The Constraints Collective is committed to understanding how applications of constraints can be successfully achieved in contexts related to education, development, teaching, training, coaching, understanding performance analytics and providing sport science support.

At its most fundamental level the concept of constraints is about change in systems over different timescales when interacting with environmental objects, surfaces, events and others. Research continues to reveal the deep influence of constraints everywhere in life, constantly shaping the behaviours of complex adaptive systems, including biological organisms (including humans) and social collectives (like sports teams), in so many ways.

The concept of constraints in the study of complex systems has a rich history in scientific research on phenomena in physics (e.g., earthquakes; molecules of gas cohering), biology (e.g., analysing behaviours of organisms in a murmuration of starlings: chemistry (e.g., molecules of liquid changing properties as temperature changes) and evolutionary sciences (e.g., interpreting form and function of limbs from the fossil record ). This has been shown in the work and modelling of Stuart Kauffman, Per Bak and others, for example. In the social sciences, Alicia Juarrero has provided the most insightful perceptions on the effects of social, historical and cultural constraints on human behaviours, at the same time highlighting problems with philosophical thinking of Aristotle and Plato and others. I will discuss some of these contributions in future posts.

Here, I outline how the idea of constraints shaping the behaviours of performers and learners entered the sport sciences via the human movement sciences from the 1990s onwards.

“This glimpse in the rear-view mirror may be useful for understanding some of the history behind using a constraints-based approach in your professional work. Knowing where the key ideas and concepts came from, and what the theory and scientific evidence is like behind this applied perspective, will enrich your understanding and applications.”

— Keith Davids

In 1994, I co-authored an initial scene-setting paper in the gradual development of what was to become an ecological dynamics explanation for movement coordination, control and skill, along with PhD students, Craig Handford and Mark Williams https://pubmed.ncbi.nlm.nih.gov/7853448/

Why we wrote the 1994 paper

In that position paper we drew attention to prevailing arguments in psychology and human movement science criticising the dominant cybernetic rationale for understanding brain and behaviour. From the 1950s onwards, in cognitive psychology, it had become fashionable to compare human movement systems to self-regulatory, servo-mechanistic technology (feedback driven and containing an internal comparator state), such as thermo-regulation systems and computers. The aim was to develop theories of motor control mechanisms and processes. This ‘techno’ analogy rose after the secondment of engineers, psychologists and ergonomists in WWII efforts for training and selecting military personnel to use different equipment and technology in combat.

Some think that the sub-discipline of skill acquisition arose from this context in the USA and UK. Regardless, these collaborative efforts naturally led to a more technology-focused explanation for human behaviours. In 1948 this was confirmed as the information processing approach after the Hixon Symposium which is generally considered to be the birth of cognitive psychology (see below).

Flying Blind

Fast forward from there to the 1990s and beyond, it seems that few sport scientists (especially sport psychologists and motor learning specialists; but also coaches/teachers) understood how this dominating, theoretical rationale underpinned their professional work. In effect, by adopting certain ways of practising, teaching, coaching and preparing for competition, this was the theoretical framework they were ‘signing up to’: The ‘Brain as a Computer’ analogy advocated a computational approach replete with representations and programmes to be made automatic through intense repetitive training and corrective feedback. This brief glimpse in the rear-view mirror may, therefore, be a reminder for getting to understand what you are ‘signing up for’ if you want to use a constraints-based (biophysical) approach in your professional work. Knowing where it came from, and what the theory and scientific evidence is like behind this ecological perspective, will likely enrich your understanding and applications.

From a constraints-based rationale, a key criticism is that those cognitive theories of motor control and learning focus attention solely on one major constraint (i.e., the brain) on behaviours like motor control and learning. This unique focus is on establishing the nature of control mechanisms and processes, based on an internal representation of a movement constructed with experience, learning and practice. The challenge now, and back then, was to explain how the multitude of the degrees of freedom of the brain and body as it interacts with the environments in which it is embedded can be organised and controlled during skilled movement . Even in the new millennium, the emphasis is on understanding how such internal control mechanisms and processes can represent the world in an embodied way.

John Whiting was hugely influential in motor control and learning and inspired many of us through his insights and writing.

