Unimodal vs Bimodal Force-Time Curves: What CMJ Curve Shape Can Tell Us
- Jo Clubb
- May 21
- 5 min read
In Part 1 of this mini-series, we explored how to read a countermovement jump (CMJ) force-time curve in detail - breaking down each phase of the jump and discussing what the visual shape of the curve can tell us. Now here in Part 2, we’re going deeper into curve morphology, unpacking the difference between unimodal and bimodal shapes, exploring classifications used in research, and reflecting on what these shapes might mean in applied practice.
This article is part of our Athlete Testing Series, produced in collaboration with VALD, where we break down how to interpret common tests and metrics in athlete assessment.
Understanding the Countermovement Jump
The Countermovement Jump (CMJ) is a foundational test utilised to assess an athlete's explosive power. It involves a dynamic movement starting with a downward phase (countermovement) before a rapid upward acceleration, driving the body off the ground.
If the CMJ is new to you, take a more detailed look at the following posts:
Unimodal vs Bimodal Curves: What’s the Difference?
A unimodal force-time curve features a single, clean peak during the take-off phase. This has often been associated with an efficient and well-coordinated movement pattern—especially in highly trained or elastic athletes. However, we'll dive into that deeper shortly.
In contrast, a bimodal force-time curve displays two distinct peaks in the take-off phase. These can represent different movement strategies, potentially suggesting a less coordinated jump. The bimodal shape is typically further broken down based on the size and timing of these peaks:
Bimodal primary: The first peak (usually eccentric braking) is higher than the second.
Bimodal secondary: The second peak (late concentric push-off) is greater.
Bimodal symmetrical: Both peaks are of similar magnitude.
Each of these may point to different strategies in how the athlete generates force, but as we’ll explore, there isn’t a consensus yet on whether one is ‘better’ than the other.
A More Detailed Classification of Force-Time Curve Shapes
Building on this idea, researcher Helen Bayne proposed a more nuanced categorisation of CMJ force-time curves. She split the curves into five types:
Unimodal Early – Peak force occurs early in the movement.
Unimodal Late – Peak force occurs later in the concentric phase.
Bimodal High-to-Low – The first peak is higher than the second.
Bimodal Low-to-High – The second peak is higher.
Bimodal Symmetrical – Both peaks are of similar height.
This framework allows for more refined interpretation. For example, a unimodal early curve may reflect a smooth and rapid transition from eccentric to concentric phases, while a bimodal low-to-high curve might suggest a delayed or segmented push-off, potentially due to a coordination issue or rehabilitation status.
What Do These Shapes Mean in Practice?
Despite these classifications, there’s still debate in both the research and applied worlds about what these curve shapes actually represent.
Some studies have linked bimodal curves to improved jump performance. Others suggest they may reflect inefficiencies, such as poor utilisation of the stretch-shortening cycle or timing issues between muscle groups.
Helen Bayne’s 2024 study found no significant performance differences between the five curve types. Instead, the timing of peak force may be more important than the shape itself. Some evidence suggests that optimal performance occurs when peak force is generated close to the transition between eccentric and concentric phases—often associated with an early concentric force peak.
At this stage, there’s no clear evidence that one shape is universally better for all athletes. The answer, as is often the case in sports science, is: it depends.
Instead of trying to force-fit your athletes into one ideal curve type, it’s more useful to understand their preferred strategy, track its consistency within and between sessions, and monitor any shifts over time—which may reflect fatigue, adaptation, or rehabilitation status.
This visual layer of analysis can add richness to your interpretation, especially when used alongside outputs from tools like the VALD ForceDecks Hub.
Visual Inspection of the F-T Curve: Still a Valuable Tool
While numerical metrics remain crucial, visually inspecting the raw force-time curve offers complementary insight, as we discussed in Part 1.
Let’s look at some examples discussed in the video above:
Example 1 shows a classic unimodal shape with a single peak and a smooth, steep slope—indicative of an explosive, coordinated strategy.
Example 2 features a bimodal high-to-low pattern, where the force peaks early in the braking phase, possibly due to strong eccentric capabilities.
Example 3 presents a bimodal low-to-high curve, with peak force occurring late in the concentric phase—possibly a segmented or delayed push-off.
In one trial, we observe asymmetry between limbs, with one leg showing a bimodal pattern and the other less so—an important reminder to inspect left vs right contributions, not just the global curve. For more on asymmetries, be sure to look at the Asymmetry Calculation Conundrum post.
A second repetition from the same athlete shows a more stable quiet standing phase and a clear bimodal curve—highlighting the value of repeat trials for data quality.
Takeaways for Practitioners
Learn to spot curve shapes. Use real-time feedback or post-session analysis to analyse your athletes’ curves.
Track consistency. Is their strategy stable across reps or sessions? Changes may warrant further investigation.
Combine with metrics. Use shape alongside the outcome metrics (such as jump height, force outputs, or asymmetry scores) to create a fuller picture.
Don’t chase one ideal. Different athletes may perform best with different strategies especially when considering position, training age, or injury history.
Build your library. The more examples you see, the better your eye becomes at recognising meaningful patterns.
As always, we recommend combining both visual analysis and data outputs to make the most of your jump testing.
If you're looking to build your understanding of force plates further, VALD have developed an excellent series of practitioner guides—including an intermediate guide on force plates—available to download for free on their website.
FAQs about Unimodal and Bimodal Force-Time Curves in the CMJ
What is a unimodal force-time curve in the CMJ?
A unimodal force-time curve shows a single, smooth peak during the takeoff phase of a countermovement jump.
What does a bimodal force-time curve indicate?
A bimodal curve features two distinct force peaks during takeoff. These may reflect segmented or less coordinated movement strategies, with researchers categorising them based on whether the first or second peak is larger—labelled as bimodal high-to-low or bimodal low-to-high curves.
Are unimodal or bimodal CMJ curves better for performance?
Current research, including a study by Helen Bayne, suggests no consistent performance advantage of unimodal over bimodal strategies. Instead, timing of peak force—particularly early in the concentric phase—may be more closely associated with jump performance.
What are the five force-time curve categories described by Helen Bayne?
Helen Bayne classified CMJ force-time curves into:
Unimodal Early
Unimodal Late
Bimodal Symmetrical
Bimodal High-to-Low
Bimodal Low-to-High
These subtypes offer a more detailed understanding of athlete strategies during jump execution.
Why should I care about the shape of the force-time curve?
Understanding the shape and consistency of force-time curves across trials and timepoints can provide insight into an athlete’s jumping strategy, fatigue status, or neuromuscular coordination. This information is particularly useful when monitoring training adaptations or rehabilitation progress.
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This article is support by VALD Performance. For more information, about their technology, visit their website.
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