The Power of EPV Part 2: Context is key

About the Authors

Dr. Daniel Cohen is the co-founder of ForceDecks, as well as a consultant and researcher with more than 20 years of experience evaluating healthy and injured elite athletes using force platforms. He currently works with teams across the English Premier League, NBA, NFL and NHL. He is also an adjunct associate professor of Human Performance and Innovation at the University of Limerick’s School of Education.

Dr. Morgan Williams is a data scientist at VALD and adjunct associate professor at Griffith University’s School of Health Sciences and Social Work. As part of the VALD Data Science Team, he uncovers new insights into VALD data and identifies how it can be used to enhance practice.

In The Power of Eccentric Peak Velocity (EPV): Part 1, we introduced EPV as a key indicator of data quality, countermovement jump (CMJ) technique, strategy and lower-limb function. Here, we describe influences on EPV and highlight why this metric should be a “go-to” in force plate CMJ and single leg jump (SLJ) assessments.

The Origins of an EPV Target

Cohen et al. (2020) first advocated the use of a target EPV, an important shift from relying only on jump height to gauge intent. This modernizes how we provide feedback on jump execution, aligning it with the comprehensive analysis of the movement that force plates provide.

[An “EPV target”] modernizes how we provide feedback on jump execution…

Importantly, the use of EPV recognizes the insights provided by specific eccentric phase metrics. It provides a check on the intensity of eccentric phase execution and an indication of whether the countermovement is being performed at or near maximum capacity – critical to valid assessment of those metrics.

As emphasized in Part 1, “you wouldn’t only test a car’s braking performance at low speeds” and expect to understand its full capabilities.

What Is an Acceptable EPV Target?

A target value of -1.2m/s emerged from force plate assessments of professional soccer players undergoing rehabilitation after anterior cruciate ligament reconstruction (ACLR) (Cohen et al., 2020). These athletes had significantly slower EPV values (-1.0m/s) than those recorded in their healthy counterparts (-1.4m/s).

[Athletes in rehabilitation] had substantially slower EPV values (-1.0m/s) than those recorded in their healthy counterparts (-1.4m/s).

This slower EPV from the rehabilitation group likely reflects inefficient movement execution governed by injury-related factors.

EPV in Rehabilitation

In rehabilitation, EPV is not only a measure of physical capacity to descend rapidly and create large deceleration demands under the constraints of injury, but also a reflection of the athlete’s confidence or willingness to expose themselves to these demands (Cohen et al., 2020; Taberner et al., 2020) – “an objective marker of a subjective state.”

In rehabilitation, EPV is not only a measure of physical capacity… It also reflects the athlete’s confidence…

These self-imposed limitations on the execution of the countermovement typically manifest as a slower EPV and, potentially, a shallower countermovement depth. It is important to monitor both metrics, keeping in mind that countermovement depth typically recovers earlier in the rehabilitation process than EPV.

Unpublished data from Dutaillis et al. (2025) (shown below) illustrate the mean EPV trajectories for CMJ and SLJ from 20 to 60 weeks post-ACLR. The progressively faster EPV across this period coincided with improvements in other jump performance metrics, as well as patient reported outcome measures (PROMs) of confidence and knee function.

As athletes advance through rehabilitation, you should expect to see progressive increases in EPV. These are primarily driven by:

1. Reduced Intrinsic Constraints: As limiting factors such as pain, fear or instability diminish, the willingness to descend quickly increases.
2. Reconditioning: Neuromuscular adaptations to training that enhance vertical deceleration capacity.

In early rehabilitation, we often see large increases in EPV (particularly in SLJ), driven more by the reduction of these constraints. However, as rehabilitation progresses, improvement slows and reconditioning becomes the dominant contributor.

Dynamic EPV Targets in ACLR Rehabilitation: Adapting to Recovery

These trajectories show the dynamic nature of EPV during rehabilitation, demonstrating that it is inappropriate to rigidly apply a single global EPV target. Instead, any target should be adjusted for the athlete’s recovery stage and revised to reflect their progress and known or estimated pre-injury capacity.

Early Rehabilitation: Prioritizing Caution and Constraints Over Speed

In the early stages of rehabilitation, athletes are likely to experience discomfort and lack both the confidence to execute a rapid countermovement and the capacity to cope with the associated deceleration demands. A relatively slow EPV is expected, and caution should be exercised in cueing the athlete to descend “fast.”

[In early rehabilitation], best practice may involve incorporating designated “submaximal jumps” which strategically avoid [cueing to evaluate self-constrained technique].