The 1994 paper owed a lot to the influence of John Whiting

That paper was the first attempt in the sport sciences to provide an alternative view of movement coordination and its (re)organisation which did not rely on traditional cognitive psychology concepts such as comparator units, programmes, schema and internal representations. It advocated how movement coordination, control and skill acquisition were self-organised under constraints. We sought to introduce into the sports science domain, what we called ‘a natural physical alternative’. Our description was a ‘nod in the direction’ of the title of a book by H.T.A. (John) Whiting and colleagues’ advocating a biophysical orientation to understanding human movement behaviour. Looking back, this was the beginning of a decades-long research programme viewing athletes and sports teams as complex systems continuously adapting to constraints, implementing well-established concepts from physics, chemistry, and evolutionary and theoretical biology ).

John Whiting at the University of Leeds: Experimental programmes in motor control

For readers who enjoy opportunities to delve back into the history of a scientific sub-discipline like motor learning and control, the British scientist and physical education specialist, John Whiting, left a huge legacy in, not only those fields, but also in sports science and sports pedagogy. Geert Savelsbergh and I drew attention to his invaluable leadership and experimental contributions to our field in our invited tribute to the Journal of Sports Sciences in 2002.

I started my PhD at Leeds University just after Whiting had left there in 1978. He had established a remarkable research programme in movement control, using the specific task vehicle of ball catching. Whiting’s group published seminal papers between the late 1960s and mid 1980s and was heavily influenced by the dominant theoretical paradigm at the time: the information processing approach. The experiments were conducted with wonderful precision and rigour. I evidenced some insight into this experimental rigour personally when I visited my future shared office space in Leeds in the summer of 1978. It was located in the previous laboratory area of the group: a completely blacked out, darkened space for regulating visual information of certain portions of a projected ball in flight through numerous means including UV lighting. By the time I arrived to start studying in September 1978, it had been transformed into a light and bright office for two!

Major influences on research on Constraints on performance and learning

In 1978, John Whiting made the move from Leeds to the Vrieje Universiteit (VU: Free University) of Amsterdam in the Netherlands, undergoing a transition to an ecological theoretical framework in his work. One can see the transition was still happening in the title of the 1990 book, which still focused on movement control, rather than on the coordination of action with respect to the environment. Nevertheless, Whiting and his colleagues at the VU went on to establish another truly world-class programme of research which provided so much rich empirical support for key concepts in ecological psychology and dynamical systems theory, including crucially, the role of informational constraints on coordinating action and regulating movements with respect to dynamics of the environment. At the VU, top scientists like Geert Savelsbergh (ecological psychologist and sport science practitioner), Peter Beek (dynamical systems theorist), Raôul Oudejans (ecological psychologist and applied scientist), John van der Kamp (ecological psychologist), Reinoud Bootsma (ecological psychologist), and many others, were inspired in their work by John Whiting.

They mainly used dynamic interceptive sports-related tasks to provide evidence for the exquisite timing and skill adaptations that emerged under constraints in elite athletes (table tennis players) and even ordinary people during performance of dynamic interceptive actions. For example, Geert Savelsbergh elegantly showed the regulatory effects of perceptual information as a major constraint on emerging actions of infants seeking to grasp a moving ball (more on this study later).

The contribution of the Manchester Metropolitan University (MMU) group to understanding constraints on performance and learning

After I moved to MMU in 1991, we introduced sport science to the key ideas of a constraints-led perspective and examined the nature of important constraints on performance in different sports. In particular, we focused on the relationship between informational, physical and task constraints. Our main conclusion back then was that a multidisciplinary perspective was needed to understand the way that key constraints interact to shape learning and performance in sport. Our particular focus was on theoretical concepts such as self-organization, constraints, emergence, variability and stability of motor patterns in movement systems. Our research programme led to the characterization of a constraints-led approach to describe and explain the process of change in movement behaviour which underpins learning and development (e.g., published in early papers by Chris Button and Simon Bennett and colleagues during the 1990s and 2000s).

Newell’s model of Constraints: Where it all began….

Our work was particularly inspired by Karl Newell’s (1986) model and elucidated what we meant by a constraints-led approach. Adopting an ecological perspective, later confirmed as an ecological dynamics rationale by Duarte Araújo and colleagues in 2006, an important question that we examined was: How do changes in organization of complex adaptive systems emerge over different timescales? In performance environments like sport and physical education, these timescales are at the level of performance (here and now), learning (hours, days, weeks, months, years) and development (months, years, decades).

