Representative Learning Design in Dynamic Interceptive Actions Ross Andrew Pinder BSc. (Hons.) Sport & Exercise Science MSc. (Distinction) Sport & Exercise Science A thesis submitted in fulfilment of the requirements for admission to the degree of Doctor of Philosophy School of Exercise & Nutrition Sciences Queensland University of Technology Brisbane, Australia - 2012
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Representative Learning Design in
Dynamic Interceptive Actions
Ross Andrew Pinder BSc. (Hons.) Sport & Exercise Science
MSc. (Distinction) Sport & Exercise Science
A thesis submitted in fulfilment of the requirements for admission to the degree of
Doctor of Philosophy
School of Exercise & Nutrition Sciences Queensland University of Technology
Video Screen 10.31 1.82 5.25 1.71 0.01 0.02 -0.02 0.03
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Figure 3.6. Mean group horizontal bat end-point velocities for the forward drive shot across three
distinct experimental tasks (N.B. Data peaks do not align with analysed data in Table 3.1 due to peak
horizontal velocities occurring at differing times across all trials).
3.5. Discussion
The design of experimental task constraints that effectively capture organism-environment
relationships remains a prominent concern in experimental psychology (Brunswik, 1956;
Dhami et al., 2004; Dunwoody, 2006; Rogers, 2008). This study provided evidence to
support current concerns expressed by perceptual-motor behaviour researchers over the
generality of performance data from experimental and learning tasks to performance
contexts, such as sport (cf. Dicks, Button, et al., 2010; van der Kamp et al., 2008). Data
revealed significant changes in timing and organisation of junior cricket batters’ movements
under different task constraints. These findings have major implications for learning design
at these important developmental stages of learning in ball sports like cricket, particularly
due to the heavy use of ball projection machines in many training programmes.
‘Live’ bowler-ball projection machine comparisons
The most pronounced differences observed in the data demonstrated that even simple
performance measures, such as QoC and bat swing velocities, are significantly affected by
the removal of key sources of perceptual information. Batters demonstrated definitive
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Chapter 3 – Representative experimental and practice design
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movement initiation effects (backswing and front foot) shortly after ball release when
facing a ‘live’ bowler. These data provided evidence for the use of advance sources of
information to organise movement patterns, available from the kinematics of the bowlers’
actions (see Shim et al., 2005; Shim et al., 2006). This observation was particularly evident
when considering that the batters needed to complete one of two fundamentally different
tasks: that is, making a definitive movement forwards (for the drive or the defence) or
backwards (against shorter pitching trials). Due to subtle changes of the ball projection
machine head between trials (allowing us to randomise angle of delivery and therefore
pitching length), batters in this study were unaware of upcoming delivery characteristics in
advance, a concern with previous research involving ball projection machines (Gibson &
Adams, 1989; Renshaw et al., 2007). The use of perceptual information from the bowler’s
actions allowed batters to significantly increase peak bat swing heights and step lengths
(see Figure 3.5), similar to findings from previous research in which tennis players were
observed to use advance information sources from an opponent’s actions to increase their
court movement coverage by up to 1.2m (Shim et al., 2005). Importantly, the finding that
batters displayed lower backswing heights and shorter step lengths when completing a
forward defence, compared to the forward drive, supports previous work (Stretch et al.,
1998). This observation confirms that the batters were able to decide on the required
stroke before the downswing began, based on advance kinematic and early ball flight
information. Comparatively, similar variations in movement responses were observed when
batting against a ball projection machine, even with the removal of pre-release information
sources from the bowler, albeit occurring significantly later. Significant delays in backswing
and front foot movement initiation times of 80 and 100 ms, respectively, required batters
to functionally adapt their actions (implement lower peak bat swing heights and shorter
step lengths - see Figure 3.5) to ensure a degree of task success. However, batters
demonstrated significantly lower performance scores (QoC – see Figure 3.2) and lower peak
bat swing velocities (10.62 versus 11.38 m·s-1) when compared with batting against a ‘live’
bowler. Batters attained peak bat velocities just before the point of bat-ball contact (-0.02s)
under both interceptive task conditions (Stretch et al., 1998), demonstrating the use of
prospective information from ball flight characteristics for the timing of interception.
Prospective information is information about the current future, that is, the performer is
informed about the future outcomes if the current state is maintained (Montagne, Bastin,
& Jacobs, 2008); hence, it provides information for the modification of movement, allowing
performers to adapt behaviour independently of specific task constraints. However, critical
delays in movement timing imposed by the task constraints (through removal of key
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perceptual information) could not be offset by the batters prospectively controlling spatio-
temporal characteristics of the action based on ball flight information alone. Interestingly,
the strong within-task relationships between time of downswing initiation and point of bat-
ball contact suggested that the changes in timing of downswing initiation were caused by
differences in the information available between tasks. For example, the batters produced
equally consistent timings for downswing initiations in the ball projection machine
condition, but which occurred significantly later (closer to point of bat-ball contact) than
against a ‘live’ bowler.
The added temporal constraint imposed by the ball machine task constraints in this study
raises concerns over experimental and learning task designs which exclude anticipatory
perceptual sources. It appears that much of the current data on perceptual anticipation
(e.g., gaze behaviours, or movement-based skill differences) is based on experimental
designs that are not representative of human performance contexts such as sport. It is
possible that current data on technical and perceptual characteristic (e.g., visual search)
differences across skill levels in cricket batting (e.g., Land & McLeod, 2000; Weissensteiner
et al., 2009a) may be confounded by the amount of task-specific practice that participants
have been exposed to against ball projection machines in developmental programmes (e.g.,
U15 to adult level programmes). In these programmes some batters may have been
essentially learning a different task to that required in actual performance environments.
‘Live’ bowler-video simulation comparisons
Our results showed that batters were able to achieve the same temporal advantage against
a ‘live’ bowler and video simulation conditions, demonstrating comparable movement
organisation for the critical early movement initiations (i.e., preparatory actions of
backswing and front foot movement). Backswing and front foot movement initiation points
occurred ~60 and 130 ms after ball release, respectively, under both task constraints. This
performance characteristic supported equivalent peak bat swing heights and step lengths
across shot types (see Figure 3.5). Batters were able to pick up and use pre-ball release
information and from the first portion of ball flight, from a ‘live’ bowler and when
presented in a video simulation.
These findings might be considered in light of advances in behavioural neuroscience (visual
system functioning). Requiring batters to couple movements to video-simulated
Chapter 3 – Representative experimental and practice design
67
information on a screen enabled comparison with information provided by a ‘live’ bowler.
This methodological advance helped address concerns over speed/accuracy trade-offs (e.g.,
requiring participants to ‘react as quickly as possible’ in tests of perceptual skill) which
seem to have confounded previous studies in visual anticipation (see van der Kamp et al.,
2008). Data from our study demonstrated that junior batters’ perceptions, decision-making
and initial movement responses in this specific video simulation task were representative of
similar processes observed in a ‘live’ bowler condition. Action fidelity was supported, and
performance in one context (initial movements against a video simulation) statistically
corresponded with performance in the other context (e.g., that of a ‘live’ bowler). This
finding, while inconsistent with some previous work comparing in-situ and video-based
designs (e.g., Dicks, Button, et al., 2010), may be attributable to the maintenance of a fully
simulated action (coupled response), rather than a simplified micro-movement reaction
(such as a movement in the anticipated direction). Because of this methodological advance,
the video simulation allowed batters to couple preparatory movements to the pre-release
and early ball-flight information. Many researchers have previously alluded to the
possibility of using video simulation designs to study or train visual anticipation processes
(Abernethy, Wood, & Parks, 1999; Rowe & McKenna, 2001; Williams et al., 2003). Our data
suggest that video simulations may indeed provide representative performance tasks for
assessing (or training) affordance perception in developing athletes. However, it remains
unclear whether this method could result in the same affordance perception (attunement
to subtle but critical changes in response requirements) or efficient and accurate action
production without the requirement for simulated movement performance by participants
(see van der Kamp et al., 2008). An important finding from this experiment is that, when
perception for action is available (under video simulation constraints), it enables a higher
fidelity of the initial simulated action responses than when an interceptive action is
performed without the availability of representative perceptual variables (under ball
machine conditions). These data provide a demonstration of the theoretical role of
affordances in guiding skilled actions, and are a relevant indication for the strategy of
manipulating key task constraints in training sessions. Further work is needed to
understand how the perception of affordances for action may be incorporated into learning
designs in developmental sport programmes.
The most pronounced differences in our batting data provided clear evidence for concerns
over generalising observations between experimental tasks which lack fidelity of
performance characteristics. Changes in the initiation of the downswing and peak bat swing
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velocities demonstrated a prospective control strategy, with batters’ comparing the
perceived current state of the environment (e.g., time to contact) with the requirements
for successful interception (Fajen et al., 2009; Montagne, 2005). The a priori concern that
two-dimensional simulation displays do not provide sufficient information on ball flight
characteristics to support actions such as interceptions, was vindicated by observations of
significant differences in timing of downswing initiation, and markedly lower peak bat swing
velocities compared to when batting against a ‘live’ bowler. Furthermore, data on the time
at which peak bat swing time was attained by the batters under video simulation conditions
poses some challenges for such experimental designs. For example, in the video simulation
task constraints peak bat velocity occurred after the point at which interception was
predicted to have occurred (see Figure 3.6). Batters were unable to accurately judge
movement requirements without actual ball flight and bounce location information, which
are both important for enhancing the quality of interceptive actions (see Müller et al.,
2009). Batters were either not able to attune to this information, or it could not be
faithfully represented in the 2D video simulation methodology. Our findings offer further
support for previous research demonstrating that the assessment of perceptual-motor
performance using video-based simulation paradigms, particularly when perception and
action are decoupled, can lead to serious errors by participants in judging projectile
interception location (for a collation of assessment studies see van der Kamp et al., 2008).
