Agility Cognitive

Cognitive Training for Agility: The Integration Between Perception and Action Tania Spiteri, PhD,1 Fleur McIntyre, PhD,1 Christi Christina na Specos Specos,, MSc,2 and Shawn Myszka, PhD3 1 School of Health Science, The University of Notre Dame Fremantle, Fremantle, Australia; 2Purdue University, West Lafayette, Indiana; and 3Movement Mastery, Minneapolis, Minnesota

ABSTRACT AGILITY IS A KEY FEATURE WITHIN MANY STRENGTH AND CONDITIONING PROGRAMS, WITH THE DEVELOPMENT OF ATHLETE’S PHYSICAL AND TECHNICAL QUALITIES BEING THE PRIMARY FOCUS TO INCREASE PERFORMANCE. HOWEVER, THIS APPROACH IS SOMEWHAT LIMITED AS TRUE RETENTION AND TRANSFER OF PERFORMANCE FROM TRAINING TO SPORT CANNOT BE ACHIEVED UNLESS COACHES DEVELOP AN ATHLETE’S ABILITY TO IDENTIFY RELEVANT STIMULI AND LEARN TO ADAPT MOVEMENT IN RESPONSE TO VARYING CONSTRAINTS. THE PURPOSES OF THIS ARTICLE ARE TO DISCUSS THE CONSTRAINTS ACTING ON THE ATHLETE AND PROVIDE EXAMPLES OF HOW THESE CAN BE MANIPULATED TO ENHANCE INFORMATIONINFORMATIONMOVEMENT COUPLING DURING TRAINING TO IMPROVE THE OVERALL AGILITY PERFORMANCE.

INTRODUCTION

he most common athletic maneuver req requiri uiring ng a com combin binati ation on of physical, technical, and tactical

T

Address correspondence to Dr. Tania Spiteri, [email protected].. [email protected]

attributess is agili attribute agility ty move movement ments, s, performed by athletes to evade and pursuee op su oppo pone nent ntss du duri ring ng sp spor orti ting ng compe co mpetit tition ion (35 (35). ). Exa Examin minat ation ion of performance times during agility protocols (6,30,31) suggests when combining perception and action during agility, the task itself not only becomes more sport specific but elite athletes have the ability to produce a faster performance (8,21). Previous research investigating differences between elite and novice athletes during agility have primarily attributed these differences to an im impr prov oved ed ab abil ilit ityy to id iden enti tify fy task-relevantt cues to produce an accutask-relevan rate and rap apid id mot oto or re resp spo onse (2,8 (2 ,8,2 ,29, 9,42 42,4 ,45) 5).. Fro rom m th this is bo body dy of research, athletes have been classified into one of the two groups; fast thinkers with slow movement, or slow thinkers with fast movement (11), in an attempt to ca cate tego gori rize ze an and d id iden entif tifyy th thee ma main in weakness in one’s performance. Despite this, current training practices have predominant domi nantly ly focu focused sed on the deve developm lopment ent of physi physical cal qualit qualities, ies, techn technique ique (12,44 (12,44)) and strength (15,16), to overcome limitations in perceptual-cognitive qualities. However, this only addresses half of the equation to optimize an athlete’s agility performance. It is well established that an at athle hlete te’s ’s ab abil ilit ityy to id iden enti tify fy ta task sk-releva rel evant nt cue cuess to pro produc ducee an acc accura urate te and rap rapid id mot motor or res respon ponse se (2, (2,8,4 8,42,4 2,45) 5) is a prerequisite for a faster agility

Copyright  Na Nati tion onal al St Stren rengt gth h an and d Co Cond ndit itio ioni ning ng As Asso soci ciati ation on

performan perfor mance ce (3 (37–3 7–39). 9). As a res result ult,, there is an incre increasing asing need to establish tra traini ining ng dri drills lls tha thatt eff effect ective ively ly integrate perception-action coupling to enhance decision making and agility performance. WHAT IS DECISION MAKING?

