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Purpose: This study compared pooled against individualized load–velocity profiles (LVPs) in the free-weight back squat and power clean. Methods: A total of 10 competitive weightlifters completed baseline 1-repetition maximum assessments in the back squat and power clean. Three incremental LVPs were completed, separated by 48 to 72 hours. Mean and peak velocity were measured via a linear-position transducer (GymAware). Linear and nonlinear (second-order polynomial) regression models were applied to all pooled and individualized LVP data. A combination of coefficient of variation (CV), intraclass correlation coefficient, typical error of measurement, and limits of agreement assessed between-subject variability and within-subject reliability. Acceptable reliability was defined a priori as intraclass correlation coefficient > .7 and CV < 10%. Results: Very high to practically perfect inverse relationships were evident in the back squat (r = .83–.96) and power clean (r = .83–.89) for both regression models; however, stronger correlations were observed in the individualized LVPs for both exercises (r = .85–.99). Between-subject variability was moderate to large across all relative loads in the back squat (CV = 8.2%–27.8%) but smaller in the power clean (CV = 4.6%–8.5%). The power clean met our criteria for acceptable reliability across all relative loads; however, the back squat revealed large CVs in loads ≥90% of 1-repetition maximum (13.1%–20.5%). Conclusions: Evidently, load–velocity characteristics are highly individualized, with acceptable levels of reliability observed in the power clean but not in the back squat (≥90% of 1-repetition maximum). If practitioners want to adopt load–velocity profiling as part of their testing and monitoring procedures, an individualized LVP should be utilized over pooled LVPs.

Thompson, Rogerson, Ruddock, and Barnes are with the Dept for Sport and Physical Activity, Sheffield Hallam University, Sheffield, United Kingdom. Banyard is with the Dept of Health Science, Swinburne University of Technology, Melbourne, VIC, Australia.

Thompson (s.w.thompson@shu.ac.uk) is corresponding author.
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