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Influence of Number of Contact Efforts on Running Performance During Game-Based Activities

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

Purpose:

To determine the influence the number of contact efforts during a single bout has on running intensity during game-based activities and assess relationships between physical qualities and distances covered in each game.

Methods:

Eighteen semiprofessional rugby league players (age 23.6 ± 2.8 y) competed in 3 off-side small-sided games (2 × 10-min halves) with a contact bout performed every 2 min. The rules of each game were identical except for the number of contact efforts performed in each bout. Players performed 1, 2, or 3 × 5-s wrestles in the single-, double-, and triple-contact game, respectively. The movement demands (including distance covered and intensity of exercise) in each game were monitored using global positioning system units. Bench-press and back-squat 1-repetition maximum and the 30−15 Intermittent Fitness Test (30−15IFT) assessed muscle strength and high-intensity-running ability, respectively.

Results:

There was little change in distance covered during the single-contact game (ES = −0.16 to −0.61), whereas there were larger reductions in the double- (ES = −0.52 to −0.81) and triple-contact (ES = −0.50 to −1.15) games. Significant relationships (P < .05) were observed between 30–15IFT and high-speed running during the single- (r = .72) and double- (r = .75), but not triple-contact (r = .20) game.

Conclusions:

There is little change in running intensity when only single contacts are performed each bout; however, when multiple contacts are performed, greater reductions in running intensity result. In addition, high-intensity-running ability is only associated with running performance when contact demands are low.

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The Influence of Physical Fitness and Playing Standard on Pacing Strategies During a Team-Sport Tournament

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

Purpose:

To assess the influence of playing standard and physical fitness on pacing strategies during a junior team-sport tournament.

Methods:

A between-groups, repeated-measures design was used. Twenty-eight junior team-sport players (age 16.6 ± 0.5 y, body mass 79.9 ± 12.0 kg) from a high-standard and low-standard team participated in a junior rugby league tournament, competing in 5 games over 4 d (4 × 40-min and 1 × 50-min game). Players wore global positioning system (GPS) microtechnology during each game to provide information on match activity profiles. The Yo-Yo Intermittent Recovery Test (level 1) was used to assess physical fitness before the competition.

Results:

High-standard players had an initially higher pacing strategy than the low-standard players, covering greater distances at high (ES = 1.32) and moderate speed (ES = 1.41) in game 1 and moderate speed (ES = 1.55) in game 2. However, low-standard players increased their playing intensity across the competition (ES = 0.57–2.04). High-standard/high-fitness players maintained a similar playing intensity, whereas high-standard/low-fitness players reduced their playing intensities across the competition.

Conclusions:

Well-developed physical fitness allows for a higher-intensity pacing strategy that can be maintained throughout a tournament. High-standard/low-fitness players reduce playing intensity, most likely due to increased levels of fatigue as the competition progresses. Low-standard players adopt a pacing strategy that allows them to conserve energy to produce an “end spurt” in the latter games. Maximizing endurance fitness across an entire playing group will maximize playing intensity and minimize performance reductions during the latter stages of a tournament.

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Physical Demands of Match Play in Successful and Less-Successful Elite Rugby League Teams

Billy T. Hulin, Tim J. Gabbett, Simon Kearney, and Alex Corvo

Purpose:

To quantify activity profiles in approximately 5-min periods to determine if the intensity of rugby league match play changes after the most intense period of play and to determine if the intensity of activity during predefined periods of match play differ between successful and less-successful teams playing at an elite standard.

Methods:

Movement was recorded using a MinimaxX global positioning system (GPS) unit sampling at 10 Hz during 25 rugby league matches, equating to 200 GPS files. Data for each half of match play were separated into 8 equal periods. These periods represented the most intense phase of match play (peak period), the period after the most intense phase of match play (subsequent period), and the average demands of all other periods in a match (mean period). Two rugby league teams were split into a high-success and a low-success group based on their success rates throughout their season.

Results:

Compared with their less-successful counterparts, adjustables and hit-up forwards from the high-success team covered less total distance (P < .01) and less high-intensity-running distance (P < .01) and were involved in a greater number of collisions (P < .01) during the mean period of match play.

Conclusions:

Although a greater number of collisions during match play is linked with a greater rate of success, greater amounts of high-intensity running and total distance are not related to competitive success in elite rugby league. These results suggest that technical and tactical differences, rather than activity profiles, may be the distinguishing factor between successful and less-successful rugby league teams.

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The Use of Relative Speed Zones in Australian Football: Are We Really Measuring What We Think We Are?