Decision making is the ability to rapidly id ly an and d ac accu cura rate tely ly id iden enti tify fy ta task sk-relevant cues from a variety of stimuli within the environment, process the incoming information, and select the appropri appr opriate ate resp response onse (37 (37,38). ,38). Ofte Often n referred to as “reading the play,” decision making involves the integration of in inte tern rnal al an and d ex exte tern rnal al fe feed edba back ck between betw een the orga organism nism (the athl athlete) ete),, the task, and the environment, which assists in enabling movement adaptation to occur in response to various stimuli. Depending on the complexity of the task and environmen environmental tal constra st rain ints ts ac acti ting ng on th thee at athl hlet ete, e, th thee percep per ceptua tual-c l-cog ognit nitive ive dem deman and d wil willl vary. Specifically, as agility occurs in a dyn dynami amicc fa fastst-pac paced ed env enviro ironme nment nt there the re are var variou iouss org organi anismi smic, c, tas task, k, and environmental constraints, which KEY WORDS:

agility; decision making; cognitive training; movement development; perception-action coupling; dynamical systems

Stre St reng ngth th an and d Co Cond ndit itio ioni ning ng Jo Jour urna nall | www www.n .nsc sca-s a-scj cj.c .com om

1

Cognitive Training for Agility

have the potential to influence an athlete’s agility performance (Figure 1). ORGANISMIC CONSTRAINTS

Organismic constraints refer to individual characteristics of the athlete and how these affect movement output. Although all organismic constraints have the potential to effect how an athlete executes an agility movement, current research has predominantly focused on investigating physical, technical, and perceptualcognitive qualities to identify the underlying mechanisms that contribute to agility and highlight the integrated nature of these qualities to achieve a faster performance. PHYSICAL QUALITIES

Physical qualities refer to an athlete’s anthropometrics and general motor abilities, which can influence the execution of an agility movement. Agility is underpinned by multiple strength components as a result of the unique demands associated with braking (eccentric strength and stretchshortening cycle ability of the muscle), adopting the appropriate body position during plant phase (isometric strength), and reaccelerating in the new direction (concentric and dynamic strength) (34,38). Previous research has observed weak

correlations between various strength qualities and agility performance (3,41), indicating that the decreased number and degree of directional changes observed in agility tests reduce the amount of muscular involvement (3). To address this limitation, Spiteri et al. (2015) developed a multidirectional agility test comprising 2 directional changes. Despite observing no relationship between strength and agility, athletes who produce a faster agility performance possessed greater lean body mass and lower total body mass (38). Increasing lean mass is achieved through strength training subsequently increasing the muscle cross-sectional area and hypertrophy (5). These findings indicate while strength may not share a strong relationship with overall agility performance, a greater strength capacity is required to execute the movement, and assists with “over-coming” nonmodifiable characteristics (anthropometrics), to positively influencing performance.

impulse production have been identified as critical factors to detect differences in agility performance, with a greater application of force and impulse (37), greater rate of force development (39), and shorter ground contact times (12,38) observed in faster performances. Furthermore, these authors also established that a clear relationship exists between lower-body strength, propulsive force, and impulse application increasing reacceleration out of agility movements (40). These findings demonstrate that although a clear relationship between strength and agility is not observed, an athlete’s ability to use their strength in a complex dynamic movement is critical to coordinate force and impulse application. This is further evident when investigating kinematics during agility maneuvers. Athletes with greater lower-body strength have the capacity to execute the directional change with greater knee and spine flexion (12,37), allowing athletes to adopt a lowerbody position to better direct force application improving propulsive ability.

TECHNICAL QUALITIES

PERCEPTUAL-COGNITIVE QUALITIES

Technical qualities refer to an athlete’s ability to sequence appropriate muscle actions, adopt an appropriate body position, and systemically coordinate force and impulse to produce a fast agility performance. Recently, both force and

Perceptual constraints refer to an athlete’s ability to control their gaze and identify task-relevant cues within the surrounding environment, whereas cognitive constraints refer to an athlete’s

Figure 1. Specific organismic, task, and environmental constraints influencing an individual athlete’s agility performance.

