3    Interacting constraints and self-organisation tendencies

In Chapter 2 we argued that a most significant challenge in sport concerns the continuous re-organisation of movement system degrees of freedom during performance to produce functional solutions. Human beings can adapt actions continuously by exploiting inherent movement system self-organisation tendencies, which are available to all biological organisms, such as bird, fish and insects.

Choreography in the sky: A wonderful example of self-organisation tendencies in open systems exists in a murmuration of starlings, small birds that gather in vast numbers to spontaneously swoop and swirl at high speed at dusk, forming rich patterns of coordinated behaviours on the wing. This breath-taking video clip shows how the movement of each bird influences the co-adaptive movement of immediately adjacent birds and from these local interactions comes global pattern formation. The movements are not pre-planned and orchestrated but emergent under the constraint of interacting locally with nearby birds:

(A Murmuration of Starlings https://vimeo.com/31158841).

Ecological Dynamics argues that spontaneous self-organising tendencies also exist in the movement systems of athletes (e.g. when running on a track [more quickly or slowly, when facing a head wind or in slippery conditions]). Tendencies for self-organisation under constraints can be exploited in many dynamic performance contexts. (For example, when running on a variety of surfaces (stable and unstable) such as rocky trails, race tracks (when wet or dry), sand dunes or mud. They are also important in the interpersonal interactions of competing and cooperating team games players performing on different surfaces, indoors and outdoors, in different venues and against different opposition playing styles and in varied game formats.

In sport, self-organising coordination tendencies emerge within and between individuals as they engage with the task and performance environment. These coordination tendencies can support intra–individual–environment or inter–individual–environment interactions. They result in the formation of localised synergies between body parts in an individual athlete (a coordination pattern to achieve a specific performance goal) or between team members (a pattern of interactions in an attacking phase of play or in a defensive unit). Inter-individual co-ordination tendencies also emerge between opponents, for example, when an attacker tries to run past a defender. System interactions spontaneously emerge when previously uncorrelated components (neurons, muscles, joints in an individual performer or teammates and opponents in a sports team) form groupings or synergies that are interrelated and entrained under ecological constraints of competitive performance environments.

Complex adaptive systems like athletes and sports teams display these hallmark properties of synergy formation under constraints and sensitivity to surrounding information. In different sport performance contexts, a key strategy is to identify the nature of the information that constrains self-organisation tendencies over different timescales. Synergies in movement systems and sports teams are temporarily assembled to achieve specific performance goals. Because synergies can be rapidly put together and dissolved quickly, athletes and sports teams can enjoy both stability and flexibility of action. They are flexible, stable and exquisitely context-dependent, meaning that synergies are rapidly adaptable to changing circumstances. The functionality of a synergy (i.e. its usefulness and relevance for supporting performance) evolves over time through experience, practice and learning: more useful and relevant synergies are strengthened, and less useful ones are de-stabilised over time because of their growing irrelevance. In an invasion game context, a defender will self-organise and manipulate the body and foot position in a 1 v 1 situation to channel an attacker away from goal and apply appropriate pressure on the ball. This type of body orientation towards the opponent and the ball is a temporarily assembled synergy. If the attacker changes his/her attacking angle, speed or direction, the previous synergy will become irrelevant and a new synergy will be required. In this respect, skill acquisition (i.e. skill adaptability) is an evolutionary process, rather than a revolutionary one.

A pause to gather your thoughts: While self-organising tendencies can spontaneously emerge in athletes and sports teams, they can be exploited by applying specific task constraints during practice to shape the formation of stable, yet adaptable synergies. This is why it is always a good idea to consider that self-organisation tendencies emerge under constraints, so that these processes can be exploited in learning designs for specific performance behaviours.

Newell’s model of interacting constraints

In Newell’s (1986) model, interacting constraints have been defined as boundaries or features that shape the form of a complex adaptive system searching for functional states of organisation. Performance functionality implies being able to make sense of a particular performance context and then to carry out intended tasks and activities during behaviour that is goal-directed. Constraints act to reduce the number of configurations available to a complex, dynamical system at any instance. They help to structure the number of possible system configurations for an individual. It should be pointed out that system configurations are based on the current action capabilities of an individual or team at any one time. This might mean that the emergent co-ordination patterns may not fit the optimal movement solutions often reported as ‘classical techniques’ in coaching books. However, these emergent movement patterns may be the best fit in terms of what the individual’s intentions are at a specific point in time. For this reason, coaches of young performers should not consider their performance in the same way as they may view adult performance levels. Children are not mini-adults, but rather are at varying stages of development and maturation which constrains their behaviours.

