Research · Testing & Assessment

Force Plate Testing Explained: What the Data Actually Predicts (and What It Doesn't)

By Muhammad Dzulhisham · MSc Sports Coaching, NSCA-CSCS

Force plates have moved a long way from national institutes and pro-team performance labs. Portable dual-plate systems are now common in university athletics departments, physiotherapy clinics, and a growing number of private strength and conditioning facilities — the technology itself is no longer the barrier it was a decade ago. What hasn't kept pace is the evidence behind every number the software prints out. Some countermovement jump (CMJ) metrics have a genuinely solid research base. Others are widely quoted, sold as insight, and still don't have much holding them up. Telling the two apart matters more than owning the hardware.

What a force plate actually measures

A countermovement jump — stand still, dip down, jump as high as possible — looks like a simple test. Underneath it, a force plate is sampling ground reaction force hundreds of times per second and using that force-time curve to derive everything else. Sport scientists McMahon, Suchomel, Lake, and Comfort formalised a standard way of breaking that curve into six phases in the Strength and Conditioning Journal: weighing, unweighting, braking, propulsion, flight, and landing¹. Jump height itself is really just the output of the flight phase — how long the athlete was in the air — but the braking and propulsive phases contain most of the information a coach actually cares about: how quickly force is absorbed on the way down, how much force is produced on the way up, and how efficiently one turns into the other.

This is the real value proposition of a force plate over a jump mat or a phone app: it isn't just telling a coach how high someone jumped, it's showing the strategy used to get there. Two athletes can jump the exact same height with very different force-time signatures — one relying on a fast, stiff rebound, the other on a longer, deeper countermovement. A jump mat can't see that difference. A force plate can.

The metric with the strongest evidence: tracking a trend, not a score

Of everything a CMJ produces, jump height and the broader family of force-time outputs (peak power, peak force, mean power) have the best-supported use case: tracking an individual athlete's own neuromuscular status over time. A 2017 meta-analysis by Claudino and colleagues in the Journal of Science and Medicine in Sport pooled 531 effect sizes across 151 studies and found these outputs were genuinely sensitive to fatigue and recovery — a jump gets measurably worse after a heavy training block and measurably better with supercompensation². One detail from that analysis is worth knowing: the vast majority of studies (over 85%) reported the single best jump of a session, but the meta-analysis found the average of several jumps was actually more sensitive at picking up real change than the best-of trial. Coaches chasing a personal best on the plate are, statistically, using the noisier number.

The important caveat sits right next to that finding. This evidence supports within-athlete monitoring against their own baseline over weeks and months — not a normative "good" jump height to compare across athletes, and not a single-session cutoff that flags someone as "not ready." A 32cm jump means something different for a 14-year-old netball player than a professional sprinter, and even for the same athlete, one low session in isolation is closer to daily biological noise than a signal. The evidence is strongest exactly where it's used most conservatively.

Reactive strength index: useful, if you know how it was calculated

Reactive strength index (RSI) — broadly, jump height divided by ground contact time, most often measured from a drop jump — is meant to capture how efficiently an athlete uses the stretch-shortening cycle: producing force fast, not just eventually. It's a real and reasonably well-supported construct. But a 2019 study by Louder, Thompson, Banks, and Bressel in the journal Sports found that the conventional way most systems compute RSI rests on assumptions that don't always hold — chiefly, that an athlete's center of mass is in the same position at take-off and landing, and that they actually reach the theoretical impact velocity implied by the drop height³. In their data, measured impact velocities ran 10–13% below the theoretical value, meaning technique differences between athletes were quietly being folded into a number presented as pure "reactive ability." Their conclusion was blunt: practitioners should "practice caution when interpreting RSI scores computed using the conventional approach."

None of this means RSI is worthless. It means the number on the screen is only as good as the software computing it, and comparing RSI scores across two different systems — or even the same athlete tested on different equipment — is a much shakier comparison than it looks.

The eccentric/concentric ratio: the most overhyped number on the printout

The eccentric utilization ratio (EUR) — CMJ height divided by static (no-countermovement) squat jump height — is sold as a measure of how well an athlete exploits the stretch-shortening cycle. It's one of the most commonly cited "advanced" metrics on a force plate report, and it's also the one with the least evidence behind it of anything covered here.

A 2017 review in the Journal of Strength and Conditioning Research by van Hooren and Zolotarjova examined the mechanisms behind the CMJ-versus-squat-jump difference in detail and recommended the field stop using the term "eccentric" for this phase altogether, since the physiology involved doesn't cleanly map onto a true eccentric contraction the way the name implies⁴. More directly, a 2021 study on volleyball players by Kozinc, Pleša, and Šarabon in the International Journal of Environmental Research and Public Health tested whether EUR actually tracked anything useful about performance and found close to nothing — individual CMJ height alone was a better predictor of sport-relevant outcomes than the ratio⁵.

