RESEARCH PAPER
The Relationship between Training Load Indicators and Total Quality Recovery Scale during the Preseason Period in Collegiate Taekwondo Athletes
1
Department of Physical Education, Graduate School, Kyung Hee University, Yongin, Republic of Korea.
2
Department of Sports Coaching, Kyung Hee University, Yongin, Republic of Korea.
3
Sports Science Research Center, Kyung Hee University, Yongin, Republic of Korea.
Submission date: 2025-10-04
Final revision date: 2025-12-24
Acceptance date: 2026-01-21
Publication date: 2026-04-02
Corresponding author
Hyun Chul Jung
Department of Sports Coaching, College of Physical Education, Kyung Hee University-Global Campus, 1732, Deogyeong-daero, 17104, Yongin, Korea (South)
Department of Sports Coaching, College of Physical Education, Kyung Hee University-Global Campus, 1732, Deogyeong-daero, 17104, Yongin, Korea (South)
Journal of Human Kinetics 2026;101:133-145
KEYWORDS
training monitoringrecovery statussession rating of perceived exertionexponentially weighted moving average
TOPICS
ABSTRACT
This study examined the relationship between training load (TL) indicators and recovery status (total quality recovery, TQR) during the preseason training period in collegiate Taekwondo athletes. A total of 25 athletes (17 males and 8 females; age: 19.2 ± 1.04 years, training experience: 6.8 ± 3.40 years, body height: 168.0 ± 8.08 cm, body mass: 64.1 ± 8.38 kg, fat content: 15.9 ± 7.21%) participated in this prospective observational study. Over eight weeks, 855 training sessions were monitored. TL was quantified using the session rating of perceived exertion (sRPE) method, and derived TL indicators [weekly load variation (SDΔ), rolling average acute:chronic workload ratio (RA ACWR), exponentially weighted moving average acute:chronic workload ratio (EWMA ACWR), training monotony (TM), and training strain (TS)] were calculated. Recovery status was assessed daily using the TQR scale. In the univariate linear mixed model analyses, SDΔ (β = −0.30, 95% CI [−0.51, −0.08], p = 0.006) and the EWMA ACWR (β = −0.46, 95% CI [−0.64, −0.29], p < 0.001) were significantly associated with TQR. However, in the multivariate model, only the EWMA ACWR (β = −0.74, 95% CI [−0.97, −0.52], p < 0.001) remained a significant predictor. These findings suggest that the EWMA ACWR is the most sensitive TL indicator for capturing short-term changes in recovery status. Integrating the EWMA ACWR with simple tools such as the TQR scale may help coaches balance TL and recovery in preseason training. Future studies should include additional physiological and psychological markers to evaluate whether EWMA ACWR-based load management can effectively reduce injury risk and enhance athletic performance.
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