Testing Practices and Applications of Flywheel Resistance Technologies-Implications for Performance Assessment and...

Mak, MCW, Beato, M, De Keijzer, K, Turner, A, Weldon, A, and Bishop, C. Testing practices and applications of flywheel resistance technologies-Implications for performance assessment and injuries from a survey study. J Strength Cond Res 40(8): 953-963, 2026-This study explores current practices and applications associated with flywheel resistance technologies in performance assessment, asymmetry, and injury risk. A cross-sectional online survey was conducted among sports scientists, strength and conditioning coaches, and medical professionals. The findings showed that monitoring and testing frequency among practitioners ( n = 42) are low, with 70% ( n = 29) conducting it less than once a month. Monitoring and testing are crucial for adjusting training modalities, allowing practitioners to make informed decisions to condition athlete performance. Currently, practitioners reported using 2.38 ± 0.87 familiarization sessions and 29.0 ± 21.8 (range:3-75) maximal intent repetitions. It is recommended to continuously assess reliability to ensure the data remains reliable and valid, because the actual familiarization period can be influenced by various factors. The flywheel squat was the most commonly used exercise (89.9% with rotary encoders), while practitioners suggested hamstring-focused exercises (e.g., straight leg hip extensions) as having high potential for injury risk assessment. The most commonly used metrics for monitoring and testing include (a) eccentric (E) peak power, (b) concentric (C) peak power, and (c) the E: C ratio. Overall, the findings suggest that flywheel testing is still underexplored in practice; there is a clear need for standardized, evidence-based protocols to bridge the gap between its potential and current implementation. Future research directions should focus on (a) testing reliability at higher moments of inertia (>0.15 kg·m 2 ), (b) evaluating the feasibility of assessing asymmetry through the flywheel, (c) investigating predictive links between flywheel metrics and field performance, and (d) developing validated assessment protocols for a broader range of exercises.