TY - JOUR
T1 - Current Periodization, Testing, and Monitoring Practices of Strength and Conditioning Coaches
AU - Washif, Jad Adrian
AU - James, Carl
AU - Pagaduan, Jeffrey
AU - Lim, Julian
AU - Lum, Danny
AU - Azidin, Raja Mohammed Firhad Raja
AU - Mujika, Iñigo
AU - Beaven, Christopher Martyn
N1 - Publisher Copyright:
© 2025 Human Kinetics, Inc.
PY - 2025/9
Y1 - 2025/9
N2 - Purpose: This study investigated the periodization, testing, and monitoring practices of strength and conditioning practitioners across different levels of coaching experience and sports. Methods: An online survey was completed by 58 practitioners (25 sports/events) from 9 Southeast and East Asian countries. The survey focused on periodization models, programming frameworks, unloading strategies, fitness assessments, and pretraining readiness monitoring. Frequency analysis and chi-square tests were used to assess data distribution and differences. Results: Hybrid (multiple) periodization was favored over a single model for different training objectives (39%–45%), including very short-term training (≤4 wk). Emerging approaches including flexible programming were similarly adopted (43%). Program adjustment was primarily driven by athlete feedback (90%), selfobservation (78%), and technical execution (74%). Major programming challenges identified were managing fatigue (72%), optimizing training stimuli (53%), specificity (50%), and adherence (47%). Deloading practices (95%) and tapering applications (91%) were common. Physical performance changes were primarily identified from testing (90%) but also from athlete/coach feedback (76%), monitoring (71%), training data (67%), and performance data/statistics (62%). Strength assessments were conducted 2 to 4 times yearly (67%) using 1 to 4 exercises (76%). Pretraining readiness was monitored via conversations (71%), wellness tools (46%), and performance devices (31%). Practitioners also utilized monitoring technology, force plates (21%), and velocity-tracking devices (23%). Training load was commonly quantified using volume load (81%) and session rating of perceived exertion (72%). None of the comparisons differed across experience levels and sport types (P > .05). Conclusion: Practitioners employed a range of periodization models, often integrating flexible approaches. Unloading strategies were commonly implemented alongside various assessment methods. Technologies were used for monitoring, but conversational/ subjective methods remained more widespread.
AB - Purpose: This study investigated the periodization, testing, and monitoring practices of strength and conditioning practitioners across different levels of coaching experience and sports. Methods: An online survey was completed by 58 practitioners (25 sports/events) from 9 Southeast and East Asian countries. The survey focused on periodization models, programming frameworks, unloading strategies, fitness assessments, and pretraining readiness monitoring. Frequency analysis and chi-square tests were used to assess data distribution and differences. Results: Hybrid (multiple) periodization was favored over a single model for different training objectives (39%–45%), including very short-term training (≤4 wk). Emerging approaches including flexible programming were similarly adopted (43%). Program adjustment was primarily driven by athlete feedback (90%), selfobservation (78%), and technical execution (74%). Major programming challenges identified were managing fatigue (72%), optimizing training stimuli (53%), specificity (50%), and adherence (47%). Deloading practices (95%) and tapering applications (91%) were common. Physical performance changes were primarily identified from testing (90%) but also from athlete/coach feedback (76%), monitoring (71%), training data (67%), and performance data/statistics (62%). Strength assessments were conducted 2 to 4 times yearly (67%) using 1 to 4 exercises (76%). Pretraining readiness was monitored via conversations (71%), wellness tools (46%), and performance devices (31%). Practitioners also utilized monitoring technology, force plates (21%), and velocity-tracking devices (23%). Training load was commonly quantified using volume load (81%) and session rating of perceived exertion (72%). None of the comparisons differed across experience levels and sport types (P > .05). Conclusion: Practitioners employed a range of periodization models, often integrating flexible approaches. Unloading strategies were commonly implemented alongside various assessment methods. Technologies were used for monitoring, but conversational/ subjective methods remained more widespread.
KW - assessment
KW - high performance
KW - planning
KW - resistance training
KW - tapering
KW - unloading training
UR - https://www.scopus.com/pages/publications/105014129804
U2 - 10.1123/ijspp.2025-0051
DO - 10.1123/ijspp.2025-0051
M3 - Journal article
SN - 1555-0265
VL - 20
SP - 1239
EP - 1252
JO - International Journal of Sports Physiology and Performance
JF - International Journal of Sports Physiology and Performance
IS - 9
ER -