There are many classes of constraints that can shape the behaviours of a complex dynamical system and it has been well documented that Newell (1986) considered individual (termed ‘organismic’), task and environmental constraints to be the most influential (see Figure 3.1 for some examples). Organismic constraints refer to the personal characteristics of each individual, such as genes, height, weight, muscle-fat ratio, cognitions and patterns of thinking, amount of previous experience and learning, motivation, emotions, feelings and desires. They need to be considered carefully by coaches since such personal constraints vary between and within each individual over different timescales. They can be influenced by factors operating over timescales of learning (hours, days, weeks) and maturation, ageing and development (months and years). Environmental constraints are more global, and can consist of physical variables in nature, such as ambient light, temperature, or altitude, or social features such as historical, cultural and societal values, beliefs and customs. Task constraints are more specific to performance contexts than environmental constraint and include task goals, specific rules associated with an activity, use of activity-related implements or tools and particular surfaces or objects involved in performance (Davids et al., 2008).

What can we learn from evolutionary science?

Constraints are specific to performance niches and operate at many different levels of the system or the environment and at various timescales. This is what makes them challenging to use in practice task design (the ‘what’, ‘how’, ‘when’, ‘whom’ and ‘why’ questions raised earlier). Organisms are also shaped by system pressures over longer timescales in an evolutionary process, where personal constraints interact with environmental constraints. At the level of a species, they are allied to selection as part of the evolutionary process that guides biological organisms toward functionally appropriate behaviours in a particular niche or habitat. This idea from evolutionary science can be applied to understanding sport performance behaviours. When a talented young games player moves up to the next performance level, in team games for example, the time and space available to perform skills is generally decreased and the young learner must adapt his or her actions to successfully survive and then thrive in this new performance niche. The relationship between the organism and the environment defines a ‘form of life’ for that species. This concept can be applied to the context of sport and exercise by defining different units within a team as a separate ‘species’ all with their own forms of life. Defenders, midfielders, forwards and goalkeepers, for example, could all be viewed as different species. A squad of club players could be defined as different to a squad for international athletes, with a different niche in the world and, therefore, different forms of life. A niche is a set of multi-dimensional affordances for a particular individual (Chemero, 2003; Heft, 2003). We will discuss this concept in more detail in the following chapter.

Figure 3.1  Examples of interacting constraints.

At the performance-relevant timescale of perception and action (micro-seconds or fractions of a minute), constraints operate to select emergent patterns of behaviour in a continuous ‘adaptation + feedback’ loop. In sport performance, functional patterns of behaviour can be explored and refined over time by athletes as they emerge under interacting constraints. Coaches could understand how to interact personal constraints of individual learners (e.g. training status, level of experience, skill needs) with specific task constraints, such as performance space, time, properties of objects and implements used, and task goals of practice. Environmental constraints could also be integrated into the most efficient of practice designs by harnessing weather conditions, travelling to train at altitude and by simulating social and cultural constraints of competitive performance environments. Cultural environments are important factors that should be carefully considered by practitioners. Culture is an important component of the ‘form of life’ of coaches in sports (as introduced previously and discussed in depth in later chapters) and is shaped by the history of practice and by practitioners in the moment, in terms of what they say to learners and performers in addition to how they lay out the physical environment. Cultural constraints are, therefore, shaped as much by the philosophy of the practitioner, which sits within the culture of an individual sport, organisation or school ethos. In Chapter 4 we examine the important effects of social and cultural constraints in more detail.

In order to ensure a close simulation of competition conditions, the interaction of categories of constraints during practice should be continuously framed by cognitions and intentionality of athletes: that is, performance during practice should always be framed by striving for specific goals, objectives and aims of an athlete or sports team. Framed intentionality forms the basis of the ‘adaptation + feedback’ loop that guides an athlete’s motivation and performance awareness during practice.

