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Jeremy M. Sheppard, Tim Gabbett, Kristie-Lee Taylor, Jason Dorman, Alexis J. Lebedew, and Russell Borgeaud

Purpose:

The authors conducted a study to develop a repeated-effort test for international men’s volleyball. The test involved jumping and movement activity that was specific to volleyball, using durations and rest periods that replicated the demands of a match.

Methods:

A time–motion analysis was performed on a national team and development national team during international matches to determine the demands of competition and thereby form the basis of the rationale in designing the repeated-effort test. An evaluation of the test for reliability and validity in discriminating between elite and sub-elite players was performed.

Results:

The test jump height and movement-speed test parameters were highly reliable, with findings of high intraclass correlations (ICCs) and low typical errors of measurement (TE; ICC .93 to .95 and %TE 0.54 to 2.44). The national team’s ideal and actual jump height and ideal and actual speeds, mean ± SD, were 336.88 ± 8.31 cm, 329.91 ± 6.70 cm, 6.83 ± 0.34 s, and 7.14 ± 0.34 s, respectively. The development national team’s ideal and actual jump heights and ideal and actual speeds were 330.88 ± 9.09 cm, 323.80 ± 7.74 cm, 7.41 ± 0.56 s, and 7.66 ± 0.56 s, respectively. Probabilities of differences between groups for ideal jump, actual jump, ideal time, and actual time were 82%, 95%, 92%, and 96%, respectively, with a Cohen effect-size statistic supporting large magnitudes (0.69, 0.84, 1.34, and 1.13, respectively).

Conclusion:

The results of this study demonstrate that the developed test offers a reliable and valid method of assessing repeated-effort ability in volleyball players.

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Shane Malone, Mark Roe, Dominic A. Doran, Tim J. Gabbett, and Kieran D. Collins

Purpose:

To examine the association between combined session rating of perceived exertion (RPE) workload measures and injury risk in elite Gaelic footballers.

Methods:

Thirty-seven elite Gaelic footballers (mean ± SD age 24.2 ± 2.9 y) from 1 elite squad were involved in a single-season study. Weekly workload (session RPE multiplied by duration) and all time-loss injuries (including subsequent-wk injuries) were recorded during the period. Rolling weekly sums and wk-to-wk changes in workload were measured, enabling the calculation of the acute:chronic workload ratio by dividing acute workload (ie, 1-weekly workload) by chronic workload (ie, rolling-average 4-weekly workload). Workload measures were then modeled against data for all injuries sustained using a logistic-regression model. Odds ratios (ORs) were reported against a reference group.

Results:

High 1-weekly workloads (≥2770 arbitrary units [AU], OR = 1.63–6.75) were associated with significantly higher risk of injury than in a low-training-load reference group (<1250 AU). When exposed to spikes in workload (acute:chronic workload ratio >1.5), players with 1 y experience had a higher risk of injury (OR = 2.22) and players with 2–3 (OR = 0.20) and 4–6 y (OR = 0.24) of experience had a lower risk of injury. Players with poorer aerobic fitness (estimated from a 1-km time trial) had a higher injury risk than those with higher aerobic fitness (OR = 1.50–2.50). An acute:chronic workload ratio of (≥2.0) demonstrated the greatest risk of injury.

Conclusions:

These findings highlight an increased risk of injury for elite Gaelic football players with high (>2.0) acute:chronic workload ratios and high weekly workloads. A high aerobic capacity and playing experience appears to offer injury protection against rapid changes in workload and high acute:chronic workload ratios. Moderate workloads, coupled with moderate to high changes in the acute:chronic workload ratio, appear to be protective for Gaelic football players.

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Tyler L. Goodale, Tim J. Gabbett, Ming-Chang Tsai, Trent Stellingwerff, and Jeremy Sheppard

Purpose:

To evaluate the effects of contextual game factors on activity and physiological profiles of international-level women’s rugby sevens players.

Methods:

Twenty international-level female rugby sevens players from the same national team participated in this study. Global positioning system and heart-rate data were collected at 5 World Rugby Women’s Sevens Series events (2013–14 season).

Results:

Total, moderate-speed (0.2–3.5 m/s), and high-speed running (3.5–5.0 m/s) distances were significantly greater in the first half (20.1% ± 4.1%, 17.6% ± 6.9%, 24.5% ± 7.8%), during losses (11.4% ± 6.1%, 6.1% ± 6.4%, 26.9% ± 9.8%), during losses of large magnitudes (≥2 tries) (12.9% ± 8.8%, 6.8% ± 10.0%, 31.2% ± 14.9%), and against top-4 opponents (12.6% ± 8.7%, 11.3% ± 8.5%, 15.5% ± 13.9%). In addition, total distance increased (5.0% ± 5.5%) significantly from day 1 to day 2 of tournaments, and very-high-speed (5.0–6.5 m/s) running distance increased significantly (26.0% ± 14.2%) during losses. Time spent between 90% and 100% of maximum heart rate (16.4% ± 14.5%) and player load (19.0% ± 5.1%) were significantly greater in the second half. No significant differences in physiological or activity profiles were observed between forwards and backs.