2

VOLUME 0 | NUMBER 0 | MONTH 2017

ability to use their perceptual ability to identify familiar patterns of play and opponent’s movements (6). Cognitive constrains are therefore influenced by an athlete’s prior knowledge of the game, level of concentration, and playing experience. When considering the dynamic control of a task like agility, there is a clear integration between higher perceptualcognitive function and the athlete’s technical and physical qualities to modulate motor behavior in response to the surrounding environment. Specifically, faster performers have demonstrated a greater ability to anticipate opponent’s movements (18), detect kinematic cues from an opponent’s proximal body segments (1), demonstrate more permanent search rates (21,27), and can recognize and recall game situations (21,27), making accurate and efficient sport-specific decisions. Producing a faster initial response to the stimulus enables athletes to prepare and adjust their movement in response through preactivation of the muscles (22,39), increasing the rate of force development and muscular stiffness, resulting in a faster agility performance (19). Despite these findings, it is currently unknown what visual cues and search strategies athletes use to achieve a faster agility performance. TASK CONSTRAINTS

Task constraints vary across numerous sports due to the aim and rules of the activity. Simply put, they influence the control of movement and the effectiveness of movement outcomes. These constraints include the number of players, speed of the movement, object manipulation, and presentation of the stimulus. Typically in sporting environments, movement execution needs to occur rapidly. Although this is directly influenced by an athlete’s organismic constraints, the inability to transfer agility performance from training to game environments is in part due to a lack of replicating game speed (6). Studies have indicated when athletes approach the stimulus at a faster velocity; the stimulus is presented closer to the point of movement execution; or there is a reduced time to respond to successive stimuli, a slower decision-making time is

observed (24,37,38). Failing to replicate the required movement speed and time constraints limits the successful transfer to game environments, as athletes may not be able to adequately adjust movement output at the required game speed. In addition, many sports often require directional changes to occur while simultaneously manipulating equipment. Elite athletes have been found to produce a faster performance, by successfully adjusting their movement output to account for the task constraints (36,43). However, this has only been investigated during a change of direction task under closed preplanned conditions. It can be assumed that manipulating equipment (e.g., bouncing a basketball) during agility will increase the cognitive demand required and therefore increase the constraints placed on the athlete. ENVIRONMENTAL CONSTRAINTS

Environmental constraints refer to the environment in which the sport is played; specifically how the type of stimulus, external distractions, and playing surface influence movement output. Several studies have assessed cognitive function in agility tests by the inclusion of an external sensory stimulus. Stimulus specificity and presentation is crucial, as anticipatory and perceptual expertise appear to be dependent on the type of stimulus used (32). Reacting to a stimulus requires processing based on retrieval of information from stored memory; therefore, greater similarity between the stimulus and sporting environment should decrease response time (10). External distractions including the number of players and atmosphere of the crowd can also impact an athlete’s ability to identify relevant cues during a game. Compared to tennis, basketball and football, have large numbers of athletes on the field and greater crowd engagement, can increase an athlete’s arousal and anxiety (14). According to the inverted-U principle, an athlete will miss relevant stimuli if they experience a low or high state of arousal (14). This will negatively affect an athlete’s ability to identify relevant stimuli resulting in a slower decision-making time and

agility performance. Therefore, manipulating environmental constraints that mirror game situations is critical to improve movement output and the ability to identify task-relevant cues. LIMITATIONS IN CURRENT DECISION-MAKING TRAINING

