So sánh phương pháp

	Tỷ lệ Tải trọng Cấp tính-Mãn tính	Mô hình Banister TRIMP	GPS theo dõi thời gian-chuyển động
Lĩnh vực	Khoa học thể thao	Khoa học thể thao	Khoa học thể thao
Họ	Hypothesis test	Hypothesis test	Hypothesis test
Năm ra đời	2016	1975	2010
Người khởi xướng	Tim Gabbett	Eric Banister	Osgnach & Di Prampero
Loại	workload monitoring	mathematical modeling	GPS tracking
Công trình gốc	Gabbett, T. J. (2016). The training-injury prevention paradox: should athletes be training smarter and harder? British Journal of Sports Medicine, 50(5), 273-280.	Banister, E. W., Calvert, T. W., Savage, M. V., & Bach, T. (1975). A systems model of training responses and its relationship to muscular strength. Transactions of the ASME, 97(3), 177-183.	Gregory, P., & Drust, B. (2007). Physical demands of rugby union: quantification of accelerations and movements patterns in play. Journal of Strength and Conditioning Research, 21(2), 309-314.
Tên gọi khác	ACWR, workload ratio, training load balance	TRIMP, training impulse, fitness-fatigue model	GPS analysis, movement tracking, workload quantification, physical demands
Liên quan	3	3	4
Tóm tắt	The acute-chronic workload ratio (ACWR) is the ratio of acute training load (typically the past 1 week) to chronic training load (typically the rolling 4-week average). Formalized by Tim Gabbett (2016), ACWR is a widely adopted metric for predicting injury and illness risk in sports. The logic is straightforward: rapid increases in training load—when acute load spikes far above what the athlete has adapted to—exceed tissue tolerance and increase injury risk. Conversely, maintaining ACWR within optimal ranges (typically 0.8-1.3) is associated with better performance and lower injury incidence. ACWR monitoring is now standard in elite sports for load management.	The Training Impulse (TRIMP) model, developed by Eric Banister and colleagues (1975), quantifies the physiological stimulus of a training session by combining duration and intensity. The Banister fitness-fatigue model proposes that training effects on performance follow two opposing dynamics: fitness (beneficial) accumulates with time constant tau_f (~42 days) and fatigue (temporary decrement) accumulates faster but decays quickly (tau_d ~5-10 days). By tracking TRIMP and modeling these two processes, coaches can predict performance trajectories and optimize training load. Although superseded by newer frameworks, the Banister model remains influential and intuitive.	Time-motion analysis with GPS and micro-sensor technology quantifies the movement patterns, workload, and physical demands during training or match play in team sports. Pioneered by Osgnach and colleagues (2010), modern GPS units track athletes' positions in real-time, calculating distance covered, velocity profiles, and acceleration/deceleration frequencies. Combined with heart rate and other sensor data, GPS analysis provides comprehensive workload quantification enabling coaching staff to monitor player fatigue, balance training intensity, and prevent injury. GPS is now standard in elite soccer, rugby, Australian Rules football, and other intermittent sports.