Conclusions:

Game half, game outcome, tournament day, opponent rank, and margin of outcome all affected activity profiles, whereas game half affected physiological profiles. No differences in activity or physiological profiles were found between playing positions. Practitioners are advised to develop high-speed running ability in women’s rugby sevens players to prepare them to tolerate the varying factors that affect activity profiles.

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Tyler L. Goodale, Tim J. Gabbett, Trent Stellingwerff, Ming-Chang Tsai, and Jeremy M. Sheppard

Purpose:

To investigate the physical qualities that differentiate playing minutes in international-level women’s rugby sevens players.

Methods:

Twenty-four national-level female rugby sevens players underwent measurements of anthropometry, acceleration, speed, lower- and upper-body strength, lower-body power, and aerobic fitness. Playing minutes in international competition were used to differentiate players into 2 groups, a high- or low-playing-minutes group. Playing minutes were related to team selection, which was determined by the coaching staff. Playing minutes were therefore used to differentiate performance levels.

Results:

Players in the high-playing-minutes group (≥70 min) were older (mean ± SD 24.3 ± 3.1 vs 21.2 ± 4.3 y, P = .05, effect size [ES] = 0.77 ± 0.66, 90% confidence limit) and had greater experience in a national-training-center environment (2.4 ± 0.8 vs 1.7 ± 0.9 y, P = .03, ES = 0.83 ± 0.65), faster 1600-m time (374.5 ± 20.4 vs 393.5 ± 29.8 s, P = .09, ES = –0.70 ± 0.68), and greater 1-repetition-maximum upper-body strength (bench press 68.4 ± 6.3 vs 62.2 ± 8.1 kg, P = .07, ES = 0.80 ± 0.70, and neutral-grip pull-up 84.0 ± 8.2 vs 79.1 ± 5.4 kg, P = .12, ES = 0.68 ± 0.72) than athletes who played fewer minutes. Age (rs = .59 ± ~.28), training experience (rs = .57 ± ~.29), bench press (r = .44 ± ~.36), and 1600-m time (r = –.43 ± ~.34) were significantly associated with playing minutes. Neutral-grip pull-up and bench press contributed significantly to a discriminant analysis. The average squared canonical correlation was .46. The discriminant analysis predicted 7 of 9 and 6 of 10 high- and low-playing-minutes athletes, respectively.

Conclusions:

Age, training experience, upper-body strength, and aerobic fitness differentiated athlete playing minutes in international women’s rugby sevens.

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Michael J.A. Speranza, Tim J. Gabbett, David A. Greene, Rich D. Johnston, Andrew D. Townshend, and Brett O’Farrell

This study investigated the relationship between 2 tests of tackling ability, muscle strength, and power in semiprofessional rugby league players. Thirty-one players, 19 first-grade and 12 second-grade, underwent tests of muscle strength (1-repetition-maximum bench press, chin-up, and squat) and power (plyometric push-up and countermovement jump). Tackling ability was assessed via video analysis of under-and over-the-ball tackle drills. The first-grade players had significantly greater scores in both the under-the-ball (P = .03, effect size [ES] = 0.84, 95% CI 0.07–1.50) and over-the-ball tackling-ability tests (P < .001, ES =1.86, 95% CI 0.83–2.52) than the second-grade players. A large, significant relationship was found between under- and over-the-ball tackling ability (r = .55, 95% CI .24–.76, P = .001). Lower-body strength (r = .37, 95% CI .02–.64, P = .04) was moderately associated with under-the-ball tackling ability, whereas over-the-ball tackling ability was moderately associated with plyometric push-up performance (r = .39, 95% CI .04–.65, P = .03). This study found that over-the-ball tackling ability was significantly associated with under-the-ball tackling in semiprofessional rugby league players. Furthermore, it was found that, compared with the second-grade players, the first-grade players had superior tackle ability in both tackle drills. In this study it was observed that plyometric push-up peak power was significantly related to over-the-ball tackling ability and absolute lower-body strength was associated with under-the-ball tackling ability. These findings provide skill coaches and strength and conditioning staff a greater understanding of elements that contribute to effective tackling ability.

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Nicola Furlan, Mark Waldron, Kathleen Shorter, Tim J. Gabbett, John Mitchell, Edward Fitzgerald, Mark A. Osborne, and Adrian J. Gray

Purpose:

To investigate temporal variation in running intensity across and within halves and evaluate the agreement between match-analysis indices used to identify fluctuations in running intensity in rugby sevens.

