In many sport tasks, especially fast ball and interceptive sports such as rugby, tennis, and cricket, the ability to anticipate the direction of an opponent’s action is crucial. The temporal demands of the situation may make such anticipation a necessity if one is to intercept the ball in time (e.g., facing a fast bowler in cricket) or at the very least buy the receiving player time in which to prepare an appropriate response (e.g., returning a serve in tennis). The biomechanical properties of most sport skills ensure that performers must adhere to a relatively predetermined sequence of skill execution if they are to produce a biomechanically efficient action. For example, hitting a powerful tennis serve while maintaining an acceptable level of accuracy requires a player to produce hip to shoulder rotation that leads to a ballistic, sequential overarm action of the shoulder, arm, and wrist to serve the ball. This constraint on a server guarantees that at some point prior to racket–ball contact, a receiving player will be provided with invariant movement pattern information that is reliably predictive of the forthcoming service direction and spin.
Temporal Occlusion Measurement Approach
A variety of measurement approaches have been used to examine the anticipatory skill (i.e., advance information usage patterns) of elite and subelite performers involved in “open,” interceptive sport skills. The most prominent method has been the temporal occlusion approach, which relies on the use of sport-specific dynamic visual images filmed from the perspective of a player while competing (e.g., a soccer goalkeeper facing a penalty kick is filmed from the perspective of the goalkeeper). These images are then selectively edited to provide differing amounts of advance and ball-flight information. Within this approach, participants are typically required to predict the opponent’s action (e.g., kick direction in soccer goalkeeping) from the information available to them under the different temporal occlusion conditions. A significant change in the prediction accuracy from one occlusion condition to the next is assumed to be indicative of information pickup from within the additional viewing period. For example, Farrow and colleagues (2005a) demonstrated that elite tennis players were able to pick up information to improve their prediction accuracy during the time period 300 ms before the ball was struck, whereas novices didn’t extract any predictive information. By examining the key kinematic changes in the opponent’s action during this time period (it coincided with the throwing action and ball toss of the opponent’s action), elite players could determine the information usage patterns of the different skill groups. The use of the progressive temporal occlusion approach has repeatedly shown a visual–perceptual advantage in anticipation for elite players in comparison to their lesser-skilled counterparts that holds across a variety of sports, such as tennis (Goulet et al. 1989), badminton (Abernethy and Russell 1987), squash (Abernethy 1990), cricket (Müller et al. 2006), soccer (Savelsbergh et al. 2002), field hockey (Starkes 1987), and volleyball (Wright et al. 1990). Although obviously the information sources differ between sports, the pick-up of predictive movement pattern information from earlier time-windows remains a robust finding.
Visual Search Measurement
Another approach frequently used to assess information pickup in sports settings is to record players’ eye movements as they view, and ideally respond to, a perceptual display identical, or at least very similar, to those they would encounter in the natural setting. It has been hypothesized that players’ visual search patterns may provide a good indication of the location of the most informative features of an opponent’s action that may be used for anticipatory purposes. In some instances, studies measuring visual search patterns have supported the occlusion-based research findings relating to the identification of what kinematic information sources experts use in their preparation of a response to an opponent’s action (e.g., Savelsbergh et al. 2002; Singer et al. 1996; Williams et al. 1994). However, although many of these studies show some visual search differences between elite and lesser-skilled performers the differences are generally quite small, arguably trivial, leading at least some researchers (e.g., Abernethy 1990; Goulet et al. 1989) to conclude that visual search differences cannot alone explain information-processing differences and performance differences between elite and subelite performers.
Reactive Agility Measurement
In the previous edition of this text, the protocol for the assessment of agility performance in team sport athletes suggested that the ability to use agility movements “successfully in the actual game would depend on other factors such as visual processing, timing, reaction time, perception, and anticipation. Although all these factors combined are reflected in the player’s on-field ‘agility,’ the purpose of most agility tests is simply to measure the ability to rapidly change body direction and position in the horizontal plane” (Ellis et al. 2002, pp. 132). Yet, ironically, at that time none of the typical agility tests actually attempted to measure any of these supposedly critical qualities. Rather, existing agility tests were based on planned movements initiated by the athlete (e.g., Draper and Lancaster 1985).
Farrow and colleagues (2005b) argued that agility tests must cater to this reactive aspect of performance through the addition of a visual–perceptual test component and accordingly examined the impact of such a stimulus to a planned netball agility task. Specifically, a near life-size video image of a skilled netball player was projected in front of the test participant. The projected player completed a pass directed to either the left or right of the participant, who was instructed to attempt to intercept the simulated pass by adjusting the response and running through the corresponding timing gates. In addition to typical movement time measures, the decision-making time of the participant was recorded in the reactive test condition (refer to chapter 22, Netball Players, for the complete experimental protocol). A planned test condition was designed to replicate the movement requirements of the reactive condition with the key difference being that the participant knew the direction of travel before commencing the test and hence was not required to respond to a video stimulus (as per more typical agility tests).
The results demonstrated that although the planned agility test was completed faster than the reactive test, irrespective of skill level, it was the reactive test condition that was more likely to differentiate between the differing skill levels. In particular, the movement time component subsequent to the perceptual stimulus was the facet most likely to elicit time differences between the groups. In contrast, the planned components of agility performance contributed little to the between group differences found. Closer inspection of the reactive sprint time component revealed that decision-making time differed significantly between the elite and club level players examined. It is argued that the elite players’ ability to anticipate the intended pass direction, as evidenced by a negative decision-making mean (–149 ms), allowed them to predict earlier their change of direction and hence complete the sprint component of the test with greater speed. In comparison, the lesser-skilled group’s decision times (22 ms)
indicated that they waited until the passer presented all available information before initiating their change of direction. This in turn slowed their sprint time component accordingly (see Farrow et al. 2005b for more details). Subsequently a number of researchers have used reactive agility tasks across a variety of sports, demonstrating findings consistent with those described above (e.g., Australian rules: Sheppard et al. 2006; Young et al. 2011; and rugby league: Gabbett et al. 2008; Gabbett and Benton 2009).