In this phase, best practice may involve incorporating designated “submaximal jumps” (Taberner et al., 2020), which strategically avoid height and velocity cues, allowing evaluation of self-constrained execution. A case example of the EPV recovery trajectory during ACLR rehabilitation, involving changing cues across the pathway, is shown below.

Precision EPV: Your Own Data and Best Estimates

Selecting an appropriate EPV target in rehabilitation is easier when routine CMJ monitoring is in place, providing pre-injury data and reducing the need for external reference values.

It is nonetheless useful to understand how group and athlete factors influence EPV. When pre-injury data is not available, which is often the case, recognizing how these factors typically shift EPV values is critical for estimating whether an achieved EPV reflects a true recovery of capacity and willingness.

Beyond the Baseline: Rethinking EPV Targets in ACLR Rehabilitation

Some athletes surpass their pre-injury EPV in late-stage ACLR rehabilitation. We typically see this trend in the following cases:

• They had minimal exposure to explosive strength or reactive work prior to injury, but positively adapted to it during rehabilitation.
• They were newly introduced to the “jump high and fast” CMJ cue during rehabilitation.

Consequently, their pre-injury EPV does not always represent the optimal return-to-capacity target.

Influence of performance and injury-related factors on EPV.

EPV in Healthy Athletes

What is an acceptable EPV to mark sufficient intent in healthy athletes? Sports-specific EPV values from a selection of the normative data reports in VALD Hub are presented in the figure below.

The observed differences in EPV among athlete groups are expected and align with the varying physical demands of different sports, competitive levels, training exposure and individual responses to strength and power conditioning (Cormie et al., 2010). In “healthy” athlete populations, as in rehabilitation, a single EPV target is not applicable across all sports, levels and ages.

In “healthy” athlete populations, as in rehabilitation, a single EPV target is not applicable across all sports, levels and ages.

While these athletes were likely not all given the same cues – the effect of which we discuss below – these sport-specific measures of central tendency and dispersion remain a useful reference resource.

New Technology Calls for New Cues

Historically, the CMJ has been included in test batteries as an indicator of stretch-shortening cycle (SSC) function and muscular power. However, until recently, it was typically performed using contact mats or optical devices, providing only flight time output. With jump height being the only measured metric, “jump as high as you can” was naturally the most common instruction given, reflecting a focus on the performance outcome, with no cues on movement execution.

SSC function was estimated by the difference in jump height achieved using a countermovement vs. the squat jump (without a countermovement). However, jump execution, force production and SSC function within the movement – metrics that force platform assessment generates – were not available.

In contemporary performance, health and tactical environments, with access to force plates, many practitioners use an additional instruction, adding “AND fast” to “jump high.” This instruction does not specifically focus attention on the descent.

However, it has a greater impact on eccentric than concentric phase execution, resulting in a larger increase in EPV compared to concentric peak velocity. Pérez-Castilla et al. (2021) demonstrated this in a randomized study (shown in the following figure).

What to Cue and What Not to Cue

Lack of velocity cueing appears to increase the likelihood of inconsistent execution of the downward phase. This can manifest in both poor values and high variability for EPV and related “downstream” variables such as eccentric deceleration rate of force development and flight time to contraction time ratio (FT:CT).

The trial-by-trial data of an athlete who did not receive specific velocity instruction at the beginning of the assessment (shown in the figure below) exemplifies this.

While a lack of cue standardization and low familiarity with the assessment increase the likelihood of variability across trials and reduce reliability, this data shows that variability in test execution (EPV) disproportionately impacts eccentric metrics.

…inconsistency in [EPV] can be misinterpreted as inherent poor reliability, when often the issue is inadequate cueing…

Lonergan et al. (2025) highlighted that inconsistency in these metrics can be misinterpreted as inherently poor reliability, when the issue is more often inadequate cueing or a suboptimal testing culture (see below). It also results in a value which does not accurately reflect maximal SSC function, undermining the interpretation of profiling assessments – illustrating the “EPV as a gatekeeper” concept described in Part 1.

When Velocity Cues Matter Less (And When They Still Do)

Some practitioners still prefer to use a “jump high” cue, aimed at allowing the athlete to use their preferred “strategy. Experience and evidence suggest velocity cues may have less impact on intent in environments with a well-established and competitive assessment culture (Howarth et al., 2022).

Consistent assessment and a competitive, informed and feedback-rich environment – features that promote athlete buy-in – appear to drive adequate and consistent EPVs, even without specific velocity cues. Athlete familiarity and engagement with the assessment process also drive maximal intent and EPVs.