Through manipulation of key interacting constraints, more functional (relevant and useful) patterns of behaviour gradually become more stable over time, and less functional states of system organisation are destroyed (due to their instability). Sport practitioners should allow athletes to gain experience in exploring a variety of task designs, learning how to find performance solutions that are most functional and then continuously refine them through exploiting feedback loops. The notion of ‘adaptation + feedback’ underpins Bernstein’s (1967) conceptualisation of practice as ‘repetition without repetition’.

How cognition, perception and action support goal-directed behaviours

In performance and practice, the process of establishing a stable perception–action coupling (the basis of skilled performance) is deeply integrated with knowledge predicated on specific intentions and cognitions. An athlete maintains contact with a dynamic performance environment by continuously using his/her cognitive activity and perceptual information to guide interactions.

For example, a performer may decide to: reach and grasp an object moving in space, or avoid an individual running to make a tackle, or accelerate through a gap between two opponents, or simply to stand still. An athlete’s intentionality expresses their cognitive activity through anticipation, memories, attention and decision-making. Intentions, perception and action are completely intertwined, functioning in an integrated way, and none of these processes can function in isolation of each other. One cannot act without perceiving and one cannot successfully perceive information from the environment without acting. The implication for practice is that this continuous coupling of perceiving and acting needs to be continually framed by an athlete’s intentions.

It is worth noting that Kelso (1995) viewed intentions as a most important source of constraint: a specific informational constraint that could be used to stabilise or destabilise existing system organisation, depending on needs, wishes, desires of an individual. In sport, intentionality is very much related to skilled performance and the capacity to select amongst available affordances. Skilled intentionality (Kiverstein & Rietveld, 2015) is defined as ‘the individual’s selective openness and responsiveness to a rich landscape of affordances’ (p. 701). This is the fundamental essence of decision-making in sport, which coaches can harness and develop in training designs: adaptive behaviours can emerge continuously from the confluence of constraints framed by intentions embedded within agreed and negotiated task goals.

These ideas suggest that it is important to design opportunities for action that allow athletes to continuously seek perceptual information from a learning context to couple with their intended actions. In the next sections of this chapter, we will discuss some examples of how skill may be enhanced by allowing localised action solutions to emerge as internal and external system conditions change. This ‘adaptations + feedback loop’ harnessed by athletes, using representative practice task designs, can lead to a tight coupling of perception and action sub-systems during performance.

To summarise so far, Ecological Dynamics is an integrated framework with four features of significance for understanding sport performance and how it can enhanced in practice: (i) the individual–environment relationship is the fundamental level of analysis for scientists and practitioners wishing to understand performance and learning in sport; (ii) behaviours emerge from self-organisation tendencies in multiple subsystems; (iii) interacting constraints shape these emergent behaviours; and (iv), designing opportunities for action or affordances into landscapes for learning can guide individuals to use actions to explore perceptual information available.

