Movement in Sport




Riding the bicycle to work, walking up the stairs to the apartment, taking a book from the shelf, and playing the violin are all examples of motor activities, which are signified by the planning of future goal states, the coordination of different limbs and various  whole-body  postures,  and  the  regulation of muscle forces during the dynamic control of the different movements. The skillful coordination of such  movement  actions  is  one  of  the  major  challenges in mastering the various tasks of our daily life. To do so, people do not only passively take in the  information  from  the  environment  with  their senses  when  they  interact  with  objects  or  with other  people  but  also  plan  their  movements  in advance to change the environment in a purposeful way. Most of the time, people’s movements are therefore voluntary, goal-directed, and intentional, relying  mainly  on  higher-level  perceptual–cognitive  control  processes.  This  is  markedly  different from motor reflexes, which are hardwired, involuntary,  and  unintentional,  relying  on  lower-level sensorimotor control processes and providing the basic  building  blocks  of  human  behavior  (e.g., stepping reflex, grasping reflex). This entry focuses on  the  performance  of  complex  movements  that can be readily observed in various sport disciplines and  settings.  Of  chief  interest  are  three  aspects: (1)  conceptualizing  movements  within  different taxonomies, (2) practicing movements within different schedules, and (3) mastering movements at different levels of expertise.

Conceptualizing Movements Within Different Taxonomies

There  are  at  least  three  ways  to  differentiate the  various  kinds  of  movements  into  different taxonomies.  The  first  is  to  consider  the  number of  different  movement  elements,  components,  or actions  that  need  to  be  generated  and  executed. In  this  context,  three  different  categories  can  be identified:  discrete  movements,  serial  movements, and  continuous  movements.  Discrete  movements are characterized by a well-defined beginning and endpoint.  The  motor  action  is  usually  executed within a short time window. Examples of discrete movement skills are kicking a soccer ball, throwing punches, or dancing a pirouette. Serial movements  are  of  longer  duration,  as  they  consist  of two  or  more  discrete  motor  actions,  which  are executed in an ordered sequence of events. A gymnastic  routine,  high-jumping,  or  the  turnaround in  swimming  are  examples  of  serial  movement skills.  Continuous  movements  have  no  recognizable  beginning  and  end,  as  the  different  elements are  repeated  in  a  way  that  the  movement’s  final phase  merges  into  the  new  initial  phase,  starting the  whole  series  of  motor  action  all  over  again. Examples of continuous movement skills are running, swimming, and cycling.

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The  second  way  to  classify  movement  skills into  different  categories  is  to  look  at  the  relative importance  of  perceptual,  motor,  and  cognitive elements  and  components  for  task  performance. Perceptual  skills  rely  mainly  on  the  processing of  visual,  auditory,  and/or  tactile  information, whereas  the  execution  of  corresponding  motor action is of less importance. For a catcher in baseball, the demands on the motor elements (and on decision making [DM]) of the catching action are (considerably)  simple  compared  to  the  demands on visual anticipation of the fastball pitch. Motor skills depend primarily on the quality of movement performance. A weight lifter, for example, must be able to maximize his lift-up and push-out actions, in order to realize a heavy weight. Cognitive skills require complex DM and the use of strategies. The strong safety in American football must recognize different  playing  patterns  of  the  attacking  team and come up with quick decisions for his defensive maneuvers. When looking at these three previous examples,  however,  it  should  be  noted  that  task performance  for  each  of  these  different  types  of movement  skills  does  not  solely  rely  on  a  single element or component. Rather, the focus is on the movement element or component, which is mainly “responsible” for successful task performance.

