Why seeking to improve X or Y when the objective is to improve jump, sprint, or more generally “sports” performance?

This post is an attempt to better define/explain our research framework, and stems from various discussions we’ve had in the recent years with open-minded coaches and colleagues. This is how I can summarize the main comment we want to address here: “Seeking to improve mechanical power, force, and/or velocity output in jumping or sprinting is irrelevant since what you want to improve is jump height or sprint times/speed”. In the context of team sports, a preliminary question is also: “Seeking to improve individual players’ jumping or sprinting performance is irrelevant since what you want to improve is the team performance in terms of game results”.

I will briefly address the latter point here. It is obvious that team sport performance is multifactorial and goes way beyond physical capabilities of individual players. However, I firmly disagree with statements I hear sometimes such as “the ball needs to move fast, not the players”. I guess you will not find a single, honest team sports coach who will answer “no” to the following question: “do you agree that if each of your players is able to jump higher and sprint faster this will eventually help the team reaching better results”. So basically, in any team sport, players’ physical capability in jumping and sprinting is just one component of their overall player profile (that also includes tactical intelligence, specific skills, vista, mindset, etc), and this is just one component of the larger-scale team performance. Then, each training exercise is a focus on one or several performance components (or their physiological/biomechanical sub-components) and is likely not sufficient in itself to directly improve the overall performance. However, this does not mean they are useless: they are just a part of a much bigger puzzle. They are not THE puzzle, but the puzzle is incomplete without them. If you do not agree with that, then maybe you consider that the only acceptable, effective training scenario is a competition game in a crowded arena, so that all the specific performance factors are stimulated in an integrated manner. Absurd. Our research work focuses on this sub-component of a sub-component of sports performance, and we never claimed otherwise.

Now let’s tackle the main question: why focusing on improving force, velocity, power, or other neuromuscular factors when the objective is to improve e.g. the time to cover 20-m or the distance covered within a 3-s maximal acceleration? Our first, seemingly provocative answer, is to ask “ok, then what’s your plan to improve your 20-m time”. Immediately the discussion shifts to a kind of agreement. In order to improve a final outcome, we must “push the buttons” of the underlying “key performance indicators”, because if the answer is simply “well, do 20-m sprints in training over and over again”, we all know that this will help for a while, but if this was the best training possible then all coaches would lose their job. One of the pillars of sports training is to stimulate the athlete’s system in a way that induces adaptations. Thus, by definition, greater adaptations might result from unusual types of stimuli (in terms of load, muscles, coordination, force-velocity context, etc.) rather than usual ones. The neuromuscular system should be stimulated out of its “business as usual” comfort zone once performance plateau is met, which aligns with the principle of “diminishing returns”.

The following framework explains our research philosophy, and applies to both performance and injury prevention, by replacing key performance indicators by key risk factors and so on…We will discuss this framework step by step, keeping in mind that in the research context, each arrow means one or more scientific studies, so months and months of time and energy spent exploring or testing hypotheses.

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Step 1: From performance in a given sport to jump and sprint capability as KPIs

The main question here is: what individual physical capabilities are key performance indicators? Within the complex network underpinning final individual or team sports performance (e.g. race time, game or championship result), the numerous individual components include physical components and for some sports, jump and linear sprint performance. In football, rugby or basketball, of course, individual players’ jumping or accelerating capability will not win titles. However, they are major physical performance components: you will not find a single coach who will not agree that adding say 5% jumping and sprinting capability to his entire squad might eventually translate to better team performance. So things should be clear: don’t mistake an individual player’s physical performance metric (jump height, top speed or acceleration) with their performance as an athlete or a player. And in turn, jump height or linear sprint performance should not be confused with their respective underlying KPIs and associated determinant neuromuscular variables, as we’ll discuss in the next section. Note that jumping and sprinting capabilities have been identified as KPIs in sports such as volleyball, or rugby, but our aim here is not to go into such details. Furthermore, KPIs might differ depending on the level of performance and contexts.

Step 2: From jump and sprint capability to their underlying physiological and biomechanical factors

The main question here is: what are the macroscopic determinants of jump or sprint performance and what are the underlying modifiable physiological components?

Our approach aims at identifying key macroscopic neuromuscular and anthropometrical determinants of jump and sprint performance, following the “macroscopic-to-microscopic” sequence. According to the great biomechanist and biologist Robert McN. Alexander, interviewed about modeling approaches in biomechanics: “the simpler the model, the clearer it is which of its feature is essential to the calculated effect (here performance)”. This does not mean we simplify human locomotion and performance just for the sake of simplifying, but we think it is more logical to study specific “microscopic” physiological variables afterhaving identified them as key components in the model. Otherwise, the risk of studying irrelevant variables is clear. This step might require modeling, musculoskeletal simulation, and more mechanistic approaches, but eventually real-life experiments must provide testing of the validity of the model, making further steps possible. For example, Pierre Samozino’s studies have shown that a given individual vertical jump height performance was explained almost entirely by three macroscopic factors quantified over the jump push-off: the maximal power output capability, the slope of the force-velocity profile in jumping and its relative difference with the “optimal profile” value, and the distance of push-off.

