In our previous blogs discussing athlete monitoring initiatives, most examples have revolved around the weekly jump testing we perform at HQ every Saturday on our dual force plates. Whilst not as sport-specific as some of our testing has become (more on that at a later date) evidence exists for the correlation between vertical jump performance and weightlifting performance (Carlock et al., 2004; Suarez, 2022; Travis et al., 2018). Given that jump testing is minimally invasive and non-fatiguing, it is a worthwhile athlete monitoring tool that at the very least may allow us to track weekly fatigue; best-case scenario, long-term neuromuscular adaptions can be identified. The purpose of this blog is to discuss some potentially useful jump metrics that can be derived from force plates. Ultimately, these metrics are why I believe solely tracking jump height is likely not going to tell you much about your athletes.
The amazing thing about force plates, compared to instruments such as jump mats or Vertecs, is the ability to collect the kinetics facilitating the athlete’s jump. The entire purpose of using dual force plates is to measure ground reaction forces (GRF) that otherwise are unknown. For clarity, our force plates only measure vertical GRF (vGRF); higher-end force plates used in research typically measure horizontal GRF as well using a 3-dimensional (X, Y, Z) Cartesian coordinate system. Figure 1 provides an excellent clip of the force-time (FT) curve of a countermovement jump (CMJ) where the x-axis is time in seconds and the y-axis is vGRF in newtons. Briefly, I will give some background on why jump height may be less sensitive for monitoring fatigue; subsequently, I will go over a metric that may be worth examining and why it’s useful to examine kinetics underpinning jump height when getting started with force plate jump testing.
Jump Height: Digging deeper
The FT curve, as displayed in Figure 1, is used to estimate an extensive array of kinetic metrics in addition to jump height. CMJ height is commonly viewed as a decent measure of athletic performance and capability; anecdotally speaking, when we see someone jump high the immediate thought is something along the lines of “…wow, that person is so athletic.” The connection between CMJ height and athleticism presumed by most is not incorrect: CMJ height is determined by takeoff velocity (Moir, 2008) and the takeoff velocity is determined by the vertical net impulse the athlete produces into the ground and the system mass (body mass + any external mass attached to athlete such as a barbell) (Suarez, 2022), which is the product of net force and time. Essentially, the more vGRF the athlete generates during the time it takes to perform the countermovement, the greater the takeoff velocity and the greater the jump height. Transitively simple enough. The pitfall of CMJ height, however, is its interpretation when routinely monitored week after week or day after day in hopes of understanding acute fatigue.
If CMJ height is driven by net impulse (net force x time), a similar CMJ height can be achieved through multiple iterations of the net impulse equation. This can be referred to as jump strategy. Jump strategy has been seen to fluctuate after fatiguing exercise (Gathercole et al., 2015; Hughes et al., 2022), presenting a point of interest when using jump testing to monitor fatigue, as we do at HQ. In weightlifting, success is dependent on high levels of force generation, with these forces produced as quickly as possible. For example, the discrepancy between your maximum clean-grip deadlift and your maximum clean; just because you can generate the force necessary to lift the barbell does not mean you can clean it – this is due to the rate at which force is generated. For an actual descriptive case example, Figure 2 displays CMJ durations during two different jump test sessions. The jump heights are nearly identical; however, the duration of the movements is vastly different. Hence, if only jump height was inspected, we may assume the athlete is performing at average – this could be incorrect. The athlete is likely compensating for some acute peripheral fatigue by altering their jump strategy (represented by braking phase duration in Figure 2), evidenced by the lengthier duration to perform the eccentric portion of the jump. This can also be seen in the next metric we will discuss: concentric impulse during a specified time window.
Impulse: Be high force but do it quickly
Net impulse has been correlated to weightlifting performance (Suarez, 2022) and, as mentioned previously, is a key determinant of jump height (Ruddock & Winter, 2016; Sole et al., 2018). Using the FT curve, impulse can be calculated for specific phases (i.e., eccentric or concentric contraction phases) over specific time windows (e.g., 0-100ms of eccentric phase, entire eccentric phase, or entire positive impulse) by calculating the integral of the phase-specific impulse. I often examine concentric impulse at 100ms which is the integral of the impulse during the first 100ms of the concentric phase of the CMJ. Whilst net impulse has been shown to correlate with weightlifting performance, I like to focus on the concentric portion since weightlifting is a concentric contraction-dominant sport. The short time window is to put a constraint on the time component of the impulse (recall that impulse is the product of force and time) since it is important in weightlifting that force is produced quickly. To put it simply, a large magnitude of force during those 100ms, produced rapidly, is going to maximize the integral used to calculate impulse. Concentric impulse at 100ms can be interpreted as a measure of the combination of the maximum amount of force generated and how rapidly it was produced. For example, if an athlete produces the same amount of concentric mean force on two separate occasions, the jump where force was generated more rapidly will likely possess a greater concentric impulse at 100ms.
