Velocity-Based Training – A Critical Review

Velocity-Based Training - A Critical Review

Force-generating capacity is crucial for athletic performance (sprinting, jumping, changing direction) and sport-specific skills.
Maximal strength protects against fatigue and mitigates injury risk.
Resistance exercises like squats, deadlifts, and bench presses are used to improve maximal strength.
Traditional load prescription methods (percentage-based, RM loads) have drawbacks, such as not accounting for changes in strength or leading to increased training strain.
Autoregulation, altering training volume/intensity based on daily training status, is suggested.
Subjective methods like RPE and RIR may be unreliable, especially for novice lifters.
Objective measurement of movement velocity during resistance exercise is a viable means for modulating training loads.
Monitoring velocity can help tailor training to match the athlete’s current training status.

Central to velocity-based programming is the relationship between velocity and lifted load.
Gonzalez-Badillo and Sanchez-Medina highlighted using relative load (%1RM) and velocity to monitor training loads.
Load-velocity relationship can be modeled with a second-order polynomial function or linear regression.
Generalized load-velocity profiles do not account for individual differences or biological sex; thus, profiles are needed for each athlete.
Load-velocity profiles are exercise-specific and not transferable between exercises.

Using warm-up sets to create a daily load-velocity profile to estimate 1RM has been suggested for precise load prescriptions.
This method aims to remove the need for time-consuming and fatiguing maximal strength testing.
However, empirical evidence supporting the validity of this practice is limited.
Studies have reported overestimation of 1RM when using load-velocity profiles created from free-weight exercises.
The difference between estimated and measured 1RM increases with the athlete's strength.
Correlation coefficients do not assess bias between measures and should not be used in method comparison studies.
Inaccurate 1RM estimation via load-velocity profile is due to difficulties in selecting an appropriate velocity at 1RM (v1RM).
Using generalized v1RM results in similar prediction errors and inferior precision.
Machine-learning models not requiring v1RM have shown promise but require further research.
Estimating 1RM via a load-velocity profile is not yet feasible and can result in mis-programming of training loads.
Traditional methods of assessing maximum strength and using the load-velocity profile to monitor fatigue may be more appropriate.

Adjusting barbell load on a set-by-set basis using the load-velocity profile can be implemented.
During training, velocity is compared to predicted velocity, with load adjustments made based on deviations.
Studies show improved fatigue management and similar strength development compared to traditional methods.
Optimal time to use the load-velocity profile may be during the in-season or competitive period.
Limited evidence suggests improved performance outcomes with load-velocity profile-based programming.
Calculating the load-velocity profile is time-consuming, requiring two testing sessions per athlete for each exercise.

Using percentage velocity decline to control volume within a set is another autoregulation method.
Sets are terminated upon reaching a pre-determined velocity-loss threshold from the first repetition.
Decline magnitude depends on the targeted physical quality.
Higher decline magnitudes (30-40%) are prescribed during general preparation phases, while smaller declines (10-20%) are used during pre- or in-season phases.
Fixed number of sets can be combined with letting the athlete perform as many repetitions as possible before reaching the prescribed cut-off threshold (i.e. 10, 20, or 30%).
There could be considerable inter-individual differences in the number of repetitions that can be performed at a particular velocity-loss thresholds.
However, If strength and conditioning professionals were to implement these unconstrained approaches during pre-season or in-season training periods, they risk exposing athletes to excessively fatiguing volumes of training and would therefore counteract the purpose of implementing the programming strategy.
Velocity-loss thresholds may be best implemented as a tool to augment traditional ‘fixed’ programming strategies and prevent excessive exposure to highly fatiguing training (e.g., training to failure) rather than serving as a standalone method for controlling the overall training volume.

Load-velocity profile could assess and monitor neuromuscular fatigue.
Decreases in mean velocity (MV) during submaximal squats indicate increased fatigue.
Limitations include the need for extensive pre-implementation testing and exercise-specific profiles.
Accurate velocity measurements are essential for reliable fatigue monitoring.

Velocity-based programming relies on accurate velocity measurement during resistance exercise.
Many commercially available devices have measurement errors exceeding acceptable thresholds.
Accelerometer-based devices and inertial measurement units may have poor validity due to integration drift.
Linear position transducers (LPTs) generally demonstrate stronger validity and lower measurement errors.
Strength and conditioning professionals seeking to implement velocity-based programming strategies should preferentially use LPTs as these offer the most reliable and accurate velocity measurements.

VBT may be most effective during pre- or in-season periods, where mitigation of fatigue and the optimization of sports performance may be needed.
For mesocycle blocks targeting strength development, 3-5 sets of 4-6 repetitions can be capped when autoregulatory control of volume may then be implemented through the use of 20-25% velocity-loss thresholds.
VBT should be used to augment the training process and still requires the strength and conditioning professional to coach the athlete in front of them rather than simply monitoring the device outputting the velocity measure.

Using a load-velocity profile to estimate daily 1RM strength should be avoided in favor of directly testing the 1RM at pre-planned time points.
Adjusting loads on a set-by-set basis in response to acute changes in velocity facilitate improved fatigue management but are dependent on the accuracy of the device used to quantify the velocity generated during resistance exercise and do not appear to induce greater gains in strength than traditional methods.
Strength and conditioning professionals should also consider how the implementation of velocity-based programming strategies aligns with the goals of each specific phase or period of their athlete’s annual plan.