Manipulation of constraints in individual sports

An important personal constraint in sport is the experience and expertise that an individual brings to the performance context. Ecological Dynamics highlights how the nature of perception–action couplings is not the same for beginners and experts, since the expert is more capable of exploiting information about environmental and task-related constraints in order to continuously reorganise the multiple degrees of freedom of the body. The greater adaptability of experts to a variety of interacting constraints emphasises the functional role of movement variability in supporting sport performance. Movement system degeneracy allows a skilled performer to explore different motor solutions, facilitating the discovery of functional patterns of coordination. By harnessing system degeneracy, with practice, a learner can structurally adapt his/her motor organisation without compromising function in order to satisfy task constraints (gaining feedback that strengthens the possibility of the action re-emerging in similar situations in the future). In complex performance environments, skilled athletes are able to perform several types of movement and/or to switch between synergetic modes of coordination in order to achieve the same functional performance outcomes. This capacity for flexible variability in exploiting motor system degrees of freedom for achieving task goals was demonstrated by Hristovski et al. (2006), who investigated how boxers adapted their strike patterns when they were asked to punch a heavy bag from various distances, without any precise verbal instructions. The task was simply to hit the heavy bag as hard as possible with any boxing action. At further distances from the boxing bag, a ‘jab’ action with a straight arm tended to emerge, whereas at close distances ‘uppercuts’ or ‘hooks’ patterns appeared. Intermediate distances from the boxing bag represented a meta-stable performance region (i.e. where a range of useful behavioural solutions could emerge). In this region, varied and creative range of movement patterns occur such as ‘uppercuts’, ‘hooks’ and ‘jabs’ (Hristovski et al., 2006). These observations suggested that the boxing striking patterns transitioned according to the perception of a ‘strikeability’ affordance (i.e. the perception of distance information to a target invited certain actions). This type of affordance-based regulation of action has also been reported in other individual sports like rock climbing. Boschker et al. (2002) previously analysed the perceived structural features of climbing walls and climbing opportunities (defined ‘climbing’ affordances by Boschker and co-workers). The results showed that unlike the beginners, expert rock climbers were able to utilise more information and perceive the functional properties of the climbing wall, showing greater exploitation of climbing affordances. Rock climbing affordances include hold reach-ability, grasp-ability and climb-ability. Note how all these affordances emphasise opportunities for climbers to interact with important surface features. An important consideration is the interaction between an individual’s intentions and how they perceive the environment. For example, a beginner level climber who is focused on not falling off the rock will attune to different affordances (e.g. closer holds that help them maintain a forward facing orientation to the rock) than an experienced climber who is looking to move up the rock face fast (e.g. potential holds that require body orientation changing to be ‘side-on’ to the rock). Interestingly, skilled climbers were only as good as the novices in perceiving the structural features of the climbing wall, such as colour and or hue of the surface. This type of knowledge is based on perceptual processes that support a verbal description about the environment. Gibson (1966) called this ‘knowledge about’ the environment. According to Gibson’s (1977) ideas, knowledge about the environment can be learned indirectly via exposure to images, pictures, video analysis or other sources of symbolic information, which facilitates the provision and sharing of explicit information between athletes and coaches. One example of this type of knowledge occurs when a coach communicates specific information (principles of performance) to athletes, in a learning environment (coaching session), or even in a team meeting or briefing session preceding performance. This may involve instructing an athlete when and how to act in a specific performance situation. Through verbalised/pictorial/graphic information, a platform of shared knowledge can be designed that may be collectively internalised among athletes and support staff, thus allowing shared understanding and coordination of activity (Figure 3.2). For example, a coach may show video clips of opponents to direct her players’ attention to specific features of an opponent’s movements or specific patterns of play.

In contrast, Gibson (1977) proposed that information for action is predicated on ‘knowledge of’ the environment, which supports the perception and utilisation of affordances. This type of information can be designed into practice environments full of invitations for the emergence of different performance behaviours. This emphasis in learning design provides opportunities for interactions allowing athletes to seek, discover and exploit affordances to support performance in specific sport contexts.

Figure 3.2  Verbal instructions have value in guiding the search of athletes for functional task solutions during practice. Verbal guidance should be composed of ‘knowledge of’ the environment to invite athletes to seek and utilise affordances in a performance landscape.

This idea was exemplified in an intervention study investigating affordances designed into traditional training practices in elite springboard diving. Barris and colleagues (2014) studied preparation for take-off in an elite sample of Olympic-level springboard divers when diving into a pool and under the different task constraints of training in a dry-land facility comprising a foam pit. Elite divers tend to routinely practise in separate training environments (dry-land and pool), affording differences in final performance outcomes. The watery surface of a pool afforded penetration with the hands of the divers, whereas the harder texture of foam pits in the dry-land facility afforded landing feet first. Divers seek to practise the same preparation phase, take-off and initial aerial rotation in both practice environments, although there is little empirical evidence to suggest that the tasks completed in the dry-land training environment are representative of those performed in the pool environment. The concept of conditioned coupling in Ecological Dynamics signifies that performance of different movement components would remain dependent on each other, and slight variations in task constraints could lead to different emergent coordination patterns (Davids et al., 2013). In line with these theoretical predictions, it was expected that emergent self-organisation tendencies under the affordances of the two distinct task constraints would lead to differences in preparation. Barris et al. (2014) observed similar global topological characteristics in all participants who used the same joint coordination patterns during dive take-offs completed in the dry-land and aquatic environments. However, as a group, participants showed statistically significant differences in performance at key events (second approach step, hurdle step, hurdle jump height and board angles during the hurdle and at landing) during the preparation phase of dive take-offs completed in dry-land and aquatic training environments. For example, participants showed significantly less board angle depression at landing (from the hurdle jump) during take-offs completed in the dry-land area (M = 14.27, SE = 0.24), than those completed in the pool (M = 15.99, SE = 0.26). It is possible that the different affordances of the distinct learning environments may have led these subtle differences in performance behaviours to emerge. The findings highlight the sensitivity of learners to the design of learning tasks since such subtle differences in actions emerged under the different task constraints.

