Elsevier

Human Movement Science

Volume 28, Issue 4, August 2009, Pages 468-479
Human Movement Science

Information–movement coupling in developing cricketers under changing ecological practice constraints

https://doi.org/10.1016/j.humov.2009.02.003Get rights and content

Abstract

Changing informational constraints of practice, such as when using ball projection machines, has been shown to significantly affect movement coordination of skilled cricketers. To date, there has been no similar research on movement responses of developing batters, an important issue since ball projection machines are used heavily in cricket development programmes. Timing and coordination of young cricketers (n = 12, age = 15.6 ± 0.7 years) were analyzed during the forward defensive and forward drive strokes when facing a bowling machine and bowler (both with a delivery velocity of 28.14 ± 0.56 m s−1). Significant group performance differences were observed between the practice task constraints, with earlier initiation of the backswing, front foot movement, downswing, and front foot placement when facing the bowler compared to the bowling machine. Peak height of the backswing was higher when facing the bowler, along with a significantly larger step length. Altering the informational constraints of practice caused major changes to the information–movement couplings of developing cricketers. Data from this study were interpreted to emanate from differences in available specifying variables under the distinct practice task constraints. Considered with previous findings, results confirmed the need to ensure representative batting task constraints in practice, cautioning against an over-reliance on ball projection machines in cricket development programmes.

Introduction

Batting in cricket is a quintessential example of a dynamic interceptive action in sport, and an ideal vehicle for studying interactions between perception and action (Stretch, Bartlett, & Davids, 2000). Ecological psychologists have attempted to describe the control mechanisms involved in regulating movement to satisfy specific task constraints in interceptive actions (e.g., Davids et al., 2005, Montagne, 2005, Montagne et al., 2000). James Gibson’s theory of direct perception proposes how movement is shaped using information constantly available in the surrounding environment (e.g., Gibson, 1979). It has become clear how performers can exploit information to regulate action from movements of other players (see Renshaw and Fairweather, 2000, Renshaw et al., 2007) or moving objects (see Regan, 1997, Williams et al., 1999).

From this viewpoint the process of practice involves becoming better attuned to specifying variables available in different performance contexts (Davids, Button, & Bennett, 2008), and calibrating movement responses to those variables. Since the perception of environmental information is specific and constrained by each individual performance setting, it is important that learners improve their capacity to detect specifying from non-specifying variables (see Jacobs & Michaels, 2002; see also Dicks, Davids, & Araújo, 2008). In particular performance contexts, specifying variables provide more functional information to constrain performers’ actions than non-specifying variables (Araújo, Davids, & Passos, 2007).

Learners pick up specifying variables to support action in specific performance environments through the education of attention, or perceptual attunement (Fajen et al., 2009, Jacobs and Michaels, 2002). Jacobs and Michaels (2002) suggested that the two stages of constructing information–movement couplings are: (a) the education of attention to key informational sources, and (b) the fine tuning of movements to a “critical information source” (Davids et al., 2005). Clearly, the removal of critical information sources at specific developmental stages could impede learning, resulting in unintended changes to coordination of actions. Therefore, while practice task constraints might contain some specifying variables which are available to support learners’ actions during practice tasks (i.e., batting against a bowling machine), learners should also be provided with opportunities to pick up specifying variables available to support performance in competitive contexts. It is important that practice task constraints should not lead learners to pick up non-specifying variables for competitive performance environments.

Batting against a bowling machine affords learners the opportunity to become perceptually attuned to ball flight information during practice. Clearly, while specifying variables may be available from ball flight characteristics when batting against bowling machines, these variables may be non-specifying in competitive performance environments due to the time constraints on action. In cricket batting the time constraints are often severe with ball velocities typically ranging from 19–40 m s−1 (Bartlett, 2003). Thus, when facing medium to fast deliveries from a bowler, batters have to decide on an appropriate shot and initiate it within about 0.7 s (McLeod & Jenkins, 1991). These findings highlight that, due to ball velocities generated by bowlers, batters need to attune to specifying variables that exist in bowlers’ actions prior to ball release which are available in competitive performance environments (Abernethy and Russell, 1984, Weissensteiner et al., 2008).

