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Dean J. McNamara, Tim J. Gabbett, Paul Chapman, Geraldine Naughton, and Patrick Farhart

Purpose:

The use of wearable microtechnology to monitor the external load of fast bowling is challenged by the inherent variability of bowling techniques between bowlers. This study assessed the between-bowlers variability in PlayerLoad, bowling velocity, and performance execution across repeated bowling spells.

Methods:

Seven national-level fast bowlers completed two 6-over bowling spells at a batter during a competitive training session. Key dependent variables were PlayerLoad calculated with a MinimaxX microtechnology unit, ball velocity, and bowling execution based on a predetermined bowling strategy for each ball bowled. The between-bowlers coefficient of variation (CV), repeated-measures ANOVA, and smallest worthwhile change were calculated over the 2 repeated 6-over bowling spells and explored across 12-over, 6-over, and 3-over bowling segments.

Results:

From the sum of 6 consecutive balls, the between-bowlers CV for relative peak PlayerLoad was 1.2% over the 12-over bowling spell (P = .15). During this 12-over period, bowling-execution (P = .43) scores and ball-velocity (P = .31) CVs were calculated as 46.0% and 0.4%, respectively.

Conclusions:

PlayerLoad was found to be stable across the repeated bowling spells in the fast-bowling cohort. Measures of variability and change across the repeated bowling spells were consistent with the performance measure of ball velocity. The stability of PlayerLoad improved when assessed relative to the individual’s peak PlayerLoad. Only bowling-execution measures were found to have high variability across the repeated bowling spells. PlayerLoad provides a stable measure of external workload between fast bowlers.

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Billy T. Hulin, Tim J. Gabbett, Nathan J. Pickworth, Rich D. Johnston, and David G. Jenkins

Purpose: To examine relationships among physical performance, workload, and injury risk in professional rugby league players. Methods: Maximal-effort (n = 112) and submaximal (n = 1084) running performances of 45 players were recorded from 1 club over 2 consecutive seasons. Poorer and better submaximal running performance was determined by higher and lower exercise heart rates, respectively. Exponentially weighted moving averages and daily rolling averages were used to assess microtechnology-derived acute and chronic field-based workloads. The associations among within-individual submaximal running performance, workload, and noncontact lower-limb injury were then investigated. Results: The injury risk associated with poorer submaximal performance was “likely” greater than stable (relative risk = 1.8; 90% confidence interval, 0.9–3.7) and better submaximal performance (relative risk = 2.0; 90% confidence interval, 0.9–4.4). Compared with greater submaximal performance, poorer performance was associated with lower chronic workloads (effect size [d] = 0.82 [0.13], large) and higher acute:chronic workload ratios (d = 0.49 [0.14], small). Chronic workload demonstrated a “nearly perfect” positive relationship with maximal-effort running performance (exponentially weighted moving average, R 2 = .91 [.15]; rolling average, R 2 = .91 [.14]). At acute:chronic workload ratios >1.9, no differences in injury risk were found between rolling average and exponentially weighted moving average methods (relative risk = 1.1; 90% confidence interval, 0.3–3.8; unclear). Conclusions: Reductions in submaximal running performance are related with low chronic workloads, high acute:chronic workload ratios, and increased injury risk. These findings demonstrate that a submaximal running assessment can be used to provide information on physical performance and injury risk in professional rugby league players.

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Craig Twist, Jamie Highton, Mark Waldron, Emma Edwards, Damien Austin, and Tim J. Gabbett

Purpose:

This study compared the movement demands of players competing in matches from the elite Australian and European rugby league competitions.

Methods:

Global positioning system devices were used to measure 192 performances of forwards, adjustables, and outside backs during National Rugby League (NRL; n = 88) and European Super League (SL; n = 104) matches. Total and relative distances covered overall and at low (0–3.5 m/s), moderate (3.6–5 m/s), and high (>5 m/s) speeds were measured alongside changes in movement variables across the early, middle, and late phases of the season.

Results:

The relative distance covered in SL matches (95.8 ± 18.6 m/min) was significantly greater (P < .05) than in NRL matches (90.2 ± 8.3 m/min). Relative low-speed activity (70.3 ± 4.9 m/min vs 75.5 ± 18.9 m/min) and moderate-speed running (12.5 ± 3.3 m m/min vs 14.2 ± 3.8 m/min) were highest (P < .05) in the SL matches, and relative high-speed distance was greater (P < .05) during NRL matches (7.8 ± 2.1 m/min vs 6.1 ± 1.7 m/min).

Conclusions:

NRL players have better maintenance of high-speed running between the first and second halves of matches and perform less low- and moderate-speed activity, indicating that the NRL provides a higher standard of rugby league competition than the SL.

