Force-Velocity Profiling Research: Methods & Applications

A 2016 study by Jiménez-Reyes et al. in International Journal of Sports Physiology and Performance demonstrated that athletes who trained according to their individual force-velocity (F-V) imbalance score improved sprint time by 5.4% over 9 weeks, compared to 3.6% for a group following a generic power training protocol. The 1.8 percentage point advantage — from identical training volume with only the force-velocity emphasis changed — established F-V profiling as one of the most actionable individualization tools available to strength and conditioning coaches. The principle is straightforward: two athletes can produce identical peak power output through entirely different combinations of force and velocity, and improving their power output requires targeting the specific quality that is limiting them individually. F-V profiling identifies that bottleneck quantitatively.

The force-velocity relationship in muscle physiology was formalized by A.V. Hill in 1938 using isolated muscle preparations: as contraction velocity increases, force output decreases hyperbolically, and vice versa. Peak power — the product of force and velocity — occurs at an intermediate velocity point (approximately 30% of maximum shortening velocity and 30% of isometric force in isolated preparations).

Translating this muscle-level relationship to whole-body human movement required substantial theoretical and empirical development. Samozino et al. (2012) were the first to demonstrate that the F-V relationship for ballistic movements (squat jumps across a range of external loads) is linear rather than hyperbolic at the whole-body level, and that the slope of this linear relationship — called the F-V profile slope — characterizes each athlete's individualized mechanical capabilities.

The four key variables derived from a whole-body F-V profile are:

• F0 (maximal theoretical force): The y-intercept of the F-V profile — the maximum force the lower body could theoretically produce at zero velocity. Strongly correlated with maximal strength metrics.
• V0 (maximal theoretical velocity): The x-intercept — the maximum velocity at which the lower body could theoretically move under zero external load. Correlated with sprint acceleration peak velocity.
• Pmax (maximal mechanical power): The product F0 × V0 / 4, representing the peak of the power-velocity parabola. This is the performance variable both training emphases aim to increase.
• SFV (F-V profile slope): The ratio F0/V0, characterizing whether the athlete is relatively more force-oriented or velocity-oriented in their mechanical profile.

Force-velocity profiling was originally conducted using force plate-based squat jump measurements across 5–8 external load conditions, allowing computation of mean force and mean velocity for each jump. The technical and financial barriers of this approach limited adoption to elite sport settings. Significant methodological advances have since made profiling accessible in field environments:

The Samozino et al. (2016) field method for vertical jump profiling uses bodyweight and 2–4 additional load conditions to compute the full F-V profile from jump height measurements alone — a significant simplification that has been validated against force plate reference measurements with correlations of r = 0.91–0.96 for Pmax.

The F-V profile slope (SFV) is the primary individualization parameter. Samozino et al. define an optimal SFV for each athlete based on their individual F0 and V0 values — the slope that would maximize Pmax if force and velocity were perfectly balanced. An athlete's actual SFV is then compared to their optimal SFV to compute an F-V imbalance score:

• Force-deficit (FD) profile: Athlete's SFV is more negative (steeper) than optimal, meaning force production limits power output. These athletes produce relatively low force per unit of velocity. Training prescription: prioritize maximal strength work — heavy squats, deadlifts, weighted jumps — to shift F0 upward.
• Velocity-deficit (VD) profile: Athlete's SFV is less negative (flatter) than optimal, meaning velocity production limits power output. These athletes are relatively strong but slow. Training prescription: prioritize speed-strength methods — unloaded jumps, light barbell jump squats, plyometrics — to increase V0.
• Balanced profile: Athlete's actual SFV is within ±10% of optimal SFV. Both qualities contribute approximately equally; training can use a mixed approach or advance to more specific sport demands.

Research by Jiménez-Reyes et al. (2016) found that 65% of a sample of 144 trained athletes had a measurable F-V imbalance exceeding 10%, meaning the majority of athletes would benefit from profile-targeted training rather than generic power work.

