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Robert J. Aughey

Global positioning system (GPS) technology was made possible after the invention of the atomic clock. The first suggestion that GPS could be used to assess the physical activity of humans followed some 40 y later. There was a rapid uptake of GPS technology, with the literature concentrating on validation studies and the measurement of steady-state movement. The first attempts were made to validate GPS for field sport applications in 2006. While GPS has been validated for applications for team sports, some doubts continue to exist on the appropriateness of GPS for measuring short high-velocity movements. Thus, GPS has been applied extensively in Australian football, cricket, hockey, rugby union and league, and soccer. There is extensive information on the activity profile of athletes from field sports in the literature stemming from GPS, and this includes total distance covered by players and distance in velocity bands. Global positioning systems have also been applied to detect fatigue in matches, identify periods of most intense play, different activity profiles by position, competition level, and sport. More recent research has integrated GPS data with the physical capacity or fitness test score of athletes, game-specific tasks, or tactical or strategic information. The future of GPS analysis will involve further miniaturization of devices, longer battery life, and integration of other inertial sensor data to more effectively quantify the effort of athletes.

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Robert J. Aughey

Background:

Australian football (AF) is a highly intermittent sport, requiring athletes to accelerate hundreds of times with repeated bouts of high-intensity running (HIR). Players aim to be in peak physical condition for finals, with anecdotal evidence of increased speed and pressure of these games.

Purpose:

However, no data exists on the running demands of finals games, and therefore the aim of this study was to compare the running demands of finals to regular season games with matched players and opponents.

Methods:

Player movement was recorded by GPS at 5 Hz and expressed per period of the match (rotation), for total distance, high-intensity running (HIR, 4.17-10.00 m·s-1) and maximal accelerations (2.78-10.00 m·s–2). All data was compared for regular season and finals games and the magnitude of effects was analyzed with the effect size (ES) statistic and expressed with confidence intervals.

Results:

Each of the total distance (11%; ES: 0.78 ± 0.30), high-intensity running distance (9%; ES: 0.29 ± 0.25) and number of maximal accelerations (97%; ES: 1.30 ± 0.20) increased in finals games. The largest percentage increases in maximal accelerations occurred from a commencement velocity of between 3–4 (47%; ES: 0.56 ± 0.21) and 4–5 m·s-1 (51%; ES: 0.72 ± 0.26), and with <19 s between accelerations (53%; ES: 0.63 ± 0.27).

Conclusion:

Elite AF players nearly double the number of maximal accelerations in finals compared with regular season games. This large increase is superimposed on requirements to cover a greater total distance and spend more time at high velocity during finals games. Players can be effectively conditioned to cope with these increased demands, even during a long competitive season.

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Robert J. Aughey

Previous research has suggested elite Australian footballers undertake pacing strategies to preserve high intensity activity later in matches. However, this research used GPS with slow sample rates, did not express performance relative to minutes played during games and used lowly ranked players.

Methods:

Therefore in this study movement was recorded by GPS at 5 Hz. Running performance was expressed per period of the match (rotation) divided into low-intensity activity (LIA, 0.10 to 4.17 m⋅s–1); high-intensity running (HIR, 4.17 to 10.00 m⋅s–1) and maximal accelerations (2.78 to 10.00 m⋅s–2). All data were expressed relative to the first period of play in the match and the magnitude of effects was analyzed with the effect size (ES) statistic and expressed with confidence intervals.

Results:

The total and LIA distance covered by players did not change by a practically important magnitude during games (ES< 0.20). High intensity running was reduced in both rotations of the second quarter, Q3R2 and both rotations of the fourth quarter (ES -0.30 ± 0.14; -0.42 ± 0.14; -0.30 ± 0.14; -0.42 ± 0.14; and -0.48 ± 0.15 respectively). Maximal acceleration performance was reduced in Q1R2, and each rotation of the second half of matches.

Conclusion:

When expressed per minute of game time played, total distance and low intensity activity distance are not reduced by a practically important magnitude in AF players during a match. These data are therefore inconsistent with the concept of team sport players pacing their effort during matches. However, both high intensity running and maximal accelerations are reduced later in games, indicative of significant fatigue in players.

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Luke J. Boyd, Kevin Ball and Robert J. Aughey

Purpose:

To assess the reliability of triaxial accelerometers as a measure of physical activity in team sports.

Methods:

Eight accelerometers (MinimaxX 2.0, Catapult, Australia) were attached to a hydraulic universal testing machine (Instron 8501) and oscillated over two protocols (0.5 g and 3.0 g) to assess within- and between-device reliability. A static assessment was also conducted. Secondly, 10 players were instrumented with two accelerometers during Australian football matches. The vector magnitude was calculated, expressed as Player load and assessed for reliability using typical error (TE) ± 90% confidence intervals (CI), and expressed as a coefficient of variation (CV%). The smallest worthwhile difference (SWD) in Player load was calculated to determine if the device was capable of detecting differences in physical activity.

Results:

Laboratory: Within- (Dynamic: CV 0.91 to 1.05%; Static: CV 1.01%) and between-device (Dynamic: CV 1.02 to 1.04%; Static: CV 1.10%) reliability was acceptable across each test. Field: The between-device reliability of accelerometers during Australian football matches was also acceptable (CV 1.9%). The SWD was 5.88%.

