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VELOCITY RESERVE AS A MEAN TO QUANTIFY THE LEVEL OF EFFORT IN
RESISTANCE TRAINING
Preprint · August 2020
DOI: 10.13140/RG.2.2.25488.23040
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Journal of Australian Strength and Conditioning
Velocity reserve as a mean to quantify the level of effort in resistance training.
Journal of Australian Strength & Conditioning. 29(01):29-35. 2021 © ASCA.
From the Field – Directed Topic
VELOCITY RESERVE AS A MEAN TO QUANTIFY THE LEVEL OF EFFORT IN RESISTANCE TRAINING
Clément Chéry1
1Kaizen
Squad, Saint-Clément-de-Rivière, France.
BLUF
From the perspective of prescriptive convenience, biofeedback perceptual comprehension and conceptual relevance,
velocity reserve may represent a better alternative compared to current velocity-based methods when aiming to quantify
a level of effort during a lift.
ABSTRACT
The aim of the present article was to evaluate the strength and weaknesses of three velocity-based methods commonly
used to quantify the level of effort during a lift, and to propose a new metric to regulate training volume. Thus far, the
assessment of a degree of accumulated fatigue in a set is obtained through the use of percentages of velocity loss
(%VL), individualized Exertion – Velocity (E-V) profile, or the effort index (EI). Although these methods are all based on
the decrement of movement velocity during a lift, they do not possess the same relevance in regard to different efficiency
criteria. Among these criteria, the understanding of the biofeedback, prescriptive convenience, and the possibility to
transcribe positive, stable and negative trend in movement velocity needs to be considered. The concept of velocity
reserve (ΔVres) is based on a normalization of absolute %VL, according to a specific minimum velocity threshold
achievable in a lift. This new metric allows for the quantification of a level of effort in relation to a maximal effort threshold
corresponding to task failure, on a 0 to 100 scale. It therefore allows the standardization in the prescription of training
volume, independently of the individual, the load, or the exercise considered. Practitioners aiming to target specific
training adaptations should use %ΔVres loss thresholds lower or equal to 15% to increase athletic related performances.
Medium %ΔVres loss, ranging from 15 to 30%, seems to be more efficient to improve strength. Finally, training for
muscular hypertrophy requires achieving high %ΔVres loss, equal or greater than 50%. On a theoretical plan, the
%ΔVres method constitutes a good alternative to quantify the level of effort during resistance exercise.
Key Words - Velocity-based training, velocity loss, training prescription, training volume.
INTRODUCTION
Strength has been shown to be a key fitness component for many sports disciplines (30). Whether the development of
this capacity is seen as an end in itself, as it is the case in powerlifting and weightlifting, or with the aim to enhance the
performance of another specific athletic skill. Nonetheless, the nature and magnitude of the physical and physiological
adaptations (strength, power, hypertrophy, etc.) will depend on the characteristics of the applied stimulus. Thus, the
best way to obtain a certain result on this final product – called performance – is to shape this stimulus through the
adjustment of several training parameters. A large part of the scientific literature has therefore focused on determining
the optimal configuration of intensity, volume, or density of training that would best meet specific adaptive objectives.
Traditionally, general recommendations related to how to adjust these different parameters are often based on
percentages of the maximal load that can be lifted (%1RM) (19).
Nonetheless, this methodological approach of prescribing intensity and volume of training present some flaws, as it
does not take into account some key aspects of sport performance: 1) the change in performance output due to the
variation of fatigue levels (13) 2) the inter-individual variability in strength endurance (22), and 3) the inter-individual
differences in the magnitude of physiological adaptation that occur during the training process (15). Therefore, this
traditional way of programming base the intensity of training on an estimate of the individual's strength level which may
be inadequate. It is also inferred on the athlete’s ability to produce a certain volume of repetition with a given load. Far
from denying the importance of a better control over training parameters, the inter and intra individual biological
variances in maximal strength, strength endurance and adaptive rate leads us to better consider the principle of
individualization. Thus, there is a need of refining our methodological approach of strength training, to better quantify
this biological response and to allow individualization within and between sessions.
Recently, a new conception of strength training has emerged and gained popularity among the strength and conditioning
community. This methodology, often referred to as velocity-based training (VBT), uses concentric movement velocity
as a marker of intensity and fatigue by taking advantage of the unique characteristics of the Load - Velocity (L-V)
relationship (1) and of the Exertion – Velocity (E-V) relationship (20). Among other attributes, the L-V relationship is
known to be remarkably linear (2,3,29), stable (11,28) and less sensitive to strength changes than %1RM. Such
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relationships allow practitioners to reliably prescribe a training intensity that matches the athlete’s capability of the day
(5,6) or evaluate athlete’s readiness (16).
