- John R. Harry, PhD, CSCS
CMJ Force Platform Analysis: You Better Account for the Start Strategy!
Updated: Mar 26, 2021
It's fair to say that countermovement jump (CMJ) testing is "trending" among sports scientists and performance practitioners. This is for good reason, presuming the user has a solid grasp of both the things that need to be controlled during testing and basic mechanics. For this post, I am going to focus on the strategy athletes use to initiate the CMJ: unloading or pre-loading.
As I write this, I must come clean about something. To date, I have published quite a few articles that focus on the CMJ. However, the majority of those articles ignore the potential pre-loading CMJ strategy. Here's a look at me in my chair I share this with the world:
Now that I've come clean with my embarrassment, let's clear up what I mean by "unloading" and "pre-loading". Unloading reflects a start strategy characterized by a noticeable reduction in force to begin the "unloading phase" as I refer to it (you can read this paper for an overview of CMJ phases from my perspective). Pre-loading reflects a start strategy characterized by an increase in force prior to the typical unloading of force applied into the ground. In the figure below is a vertical force curve for the CMJ, including the time period between the first recorded data point and takeoff (left graph) and a zoomed in time period to show the force curve around the time we'd expect the CMJ to be initiated (right graph). Focusing solely on the unloading strategy (i.e., ignoring the possibility of the pre-loading strategy) would detect the start of the CMJ 0.08 seconds later than when the pre-loading strategy is included as a potential criterion.
If you research or monitor the CMJ, it's likely that this difference would be impactful to you, as common performance and strategy metrics, such as modified reactive strength index (RSImod) and jump time (i.e., time to takeoff), respectively, will be wildly different depending on the method used and the athlete's preferred strategy. For instance, the male basketball athlete from which these data were obtained demonstrated a 0.7 m (70 cm) jump height. Using the 0.08 s difference in jump time (i.e., 1 s versus 1.08 s), RSImod would differ by 0.052 (0.700 versus 0.648). This difference should be considered important because the average RSImod value we've seen is 0.645 over 3 years of collecting CMJ data in male basketball athletes.
Another reason I have become firm in my stance on checking for both pre-loading and unloading start strategies is that athletes do not appear to demonstrate one strategy over the other. For instance, in one of our testing sessions where we had athletes complete 3 CMJ trials, the majority of athletes employed both strategies, as shown in the table below. Had we only accounted for the unloading strategy, we'd have probably obtained erroneous results for some time-dependent metrics.
Now that we've demonstrated the importance of searching for both unloading and pre-loading CMJ start strategies, the questions becomes "how" to do so in your analysis. The foundational paper on this topic (at least to my knowledge) can be found here. However, some really smart folks (e.g., Dr. Jason Lake, Dr. John McMahon) and myself are all working on identifying how to improve upon this method. The most current approach can be found here, though I know of other papers also using that same approach that should become available in other journals soon (peer-review takes awhile...).
To summarize, don't be like me. Don't be stubborn and use a Sith-based approach (i.e., don't deal in absolutes!). Yes, I am a Star Wars fan and you'll never convince me that Mace Windu was not the most powerful Jedi of all time.
All jokes aside, we need to take a real ownership of what we do so that we have dotted the i's and crossed the t's with our protocols and analysis techniques. I've had to learn that the hard way so to speak. Okay, that's all for now. See y'all next time!