Strength and Power Assessment: 1RM, Isokinetic Testing, and Force-Velocity Profiling
Prerequisites: This article assumes familiarity with muscle contraction types, basic Newtonian mechanics, and periodisation concepts. If any of these topics are new to you, start with:
Learning Objectives
- Explain the principles, applications, and limitations of maximal strength assessment (1RM).
- Distinguish the purposes and key metrics of isokinetic dynamometry and isometric testing (e.g., IMTP).
- Interpret the key metrics of the Force-Velocity-Power Profile (F₀, V₀, Pmax, SFV, FVimb).
- Explain the application context of kinetic metrics derived from force platform-based dynamic assessments (CMJ, SJ, DJ).
- Understand the principles of profile-based individualised training prescription and the limitations of a one-size-fits-all approach.
Strength Is Velocity-Dependent
Maximal strength is the highest force an individual can produce under the highest resistance and lowest velocity conditions. It is one of the most important physical qualities in sports that demand explosive, ballistic movements (Morin & Samozino, 2022). Maximal strength must not be confused with the force exerted during a maximal effort in a specific task. The latter is constrained by the mechanical properties of the task itself — its inertia, resistance, and movement speed — and therefore does not fully represent an athlete’s underlying strength capacity.
A foundational principle of neuromuscular physiology is that muscle force output depends on movement velocity. As velocity increases, the maximal force the neuromuscular system can produce decreases. This relationship holds from isolated muscle fibres through single-joint movements to complex multi-joint tasks such as squats, jumps, and sprints (Morin & Samozino, 2022).
The practical implication is significant. A study of over 500 male and female athletes across 14 sports found that the correlation between force production at low velocities and force production at high velocities was generally low — and the higher the training level, the lower the correlation (Morin & Samozino, 2022). An athlete who is strong at low speeds is not necessarily strong at moderate or high speeds. As an illustration, elite sprinters with sub-10-second 100 m times had half-squat 1RM values below 120 kg, yet they produced greater ground reaction forces at running speeds above 10 m/s than their peers. These athletes were strong at the very high-velocity end of the force-velocity spectrum.
This velocity dependency means that a single assessment — such as a 1RM test — captures only one narrow region of the force-velocity spectrum. To understand an athlete’s full strength and power capacity, the entire spectrum must be evaluated.
1RM and Isometric Tests: The Low-Velocity End
The one-repetition maximum (1RM) is the heaviest load an athlete can lift for one complete repetition through a full range of motion. It remains the most widely used dynamic measure of maximal strength.
In elite football, the trap bar deadlift (TBD) has become the most commonly used 1RM exercise, reported by 51% of practitioners in a survey of elite S&C professionals (Beere et al., 2023). The TBD generates greater force, power, and rate of force development than conventional squats or deadlifts, correlates highly with vertical jump performance, and accommodates athletes with limited hip or ankle mobility. Some athletes lack the powerlifting technique or mobility for a back squat 1RM, making the TBD or other alternative test modes a practical necessity.
While 1RM testing is valuable, it evaluates only the high-resistance, low-velocity end of the spectrum. Isometric tests complement 1RM by providing information about maximal force production and explosive characteristics without requiring dynamic movement.
The Isometric Mid-Thigh Pull (IMTP) is the most widely used multi-joint isometric test. The athlete pulls maximally against a fixed bar positioned at approximately 125–150° of knee flexion, replicating the “second pull” position in Olympic lifts. Other isometric variants include the isometric squat (IsoSq) at approximately 90° knee flexion and the isometric posterior chain test (IPC) for hamstring and hip extensor assessment. The primary metrics derived from these tests are peak force (F_peak) and Rate of Force Development (RFD).
F_peak from the IMTP shows strong correlations with 1RM in major compound lifts and with sprint velocity and acceleration capacity (Cohen & Kennedy, 2022). RFD, measured across time epochs (0–50 ms, 0–100 ms, 100–200 ms), captures the explosive characteristics of force production. Early RFD (0–75 ms) reflects neural and proprioceptive qualities, while later epochs relate more to contractile properties.