Specifying variables for action need to be constantly available for perception in the practice and performance environment (Dicks et al., 2008). Practice task constraints that provide specifying variables for pick up by learners during competitive performance can be considered to be high in representative task design (see Araújo et al., 2007). Changing the informational constraints in practice environments might lead to the design of less representative practice tasks by altering availability of specifying variables, resulting in changes to a learner’s acquisition of functional movement patterns (Beek, Jacobs, Daffertshofer, & Huys, 2003). The pick-up of non-specifying variables might result in performance success under specific task constraints, but perceivers may become too dependent on these variables even when performance task constraints change (Beek et al., 2003). Dependent on the specific performance context, this unintended reliance may not be a problem. As Withagen (2004, p. 242) highlighted “a human being who intercepts 70% of the balls thrown at him or her because she exploits a non-specifying, moderately informative variable will not die because of it”. However, Withagen (2004) noted the significance of becoming better attuned to specifying variables by arguing that “the animals that do survive are the ones that do better than their competitors”. In sports performance, as levels of competition increase, those athletes that continue to rely on non-specifying variables will eventually become less competitive than their counterparts who have learned to pick-up specifying variables to regulate actions.

Based on these ideas, an important question is: How does altering the informational constraints in specific practice environments affect the coordination of dynamic interceptive actions, such as cricket batting? Some previous work has demonstrated how ball projection machines (e.g., cricket bowling machines) influence the movement patterns of skilled cricketers (Renshaw et al., 2007). Bowling machines in cricket are considered to be useful equipment to allow performers to practice batting movements away from the performance environment. They are considered to provide consistent, accurate and specific conditions for practice (e.g., bowling pace or length) to enable batters to acquire individual shot types. One clear advantage of bowling machines is that they alleviate the workload required of developing bowlers, with overuse injuries being a major concern (Dennis, Finch, & Farhart, 2005). Nevertheless, a key issue is whether practising with a bowling machine may actually impede the pick up of specifying information variables from the performance environment for batting (Renshaw et al., 2007).

The role of anticipation is firmly established as a key component of expert performance in dynamic fast ball sports, with the use of pre-ball flight information viewed as essential to skilled cricket batting (Müller & Abernethy, 2006). Research in cricket batting has demonstrated a relationship between skill level and anticipation, consistent with those seen in other sports (Müller, Abernethy, & Farrow, 2006). Current evidence from expertise research suggests that only skilled batters have an ability to utilize information from the pre-release actions of a bowler (Weissensteiner et al., 2008). They can gain an advantage, under severe time constraints, by picking up information from limb and body orientations of the bowler during the run-up, bound, and moment of release (Davids et al., 2005). Skilled performers use this information to predict ‘line and length’ of deliveries from both fast (e.g., Abernethy and Russell, 1984, McRobert and Tayler, 2005, Penrose and Roach, 1995) and slow bowlers (e.g., Renshaw & Fairweather, 2000), in addition to specifying the point of ball release (Gibson & Adams, 1989). In contrast, less-skilled players appear to gain little information from pre-release sources, relying primarily on ball flight characteristics (Renshaw & Fairweather, 2000). A number of reasons have been proposed to explain why developmental level performers may not be able to pick up information from a bowler’s actions. First, it is felt that the lower bowling speeds faced by batsmen in junior competition may not necessarily require them to anticipate for success. This is because the time from ball release to bat contact is long enough to make the need to attune to pre-flight information redundant. A second related suggestion is that anticipation makes a less significant contribution to successful performance in developing athletes, compared to factors such as relative age, strength, and maturity in determining success in junior cricket batting (Weissensteiner et al., 2008).

However, recently van der Kamp, Rivas, van Doorn, and Savelsbergh (2008) have criticized the occlusion paradigm on which these assumptions are based. Typically, occlusion studies have tended to examine perception in isolation from action, suggesting that the actual performance of experts in these tests may not be truly ‘expert’. For example, these authors collated results from a number of key occlusion studies noting significant spatial errors in predicting the landing location of an object even under full vision conditions for both novices and experts (e.g., in badminton 1.4–1.8 m, Abernethy & Russell, 1984; in cricket wicket-keeping 45–55 inches, Houlston & Lowes, 1993; in soccer, 3.3 m, McMorris & Colenso, 1996; in squash, 0.6–1.8 m, Abernethy et al., 2001, van der Kamp et al., 2008). Re-evaluation of these data suggested that the occlusion paradigm has significant limitations and highlights the need to analyze anticipation in tasks such as cricket batting by examining perception and action in unison.

