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TRAINING TAKEAWAY:

On a per set basis, the reps early in a set will be the most efficient for strength gains. However, multiple factors play into this because volume and proximity to failure are both changing as reps are accumulated.

Background

Strength is a measure of maximal force production, and force production is highest early in a set before fatigue rises. For this reason, from a force production perspective, the reps early in a set are the most specific for strength.

However, a lot of factors go into strength. This includes (but is not limited to) muscle size, muscle architecture, neuromuscular characteristics, skill, and psychological factors.

Given the complexity of strength, we should lean into the longitudinal training data to see how this plays out. Luckily, a recent meta-analysis by Zhang and colleagues provides insight into the research in this area.

Study Overview

Zhang and colleagues meta-analyzed nine velocity loss studies that measured one repetition maximum (1RM) strength. In all of these studies, strength gains were compared between two or more groups differing in velocity loss while controlling the number of sets and load (% of 1RM).

Velocity loss is the percentage decrease in barbell velocity that is allowed before a set is terminated. For example, if the fastest rep in a set is 0.50 m/s and an individual is training at 30% velocity loss, the set would be terminated once a rep is 0.35 m/s or slower. While far from perfect in controlling repetitions in reserve (RIR), velocity loss on the group level provides a decent comparison of different proximities to failure. In other words, a group training at a higher percentage velocity loss percentage will have a lower average RIR than a group training at a lower percentage velocity loss.

The primary analysis the authors performed was a dose-response analysis. In this analysis, velocity loss was treated as a continuous variable and was used to predict 1RM strength gains in kg. As seen below, this analysis revealed an inverted-U shape, with strength gains peaking around 20-30% velocity loss.

Before reading too much into these findings, we need to acknowledge an important consideration of the design of these studies. All of these studies isolate the variable velocity loss while controlling the number of sets. For example, a group training with 40% velocity loss and a group training with 20% velocity loss will both perform three sets per session. Importantly, this results in greater reps per set in the higher velocity loss condition. While set volume is controlled, relative volume (% of 1RM x sets x reps) is considerably higher in the higher velocity loss conditions. For example, one of the included studies compared 10% and 30% velocity loss, and the latter group performed more than twice the relative volume. Ultimately, this design makes it unclear whether 20-30% velocity loss is indeed the sweet spot or if this is simply the appropriate volume sweet spot.

The authors recognized this limitation and performed a second analysis we’ll refer to as the efficiency analysis. In this analysis, velocity loss was again treated as a continuous variable. However, instead of 1RM gains serving as the dependent variable, the authors used 1RM gains (in kg) divided by the total repetitions performed.

The efficiency analysis revealed clear diminishing returns of higher velocity loss training. However, this analysis is also confounded by differences in relative volume. When viewed through the volume lens (i.e., that lower velocity loss groups completed lower volumes), these results make intuitive sense: doing some volume will be way better than no volume, but additional volume will become less and less efficient.

What Does This Mean for Training?

In short, this meta-analysis found that A) moderate (~20-30%) velocity loss thresholds generally led to the greatest 1RM strength gains and B) lower velocity loss thresholds are the most efficient. However, these findings are confounded by volume as lower velocity loss groups also completed lower volumes. For this reason, we can’t make strong conclusions about optimal proximity to failure for strength from this meta-analysis. Thus, we have to incorporate other areas of research to come to tentative conclusions.

First, we can look at velocity loss research that controls relative volume by having the lower velocity loss group perform more sets. To my knowledge, there’s only two studies (one, two) of this nature, and the strength test in one of them was unilateral leg press. Nonetheless, neither of these studies found a between-group difference in strength gains.

Next, we can turn to the literature examining the influence of volume on strength. In short, this literature seems to indicate that, to some degree, more volume leads to greater strength gains. While this relationship doesn’t seem to be extremely strong, I would at least expect that additional volume would be beneficial in the ranges used in the studies in the Zhang meta-analysis (range: 4-12 sets/week; mode: 6 sets/week).

Since velocity losses greater than ~30% led to less strength gains, that means that either the additional volume was too much or high velocity losses are inherently counterproductive for strength. I don’t think we can make a truly evidence-based claim for which is correct, but I have a hard time believing that the former is the case. This is supported (to some degree) by the efficiency analysis Zhang and colleagues performed.

Although I’m trying to keep this article on the shorter side, I should briefly mention a few important limitations to keep in mind: 1) these studies utilized Smith Machine and not free-weight lifts; 2) many of these subjects had resistance training experience but their strength levels are far from the average reader of this article; 3) these studies are short-term and their results may not apply to longer time scales, especially since hypertrophy likely plays a greater role in strength with increasing time scales.

Practical Application

In the short-term, there doesn’t seem to be anything inherently beneficial to close proximities to failure for strength gains. (Note: this is at a given load, and load-mediated decreases in RIR are a different story.) So, if the proximity to failure being used seems to lead to disproportionate fatigue and thus is negatively impacting the volume or loads that can be used, it may be worth experimenting with training protocols that increase average RIR.