A critical distinction between these two metrics is their sensitivity to fatigue. IMTP RFD responds more sensitively to acute and residual neuromuscular fatigue than F_peak (Cohen & Kennedy, 2022). RFD also recovers more slowly after injury than F_peak, meaning that practitioners should monitor RFD asymmetries — not just peak force — during return-to-sport processes. Adequate familiarisation is essential for reliable RFD measurement, particularly for short time epochs (under 200 ms) where variability is inherently higher.
Isokinetic Dynamometry: Role and Limitations
Isokinetic dynamometry measures maximal torque production at a constant angular velocity. Unlike 1RM or isometric tests, which assess multi-joint force output, isokinetic testing isolates joint-specific strength — typically at the knee, shoulder, or ankle.
The primary application in football is position-specific injury risk assessment. Goalkeeper shoulder strength profiles, hamstring eccentric-to-concentric ratios, and bilateral strength asymmetries are common targets (Beere et al., 2023). The test provides detailed information about muscle group balance that cannot be obtained from multi-joint assessments alone.
When selecting any strength assessment, practitioners should consider six practical questions: (1) Is the test feasible in the current environment? (2) Will results be meaningful to both staff and athletes? (3) Will the data directly inform programming? (4) Can the test be repeated during the season? (5) Is the test related to match performance? (6) Will results have a genuine positive effect on athlete performance? (Beere et al., 2023). These questions guard against “testing for testing’s sake” — collecting data that never reaches a training decision.
The limitation of isokinetic testing is well captured by the specificity-sensitivity trade-off (Marsh et al., 2023). As test specificity increases — meaning the test more closely targets a specific muscle group or joint action — sensitivity to broader performance changes decreases. Isokinetic dynamometry sits at the high-specificity end for the joint in question, but its ecological validity for whole-body athletic performance is lower than multi-joint tests. Equipment cost, portability constraints, and the need for trained operators further limit field implementation. For many practitioners, handheld dynamometry offers a more accessible — though less precise — alternative for joint-specific strength screening.
F-V-P Profiling: Assessing the Full Spectrum
The assessments described above each evaluate strength at specific points along the force-velocity continuum. Force-Velocity-Power (F-V-P) profiling captures the entire relationship in a single evaluation.
In multi-joint functional tasks such as pedalling, squatting, jumping, and sprinting, the force-velocity relationship is consistently linear (Morin & Samozino, 2022). This linearity — observed up to approximately 90% of theoretical maximal force and 80% of theoretical maximal velocity — is not a simplification of the classic hyperbolic single-fibre model. It is an empirically validated property of multi-joint movements, confirmed across a wide range of tasks and populations.
Because power equals force multiplied by velocity, the power-velocity relationship follows an inverted-U shape, with a peak at the midpoint. The key metrics derived from the linear F-V model are:
| Metric | Definition | Jump Range | Sprint Range |
|---|---|---|---|
| F₀ (N/kg) | Theoretical maximal force (y-intercept) | 20–50 | 4–12 |
| V₀ (m/s) | Theoretical maximal velocity (x-intercept) | 1.5–6.5 | 6–12 |
| Pmax (W/kg) | Maximal power output (apex of P-V curve) | 15–45 | 7–30 |
| SFV | Slope of the F-V line (= −F₀/V₀) | −29 to −3.5 | −1.8 to −0.4 |
| FVimb (%) | Gap between actual and optimal SFV | 0–100 | — |
Pmax is calculated as:
While Pmax represents the most global indicator of dynamic strength, two athletes with identical Pmax can have very different force and velocity capacities. One may be force-dominant (steep SFV), the other velocity-dominant (shallow SFV). Only by examining F₀, V₀, and SFV together can a practitioner understand the full picture. FVimb quantifies the gap between an athlete’s actual F-V profile and their individual optimum — the slope that would maximise ballistic performance for their given Pmax. A value of 0% indicates perfect balance; higher values indicate room for improvement.