The most cited paper on constraints (naturally) was published by Karl Newell to address how motor development occurred. It became a major stimulus for our work at MMU when we realised that its significance went way beyond motor development but could also help explain coordination, control and skill performance with implications for designing practice, teaching and training environments in sport and physical education. It has even been suggested that the key concept of constraints can form a Grand Unifying Theory by Paul Glazier, (who completed his PhD at Sheffield Hallam University), one of the most sought-after explanations in any discipline of science .

Karl Newell’s 1986 paper was a key landmark study that inspired work on Constraints-led Approaches

For example, our research at MMU suggested that movement performance in sport may become more skillful as a learner couples their actions with surrounding perceptual information, seeking more stable and functional states of coordination (or ‘attractors’ in dynamical systems language) during performance. Ian Renshaw and his colleagues have continued to show how constraints shape perception and action in practice and performance using the run-up approach in sports like running to kick a ball at full speed, long jumping and cricket bowling. Interestingly, Ian worked with Mark Scott, whose work on visual regulation of long jump run-ups with me at MMU inspired Ian’s PhD studies after watching the impact of the presence (and non presence) of an umpire on bowlers at his winter cricket nets whilst at Teesside University. Essentially, Ian’s work on cricket bowling run-ups built on the long jump papers of Gilles Montagne and then Mark Scott and showed that cricket bowlers were able to adjust their footfalls as they ran in to bowl as and when they needed to; to make sure they ‘hit’ the crease and didn’t bowl a no-ball. We still need more work here and no-balls can be seriously costly (see the image below!). This was the first study to reveal continuous perception-action coupling throughout the run-up as previous studies had shown that athletes only visually regulated at the end of the run-up. We suggested that fast bowlers were able to do this because of the presence of the umpire that acted as an information source that gave them a reference point near the crease. We will discuss these ideas and what they imply for cricket coaches in a later blog post.

Trying to help solve performance problems is one of the reasons we do what we do…we need to work harder in trying to help people to listen :)

Constraints shape Coordination Solutions

Karl Newell’s (1986) model of constraints has been most influential in showing that, during development and learning, behaviour emerges under interacting constraints as individuals exploit inherent tendencies for self-organization. This emergent process is relevant when individuals learn to coordinate their actions with respect to constraints imposed by surrounding objects, surfaces and other individuals in a range of different sport performance environments. Craig Handford co-authored a paper providing an ecological perspective on skill acquisition in 1997 , explaining how constraints manipulations can support athletes to seek, explore, discover, assemble, and stabilize reliable movement patterns that can be adapted to changes in dynamic contexts of performance. Karl Newell and his colleagues showed that practice, is best considered as a continuous search for coordination solutions arising from constraints of a perceptual-motor workspace generated by the continuous interactions of a learner, environment and task. In the perceptual-motor workspace of practice there are many possible ways in which appropriate solutions to particular task constraints may be discovered. The search process involves the variation (modification and perfection) of movements from trial to trial without identical repetitions, which Nikolai Bernstein showed in analyses of Blacksmiths striking a nail with a hammer and Chris Button revealed in basketball free throw shooters.

Behaviour emerges under interacting constraints as individuals exploit inherent tendencies for self-organization.

A constraints-led perspective on motor learning indicates that, once a functional task goal for a performer has been specified in their intentions, then a process of continuous exploration eventually results in the emergence of a useful solution to the task, satisfying immediate constraints on the individual learner. This task solution becomes more refined and results in the strengthening of the connections between different parts of the body as a functional coordinative pattern. Handford et al. (1997) proposed how skill acquisition, in continuously satisfying interacting constraints, is a process reminiscent of evolutionary biology’s emphasis on the struggle for the emergence of a fit, highly adapted biological organism. They argued that ‘successful’ (relevant, functional) coordination patterns gain increasing stability as practice progresses, whilst other movement patterns stimulated during the search process are discarded because they are less useful for satisfying the task constraints. From this perspective self-organizational processes in skill acquisition underpin a gradual process of what Esther Thelen, the great development psychologist, called ‘selection under constraint’, in which the relationship between movement organisation and performance outcomes is vital.

Evidence for ‘selection under interacting constraints’: Don’t be afraid of the dark!

Going back to the darkened laboratory of Whiting’s group at Leeds University, there were early reports of performance adaptations by skilled catchers in a study by Whiting et al. (1970). Good catchers in their study were observed to use a typically less efficient ‘snatch type’ of action when required to catch a moving ball in the dark after its projection in light. In contrast, in full light conditions when they could see the whole of ball flight, they withdrew the hand smoothly to cushion the impact of the approaching ball.