Methods:

Data from a 15-Hz global positioning system (GPS) were collected from 12 elite rugby sevens players during the IRB World Sevens Series (N = 21 full games). Kinematic (eg, relative distance [RD]) and energetic (eg, metabolic power [MP]) match-analysis indices were determined from velocity–time curves and used to investigate between-halves variations. Mean MP and RD were used to identify peak 2-minute periods of play. Adjacent 2-minute periods (prepeak and postpeak) were compared with peak periods to identify changes in intensity. MP and RD were expressed relative to maximal oxygen uptake (V̇O2max) and speed at V̇O2max, respectively, and compared in their ability to describe the intensity of peak periods and their temporal occurrence.

Results:

Small to moderate reductions were present for kinematic (RD; 8.9%) and energetic (MP; 6%) indices between halves. Peak periods (RD = 130 m/min, MP =13 W/kg) were higher (P < .001) than the match average (RD = 94 m/min, MP = 9.5 W/kg) and the prepeak and postpeak periods (P < .001). RD underestimated the intensity of peak periods compared with MP (bias 16%, limits of agreement [LoA] ± 6%). Peak periods identified by RD and MP were temporally dissociated (bias 21 s, LoA ± 212 s).

Conclusions:

The findings suggest that running intensity varies between and within halves; however, the index used will influence both the magnitude and the temporal identification of peak periods.

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Nick B. Murray, Georgia M. Black, Rod J. Whiteley, Peter Gahan, Michael H. Cole, Andy Utting, and Tim J. Gabbett

Purpose:

Throwing loads are known to be closely related to injury risk. However, for logistic reasons, typically only pitchers have their throws counted, and then only during innings. Accordingly, all other throws made are not counted, so estimates of throws made by players may be inaccurately recorded and underreported. A potential solution to this is the use of wearable microtechnology to automatically detect, quantify, and report pitch counts in baseball. This study investigated the accuracy of detection of baseball pitching and throwing in both practice and competition using a commercially available wearable microtechnology unit.

Methods:

Seventeen elite youth baseball players (mean ± SD age 16.5 ± 0.8 y, height 184.1 ± 5.5 cm, mass 78.3 ± 7.7 kg) participated in this study. Participants performed pitching, fielding, and throwing during practice and competition while wearing a microtechnology unit. Sensitivity and specificity of a pitching and throwing algorithm were determined by comparing automatic measures (ie, microtechnology unit) with direct measures (ie, manually recorded pitching counts).

Results:

The pitching and throwing algorithm was sensitive during both practice (100%) and competition (100%). Specificity was poorer during both practice (79.8%) and competition (74.4%).

Conclusions:

These findings demonstrate that the microtechnology unit is sensitive to detect pitching and throwing events, but further development of the pitching algorithm is required to accurately and consistently quantify throwing loads using microtechnology.

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Jake Schuster, Dan Howells, Julien Robineau, Anthony Couderc, Alex Natera, Nick Lumley, Tim J. Gabbett, and Nick Winkelman

Rugby sevens, a sport new to the Olympics, features high-intensity intermittent running and contact efforts over short match durations, normally 6 times across 2 to 3 d in a tournament format. Elite rugby sevens seasons often include over a dozen competitive tournaments over less than 9 months, demanding deliberate and careful training-stress balance and workload management alongside development of the necessary physical qualities required for competition. Focus on running and repeated power skills, strength, and match-specific conditioning capacities is advised. Partial taper approaches in combination with high-speed running (>5 m/s from GPS measures) before and between tournaments in succession may reduce injury rates and enhance performance. In a sport with substantial long-haul intercontinental travel and repetitive chronic load demands, management of logistics including nutrition and recovery is inclusive of the formula for success in the physical preparation of elite rugby sevens athletes.

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Pitre C. Bourdon, Marco Cardinale, Andrew Murray, Paul Gastin, Michael Kellmann, Matthew C. Varley, Tim J. Gabbett, Aaron J. Coutts, Darren J. Burgess, Warren Gregson, and N. Timothy Cable

Monitoring the load placed on athletes in both training and competition has become a very hot topic in sport science. Both scientists and coaches routinely monitor training loads using multidisciplinary approaches, and the pursuit of the best methodologies to capture and interpret data has produced an exponential increase in empirical and applied research. Indeed, the field has developed with such speed in recent years that it has given rise to industries aimed at developing new and novel paradigms to allow us to precisely quantify the internal and external loads placed on athletes and to help protect them from injury and ill health. In February 2016, a conference on “Monitoring Athlete Training Loads—The Hows and the Whys” was convened in Doha, Qatar, which brought together experts from around the world to share their applied research and contemporary practices in this rapidly growing field and also to investigate where it may branch to in the future. This consensus statement brings together the key findings and recommendations from this conference in a shared conceptual framework for use by coaches, sport-science and -medicine staff, and other related professionals who have an interest in monitoring athlete training loads and serves to provide an outline on what athlete-load monitoring is and how it is being applied in research and practice, why load monitoring is important and what the underlying rationale and prospective goals of monitoring are, and where athlete-load monitoring is heading in the future.