Additionally, some possible limitations of other methods of assessing interceptive timing
(e.g., comparison with coaches' predictions, Taliep et al., 2007) and possible differences in
the level of experience that batters had in the three distinct conditions in the current study,
should be acknowledged as issues in need of further study.
General discussion
The results of the present study revealed significant differences in performance of
developmental batters between a representative practice task (batting against a ‘live’
bowler), and both video simulation and ball projection machine task constraints,
traditionally used in the assessment of perceptual-motor skill in ball sports. Results
demonstrated that the batters were able to functionally adapt behaviour for each specific
set of task constraints (e.g., the regulation of spatial characteristics under ball machine task
constraints to account for delays in movement initiations). However, the removal of key
perceptual variables to support action (both pre-release, or actual ball flight), suggested
that empiricists should be cautious in interpreting which aspects can be generalised from
Chapter 3 – Representative experimental and practice design
69
experimental to performance task constraints (e.g., kinetic and kinematic variables, Taliep
et al., 2007). It is feasible that current popular experimental designs may actually be
limiting progress in understanding and training perceptual and technical abilities of
developmental performers in ball sports. In order to better understand the characteristics
of perceptual-motor skill, and how to develop them, empiricists should attempt to design
experimental task constraints that are representative of specific performance contexts. The
representative task adopted in the present study was that of a normal practice context in
the sport of cricket. Some may argue that differences may exist between observations of
batting performance against a ‘live’ bowler in a different context (e.g., competitive sport).
This concern was beyond the scope of the current study, and is an important question for
future research to assess. Future work should also focus on the assessment of learning
design across various skill levels and temporal constraints (ball speeds), to assess how
informational variables are used at different performance development levels. Indeed, it is
currently unknown if the findings regarding video simulations presented here would also be
observed in groups of highly skilled or senior batters in elite sport programmes, and this is
another aspect which should be investigated in future work. However, there are both
empirical (Renshaw et al., 2007) and experiential reports (Renshaw & Chappell, 2010)
showing similar findings for senior and skilled batters.
The first stage of truly understanding how skilled performance in interceptive actions can
be developed must be to measure and formally describe tasks that adequately capture the
functional behaviour of individuals in a specific performance environment, before posing
questions on how individuals achieve knowledge about that environment (See Chapter 4.
Also see Araújo & Davids, 2009; Fajen et al., 2009; Pinder, Davids, et al., 2011b). The
concept of action fidelity could be used to examine whether a performer’s responses (e.g.,
actions or decisions based on availability of perceptual information) are the same under
various task constraints.
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“A theory is the more impressive the greater the simplicity of its premises, the more
different kinds of things it relates, and the more extended its area of applicability.”
Albert Einstein (1879-1955)
Chapter 4 – Representative Learning Design in sport
73
Chapter 4 – Representative Learning Design: A theoretical framework
for research and practice design in sport
Following the findings of Chapter 3, it became apparent that many current experimental
and learning designs (e.g., the design of practice tasks) in sport may not adequately
represent the performance setting of interest; despite some previous attempts to highlight
this issue (e.g., Araújo et al., 2007; Dicks et al., 2008). Here, therefore, is a developed
theoretical framework, based on the tenets of Ecological Dynamics to provide a principled
approach for experimental and practice design in sports research and performance.
This chapter is based on the following peer-reviewed journal article:
Pinder, R. A., Davids, K., Renshaw, I., & Araújo, D. (2011b). Representative learning design
and functionality of research and practice in sport. Journal of Sport & Exercise
Psychology, 33, 146-155.
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4.1. Abstract
Egon Brunswik proposed the concept of representative design for psychological
experimentation, which has historically been overlooked or confused with another of
Brunswik’s terms, ecological validity. In this article, we reiterate the distinction between
these two important concepts and highlight the relevance of the term representative design
for sports psychology, practice and experimental design. We draw links with ideas on
learning design in the constraints-led approach to motor learning and nonlinear pedagogy.
We propose the adoption of a new term, representative learning design to help sport
scientists, experimental psychologists, and pedagogues recognise the potential application
of Brunswik’s original concepts, and ensure functionality and action fidelity in training and
learning environments.
halla
Due to copyright restrictions, the published version of this article is not available here. Please consult the hardcopy thesis available from QUT Library or view the published version online at: http://eprints.qut.edu.au/47250/
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Wisden Cricketers’ Almanack (1867)
Chapter 5 – Principles for the use of ball projection machines
87
Chapter 5 – Principles for the use of ball projection machines
Further to Chapter 4, the second paper of the theoretical phase of this thesis aimed to
provide a specific and principled theoretical framework to guide future experimental and
practical uses of ball projection technology in sport. Due to the prominence of ball
projection technology in both experimental (Croft et al., 2010; Land & McLeod, 2000;
Weissensteiner et al., 2009a) and learning designs (particularly in developmental
programmes – Woolmer et al., 2008), the purpose of this paper was to provide an overview
of the extant research to date and provide a useful model for both scientists, coaches and
practitioners to guide the future use of such technology.
This chapter is based on the following peer-reviewed journal article:
Pinder, R. A., Renshaw, I., Davids, K., & Kerhervé, H. (2011). Principles for the use of ball
projection machines in elite and developmental sport programmes. Sports Medicine,
41(10), 793-800.
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5.1. Abstract
Use of ball projection machines in the acquisition of interceptive skill has recently been
questioned. The use of projection machines in developmental and elite fast ball sports
programmes is not a trivial issue, since they play a crucial role in reducing injury incidence
in players and coaches. A compelling challenge for sports science is to provide theoretical
principles to guide how and when projection machines might be used for acquisition of ball
skills and preparation for competition in developmental and elite sport performance
programmes. In this Chapter, we demonstrate how principles from an ecological dynamics
theoretical framework could be adopted by sports scientists, pedagogues and coaches to
underpin the design of interventions, practice and training tasks, including the use of hybrid
video-projection technologies. The assessment of representative learning design during
practice may provide ways to optimise developmental programmes in fast ball sports and
inform the principled use of ball projection machines.
Chapter 5 – Principles for the use of ball projection machines
89
5.2. Introduction
Ball projection machines typically play an integral role in practice and training environments
in many sports, from cricket and baseball to volleyball and tennis. Recently, it has emerged
that not all skilled performers agree that the use of projection machines in practice
provides a functional task to practice interceptive actions, leading to some contention
among expert coaches. For example, some high performance and developmental
programmes have taken steps to extensively reduce the use of these machines in the sport
of cricket (Renshaw & Chappell, 2010). Greg Chappell, a former prominent Australian
cricket batsman and head coach of the National Centre of Excellence, now talent
development manager, describes his stance:
“...what my intuition told me for years was that the bowling machine was
a totally different exercise from batting against the bowler. From my own
personal experience of batting against the bowling machine, it wasn’t a
great experience because once I’ve done it a few times I decided that it
wasn’t going to help me with batting. I was better off not to bat at all than
to go and bat on a bowling machine because the activity is so different. [In
an actual cricket match] you know the bowler’s preparation to bowl; you
know everything—all of the cues and clues that you’re getting from the
bowler is really important to get into the rhythm of the bowler and to get
the timing of your movements. You take the bowler out of the equation,
you stick a machine there that spits balls out at you and you’ve lost all
those cues and clues. What I’ve subsequently found is that research is
telling us what my intuition and my experience was telling me. The other
thing is that the research into expertise tells you that experts are better at
picking up the cues and clues than the average player. So why take it away
from everyone and stop them from developing the things that will help
them get better?”
(Renshaw & Chappell, 2010)
Conversely, the late Bob Woolmer, an equally respected and renowned former
international batsman and national coach of South Africa and Pakistan, considered the ball
machine one of the “most essential tools in modern cricket” (Woolmer et al., 2008). One of
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the primary uses of projection machines in practice seems predicated on movement
repetition (Woolmer et al., 2008) considered traditionally as an essential feature of
‘perfecting’ a putative ‘ideal’ technique in the process of skill acquisition (Gentile, 1972;
Schneider, 1985). This idea is exemplified in the most up-to-date coaching literature on
cricket batting, which discusses the use of ball machines to help ‘groove the skill’ (Woolmer
et al., 2008). Additionally, projection machines allow individuals to achieve a high volume of
practice by facing more balls in a short period of time in order to practice specific actions
hundreds of times. This is not only a critical issue for sports coaches, but a very important
theoretical and methodological one for sport science researchers.