At MMU in 1996, Simon Bennett and I verified the movement profiles that these initial studies at Leeds implied when we filmed the kinematics (space and time changes) of movement organisation of skilled catchers under different informational constraints. Our investigation clearly showed that skilled catchers could re-organise their movement patterns as visual informational constraints of performance changed in order to still achieve a successful catch.

Our data showed how changing informational constraints (in this case visual conditions of catching) affect the organisation of a successful coordination pattern. When skilled catchers were asked to catch a luminous ball in the dark and in full lights conditions, the manner in which they achieved the intended task goal reflects the weak organisation of the relationships between the components of the movement system. The lack of rigidity in the relationship between the catcher’s degrees of freedom is useful because it allowed the basic coordination pattern for catching to be adapted so that the catchers could still achieve the task goal. These findings show how skilled catchers can be highly flexible and adaptable to sudden changes in the information that surrounds them. To be clear: an intended action of less skilled individuals can also self-organize under constraints too….it is not just a feature of expert behaviour. Data from other studies of unskilled catchers, including the infants studied by Geert Savelsbergh show this clearly.

Geert Savelsbergh and his remarkable inflating balls

Child’s Play: The study of infant interceptive actions by Geert Savelsbergh and John Van der Kamp (1998) in Amsterdam

Savelsbergh and Van der Kamp (1998) studied whether infants aged 18 months could intercept balls approaching towards them attached to the BallTrap machine. The BallTrap is a computer-controlled ball machine that can precisely vary approach velocity of an attached ball, while maintaining a fixed spatial pathway towards the catchers. Infants sat on their mother’s lap and were encouraged to reach and grasp an approaching ball, but clearly no explicit instructions could be given due to the age of the participants.

The group results on timing coordination of the intercepting hand and arm with respect to the approaching ball showed that even infants aged only 18 months are able to organize their movement patterns in an adaptive way, as task constraints changed. At lower levels of ball velocity, they tended to reach towards the ball earlier and open the hand on the way. Consequently, the hand made contact with the ball earlier during slower ball approaches. Conversely, higher ball velocities invoked shorter reaching times. Clearly, infants were able to vary the movement duration of the catching action under the different task constraints, just like the expert catchers in the study by Bennett and Davids (1996).

Further data showed that the infants could choose to use two hands to intercept the ball, compared to one hand when needed. This choice was scaled according to the information perceived on the size of the approaching ball. Larger balls led them to use two hands for interception and smaller balls sometimes elicited more one-handed responses in the infants. This study showed how ‘ordinary people’ could adapt their actions to task constraints as required (in this study exemplified by ball velocity and dimension). This skill adaptation in such young participants was revealed in the spatial and temporal (re)organisation of the interceptive movement pattern that emerged without specific instructions and teaching.

***Catching has been a favourite task vehicle for motor learning scientists***

A key point to note: Constraints interact to shape performance!

The most significant point to note about Newell’s (1986) model of constraints is that categories of constraints interact to shape system behaviour and should not be considered as acting independently. What this means is that there are many constraints on our behaviours, each exerting varying amounts of influence at different times during the lifespan of each individual, each with the potential to interact with other constraints. For example, constraints may be imposed by many factors such as the transmission of networks of genes predisposing patterns of connectivity in the neural subsystem, or by the pressures of the socio-cultural backgrounds of athletes learning sport skills. A constraints-led approach to skill acquisition favours the “Simultaneous influence of multiple levels of causality” as Esther Thelen and colleagues have noted.

Practical Implications of a Constraints-Led Perspective

Here I will conclude by signposting the main implications for practitioners in brief:

• Sport scientists and practitioners need to work together to fully understand the nature of the organismic (personal), task and environmental constraints interacting on each individual performer in different sports and physical activities. Martyn Rothwell has referred to the need for sports organisations to develop a Department of Methodology which can provide a unifying framework for organising collaborations across scientific disciplines of multiple specialists to ensure that they are not pulling in different directions in their work with athletes and teams .

• A major emphasis should be on the personal development history of each individual performer and careful consideration needs to be given to how key constraints interact to influence performance and skill acquisition for each individual learner.

• Time spent in practice is just one amongst many important constraints on attainment of excellence. It’s role should not be overemphasized by practitioners.