Step 3: what are the underlying, modifiable, anthropometrical and/or neuromuscular variables?

The main objective here is to identify the potential “candidates” for specific physical training.

Based on the literature, functional anatomy, sometimes anecdotal/coaching evidence and experience, this process is the key step to transition from the macroscopic to the microscopic level. This is where sports training science and basic anatomy, physiology or biomechanics meet. Tendon mechanical behavior, motor unit recruitment and firing rate, pennation angle, levers, muscle slack, motor command and motor control, intra- and inter-muscle coordination, joint stiffness body segment dimensions, muscle physiological cross-sectional area…The game here is to connect the dots and run experiments to orient towards neuromuscular variables that essentially influence the previously identified macroscopic factors.

Step 4: are these neuromuscular factors modifiable with a specifically designed training?

It is important to note here that we tend to always think first about some type of training interventions that are possible in real-life sport scenarios. For practitioners, what’s the interest of a type of “training” or intervention that is proven effective but strictly restricted to laboratory conditions because of the associated technology or savoir-faire? That being said, research performed in laboratory conditions is absolutely necessary to test potential neuromuscular factors, but researchers should at least suggest possible transfers to field practice (if any) when publishing their important discoveries. The final step is then to plan a collaborative work so that these “real life” testing studies are designed to respect both research hypotheses and practical constraints. Each side of the table should then understand the non-negotiables of the other side, so that such studies are made possible. Not enough sport and exercise science researchers practice/coach/train (or did in the past) and not enough coaches have a minimal scientific background. I understand this sounds utopian, but speaking a common language (here, actually, two) is the key to better designed and thus more applicable research.

Step 5: training content, training effects, and “back to step 1” loop

The key question here is “was the training leading to positive effects on the targeted neuromuscular factors, and in turn on identified KPIs and physical performance outcomes”. Of course, the loop that goes up the framework might not be completed within single studies, and depending on the cases several separate studies might be necessary. The key role of authors here is to clearly explain the specific aims of their study within that overall sequence so that Editors, Reviewers and eventually readers understand why some variables (eg final performance) are measured or not. The ideal scenario is a training study with a comprehensive assessment of microscopic neuromuscular variables, the key performance indicators they determine and the final physical performance outcome…Easier said than done. But this is a noble objective. For many reasons, some studies (ours included) use methodological short-cuts and directly assess the training effects on KPIs or even final individual performance (eg jump height or sprint times). Such studies provide valuable information, provided the training design and the variables assessed are fitting the preliminary reasoning (Steps 1 to 3). The downside is that interpretation of the results (whether positive or negative) is based on speculations about the mechanistic links between the training inputs and the final outputs. In this context, a partially complete study is still a better source of information/thought than no study at all. It’s easy to sit and wait for the “perfect one” forever, and shoot all the imperfect ones with a keyboard. Better to do something imperfectly than to do nothing flawlessly.

Conclusion

My intent here was to try and map our ideal sports performance research framework, without going into details about specific studies. Some of our studies belong to some Steps described above, and we are doing our best to design, collaborate, perform studies or series of studies that follow this framework. Although clearly imperfect, this framework makes sense to us, and might be useful to step back and think about the way you follow, read, review, design, perform or “use” sport science. It might also apply to other sports, other physical components, other KPIs, and other contexts such as injury prevention/rehabilitation scenarios.

 

References:

  1. Alexander RM. R. McNeill Alexander. Curr Biol [Internet]. 2006;16(14):R519–20.
  2. Alexander RM. Modelling approaches in biomechanics. Philos Trans R Soc Lond B Biol Sci. 2003;358(1437):1429–35.
  3. Samozino P, Rejc E, Di Prampero PE, Belli A, Morin JB. Optimal force-velocity profile in ballistic movements-Altius: Citius or Fortius? Med Sci Sports Exerc. 2012;44(2):313–22.
  4. Samozino P, Edouard P, Sangnier S, Brughelli M, Gimenez P, Morin JB. Force-velocity profile: Imbalance determination and effect on lower limb ballistic performance. Int J Sports Med. 2014;35(6):505–10.
  5. Samozino P, Morin J-B, Hintzy F, Belli A. Jumping ability: A theoretical integrative approach. J Theor Biol. 2010;264(1):11–8.

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