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Validity and Reliability of the Load-Velocity Relationship to Predict the One-Repetition Maximum in Deadlift
Ludwig Ruf1, Clément Chéry1, Kristie-Lee Taylor2
1Cardiff School of Sport, Cardiff Metropolitan University, Cardiff, United Kingdom.
Abstract:
Ruf, L, Chéry, C, Taylor, KL. Validity and reliability of the load-velocity relationship to predict the 1RM in deadlift. J Strength Cond Res 32(3): 681-689, 2018-The aim of this study was to verify the reliability and validity of using submaximal loads from the load-velocity relationship to predict the actual 1 repetition maximum (1RM) in the deadlift. Data from 11 resistance-trained athletes were analyzed performing three 1RM assessments separated by at least 3 days. Reliability was assessed by comparing predicted 1RMs of sessions 2 and 3, whereas for validity purposes, predicted 1RMs of session 3 were compared with actual 1RMs of session 2. Mean concentric velocity at 1RM (v at 1RM) was entered in individualized linear regression equations, derived from the load-velocity relationship for 3 (20-60%, 40-80%, and 60-90% of 1RM), 4 (20-80% and 40-90% of 1RM), and 5 (20-90% of 1RM) incremental loads to predict 1RMs. There were trivial changes for all predicted 1RMs between sessions with 20-90% of 1RM being the most reliable model. Similarly, the actual 1RM was very stable (effect size [ES] = 0.04, 90% confidence limit [CL] [-0.03 to 0.12], typical error of measurement [TE] = 3.4 kg [2.5-5.4], intraclass coefficient [ICC] = 0.99 [0.96-0.996], and coefficient of variation [CV] = 1.9% [1.4-3.0]), whereas the v at 1RM was unreliable between trials (ES = -0.30, 90% CL [-0.78 to 0.17], TE = 0.029 m·s [0.022-0.047], ICC = 0.63 [0.19-0.86], and CV = 15.7% [11.7-26.1]). However, predicted 1RMs computed from all submaximal load ranges substantially overestimated the actual 1RM with considerable differences between athletes. Although 1RM predictions showed high reliability, they all overestimated the actual 1RM, which was stable between sessions. Therefore, it is not recommended to apply the prediction models used in this study to compute daily 1RMs.
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