Manipulation of constraints in team sports

Manipulation of task constraints in team sports has mainly focused on understanding how coordination emerges from interactions between players within and between teams, under the constraints of competitive performance. Passos, Araújo and Davids (2016) summarised work on the continuous interactions that emerged at different scales of analysis (between dyads – in 1 v 1 situations – and between and within sub-groups – attacking and defending units of players).

Dyads

A considerable amount of research has sought to identify coordination patterns in attacker–defender dyads in team sports over the past two decades. Dyadic systems are formed by 1 vs 1 interactions during performance and are considered the basic unit of analysis for studying interpersonal coordination tendencies in team sports (Passos et al., 2013). Dyadic system relations in competitive matches reveal the pattern forming dynamics that are the essential unit of analysis for understanding how the microscopic degrees of freedom (competing team sports players) co-adapt their actions during performance.

Research suggests that successful performance in team sports demands that athletes learn how to interact with teammates and opponents to achieve their goal. The continuous interactions that emerge as athletes co-adapt to each other’s behaviours are constrained by locally created information from the actions of each individual involved in a dyadic system (Passos, Araújo, & Davids, 2016). This information emerges from interactions with a range of different task constraints, including field locations, markings and boundaries, and rules, which act as boundary constraints on the relative co-adaptations of players. A significant source of information that constrains performance behaviours is the relative co-positioning of interacting players during performance as they compete to find/restrict space and time and achieve performance goals. Research has shown how actions of performers are continuously modified due to the presence and location of significant others onfield. For example, Orth et al. (2014) investigated the characteristics of competing attacker–defender dyads in football, investigating how performers modulated their running velocity to kick a stationary ball, under the constraint of defensive pressure. Approach velocity and ball speed/accuracy data were recorded from eight youth players, as they ran to cross a ball to a teammate in an attacking position. Defensive pressure was manipulated in three counterbalanced conditions: without defenders present, with a defender positioned far away, and with a defender positioned near the player crossing the ball. Findings showed that players altered their actions under changing task constraints without any instructions from the experimenters. For example, ball speed during the cross was significantly reduced as defensive pressure increased by locating the defender closer to the starting position of the attacker. In footfalls during the final approach to the ball, running velocity was dependent on both presence and initial distance from a defender as a key task constraint. Despite these changes to movement organisation, passing accuracy was maintained under changing defensive pressure by the skilled footballers. Overall, the results showed how the regulation of kicking behaviours is specific to the design of a performance context. Some features of movement organisation emerge under varying task constraints, for example as the presence of a defender is manipulated during performance.

Another study investigating dyadic system behaviours in soccer by Headrick et al. (2012) showed how field location for performance constrained the regulation of action by players. They sought to determine whether spatiotemporal relations between players and the ball in 1 vs 1 dyadic systems were constrained by their distance to a goal area. They observed each participant performing as an attacker (dribbling the ball) and defender. The modification of the distance of the dyadic system to the attacking goal area shaped players’ behaviours and intentionality. A key variable ‘defender’s-distance-to-the ball’ appeared to be a critical collective variable. The percentage of trials in which the player in possession of the ball dribbled past the defender revealed higher success rates in positions closer to the goal. The implication for coaches here is that even the smallest modifications to the details in the design of practice tasks can shape the interactive co-adaptations between players in 1 vs 1 dyads.

Sub-phases of play during practice

Dyadic systems represent the basic scale of interaction within many team (invasion and field) games; research also suggests that more complex sub-phases of play are important for understanding the patterns of coordination emerging when players form larger synergies during performance. The implication of these studies is that small-sided and conditioned games (SSCGs) provide an opportunity to practise performance in a sub-scaled version of the whole, formal game. Different SSCG formats can effectively condense and specify constraints of competitive performance contexts and help to potentiate the emergence of specific technical and collective tactical behaviours (Ometto et al., 2018), as well as to provide opportunities to experience physical, physiological and technical demands of competition in a contextualised simulation. An important benefit of SSCGs is that they provide coaches with opportunities to manipulate key task constraints, such as player numbers involved, as well as space and time, which aid the development of tactical intentionality in players during different sub-phases of play. The development of tactical performance behaviours depends on task design since a well-designed SSCG simulates key aspects of the competitive performance environment. This enables players to reproduce the behaviours needed in the type of dynamic competitive environment where there are opportunities for players to experience the ‘repetition without repetition’ that Bernstein (1967) envisaged was the cornerstone of relevant practice.