Figure 3 displays an example where jump height slightly decreased but concentric impulse at 100ms decreased to the point where the change was evident when factoring in measurement error (see our blog on this topic) around the data point. Thus, although jump height displayed a possible trend, concentric impulse at 100ms may have been more sensitive to the stimuli resulting in a decrease in performance between time points. Being able to estimate and detect true changes in performance is important as it indicates to the sport scientist or coach to more deeply examine training or external factors that may have led to this change in performance. Hence, it is beneficial to examine the underlying kinetics and strategies behind jump height.
Take Home
If implementing force plates with your weightlifters, an easy place to start is routinely collecting jump testing sessions; a plethora of research exists regarding jump testing, making it a welcoming way to begin familiarizing yourself with your force plates, how they work, and creative ways to analyze the data. I touched on a single metric outside of jump height that we have found useful for monitoring athlete fatigue; however, there are many jump metrics that force plate software can provide discrete data for that may be useful, therefore I recommend becoming familiar with the phases of the CMJ (McMahon et al., 2018). To keep this blog brief, for a deeper discussion on the CMJ, its variables, and how it can be used for testing, I point the reader to the literature review that can be found in Dr. Dylan Suarez’s doctoral dissertation extensively examining jumping and weightlifting performance (provided in the references). Additionally, other jumps could be performed; we have recently started performing squat jumps (protocol described in Travis et al. 2018 study referenced) that aim to attenuate the stretch-shortening cycle of muscle contraction, thereby making the movement concentric focused and possibly a stronger predictor of performance in weightlifting (Travis et al., 2018). Thereafter, there are numerous ways you could integrate force plates into training and collect data more specific to weightlifting performance (i.e., lifting on the force plates). At Power and Grace HQ, we have begun this type of data collection and will hopefully have findings to discuss in future blogs.
Jake
References
Carlock, J. M., Smith, S. L., Hartman, M. J., Morris, R. T., Ciroslan, D. A., Pierce, K. C., Newton, R. U., Harman, E. A., Sands, W. A., & Stone, M. H. (2004). The relationship between vertical jump power estimates and weightlifting ability: A field-test approach. The Journal of Strength and Conditioning Research, 18(3), 534. https://doi.org/10.1519/R-13213.1
Gathercole, R., Sporer, B., Stellingwerff, T., & Sleivert, G. (2015). Alternative Countermovement-Jump Analysis to Quantify Acute Neuromuscular Fatigue. International Journal of Sports Physiology and Performance, 10(1), 84–92. https://doi.org/10.1123/ijspp.2013-0413
Hughes, S., Warmenhoven, J., Haff, G. G., Chapman, D. W., & Nimphius, S. (2022). Countermovement Jump and Squat Jump Force-Time Curve Analysis in Control and Fatigue Conditions. Journal of Strength and Conditioning Research, 36(10), 2752–2761. https://doi.org/10.1519/JSC.0000000000003955
McMahon, J. J., Suchomel, T. J., Lake, J. P., & Comfort, P. (2018). Understanding the key phases of the countermovement jump force-time curve. Strength & Conditioning Journal, 40(4), 96–106.
Moir, G. L. (2008). Three Different Methods of Calculating Vertical Jump Height from Force Platform Data in Men and Women. Measurement in Physical Education and Exercise Science, 12(4), 207–218. https://doi.org/10.1080/10913670802349766
Ruddock, A. D., & Winter, E. M. (2016). Jumping depends on impulse not power. Journal of Sports Sciences, 34(6), 584–585. https://doi.org/10.1080/02640414.2015.1064157
Sole, C. J., Mizuguchi, S., Sato, K., Moir, G. L., & Stone, M. H. (2018). Phase Characteristics of the Countermovement Jump Force-Time Curve: A Comparison of Athletes by Jumping Ability. The Journal of Strength & Conditioning Research, 32(4), 1155. https://doi.org/10.1519/JSC.0000000000001945
Suarez, D. G. (2022). An Investigation into the Use of Biomechanical and Performance Data from Vertical Jump Testing to Monitor Competitive Weightlifters [East Tennessee State University]. Electronic Theses and Dissertations. https://dc.etsu.edu/etd/4108/
Travis, S. K., Goodin, J. R., Beckham, G. K., & Bazyler, C. D. (2018). Identifying a test to monitor weightlifting performance in competitive male and female weightlifters. Sports, 6(46), 1–12.