The diagnostic power of F-V-P profiling becomes clearest when athletes with identical performance outcomes are compared. Two athletes may produce the same squat jump height of 27 cm yet possess entirely different profiles: one with 20% higher Pmax but a large FVimb of 40%, the other with lower Pmax but near-optimal balance. Prescribing the same programme to both would likely produce suboptimal adaptations in at least one athlete (Morin & Samozino, 2022).
The same principle applies to sprinting. Two rugby players with nearly identical 30 m times (4.41 s vs. 4.42 s) showed markedly different mechanical profiles. One had higher Pmax and initial mechanical effectiveness (RFmax: 49%), while the other demonstrated superior ability to maintain horizontal force orientation as speed increased (DRF: −7.64 vs. −11.2 %·s/m) (Morin & Samozino, 2022). Sprint test interpretation should therefore not depend on a single distance but should reconstruct the full F-V profile from a single maximal sprint.
For field implementation, simplified methods have been validated that require only basic inputs. Jump profiling needs body mass, jump height, and push-off distance. Sprint profiling requires anthropometric variables and split times from a single maximal sprint. Both approaches show high concurrent validity against force plate measurements (Morin & Samozino, 2022). Free spreadsheets and smartphone applications make these methods accessible to practitioners without laboratory equipment.
A minimum of 4–6 progressive load conditions is recommended for reliable jump profiling, though covering a wide velocity range matters more than the number of conditions. For experienced athletes familiar with the protocol, a two-load method may suffice.
Force Platform Assessment: Beyond the CMJ
Force platforms measure ground reaction forces at sampling frequencies of 500–2,000 Hz, producing detailed force-time curves from which a wide range of kinetic variables can be derived. The countermovement jump (CMJ) is the most common force platform assessment in applied sport settings (Cohen & Kennedy, 2022).
Jump height (JH) is the most frequently reported CMJ variable. It correlates with sprint performance and other athletic abilities and serves as a useful indicator of cumulative fatigue or training readiness. However, JH alone provides an incomplete picture of neuromuscular function.
FT:CT (flight time to contraction time ratio) and RSImod (reactive strength index modified) are functionally equivalent metrics that divide the output (flight time or JH) by the time required to produce it (time to takeoff). These metrics act as indicators of CMJ “efficiency” — how much output an athlete produces relative to the time invested.
FT:CT and RSImod are more sensitive to acute and residual neuromuscular fatigue than JH (Cohen & Kennedy, 2022). Some athletes compensate for fatigue not by jumping lower but by extending their time to takeoff. This strategy lengthens the eccentric phase duration to preserve net impulse, thereby maintaining JH while reducing FT:CT. A stable JH with declining FT:CT signals neuromuscular fatigue that JH alone would miss. Conversely, if FT:CT is maintained or improves alongside stable JH, this reflects a more efficient stretch-shortening cycle — a positive adaptation.
Within the time-to-takeoff metric, the eccentric phase duration is more sensitive to training and match load than the concentric phase and should be prioritised in monitoring (Cohen & Kennedy, 2022).
Force at zero velocity (FV0) — the force at the eccentric-concentric transition point where centre-of-mass velocity equals zero — decreases after fatiguing exercise and increases following training interventions. It provides additional insight into the loading state of the neuromuscular system.
The Dynamic Strength Index (DSI) bridges isometric and dynamic assessment:
A benchmark range of 0.60–0.80 has been proposed (McGuigan, 2022). Values above 0.80 suggest the athlete may benefit from maximal strength training to raise their force ceiling. Values below 0.60 suggest the athlete is not expressing their available strength dynamically and may benefit from ballistic or explosive training. DSI should not be interpreted in isolation — it must be considered alongside other test results and the broader training context, as no single ratio should drive programming decisions.
Accurate body mass measurement (quiet standing weigh-in) and a 1–2 second still period before each jump are non-negotiable prerequisites for all force platform protocols (Cohen & Kennedy, 2022). These directly affect the accuracy of derived variables and the identification of movement onset. Arms-akimbo (no-arms) CMJ is the default protocol for monitoring, as arm swing reduces force-time curve stability and complicates movement onset detection.