For example, 2 vs 2 in basketball can provide a useful context for learning many different skills and basic tactical patterns when attacking, transitioning and defending in the team sport. Similarly, 7 vs 7 in rugby union can be relevant for gaining increments in physical conditioning, tactical understanding and skill acquisition. Indeed, SSCGs are also useful for experiencing the structural and functional patterns that emerge in full-sided versions of a game. An important consideration for practitioners is to consider the representativeness of the SSCG in terms of the full-sided version of the game. Failure to do so would only lead to the transfer of generic skills rather than specific skills (ideas, perceptions and actions), which would be less useful in the full-sided game.

Coaches often refer to the ‘centre of gravity’ of a team during play. An operational definition of this concept is a team’s centre (also known as centroid, or geometrical centre). This measure has been used in various ways to evaluate intra- and inter-team coordination during sub-phases of play in team sports. Team centres can represent, in a single variable, the relative positioning of both teams in forward-backward and side-to-side movement displacements of sub-systems (e.g. 3 vs 3 in basketball or 4 vs 4 in football). Principles of play in team sports suggest that the team in possession of the ball should seek to create space by stretching and expanding the team centre in play (increasing distances between players), while a defending team should restrict space by contracting and reducing distances between players. Such collective behaviours have been captured by specific measures of team coordination in performance analysis that quantify the overall spatial dispersion of players in play. The stretch index (or radius), the team spread and the effective playing space (or surface area) are measures that record such spatial distributions. Also, it is important for a successful team to outnumber the opposition (creating numerical overloads) during different performance phases (attack and defence) in specific locations adjacent to the ball, expressed through inter-team coordination variables. These measures capture the existence of possible differences in players’ interactive behaviours at specific locations on field (e.g. wings and midfield sectors). Research in sub-phases of football has shown how the centroids of competing teams approach and move away from each other’s defensive lines in a systematically interrelated (ebbing and flowing) manner, particularly just before loss of stability. The emergence of such characteristics was stimulated to a prominent degree by the distance values between an attacking and defensive line of players, which suggests that the design of SSCGs needs to consider the effects of playing area dimensions on tactical behaviours that emerge during practice. Likewise, emergent playing patterns in SSCGs (4 vs 4), measured by centroid positions and surface area measures of competing teams, displayed synchronous tendencies to move in the same directions during a competitive game. Findings revealed a stronger association between forward-backward and lateral oscillations of centroids. There is still a need for more research to understand whether the dynamics of some collective variables (e.g. team centroid and surface area) that emerge during performance in SSCGs, with a reduced number of players (e.g. 3 vs 3, 4 vs 4, 7 vs 7), correspond to patterns observed in full-sided games.

The micro-structure of practice

What should coaches/teachers have in mind when they use a constraints-led approach to design effective practice tasks and learning activities, undertaken daily, weekly and monthly, in preparation for the physical, psychological and emotional demands of competitive performance? The micro-structure of practice, day in-day out, involves pedagogical activities that include tasks designed, constraints manipulated, intentions harnessed, emotions experienced and adaptive interactions required of athletes continuously during learning. Adopting an individualised approach, based on the needs of specific athletes, coaches can vary the nature and intensity of these sport performance aspects. Well-considered manipulations of constraints should create individualised problems and challenges for learners, which simulate key aspect(s) of a performance environment (whether physical, cognitive, emotional, social or a mixture of these features).

Facilitating athlete dexterity in the micro-structure of practice

As previously mentioned, all coaching methodologies involve constraints manipulations of some sort. However, traditional pedagogies tend to focus on a narrow range of constraints being manipulated in practice, especially early in learning, to ensure that athletes can repeat actions and rehearse movement patterns in drills. Sometimes, to make matters worse, drills designed in the micro-structure of practice are performed at low-intensity levels in static conditions, with minimal information being present.