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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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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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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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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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Peter Le Rossignol, Tim J. Gabbett, Dan Comerford, and Warren R. Stanton

Purpose:

To investigate the relationship between selected physical capacities and repeated-sprint performance of Australian Football League (AFL) players and to determine which physical capacities contributed to being selected for the first competition game.

Methods:

Sum of skinfolds, 40-m sprint (with 10-, 20-, 30-, and 40-m splits), repeated-sprint ability (6 × 30-m sprints), and 3-km-run time were measured during the preseason in 20 AFL players. The physical qualities of players selected to play the first match of the season and those not selected were compared. Pearson correlation coefficients were used to determine the relationship among variables, and a regression analysis identified variables significantly related to repeated-sprint performance.

Results:

In the regression analysis, maximum velocity was the best predictor of repeated-sprint time, with 3-km-run time also contributing significantly to the predictive model. Sum of skinfolds was significantly correlated with 10-m (r = .61, P < .01) and 30-m (r = .53, P < .05) sprint times. A 2.6% ± 2.1% difference in repeated-sprint time (P < .05, ES = 0.88 ± 0.72) was observed between those selected (25.26 ± 0.55 s) and not selected (25.82 ± 0.80 s) for the first game of the season.

Conclusions:

The findings indicate that maximum-velocity training using intervals of 30–40 m may contribute more to improving repeated-sprint performance in AFL players than short 10- to 20-m intervals from standing starts. Further research is warranted to establish the relative importance of endurance training for improving repeated-sprint performance in AFL football.

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Kieran P. Young, G. Gregory Haff, Robert U. Newton, Tim J. Gabbett, and Jeremy M. Sheppard

Purpose:

To evaluate whether the dynamic strength index (DSI: ballistic peak force/isometric peak force) could be effectively used to guide specific training interventions and detect training-induced changes in maximal and ballistic strength.

Methods:

Twenty-four elite male athletes were assessed in the isometric bench press and a 45% 1-repetition-maximum (1RM) ballistic bench throw using a force plate and linear position transducer. The DSI was calculated using the peak force values obtained during the ballistic bench throw and isometric bench press. Athletes were then allocated into 2 groups as matched pairs based on their DSI and strength in the 1RM bench press. Over the 5 wk of training, athletes performed either high-load (80–100% 1RM) bench press or moderate-load (40–55% 1RM) ballistic bench throws.

Results:

The DSI was sensitive to disparate training methods, with the bench-press group increasing isometric bench-press peak force (P = .035, 91% likely), and the ballistic-bench-throw group increasing bench-throw peak force to a greater extent (P ≤ .001, 83% likely). A significant increase (P ≤ .001, 93% likely) in the DSI was observed for both groups.

Conclusions:

The DSI can be used to guide specific training interventions and can detect training-induced changes in isometric bench-press and ballistic bench-throw peak force over periods as short as 5 wk.

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Billy T. Hulin, Tim J. Gabbett, Rich D. Johnston, and David G. Jenkins

Purpose: To determine (1) how change-of-direction (COD) workloads influence PlayerLoad (PL) variables when controlling total distance covered and (2) relationships among collision workloads and PL variables during rugby league match play. Methods: Participants completed 3 protocols (crossover design) consisting of 10 repetitions of a 60-m effort in 15 s. The difference between protocols was the COD demands required to complete 1 repetition: no COD (straight line), 1° × 180° COD, or 3° × 180° COD. During rugby league matches, relationships among collision workloads, triaxial vector-magnitude PlayerLoad (PLVM), anteroposterior + mediolateral PL (PL2D), and PLVM accumulated at locomotor velocities below 2 m·s−1 (ie, PLSLOW) were examined using Pearson correlations (r) with coefficients of determination (R 2). Results: Comparing 3° × 180° COD to straight-line drills, PLVM·min−1 (d = 1.50 ± 0.49, large, likelihood = 100%, almost certainly), PL2D·min−1 (d = 1.38 ± 0.53, large, likelihood = 100%, almost certainly), and PLSLOW·min−1 (d = 1.69 ± 0.40, large, likelihood = 100%, almost certainly) were greater. Collisions per minute demonstrated a distinct (ie, R 2 < .50) relationship from PLVM·min−1 (R 2 = .30, r = .55) and PL2D·min−1 (R 2 = .37, r = .61). Total distance per minute demonstrated a very large relationship with PLVM·min−1 (R 2 = .62, r = .79) and PL2D·min−1 (R 2 = .57, r = .76). Conclusions: PL variables demonstrate (1) large increases as COD demands intensify, (2) separate relationships from collision workloads, and (3) moderate to very large relationships with total distance during match play. PL variables should be used with caution to measure collision workloads in team sport.