Abstract
This aims of this study were (I) to determine the velocity variable and regression model which best fit the load-velocity relationship during the free-weight prone bench pull exercise, (II) to compare the reliability of the velocity attained at each percentage of the one-repetition maximum (1RM) between different velocity variables and regression models, and (III) to compare the within- and between-subject variability of the velocity attained at each %1RM. Eighteen men (14 rowers and four weightlifters) performed an incremental test during the free-weight prone bench pull exercise in two different sessions. General and individual load-velocity relationships were modelled through three velocity variables (mean velocity [MV], mean propulsive velocity [MPV] and peak velocity [PV]) and two regression models (linear and second-order polynomial). The main findings revealed that (I) the general (Pearson's correlation coefficient [r] range = 0.964–0.973) and individual (median r = 0.986 for MV, 0.989 for MPV, and 0.984 for PV) load-velocity relationships were highly linear, (II) the reliability of the velocity attained at each %1RM did not meaningfully differ between the velocity variables (coefficient of variation [CV] range = 2.55–7.61% for MV, 2.84–7.72% for MPV and 3.50–6.03% for PV) neither between the regression models (CV range = 2.55–7.72% and 2.73–5.25% for the linear and polynomial regressions, respectively), and (III) the within-subject variability of the velocity attained at each %1RM was lower than the between-subject variability for the light-moderate loads. No meaningful differences between the within- and between-subject CVs were observed for the MV of the 1RM trial (6.02% vs. 6.60%; CVratio = 1.10), while the within-subject CV was lower for PV (6.36% vs. 7.56%; CVratio = 1.19). These results suggest that the individual load-MV relationship should be determined with a linear regression model to obtain the most accurate prescription of the relative load during the free-weight prone bench pull exercise.
Highlights
The use of technology in sport can provide information for optimizing the prescription and monitoring of training programs [1,2]
The linear regression model provided a higher F statistic compared to the polynomial regression model for Mean velocity (MV) and mean propulsive velocity (MPV), while no meaningful differences in the magnitude of the F statistic was observed between both regression models for peak velocity (PV)
A significant interclass correlation coefficient (ICC) value was observed at all relative loads with the exception of the heavy loads (85–100%one-repetition maximum (1RM)) for MV and MPV and the moderate loads (45–60%1RM) for the PV modelled through a polynomial regression model (Table 3)
Summary
The use of technology in sport can provide information for optimizing the prescription and monitoring of training programs [1,2]. Velocity-based resistance training requires the measurement of velocity in real-time and provides at least three important practical applications: (I) load can be adjusted on a daily basis to match the desired intensity (commonly expressed as a percentage of the one-repetition maximum; 1RM) due to the strong relationship between movement velocity and the load lifted [6,7], (II) the volume of the training session (e.g., the number of exercises per session, sets per exercise or repetitions per set) can be prescribed based off the magnitude of velocity loss due to its close relationship with markers of fatigue [8,9], and (III) the administration of real-time velocity feedback improves motivation and enables the maintenance of higher movement velocities during resistance training, which in turn may stimulate long-term training adaptations [10,11] Despite these encouraging applications, many aspects related to the velocity-based resistance training approach still need to be investigated to facilitate and optimize the application of this novel strength-training methodology. Due to the unique movement patterns of each exercise, it is important to explore whether the previous findings obtained with the bench press exercise could be extended to another commonly used upper-body exercise such as the prone bench pull
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