Nonetheless, in athletes who are less motivated or less familiar with the assessment, cueing “jump high and fast” can improve EPV, as well as its consistency and reliability, and is therefore recommended to reduce the likelihood of low EPV values.

…cueing “jump high and fast”…[is] recommended, to reduce the likelihood of low EPV values.

A low mean EPV or large inter-trial variation in EPV in healthy athletes given this cue could indicate a lack of motivation or a deliberate pacing strategy – holding back maximal effort until the last trial. However, it could also indicate poorly executed or failed analysis trials that might need editing or exclusion from your database.

In contrast, self-regulated velocity jumps are appropriate and even recommended in early rehabilitation to allow the expression of the athlete’s willingness to create deceleration demands as well as their capacity.

Variability: Nuisance or Nuance

In a healthy athlete, a large across-trial variability (high coefficient of variation) and low EPV would be considered “poor quality” and potentially warrant deletion of trials. In contrast, in rehabilitation, variability and the EPV pattern across trials can provide real-time insight into an athlete’s confidence in performing a rapid countermovement and how that evolves, or regresses across trials.

This also highlights the importance of not only considering mean values in the rehabilitation setting but also peak values, as in profiling. Once the environment and conditions are right, valuable insights into an athlete’s status can be revealed through interpreting the within- and between-session variability and how this changes longitudinally.

No Magic Numbers

We have shown that, since a range of factors influence EPV, there is no EPV “magic number” to universally target – context is key.

This begs the question: is -1.2m/s an appropriate target?

• For healthy athletes, -1.2m/s is a good start, though it may fall below many sports’ Norms.
• For most athletes in early-stage ACLR rehabilitation, -1.2m/s may be too aggressive.
• For an elite athlete with a pre-injury value of -1.9m/s, in early-stage ACLR rehabilitation, -1.2m/s is a reasonable target.

In a future blog, we will dive deeper into VALD’s Data Lakehouse, focusing on EPV’s threshold as a data hygiene application.

If you would like to learn more about ForceDecks, explore how it can enhance your practice, or dive deeper into EPV and related metrics, get in touch with our team.

References

1. Cohen, D.D., Burton, A., Wells, C., Taberner, M., Alejandra Diaz, M., & Graham-Smith, P. (2020). Single vs double leg countermovement jump tests: Not half an apple! Aspetar Sports Medicine Journal, 9, 34–41. https://www.researchgate.net/publication/339831206
2. Taberner, M., Van Dyk, N., Allen, T., Jain, N., Richter, C., Drust, B., Betancur, E., & Cohen, D. D. (2020). Physical preparation and return to performance of an elite female football player following ACL reconstruction: A journey to the FIFA Women’s World Cup. BMJ Open Sport & Exercise Medicine, 6(1). https://doi.org/10.1136/bmjsem-2020-000843
3. Dutaillis, B., Collings, T., Bellinger, P., Timmins, R. G., Williams, M. D., & Bourne, M. N. (2025). Time‐course changes in lower limb strength, vertical jump metrics and their relationship with patient reported outcomes following anterior cruciate ligament reconstruction. Knee Surgery, Sports Traumatology, Arthroscopy, 33(7), 2684–2699. https://doi.org/10.1002/ksa.12694
4. Cormie, P., McGuigan, M. R., & Newton, R. U. (2010). Changes in the eccentric phase contribute to improved stretch-shorten cycle performance after training. Medicine & Science in Sports & Exercise, 42(9), 1731–1744. https://doi.org/10.1249/MSS.0b013e3181d392e8
5. Pérez-Castilla, A., Rojas, F. J., Gómez-Martínez, F., & García-Ramos, A. (2021). Vertical jump performance is affected by the velocity and depth of the countermovement. Sports Biomechanics, 20(8):1015–1030. https://doi.org/10.1080/14763141.2019.1641545
6. Lonergan, B., Cohen, D. D., Williams, S., Lawson, R., Howarth, D. J., Johnson, D. M. (2025). Inter-day reliability of countermovement jump metrics in elite academy soccer players. International Journal of Strength and Conditioning. https://researchportal.bath.ac.uk/en/publications/inter-day-reliability-of-countermovement-jump-metrics-in-elite-ac
7. Howarth, D. J., Cohen, D. D., McLean, B.D., & Coutts, A.J. (2022). Establishing the noise: Interday ecological reliability of countermovement jump variables in professional rugby union players. Journal of Strength and Conditioning Research, 36(11), 3159–3166. https://doi.org/10.1519/JSC.0000000000004037