The interaction between intensity and volume reveals a third variable that researchers has termed as the level of effort.
The level of effort has been defined as the actual degree of demand in relation to the current possibilities of a given
subject (12). When applied to resistance training, this concept should be understood as the actual number of repetitions
performed in a set in relation to the maximum number that can be completed before reaching task failure (20). Controlling
the level of effort during a lift is crucial to avoid task failure and to better control the magnitude of accumulated fatigue
within a set. Interestingly, training to failure seems not to provide clear additional gains on performances compared to
non-failure protocols (4). Indeed, an increasing amount of evidence tend to show the existence of a curvilinear
relationship (an inverted “U”-shaped curve) between training volume and the adaptive response in strength gains (23),
suggesting the existence of a point of diminished returns. There is therefore a gap between current field practices and
scientific research regarding to the correct level of effort to program in resistance exercise. Indeed, the RM method is
commonly used in the strength and conditioning community, despite bringing the athlete to reach his limits in every sets
of an exercise. This method requires finding the maximum load that can be lifted for a given number of repetitions (i.e.,
3 RM, 5 RM, 8 RM, etc.), and hence to terminate the set with no repetitions left in reserve. In this regard, it has been
proposed to use movement velocity to better control the level of effort during a lift and thus avoiding task failure. Indeed,
gradual decrement in movement velocity has been shown to be highly correlated to the building of neuromuscular fatigue
(26). Furthermore, measuring concentric velocity during a lift allows to gauge proximity to task failure and thus to assess
the level of effort experienced by athletes (10). Consequently, movement velocity can be used to indirectly regulate
training volume during resistance exercise. This way of prescribing volume appears to be superior, as it allows to
integrate a part of autoregulation into the training process. Compared to traditional methods, a velocity-based approach
allows for a better inclusion and management of several individual variables, such as strength endurance capacity or
level of readiness.
Therefore, the aim of this article was to review three different velocity-based methods commonly used to quantify the
level of effort during resistance exercise, and to propose a novel metric to assess this crucial training parameter.
VELOCITY-BASED METHODS COMMONLY USED TO QUANTIFY THE LEVEL OF EFFORT
To date, three velocity-based methods aimed to quantify the level of effort have been proposed:
•
•
•
The estimation of a number of repetitions in reserve (RIR) through the use of individualized E-V profile (10);
The use of velocity loss percentage (%VL) (7,21,23,26,27,31);
The use of the effort index (EI) (24).
An E-V profile is based on the decrement of velocity recorded during a test of maximum number of repetition (RM) on a
given exercise. These profiles are supposed to quantify a level of RIR at any time in a set, based on a velocity
measurement. However, there are several problems with this approach:
1. The estimate of the number of RIR obtained by this method is very sensitive to the duration of the inter-repetition
rest period used. Indeed, the intra set temporal layout of a resistance exercise protocol affect the level of
strength recovery consecutive to the execution of one or several repetitions, and thus influences the rate of
velocity drop occurring during a set (8). Predictions made with the use of an E-V profile will therefore vary
substantially as a result of rest periods of different durations.
2. This method reveals poor repeatability, even when the inter-repetition rest period is controlled (Figure 1). This
affects the level of reliability and validity of the methodology.
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Journal of Australian Strength and Conditioning
Figure 1 - Individual E-V profile based on 11 RM tests completed with a 7RM load (6) and a 4RM load (5), on the back
squat exercise. Individual measurement points are shown in red with associated 1-sigma error in black. The relation
between average velocity values and reserve repetition is given in blue.
3. Finally, this method does not take into account the phenomenon of post-activation potentiation (PAP), which further
alters the prediction model. PAP is described as an increase in muscle twitch and low-frequency tetanic force after
a conditioning contractile activity (25). Indeed, during a set, it is not uncommon to notice an increase (and not a
decrease), of the movement velocity. While this phenomenon is completely natural and unrelated to measurement
errors, it does not follow the initial assumption of the E-V profile-based method, which state that the evolution of
the movement velocity during a set should always be negative. Resulting in paradoxical situations where the
estimates of the number of RIR increase as the set progress.