Current training practices to improve decision-making ability typically occur in sterile laboratory conditions, with confounding factors such as task and environmental constraints being held constant. Various studies have investigated visual search strategies and the influence of knowledge (1,9,17,28), prior experience (21,25), and practice (7,27) on decision making from a testing and training perspective. Findings from this research have limited transfer to sporting environments as they used standardized or simulated conditions that do not elicit true behaviors that occur during game scenarios (23,33). As the transfer of performance into game environments is a key criterion in any training program (41), true improvements in agility performance will not occur unless coaches develop an athlete’s ability to identify relevant stimuli and learn to adapt movement in response to varying constraints. Athletes who can recognize and recall a familiar situation and associate that with a familiar action will typically produce a faster decision-making time (20). From an agility perspective, if an athlete could recall familiar movement solutions to familiar task and environmental constraints, agility performance should improve during competition (e.g., improved retention and transfer). Despite this, a majority of agility training occurs during preplanned drills, limiting athletes’ exposure to adjust their movement strategy to reach the desired goal. This lack of perceptionaction coupling in current training environments is why movement breakdown and injury occur during competition and may explain why athletes cannot replicate the same movement kinematics in competition as then they do in a closed training environment.

Strength and Conditioning Journal | www.nsca-scj.com

3


a variety of directional changes (e.g., backward pedaling, side-shuffling, and forward running) in close succession to evade or pursue opponents. These directional changes vary in their technical and physical demands (38), requiring athletes to constantly adapt and change their movement strategy to produce a fast performance. Exposing athletes to this type of movement variability can be achieved by implementing random practice conditions. Random practice refers to a practice sequence where individual skills or drills are executed in a random order duringthe session (46). For example, performing a 1808 directional change followed by a lateral shuffle requires athletes to modify their biomechanics to execute the movement efficiently. Varying the order of repetition allows athletes to engage and explore the degrees of freedom of each directional change to develop a coordinated and adaptive movement output (46). Essentially, although these types of changes to the typical agility practice scenario may make the session itself appear “messier,” the result will be an athlete who displays more masterful movement solutions under a wider diversity of motor problems in sport. To direct athletes’ engagement with the movement, implementing a whole-part-whole practice methodology, that is, breaking down the directional change into deceleration and re-acceleration phases, can direct athletes’ attention to individual components of the movement before piecing the movement together and executing the whole skill (14). Speed and distance available to execute the movement can also be manipulated to reflect the constraints of the sport. This will alter the physical and technical requirements of each directional change requiring athletes to further adjust and manipulate movement output.

PERCEPTION-ACTION COUPLING AND AGILITY PERFORMANCE

In any given situation, an athlete will be faced with a range of stimuli and movement choices that are directly dependent on how they perceive sensory information from their environment. During agility, perceptual information is gathered from external and internal sources, which is used to direct subsequent movement output. This cyclical relationship between perception and action is termed perception-action or information-movement coupling, and is typically enhanced when there is an inherent link between the stimulus and movement response (4,6). From a practical perspective, this highlights the need to create training environments that expose athletes to context-specific stimuli, enabling them to explore the multiple combinations for a given situation. DETERMINING THE APPROPRIATE “ACTION” TO TRAIN

From a movement development perspective, research has suggested a lower center of gravity, forward lean of torso and shoulders, lateral lean during directional changes, and reduced knee flexion would be advantageous for a faster agility performance (13,32). Agility is a context-specific movement where athletes are required to match the most appropriate movement solution to a movement problem. As a result, movement execution during a game may not reflect what research has described as “optimal” agility technique. Thus, training should not always focus on movement perfection, rather the capability of an athlete to decelerate, adjust their body position, and reaccelerate within their own physical and technical constraints and secondly, the ability to successfully control and coordinate their movement responses to changing task and environmental constraints. When the aim of a training session is to develop movement for agility, it is still important to manipulate practice conditions to replicate the ever-changing nature of sport (Table). Simply put, athletes are often required to perform 4