The  third  way  of  skill  categorization  is  to address    the    context-specific    environmental demands  during  task  performance.  On  one  end of  the  continuum,  these  may  be  always  stable and  predictable,  whereas  on  the  other  end,  task demands  may  be  constantly  changing  in  a  most unpredictable  way.  Accordingly,  movements  are either  closed  skills  or  open  skill,  or  they  are  in between  these  two  poles  somewhere  on  the  continuum. The extent to which changes in the environment can be predicted may be further affected by  time  constraints  and/or  the  interaction  with teammates  and  opponents.  Playing  darts  is  an example of a closed skill, where the task demands are always similar and the environmental context does not change, while the discrete movement can be  executed  without  much  time  pressure  and  no physical interaction with the opponent. The same is  true  for  high-jumping  (indoors),  but  the  serial movement has to be adapted to changes in the task context,  as  the  bar  is  raised  higher.  Backcountry skiing  is  more  complex,  because  serial  and  continuous  movements  have  to  be  adapted  to  the (natural) environment of the skiing resort, making this a slightly more open skill. Still more complex and  open  is  the  Olympic  discipline  of  freestyle skiing, because there is high time pressure, as the skiers  race  against  one  opponent  (although  without  coming  into  physical  contact).  Playing  rugby is an example of an open skill, where performance must  be  adapted  to  varying  task  demands  and  a constantly  changing  environment,  under  high time  pressure  and  against  a  number  of  different opponents.

Practicing Movements Within Different Schedules

Movements become skills when they are practiced deliberately. K. Anders Ericsson, Ralf Krampe, and Clemens  Tesch-Römer  defined  deliberate  practice as  “activities  that  have  been  specially  designed to  improve  the  current  level  of  performance” (p. 368). Thereby, distinct changes of performance are  the  direct  result  of  the  activities  experienced during  the  training  session.  Most  all  of  the  time, such  activities  (i.e.,  physical  practice)  lead  to effects  of  performance  improvement,  which  can be  readily  observed  in  an  increase  of  some  critical variables (e.g., score points, reaction time [RT], movement  time  [MT],  performance  errors).  But under specific circumstances, physical practice can also  produce  effects  of  performance  decrement. Take the implementation of a new training method or drill as an example. After this new method or drill  has  been  introduced  into  training,  athletes may not be able to perform a certain skill with the efficiency as before. Such changes of performance, however, may only be of short duration, when the movement  is  not  practiced  over  a  longer  amount of time. More permanent changes of performance are  thought  to  reflect  effects  of  motor  learning, which results from extended amounts of physical (and  mental)  practice.  Characteristic  effects  associated  with  motor  learning  are  the  higher  consistency  of  performance  and  better  performance results,  the  optimization  of  movement  economy and  the  (quasi)  automatic  execution  of  skills,  as well as the ability to flexibly adapt any movement to  fast  changes  in  the  environment.  Also,  with extended practice, the execution of even the most complex  movement  skills  will  demand  less  attentional resources, which can be used to direct attention to other aspects in the environment. Whether or not an athlete has actually learned from practice can only be assessed with a retention test (i.e., testing  the  level  of  performance  after  a  period  without practice) and/or a transfer test (i.e., testing the level of performance in a new task or under a new task context).

Deliberate  practice  can  be  scheduled  in  many different  ways.  However,  the  most  important variable  of  motor  learning—with  all  other  factors being equal—is practice. That is, only a large amount  of  deliberate  practice  will  improve  the level of performance in the long term. Many studies therefore focused on how to schedule physical training  and  to  distribute  the  amount  of  practice for a particular skill. Consider the following example: A basketball player would like to improve her performance for the jump shot. She can go ahead and perform 100 jump shots, without a break and always  from  the  same  spot  on  the  court.  Such  a training schedule is referred to as massed practice. Alternatively, she may perform 10 shots in a row, take  a  short  break,  and  then  continue  with  the next 10 shots, take a break, continue for 10 shots, and so on, for a total amount of (again) 100 jump shots from the same spot. This is called distributed practice.  As  research  shows,  athletes  will  learn  a certain skill better when the activity is distributed over  several  blocks  of  practice,  as  seen  in  better retention  and  transfer  test  results.  Some  of  the benefits  of  distributed  practice  schedules  may  be explained  with  the  recovery  of  perceptual,  cognitive, and motor functions during practice breaks.

