The Idea of Variability in Sport and Movement Practice (Part 1, History of Motor Learning & Defining Attractors)

I distinctly remember an interview with one of my sporting icons, Rafael Nadal, many years ago now. It stuck in my head due to one specific detail he mentioned, which was that “every shot is different, every single one... it comes at you an infinitesimal number of angles and speeds." At the time, I thought nothing of this really; however, in the last few years, my understanding around movement changed. 

As someone who learnt tennis from a very young age, I seem to remember the coach really drumming into me one “correct technique” of executing the forehand, backhand, or serve. I remember vividly that when the outcome of a shot was poor or "wrong," the coach more often than not attributed it to a technical flaw in the execution or preparation of the shot. “You didn’t take a big enough back swing” or “you weren’t side on enough during the preparation of your swing,” they would shout. So if this were to be the case, my understanding is that there are only a handful of ways the ball could arrive at your strings, right? However, according to one of the best tennis players of his generation and one of the most successful athletes of all time, “every shot is different.". So, how can there be one “correct technique” if Nadal states that he has never played the same shot twice during his staggering 1,307 ATP Tour matches? 

Rob Gray’s book How We Learn to Move: A Revolution in the Way We Coach & Practice Sports Skills (2021) really caught my attention from the reading list when I started my Strength and Conditioning MSc. Up until this point, the majority of books I had read predominantly focused on the most effective ways to create adaptations to an individual's physiology from a strength, speed, or capacity perspective. Very few delved into the intricacies of creating neurological adaptations, more specifically altering an individual's movement solutions. The book follows a strong belief of mine that there is far more to recurrent injuries, pain, and performance than simply identifying “weak” physiology and altering it. 

Earlier on, Rob refers to the work of Nikolai Bernstein in his book The Coordination of Regulation of Movements (1967), where comparisons are made between a novice and a master blacksmith. Bernstein tried to understand how the master blacksmith was able to consistently arrive at the same hitting spot time and time again. Initially he arrived at the conclusion that surely the backswing of the master blacksmith must be far more repeatable compared to the novice to create this consistency; however, this was not the case at all. So, what exactly was it? To cut a long story short, the master had practised so many times with so many different variations of backswings that no matter the backswing, the outcome would always be the same, and that is where the well-known quote “practice is a particular type of repetition without repetition” originates from.

But you may be wondering, why is it that all professionals forehands, backhands, and serves (if we are continuing with the tennis theme) arrive at very similar patterns to complete these tasks? Bernstein introduces us to the degrees of freedom problem, which is described as the many possibilities in which a movement skill can be performed. To understand this question, we must go back to the literature published in the 1980s. Firstly, Karl Newell’s influential paper, Constraints on the Development of Coordination (1986), introduced the theory of ‘perceptual-motor landscape’ to aid in our understanding of motor coordination and learning. A year prior, Haken and colleagues (1985) developed the concept of 'relative phase’ to describe coordination between two systems. It was these two papers that really laid the foundation for the more recent research and progression in our understandings within this field. As Rob Gray (2021) defined, "the locations in our landscape [perceptual-motor landscape] represent different relationships... technically called their relative phase." According to Haken and colleagues (1985), 0° is known as the ‘in-phase’ and 180°, the ‘anti-phase’. Furthermore, the groundbreaking work of Schöner and colleagues (1992) firstly found that this perceptual-motor landscape was not flat but created with valleys, and secondly, that the ‘in-phase’ and ‘anti-phase’ in our landscape are naturally stable and attractive, as they minimise neural and biomechanical effort for most! These stable and attractive movement solutions in the form of valleys or wells in our perceptual-motor landscape are what are known as attractors, and you can take guess where the name arose from! 