LINKING ACTION WITH PERCEPTION: DEVELOPMENT OF A PRACTICAL FRAMEWORK


To maximize the transfer of agility performance from training to sport, athletes need to be able to recognize relevant stimuli, assess the situation, and formulate a controlled movement

response that is flexible and adaptive to a changing environment. Progressing from a closed training environment and introducing a nonspecific stimulus (light, voice commands) creates a “controlled reactive” environment and trains an athlete’s ability to recognize and react to a stimulus (Table). This provides athletes with a goal-directed search strategy, requiring basic information processing to identify the stimulus and react accordingly. Although similar practice conditions can be implemented as the closed environment, variability within the training session will predominantly be directed by the stimulus. For example, allocating a different directional change to a colored cone, and verbally cueing which color cone to move to, requires the athlete to visually identify the correct cone and execute the appropriate movement response. This introduces basic perception-action coupling (6,23) requiring athletes to execute a predetermined movement in response to the correct stimulus. Implementing a time constraint, whereby athletes must react and respond urgently to the command, often a requirement during competition, can further alter this drill. Additional modifications to the practice environment can be achieved by introducing temporal and spatial variability. Temporal variability refers to the timing variance of a signal, whereas spatial variability refers to the various directions from which the stimulus can originate. For example, increasing and decreasing the length of time between cueing the stimulus and changing the location of the colored cones after several repetitions changes the temporal and spatial locating of the stimulus, ensuring athletes do not anticipate or become complacent during the drill. Allowing athletes to explore the most appropriate agility movement to execute in response to a given task or environmental constraint during training reflects the dynamic interaction between the movement, an athlete’s perception, and the environment. This enables athletes to explore the biomechanical and perceptual degrees of freedom for a particular agility movement based on a variety of

Table Development of agility performance progressing from movement-orientated (basic) to perception-action coupling (advanced) training using a structured practical framework Training aim

Movement competency and identification of limitations in physical and technical capacity

Create a “controlled reactive setting”: training ability to recognize and respond to a stimulus (reaction)

Allow athletes to explore movement solutions in response to a movement problem

Stimulus type

No stimulus

Introduce nonspecific stimulus (light, whistle, voice commands, and colored cones)

Sport-specific/context-specific stimulus (another team mate) Responding to movement of an object used in the game

Practice conditions

Random practice (order of drill repetition) Part-to-whole practice Manipulate the environment (distance of movement execution) Manipulate the task (speed of movement execution)

Random practice Temporal variability (timing of the stimulus changes) Alter the type of stimulus Time constraints

Random practice Temporal and spatial variability (timing and location of the stimulus) Vary environmental and task constraints

Feedback and cueing

Extrinsic feedback (coach or trainer) KR (outcome of the movement) Cueing: external focus (movement cues)

Extrinsic feedback (start to decrease) Intrinsic feedback (start to increase) KR KP (quality of the movement) Cueing: external focus (movement cues)

Intrinsic feedback KR KP Cueing: external focus (movement and perceptual cues)

Example drill progression

Star drill: emphasis deceleration body control—“stick and hold” on deceleration One repetition forward running One repetition backward pedaling One repetition 458 forward running One repetition lateral shuffle Onerepetition 458 backwardpedaling

Reactive star drill: emphasis deceleration body control—“stick and hold” on reactive deceleration Forward running (blue cone) Backward pedaling (red cone) Lateral shuffle (orange cone) 458 backward pedaling (green cone)

Man-on-man drill (space restricted): athlete must perform a variety of directional changes to bypass a defensive opponent and reach the finish line

*Can manipulate the size of this drill

*Can implement a time constraint, size of the drill, add an object (e.g., basketball), or increase the number *Randomly alternate movement by of defensive or offensive opponents cueing cone color

Environment

KP

5

knowledge of performance; KR

5

knowledge of results.

task and environment constraints to facilitate the development of a coordinated and controlled movement output. This can be achieved during training by identifying a perceptual-cognitive skill to be trained and manipulating a task and/

or environmental constraint to train the perceptual-cognitive skill (Figure 2). For example, athletes are often required to identify relevant kinematic cues from an opponent to determine subsequent movement direction. Using a man-on-

man drill (Table) requires athletes to identify relevant kinematic cues from a defensive opponent (task constraint) and perform multiple directional changes within a confined space (environmental constraint) to bypass the