Nick B. Murray, Tim J. Gabbett, and Andrew D. Townshend

Objectives: To examine the difference between absolute and relative workloads, injury likelihood, and the acute:chronic workload ratio (ACWR) in elite Australian football. Design: Single-cohort, observational study. Methods: Forty-five elite Australian football players from 1 club participated. Running workloads of players were tracked using Global Positioning System technology and were categorized using either (1) absolute, predefined speed thresholds or (2) relative, individualized speed thresholds. Players were divided into 3 equal groups based on maximum velocity: (1) faster, (2) moderate, or (3) slower. One- and 4-wk workloads were calculated, along with the ACWR. Injuries were recorded if they were noncontact in nature and resulted in “time loss.” Results: Faster players demonstrated a significant overestimation of very high-speed running (HSR) when compared with their relative thresholds (P = .01; effect size = −0.73). Similarly, slower players demonstrated an underestimation of high-(P = .06; effect size = 0.55) and very-high-speed (P = .01; effect size = 1.16) running when compared with their relative thresholds. For slower players, (1) greater amounts of relative very HSR had a greater risk of injury than less (relative risk [RR] = 8.30; P = .04) and (2) greater absolute high-speed chronic workloads demonstrated an increase in injury likelihood (RR = 2.28; P = .16), whereas greater relative high-speed chronic workloads offered a decrease in injury likelihood (RR = 0.33; P = .11). Faster players with a very-high-speed ACWR of >2.0 had a greater risk of injury than those between 0.49 and 0.99 for both absolute (RR = 10.31; P = .09) and relative (RR = 4.28; P = .13) workloads. Conclusions: The individualization of velocity thresholds significantly alters the amount of very HSR performed and should be considered in the prescription of training load.

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Validity of a Microsensor-Based Algorithm for Detecting Scrum Events in Rugby Union

Ryan M. Chambers, Tim J. Gabbett, and Michael H. Cole

Purpose: Commercially available microtechnology devices containing accelerometers, gyroscopes, magnetometers, and global positioning technology have been widely used to quantify the demands of rugby union. This study investigated whether data derived from wearable microsensors can be used to develop an algorithm that automatically detects scrum events in rugby union training and match play. Methods: Data were collected from 30 elite rugby players wearing a Catapult OptimEye S5 (Catapult Sports, Melbourne, Australia) microtechnology device during a series of competitive matches (n = 46) and training sessions (n = 51). A total of 97 files were required to “train” an algorithm to automatically detect scrum events using random forest machine learning. A further 310 files from training (n = 167) and match-play (n = 143) sessions were used to validate the algorithm’s performance. Results: Across all positions (front row, second row, and back row), the algorithm demonstrated good sensitivity (91%) and specificity (91%) for training and match-play events when the confidence level of the random forest was set to 50%. Generally, the algorithm had better accuracy for match-play events (93.6%) than for training events (87.6%). Conclusions: The scrum algorithm was able to accurately detect scrum events for front-row, second-row, and back-row positions. However, for optimal results, practitioners are advised to use the recommended confidence level for each position to limit false positives. Scrum algorithm detection was better with scrums involving ≥5 players and is therefore unlikely to be suitable for scrums involving 3 players (eg, rugby sevens). Additional contact- and collision-detection algorithms are required to fully quantify rugby union demands.

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Training and Competition Workloads and Fatigue Responses of Elite Junior Cricket Players

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

Purpose:

This study investigated key fatigue and workload variables of cricket fast bowlers and nonfast bowlers during a 7-wk physical-preparation period and 10-d intensified competition period.

Methods:

Twenty-six elite junior cricketers (mean ± SD age 17.7 ± 1.1 y) were classified as fast bowlers (n = 9) or nonfast bowlers (n = 17). Individual workloads were measured via global positioning system technology, and neuromuscular function (countermovement jump [relative power and flight time]), endocrine (salivary testosterone and cortisol concentrations), and perceptual well-being (soreness, mood, stress, sleep quality, and fatigue) markers were recorded.

Results:

Fast bowlers performed greater competition total distance (median [interquartile range] 7049 [3962] m vs 5062 [3694] m), including greater distances at low and high speeds, and more accelerations (40 [32] vs 19 [21]) and had a higher player load (912 [481] arbitrary units vs 697 [424] arbitrary units) than nonfast bowlers. Cortisol concentrations were higher in the physical-preparation (mean ± 90% confidence intervals, % likelihood; d = –0.88 ± 0.39, 100%) and competition phases (d = –0.39 ± 0.30, 85%), and testosterone concentrations, lower (d = 0.56 ± 0.29, 98%), in the competition phase in fast bowlers. Perceptual well-being was poorer in nonfast bowlers during competition only (d = 0.36 ± 0.22, 88%). Differences in neuromuscular function between groups were unclear during physical preparation and competition.

Conclusions:

These findings demonstrate differences in the physical demands of cricket fast bowlers and nonfast bowlers and suggest that these external workloads differentially affect the neuromuscular, endocrine, and perceptual fatigue responses of these players.

