Velocity Variables: Determining Predictive Metrics during the Back Squat and Bench Press to Failure at Different...

Lawson, DJ, Olmos, AA, Mosiman, SJ, Sontag, SA, Goodin, JR, and Dawes, JJ. Velocity Variables: Determining Predictive Metrics during the Back Squat and Bench Press to Failure at Different Relative Loads. J Strength Cond Res XX(X): 000-000, 2025-This study aimed to determine a best velocity variable and prediction model for estimating repetitions to failure (RTF) across 3 relative loads (%1RM) comparing the average concentric velocity (ACV) of a single repetition set (ACVSingle), ACV from the first repetition (ACVFirst), ACV across all repetitions (ACVMean), and the fastest repetition velocity (FRV) achieved during the back squat and bench press exercises. Twenty-six (n = 26; males = 18, females = 8) resistance-trained individuals performed 3 sets to failure at 90, 80, and 70% of their 1RM on both exercises for 2 testing sessions. Repeated measures mixed effects models were constructed for univariate, adjusted (corrected for sex), and interaction (velocity*sex) models from Visit 2 data. Model selection criteria were determined by the smallest residual mean error (RME) and standard deviation (SD), Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC) serving as fit indicators. Best fit models were cross-validated by applying fixed-effects coefficients from Visit 2 to Visit 3 velocity variables, estimating RTF and calculating error as the predicted versus observed variable delta. The ACVSingle adjusted model demonstrated the best fit for the squat (RME = 0.0056, SD = 3.7731, AIC = 360.88, BIC = 363.24). The FRV interaction model demonstrated the best fit for the bench press (RME = 0.0303, SD = 2.4011, AIC = 300.71, and BIC = 303.07). Although no single predictor exhibited superiority across all intensities, ACVSingle and FRV provide lower prediction error variability under specific conditions, with the best predictor determined by both intensity and exercise.