5.3. The problem of practice volume
Projection machines provide relatively consistent and accurate practice conditions, which
developing athletes (e.g., pitchers, bowlers) may not be capable of producing for their
peers. This is important, since skill acquisition in interceptive actions has been associated
with large volumes of task-specific practice (Weissensteiner et al., 2008). However, an over-
reliance on projection machines may have been inadvertently induced by some
perspectives of expertise which have over-emphasised practice volume (e.g., quantity of
balls hit) over the quality of practice task design. Practice volume is central to many
prevalent perspectives on expertise, such as the 10 000 hour rule (Simon & Chase, 1973),
the power-law of practice (Newell & Rosenbloom, 1981), and deliberate practice (Ericsson
et al., 1993). To exemplify, the most comprehensive and relevant coaching literature in
cricket batting proposes that batsmen require “10 000 repetitions of an action or skill to
penetrate the subconscious” and that this conditioning “enables the batsmen to react
instinctively in match conditions” (Woolmer et al., 2008). In complex skilled actions, it is
important to consistently achieve a particular performance outcome; however it has been
demonstrated that skilled movement patterns are rarely repeated in an identical way on
two or more occasions as performance outcomes are achieved (Davids et al., 2008). The
need for ‘repetition without repetition’ in practice has been noted as a critical feature of
successful motor-learning (Bernstein, 1967; Renshaw et al., 2010), with performers using
movement variability and stability paradoxically to influence periods of performance
outcome consistency and movement pattern adaptability (Renshaw et al., 2010). This is
important to note since the ways in which projection machines are currently used appears
to be focused on stability and blocked practice of isolated movement aspects (e.g., blocked
practice of a single type of shot).
Chapter 5 – Principles for the use of ball projection machines
91
But how does one practice multi-articular actions for an extended number of trials and for
prolonged periods of time, without placing too much stress on the bodies of coaches,
pitchers or bowlers? The practical benefits of projection machines have been highlighted by
research into overuse injuries in sports relying heavily on multi-articular projecting actions
(e.g., baseball pitching, cricket bowling). A clear advantage gained from using ball
projection machines is that they alleviate the workload required from bowlers or pitchers
during batting practice. This is most important since, in cricket, bowling injuries are heavily
attributed to overuse through high bowling workloads, particularly at developmental stages
(Dennis et al., 2005; Stretch, 2003). Critically, once a player sustains an injury, the likelihood
of re-occurrence is increased (Nuttridge, 2001; Stretch, 2003). Similar findings exist in
baseball, with overuse injuries of the shoulder being a primary concern for developing
performers (Fleisig et al., 2011; Wilk et al., 2011). A recent prospective study demonstrated
that youth athletes pitching more than 100 innings per calendar year were significantly
more likely to sustain injury. To counter the problem of injuries, many coaches in cricket
rely heavily on providing simulated actions such as ‘throw downs’ (over-arm throws from a
reduced distance) to replicate ball flight information and maintain the temporal demand
reminiscent of bowling. However, there is some anecdotal evidence from the coaching
literature of similar levels of overuse injuries in coaches using ‘throw downs’ to simulate
bowling deliveries in cricket (Woolmer et al., 2008). In light of these data it is apparent that
use of projection machines in practice programmes remains important in reducing the risks
of injury incidence.
5.4. Implications for skill acquisition
As well as being perceived as a benefit in reducing injury incidence, ball projection
machines have also been considered useful tools for the acquisition of skilled hitting
actions; allowing a performer to focus on one isolated aspect (e.g., a specific shot or
stroke), practice individually, and complete large volumes of practice in a short period of
time. Despite these reasons, some studies assessing the use of projection machines in
sports performance have questioned their role in athlete preparation, skill acquisition and
assessment. There is clear evidence that use of projection machines in tennis and cricket
creates significant differences in timing and control of performers’ actions, as well as a
reduction in the quality of interception when compared to facing a ‘live’ opponent
delivering a ball with the same characteristics (see Chapter 3; Pinder, Davids, et al., 2011a;
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Pinder et al., 2009; Renshaw et al., 2007; Shim et al., 2005). In developing junior
performers, especially, these differences are manifested in significant delays in movement
initiation times which increase the temporal demand on the unfolding action. For example,
it has been reported that developing junior cricket batters initiated the backswing of the
bat and front foot movement significantly later when performing front foot shots (e.g.,
moving the front foot towards ball bounce) against a projection machine set to the same
speed (≈28 m·s-1) and with similar trajectory characteristics as a ‘live’ performer (Pinder et
al., 2009). Critically, these delays in movement initiation resulted in a reduction in quality of
contact of the interceptive action, a reduction in bat swing speeds, and significantly shorter
step lengths; the need to place the foot as close to the pitch of the ball in these type of
shots (e.g., minimising the impact of late ball-flight deviation) is a well established cricket
coaching principle. Changing the practice task constraints and using projection machines in
junior cricket batting leads performers to re-organise their actions in attempts to achieve
the required spatial-temporal orientation (Pinder, Davids, et al., 2011a; Savelsbergh &
Bootsma, 1994). Here we argue that differences exist between performance contexts and
training task constraints because the latter are used to simulate the former. Differences
may exist between specific training tasks and competitive match contexts. This is a rich area
for future research to address using the principles we outline below (see section 5.5).
Critically relevant information sources from the competitive performance environment are
not available under practice task constraints involving projection machines. Research
suggests that in their current mode of use, prolonged exposure to projection machine
practice tasks may lead athletes to attune to information sources which are not present
during competitive performance, leading to a predictive rather than prospective control
strategy emerging in learners (Croft et al., 2010; Renshaw et al., 2007). Renshaw and
colleagues (2007) demonstrated that, contrary to data reported for junior performers,
experienced cricket batters initiated the backswing of the bat earlier against a projection
machine than when batting against an experienced medium-paced bowler at the same
bowling speed (≈27 m·s-1) (also see Gibson & Adams, 1989). It has also been demonstrated
recently that highly distinctive visual search patterns are used by experienced cricket
batters when practising with projections machines, since they ‘park’ their gaze at a point on
the anticipated trajectory of the ball before release (Croft et al., 2010). Although it is
intuitive to predict differences between batting performance contexts, no research has yet
compared visual strategies of batters under ball projection machine and ‘live’ bowler task
constraints. The use of a principled framework for these comparisons would support
Chapter 5 – Principles for the use of ball projection machines
93
analyses to observe whether differences between the two tasks might emerge (for an
empirical study assessing visual strategies between practice task constraints see Chapter 6).
However, a key point to note is that the use of projection machines reduces the
opportunities for developing batters to attune to subtle and relevant sources of pre-ball
release information from a bowler/pitcher’s movements for differentiating ball trajectory,
speed or ball type variations (e.g., different spin rotations), a critical feature of expertise in
Fairweather, 2000). This criticism can also be directed at the use of ‘throw downs’ to
simulate bowling deliveries in cricket. For these reasons, Pinder et al. (2009) have cautioned
against an “over-reliance of ball projection machines in developmental programmes”. But it
is important to note that this message should not be interpreted as ‘ball machines should
not be used at all during practice’. Rather, practitioners and sport scientists need to
develop a principled theoretical rationale for their use as a skill enhancement tool in sport,
which is elucidated in section 5.5.
5.5. Principles for Future Work
A compelling challenge for sports science is to understand ‘how’ and ‘when’ projection
machines might be used for acquisition of ball skills and preparation for competition.
Ecological dynamics is a theoretical framework which could underpin a reasoned analysis
for use of ball machines in developmental and elite sport programmes. Ecological dynamics
is predicated on ideas of ecological psychology and dynamical systems theory, with a level
of analysis embedded in the performer-environment relationship (Araújo et al., 2006;
Warren, 2006). This theoretical framework proposes that movement behaviours emerge
from dynamic interactions between neurobiological movement systems and their
performance environments (Davids et al., 2008; Newell, 1986). The interaction between
performer, environmental and task constraints results in the emergence of patterns of
movement behaviour that become stabilised through learning and practice.
A model based on the tenets of ecological dynamics has already been outlined for sport
scientists, coaches, experimental psychologists, and pedagogues, to underpin the design of
training interventions and practice tasks in sport (see Chapter 4; Pinder, Davids, et al.,
2011b). The model was predicated on concepts from ecological dynamics and a nonlinear
pedagogy (see Renshaw et al., 2010 for recent reviews of skill acquisition in sport).
Assessment of ‘representative learning design’ in specific practice tasks allows sport
94
scientists to understand the functionality and limitations of particular training
environments. Understanding representative learning design may provide opportunities to
optimise learning programmes in sport and inform use of performance enhancement tools,
such as projection technology, during practice. To assess representative learning design of
specific tasks, practitioners should consider the functionality of the practice task constraints
in allowing performers to pick up and use information sources representative of the
performance context (e.g., by comparing visual search strategies between projection and
‘live’ bowler/ pitcher situations – see Chapter 6). Since information regulates actions, an
important principle is that the key perception and action processes which are coupled in a
competitive performance environment should be maintained in the design of practice task
constraints. In simulations, the degree of association between practice and performance
contexts should be analysed by considering the fidelity of the performer’s actions (for a
detailed overview see Chapter 4; Pinder, Davids, et al., 2011b), such as by measuring and
comparing movement organisation between the different contexts (see Figure 5.1).
Chapter 5 – Principles for the use of ball projection machines
95
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96
Principles of representative learning design are summarised in Figure 5.1. The use of
projection machines should be considered in light of ways in which they might alter
learners’ emergent spatio-temporal responses, movement coordination and visual search
behaviours, when compared to facing a real bowler during performance. Future research is
needed to explore ways to increase the functionality of current practice tasks involving ball
projection machines. For example, it was recently reported that a specific ‘near life-size’
video simulation task which maintained a coupling between perception and action
processes, allowed the action fidelity of cricket batters’ preparatory and initial movement
responses to be maintained when compared to facing a ‘live’ bowler (see Chapter 3; Pinder,
Davids, et al., 2011a). Recent technological advances, which combine both video and ball
projection machines (e.g., ‘ProBatter’ – ProBatter Sports, LLC), may have a significant future
in elite sport and development programmes.