The percentage of velocity loss (%VL) method is easier to integrate into the training process than the E-V profile basedmethod, since it does not require the athletes to undergo a maximum-effort test beforehand. All is needed to apply the
%VL method is a measuring device that allows to display this metric in real time. A %VL is the quotient of the difference
between the velocity of the first (Vfirst) and the last (Vlast) repetition of a set with Vfirst, expressed in percent:
%VL = 100*(Vfirst – Vlast) / Vfirst
In addition, many studies have looked at the impact that different %VL have on kinetic and kinematic variables, athletic
related tests and on certain physiological components. In that respect, low to moderate percentages of velocity loss (1025%VL) appear to improve the magnitude of strength gains in a similar if not superior way than higher percentage of
velocity loss (30-50%VL), despite enabling a much lower volume of repetition to be completed (21,23,27). The better
efficiency of lower %VL in regard to the development of strength seems to be mediated by a better maintenance of
kinetic and kinematic output across sets of an exercise (31), and a lower reduction of myosin heavy chain IIX (21).
Improvement in athletic related performances seems to comply with the same general rule of “lower is better”, where
%VL as low as five percent have been shown to promote a better training efficiency (7). Conversely, higher percentages
of velocity loss are more effective to improve hypertrophy, as it allows for a greater volume of repetition to be performed
before ending a set and thus inducing higher levels of mechanical tension (21). This metric provides coaches with
valuable information, as it allows to adjust training volume according to the expected output in terms of physiological
adaptations or performances. However, this method prevents practitioners to easily and precisely establish a degree of
proximity to task failure, as the level of %VL achieved when reaching this point vary depending on the exercise or the
load used. Therefore, there is a loose correspondence between the %VL reached at task failure on a squat and benchpress, or between the %VL reached at task failure for two different load (e.g. 60% 1RM and 80% 1RM) on a unique
exercise (26).
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The effort index (EI) is defined as the product of the fastest velocity (Vbest) on the first set of an exercise by the average
velocity loss (%) over all the training sets (24):
EI = Vbest * average %VL
Although this index is interesting and valid as part of a longitudinal monitoring of training load, the EI will not inform the
practitioner of a degree of proximity to task failure during a set. Although having the merit of taking into account both
the volume and the intensity in its calculation, the EI nevertheless constitutes a conceptually more complex - and
therefore less comprehensible - biofeedback than %VL or RIRs for athletes.
In the light of this analysis, it becomes possible to draw up an inventory of the efficiency standards of a method aiming
to quantify the level of effort during a resistance training exercise:
•
•
•
•
•
•
Valid and reliable to assess a level of effort during a lift,
Allow to gauge the evolution of fatigue in relation to a maximal effort threshold,
Allow a comparison of the level of effort regardless of the individual, intensity or the exercise,
Allow to standardize the prescription of a level of effort for a group of athletes,
Based on a theoretical model accepting negative, positive, and stable variations in movement velocity,
Constituting understandable and motivating feedback for athletes.
THE CONCEPT OF VELOCITY RESERVE
With regard to the efficiency criteria that had just been described, the aim of this article is to provide practitioners with
an alternative to current velocity-based methods used to quantifying the level of effort by compensating for their
respective biases. It therefore introduces the concept of velocity reserve (ΔVres), calculated from the difference between
Vfirst and a minimum velocity threshold (MVT). The MVT corresponds to the velocity reached on the last successful
repetition of a RM test carried out with a maximum velocity intent (17). This threshold is individual and exercise specific.
However, the reliability of the velocity achieved at this threshold has been shown to be relatively poor (CV > 18.3%, ICC
< 0.60) (9). Thus, the decision to recourse to a RM test to determine a MVT value must be carefully considered, in
regards to the risk-benefit balance. Practitioner should therefore consider the use of other markers, in order to avoid
unnecessary fatigue. Thus, the velocity reached on a 1RM test (v@1RM), or generic MVT value of an exercise can be
used interchangeably with values obtained from the RM test, as suggested by other authors (9). MVT value could then
be adjusted subsequently on an individual basis, if an athlete reaches a lower velocity threshold during training. A value
of ΔVres can be obtained through the use of the following formula:
ΔVres = Vfirst – MVT
The level of effort is then quantified by translating Vlast as a percentage of ΔVres (%ΔVres), according to the following
equation:
%ΔVres = 100 * ((Vlast - MVT) / (Vfirst - MVT))
Figure 2 illustrates how the %ΔVres evolves in three different scenarios where movement velocity follows a negative,
stable, or positive trend. Inferences made to explain the trend in movement velocity through a set are based on the initial
assumption that each repetition are performed with maximum velocity intent. This is a fundamental prerequisite of the
VBT methodology that enable practitioners to acquire reliable data to prescribe, monitor and regulate important training
parameters.