Conclusions:

The reliability of the MinimaxX accelerometer is acceptable both within and between devices under controlled laboratory conditions, and between devices during field testing. MinimaxX accelerometers can be confidently utilized as a reliable tool to measure physical activity in team sports across multiple players and repeated bouts of activity. The noise (CV%) of Player load was lower than the signal (SWD), suggesting that accelerometers can detect changes or differences in physical activity during Australian football.

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Luke J. Boyd, Kevin Ball and Robert J. Aughey

Purpose:

To describe the external load of Australian football matches and training using accelerometers.

Methods:

Nineteen elite and 21 subelite Australian footballers wore accelerometers during matches and training. Accelerometer data were expressed in 2 ways: from all 3 axes (player load; PL) and from all axes when velocity was below 2 m/s (PLSLOW). Differences were determined between 4 playing positions (midfielders, nomadics, deeps, and ruckmen), 2 playing levels (elite and subelite), and matches and training using percentage change and effect size with 90% confidence intervals.

Results:

In the elite group, midfielders recorded higher PL than nomadics and deeps did (8.8%, 0.59 ± 0.24; 34.2%, 1.83 ± 0.39 respectively), and ruckmen were higher than deeps (37.2%, 1.27 ± 0.51). Elite midfielders, nomadics, and ruckmen recorded higher PLSLOW than deeps (13.5%, 0.65 ± 0.37; 11.7%, 0.55 ± 0.36; and 19.5%, 0.83 ± 0.50, respectively). Subelite midfielders were higher than nomadics, deeps, and ruckmen (14.0%, 1.08 ± 0.30; 31.7%, 2.61 ± 0.42; and 19.9%, 0.81 ± 0.55, respectively), and nomadics and ruckmen were higher than deeps for PL (20.6%, 1.45 ± 0.38; and 17.4%, 0.57 ± 0.55, respectively). Elite midfielders, nomadics, and ruckmen recorded higher PL (7.8%, 0.59 ± 0.29; 12.9%, 0.89 ± 0.25; and 18.0%, 0.67 ± 0.59, respectively) and PLSLOW (9.4%, 0.52 ± 0.30; 11.3%, 0.68 ± 0.25; and 14.1%, 0.84 ± 0.61, respectively) than subelite players. Small-sided games recorded the highest PL and PLSLOW and were the only training drill to equal or exceed the load from matches across positions and playing levels.

Conclusion:

PL differed between positions, with midfielders the highest, and between playing levels, with elite higher. Differences between matches and training were also evident, with PL from small-sided games equivalent to or higher than matches.

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Mathew W.H. Inness, François Billaut and Robert J. Aughey

Purpose:

To determine the time course for physical-capacity adaptations to intermittent hypoxic training (IHT) in team-sport athletes and the time course for benefits remaining after IHT.

Methods:

A pre–post parallel-groups design was employed, with 21 Australian footballers assigned to IHT (n = 10) or control (CON; n = 11) matched for training load. IHT performed eleven 40-min bike sessions at 2500-m altitude over 4 wk. Yo-Yo Intermittent Recovery Test level 2 (Yo-Yo IR2) was performed before; after 3, 6, and 11 IHT sessions; and 30 and 44 d after IHT. Repeated time trials (2- and 1-km TTs, with 5 min rest) were performed before, after, and 3 wk after IHT. Hemoglobin mass (Hbmass) was measured in IHT before and after 3, 6, 9, and 11 sessions.

Results:

Baseline Yo-Yo IR2 was similar between groups. After 6 sessions, the change in Yo-Yo IR2 in IHT was very likely higher than CON (27% greater change, effect size 0.77, 90% confidence limits 0.20;1.33) and likely higher 1 d after IHT (23%, 0.68, 0.05;1.30). The IHT group’s change remained likely higher than CON 30 d after IHT (24%, 0.72, 0.12;1.33) but was not meaningfully different 44 d after (12%, 0.36, –0.24;0.97). The change in 2-km TT performance between groups was not different throughout. For 1-km TT, CON improved more after IHT, but IHT maintained performance better after 3 wk. Hbmass was higher after IHT (2.7%, 0.40, –0.40;1.19).

Conclusion:

Short-duration IHT increased Yo-Yo IR2 compared with training-load-matched controls in 2 wk. An additional 2 wk of IHT provided no further benefit. These changes remained until at least 30 d posttraining. IHT also protected improvement in 1-km TT.

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Matthew C. Varley, George P. Elias and Robert J. Aughey

Purpose:

To compare the peak 5-min period of high-velocity running (HiVR) during a soccer match using a predefined vs a rolling time interval.

Methods:

Player movement data were collected from 19 elite Australian soccer players over 11 competitive matches (77 individual match files) using a 5-Hz global-positioning system. Raw velocity data were analyzed to determine the period containing the greatest HiVR distance per match half and the distance covered in the subsequent epoch. Intervals were identified using either a predefined (distance covered in 5 min at every 5-min time point) or rolling (distance covered in 5 min from every time point) method. The percentage difference ± 90% confidence limits were used to determine differences between methods.