However, caution is needed with these new technologies, and the assessment of their
representative learning design may help identify the benefits and limitations of these
hybrid training tasks. As discussed, Croft et al. (2010) found that against projection
machines experienced batters fixated their gaze at a point on the anticipated trajectory of
the ball from the machine. As ‘ProBatter’ systems release the ball from a specific position (a
screen with one hole), it needs to be verified whether the pickup and use of information in
that simulation task actually replicates the competitive performance context. Because of
the high current cost of high fidelity ball projection systems, the standard projection
machine is likely to remain prominent in development programmes for some time. For this
reason, researchers should focus on carefully assessing and designing the informational
properties of a competitive performance environment that might be replicated at different
development and skill levels. This level of analysis is needed to provide insights into the
nature of the transfer of interceptive actions performed against projection machines and
real bowlers, for instance when comparing visual search strategies under both task
constraints (see Chapter 6).
5.6. A future role for ball projection machines?
The relevance of projection machines as part of training programmes needs careful
consideration. The key issue is how best to use them during practice. Current research does
not advocate removal of ball projection machines from cricket training programmes, since
investigation of their use is still in its infancy. Research has not yet examined their role in
Chapter 5 – Principles for the use of ball projection machines
97
high and low ball delivery speeds or looked at their effect on timing and coordination in
back foot shots (where a cricket batter moves backwards from their initial position to
intercept a ball which bounces closer to the bowler and reaches the batter around or above
waist height).
An important challenge is to examine their role in developing interceptive actions in early
and more advanced learners in ball sports. In the very early stages of learning when the
focus should be on the construction of a basic coordination pattern from all the possible
degrees of freedom, it is expected that the stable and consistent practice conditions would
greatly benefit the rate of learning (Schöllhorn, Mayer-Kress, Newell, & Michelbrink, 2009)
(also see Davids et al., 2008 for a review). To exemplify this in cricket batting, ball
projection machines could be used to deliver the ball to a restricted spatial location so that
learners stabilise a functional stroke, such as a forward defensive or straight drive.
Developing athletes, in particular, need to be provided with opportunities to establish
functional and stable relationships between perception of information from the
performance environment and their movements (Davids et al., 2008; Newell, 1985).
However, later in learning it is clear that stability and variability of practice task constraints
may allow for the development of more adaptable performers (Renshaw, Davids, Phillips, &
Kerhervé, 2011). At later stages of learning, ball projection machines could be used to
locate the learner in a meta-stable region of a perceptual-motor workspace. In this region,
learners remain in a state of relative coordination with the practice environment, being
unable to function completely independently, nor dependently, on environmental
information to regulate their actions. In the meta-stable region, functional movement
solutions can emerge during task performance, for instance when learners need to decide
whether to move forward or backward in playing cricket batting strokes (see Chapter 7 for
an exploratory investigation into the emergence of a meta-stable performance region in a
representative interceptive cricket action). By accurately projecting the ball onto specific
locations of the cricket pitch, more advanced learners can be forced to enter a meta-stable
region of batting performance to enrich performance during practice (see Hristovski,
Davids, & Araújo, 2009 for an example in boxing). These theoretical ideas imply that
traditional blocked practice methods utilising ball projection technology may prevent more
advanced learners from harnessing motor system degeneracy to functionally adapt stable
patterns of movement organisation, and may actually be dysfunctional when transferring to
more dynamic performance contexts (Kauffmann, 1995).
98
As a principle, therefore, it seems that, at all stages of learning, the role of projection
machines may be to ‘supplement’ rather than ‘replace’ the role of the ‘live’ bowler in the
acquisition of batting actions. Ensuring a balance between the use of projection machines
and bowlers may also ensure that batters are able to constantly attune and recalibrate
(recognise and adjust) to differences in ball flight characteristics under the distinct practice
contexts and establish important information-movement couplings. However, further
research is needed to assess the effects on skill acquisition of different volumes (amount of
time) of supplementary practice in fast ball sports (e.g., visual training through video
simulation designs or ball projection machines).
Additionally, variations in ball speed and trajectories (e.g., constant changes in bounce
location) may allow increased opportunities for batters to exploit and master the
perceptual degrees of freedom which support adaptive movement behaviours needed
during performance (see Savelsbergh, van der Kamp, Oudejans, & Scott, 2004). Intuitively,
it would be predicted that when there is a reduced temporal constraint on batters’ actions,
such as when playing against slow bowling, ball-flight information might become more
salient (i.e., less reliance on pre-release information) and could provide opportunities for
increased fidelity of performance when using projection machines. Ball projection
machines, as outlined in section 5.4, are able to replicate the same ball speeds and angle of
release as a ‘live’ performer, providing some level of ‘representativeness’ of practice task
information. It is important to consider the goal of the learning or practice session, as this
may dictate the degree to which a design is a representative simulation of a performance
environment; essentially it is important to sample the important aspects of the
performance context that support these goals. Therefore, the consideration and
assessment of the representative design of ball projection machines nested within
particular performance contexts (e.g., middle wicket practice with typical game demands)
may increase action fidelity at more elite levels. With respect to this idea, it is important to
note that most projection systems available to practice batting in cricket do not currently
support the use of balls with the same properties as those typically used during competitive
performance. This is a major issue since expert performers have been shown to use seam
characteristics of balls to support perceptual decision making in fast ball sports (Hyllegard,
1991). The use of tasks which more closely replicate the flight and bounce characteristics of
a ball used in competitive performance should become a focus for future work.
Chapter 5 – Principles for the use of ball projection machines
99
5.7. Conclusion
Using projection machines in sport should not be considered dysfunctional. Importantly
they help alleviate workload stresses on bowlers or pitchers during ball delivery which can
lead to overuse injuries in developing and elite performers. Nevertheless, it is disingenuous
to call ball projection machines ‘bowling machines’, because they can only generally
simulate post-ball release information sources during batting practice. They do not allow
learners to pick up specific sources of pre-release information from bowlers’ actions, a vital
part of the information-movement coupling link in batting performance. Current practices
of using such projection technology in athlete development programmes can be enhanced
by using theoretically guided principles to underpin their implementation as a skill
acquisition and performance preparation tool in ball sports. Principles of ecological
dynamics suggest that: (i) their use is likely to differ according to the needs of different skill
groups; (ii) they are most functional when used in high fidelity simulations of performance
environments (e.g., nested in performance settings such as middle wicket practice, or in
combination with video simulations); and (iii) they should supplement practice with ball
projection by real individuals so that all learners can attune to the affordances for action
provided by movements of opponents during ball delivery.
101
"We know as much of the history of cricket as we shall ever know now, and we have been
told everything relating to the science of the game. There is no fresh ground to be
explored."
Rev. Holmes (1893)
Chapter 6 – Visual strategies under distinct practice task constraints
103
Chapter 6 – Visual strategies of developmental level cricket batters
under distinct practice task constraints
Due to the concerns raised in this thesis with regards to experimental and practice design
utilised in previous research, there was a need to reassess visual strategies of cricket
batters under ball machine and ‘live’ bowler constraints.
This chapter is based on the following article currently being finalised for submission for
peer review:
Pinder, R. A., Mann, D., Renshaw, I., & Davids, K. (to be submitted). Visual strategies of
developmental level cricket batters under distinct practice task constraints.
104
6.1. Abstract
Land and McLeod (2000) proposed that cricket batters pursuit tracked the ball for the first
100-150 ms of ball flight following release from a ball projection machine, before making an
early and predictive visual saccade to the anticipated bounce point of the upcoming
delivery; a characteristic more evident in highly skilled batters. However, the use of ball
projection machines in experimental and practice design has recently been questioned and
reviewed (Pinder, Renshaw, et al., 2011). There is a need to discover how differences in the
way a ball is delivered in tasks such as batting against a bowler versus a ball projection
machine, changes the visual search strategies during performance in fast ball sports. This is
a particular concern given the strong reliance on blocked practice using ball projection
machines in developmental training programmes, when a performer is aware in advance of
the predictable, consistent bounce point of the ball. In this Chapter, the performance and
visual search strategies of developmental level cricket batters (n = 5) were assessed when
facing a ‘live’ bowler and a ball projection machine (in both blocked and random ball
delivery conditions). Findings demonstrated that visual strategies of developmental batters
under moderate to high temporal demand (≈ 28 ms·-1) are significantly affected by
differences in pre-release information under changing task constraints. When facing a ‘live’
bowler compared to both ball projection machine tasks, batters initiated the pursuit track
earlier after release, tracked the ball for a longer proportion of early flight and performed
fewer visual saccades. The presence of a visual saccade was not indicative of highly skilled
performance; in fact higher ranked batters performed fewer visual saccades (≈ 60% of
trials) than their lower ranked counterparts (≈ 100%). Furthermore, higher ranked batters
demonstrated an ability to initiate the pursuit track sooner after ball release enabling them
to sample a greater proportion of critical early ball flight. Findings are discussed with
reference to practice routines, providing some evidence to support previous concerns
cautioning against the overuse of ball machines for learning design with developmental
performers (see Chapter 5). Previous interpretations and understandings of visual saccades
and their relationship to visual pursuit tracking appear to have been limited by artificial task
designs, and future research is recommended to advance understanding of perception-
action processes during skilled interceptive actions.
