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Methodological Considerations When Quantifying High-Intensity Efforts in Team Sport Using Global Positioning System Technology.
International Journal of Sports Physiology and Performance 2017 September
PURPOSE: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: 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.
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