Global positioning systems (GPS) are commonly used in team sports to quantify the movement patterns of athletes during training and competition. 1 GPS devices can provide a large number of movement variables including distance, speed, acceleration/deceleration, and metabolic power. 1 , 2 By
Heidi R. Thornton, André R. Nelson, Jace A. Delaney, Fabio R. Serpiello and Grant M. Duthie
Benjamin M. Jackson, Ted Polglaze, Brian Dawson, Trish King and Peter Peeling
Global positioning system (GPS) devices are commonly used in elite-level team sports as a way of tracking player movements and quantifying workloads. 1 – 3 The data collected from GPS devices are important to coaches, athletes, and scientists, as they provide details about the movement patterns
Matthew C. Varley, Arne Jaspers, Werner F. Helsen and James J. Malone
Sprints and accelerations are popular performance indicators in applied sport. The methods used to define these efforts using athlete-tracking technology could affect the number of efforts reported. This study aimed to determine the influence of different techniques and settings for detecting high-intensity efforts using global positioning system (GPS) data.
Velocity and acceleration data from a professional soccer match were recorded via 10-Hz GPS. Velocity data were filtered using either a median or an exponential filter. Acceleration data were derived from velocity data over a 0.2-s time interval (with and without an exponential filter applied) and a 0.3-second time interval. High-speed-running (≥4.17 m/s2), sprint (≥7.00 m/s2), and acceleration (≥2.78 m/s2) efforts were then identified using minimum-effort durations (0.1–0.9 s) to assess differences in the total number of efforts reported.
Different velocity-filtering methods resulted in small to moderate differences (effect size [ES] 0.28–1.09) in the number of high-speed-running and sprint efforts detected when minimum duration was <0.5 s and small to very large differences (ES –5.69 to 0.26) in the number of accelerations when minimum duration was <0.7 s. There was an exponential decline in the number of all efforts as minimum duration increased, regardless of filtering method, with the largest declines in acceleration efforts.
Filtering techniques and minimum durations substantially affect the number of high-speed-running, sprint, and acceleration efforts detected with GPS. Changes to how high-intensity efforts are defined affect reported data. Therefore, consistency in data processing is advised.
Matthew D. Portas, Jamie A. Harley, Christopher A. Barnes and Christopher J. Rush
The study aimed to analyze the validity and reliability of commercially available nondifferential Global Positioning System (NdGPS) devices for measures of total distance during linear, multidirectional and soccer-specific motion at 1-Hz and 5-Hz sampling frequencies.
Linear (32 trials), multidirectional (192 trials) and soccer-specific courses (40 trials) were created to test the validity (mean ± 90% confidence intervals), reliability (mean ± 90% confidence intervals) and bias (mean ± 90% confidence intervals) of the NdGPS devices against measured distance. Standard error of the estimate established validity, reliability was determined using typical error and percentage bias was established.
The 1-Hz and 5-Hz data ranged from 1.3% ± 0.76 to 3.1% ± 1.37 for validity and 2.03% ± 1.31 to 5.31% ± 1.2 for reliability for measures of linear and soccer-specific motion. For multidirectional activity, data ranged from 1.8% ± 0.8 to 6.88% ± 2.99 for validity and from 3.08% ± 1.34 to 7.71% ± 1.65 for reliability. The 1-Hz underestimated some complex courses by up to 11%.
1-Hz and 5-Hz NdGPS could be used to quantify distance in soccer and similar field-based team sports. Both 1-Hz and 5-Hz have a threshold beyond which reliability is compromised. 1-Hz also underestimates distance and is less valid in more complex courses.
Darcy M. Brown, Dan B. Dwyer, Samuel J. Robertson and Paul B. Gastin
The purpose of this study was to assess the validity of a global positioning system (GPS) tracking system to estimate energy expenditure (EE) during exercise and field-sport locomotor movements. Twenty-seven participants each completed a 90-min exercise session on an outdoor synthetic futsal pitch. During the exercise session, they wore a 5-Hz GPS unit interpolated to 15 Hz and a portable gas analyzer that acted as the criterion measure of EE. The exercise session was composed of alternating 5-minute exercise bouts of randomized walking, jogging, running, or a field-sport circuit (×3) followed by 10 min of recovery. One-way analysis of variance showed significant (P < .01) and very large underestimations between GPS metabolic power– derived EE and oxygen-consumption (VO2) -derived EE for all field-sport circuits (% difference ≈ –44%). No differences in EE were observed for the jog (7.8%) and run (4.8%), whereas very large overestimations were found for the walk (43.0%). The GPS metabolic power EE over the entire 90-min session was significantly lower (P < .01) than the VO2 EE, resulting in a moderate underestimation overall (–19%). The results of this study suggest that a GPS tracking system using the metabolic power model of EE does not accurately estimate EE in field-sport movements or over an exercise session consisting of mixed locomotor activities interspersed with recovery periods; however, is it able to provide a reasonably accurate estimation of EE during continuous jogging and running.