Chapter 6 – Visual strategies under distinct practice task constraints
105
6.2. Introduction
Spatial-temporal constraints in fast ball sports, such as cricket, can go beyond the intrinsic
limitations in visuo-motor delays and movement times (Regan, 1997; van der Kamp et al.,
2008), and allow for excellent insights into the use of information for the support of action
under changing task constraints (e.g., amount of advanced information provided in
experimental conditions). Analysis of movement models in fast ball sport exemplifies the
functional coupling of perception and action processes, and the synergetic relationship
between a performer and environmental context. Previously, there have been assumptions
that athletes are required to fixate and pursuit track an object for skilled interception
(Regan, 1997), or that high levels of visual function are required for skilled performances to
be sustained. Indeed, many people believed that Sir Donald Bradman, widely regarded as
the greatest cricket batsmen in the history of the sport, benefitted from superior visual
function and reaction times. It is, however, reported that Bradman was discharged from the
army due to poor eyesight (Glazier et al., 2005; Hutchins, 2002) and recent studies by Mann
and colleagues (2010; 2007) demonstrated that no discernible reductions in batting
performances were evident under increasing levels of myopic blur that resulted in
impairment of foveal vision under moderate and high temporal demands (moderate ball
speed in cricket batting: 30-40 m·s-1). It has been surmised, therefore, that skilled
performance in sport is not necessarily dependent on the pickup of accurate trajectory
information of an object to successfully intercept it (Mann et al., 2010). Aligned to this, it
has also been proposed that performers are unable to pursuit track for the entire duration
of a target’s approach due to high ball speeds. For example in cricket batting, it has been
demonstrated that performers used a combination of target pursuit tracking and visual
saccades when intercepting balls delivered from a ball projection machine. Visual saccades
appear to enable a visual ‘catch-up’ of foveal vision in instances where the visual system is
unable to “keep up” with the ball flight (Land & McLeod, 2000). However, to successfully
intercept balls moving at high speeds it is also generally accepted that performers require
the ability to perceive ball trajectory information (e.g., angle of approaching ball, predicted
bounce point) quickly and accurately in order to support shot and movement response
selection. Indeed, information about ball flight elicited from a bowler’s actions has been
shown to contribute towards batters’ judgements of ball delivery type (Müller &
Abernethy, 2006; Müller et al., 2009).
106
Smooth visual pursuit tracking strategies during human performance allows for the
extraction of detailed and meaningful information from the environmental context (Spering
& Gegenfurtner, 2008). Tracking objects with foveal vision over longer periods of total flight
time increases the perceptual acuity of the object (e.g., the speed and angle of an
approaching ball to be intercepted). However, Spering and Gegenfurtner (2008) recently
concluded that eye movement strategies, such as the ability to smoothly track objects, are
highly context dependent, with visual strategies constrained by numerous factors, such as
absolute or angular speed of an approaching object, or the predictability of an object’s
flight (McPherson & Vickers, 2004). Land and McLeod (2000) published their seminal and
highly cited paper more than ten years ago; assessing the visual strategies of three
cricketers batting against a ball projection machine. Land and McLeod (2000) assessed the
eye movements of three cricket batters (skilled, experienced and novice) when facing a ball
projection machine under moderate temporal constraints (25 m·s-1). Findings demonstrated
that batters picked up trajectory information after the release of the ball from the machine
for a period of 100-150 ms (equating to 50-80% of total ball flight), before making an
anticipatory saccade to the predicted bounce point. Findings suggested that batters cannot
‘pursuit track’ the ball for the duration of ball-flight, therefore requiring them to pick up
trajectory information as soon as possible to predict bounce point and/or delivery type.
Croft, Button and Dicks (2010) recently attempted to reassess the findings of Land and
McLeod (2000) to establish if there was a critical velocity at which predictive saccades were
required. However, they found that no simple relationship existed between projection
speed and the initial tracking duration. Croft et al. (2010) found that under slow to
moderate temporal constraints (17-25 m·s-1), experienced sub-elite batters used a variety
of highly individual strategies, with considerable variation beyond a group tracking mean of
between 63 and 71% of ball flight. Large within- and between-participant variability
demonstrated that batters used different strategies both before, and immediately after ball
release (e.g., saccade or track); a finding consistent in other fast ball sports (McPherson &
Vickers, 2004; Singer et al., 1998). Some batters in the Croft et al. (2010) study tracked the
ball immediately following ball release and then for the majority of ball flight; a finding
consistent with skilled batters in Land and McLeod’s (2000) study. It is possible that ball
deliveries with longer flight times due to bouncing closer to the batter, and/or moving at
slower velocities, allow for increases in tracking duration and do not exceed the limitations
of the visual tracking processes. These findings suggest the ability of a batter to pick up ball
flight information as early as possible may afford a longer tracking duration. Previous
interpretations suggest that the occurrence of a visual saccade may be due to a critical
Chapter 6 – Visual strategies under distinct practice task constraints
107
change in vertical velocity at ball release (e.g., short balls that bounce further away from
the batter and are delivered on a steeper angle from release) (Land & McLeod, 2000).
Latencies between the release and initial pursuit tracking of the ball in both instances may
account for the appearance of predictive saccades, with some skilled batters in Croft et al.’s
(2010) study able to track directly from release and therefore may in fact be able to counter
this need to ‘catch up’ with the ball.
A concern, however, has been recently highlighted, with the role of ball projection
machines in performance and athlete preparation being questioned and reviewed (for a
comprehensive review see Pinder, Renshaw, et al., 2011; also see Chapter 5). There is a
need to discover how differences in the way a ball is delivered in tasks such as batting
against a bowler versus a ball projection machine changes the visual search strategies
during performance in fast ball sport. This is a particular concern given the widespread
acceptance of the findings of the Land and McLeod study (based on 3 performers of widely
varying skill level). Additionally, the issue is important on a practical level given the
tendency for developmental programmes in cricket to utilise projection machines to
provide large volumes of blocked practice (e.g., via practice where a performer is aware in
advance of the predictable, consistent bounce point of the ball; Woolmer et al., 2008).
Research comparing batting performance against ball machines and ‘live’ bowlers has
demonstrated significant differences in spatio-temporal characteristics of batting
performance and movement responses (Mann et al., 2010; Pinder, Davids, et al., 2011a;
Pinder et al., 2009; Renshaw et al., 2007). These differences are a result of the fact that
batting against a ball machine removes the critical information sources present in a
performance context representative of facing an opponent (e.g., removal of bowler’s
movement information such as angle of arm at ball release). Failure to be able to attune to
this crucial information source leads to a critical delay in movement initiations of
developmental level batters. This is because early ball flight needs to be sampled before the
bounce point can be identified to enable the batter to make a decision to move forward or
backward to intercept the ball1. It is this increased temporal demand that ultimately results
in a reduction in batting performance.
1 Balls that pitch short, or further away from the batter will bounce higher and the batter needs to step back to typically intercept the ball at approximately waist-chest height. In contrast, balls that bounce close to the batter can be stepped forward to, and be intercepted around knee height.
108
Additionally, some researchers have utilised video projections to provide experimental
control between participants (e.g., Barras, 1990). Barras (1990) suggested that batters
should focus on the ball in the bowler’s hand up until less than 1 second before the release
(during the bowlers final delivery stride), at which point they should move their visual gaze
to the anticipated release point. However, due to the separation of the perception and
action processes in task designs (removal of a representative response), the results of such
studies are questionable (see section 2.8; also see Chapter 4). For example, Dicks and
colleagues (2010) recently observed different visual strategies present in soccer
goalkeepers under different degrees of perception-action separation. Croft et al. (2010)
reported that batters used very different visual strategies before the release of the ball,
with some batters looking directly at the ball machine outlet, while others ‘parked’ their
gaze on an anticipated trajectory of flight. Similar to previous spatio-temporal analyses of
batting performance, it appears that experience with a ball projection machine may lead
batters to tend towards a predictive visual strategy (see Chapter 5; also see Renshaw et al.,
2007), which may not be indicative of other performance settings; based on this body of
work, it is intuitive to suggest that differences are likely to exist in visual strategies under
changing task constraints in cricket batting. Intuitively, the removal of information from the
bowler’s action may have led to the adoption of specific visual strategies at, and
immediately after, ball release in previous studies (e.g., Croft et al., 2010; Land & McLeod,
2000) However, until now few attempts have been made to assess visual strategies in
cricket batting, and to our knowledge none that have compared visual strategies under ball
machine constraints to those representative of a performance context of facing a ‘live’
opponent.
The previous discussion raises two important issues: i) no previous work has reported the
frequency at which saccades occur during performance under varying task constraints, and
ii), analyses have only been completed with performers facing ball projection machine task
constraints under moderate time constraints for highly skilled or experienced performers
(with the exception of one novice participant – see Land & McLeod, 2000) . The use of
projection machines may increase the latency between release and initial pursuit tracking
initiation. Indeed large volumes of blocked practice experience using a ball machine may
increase the predictability of the ball trajectory and result in visual search strategies not in
line with those adopted when the bounce point is not known in advance. Understanding of
the functional role of visual saccades in fast ball sports (and their relationship to the initial
pursuit tracking strategy) may, therefore, currently be at best limited, or at worse
Chapter 6 – Visual strategies under distinct practice task constraints
109
misleading given previous assessments under artificial task constraints such as batting
against ball projection machines rather than real bowlers. An interesting question concerns
whether visual strategies may be compromised under ball projection machine performance
conditions. Previous research has suggested that an important element of expertise in
cricket batting against a ball projection machine is the ability to initially pursuit track early
in ball flight before accurately making early visual saccades to a predicted landing point of
the ball; these are critical aspects since these pursuits or saccades may differ substantially
between ball machine and ‘live’ bowler task constraints.