Results:

Predefined periods underestimated peak distance covered by up to 25% and overestimated the subsequent epoch by up to 31% compared with rolling periods. When the distance decrement between the peak and following period was determined, there was up to a 52% greater reduction in running performance using rolling periods than predefined ones.

Conclusions:

It is recommended that researchers use rolling as opposed to predefined periods when determining specific match intervals because they provide a more accurate representation of the HiVR distance covered. This will avoid underestimation of both match running distance and the decrement in running performance after an intense period of play. This may have practical implications for not only researchers but also staff involved in a club setting who use this reduction as evidence of transient fatigue during a match.

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Denise Jennings, Stuart Cormack, Aaron J. Coutts, Luke J. Boyd and Robert J. Aughey

Purpose:

To examine the difference in distance measured by two global positioning system (GPS) units of the same model worn by the same player while performing movements common to team sports.

Methods:

Twenty elite Australian football players completed two trials of the straight line movement (10, 20, 40 m) at four speeds (walk, jog, stride, sprint), two trials of the changes of direction (COD) courses of two different frequencies (gradual and tight), and five trials of a team sport running simulation circuit. To assess inter-unit variability for total and high intensity running (HIR) distance measured in matches, data from eight field players were collected in three Australian Hockey League (AHL) matches during the 2009 season. Each subject wore two GPS devices (MinimaxX v2.5, Catapult, Australia) that collected position data at 5 Hz for each movement and match trial. The percentage difference ±90% confidence interval (CI) was used to determine differences between units.

Results:

Differences (±90% CI) between the units ranged from 9.9 ± 4.7% to 11.9 ± 19.5% for straight line running movements and from 9.5 ± 7.2% to 10.7 ± 7.9% in the COD courses. Similar results were exhibited in the team sport circuit (11.1 ± 4.2%). Total distance (10.3 ± 6.2%) and HIR distance (10.3 ± 15.6) measured during the match play displayed similar variability.

Conclusion:

It is recommended that players wear the same GPS unit for each exercise session to reduce measurement error. The level of between-unit measurement error should be considered when comparing results from players wearing different GPS units.

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Denise Jennings, Stuart J. Cormack, Aaron J. Coutts and Robert J. Aughey

Purpose:

The purpose of this study was to investigate the influence of multiple games on exercise intensity during a world-class hockey tournament.

Methods:

15 players (mean ± SD age 27 ± 4 y, stature 179 ± 5 cm, body mass 77 ± 5 kg, and estimated VO2 64.2 ± 3.1 mL · kg−1 · min−1) competing in the Champions Trophy (CT). Global-positioning systems assessed total distance (TD), low-speed activity (LSA; 0.10–4.17 m/s), and high-speed running (HSR; >4.17 m/s) distance. Differences in movement demands (TD, LSA, HSR) between positions and matches were assessed using the effect size and percent difference ± 90% confidence intervals. Two levels of comparison were made. First, data from subsequent matches were compared with match 1, and, second, data from each match compared with a tournament average (TA).

Results:

In all matches, compared with game 1, midfielders performed less HSR distance. However, the amount of HSR did not decrease as the tournament progressed. When compared with the TA, defenders showed more variation in each match. All positions showed lower movement outputs when the team won by a large margin.

Conclusions:

It was possible for elite team-sport athletes to maintain exercise intensity when playing 6 matches in a period of 9 days, contrary to the only other investigation of this in elite male field hockey.

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Amber E. Rowell, Robert J. Aughey, Will G. Hopkins, Andrew M. Stewart and Stuart J. Cormack

Objective measures of recovery from football match play could be useful for assessing athletes’ readiness to train, if sensitive to preceding match load.

Purpose:

To identify the sensitivity of countermovement-jump (CMJ) performance and concentration of salivary testosterone and cortisol relative to elite football match load.

Methods:

CMJ performance and salivary hormones were measured in 18 elite football players before (27, 1 h) and after (0.5, 18, 42, 66, 90 h) 3 consecutive matches. Match load was determined via accelerometer-derived PlayerLoad and divided into tertiles. Sensitivity of CMJ performance and hormone concentrations to match load was quantified with t statistics and magnitude-based inferences (change in mean as % ± 90% confidence interval) derived with a linear mixed model.

Results:

Jump height was reduced in medium and high load at 0.5 h (10% ± 7% and 16% ± 8%) and 18 h (7% ± 4% and 9% ± 5%) postmatch. There was a 12% ± 7% reduction in ratio of flight time to contraction time (FT:CT) in high load at 0.5 h post, with reductions in medium and high load at 18 h. Reductions in FT:CT persisted at later postmatch time points than changes in jump height. Increased cortisol (range 55–165%) and testosterone (range 17–20%) were observed in all match loads at 0.5 h post, with individual variability thereafter.

Conclusions:

Measures of CMJ performance and hormonal concentrations were sensitive to levels of A League football match load. Although jump height was reduced immediately postmatch, FT:CT provided a more sensitive measure of recovery. Football match play induces an acute hormonal response with substantial individual variability thereafter.