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Pradeep Y. Ramulu, Emilie S. Chan, Tara L. Loyd, Luigi Ferrucci and David S. Friedman

Background:

Measuring physical at home and away from home is essential for assessing health and well-being, and could help design interventions to increase physical activity. Here, we describe how physical activity at home and away from home can be quantified by combining information from cellular network–based tracking devices and accelerometers.

Methods:

Thirty-five working adults wore a cellular network–based tracking device and an accelerometer for 6 consecutive days and logged their travel away from home. Performance of the tracking device was determined using the travel log for reference. Tracking device and accelerometer data were merged to compare physical activity at home and away from home.

Results:

The tracking device detected 98.6% of all away-from-home excursions, accurately measured time away from home and demonstrated few prolonged signal drop-out periods. Most physical activity took place away from home on weekdays, but not on weekends. Subjects were more physically active per unit of time while away from home, particularly on weekends.

Conclusions:

Cellular network–based tracking devices represent an alternative to global positioning systems for tracking location, and provide information easily integrated with accelerometers to determine where physical activity takes place. Promoting greater time spent away from home may increase physical activity.

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James J. Malone, Ric Lovell, Matthew C. Varley and Aaron J. Coutts

Athlete-tracking devices that include global positioning system (GPS) and microelectrical mechanical system (MEMS) components are now commonplace in sport research and practice. These devices provide large amounts of data that are used to inform decision making on athlete training and performance. However, the data obtained from these devices are often provided without clear explanation of how these metrics are obtained. At present, there is no clear consensus regarding how these data should be handled and reported in a sport context. Therefore, the aim of this review was to examine the factors that affect the data produced by these athlete-tracking devices and to provide guidelines for collecting, processing, and reporting of data. Many factors including device sampling rate, positioning and fitting of devices, satellite signal, and data-filtering methods can affect the measures obtained from GPS and MEMS devices. Therefore researchers are encouraged to report device brand/model, sampling frequency, number of satellites, horizontal dilution of precision, and software/firmware versions in any published research. In addition, details of inclusion/exclusion criteria for data obtained from these devices are also recommended. Considerations for the application of speed zones to evaluate the magnitude and distribution of different locomotor activities recorded by GPS are also presented, alongside recommendations for both industry practice and future research directions. Through a standard approach to data collection and procedure reporting, researchers and practitioners will be able to make more confident comparisons from their data, which will improve the understanding and impact these devices can have on athlete performance.

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Jason D. Vescovi

The aim of this study was to examine the impact of maximum sprint speed on peak and mean sprint speed during youth female field hockey matches. Two high-level female field hockey teams (U-17, n = 24, and U-21, n = 20) were monitored during a 4-game international test series using global position system technology and tested for maximum sprint speed. Dependent variables were compared using a 3-factor ANOVA (age group, position, and speed classification); effect sizes (Cohen d) and confidence limits were also calculated. Maximum sprint speed was similar between age groups and positions, with faster players having greater speed than slower players (29.3 ± 0.4 vs 27.2 ± 1.1 km/h). Overall, peak match speed in youth female field hockey players reaches approximately 90% of maximum sprint speed. Absolute peak match speed and mean sprint speed during matches were similar among the age groups (except match 1) and positions (except match 2); however, peak match speed was greater for faster players in matches 3 and 4. No differences were observed in the relative proportion for mean sprint speeds for age groups or positions, but slower players consistently displayed similar relative mean sprint speeds by using a greater proportion of their maximum sprint speed.

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Helen J. Moore, Catherine A. Nixon, Amelia A. Lake, Wayne Douthwaite, Claire L. O’Malley, Claire L. Pedley, Carolyn D. Summerbell and Ashley C. Routen

Background:

Evidence suggests that many contemporary urban environments do not support healthy lifestyle choices and are implicated in the obesity pandemic. Middlesbrough, in the northeast of England is one such environment and a prime target for investigation.

Methods:

To measure physical activity (PA) levels in a sample of 28 adolescents (aged 11 to 14 years) and describe the environmental context of their activity and explore where they are most and least active over a 7-day period, accelerometry and Global Positioning System (GPS) technology were used. Twenty-five of these participants also took part in focus groups about their experiences and perceptions of PA engagement.

