Audio Abstracts are changing the way scientific research is being communicated. Watch Harry’s video below where he delves into his article ‘The Reliability of Individualised Load-Velocity Profiles’, highlighting the purpose of the study, its limitations and the practical applications. If you want to read the abstract or access the full paper (where available), all links are below.

The full paper can be found on Researchgate

Harry can be found on Twitter @banyardharry

Abstract: This study examined the reliability of peak velocity (PV), mean propulsive velocity (MPV), and mean velocity (MV) in the development of load-velocity profiles (LVP) in the full depth free-weight back squat performed with maximal concentric effort. Methods: Eighteen resistance-trained men performed a baseline one-repetition maximum (1RM) back squat trial and three subsequent 1RM trials used for reliability analyses, with 48-hours interval between trials. 1RM trials comprised lifts from six relative loads including 20, 40, 60, 80, 90, and 100% 1RM. Individualized LVPs for PV, MPV, or MV were derived from loads that were highly reliable based on the following criteria: intra-class correlation coefficient (ICC) >0.70, coefficient of variation (CV) ≤10%, and Cohen’s d effect size (ES) <0.60. Results: PV was highly reliable at all six loads. Importantly, MPV and MV were highly reliable at 20, 40, 60, 80 and 90% but not 100% 1RM (MPV: ICC=0.66, CV=18.0%, ES=0.10, standard error of the estimate [SEM]=0.04m·s(-1); MV: ICC=0.55, CV=19.4%, ES=0.08, SEM=0.04m·s(-1)). When considering the reliable ranges, almost perfect correlations were observed for LVPs derived from PV20-100% (r=0.91-0.93), MPV20-90% (r=0.92-0.94) and MV20-90% (r=0.94-0.95). Furthermore, the LVPs were not significantly different (p>0.05) between trials, movement velocities, or between linear regression versus second order polynomial fits. Conclusions: PV20-100%, MPV20-90%, and MV20-90% are reliable and can be utilized to develop LVPs using linear regression. Conceptually, LVPs can be used to monitor changes in movement velocity and employed as a method for adjusting sessional training loads according to daily readiness.