More simply put, attractors or attractor states are the movement solutions we can continually rely upon no matter what constraints or perturbations are thrown our way. According to Steffan Jones in a more cricket context, attractors are the “key basic, essential, fixed movements, stable in the technical completion of the action." Steffan often refers to three main attractors in fast bowling, which are a blocked front foot contact, contralateral upper limb extension, and hip shoulder separation. These components of fast bowling he deems to be attractors, mainly due to his data from research and the very fact that these attractors are universally adopted by most top level fast bowlers. However, to fully understand what makes an attractor an attractor, we must refer back to Newell’s (1986) paper, where his Model of Constraints derives from. I believe (among others, I hope!) that individual (height, weight, muscle mass, etc.), environmental (temperature, wind, noise, etc.), and task (goals, equipment, rules, etc.) ordinated constraints shape what the attractors are for a given sport skill. Generally, due to such constraints presented during a movement task (like hitting a forehand in tennis), there is a more advantageous movement solution to execute that task well and efficiently. The movement solutions you see most tennis professionals adopt utilise the most optimal biomechanics to get the ball over the net and in the court in the most powerful and efficient manner possible. At the end of the day, the movement task associated with tennis is to get a ball over a net and in the court in the most powerful and precise way possible. This is why they all arrive at very similar looking strokes aside from some individuality and style (most notably the one-handed Roger Federer backhand - a thing of beauty!) 

Furthermore, recent literature by Kostrubiec and colleagues (2012) understood that all individuals possess pre-existing coordination patterns shaped by their motor history and development and very much have bearing on how new patterns or skills are learnt, developed, and produced. In other words, we are attracted to more stable, repeatable movement solutions and struggle to execute those that are unstable based off our movement history or intrinsic dynamics. Furthermore, it is common that attractor valleys can be deeply embedded into our landscape from so many repetitions that the bifurcation (Haken et al., 1985) or the creation of a new attractor valley is made very difficult. 

Digging of a new attractor valley requires exploring our landscape and entering unstable regions; however, for most with such deep attractor valleys, it can be easy to slide back into old valleys or movement solutions instead of creating new ones. Individuals may find that when exploring these unstable regions in the quest for a new attractor valley in their perceptual-motor landscape, they usually find it accompanied by high numbers of errors, variability in trying to reproduce the desired movement solution, difficulty to coordinate the movement, or an inability to produce the movement subconsciously. And no one enjoys sticking to things we are not very good at! 

So perhaps instead of creating an entirely new attractor valley, would it not be more efficient of our time to use, reorganise and develop what attractors we currently do have in our perceptual-motor landscape? Newell (1986) categorised this as a 'shift’. Using tennis as an example, this may look like a novice developing their serve. At the start, their toss height and swing path may not be entirely effective from a biomechanical standpoint for what the task requires (i.e., getting the ball over the net and in the service box at speed with accuracy). However, through practice, their efficiency improves, and the attractor valley shifts into a deeper state, becoming more and more stable. As this ‘shift’ continues to develop, such inefficiencies in their movement solutions dissolve as reorganised solutions solidify.

In conclusion, we return to Newell’s Model of Constraints, as these constraints ultimately shape and dictate the most efficient and biomechanically advantageous movement solutions for any given task. While we all have access to a wide range of degrees of freedom in completing movement tasks, it is crucial to break down the specifics of each task. As Harry Simington suggests, we must be able to provide a “bandwidth” or wiggle room of suitable and efficient movement solutions established from task constraints. Through variability within our practise and training we can then develop and stabilise these suitable movement solutions into deep attractor valleys within our perceptual-motor landscape. In the second part of this article, I will explore the relevance and application of variability and the role of attractors in sport and movement practice.

References / Sources: 

Bernstein, N. (1967). The Co-ordination and Regulation of Movements. United Kingdom: Pergamon Press.

Gray, R. (2021). How We Learn to Move: A Revolution in the Way We Coach & Practice Sports Skills. United States: Rob Gray.

Haken, H., Kelso, J. S., & Bunz, H. (1985). A theoretical model of phase transitions in human hand movements. Biological cybernetics, 51(5), 347-356. 

Harry Simington - Athletic Consultant & Founder of Calibrate Sports 

Kostrubiec, V., Zanone, P. G., Fuchs, A., & Kelso, J. S. (2012). Beyond the blank slate: routes to learning new coordination patterns depend on the intrinsic dynamics of the learner—experimental evidence and theoretical model. Frontiers in human neuroscience, 6, 222.

Newell, K. M. (1986). Constraints on the Development of Coordination. In M. G. Wade, & H. T. A. Whiting (Eds.), Motor Development in Children: Aspects of Coordination and Control 341-360. The Netherlands: Martinus Nijhoff, Dordrecht.

Schöner, G., Zanone, P. G., & Kelso, J. A. S. (1992). Learning as change of coordination dynamics: Theory and experiment. Journal of motor behavior, 24(1), 29-48. 

Steffan Jones - Fast Bowling Coach