The aims of the study reported in this Chapter were to assess the pursuit tracking and
saccadic strategies of developmental performers in cricket batting under moderate to high
temporal demand when presented with three distinct tasks. Based on previous work and
developmental practices, batters were required to face ‘live’ opponents bowling a ball, a
ball projection machine delivering balls in a random order (where a coach follows a random
script for targeted ball bounce location and therefore changes in the angle of the ball
machine head), and a ball machine delivering balls in a blocked order (where balls at three
distinct ball-length/ bounce points were presented in blocked order with little between trial
variation in machine positioning). It was hypothesised that developmental batters would
pursuit track sooner after ball release when facing a ‘live’ bowler compared with ball
machine task constraints, enabling earlier and more accurate saccadic predictions.
Furthermore, it was predicted that higher skilled developmental batters would also show
distinct differences in visual strategies than their less skilled counterparts. Specifically,
based on previous research it was predicted that higher skilled batters would make early
predictive saccades to the expected bounce point.
6.3. Method
Participants
Six junior cricketers (age 16.32 ± 0.30 years; 8.83 ± 1.72 years of competitive cricket
experience) were recruited for the study. Participants were matched in height (1.76 ± 0.04
m) to standardise body-scaling of ball-bounce performance regions (see Figure 6.1), and
were considered to be moderately skilled junior performers at the control stage of motor
learning by 2 Cricket Australia Level 3 coaches and motor learning specialists (Newell,
1985). Each batter faced three bowlers during performance (n = 5; mean age: 15.25 ± 0.99
110
years) due to work load concerns on junior bowlers (Dennis et al., 2005). Bowlers had
similar conventional bowling (ball delivery) actions and physical attributes (all right arm
bowlers; peak height of bowling arm: 2.10 ± 0.05 m; bowling speed: 28.29 ± 0.96 m·s-1).
Peak height was measured from a sagittal view of the bowling line. Bowling workloads were
controlled by an experienced Australian Level 3 cricket coach. Bowling speed was assessed
prior to data collection, and monitored throughout the testing session using a sports radar
gun (Stalker Radar, Texas). One batter was later removed from the analysis due to
equipment failure. All participants wore full protective equipment and provided informed
consent to a protocol approved by a university ethics committee.
Table 6.1. Participant information. CPE= Competitive playing experience in years; BPW = Self-report
average of ‘balls’ per week practiced using a ball projection machine; QoC = Quality of contact; FoBS
=Forcefulness of bat swing.
Batter CPE Ball Machine BPW Within task
QoC ranking
Within task
FoBS ranking
Coaches
Ranking
Combined
Skill Ranking
1 11 100-200 1 1 2 1
2 9 30 2 3 1 2
3 8 20 3 2 4 3
4 6 0 4 4 3 4
5 9 100 5 5 5 5
Procedure
Performance observations occurred in the participants’ regular practice facility. Batters
undertook three distinct experimental tasks - batting against: i) ‘live’ bowlers, ii) a ball
machine ‘random’, and iii) ball machine ‘blocked’ projection regimes. In the blocked
condition, the batter was aware of the intended bounce point of the ball delivered from a
ball machine, and three different areas for the bounce point (ball-length) were presented in
blocked conditions until required trials were completed. In the random condition, the three
different bounce points were randomised by the experimenter and coach operating the
machine. Task conditions were counterbalanced between participants to control for order
and learning effects. Batters were appropriately matched to the skill level of the bowlers.
Due to the large between-participant variability seen in previous work (e.g., Croft et al.,
2010; Land & McLeod, 2000), batters were ranked by their coach, and rankings were
supported by within-task measures of quality and aggressiveness of their batting
Chapter 6 – Visual strategies under distinct practice task constraints
111
performance (see Table 1; also see Figure 2). Batters 1 and 2 are considered to be top order
batsmen (highly skilled relative to participant group – state representative level), batters 3
and 4 were middle order batsmen (moderately skilled relative to group) and batter 5 was a
low order player (low skilled relative to other batters)2. Given potential impact of
experience of facing ball machines on eye tracking and movement responses, it was
important to consider information regarding individual practices. All batters had experience
of playing against the same ball machine used in the study; however individual batters
reported different weekly volumes of practice under ball machine constraints (i.e., number
of balls per week - see Table 6.1).
Prior to data collection, three distinct spatial areas (ball-lengths) for ball bounce were
chosen based on consultation with the coach. These areas (see Figure 6.1) were body-
scaled to the batters in the study, and were based on typical ball-lengths focused on during
batting skill development to provide a representative sample of deliveries a batter might
face in a match situation (Woolmer et al., 2008); i) a ‘Full-length’ ball that bounces close to
the batter (2.5-3.5 m from the stumps) and is typically intercepted at shin height, ii) a
‘Good-length’ ball (5-6 m) bouncing to the height of the top of the stumps (bowlers’ target
in cricket) typically intercepted at approximately knee height, and iii) a ‘short-length’ ball
(8-9 m) which bounces higher, and typically requires a batter to move backwards to
intercept the ball at around waist to chest height. The inclusion of deliveries which required
batters to move forward and back ensured that batters had a crucial decision to make on
each trial; batters were not primed to move in one direction which might have influenced
visual measures.
The same balls (‘Oz’ ball machine ball) were used across all conditions to provide
consistency in bounce and flight characteristics. The ball machine (Jugs Inc., Tualatin,
Oregon) was set at the same height and bowling speed recorded from the bowlers to
replicate their ball delivery characteristics (e.g., release speed, angle of delivery). Bowlers
followed an individual and randomised script of pitching locations to target, and waited for
a ready signal from the batter before beginning their approaches. The randomised scripts
were replicated in the ball machine condition; where between trials, batters were
instructed to turn and walk to touch the back of the protective net behind the stumps 2 Top order players are those in the early positions (1-5) of a cricket batting line-up, and are typically the best batters. Middle order players (positions 6-8) are typically ‘all rounders’, who both bat and bowl. Lower order batters are typically the bowlers who have the lowest batting skill (positions 9-11).
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allowing the angle of the machine head to be altered. In addition to batters being blind to
any initial adjustment of the machine head, the ball machine operator was able to make
subtle changes to the trajectory at release that could not be detected by the batters. The
ball machine was operated by a highly experienced Australian Level 3 coach using a
standardised pre-delivery routine used in practice; the operator waited for a ready signal
before holding up the ball for the batter to see before lowering directly into the machine
(see Pinder, Davids, et al., 2011a; Renshaw et al., 2007; Shim et al., 2005). The time
between the ball entering and exiting the machine (approximately 1 s) was consistent
across all conditions and ball release trajectories. Similar to previous work (Pinder, Davids,
et al., 2011a; Shim et al., 2005), the sound of the machine was expected to provide
supportive information for the prediction of release through previous ball machine
experience (i.e. perceptual attunement of batters’ responses).
Batters were instructed to perform as they would in a competitive performance context, by
attempting to score as many runs as they could while avoiding being bowled (ball hitting
stumps). No specific task instructions or knowledge of the experimental aims were
provided. Batters were given six practice trials before the commencement of each
condition. Participants continued to bat until they had completed a minimum of five trials
at each ball-length (see Figure 6.1). Participants generally faced 20-36 deliveries in each of
the interceptive conditions (ball machine and bowler) to generate the required number of
shots for data analysis, in line with previous empirical research (Stretch et al., 1998). A
trained research assistant noted the location of ball-bounce ‘live’, and bounce location was
confirmed post hoc using video footage (see below). Trials in which the ball did not bounce
within specified locations were excluded from the analysis.
Chapter 6 – Visual strategies under distinct practice task constraints
113
Figure 6.1. Side and above views of experimental set-up
Data collection
Participants wore a mobile eye-tracking unit under a customised batting helmet (25 Hz:
Mobile Eye, Applied Sciences Laboratories) to track the location of visual gaze during
batting performances (see Figure 6.2). The Mobile Eye unit was attached to a Digital Video
recording device (Sony DV Walkman) worn in a lightweight pouch around the lower back
during the batting tasks. The unit (≈ 1 kg) was fitted securely so it did not obstruct the
batters movement requirements. The DV unit was attached to a Radio Frequency (RF)
transmitter allowing the eye movement footage to be sent wirelessly to a receiver (large
LCD display) for real time monitoring by an experienced researcher. Consequently, any
changes to the location of the scene or eye cameras were able to be detected, maximising
the percentage of useable trials for data analysis; a major concern in previous work. The
customised helmet had a portion of the peak removed to minimise obstructions or ‘knocks’
to the Mobile Eye unit. Calibration of the visual gaze footage was performed using a
number of pre-determined locations within the batters expected visual scene (for example
marked distances on the ground and mouth of the ball machine or ball at a typical release
position of a bowler). Re-calibrations were performed before and after each condition,
anytime the unit was moved, or when a change in the scene or eye cameras was detected.
These checks allowed for the successful analysis of 95% of all collected footage (including
trials not selected for analysis).