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Influence of Physical Contact on Pacing Strategies During Game-Based Activities

Rich D. Johnston, Tim J. Gabbett, Anthony J. Seibold, and David G. Jenkins

Purpose:

Repeated sprinting incorporating tackles leads to greater reductions in sprint performance than repeated sprinting alone. However, the influence of physical contact on the running demands of game-based activities is unknown. The aim of this study was to determine whether the addition of physical contact altered pacing strategies during game-based activities.

Methods:

Twenty-three elite youth rugby league players were divided into 2 groups. Group 1 played the contact game on day 1 while group 2 played the noncontact game; 72 h later they played the alternate game. Each game consisted of offside touch on a 30 × 70-m field, played over two 8-min halves. Rules were identical between games except the contact game included a 10-s wrestle bout every 50 s. Microtechnology devices were used to analyze player movements.

Results:

There were greater average reductions during the contact game for distance (25%, 38 m/min, vs 10%, 20 m/min; effect size [ES] = 1.78 ± 1.02) and low-speed distance (21%, 24 m/min, vs 0%, 2 m/s; ES = 1.38 ± 1.02) compared with the noncontact game. There were similar reductions in high-speed running (41%, 18 m/min, vs 45%, 15 m/min; ES = 0.15 ± 0.95).

Conclusions:

The addition of contact to game-based activities causes players to reduce low-speed activity in an attempt to maintain high-intensity activities. Despite this, players were unable to maintain high-speed running while performing contact efforts. Improving a player’s ability to perform contact efforts while maintaining running performance should be a focus in rugby league training.

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Relationship Between a Standardized Tackling Proficiency Test and Match-Play Tackle Performance in Semiprofessional Rugby League Players

Michael J.A. Speranza, Tim J. Gabbett, Rich D. Johnston, and Jeremy M. Sheppard

Purpose:

This study examined the relationships between tackling ability, playing position, muscle strength and power qualities, and match-play tackling performance in semiprofessional rugby league players.

Methods:

Sixteen semiprofessional rugby league players (mean ± SD age 23.8 ± 1.9 y) underwent tests for muscle strength and power. Tackling ability of the players was tested using video analysis of a standardized 1-on-1 tackling drill. After controlling for playing position, players were divided into “good tackler” or “poor tackler” groups based on the median split of the results of the 1-on-1 tackling drill. A total of 4547 tackles were analyzed from video recordings of 23 matches played throughout the season.

Results:

Maximal squat was significantly associated with tackling ability (r S = .71, P < .05) and with the proportion of dominant tackles (r S = .63, P < .01). Forwards performed more tackles (P = .013, ES = 1.49), with a lower proportion of missed tackles (P = .03, ES = 1.38) than backs. Good tacklers were involved in a larger proportion of dominant tackles and smaller proportion of missed tackles than poor tacklers.

Conclusions:

These findings demonstrate that lower-body strength contributes to more effective tackling performance during both a standardized tackling assessment and match play. Furthermore, players with good tackling ability in a proficiency test were involved in a higher proportion of dominant tackles and missed a smaller proportion of tackles during match play. These results provide further evidence of the practical utility of an off-field tackling assessment in supplying information predictive of tackling performance in competition.

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Variability of PlayerLoad, Bowling Velocity, and Performance Execution in Fast Bowlers Across Repeated Bowling Spells

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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Effect of Different Repeated-High-Intensity-Effort Bouts on Subsequent Running, Skill Performance, and Neuromuscular Function

Rich D. Johnston, Tim J. Gabbett, David G. Jenkins, and Michael J. Speranza

Purpose:

To assess the impact of different repeated-high-intensity-effort (RHIE) bouts on player activity profiles, skill involvements, and neuromuscular fatigue during small-sided games.

Participants:

22 semiprofessional rugby league players (age 24.0 ± 1.8 y, body mass 95.6 ± 7.4 kg).

Methods:

During 4 testing sessions, they performed RHIE bouts that each differed in the combination of contact and running efforts, followed by a 5-min off-side small-sided game before performing a second bout of RHIE activity and another 5-min small-sided game. Global positioning system microtechnology and video recordings provided information on activity profiles and skill involvements. A countermovement jump and a plyometric push-up assessed changes in lower- and upper-body neuromuscular function after each session.

Results:

After running-dominant RHIE bouts, players maintained running intensities during both games. In the contact-dominant RHIE bouts, reductions in moderate-speed activity were observed from game 1 to game 2 (ES = –0.71 to –1.06). There was also moderately lower disposal efficiency across both games after contact-dominant RHIE activity compared with running-dominant activity (ES = 0.62–1.02). Greater reductions in lower-body fatigue occurred as RHIE bouts became more running dominant (ES = –0.01 to –1.36), whereas upper-body fatigue increased as RHIE bouts became more contact dominant (ES = –0.07 to –1.55).

Conclusions:

Physical contact causes reductions in running intensity and the quality of skill involvements during game-based activities. In addition, the neuromuscular fatigue experienced by players is specific to the activities performed.