All athletes, whether beginners, advanced learners or experts, can benefit from using their cognitions, perceptions and actions in an integrated way to solve problems that they may encounter during competitive performance. Solving performance problems and meeting challenges with actions enhances ‘dexterity’ in individuals. That is why practice task constraints should be designed to encourage exploration of relevant performance solutions needed in competitive environments. Exploratory activity is an integral part of human development and babies (for example) spend a lot of time in their infancy exploring the environment to learn about affordances of objects and surfaces and other people (Gibson, 1988). Continuous exploratory interactions with the environment, termed ‘experiments on the world’ by Gibson (1988, p. 7) are typical in human development and lead to skills that can be harnessed in later athletic development when people start to specialise in competitive sport.

Through continuous interactions with equipment, space, other individuals and events, during sport training and practice, athletes can be supported by coaches in exploring the range of affordances available in a perceptual-motor landscape of possible performance solutions (Davids et al., 2016). Practice needs to help athletes develop individualised and contextually functional motor solutions, rather than to rehearse and reproduce a collective ‘default technique’ or optimal movement ‘template’, towards which all athletes should aspire (Brisson & Alain, 1996; Chow et al., 2016).

Figure 3.3  Drills in practice are over-used, emphasising repetition and rehearsal of specific movement patterns in static performance conditions, rather than the search for functional action solutions.

Designing opportunities to display dexterity during practice in tennis and rugby union

This Bernsteinian perspective emphasises that a fundamental aim of practice is not to ‘optimise’ performance of specific movement pattern through repetition and rehearsal. Rather, dexterity implies athletes enhancing their skill in co-adapting to the conditions of a performance environment. To achieve this aim, practice micro-structure should continuously seek to present each learner with a wide range of tasks and conditions that they need to explore. This type of design would enhance the dexterity of an athlete by helping him/her to become more adaptive, innovative and flexible to cope with variations in task and environmental constraints. For example, in the sport of rugby union, a challenging decision is when to kick the ball upfield to create attacking opportunities and when to run at a defence with ball in hand. Designing an ‘affordance field’ in practice, athletes can be encouraged to co-adapt their decisions and actions to what an opposition’s defensive pattern invites. Athletes can be required to adapt their actions throughout an unfolding practice game, employing a kicking game against the opposition depending on what their defensive strategy offers them. Essentially, coaching in these games involves asking players to consider ‘where is the space?’ and ‘what are the best ways to get the ball in the hands of a team mate/player in that space?’ – something we address in Chapter 5 when we present the Environment Design Principles for coaches. If the defence leaves the full back behind the pack (forwards) alone, with the defending wingers also playing high up the pitch, performers may be encouraged to notice the spaces around the full back that invite them to kick the ball more frequently into these areas. If the wingers hang back, then it means that there is more likely to be space around the outside of the defensive back line, inviting a potential overload situation if the ball can be moved wide quickly enough. Therefore, kicking more or less frequently, when attacking, will emerge, depending on what the defensive formation affords for the attacking team. Coaches could change affordances in the micro-structure of practice, making sure that, every day, training and practice abound with problem solving scenarios, just as implied in Bernstein’s (1967) ideas on developing dexterity.

Being able to perceive and use affordances, as opportunities for action, is a major feature of each individual’s capacity to co-adapt to task and environmental constraints which coaches can facilitate in the designs they use for practice. This idea has been exemplified in the work of Anna Fitzpatrick and colleagues in tennis, a sport known to be initially challenging to become proficient at, due to the coordination demands of manipulating a racket to intercept a ball travelling at high speeds, the movements required to cover the relevant court areas and tactical behaviours needed when playing against opponents with different characteristics (tall, fast, left-handed, power-serving, to highlight a few), in singles and doubles tournaments.

