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Characterization of Running Intensity in Canadian Football Based on Tactical Position
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Characterization of Running Intensity in Canadian Football Based on Tactical Position
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Journal Article
Characterization of Running Intensity in Canadian Football Based on Tactical Position
2024
Overview
This study aimed to use a data-driven approach to identify individualized speed thresholds to characterize running demands and athlete workload during games and practices in skill and linemen football players. Data were recorded from wearable sensors over 28 sessions from 30 male Canadian varsity football athletes, resulting in a total of 287 performances analyzed, including 137 games and 150 practices, using a global positioning system. Speed zones were identified for each performance by fitting a 5-dimensional Gaussian mixture model (GMM) corresponding to 5 running intensity zones from minimal (zone 1) to maximal (zone 5). Skill players had significantly higher (p < 0.001) speed thresholds, percentage of time spent, and distance covered in maximal intensity zones compared to linemen. The distance covered in game settings was significantly higher (p < 0.001) compared to practices. This study highlighted the use of individualized speed thresholds to determine running intensity and athlete workloads for American and Canadian football athletes, as well as compare running performances between practice and game scenarios. This approach can be used to monitor physical workload in athletes with respect to their tactical positions during practices and games, and to ensure that athletes are adequately trained to meet in-game physical demands.
Publisher
MDPI AG,Multidisciplinary Digital Publishing Institute (MDPI),MDPI
Subject
/ Athletes
/ Athletic Performance - physiology
/ Canada
/ De Beaumont, L. Characterization of wearable sensors
/ Football
/ game
/ Geographic Information Systems
/ GPS
/ Guay, S
/ Humans
/ Male
/ Orthopedics, rehabilitation & sports medicine
/ Orthopédie, rééducation & médecine sportive
/ Running
/ Sciences de la santé humaine
/ Sensors
/ training
/ Velocity
/ workload
/ Zafar, A