5


Figure 2. Practical model to develop an effective training environment for agility to aid movement development and exploration in response to changing task and/or environmental constraints.

opponent and reach the finish line. Implementing a time restriction required to reach the finish line, increasing the number of defensive opponents, or performing directional changes with equipment used in the sport adds additional task and environmental constraints increasing the complexity and cognitive demand of the drill. During training, it may be necessary to use directional instructions to help guide athlete’s attention to the perceptual-cognitive skill and place further restrictions on the drill. This can be achieved by implementing the following: If-Then Rule : Assists to develop pattern recognition and an athlete’s ability to recall and transfer movement solutions from training to games. For example, in a man-on-man drill, rules including “if the defensive player moves towards you stepping forward with their right leg, then change direction to your left,” allows athletes to identify when their opponent will be at a disadvantage and rapidly adjust their movement strategy by changing direction to the left. This rule emphasizes basic perception-action coupling, instructing athletes to focus on specific kinematic cues from their opposition and provides a movement solution to a perceived movement problem. Option Generation : Refers to the development of different cognitive choices for the same situation. For example, in a man-on-man drill, instead of always changing direction to the left when the defensive opponent steps forward with their right leg, athletes are instructed to perform a different directional change for the same situation. This allows athletes to explore the most appropriate movement output for a given situation. Initially, verbal instruction of specific kinematic cues 



6


to focus on should be provided by the coach, to reduce the number of options generated, enabling faster choices to be made throughout the drill. MAXIMIZING AGILITY TRAINING: THE ROLE OF FEEDBACK AND CUEING

Verbal cues, instruction, and feedback are essential coaching tools implemented before, during, and after the performance of a skill to direct athlete’s attention to certain components of the movement to improve performance. Feedback is obtained throughout the movement via 2 primary sources, intrinsic and extrinsic sensory information. Intrinsic feedback describes sensory information sourced from inside and outside (proprioception, vision, audition, and smell) the body, whereas extrinsic feedback refers to information provided to the athlete via an outside source (e.g., coach) (14). Knowledge of results (KR) and knowledge of performance (KP) are 2 forms of extrinsic feedback relating to the outcome and quality of the movement, respectively. When a learner is at the initial stage of movement development for agility performance, it is best to increase KR and KP directing an athlete’s attention to errors within the movement. As the athlete learns to adjust, coordinate, and adapt movement, intrinsic feedback becomes the predominant information source. Although extrinsic feedback typically reduces as the learning process continues, it is still important to provide movement and perceptual cues to guide athlete’s attention throughout the movement. Using external cues during agility such as “accelerate away from the opponent

as quick as possible” or “push off the ground as hard as possible” has been shown to increase agility performance by creating an external focus of attention allowing motor behavior to occur automatically (26). Although it is currently unknown as to what specific visual cues and search strategies faster performers use when changing direction, an external focus of attention can still be implemented to guide athlete’s attention to relevant perceptual-cognitive cues. Research has indicated athletes who focus on proximal kinematic cues (trunk and hips) produce a faster decisionmaking time compared with those who focus on distal kinematic cues (arms and legs) (1). Implicitly directing an athlete’s attention to a specific cue during the drill (i.e., hips), whichcan be achieved by placing a colored belt to the opponent’s body or utilizing short cuing words such as “hips” before or during the drill, instructs athletes where to fixate throughout the drill, narrowing their attentional-focus. CONCLUSION

Implementing drills that incorporate task and/or environmental constraints replicates the ever-changing dynamic nature of sport, allowing athletes to explore and adapt movement output in response to situations they will typically encounter during sport. Furthermore, incorporating perception-action coupling, by introducing drills that develop decision making and movement execution simultaneously, strengthens the representation between the stimulus and appropriate movement response resulting in a faster decision and movement execution for a given situation. Using these strategies allows strength and conditioning coaches the opportunity to create a unique training

environment that maximizes the transfer of faster agility performances from training to competition.