20.12m (pitch length)
17.7m (distance between creases)
BatterFull Good Short
Bowler/ Ball Machine
Stumps3.5 m
6 m9 m
Ball Release
0.71 m
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A series of video cameras were used to capture the behavioural responses of the batters,
and link to the eye movement recordings. Two event-synchronised video cameras (Casio
EXILIM Pro EX-F1: 60 Hz) captured participants’ movement organisation and batting
performance (anterior view), and moment of ball release (perpendicular to delivery line)
concurrently. A third camera (Sony HVR-V1P, 50 Hz) was positioned behind the batter and
allowed the synchronisation of eye-movement footage with the moment of release,
bounce-point and batters behaviour. All footage was analysed frame-by-frame and visual
and behavioural responses were coded with respect to key events (e.g., release, ball
bounce, bat-ball contact).
Figure 6.2 – A participant wearing full protective equipment and mobile eye-tracking unit
Dependent variables
Performance scores
Batting performance was assessed using validated measures of Quality of Contact (QoC; see
Müller & Abernethy, 2008), and Forcefulness of Bat-swing (FoBS; see Mann et al., 2010).
QoC indicates the quality of the interception as 2, 1 or 0 for good, poor and no bat-ball
contact, respectively. FoBS indicates the aggressive intent of the action, and an indication
of the likelihood that runs would have been scored (i.e. a higher score represents a more
Chapter 6 – Visual strategies under distinct practice task constraints
115
difficult shot requiring a greater degree of spatial-temporal precision); scores of 2, 1 and 0
were used for high, moderate and low forcefulness, respectively. Reliability was assessed
on a selection of 20 random trials (≈10% of all trials). Intra-rater reliability was assessed by
comparing two video reviews (with a 4-week break) of the first observer, while inter-rater
reliability was assessed by comparing the scores of the first observer with those of a second
observer. Strong correlations were found for both intra- (rs = .87) and inter-rater (rs = .91)
reliability, consistent with previous work (Mann et al., 2010).
Visual tracking
Batters’ visual behaviours were subjected to frame-by-frame analysis from ball release to
bat-ball contact. Batters were considered to be ‘tracking’ the ball when the gaze-ball
discrepancy was less than 1.5° in accordance with previous work (Croft et al., 2010). A
saccade was coded when the gaze was seen to transition between two distinct locations on
the scene view in line with previous work (Land & McLeod, 2000). Four measures of visual
responses were analysed: i) pursuit tracking initiation (PTI) was coded as the first frame of
the smooth pursuit track following ball-release (within 1.5°), ii) pursuit tracking duration
(PTD) was defined as the initial and uninterrupted visual tracking duration following PTI, iii)
frequency/ number of visual saccades performed, and iv), timing of a saccade (if present).
All values are reported as a percentage of ball-flight from release to bounce point to allow
for comparison with previous work. Visual tracking and saccade variables were
independently assessed by two trained researchers. A random selection of trials (n = 20)
was used for inter- (Interclass Correlation Coefficient = .86) and intra-rater reliability (.88)
checks. Furthermore the presence and timing of saccade values revealed inter-rater
reliability scores of .96.
Data Analysis
Mixed model ANOVAs were used on performance scores and visual tracking variables;
allowing for the modelling of dependent variables as within-participant factors between
experimental constraints (e.g., batting tasks). Between-participants tests were used to
allow for comparisons across dependent variables on an individual level, with data checked
using Levene’s test of equality of error variances. Given recent arguments in behavioural
sciences that the tendency to average performance data for statistical analysis can mask
functional variability observed in individual participants (see Dicks, Davids, & Button, 2010;
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Schöllhorn et al., 2009), results were assessed on a group and individual basis. This is
particularly important given findings in visual search data of high between- and within-
individual variability (Croft et al., 2010; Land & McLeod, 2000; Singer et al., 1998). In
instances where data violated the sphericity assumption, a Greenhouse–Geisser correction
adjusted the degrees of freedom for treatment and error terms of the repeated measures
variables. Post hoc pairwise comparisons were undertaken to assess which comparisons
were statistically significant in each instance. Bonferroni corrections, with adjustments to
an alpha level of .01 were used to control for type I error and account for possible
interdependence between variables and multiple comparisons (Field, 2009). Finally, partial
eta-squared (ηp2) values were provided for each ANOVA to provide an indication of the
effect size or magnitude of the differences in variability. Due to the nature and current
unpredictability of the occurrence of visual saccades, linear mixed models were used to
analyse timing of visual saccades. Linear mixed models allow for individual differences in
addition to group means, but also accommodate multiple missing data points (i.e. analysis
of trials in which a visual saccade was present was not affected by trials without a saccade)
(Krueger & Tian, 2004). Bonferroni corrections, with adjustments to an alpha level of .01
were used to control for type I error and account for multiple comparisons (Field, 2009).
Finally, Pearson correlations were used to assess key relationships between visual tracking
measures and batter skill level (e.g., PTD versus skill level).
6.4. Results
Batting performance scores
A mixed model ANOVA revealed significant effects for QoC across experimental (batting)
task constraints, F(2,140) = 6.35, p < .01, η2 = .22, and individual batters, F(4,70) = 4.203, p <
.01, η2 = .19, but not a significant interaction between batter and experimental condition,
F(8,140) = 1.82, p > .05, η2 = .09. Bonferroni post hoc comparisons with an adjusted alpha
level of .01 on QoC revealed that batters 1 and 2 scored significantly higher in interceptive
quality than Batter 5. Group means demonstrated that there was a significant reduction in
QoC when facing a randomised ball machine, compared to both blocked and ‘live’ bowler
conditions (p < .01). Individual results between experimental conditions are presented in
Figure 6.3; two batters actually maintained or increased the number of good contacts when
playing against the ball machine when compared to a ‘live’ bowler (batters 1 & 5). Although
batter 5’s scores were still significantly lower, scores under blocked machine task
Chapter 6 – Visual strategies under distinct practice task constraints
117
constraints were similar to other batters. Furthermore, a mixed model ANOVA revealed a
significant main effect for FoBS on experimental task F(2,140) = 10.66, p < .01, η2 = .13.
There was no significant effect for batter, F(4,70) = 1.69, p > .05, η2 = .09, nor was there an
interaction between batter and experimental task, F(8,140) = 1.32, p > .05, η2 = .07. All
batters were similarly affected by the experimental constraints, where there were
significant reductions in FoBS scores in both blocked (p < .01) and random machine
conditions (p < .05), compared to facing a ‘live’ bowler.
Figure 6.3. Individual (a & b) and group (c) performance scores under changing task constraints.
Pursuit tracking
A mixed ANOVA revealed significant main effects for PTI on experimental task, F(2,140) =
26.66, p < .01, η2 = .29, and batter, F(4,70) = 4.237, p < .01, η2 = .20, with a significant
condition x batter interaction, F(8,140) = 3.27, p < .01, η2 = .18. Bonferroni post hoc
comparisons with an adjusted alpha level of .01 on PTI revealed that batters initiated the
pursuit track of the ball significantly earlier after release when facing a ‘live’ bowler (after
24.86 ± 12.65% of the total ball-flight from release to bounce; i.e. ≈25% of the ball-flight
had already been completed) in comparison to both blocked (36.80 ± 16.01%) and random
0.000.200.400.600.801.001.201.401.601.802.00
1 2 3 4 5
Qua
lity
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Batter
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0.000.200.400.600.801.001.201.401.601.802.00
1 2 3 4 5
Forc
eful
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atsw
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(FoB
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Batter
b)
B BMR BMB All
0.00
0.20
0.40
0.60
0.80
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QoC FoBS
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ball machine constraints (33.96 ± 14.44%). Large standard deviations are indicative of
Number of saccades .91 .02* .75 .15 .94 .02* .87 .06
6.5. Discussion
Land and McLeod (2000) proposed that a key characteristic of skilled batting performance
was the early and accurate visual saccade to the anticipated bounce point of the ball
following a short period of pursuit tracking. However, one major concern was that these
pursuit track characteristics were observed under experimental constraints representative
of an artificial training task; batting against a ball projection machine. The data in this
Chapter demonstrated that significant differences exist between the visual characteristics
of developmental batters under changing task constraints, including a representative task
of facing a ‘live’ opponent delivering a ball.
Performance and visual strategies
Similar to previous work, batting performance scores (QoC/ FoBS) were significantly
reduced when responding to balls delivered from a projection machine (see Figure 2; also
see Chapter 3). All batters (except batter 5) had a greater or equal performance (QoC)
when facing a bowler compared with a ball machine; additionally all batters performed
better under blocked constraints compared with a random ball machine condition. It is
apparent that pre-knowledge of the upcoming delivery allows the batter to greatly increase
the interceptive quality of the resulting action, however, it should be noted that all batters
had a reduction in FoBS (an indication of the aggressive intent of the shot) in the blocked
condition. Contrary to prediction, batters reduced the forcefulness of the hitting action
when they had pre-knowledge of the upcoming delivery. It may be that batters premeditate
the required action, resulting in lower levels of adaptive decision making behaviour in these
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well practiced ‘short’, ‘good’, and ‘full’ areas, with fewer different shots and deepening of
performance ‘attractor’ states (see Chapter 7; also see Pinder, Davids & Renshaw, in press).