Nacho Torreño, Diego Munguía-Izquierdo, Aaron Coutts, Eduardo Sáez de Villarreal, Jose Asian-Clemente and Luis Suarez-Arrones
To analyze the match running profile, distance traveled over successive 15 min of match play, heart rates (HRs), and index of performance efficiency (effindex) of professional soccer players with a global positioning system (GPS) and HR in official competition.
Twenty-six professional players were investigated during full matches in competitive club-level matches (N = 223). Time–motion data and HR were collected using GPS and HR technology.
The relative total distance was 113 ± 11 m/min, with substantial differences between halves. For all playing positions, a substantial decrease in total distance and distance covered at >13.0 km/h was observed in the second half in comparison with the first. The decrease during the second half in distance covered at >13.0 km/h was substantially higher than in total distance. The average HR recorded was 86.0% maximal HR, and the relationship between external and internal load (effindex) was 1.3, with substantial differences between halves in all playing positions, except strikers for effindex. Wide midfielders reflected substantially the lowest mean HR and highest effindex, whereas center backs showed substantially the lowest effindex of all playing positions.
The current study confirmed the decrement in a player’s performance toward the end of a match in all playing positions. Wide midfielders displayed the highest and fittest levels of physical and physiological demands, respectively, whereas center backs had the lowest and least-fit levels of physical and physiological demands, respectively. The position-specific relationship between external and internal load confirms that players with more overall running performance during the full match were the best in effindex.
Tannath J. Scott, Heidi R. Thornton, Macfarlane T.U. Scott, Ben J. Dascombe and Grant M. Duthie
Advancements in technology have led to the extensive implementation of global positioning systems (GPS) and microtechnology in team sports to quantify movement demands. The ability to more reliably quantify and interpret these demands has led to a greater understanding of the external loads
Mark Waldron, Jamie Highton and Craig Twist
This study assessed the reliability of a rugby league movement-simulation protocol, relative to interchanged players (RLMSP-i).
Fifteen male participants completed 2 trials of the RLMSP-i, separated by 1 wk. The RLMSP-i comprised low- to moderate-intensity running, interspersed by high-intensity sprinting and tackling activity, based on global positioning system (GPS) data recorded during Super League performances.
The lowest coefficient of variation (CV ± 95% CI) was observed for total m/min during both interchange bout 1 (1.1% ± 0.2%) and bout 2 (1.0% ± 0.2%). The percentage of heart rate peak and ratings of perceived exertion demonstrated CVs of 1.2–2.0% and 2.9–3.5%, respectively. The poorest agreement between trials was found for blood lactate concentration (16.2% ± 2.8%). In no case was the CV smaller than the smallest worthwhile change, yet in every case the moderate changes were larger than the CV.
The RLMSP-i’s reliability is sufficient to enable the detection of moderate changes in various performance and physiological measurements that accurately simulate some, but not all, aspects of rugby league matches.
Mark Waldron, Jamie Highton, Matthew Daniels and Craig Twist
This study aimed to quantify changes in heart rate (HR) and movement speeds in interchanged and whole-match players during 35 elite rugby league performances.
Performances were separated into whole match, interchange bout 1, and interchange bout 2 and further subdivided into match quartiles. Mean percentages of peak HR (%HRpeak) and total and high-intensity running (> 14 km/h) meters per minute (m/min) were recorded.
For whole-match players, a decline in high-intensity m/min and %HRpeak was observed between successive quartiles (P < .05). High-intensity m/min during interchange 1 also progressively declined, although initial m/min was higher than whole match (24.2 ± 7.9 m/min vs 18.3 ± 4.7 m/min, P = .018), and %HRpeak did not change over match quartiles (P > .05). During interchange 2, there was a decline in high-intensity m/min from quartile 1 to quartile 3 (18 ± 4.1 vs 13.4 ± 5 m/min, P = .048) before increasing in quartile 4. Quartiles 1 and 2 also showed an increase in %HRpeak (85.2 ± 6.5 vs 87.3 ± 4.2%, P = .022).
Replacement players adopted a high initial intensity in their first match quartile before a severe decline thereafter. However, in a second bout, lower exercise intensity at the outset enabled a higher physiological exertion for later periods. These findings inform interchange strategy and conditioning for coaches while also providing preliminary evidence of pacing in team sport.
James J. Malone, Arne Jaspers, Werner Helsen, Brenda Merks, Wouter G.P. Frencken and Michel S. Brink
) and the in-season period (39 wk). The GK trained on average of 5 times per week during preseason and 4.2 times per week during in-season, respectively. The GK wore a global positioning system (GPS) device (firmware version 717, OptimEye G5; Catapult Sports, Melbourne, Australia), which has shown