The most common stroke in cricket is the forward defensive which also forms the basis of the drive (Stretch, Buys, Du Toit, & Viljeon, 1998), and consequently, it is often the starting point for many coaches when teaching novices. A previous two-dimensional analysis of the forward defensive stroke in cricket batting (Renshaw et al., 2007) examined the movement coordination and timing of four ‘high intermediate’ standard batsmen during the forward defensive stroke, against a medium pace bowler and bowling machine (26.76 m s−1). Significant adaptations were observed under the two different informational constraints and central to these changes was the organization of the two phases of bat swing. The backswing in the bowling machine condition varied greatly, but was coupled to ball release (0.02 ± 0.10 s after ball release), whereas against the bowler, initiation of the backswing occurred later (0.12 ± 0.04 s). Similarly, initiation and speed of the downswing occurred earlier and more quickly when facing the bowling machine (0.32 ± 0.04 s; bowler: 0.41 ± 0.03 s), resulting in different ratios of backswing–downswing between conditions.

The findings of Renshaw et al. (2007) are somewhat different to other data on cricket batting by Gibson and Adams (1989). Utilizing a case study approach, Gibson and Adams (1989) observed how one international cricketer initiated the backswing before ball release, with front foot movement occurring much earlier when facing the bowling machine compared with the bowler. This observation was rather surprising, and could be attributed to the experimental task constraints (i.e., the batsman knew in advance the landing position of the ball) or the previous experience of the participant facing the bowling machine. Renshaw et al. (2007) observed no differences in front foot initiation time under both practice task constraints, noting that it was more closely coupled with the backswing when facing the bowler (r = .88; bowling machine, r = .65), and occurred after ball release in both conditions, Additionally, it was observed that a higher peak bat height was reached against the bowler (1.56 ± 0.20 m vs. 1.72 ± 0.10 m), as well as a longer front foot stride (0.55 ± 0.07 m vs. 0.59 ± 0.06).

Differences in coordination patterns observed in these two studies when facing both the ball machine and bowlers highlighted the importance of ecological task constraints. Practice under the two distinctive ecological task constraints led to variations in functional movement solutions which might be attributed to differences in the practice task constraints (i.e., not knowing in advance versus knowing in advance where the ball would land) as well as to the absence of advanced information from the bowler. To explain their findings, Renshaw et al. (2007) proposed that the previous experiences of these relatively skilled batsman against a bowling machine might have led participants to rely on non-specifying variables provided by the machine (Renshaw et al., 2007). This strategy may have been employed by the skilled participants because of the removal of important information sources from the bowler. These explanations signalled the need for further empirical research to examine the movement responses of developing players under similar practice task constraints. This is a significant practical issue because bowling machines are used extensively in the development of young cricketers. In this regard, an important point to note is that ball projection machines prevent the use of advanced information sources available prior to ball release (e.g., the run-up, bound, and delivery stride of a bowler’s approach). Currently it is not clear whether the pick-up of kinematic and early ball flight information can be utilized by children.

Therefore, the aim of this study was to extend understanding of information–movement coupling in cricket batting by assessing the timing and kinematic responses of developing batters under two practice task constraints, when performing an attacking (forward drive) and defensive (forward defence) stroke. It was anticipated that less-skilled individuals would demonstrate differences in the temporal and spatial movement responses, leading to shorter strides and lower peak bat heights when facing the bowling machine. It was also predicted that observation of a bowlers’ movements might afford advanced information sources that allowed developing players to initiate movements earlier than against a bowling machine, providing them with more time to organize their responses.

Section snippets

Participants

Eight right-handed and four left-handed junior batsmen (n = 12, age = 15.6 ± 0.7 years), with 6.6 ± 0.6 years playing experience, provided informed consent and took part in the study. Ethical clearance was completed through a local university ethics committee. The batters were adjudged by skill acquisition specialists (who were also qualified Level II ECB cricket coaches) to be representative of individuals at the control stage in Newell’s (1985) model of skill acquisition, and were considered to have

Temporal and spatial differences

Significant differences were observed in the timing and initiation of key phases of the forward defence and forward drive strokes (see Fig. 1). Results are represented in seconds before the impact of bat and ball, with ball release in both conditions occurring 0.64 s before impact. Initiation of the backswing occurred earlier against the bowler than against the bowling machine for the defence (B: 0.58 ± 0.07 s; BM: 0.49 ± 0.08 s, t(65) = 8.27, p < .001, r = .72) and the drive (B: 0.58 ± 0.07 s vs. BM: 0.50 ± 

Discussion

This study sought to manipulate practice task constraints to evaluate effects on movement control and coordination of developing cricket batters. The aim was to investigate whether the information–movement couplings used during batting by developing players changed when facing a bowler and bowling machine. Based on previous work, if the developing players were not attuned to advanced information sources from bowlers, then relatively smaller changes in movement responses between the conditions

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