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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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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.

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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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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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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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Georgia M. Black, Tim J. Gabbett, Richard D. Johnston, Geraldine Naughton, Michael H. Cole, and Brian Dawson

Purpose: With female Australian football (AF) gaining popularity, understanding match demands is becoming increasingly important. The aim of this study was to compare running performances of rotated and whole-quarter state-level female AF players during match quarters. Methods : Twenty-two state-level female AF midfielders wore Global Positioning System units during 14 games to evaluate activity profiles. The Yo-Yo Intermittent Recovery Test Level 1 (Yo-Yo IR1) was used as a measure of high-intensity running ability. Data were categorized into whole quarter, rotation bout 1, and rotation bout 2 before being further divided into quartiles. Players were separated into high- or low-Yo-Yo IR1 groups using a median split based on their Yo-Yo IR1 performance. Short (4–6 min), moderate (6–12 min), and long (12–18 min) on-field bout activity profiles were compared with whole-quarter players. Results: High Yo-Yo IR1 performance allowed players to cover greater relative distances (ES = 0.57–0.88) and high-speed distances (ES = 0.57–0.86) during rotations. No differences were reported between Yo-Yo IR1 groups when players were required to play whole quarters (ES ≤ 0.26, likelihood ≤64%). Players who were on field for short to moderate durations exhibited greater activity profiles than whole-quarter players. Conclusions: Superior high-speed running ability results in a greater activity profile than for players who possess lower high-speed running ability. The findings also highlight the importance of short to moderate (4–12 min) rotation periods and may be used to increase high-intensity running performance within quarters in female AF players.

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Georgia M. Black, Tim J. Gabbett, Rich D. Johnston, Michael H. Cole, Geraldine Naughton, and Brian Dawson

Purpose: The transition of female Australian football (AF) players from amateur to semielite competitions has the potential for athletes to be underprepared for match play. To gain an understanding of the match demands of female football, the aims of this study were to highlight the physical qualities that discriminate selected and nonselected female AF players, investigate activity profiles of female AF players, and gain an understanding of the influence of physical qualities on performance in female AF Methods: Twenty-two female AF state academy players (mean [SD]: age = 23.2 [4.5] y) and 27 nonselected players (mean [SD]: age = 23.4 [4.9] y) completed a Yo-Yo intermittent recovery test level 1, countermovement jump, and 30-m sprint tests were completed prior to the competitive season. During 14 matches, players wore global positioning system units to describe the running demands of match play. Results: Selected players were faster over 30 m (ES = 0.57; P = .04) and covered greater distances on the Yo-Yo IR1 (ES = 1.09; P < .001). Selected midfielders spent greater time on the field and covered greater total distances (ES = 0.73–0.85; P < .01). Players faster over 5 m (r = −.612) and 30 m (r = −.807) and who performed better on the Yo-Yo IR1 (r = .489) covered greater high-speed distances during match play. Conclusions: An emphasis should be placed on the development of physical fitness in this playing group to ensure optimal preparation for the national competition.

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Paula B. Debien, Thiago F. Timoteo, Tim J. Gabbett, and Maurício G. Bara Filho

Purpose: This study described and analyzed practices and perceptions of rhythmic gymnastics coaches, medical staff, and athletes on training-load management. Methods: Online surveys were distributed among professionals and gymnasts involved in rhythmic gymnastics training across the world. One hundred (50 coaches, 12 medical staff, and 38 gymnasts) participants from 25 different countries completed the surveys. Results: Respondents stated using coaches’ perception on a daily basis as a method of monitoring external (57%) and internal (58%) load, recovery/fatigue (52%), and performance (64%). Variables and methods (eg, wearable devices, athlete self-reported measures, session rating of perceived exertion), and metrics (eg, acute and chronic load) commonly reported in the training-load literature and other sports were not frequently used in rhythmic gymnastics. The majority of coaches (60.3% [17%]) perceived that maladaptation rarely or never occurred. Medical staff involvement in sharing and discussing training-load information was limited, and they perceived that the measurement of athletes’ recovery/fatigue was poor. Gymnasts noted good quality in relation to the measurement of performance. Most participants (≥85%) believed that a specific training-load management model for rhythmic gymnastics could be very or extremely effective. Conclusions: In conclusion, rhythmic gymnastics coaches’ perception is the most commonly used strategy to monitor load, recovery/fatigue, and performance; although, this could be a limited method to guarantee effective training-load management in this sport.

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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.

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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.