• The micro-structure of practice (the details of what is done everyday day, week, month and year) needs to be organised so that qualitative differences between practice sessions are understood. Time spent in practice is only one constraint and does not guarantee the acquisition of expertise. What athletes are challenged to do during practice is a more accurate index of skill acquisition than the measurement of time spent on the training field (Chow et al., 2022 ).

• Coaches could facilitate rapid development and skill acquisition by careful identification and manipulation of the major constraints on each individual athlete during practice and training. Planned manipulations may cause behaviour sudden ‘jumps’ or performance improvements. In this respect, excellent performance may just be ‘waiting in the wings’ (Thelen & Smith, 1994).

• As we noted in our 1994 paper, sport scientists need to recognise the limitations of mono-disciplinary perspectives in understanding complex matters like sport performance, athlete development, team organisation and skill acquisition. Teams of scientists need to develop a transdisciplinary (problem-focused, individualised) approach for analyzing constraints at various levels of performance (i.e. cognitions, emotions, social interactions, physiological, biomechanical).

• Individual differences need to be understood and valued more than ever in sport. Variation is not necessarily ‘noise’ or ‘error’ but could signal successful adaptation to unique constraints. The history of sport contains many rich examples of successful athletes who have satisfied task constraints in unique ways. Learning could be viewed as a ‘personal struggle’ to achieve successful performance solutions as things change (e.g., due to effects of ageing, injuries, lack of conditioning or practice time). In this respect, an evolutionary biological perspective on constraints may be useful in helping us to understand how solutions to performance problems can be evolved over different timescales for each individual to satisfy constraints.

• For this reason, the key unit of analysis from a constraints-led view is the individual performer. Variability in movement performance needs to be carefully interpreted. For each performer, sometimes, high levels of variability help in adaptation to the environment, on other occasions low levels help increase performance stability.

References

Adé, D., Seifert, L., McGann, M. & Davids, K. (2021). Enactive and ecological dynamics approaches: Complementarity and differences for interventions in physical education lessons. Physical Education and Sport Pedagogy. DOI:10.1080/17408989.2021.1999919

Araújo, D., Davids, K. & Hristovski, R. (2006). The ecological dynamics of decision making in sport. Psychology of Sport and Exercise 7, 653-676. [NB. this was the first paper to use the term ecological dynamics]

Chow, J.-Y., Davids, K., Button, C. & Renshaw, I. (2022) (2nd Edition). Nonlinear Pedagogy in Skill Acquisition.. Routledge: London.

Glazier PS. (2017). Towards a Grand Unified Theory of sports performance. Hum Mov Science 56:139-156. doi: 10.1016/j.humov.2015.08.001.

Handford, C., Davids, K., Bennett, S. & Button, C. (1997). Skill acquisition in sport: Some applications of an evolving practice ecology. Journal of Sports Sciences 15, 621-640.

Kelso, J.A.S. (1995). Dynamic patterns: The self-organization of brain and behavior. Cambridge: MIT Press.,

McClymont, J., Davids, K., & Crompton, R. (2022). Variation, mosaicism and degeneracy in the hominin foot. Evolutionary Human Sciences, 4, E2. doi:10.1017/ehs.2021.50

Montagne, G., Cornus, S., Glize, D., Quaine, F., & Laurent, M. (2000). A perception-action coupling type of control in long jumping. Journal of motor behavior, 32(1), 37-43.

Renshaw, I., & Davids, K. (2004). Nested task constraints shape continuous perception–action coupling control during human locomotor pointing. Neuroscience Letters, 369(2), 93-98.

Rothwell, M., Davids, K., Stone, J., O’Sullivan, M., Vaughan, J., Newcombe, D. & Shuttleworth, R. (2020). A Department of Methodology Can Coordinate Transdisciplinary Sport Science Support. Journal of Expertise 3, 55-65.

Savelsbergh, G.J.P. & Davids, K. (2002). Keeping the eyes on the ball: A tribute to the legacy of John Whiting (1929-2001) in Sport Science. Journal of Sports Sciences (Guest Tribute) 20, 79-82.

Scott, M. A., Li, F. X., & Davids, K. (1997). Expertise and the regulation of gait in the approach phase of the long jump. Journal of sports sciences, 15(6), 597-605.

H.T.A. Whiting, O.G. Meijer and P.C.W. van Wieringen (1990) (Eds.), The Natural Physical Approach to Movement Control. Amsterdam: Free University Press.