Figure 2 - Fictive case scenario illustrating how %ΔVres evolve during negative (A), stable (B) and positive trend in
movement velocity during a set of five repetitions with a generic MVT of a back squat exercise.
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In the first scenario (graph 1-A), the change in movement velocity through time is negative. This can be interpreted as
a sign of the development of fatigue. In this case, the %ΔVres marker therefore also evolves negatively. The second
scenario (graph 1-B) illustrates a situation where there is no increase or decrease in movement velocity. In the absence
of an accumulation of fatigue, the values of %ΔVres remain stable. Finally, in the last case (graph 1-C) the evolution of
movement velocity through time is positive. This trend suggests the installation of a potentiation state or of a better
technical efficiency allowing the athlete to generate supra maximal values of %ΔVres. Supra maximal values can be
observed because the method used to calculate a %ΔVres takes the velocity of the first repetition as a reference. An
alternative method of calculation can be considered if the values of %ΔVres are wanted to be always inferior or equal
to one hundred per cent, by selecting the fastest repetition of a set as a reference. A %ΔVres–based method therefore
accepts negative, positive, and stable variations in movement velocity, and therefore allows to grasp the phenomena of
fatigue and potentiation that can regularly be observed in field situations. The calculation of a %ΔVres also allows the
practitioner to gauge the evolution of fatigue in relation to a maximum effort threshold, the MVT. It therefore constitutes
a more readable feedback than absolute %VL, since one hundred per cent loss of ΔVres (or reaching 0%ΔVres)
corresponds to the achievement of task failure, or of 0RER. Additionally, the quantification of %ΔVres enables to
standardize a level of effort, and therefore to compare the degree of fatigue independently of the individual, the load, or
the exercise considered. This makes it easier for coaches and athletes to gauge the level of effort achieved in an
exercise by referring to a single model based on a 0 to 100 scale of effort.
Recommendations on how to adjust and interpret this new metrics can be made in order to guide coach and athletes
into their practice. Numerous studies have investigated the association between various %VL in resistance exercises in
relation to kinetic, kinematic, metabolic and hormonal variables (7,21,23,26,27,31). Thus, a normalization of absolute
%VL allows to extrapolate the results of these studies to the %ΔVres method. Weakley et al. (31) provides valuables
insights on how the measurement of a %ΔVres can be used to modulate kinetic and kinematic output, in accordance to
specific training purposes. In this study, researchers employed a randomized crossover design to test the effect of
different %VL thresholds (10%, 20% and 30%) on kinetic, kinematic, and repetition data during a free weight back squat
exercise. Sixteen resistance-trained males were recruited to complete three resistance training protocols composing of
five sets, starting at mean concentric velocity of 0.70 m·s-1 ± 0.01 m·s-1. In order to conduct the present analysis, a
generic MVT of 0.24 m.s-1 measured on free weight back squat exercise from Banyard et al. (1) study was used.
Interestingly, the MVT value reported by Banyard et al. is in line with the findings of Zourdos et al. (32), which also
assessed a full depth back squat on a 1RM test. By plotting mean values of Vfirst and Vlast of each corresponding %VL
from Weakley et al. with the MVT value from Banyard et al. into the %ΔVres formula, the following associations was
made between three %ΔVres loss thresholds and specific kinetic and kinematic output. Thus, low %ΔVres loss
thresholds (i.e 15% > 30% > 45%) induce a better maintenance of mean and peak velocity and power across the sets.
Conversely, high %ΔVres loss thresholds (i.e 15% < 30% < 45%) allows for a greater number of repetitions to be
completed before ending a set, resulting in a significantly higher training volume. Therefore, minimal %ΔVres loss (i.e <
15%) might be more appropriated when aiming to develop power and athletic related performances, as outlined by
previous study (7). Prescribing low to medium %ΔVres loss (i.e 15 – 30%) may be an efficient way to target strength
adaptations, by mitigating the impact of neuromuscular fatigue on kinetic and kinematic output and enhancing exercise
quality (21,23,27). Higher decrement in movement velocity during an exercise can mitigate the magnitude of strength
and power adaptations but seems to be a more effective stimulus when it comes to generate muscular hypertrophy
(21,23,27). High %ΔVres loss (i.e > 50%) should therefore be utilized when muscle mass development is set as the
primary goal of the training cycle. However, avoiding task failure during training is a vital concern in order to limit the
impact of an exercise on post-workout recovery rate. Thus, practitioners should employ pre-determined cut-off velocity
thresholds (e.g a mean concentric velocity of 0.35 m·s-1 in the back squat exercise) to terminate a set before reaching
a point of acute overreaching. Alternatively, a hybrid approach can also be considered when aiming to target the
concurrent development of strength and hypertrophy, by utilizing medium %ΔVres loss (i.e 30 – 50%). This training
objective, often referred to as “functional hypertrophy”, is paramount for many disciplines where strength and
hypertrophy are important determinant of performance. The different velocity zones that can be used to regulate training
volume in accordance with specific training adaptations are summarize in the Figure 3, in the form of an E-V continuum.
