Task Constraints

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.

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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).


  1. Bartlett, R. M., & Best, R. J. (1988). The biomechanics of javelin throwing: A review. Journal of Sports Sciences, 6, 1–38.
  2. Davids, K. W., Araújo, D., Hristovski, R., Passos, P., & Chow, J.-Y. (2012). Ecological dynamics and motor learning design in sport. In A. M. Williams & N. Hodges (Eds.), Skill acquisition in sport: Research, theory & practice (2nd ed.). London: Routledge.
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  3. Headrick, J. J., Davids, K. W., Renshaw, I., Araújo, D., Passos, P., & Fernandes, O. (2012). Proximity-to-goal as a constraint on patterns of behaviour in attackerdefender dyads in team games. Journal of Sports Sciences, 30(3), 247–253.
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  6. Pinder, R. A., Davids, K. W., Renshaw, I., & Araújo, D. (2011). Representative learning design and functionality of research and practice in sport. Journal of Sport & Exercise Psychology, 33, 146–155.
  7. Warren, W. H. (2006). The dynamics of perception and action. Psychological Review, 113(2), 358–389.

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