Learning Design to Facilitate Interactive Behaviours in Team Sports
Pedro Passos and Keith Davids
The Big Idea
These authors, Passos and Davids, call their paper an “opinion piece.” Not so. It is an intelligent discussion of ecological dynamics played out in the learning of team sports through the interactive nature of the sport performance. Such interactions include those within the team and between the team and the opposing players. This dynamic continuously unfolds as players from both teams interact with constraints such as rules and boundaries, attempts at coordinating attacks and defenses and counter attacks, and managing the largely unpredictable non-linearity of game actions. And yet, even within this seeming chaos it is possible for well-coached players to use information sources found-in-the-moment to predict opponent behaviours.
- Typical team sport practices focus on skills and strategies.
- Also typical is the disconnection between these skills and strategies and what a player faces in the context of the competition itself.
- Action-relevant learning environments can significantly improve players’ ability to be comfortable with being uncomfortable on the fields of play.
- It is quite possible for players to learn how to be better attuned to what is actually happening in competition.
- Opportunities for action are called affordances.
- Affordances change over time in the context of a performance.
- Multiplying players’ affordances can be what makes the difference between novice and expert play.
- Helping players develop their perceptual attunement to key information variables, affordances, and anticipatory control means that coaches and teachers need to pay attention to representative task design in team sports.
- All too often, in football for example, the use of unrepresentative static task constraints (such as cones or a passive defender) lack any functionality with respect to the dynamic nature of the sport.
- Functional variability should be the mantra for planning and designing learning environments.
- Essentially this approach is consistent with the Constraints Based Approach (CBA). The CBA promotes player-active exploration of available task solutions for achieving performance outcomes.
This research paper is divided into five sections. The overall aim of this structure is to translate the language of team competition into meaningful learning environments. The idea is to expose the variety of information sources that players can actively explore to predict what one’s opponents will do. Once these sources are identified they will inform the players’ performance perceptions, anticipation, decisions, and actions.
What kinds of information sources are relevant to the context of performance?
Formally speaking, there are different kinds of information that define action-relevant performance. There are temporal constraints. For example, a player can accurately or not perceive when to contact an approaching player or ball. This is called time to contact. There are also spatial constraints defining where a ball should be intercepted; this suggests there are differences between players on judging object size, speed, and trajectory. In other words, players can learn how to be better attuned; and attunement may well be one of the bigger differences between novice and expert players. Knowing which factors influence such informational sources to predict interceptive actions, gives a leg up on decisions and actions in the interplaying context of team sports.
Information variables are also influenced by affordances. Affordances are opportunities for action. Perceptual attunement influences these opportunities, thus giving a player a better idea of what is likely to happen next on the playing field. The continuous interactions of players competing and cooperating with one another occur at different speeds—fast-and-short and slow-and-long. Learning how to interact with significant others occurs at slow-and-long time scales sustained by performance sequences that happen at fast-and-short time scales; performance sequences that happen at fast-and-short time scales are constrained due to slow-and-long learning.
Information variables and opportunities for action
Yes, this is seemingly quite complicated when broken down into continuously interacting episodes. To make matters worse, affordances change over time. Passing opportunities can quickly open, then close just as quickly. These researchers use an example in basketball: the “alley oop” pass. For non-basketball fans, this is when a ball-dribbling player passes the ball up in the air somewhere near the basket for another player to catch and dunk immediately. The ball-dribbling player must be perceptually attuned to an affordance of passing the ball to a player moving in the air. It is a timing play; the passer must anticipate where the air-born player will be at a certain time; and the player receiving the pass must anticipate it will be thrown.
These affordances depend on learning: perceptual, cognitive, and motor. As such, they change over longer time scales. In other words, players must first learn these possibilities to make them realities. Players and coaches must explore different ways to confront constraints. This means learning new affordances. In baseball or cricket, a player learns to switch hit. A football player learns a new way to confront a defender (such as a Cruyff or Maradona turn). So it can be a long time learning how to perform instantaneously.
In other words, information created in practice sessions within learning environments can indeed influence the way a player is attuned; and, reveal the many ways affordances become real possibilities for a player or sets of players. So, what are the factors influencing the information that sustains players’ interactive behaviours?
Methods that capture and describe players’ interactions in team sports?
Much of what we do know about players’ continuous interactions in team sport performance relies on video based methods and digitising procedures. Let’s briefly look at a few of the kinds of variables researched over the last few decades:
- In rugby union, angles between players have been used to characterise attacker-defender dyads as a single unit. This variable describes critical fluctuations in the balance of an attacker-defender system.
- In futsal, angular relations between attackers and defenders have been studied to explain affordances for passing direction. Spatial and temporal variables tied to the angular dynamics of the positioning of a ball dribbler, relative to other players on the field, constrain passing direction during competitive performance. Ball-dribblers need to be attuned to both temporal and spatial constraints that arise from their interactive coordination tendencies with teammates and opponents.
- In basketball, dyadic tendencies were measured using relative phase analysis. The study demonstrated that it was better for dyadic interacting teammates to attack a defense longitudinally (towards the basket) than laterally (sideline to sideline). But interestingly, it was better for attacking teammates in futsal to better coordinate attacks laterally. The implication of knowing what works and what doesn’t in specific sports is the need to plan and design functional training sessions that manipulate constraints relevant to the sport at hand.
- Research has also looked at the way sub-groups of players can coordinate actions to perform as a single unit to better achieve what any single player could achieve—whether attacking or defending and, as well, functioning as a system.
Representative learning tasks
What is especially important in benefitting from these kinds of research studies is to create learning environments specific to the performance demands. Helping players develop their perceptual attunement to key information variables, affordances, and prospective control means that coaches and teachers need to pay attention to representative task design in team sports. Above all, paying attention to natural variability within the team sport will better prepare the players for the dynamic nature of these sports.
Representative learning designs depend on grounding a player in the inherent variability of the performance possibilities of both one’s teammates and opponents. These include such actions as the object/ball flight path, other performer/defender’s relative position, or events/deceptive actions of an opponent. For instance, in football the use of static task constraints (such as cones or a passive defender) lacks any functionality with respect to the dynamic nature of the sport.
To be representative, the learning task must frame continuous space and time constraints. For example, space constraints can be represented by the relative positioning of the players, or changes in distances to goal, or manipulations of field dimensions. Time constraints require that the way space changes in competition is represented during training. For example, there are any number of ways to represent players’ perceptual attunement to information for successful performance: the velocity of a closing gap between defenders; the rate of change of attacker-defender interpersonal distances; or the rate of change of an angle that affords a shot at goal rate of change. Simply put, create game situations in training.
Planning and designing learning environments
Solving problems. That’s what players need to learn how to do. Functional variability should be the mantra for planning and designing learning environments. Essentially this approach is consistent with the Constraints Based Approach (CBA). The CBA promotes player-active exploration of available task solutions for achieving performance outcomes. The idea is that players will replicate in performance the same task constraints practiced. The three task constraints are: 1) individual constraints (technical skills, tactical skills, problem solving); 2) task constraints (interpersonal distances between opponents, angles between ball-dribbler and closest defender); and 3) environmental constraints (weather, presence of abusive crowd and other socio-cultural constraints).