Whilst Percentage-Based Training (PBT) has been proven to be an effective method of inducing positive adaptations in strength, it can be criticized for its ignorance to daily flections of physiological state of readiness, its complex process of testing and an increased risk of injury. Velocity-Based Training (VBT) can somewhat mitigate the risks of PBT through the predictive measures utilised in load-velocity profiling (LVP). VBT has been significantly supported within prevailing research to prescribe load and progression through allowing participants to reduce injury risk in traditional 1RM attempts. However, compared to the availability of equipment in the modern strength training facility, the exercises that have been tested and subsequently supported are limited. The introduction of the hexagonal bar deadlift
(HBD) allowed the use of the deadlift movement to be a common prescription within resistance-based settings. There is little research available to support the use of the LVP in the HBD and the LVP has not yet been explored in resistance-trained individuals. A total of 21 participants (age = 25.33 ± 3.23 years, stature = 174.52 ± 10.16 cm, mass = 76.81 ± 17.29 kg) performed a submaximal protocol of hexagonal bar deadlift utilising a self-predicted 1RM until a true 1RM was discovered. All repetitions completed were monitored using a linear positional transducer (GymAware PowerTool; Kinetic Performance Technology, Canberra, Australia) with mean concentric velocity (MV) recorded to create full load-velocity profiles for each participant. The individualised mean velocity (MV) at 100% 1RM was used to predict the 1RM value and a second order polynomial regression model gave an adjusted R2 value. Then, concurrent validity of the predicted 1RM with reference to the actual 1RM showed an almost perfect correlation between them with an R2 value of 0.939. The load-velocity relationship overestimated 1RM (absolute difference: + 0.05 ± 8.09 kg), however it was classified as a non-significant difference (p > 0.05) and showed a trivial effect size (ES) (-0.16). A near perfect correlation between predicted 1RM and actual 1RM was found (r = 0.99) and a typical error (TE) of 1.03kg was discovered. The coefficient of variation was determined to be 0.31. A predictive equation for 1RM using MV in the HBD was yielded. The results of this study corroborate earlier findings that the load-velocity relationship, in certain resistance training exercises, can be used as a separate method of load prescription to percentage-based training and actual 1RM attempts. Finally, the LVP of the HBD cannot yet be confirmed as stable due to the lack of test-retest reliability data available in current research. Future literature should aim to determine the test-retest reliability of the LVP in the HBD to allow more confidence in the use of its’ predictive abilities.
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