Results:

Findings indicated that all participants were relatively inactive throughout the observed period although bouts of moderate-vigorous physical activity (MVPA) were identified in 4 contexts: school, home, street, and rural/urban green spaces, with MVPA levels highest in the school setting. Providing access to local facilities and services (such as leisure centers) is not in itself sufficient to engage adolescents in MVPA.

Conclusion:

Factors influencing engagement in MVPA were identified within and across contexts, including ‘time’ as both a facilitator and barrier, perceptions of ‘gendered’ PA, and the social influences of peer groups and family members.

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Carl Petersen, David Pyne, Marc Portus and Brian Dawson

Purpose:

The validity and reliability of three commercial global positioning system (GPS) units (MinimaxX, Catapult, Australia; SPI-10, SPI-Pro, GPSports, Australia) were quantified.

Methods:

Twenty trials of cricket-specific locomotion patterns and distances (walking 8800 m, jogging 2400 m, running 1200 m, striding 600 m, sprinting 20- to 40-m intervals, and run-a-three) were compared against criterion measures (400-m athletic track, electronic timing). Validity was quantified with the standard error of the estimate (SEE) and reliability estimated using typical error expressed as a coefficient of variation.

Results:

The validity (mean ± 90% confidence limits) for locomotion patterns walking to striding ranged from 0.4 ± 0.1 to 3.8 ± 1.4%, whereas for sprinting distances over 20 to 40 m including run-a-three (approx. 50 m) the SEE ranged from 2.6 ± 1.0 to 23.8 ± 8.8%. The reliability (expressed as mean [90% confidence limits]) of estimating distance traveled by walking to striding ranged from 0.3 (0.2 to 0.4) to 2.9% (2.3 to 4.0). Similarly, mean reliability of estimating different sprinting distances over 20 to 40 m ranged from 2.0 (1.6 to 2.8) to 30.0% (23.2 to 43.3).

Conclusions:

The accuracy and bias was dependent on the GPS brand employed. Commercially available GPS units have acceptable validity and reliability for estimating longer distances (600–8800 m) in walking to striding, but require further development for shorter cricket-specifc sprinting distances.

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Jason C. Tee, Mike I. Lambert and Yoga Coopoo

Purpose:

In team sports, fatigue is manifested by a self-regulated decrease in movement distance and intensity. There is currently limited information on the effect of fatigue on movement patterns in rugby union match play, particularly for players in different position groups (backs vs forwards). This study investigated the effect of different match periods on movement patterns of professional rugby union players.

Methods:

Global positioning system (GPS) data were collected from 46 professional match participations to determine temporal effects on movement patterns.

Results:

Total relative distance (m/min) was decreased in the 2nd half for both forwards (–13%, ±8%, ES = very likely large) and backs (–9%, ±7%, ES = very likely large). A larger reduction in high-intensity-running distance in the 2nd half was observed for forwards (–27%, ±16%, ES = very likely medium) than for backs (–10%, ±15%; ES = unclear). Similar patterns were observed for sprint (>6 m/s) frequency (forwards –29%, ±29%, ES = likely small vs backs –13% ±18%, ES = possibly small) and acceleration (>2.75 m/s2) frequency (forwards –27%, ±24%, ES = likely medium vs backs –5%, ±46%, ES = unclear). Analysis of 1st- and 2nd-half quartiles revealed differing pacing strategies for forwards and backs. Forwards display a “slow-positive” pacing strategy, while the pacing strategy of backs is “flat.”

Conclusions:

Forwards suffered progressively greater performance decrements over the course of the match, while backs were able to maintain performance intensity. These findings reflect differing physical demands, notably contact and running loads, of players in different positions.

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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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Jace A. Delaney, Heidi R. Thornton, John F. Pryor, Andrew M. Stewart, Ben J. Dascombe and Grant M. Duthie

Purpose:

To quantify the duration and position-specific peak running intensities of international rugby union for the prescription and monitoring of specific training methodologies.