Figure 3 - Exertion – Velocity continuum based on %ΔVres loss.
However, caution should be used when implementing specific training zones of the %VL or %ΔVres loss method with
loads higher than 85%1RM. Indeed, such training intensity does not allow for a sufficient volume of repetitions to be
built through a set to be considered as an effective stimulus for hypertrophy. Furthermore, as stated by the Force –
Velocity relationship, lifting against heavy loads cause muscle fibres to contract at a slow rates in order to generate high
level of force (14). While the intention to move the load as fast as possible is important to target power adaptations,
actual movement velocity is still important to elicit high-velocity specific neuromuscular adaptations (18). Therefore, the
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Journal of Australian Strength and Conditioning
E-V continuum presented above (Figure 3) does not reliably transcribe the adaptations that can occur when training at
high intensity (i.e > 85%1RM), as heavy load mainly elicits maximal strength development. At high intensity, the
integration of biofeedback relative to the quantification of change in movement velocity or power should only be used to
motivate athlete to maintain high level of kinetic and kinematic output.
Notwithstanding the fact that the present method is based on a normalization of absolute %VL and should therefore
theoretically keep some of it previously established properties, more research is needed to establish the validity and
reliability of %ΔVres to quantify the level of effort.
PRACTICAL APPLICATIONS
The regulation of volume in resistance training is paramount when aiming to generate specific training adaptations. The
quantification of the level of effort by monitoring velocity loss in a set appears to be a method of choice to control this
parameter. Several velocity-based methods have been proposed to assess the level of fatigue accumulated during a
set. These include: percentage of velocity loss (%VL), estimates of repetitions in reserve (RIRs) calculated with
individual E-V and the effort index (EI). Based on the different strength and weaknesses of these methods, several
criteria of efficiency emerge. The validity and reliability of such markers should always be the prime criterion to be met
before inclusion into practice, as poor validity and reliability may severely decrease adherence to VBT applications.
However, any marker of effort should also constitute an understandable and motivating biofeedback for the athletes, in
order to elicit better performances. Regarding to this point, gauging the evolution of fatigue in relation to a maximal effort
threshold appears to have a lot of significance from an athletes and coach perspective, as both can relate to common
field of interoceptive sensations from their own training experiences. From a prescription standpoint, a marker of effort
should allow to standardize the prescription of a level of effort for a group of athletes, regardless of the individual,
intensity or the exercise. Finally, any marker of effort should be based on a theoretical model accepting negative,
positive, and stable variations in movement velocity, as all of these scenarios are likely to take place in practice. The
present article introduces the concept of velocity reserve as a novel way to assess the level of effort. This new method
is based on a normalization of absolute %VL, in relation to a maximal effort threshold, the MVT. Preliminary
recommendations can be made to guide practitioners aiming to integrate a velocity-based approach to orientate training
toward specifics objectives. The development of power adaptations requires minimal loss in kinetic and kinematic output
during a set of an exercise. In this regard, the use of low percentages of ΔVres loss (<15%) is recommended. Medium
%ΔVres loss, ranging from 15 to 30%, seems to be more efficient to improve maximal strength. In contrast, the
achievement of high level of effort during a lift seems to improve the magnitude of hypertrophic adaptation. Reaching
high %ΔVres loss (> 50%) should therefore be utilized when training to improve muscle mass. Although, it must be
noted that large decrement in movement velocity during an exercise is known to impair the magnitude of strength and
power adaptations. The use of specific velocity cut-off thresholds should also be considered as a complementary
strategy when high %ΔVres loss are used, in order to avoid task failure and the impairment of post-workout recovery
rate. However, caution should be used when implementing the %ΔVres method into training, as more research is
needed to assess it validity and reliability to quantify the level of effort during resistance exercise.
Acknowledgements
There is no conflict of interest and no funding was received for this study. I would like to thank Ludwig Ruf, Jean Chéry,
Bradley Wallace Cole and Pierre Debraux for their constructive criticisms of the manuscript.
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