Fitzpatrick et al. (2017) considered that, when designing practice tasks in tennis, scoring format, court dimensions, net height and ball characteristics are key task constraints. Manipulating these constraints in practice enables inexperienced participants to perform, without the need to contend with the challenging constraints of the full version of the game. However, it is important that the modified practice environments help to simplify performance constraints, allowing learners to maintain and enhance perception–action couplings required during performance in the full version of the sport. For example, a tennis ball with reduced compression will bounce lower on court, facilitating young players’ forehand and backhand performance, by allowing them to adopt a swing height that is scaled to their current body dimensions. This re-scaling in practice is useful for the long-term development of their groundstroke skills, compared to the racket swing height needed to strike a regulation tennis ball that bounces higher on court. Evidence suggests that the constraints favoured within mini versions of tennis influence emergent behaviours of players during practice. To exemplify, tennis balls with low compression levels positively influence children’s forehand groundstroke performance. Reducing ball compression from 100% (i.e. regulation tennis balls) to 75% has been reported to increase the amount of net-play and elicit a better bounce height for young children learning to hit the ball with groundstrokes, re-scaled to their dimensions. Fitzpatrick and colleagues advocated that the use of modified tennis balls, providing a longer flight phase and lower bounce height due to lower compression, should enable participants to maintain control of rallies for longer, in turn facilitating the development of a wider range of strokes. They summarised previous research into the effects of manipulating court dimensions and net height on emergent behaviours of skilled young players on court. Evidence from research showed that, although average rally length did not differ between conditions, smaller court dimensions elicited fewer winners, and a reduced net height elicited a greater number of winners. Fitzpatrick and co-workers (2017) concluded, therefore, that manipulating key task constraints, such as reducing court dimensions and net height, created a relevant environment for young children learning to play tennis. An interesting video on YouTube shows how modifying court sizes, racquets and ball types can lead to junior games that are highly representative of the adult games. Essentially, the video clearly demonstrates how the junior game can be adapted to ‘look and feel’ like the ‘real’ game (www.youtube.com/watch?v=3IbzcttoDuY&feature=youtu.be).

Harnessing self-organisation tendencies when coaching

The examples from rugby union and tennis suggest how coaches can use task constraint manipulation as a basis for designing practice tasks that can exploit the tendencies for self-organisation that exist in humans (Figure 3.4).

It is clear that the role of verbal instructions is minimised, and direct teaching or coaching is only used when needed by a coach. In other words, verbal instructions and direction is simply another tool in the ‘methodology’ of a coach. However, direct verbal instruction tends to be over-used in pedagogical practice and is often ‘over-advocated’ in coaching manuals and courses. It tends to be viewed as a ‘default’ methodology that many coaches view as absolutely essential to their practice. There is evidence that constraints manipulation is effective in helping learners to acquire skills and maintain a high level of engagement and motivation in sport and physical education contexts, as exemplified by the work of Brendan Moy and colleagues (Moy et al., 2014, 2015). In their work, they demonstrated that allowing novice hurdlers to choose the level of difficulty when presented with a row of hurdles of different heights and distance apart enhanced perceptions of competence, autonomy and relatedness. If early coaching experiences are as much about hooking children into sport, these findings are debatably just as important, if not more so than the actual skill learning that did take place.

Figure 3.4  The work of GB athletics coach Matthew Wood in manipulating informational constraints to guide the exploration of the run-up in hurdling exemplifies how verbal instructions can be kept to a minimum as the learner adapts to obstacles and signs in the environment to regulate the approach to the hurdle.

Coaches are ultimately responsible for planning and structuring practice programmes by selecting from a variety of particular task constraints to attune each performer’s attention to relevant information sources in performance settings. Their role is to manage intended self-organisation processes of individual and team tactical behaviours in achieving a specific objective to be accomplished in different phases. The main challenge of performance coaches is to develop the excellence of an individual athlete or team in practice by harnessing self-organisation tendencies of individual and team behaviours, concomitant with the application of particular intentions or tactical principles. During practice, self-organisation tendencies can be managed, driven and guided by a team coach in each phase of a competition, delimited primarily by the definition of performance intentions and tactical principles, agreed in the athlete-coach relationship. By manipulating specific key task constraints during coaching sessions, coaches may provide important information sources or shared affordances (agreed upon opportunities for action relevant collective sports and games) that support a specific communication system between athletes (or between athlete and coach), allowing self-organisation tendencies to be exploited. During preparation for competitive team games, for example, players learn to couple actions to form an interpersonal synergy (e.g. functional grouping of two or more performers in attack or defence). The couplings emerge from self-organisation or adjustments between teammates and are strengthened during practice, underpinned by the collective perception of shared affordances. The concept of shared affordances is key in team sports and requires an intimate knowledge of one’s own affordances or action possibilities, those of team mates and those of opponents. It is clear that creating effective inter-personal couplings is very demanding and only the best team seems to possess this knowledge. Players need to be given time to create synergies where every player intuitively knows how a team mate is going to act at any one time.