Methods:

Global positioning systems (GPS) were used to assess the activity profile of 67 elite-level rugby union players from 2 nations across 33 international matches. A moving-average approach was used to identify the peak relative distance (m/min), average acceleration/deceleration (AveAcc; m/s2), and average metabolic power (Pmet) for a range of durations (1–10 min). Differences between positions and durations were described using a magnitude-based network.

Results:

Peak running intensity increased as the length of the moving average decreased. There were likely small to moderate increases in relative distance and AveAcc for outside backs, halfbacks, and loose forwards compared with the tight 5 group across all moving-average durations (effect size [ES] = 0.27–1.00). Pmet demands were at least likely greater for outside backs and halfbacks than for the tight 5 (ES = 0.86–0.99). Halfbacks demonstrated the greatest relative distance and Pmet outputs but were similar to outside backs and loose forwards in AveAcc demands.

Conclusions:

The current study has presented a framework to describe the peak running intensities achieved during international rugby competition by position, which are considerably higher than previously reported whole-period averages. These data provide further knowledge of the peak activity profiles of international rugby competition, and this information can be used to assist coaches and practitioners in adequately preparing athletes for the most demanding periods of play.

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Carl Petersen, David B. Pyne, Marc R. Portus, Stuart Karppinen and Brian Dawson

Purpose:

The time-motion characteristics and the within-athlete variability in movement patterns were quantified for the same male fast bowler playing One Day International (ODI) cricket matches (n = 12).

Methods:

A number of different time motion characteristics were monitored using a portable 5-Hz global positioning system (GPS) unit (Catapult, Melbourne, Australia).

Results:

The bowler’s mean workload per ODI was 8 ± 2 overs (mean ± SD). He covered a total distance of 15.9 ± 2.5 km per game; 12 ± 3% or 1.9 ± 0.2 km was striding (0.8 ± 0.2 km) or sprinting (1.1 ± 0.2 km), whereas 10.9 ± 2.1 km was spent walking. One high-intensity (running, striding, or sprinting) repetition (HIR) occurred every 68 ± 12 s, and the average duration of a HI effort was 2.7 ± 0.1 s. The player also completed 66 ± 11 sprints per game; mean sprint distance was 18 ± 3 m and maximum sprinting speed 8.3 ± 0.9 m·s−1.

Conclusions:

The movement patterns of this fast bowler were a combination of highly intermittent activities of variable intensity on the base of ~16 km per game. This information provides insight for conditioning coaches to determine the physical demands and to adapt the training and recovery processes of ODI fast bowlers.

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Sam Coad, Bon Gray, George Wehbe and Christopher McLellan

Purpose:

To examine the response or pre- and postmatch salivary immunoglobulin A concentration ([s-IgA]) to Australian Football League (AFL) match play and investigate the acute and cumulative influence of player workload and postmatch [s-IgA] after repeated participation in AFL match play.

Methods:

Eleven elite AFL athletes (21.8 ± 2.4 y, 186.9 ± 7.9 cm, 87.4 ± 7.5 kg) were monitored throughout 3 matches during the preseason that were separated by 7 d. Saliva samples were collected across each AFL match at 24 h and 1 h prematch and 1, 12, 36, and 60 h postmatch to determine [s-IgA]. Global positioning systems (GPS) with integrated triaxial accelerometers were used to determine total player workload during match play. Hypothesis testing was conducted for time-dependent changes in [s-IgA] and player load using a repeated-measures ANOVA.

Results:

Player load during match 3 (1266 ± 124.6 AU) was significantly (P < .01) greater than in match 1 (1096 ± 115.1 AU) and match 2 (1082 ± 90.4 AU). Across match 3, [s-IgA] was significantly (P < .01) suppressed at 2 postmatch measures (12 and 36 h) compared with prematch measures (24 and 1 h), which coincided with significantly (P < .01) elevated player load.

Conclusion:

The findings indicate that an increase in player load during AFL preseason match play resulted in compromised postmatch mucosal immunological function. Longitudinal assessment of AFL-match player load and mucosal immunological function across the first 60 h of recovery may augment monitoring and preparedness strategies for athletes.