In this basketball example, the player was practicing  the  jump  shots  always  from  the  same  spot and thus shooting the ball to the basket over the same  distance  in  all  of  the  practice  trials.  This  is referred to as constant practice. A way to alter this practice schedule would be to introduce some variability  into  the  task  conditions.  To  this  end,  the player could move up closer to the basket on some trials and move farther away from it on other trials, shooting  either  from  shorter  or  longer  distances. This is an example of variable practice. Hence, the amount  of  variability  may  be  another  factor  to consider  when  scheduling  practice  session.  Much research  shows  that  practicing  movements  under constant  conditions  increases  the  level  of  performance for a short period of time, whereas performance  improvements  are  more  permanent  under variable  conditions.  If  variable  practice  is  more beneficial than constant practice, then the question that needs to be answered in this regard is how to schedule the variable conditions. Assume that the basketball  player  would  now  like  to  practice  the 100 jump shots from four different distances (e.g., 2, 3, 4, and 5 m). She could perform 25 shots in a  row  from  each  distance,  before  moving  on  for another 25 consecutive shots from the second distance, and so on. Alternatively, she could take only a single shot from one distance and then move to another  distance  in  a  random  sequence,  without attempting to shoot from any distance twice in a row. One schedule is organized as blocked practice and the other schedule as random practice. Again, more variability within a particular schedule seems to benefit motor learning and improve movement skills  in  the  long  term.  This  has  been  explained either with a deeper conceptual processing of the movement during practice or with ongoing forgetting  and  reconstruction  processes,  which  benefit the retention and transfer of the movement.

Mastering Movements at Different Levels of Expertise

The  deliberate  practice  approach  suggests  that extensive amounts of domain-specific practice are necessary to reach an expert level of performance. It  has  been  suggested  that  athletes  need  at  least 10,000 hours of deliberate practice or more than 10 years of training within a particular field, such as music, typing, chess, and sports. Most interestingly, it seems that everyone can become an expert performer, for as long as he or she will put in the effort  of  such  prolonged  and  extensive  practice for at least 4 to 5 hours a day over the number of years. If large amounts of practice are dedicated to train  a  single  skill,  the  level  of  performance  may become exceptionally high. For example, the basketball player referred to before most likely spends much  time  to  practice  his  or  her  shots  from  the foul  line.  As  a  result,  the  likelihood  of  scoring from the foul line will be much higher than what would be expected when only considering the foul line  shooting  distance  relative  to  the  success  rate from locations nearby. Such an exceptional performance in sports relies on so-called especial skills, which are an important factor of domain-specific expertise.

Before  an  athlete  becomes  an  expert  for  any movement or sports skill, however, he or she moves through  different  stages  of  proficiency  during  the learning process. For the acquisition of new movement skills, Paul Fitts and Michael Posner proposed a three-stage learning model: In the first stage, the cognitive  stage,  the  novice  performer  tries  to  get an  idea  of  what  to  do  and  how  to  solve  a  particular  movement  problem.  He  or  she  learns  the basic  sequence  of  events  constituting  a  particular movement.  Movement  execution  is  aided  by  verbal  cues.  At  this  early  point  in  time,  movements are  performed  slowly,  inaccurately,  and  with  the generation of too much force, resulting in more or less  stiff-looking  motor  actions.  Much  attention is drawn to the organization and execution of the movement pattern. In the second stage, the associative stage, the advanced performer intentionally varies different task components and associates these variations  with  success  or  failure.  Therefore,  the quality of feedback that the learner receives plays a major role on skill acquisition during this phase. Overall, the level of performance is high as long as the task context remains stable and the movement can  be  carried  out  without  much  interference  by an opponent and time pressure. Movement execution  relies  less  on  conscious  (verbal)  control  and more on automatic processes. In the third stage, the autonomous stage, the expert performer produces his  or  her  movements  virtually  without  spending much  thought  on  it.  Movement  execution  is  realized quickly, with high precision, and almost effortlessly. Skilled performance is achieved by automatic processes,  allowing  the  athlete  to  focus  on  other important aspects during competition.