Conflicts of Interest and Source of Funding: The authors report no conflicts of interest and no source of funding. Tania Spiteri is

a Lecturer in the School of Health Science (Exercise and Sport Science) at the University of Notre Dame Fremantle.

Fleur McIntyre

is an Associate Professor and Course Coordi- nator of Exercise and Sport Science at the University of Notre Dame Fremantle. Christina Specos is the

Associate Direc- tor of Sports Per- formance at Purdue University.

Shawn Myszka

is the Pro Perfor- mance Director and Content Developer for Movement Mastery.

REFERENCES 1. Aglioti SM, Cesari P, Romani M, and Urgesi C. Action anticipation and motor resonance in elite basketball players. Nat Neurosci 11: 1109–1116, 2008.

2. Bencke J and Zebis MK. The influence of gender on neuromuscular pre-activity during side-cutting. J Electromyo Kinesiol 21: 371–375, 2011. 3. Castillo-Rodrı´guez A, Fernańdez-Garcıá JC, Chinchilla-Minguet JL, and Carnero EA´ . Relationship between muscular strength and sprints with changes of direction. J Strength Cond Res 26: 725–732, 2012.

15. Jullien H, Bisch C, Largouet N, Manouvrier C, Carling CJ, and Amiard V. Does a short period of lower limb strength training improve performance in field-based tests of running and agility in young professional soccer players. J Strength Cond Res 22: 404–411, 2008.

4. Coh M, Jovanovic-Golubovic D, and Brati c M. Motor learning in sport. Phys Ed Sport 2: 45–59, 2004.

16. Keiner M, Sander A, Wirth K, and Schmidtbleicher D. Long term strength training effects on change-of-direction sprint performance. J Strength Cond Res 28: 223–231, 2013.

5. Cormie P, McGuigan MR, and Newton RU. Adaptations in athletic performance after ballistic power versus strength training. Med Sci Sports Exerc 42: 1582–1598, 2010.

17. Lee MJ, Lloyd DG, Lay BS, Bourke PD, and Alderson JA. Effects of different visual stimuli on postures and knee moments during sidestepping. Med Sci Sport Exerc 45: 1740–1748, 2013.

6. Davids K, Renshaw I, and Glazier P. Movement models from sports reveal fundamental insights into coordination processes. Exerc Sport Sci Rev 33: 36– 42, 2005.

18. Lockie RG, Jeffriess MD, McGann TS, Callaghan SJ, and Schultz AB. Planned and reactive agility performance in semiprofessional and amateur basketball players. Int J Sports Physiol Perf 9: 766– 771, 2014.









7. Ericsson KA. Deliberate practice and the modifiability of body and mind: Toward a science of the structure and acquisition of expert and elite performance. Int J Sport Psychol 38, 2007. 8. Farrow D and Abernethy B. Can anticipatory skills be learned through implicit video based perceptual training? J Sport Sci 20: 471–485, 2002. 9. Farrow D, Rendell M, and Gorman A. Enhancing the reality of a visual simulation: Is depth information important. Final Rep Aust Inst Sport 6: 31–35, 2006. 10. Gabbett TJ, Carius J, and Mulvey M. Does improved decision-making ability reduce the physiological demands of gamebased activities in field sport athletes? J Strength Cond Res 22: 2027–2035, 2008.