As hypothesised, and in accordance with performance scores, when batters were provided
with advanced information of a bowler’s action (beyond ball-flight from release provided by
a machine), they were able to significantly reduce the delay between release and the
initiation of a smooth pursuit track of the ball in flight (see Figure 6.4). Consequently,
batters were all able to pursuit track the ball for a greater percentage of the ball-flight
when facing a ‘live’ opponent (40-70% ball-flight), compared to both blocked and random
conditions (30-65%; note the large within-participant variability). Collectively,
developmental batters visual tracking performance was similar to that seen in previous
work (Croft et al., 2010; Land & McLeod, 2000); with few discernable differences
demonstrated for PTI between blocked and random ball machine conditions (however see
individual differences below; also see Figure 6.4). However, PTD was longer under blocked
conditions compared to random; a suggestion that some pre-knowledge of upcoming
delivery was useful in aiding the visual strategy, and accordingly QoC for all batters (see
Figure 6.2). It may be that despite any discernible difference in initiation times, pre-
knowledge of the possible angle of delivery allowed batters to ‘wait’ for the ball and track
for a longer duration once the correct angle was confirmed; this appears to be particularly
evident for Batter 1 (see below).
Batters facing a ball machine tracked the ball in a similar manner to batters in the study of
Land and McLeod (2000), however, when facing a ‘live’ opponent bowling the ball, batters
initiated smooth pursuit tracking significantly earlier (≈ 25% of the ball-flight), continued it
for significantly longer, and therefore sampled a greater percentage of the critical post-
release ball flight information observed to define skilled performance in cricket batting (see
Müller et al., 2009). It was hypothesised that earlier initial pursuit tracking behaviour would
result in earlier saccades to a predicted bounce location (e.g., a quicker recognition of ball
length). However, earlier PTIs resulted in significantly longer PTDs for all batters when
facing a bowler, removing the need for earlier predictive saccades. In fact, all batters
significantly reduced the number of visual saccades they performed against bowlers,
compared to batting against the ball machine (for an exception see Batter 1, Figure 6.5; also
see below). Furthermore, when these saccades were present (i.e., when they were required
as part of the batters visual strategy) they occurred significantly later in ball-flight against
bowlers (> 90% of the ball-flight), suggesting that batters produced more accurate saccades
Chapter 6 – Visual strategies under distinct practice task constraints
125
at the critical timing of bounce point. Taken together (see Figure 6.6), these visual
measures suggested that when facing a bowler, batters pursuit tracked for a longer period
of the early ball flight before ‘falling behind’3 the ball. At this point batters appear to make
no instant visual saccade but proceed to follow ‘behind’ the ball before making an accurate
visual saccade to the bounce point. In trials where no visual saccade was evident, batters
tracked the ball for a greater proportion of ball flight before falling behind, again making no
attempt to catch up via foveal vision; this suggests that the required information may have
been extracted over this longer tracking duration, or enough information was gained to rely
on peripheral vision. Under ball machine task constraints, developmental performers
demonstrated visual search strategies in line with previous research (Croft et al., 2010; Land
& McLeod, 2000). Batters tracked the ball for a similar length and period of ball flight,
before making an early saccade to the anticipated bounce point following a short lag
behind the ball. It is possible that these key differences between task constraints
demonstrate that batters adopted both a predictive strategy (when facing a bowler) and a
reactive strategy (when facing a ball machine), when functional. Batters picked up ball-
flight information later, seemingly allowing the ball to ‘wash over the retina’ therefore
appearing to track for a shorter period of time, before making a reactive and necessary
saccade ahead to an anticipated bounce point (Glazier, Davids, & Bartlett, 2002).
Individual and skill related differences
As discussed previously, batters tended to perform better on all performance and visual
measures when facing a bowler, compared with either of the ball machine tasks.
Interestingly, two Batters (the best and worst) maintained or increased the quality of action
(QoC) when facing blocked trials against a ball machine when compared to a ‘live’ bowler
(see Figure 6.2); both of these Batters (1 & 5) reported large volumes of weekly practice
time dedicated to this specific task. Furthermore, Batter 1 initiated the pursuit track
significantly later against the blocked machine with a significant reduction in the number of
visual saccades required without detriment to performance. Small individual differences
between ball machine tasks may be indicative of differences in practice histories or skill
level with the specific type of machine used, however, similarities between the two distinct
delivery methods demonstrate that the differences between visual and performance
3 A phrase used to demonstrate an instance when the foveal vision does not keep up with the previous pursuit track, lagging behind the ball falling below the visual gaze. Generally the performer still appears to be making continual adjustments following the line of the ball.
126
measures are a result of the removal of task specific information sources (e.g., a bowler’s
action) rather than differences in the additional information (e.g., knowledge of likely
bounce point). Despite being highly skilled under all conditions, distinct visual strategies of
Batter 1 may be an indication that a performer has learned to ‘bat against the machine’
(Pinder et al., 2009). Although self-reported scores do not provide a detailed history of use,
they do allow us to assess the current and shorter term volume of practice under machine
conditions. Interestingly, the three Batters (2, 3, & 4) who reported little weekly ball
machine use demonstrated larger differences between the bowler and machine task
constraints, and few discernible differences between blocked and random conditions.
QoC and FoBS scores were used as within-task assessments of skill level to support a
coaching assessment and provide an overall ranking; allowing us to assess any visual
differences within the current participant group. Furthermore, as ranking is partly based on
overall experimental task performance, some inferences can be made regarding the link
between task and visual performance. Figure 6.7 demonstrates the four key measures and
their relationship to the batters rankings. Although assessments in the current study are
only based on 5 batters there are some significant differences between (relatively) high and
low skilled batters. Top order Batters (1&2) outperformed their lower skilled counterparts
(middle order 3 & 4 and lower order Batter 5) on all visual measures. Higher skilled batters
initiated the pursuit track of the ball earlier following release, allowing for a greater PTD,
and therefore greater sampling of early ball-flight. These findings are particularly evident
when facing a ‘live’ opponent (see Table 6.2). Results also demonstrated that the presence
of a visual saccade is not necessarily required for successful performance; indeed the
highest skilled Batter (1) within the current study performed the least number of saccades,
while the lowest skilled Batter (5) performed the most (in almost every trial; number of
saccades performed appears highly related to skill level of these developmental batters –
see Figure 6.7). It may be that visual training batters to pick ball up earlier from the
moment of release may decrease the number and presence of visual saccades, in the first
instance. However, it may be that as players progress through the developmental pathways
that require them to face bowling of higher speeds, earlier tracking allows faster prediction
of bounce point under greater temporal demand. It could be speculatively suggested that
the top order players had developed their ability to initiate pursuit tracking earlier as a
result of being exposed to faster bowlers for greater periods of time and as a consequence
of performing in adult competitions alongside their commitments with the school team.
This potentially crucial idea clearly requires further empirical testing.
Chapter 6 – Visual strategies under distinct practice task constraints
127
6.6. Conclusion
Both group and individual interpretations of the data outlined above suggest that
significant and critical differences may exist between visual search strategies when facing
bowlers and ball machines. Based on findings of the current study, it is therefore suggested
that large volumes of practice under artificial task constraints (see Chapter 5) may have
influenced the interpretations made in previous research. Findings suggest that
understanding of the specific role of visual saccades and their relationship to pursuit
tracking strategies in fast ball sports are currently limited. Here, batters were, over multiple
trials, able to track the ball for an adequate period of ball-flight to negate the use of visual
saccades to ‘catch-up’ with the ball even under greater temporal demand than seen in
previous research. It could be argued that for an expert batter the moderate temporal
demand utilised in previous studies (e.g., ball machine at 25 m·s-1) would not represent a
difficult task, and they may have accrued a large history of practice against such task
constraints heavily influencing previous interpretations (Croft et al., 2010; Land & McLeod,
2000). Further work is needed to assess the visual strategies of highly skilled performers
under similar task constraints studied here, with work focussed on integrating visual search
studies with kinematic information to understand the perception-action process in rich
performance environments (e.g., Panchuk & Vickers, 2006). Future work should continue to
assess performance under both bowler and machine task constraints to further our
understanding of the specific role of visual saccades in skilled performance in fast ball
sports, and ensure that research and practice tasks are representative in their learning
design (see Chapter 4 & 5).
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“Act always so as to increase the number of choices.”
H. v. Foerster (1911-2002)
Chapter 7 – Meta-stability in dynamic interceptive actions
131
Chapter 7 – Meta-stability and emergent performance of dynamic
multi-articular interceptive actions
The following chapter provides evidence for the differences in movement organisation
under changing task constraints. The chapter is a product of the emergent nature of both
the programme of research, and movement organisation under representative practice
conditions. The chapter demonstrates how meta-stability is an important concept for
learning design in sport.
This chapter is based on the following peer-reviewed article:
Pinder, R. A., Davids, K., & Renshaw, I. (2012). Meta-stability and emergent performance of
dynamic multi-articular interceptive actions. Journal of Science and Medicine in Sport.
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7.1. Abstract
Adaptive patterning of human movement is context specific and dependent on interacting
constraints of the performer-environment relationship. Flexibility of skilled behaviour is
predicated on the capacity of performers to move between different states of movement
organization to satisfy dynamic task constraints, previously demonstrated in studies of
visual perception, bimanual coordination, and an interceptive combat task. Meta-stability is
a movement system property that helps performers to remain in a state of relative
coordination with their performance environments, poised between multiple co-existing
states (stable and distinct movement patterns or responses). The aim of this study was to
examine whether meta-stability could be exploited in externally-paced interceptive actions
in fast ball sports, such as cricket. Here we report data on meta-stability in performance of