Motor  learning  is  associated  with  (relatively) permanent  changes  of  the  procedural  memory system.  Based  on  extended  deliberate  practice, movement  experts  can  rely  on  distinct  memory structures during DM in sports, in which so-called basic action concepts (BACs) provide the representational basis for the voluntary control of complex movements.  In  high-level  experts,  these  representational frameworks are organized in a distinctive hierarchical  treelike  structure,  are  remarkably similar between individuals, and are well matched with  the  functional  and  biomechanical  demands of the task. In comparison, movement representations  in  novices  are  organized  less  hierarchically, are  more  variable  between  persons,  and  are  less matched  with  the  task’s  functional  and  biomechanical demands. Thus, the quality of any movement performance may strongly depend upon the quality of movement representations in the procedural memory system.

Expertise in a number of game sports, however, may also be reflected by the degree of the athlete’s individual bilateral competence, which signifies his or her ability to perform particular skills well on both sides of the body. The basketball player who is  able  to  handle  the  ball  with  equal  proficiency with  the  dominant  and  the  nondominant  hand has  an  advantage,  because  he  or  she  can  readily adopt  the  execution  of  skills  to  fast  changes  of play  (e.g.,  while  switching  from  the  dominant  to the  nondominant  hand),  enabling  him  or  her  to flexibly  adjust  movements  to  new  situations.  In contrast, the athlete who is not able to handle the ball with equal proficiency on both sides may not be capable to adjust his or her play sufficiently to new  situations  and  is  (therefore)  constrained  to perform a particular skill with the dominant hand, even if the situation requires use of the nondominant  hand.  Thus,  the  generation  of  optimal  solutions  for  different  game  situations  in  basketball (and  other  game  sports)  highly  depends  on  the ability  to  perform  specific  movement  skills  with either side of the body, without much decrement in performance  when  using  the  nondominant  hand. A lack of bilateral competence may hinder the progression  to  higher  levels  of  competitive  play  in  a number of game sports, harming the professional development of athletes.

References:

  1. Ericsson, K. A., Krampe, R. Th., & Tesch-Römer, C. (1993). The role of deliberate practice in the acquisition of expert performance. Psychological Review, 100, 363–406.
  2. Fitts, P. M., & Posner, M. I. (1967). Human performance. Belmont, CA: Brooks/Cole.
  3. Keetch, K. M., Schmidt, R. A., Lee, T. D., & Young, D. E. (2005). Especial skills: Their emergence with massive amounts of practice. Journal of Experimental Psychology: Human Perception and Performance, 31, 970–978.
  4. Lee, T. D., & Magill, R. A. (1985). Can forgetting facilitate skill acquisition? In D. Goodman, R. B. Wilberg, & I. M. Franks (Eds.), Differing perspectives in motor learning, memory, and control (pp. 3–22). Amsterdam: Elsevier.
  5. Schmidt, R. A., & Lee, T. D. (1999). Motor control and learning—A behavioral emphasis (3rd ed.). Champaign, IL: Human Kinetics.
  6. Shea, J. B., & Morgan, R. L. (1979). Contextual interference effects on the acquisition, retention, and transfer of a motor skill. Journal of Experimental Psychology: Human Learning and Memory, 5, 179–187.
  7. Stoeckel, T., & Weigelt, M. (2012). Plasticity of human handedness: Decreased on-hand bias and inter-manual performance asymmetry in expert basketball players. Journal of Sports Sciences, 30, 1037–1045.
  8. Weigelt, M., Ahlmeyer, T., Lex, H., & Schack, T. (2011). The cognitive representation of a throwing technique in judo experts—Technological ways for individual skill diagnostics in high performance sports. Psychology of Sport and Exercise, 12, 231–235.

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