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Patterns and peaks for jump performance

Analysis of ground reaction force during vertical jump testing allows us to look at how the athlete is achieving the performance outcome and develop a more comprehensive understanding of their neuromuscular function. While looking at dozens of countermovement jump force-time curves every week as part of routine monitoring of athletes, I was intrigued by the varying shapes of force-time curves that athletes produced and wondered that they meant for performance and training. At the recent conference of the European College of Sport Science, I gave a summary and critique of force-time curve shape categorisations and the implications for practice, particularly for return to sport after injury. This post is a summary of that presentation.


The countermovement jump (CMJ) is one of the most widely used tests of lower body strength and power. It requires the athlete to jump as high as they can from a stationary start, by quickly bending at the hips, knees and ankles and then propelling themselves upwards. This invokes the stretch shortening cycle – a fast eccentric movement followed by a quick transition to a concentric movement – which results in greater force production and jump height than if you were to perform only the concentric part of the movement from a squat position. Although jump height is the main performance outcome measure, substantial information about how the outcome is achieved can be gathered from analysis of the ground reaction force (GRF) produced during the jump.

Thanks to the laws of physics and the relationship between force and motion, force-time data can be used to calculate centre of mass acceleration, velocity and displacement through integration. Change in momentum between the initiation of the CMJ and the instant of take-off is determined by net impulse (the area under the force-time curve). This in turn determines take-off velocity, which ultimately determines how high the centre of mass will travel in the air (jump height). The impulse-momentum relationship also enables us to establish key phases during the movement. The unweighting phase occurs when GRF is less than bodyweight and the CoM is traveling downwards and accelerating. The braking phase follows, as the athlete slows down the descent until coming to a momentary stop at the bottom of the squat movement – when the positive (yellow area in the figure below) and negative (blue area) impulses cancel each other out. Then, the propulsion phase sees the CoM traveling upwards and reaching maximum velocity just prior to take-off.


The use of force plates to measure GRF during physical testing is not new but is becoming commonplace in athletic performance and sports medicine centres due to increasing accessibility of the technology. Numerous summary metrics are typically reported for CMJs, including phase-specific minimum, maximum or mean values of GRF and other variables, phase durations, and calculated ratios. If a dual force plate system is available, then an asymmetry index (AI) can also be calculated to express the difference between forces produced under the left and right feet. These metrics are used in benchmarking athletes against certain standards, monitoring performance changes over time, and assessing rehabilitation progress to guide return to sport following injury.


While it is necessary to distil the large amount of data contained in the CMJ force-time curve to more easily digestible numbers, this can overlook potentially important information in the continuous time-series. It’s also essential for practitioners to look at their raw data to ensure comprehensive understanding of their measurements and identify errors in test execution or data collection. Observation of the CMJ force-time curve of many jumps/jumpers reveals different patterns of force production during the propulsion phase. Based on the number of distinct force peaks, two types of curve shapes have been categorised as unimodal and bimodal, but the practical relevance of these shapes has been a topic of debate. Some researchers have suggested that the bimodal curve occurs due to inefficient use of the stretch shortening cycle, while others have found it to be related to better jump performance – two contradictory viewpoints on which of the two curve modalities represents better neuromuscular function.


In this recent study, we defined five subcategories of force-time curve shapes based on the relative magnitude and timing of the propulsion phase force peaks and showed that an earlier force peak (in the first half of propulsion as opposed to the second half) was associated with better jumps. This may be why previous investigations have reached conflicting conclusions, as early and late peaks were being grouped together in the uni-/bimodal categorisation. Whether the shape is unimodal or bimodal seems to be less important than producing maximum force soon after transition from the braking to propulsion phase. This agrees with an analysis of the best 100 CMJs in a collegiate athlete database, which defined eight different force-time curve profiles and concluded that the optimal profile is when peak force occurs at that transition point.


To achieve peak force at the transition from braking to propulsion means that acceleration (the “rate of change in motion”) is also greatest at this point. In other words, athletes need to be able to hit the brakes hard at the bottom of the countermovement and rapidly gain upwards velocity immediately thereafter. This places considerable demand on lower body neuromuscular function, which may be compromised following injury. Therefore, practitioners should assess the shape of the force-time curve, in particular the timing of peak force, in addition to discrete metrics when managing the return to sport process.


When assessing players after injury, it is usual to compare performance between limbs. The GRF measured under each foot during a standard bilateral CMJ on a dual force plate system represents how the athlete distributes load between the limbs during the task. To test true individual lower limb capacity, a unilateral CMJ may therefore be preferred. The example below demonstrates how different the information gathered from these two tests can be. In the bilateral jump, the two limbs display a similar patterns, with peak force occurring at the transition from braking to propulsion and moderate asymmetries (AI) in peak force, force at zero velocity, and braking impulse (~15%). In the unilateral jumps, peak force is similar between the limbs but on the left (previously injured) leg, this occurs very late in the concentric phase and there is a >20% asymmetry in force at zero velocity. The time to complete the jump is also much longer and jump height much lower on the left leg. This illustrates the value of qualitatively assessing the pattern of force production alongside discrete metrics.


Categorising patterns of propulsion phase force production in the CMJ has proven useful to investigate different ways in which athletes produce their jump performance. It appears that the timing of maximum force, rather than the number of peaks, should be the focus of analysis and intervention. Practitioners are encouraged to look at their data for a comprehensive understanding of the movement, rather than rely on selected discrete metrics alone.


References


Bayne, H., et al. Objective classification of countermovement jump force-time curve modality: within-athlete consistency and associations with jump performance. Sports Biomechanics. 2021; DOI: 10.1080/14763141.2021.1991995.


Cormie, P., et al. Power-time, force-time, and velocity-time curve analysis of the countermovement jump: impact of training. Journal of Strength and Conditioning Research. 2009;23(1):177-86.


Jordan, M., et al. Lower limb asymmetry in mechanical muscle function: A comparison between ski racers with and without ACL reconstruction. Scandinavian Journal of Medicine and Science in Sports. 2015;25(3)e301-9.


Kennedy R., and Drake, D. Is a bimodal force-Time curve related to countermovement jump performance? Sports. 2018;6(2).


McHugh, M., et al. Is there a biomechanically efficient vertical ground reaction force profile for countermovement jumps? Translational Sports Medicine. 2021;4(1):138-46.


Peng H., et al. Differences between bimodal and unimodal force-time curves during countermovement jump. International Journal of Sports Medicine. 2019;40(10):663-9.


Read, P., et al. Impaired stretch-shortening cycle function persists despite improvements in reactive strength after anterior cruciate ligament reconstruction. Journal of Strength and Conditioning Research. 2022;36(5):1238-44.


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