Hawkin's Lauren Green MS was an honored speaker at the 2024 NSCA Coaches Conference in Orlando, FL. Here is an inside look at his presentation.
The Problem:
Traditionally, the use of weightlifting as a modality for performance training has relied on maximal effort (1 Repetition Max) testing as a means of prescribing and motoring training intensity. However, there are issues of reliability with 1 Rep Max results, as well as logistical constraints.
The recent emergence of barbell velocity tracking devices has opened new avenues of prescribing and monitoring weightlifting training. With the biomechanical foundation of weightlifting being rooted in the impulse-momentum relationship, the use of barbell velocity data for measuring training intensity has gained popularity and become more widely known as velocity-based training (VBT).
While the use of VBT has grown in popularity over recent years, its practical application in sport performance and team training environments is still an experimental concept to many coaches. Furthermore, the prevalence of 1RM testing is so pervasive that almost all popularized training programs reference it as the means of prescribing training intensity. This leaves performance coaches with the task of restructuring their common approaches to training with a new perspective that lacks precedence in comparison to its counterpart.
The Solution:
Although VBT has become more well-known and commonplace in the weightlifting world, it has struggled to reach its potential as a training methodology. While many coaches have been able to grasp some of the elementary benefits of VBT, primarily augmented feedback, there has been relatively little ground made in the way of advanced programming practices and training prescription.
My goal is to highlight the foundations of using weightlifting, and its derivatives, as an effective tool in improving sports performance. Also, to showcase the reasons as to how VBT can benefit the performance coach more effectively than traditional percentage-based training. With this understanding of how VBT fits into the grand scheme of training, we can present solutions as to how previous percentage-based training approaches can be adapted to better utilize the data collected using VBT.
Learning Objectives: