The importance of interacting personal, task, and environmental constraints on the emergent behaviors of individuals, as they assemble functional states of movement organization in achieving task goals, is well established. Personal (or organismic) constraints include factors such as individual anthropometrics (height, weight, and limb lengths), fitness (strength, aerobic capacity, and flexibility), mental skills (concentration, emotional control, and motivation), perceptual and decision-making skills (recognizing patterns of play, anticipation by reading the movements of opponents) and personality factors (risk taking behaviors). As part of his constraints model, Karl M. Newell distinguished between physical environmental constraints, such as gravity, ambient temperature, and altitude and task constraints, which are task related and concerned with the goals of a specific activity. More recently, sociocultural constraints, such as family support, cultural expectations, and access to facilities, have also been considered as environmental constraints. In the study of sport performance, task constraints can include factors such as rules of games, equipment used, boundary playing areas and markings, nets and goals, number of players involved in a practice task, and the information present in specific performance contexts. In sport, task constraints can be most easily manipulated by coaches and teachers to channel the acquisition and performance of specific coordination patterns and decision-making behaviors.
Emergence of ecological dynamics (the fusion of dynamical systems theory and ecological psychology) has developed understanding of how information constrains movement coordination due to the reciprocal link between perception and action. Informational constraints, such as highly structured optical energy arrays formed by light reflecting off objects within the performance environment, represent a most significant task constraint. Indeed, the information available in specific performance contexts can be perceived and used directly by athletes to shape their ongoing behaviors and movement responses.
A key point is that individual, environmental, and task constraints all interact in order to shape the way that a performer achieves a specific task goal. Constraints can be deliberately manipulated by practitioners, such as physical conditioning, equipment modification, pitch sizes, or “rules” of a practice task, or they can be outside their control like the physical environment including weather patterns, growth and development of performers, or official changes to rules of a sport. During practice, coaches and teachers manipulate task constraints to direct the ongoing search for functional movement solutions by athletes. Manipulating constraints is a strategy that forms the basis of nonlinear pedagogy. An important task is to identify key constraints that impinge on an individual performer, considered as a nonlinear dynamical system, in order to stimulate the emergence of functional behaviors during goaldirected performance. Sport practitioners need to identify key informational constraints that can lead to transitions in behavior patterns to help performers overcome performance rate limiters (factors that might limit current performance levels).
Task goals relate to the specific intentions and aims of individuals during task performance. With few exceptions, such as predetermined movement patterns specified by the rules of a sport, exemplified by the performance criteria in diving, ice skating, or gymnastics, task goals tend to not precisely specify how a task should be achieved. Movement coordination solutions are, therefore, only optimal for individuals due to the unique interactions between individual, environmental, and task constraints, meaning that the search for a putative general ideal movement pattern or classical technique is a redundant goal in coaching and teaching. Functional movement patterns of an individual performer may vary, even within activities which require high levels of performance outcome consistency, such as a gymnastic vault, a long jump approach run, or a golf swing, because the task, environmental, and individual constraints differ from performance to performance. A good example to demonstrate that individual solutions for outcome goals need not be specified is the penalty save in association football. A functional solution for each goalkeeper is a product of the action capabilities of the goalkeeper. Goalkeepers with a faster dive time are able to leave the initiation of their dive to save the ball until later in the kicking action of the penalty taker. Goalkeepers with slower movement times tend to move earlier and rely more on anticipation processes to start their diving action early in the penalty kick.
Specific rules in sports constrain how sports performers achieve task goals. For example, in the different rugby codes, there are rules common to all formats (i.e. league and union; 7 aside, 13 aside, and 15 aside versions), such as the specifying ball shape and the need for passes to be made backward. There are also some fundamental differences in rules such as those for team numbers, tackling (what the player is allowed to do with the ball once tackled), and game restart rules when the ball is played off the field. These rules constrain the attributes of players most suited to each game type and result in the emergence of different movement patterns and tactics. Even minor rules changes have led to significant changes in the functional movement strategies for achievement and can also lead to variations in the fit between different individuals and rule-based task constraints. In learning design, it is essential that practice tasks include boundary markings since a performance location on field or on court has been shown to lead to changes in individual decision making and actions. For example, research by Headrick et al. (2012) has demonstrated how proximity-to-goal influenced behaviors in a one-on-one practice task in soccer. Players significantly vary their behaviors depending on the distance to the attacking or defensive goal area. Data provided implications for the design of practice tasks in relation to key visual reference points in the environment, such as goals and line markings.
Changes to equipment design can lead to significant changes in the way that athletes meet their performance goals. For example, the Fosbury Flop was a performance solution that emerged coinciding with the use of new technology in the high jump: softer landing areas in modern times. Directing the body over the bar, head and shoulders first and sliding over on one’s back would have likely led to injury without modern technological developments in landing mats. In soccer, the development of waterproof balls led to a 30% increase in kicking distance and led to the development of new kicking techniques in wet climates that had been impossible with heavier nonwaterproof balls. In a well-known performance paradigm shift in soccer, the first players to bend the trajectory of balls when shooting (adding swerve and dip to flight) were South Americans in the 1960s rather than European players. Why was this? Because prior to the 1970s, footballs had a leather skin that picked up moisture as a game progressed in wet conditions. Games played during winter in the Northern Hemisphere led to the ball increasing in mass to almost double its original value. In the generally drier climates of South America, the ball did not pick up as much moisture and mass, with aerodynamic forces having more influence on the lighter ball, enabling skilled players to acquire expertise in bending and curving ball trajectories. With the advent of waterproof balls in the 1970s, Northern European experts were able to re-create the same effects as their South American counterparts. In turn, changes in task constraints like physical characteristics of equipment influenced the tactical strategies available to teams and consequently reemphasized the acquisition of specific shooting and long passing skills in players. These developments showed that practitioners can deliberately manipulate the characteristics of implements to facilitate the reorganization of movement coordination.
Changing task constraints can lead to changes in new individual performance characteristics being best suited to the new task. For example, changes in specification of the javelin in 1986 led to changes in the optimal throwing technique for throwers. Because of the desire to develop javelins that landed point first on every throw, the projectile’s center of gravity was moved forward by 4 cm. The change was observed to result in the optimal technique being a higher release angle. It has also been suggested that the changes would benefit more powerful athletes who could generate high release speeds. Sudden interathlete changes in performance levels can be explained by changes in interacting personal and task constraints.
In sport, as expertise is enhanced, informational constraints designed into practice tasks can progressively attune an individual to the specifying information sources that support the organization of actions and enhance the capacity to adapt to changes in a performance environment. James J. Gibson (1979) proposed that invariant (persistent features) and variant information can act as affordances for action, through which a performer perceives information from the environment in relation to what it offers or demands in action responses. Over time, performers become attuned to information through experience and practice in different performance environments, creating relationships between movement patterning and specific sources of perceptual information (information–movement coupling). The importance of ensuring the presence of key specifying information in practice tasks is captured by the ecological concept of representative learning design. Traditionally, representativeness has referred to the generality of task constraints in a specific research context to the perceptual variables available in actual performance settings. In sports, practice environments are the equivalent of experimental settings, suggesting that they need to be accurately designed to ensure congruence with a performance environment in which the movements will be implemented. Changing the informational constraints on action might result in less representative practice designs and changes to a performer’s acquisition of functional movement control. This idea has been exemplified in cricket batting research. Ross A. Pinder, Keith Davids, Ian Renshaw, and Duarte Araújo demonstrated that batters adapted spatiotemporal characteristics of emergent action when facing a live opponent through the pickup of advanced kinematic information, in contrast to facing balls delivered via a projection machine where movements were delayed through a need to sample early ball flight to determine the bounce point of the ball.
Verbal informational constraints such as instructions or feedback, can constrain the movement patterns adopted by sport performers. For example, an instruction to a tennis player to make sure the first serve goes in will likely elicit a different movement pattern from the server than the instruction is to hit the ball as hard as possible without worrying if it goes out. A more effective pedagogical strategy involves the careful manipulation of task constraints within the context of interacting task, individual, and environmental constraints, facilitating the emergence of functional movement patterns and decision-making behaviors in learners (see Davids, Araújo, Hristovski, Passos, & Chow, 2012).
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