From Assessment to Training: Individualisation in Practice
Profiling is only valuable if it informs training decisions. The central principle of profile-based programming is straightforward: athletes with different profiles require different training stimuli.
The first direct evidence for FVimb-based individualised training came from a nine-week programme in which athletes received training matched to their individual force-velocity imbalance. The individualised group showed a clear and nearly systematic reduction in FVimb alongside greater squat jump performance improvements with markedly less inter-individual variability, compared to a group that trained without profile-based individualisation (Morin & Samozino, 2022).
A one-size-fits-all approach can produce positive group averages while concealing non-responders and negative responders. Group mean effects mask individual-level training responses — some athletes improve, some plateau, and some regress. Profile-based programming allows practitioners to identify which athletes need force-oriented work (e.g., heavy resistance training to shift the F-V line upward at the force end), which need velocity-oriented work (e.g., ballistic and plyometric training to extend the velocity end), and which need to raise their overall power ceiling.
During congested fixture periods, isometric strength training (IST) offers a practical alternative. Both IST and traditional strength training (TST) produced significant 1RM gains in male academy football players over six weeks, with no significant differences between groups (Bailey et al., 2025). The IST group also demonstrated a significant increase in maximal sprint speed. When fixture density limits gym time and recovery windows, isometric protocols can maintain or develop strength qualities with lower session demands than dynamic training.
The most effective assessment strategy combines the strength-power profile (from the tests described in this article) with the movement profile (from match GPS data) to establish training priorities (Beere et al., 2023). An athlete with adequate strength but limited high-speed running output in matches may need velocity-oriented or sprint-specific training rather than additional heavy loading. Another with high movement output but low force capacity may need the opposite. Assessment without this integration risks training what is convenient rather than what is needed.
Key Takeaways
- 1RM assesses only the low-velocity, high-resistance end of the force-velocity spectrum and cannot predict force production at high velocities.
- Isokinetic and isometric tests (IMTP) assess joint-specific strength and multi-joint peak force/RFD respectively; RFD is more sensitive to fatigue than peak force.
- Key F-V-P profile metrics (F₀, V₀, Pmax, SFV, FVimb) reveal individual mechanical differences hidden behind identical jump heights or sprint times.
- In force platform CMJ, FT:CT/RSImod is more sensitive to neuromuscular fatigue than JH, and DSI (benchmark 0.60–0.80) helps prioritise maximal strength versus ballistic training.
- FVimb-based individualised training yields greater performance gains with less inter-individual variability than a one-size-fits-all approach; the focus must be on individual-level training effects, not group means.
References
- Bailey, L. S., Phillips, J., Farrell, G., McQuilliam, S. J., & Erskine, R. M. (2025). Effect of Six Weeks’ Isometric Strength Training Compared to Traditional Strength Training on Gains in Strength, Power, and Speed in Male Academy Soccer Players. Research Quarterly for Exercise and Sport, 96(4), 689-696. https://doi.org/10.1080/02701367.2025.2488843
- Beere, M., Clarup, C., Williamson, C., & Centofanti, A. (2023). Strength, power and injury prevention. In A. Calder & A. Centofanti (Eds.), Peak performance for soccer: The elite coaching and training manual. Routledge.
- Cohen, D., & Kennedy, C. (2022). Kinetics and force platforms. In D. N. French & L. Torres Ronda (Eds.), NSCA’s Essentials of Sport Science. Human Kinetics.
- Marsh, J., Calder, A., Stewart-Mackie, J., & Buchheit, M. (2023). Needs analysis and testing. In A. Calder & A. Centofanti (Eds.), Peak performance for soccer: The elite coaching and training manual. Routledge.
- McGuigan, M. (2022). Profiling and Benchmarking. In D. N. French & L. Torres Ronda (Eds.), NSCA’s Essentials of Sport Science. Human Kinetics.
- Morin, J.-B., & Samozino, P. (2022). Strength tracking and analysis. In D. N. French & L. Torres Ronda (Eds.), NSCA’s Essentials of Sport Science. Human Kinetics.