A practical screening sequence for identifying F-V imbalance without full profiling infrastructure:

1. Loaded squat jump at 0% and 40% bodyweight: Perform 3 maximal squat jumps (no countermovement) at bodyweight and with 40% additional load. Record jump height for both conditions. If jump height drops more than 30% from bodyweight to 40% load, the athlete is likely force-limited. If jump height drops less than 15%, they are likely velocity-limited.
2. CMJ to squat jump ratio: Divide CMJ height by squat jump height (same execution, same conditions). A ratio above 1.20 indicates strong pre-stretch augmentation — suggesting elastic/reactive capacity exceeds concentric force capacity, consistent with a force-deficit profile. A ratio below 1.10 suggests strength is adequate but elasticity is undertrained.
3. Isometric to dynamic velocity comparison: Athletes who score high on isometric mid-thigh pull (force-emphasis) but low on CMJ (velocity-emphasis) relative to their sport norms are likely velocity-limited. The inverse — high CMJ, mediocre 1RM — indicates force deficit.

These field screening methods provide directional guidance without requiring a full multi-load F-V profile computation. For high-stakes training decisions or elite athlete programming, a full Samozino-method profile with 4–5 load conditions should be conducted at least twice per year.

Profile-targeted training has a specific evidence base from the Jiménez-Reyes studies. The prescriptive rules are straightforward once the imbalance direction is identified:

The Jiménez-Reyes 2016 RCT confirmed this prescription model: the profile-targeted group gained 5.4% sprint improvement vs 3.6% for the control group over 9 weeks, with re-profiling at week 9 showing that the imbalance scores had moved toward optimal in the targeted group and remained unchanged in the control group. Importantly, athletes who were already balanced at baseline showed no difference between targeted and generic training — confirming that profiling provides the most value for athletes with measurable imbalance (>10% from optimal SFV).

F-V profiles derived from sprint acceleration (Morin & Samozino sprint method) and from vertical jump progressions are related but not identical — they capture different mechanical outputs and may give different imbalance signals for the same athlete:

• Sprint F-V profiling measures horizontal force production effectiveness — specifically, the ratio of horizontal to resultant force during acceleration (the mechanical effectiveness index, DRF). An athlete with high vertical force production but low horizontal force orientation will show a velocity-deficit in sprint profiling even if their jump profile appears balanced.
• Jump F-V profiling measures vertical ballistic force-velocity characteristics. An athlete with excellent reactive strength (depth jumps) but limited slow-force capacity (heavy squats) will show a velocity-deficit here, but this may not constrain sprint performance if horizontal force production is adequate.
• Practical recommendation: Profile both if the sport involves both sprint acceleration (soccer, rugby, basketball) and vertical jump demands (volleyball, basketball, jump events). A sprint-specific imbalance and a jump-specific imbalance may co-exist and require different training emphases within the same program.

Morin et al. (2016) found that in a sample of 56 elite team sport athletes, only 61% showed the same imbalance direction in both sprint and jump profiles — meaning 39% would be given conflicting prescriptions if only one profiling method were used. The practical answer is to prioritize the profile type most relevant to the primary competitive demands of the sport.

Applying F-V profiling in practical sport settings involves acknowledging both the power of the framework and its measurement constraints:

What F-V profiling does well: It converts an abstract concept — power training — into a specific directional training priority with quantitative targets. Coaches no longer need to guess whether an athlete needs more strength or more speed; the profile slope answers the question directly. Re-profiling every 8–12 weeks confirms whether training shifted the profile toward optimal, providing objective evidence of program effectiveness independent of performance tests.

Measurement considerations: F-V profile accuracy depends on standardized squat jump execution — no countermovement, no pre-tension of the Achilles. Research by Jiménez-Reyes et al. (2017) found that 15% of athletes in typical training environments fail to perform consistent squat jumps without a countermovement component, which distorts the F0 estimate. Coaches should invest 2–3 sessions in teaching squat jump technique before relying on profiling data for training prescription decisions.

Individual variation: The optimal SFV calculation assumes a specific body geometry model (Samozino et al., 2012). Athletes with unusually long or short limb proportions — notably tall centers in basketball, or short sprinters — may have optimal SFVs that deviate from model predictions. For these athletes, use the profiling data directionally rather than prescriptively: knowing an athlete is force-limited is actionable even if the exact magnitude of imbalance is uncertain.

Longitudinal value: The most valuable application of F-V profiling is longitudinal tracking across a full annual training plan. Comparing profiles at the end of the off-season strength block, the pre-season conversion block, and the in-season maintenance phase provides the clearest evidence of how each training phase affected the athlete's mechanical capabilities — information that informs periodization decisions for the following season.