"Coaches should probably not use EUR for decision-making regarding training design." The ratio looks like a proprietary insight on a results sheet. It's the metric with the least evidence behind it of any this article covers.

If a report highlights EUR as a standout number, it's worth remembering that the researchers who studied it most directly recommended against building programming decisions around it.

Asymmetry index: the metric everyone wants to believe

Interlimb asymmetry — comparing force, power, or jump height between the left and right leg — is intuitively appealing. A weaker leg feels like it should mean a more injury-prone leg, and asymmetry gets flagged constantly in return-to-play and screening reports. The actual evidence is much messier than the intuition.

Start with what "normal" looks like. A 2025 study by Kiba, Miaki, Yokogawa, and Asai in the Journal of Physical Therapy Science measured healthy, uninjured male athletes and found leg-to-leg symmetry indices routinely sitting in the 88–103% range depending on the test — meaning asymmetry of 10% or more shows up regularly in athletes with no injury history at all⁶. It gets less stable from there. A 2019 test-retest study by Bishop and colleagues in Sports had the same healthy athletes perform isometric squats, countermovement jumps, and drop jumps across two separate sessions and found that not just the size of the asymmetry but which leg came out "weaker" shifted between sessions — agreement on direction ranged from only fair to substantial depending on the test⁷. A single test session's asymmetry number, in other words, may not even be measuring the same thing twice in the same athlete.

The clearest real-world test of whether asymmetry-based cutoffs actually predict future injury comes from anterior cruciate ligament (ACL) rehabilitation, where limb symmetry index (LSI) — typically a 90% threshold — has been the standard return-to-sport criterion for years. A 2023 study by Paterno, Rauh, Thomas, Hewett, and Schmitt in the Journal of Athletic Training followed young athletes after ACL reconstruction and found no meaningful difference in second-ACL-injury rates between those who passed the full symmetry-based criteria and those who didn't — if anything, the group that passed had a numerically higher reinjury rate (28.6%) than the group that failed at least one test (19.7%), though the difference wasn't statistically significant⁸. A 2024 critical analysis in the British Journal of Sports Medicine by Simonsson and colleagues went further, testing 80%, 85%, and 90% LSI cutoffs directly against reinjury outcomes and finding all of them showed poor ability to actually distinguish athletes who went on to reinjure from those who didn't — concluding that these widely used thresholds were "accepted through consensus statements and expert opinions but have not previously been validated"⁹.

That's a big claim to sit with: the single most established, most clinically embedded use of a symmetry metric in all of sports medicine — the ACL return-to-sport threshold — has been directly tested against real reinjury data and hasn't held up well. A general asymmetry index on a healthy athlete's testing report, used to flag injury risk with no rehabilitation context at all, is standing on considerably less evidence than that.

A hundred variables, most of them untested

Part of the problem is scale. A 2023 scoping review protocol by Robles-Palazón, Comfort, Ripley, Herrington, Bramah, and McMahon, published in PLoS ONE, was launched specifically because no one had systematically reviewed the clinical evidence behind force plate testing in sport — and the authors note that commercial force plate software can generate more than one hundred different variables from a single countermovement jump, with as many as nine different jump-based tests proposed for injury-risk screening alone¹⁰. Most of those variables have never been individually validated against a real injury or performance outcome. A results dashboard with a hundred numbers on it creates an illusion of comprehensiveness; in practice, a handful of those numbers (jump height trends, peak force, contact time) have real support, and the rest are along for the ride.

Is it worth it outside elite sport?

For a parent or a competitive-but-not-professional athlete weighing whether force plate testing is worth paying for, the honest answer depends entirely on what it's being used for.

• Tracking training load and readiness over a season. This is the best-supported use, and it doesn't require lab-grade equipment. A 2025 study in the International Journal of Sports Physical Therapy comparing portable clinical-grade force plates against laboratory-grade equipment in youth athletes found strong agreement for jump height, peak force, and eccentric rate of force development — the exact metrics with the strongest evidence behind them — though agreement was weaker for more complex impulse-based measures¹¹. For monitoring an athlete's own trend over time, a portable system is genuinely fit for purpose.
• A one-off "diagnostic" test with a stack of derived ratios. This is where the value gets thin. A single-session snapshot heavy on EUR, RSI comparisons across untracked equipment, and an asymmetry score presented as an injury-risk verdict is offering a lot of numbers and very little of what the underlying research actually supports doing with them.
• Return-to-play clearance based on a symmetry number alone. Given what the ACL literature shows about LSI specifically, a single asymmetry percentage should never be the sole gate an athlete has to pass — it's one input, not a verdict.

The technology itself isn't the issue — it's now affordable and, for the metrics that matter most, accurate enough for non-elite use. The issue is what gets asked of it. A force plate is genuinely good at answering "is this athlete trending toward fatigue or toward readiness compared to their own baseline." It is not currently a reliable oracle for "will this specific leg get injured," no matter how confidently that number is printed on the report.