Strength and conditioning specialists commonly deal with the quantification and selection the setting of protocols regarding resistance training intensities. Although the one repetition maximum (1RM) method has been widely used to prescribe exercise intensity, the velocity-based training (VBT) method may enable a more optimal tool for better monitoring and planning of resistance training (RT) programs. The aim of this study was to compare the effects of two RT programs only differing in the training load prescription strategy (adjusting or not daily via VBT) with loads from 50 to 80% 1RM on 1RM, countermovement (CMJ) and sprint. Twenty-four male students with previous experience in RT were randomly assigned to two groups: adjusted loads (AL) (n = 13) and non-adjusted loads (NAL) (n = 11) and carried out an 8-week (16 sessions) RT program. The performance assessment pre- and post-training program included estimated 1RM and full load-velocity profile in the squat exercise; countermovement jump (CMJ); and 20-m sprint (T20). Relative intensity (RI) and mean propulsive velocity attained during each training session (Vsession) was monitored. Subjects in the NAL group trained at a significantly faster Vsession than those in AL (p < 0.001) (0.88-0.91 vs. 0.67-0.68 m/s, with a ∼15% RM gap between groups for the last sessions), and did not achieve the maximum programmed intensity (80% RM). Significant differences were detected in sessions 3-4, showing differences between programmed and performed Vsession and lower RI and velocity loss (VL) for the NAL compared to the AL group (p < 0.05). Although both groups improved 1RM, CMJ and T20, NAL experienced greater and significant changes than AL (28.90 vs.12.70%, 16.10 vs. 7.90% and -1.99 vs. -0.95%, respectively). Load adjustment based on movement velocity is a useful way to control for highly individualised responses to training and improve the implementation of RT programs.
Keywords: Full squat; Performance; Resistance training; Velocity specificity; Velocity-based strength training.
©2021 Jiménez-Reyes et al.