Adam C. Stewart
People are starting to prefer self-regulating load regulations, because the limits of the classic percentage load graphs are known. However, a Metaregression has updated these load graphs, so this article explains whether the percentage prescriptions are worth revisiting.
Note: This article was the MASS Research Review cover article for December 2023 and is a review of a recent article by Nuzzo et al. If you want more content like this, subscribe to MASS.
Summits
The researchers performed a meta-regression to quantify the number of repetitions that can be performed at specific percentages of 1 rpm.
On average, with moderate loads, it was possible to perform more repetitions than previously thought. There is a large interindividual variation in repetition performance, and this repetition performance is exercise-specific.
This meta-regression represents a major update of the load graph created in the early 1990s. Percentage training with load graphs has generally fallen out of favor, but updates to this meta-regression may allow for more accurate percentage training in group settings.
When I first got serious about training, I knew everything. I failed every set, ate a billion calories seconds after the workout was over, and made sure that the workout was the most important part of my day. I would also use loading graphs to program the number of repetitions to be performed at a given percentage of 1 rpm (for example, 12 repetitions at 70% of 1 rpm). If I did 10 repetitions at a given load, I would immediately switch to the percentage graph and work backwards to determine my new Maximum. These graphs were based on scientific evidence, I guessed, so the programming and the 1WD predictions were correct. Isn’t that right?
Years later, I learned that these graphs were based on only a few studies by a single research group (2, 3). In hindsight, the lack of scientific rigor associated with these graphs made sense, because I often performed a different number of repetitions than suggested in the table. In addition, there is a high degree of interindividual variation in the number of repetitions performed at a certain percentage of 1 rpm (4, 5) and repetition performance can vary from day to day within a person. We now have self-regulation tools such as repetitions in reserve (RIR) (6) and speed-based training (7) which offer alternative options for load prescription. Nevertheless, a load chart can provide a good starting point, which can be useful for a new athlete or for a coach who has a ton of athletes and not enough time or resources to perform speed-based training or RIR. (1) uses data from numerous studies to create an updated load graph and quantify the interindividual Variation associated with its values.
Objective and assumptions
Objective
The meta-analysis currently under review had three main objectives:
- Provide a complete update of the load tables to determine on average the number of repetitions that can be performed at specific percentages of 1 rpm
- Examination of the degree of interindividual variation of the repetitions performed at certain percentages of 1 rpm
- It should be determined whether different moderators, such as gender, exercise and training status, influenced the repetitions performed.
Hypothesis
As usual in a meta-analysis, the researchers did not hypothesize.
