, although sprinters developed greater maximal power (17.2–26.5%, ES = 0.97–2.13, P < .02) at much greater velocities (16.9%, ES = 3.73, P < .001).

Conclusions:

Mechanical relationships can be accurately profiled using common sled-training equipment. Notably, the optimal loading conditions determined in this study (69–96% of BM, dependent on friction conditions) represent much greater resistance than current guidelines (~7–20% of BM). This method has potential value in quantifying individualized training parameters for optimized development of horizontal power.