19. Lo´pez-Segovia M, Marques M, van den Tillaar R, and Gonza´lez-Badillo J. Relationships between vertical jump and full squat power outputs with sprint times in U21 soccer players. J Hum Kinet 30: 135– 144, 2011. 20. Macquet AC. Recognition within the decision-making process: A case study of expert volleyball players. J Appl Sport Psychol 21: 64–79, 2009. 21. Mann DTY, Williams AM, Ward P, and Janelle CM. Perceptual-cognitive expertise in sport: A meta-analysis. J Sport Exerc Psychol 29: 457–478, 2007. 22. McBride JM, McCaulley GO, and Cormie P. Influence of preactivity and eccentric muscle activity on concentric performance during vertical jumping. J Strength Cond Res 22: 750–757, 2008.

11. Gabbett TJ, Kelly JN, and Sheppard JM. Speed, change of direction speed, and reactive agility of rugby league players. J Strength Cond Res 22: 174–181, 2008.

23. McGarry T, Anderson DI, Wallace SA, Hughes MD, and Franks IM. Sport competition as a dynamical self-organizing system. J Sport Sci 20: 771–781, 2002.

12. Green BS, Blake C, and Caulfield BM. A comparison of cutting technique performance in rugby union players. J Strength Cond Res 25: 2668–2680, 2011.

24. McLean SG, Lipfert SW, and van den Bogert AJ. Effect of gender and defensive opponent on the biomechanics of sidestep cutting. Med Sci Sports Exerc 36: 1008– 1016, 2004.

13. Hewit JK, Cronin JB, and Hume PA. Kinematic factors affecting fast and slow straight and change-of-direction acceleration times. J Strength Cond Res 27: 69–75, 2013.

25. Nunez FJ, Ona A, Raya A, and Bilbao A. Differences between expert and novice soccer players when using movement precues to shoot a penalty kick. Percept Mot Skills 108: 139–148, 2009.

14. Janelle CM. Anxiety, arousal and visual attention: A mechanistic account of performance variability. J Sports Sci 20: 237–251, 2002.

26. Porter JM, Nolan RP, Ostrowski EJ, and Wulf G. Directing attention externally enhances agility performance: A qualitative and quantitative analysis of the efficacy of


7


using verbal instructions to focus attention. Front Psychol 1: 216–221, 2010.

change of direction speed. J Sci Med Sport 9: 342–349, 2006.

27. Rendell MA, Farrow D, Masters R, and Plummer N. Implicit practice for technique adaptation in expert performers. Int J Sports Sci Coach 6: 553–566, 2011.

34. Spiteri T, Cochrane JL, Hart NH, Haff GG, and Nimphius S. Effect of strength on plant foot kinetics and kinematics during a change of direction task. Eur J Sport Sci 13: 646–652, 2013.

28. Roca A, Ford PR, McRobert AP,and Williams AM. Identifying the processes underpinning anticipationand decision-makingin a dynamic time-constrained task. Cog Proces 12: 301– 310, 2011. 29. Savelsbergh GJP, Williams AM, Van Der Kamp J, and Ward P. Visual search, anticipation and expertise in soccer goalkeepers. J Sport Sci 20: 279–287, 2002. 30. Serpell BG, Ford M, and Young WB. The development of a new test of agility for rugby league. J Strength Cond Res 24: 3270–3277, 2009. 31. Serpell BG, Young WB, and Ford M. Are the preceptual and decision-making components of agility trainable? A preliminary investigation. J Strength Cond Res 25: 1240–1248, 2011. 32. Sheppard JM and Young WB. Agility literature review: Classifications, training and testing. J Sports Sci 24: 919–932, 2006. 33. Sheppard JM, Young WB, Doyle TL, Sheppard TA, and Newton RU. An evaluation of a new test of reactive agility and its relationship to sprint speed and

8


35. Spiteri T, Cochrane JL, and Nimphius S. Human stimulus reliability during a reactive offensive and defensive agility protocol. J Aus Strength Cond 20: 20– 27, 2012. 36. Spiteri T and Hart NH. Ball inclusion into the AFL agility test can improve change of direction performance. J Aus Strength Cond (Suppl 1): 55–62, 2014. 37. Spiteri T, Hart NH, and Nimphius S. Offensive and defensive agility: A sex comparison of lower body kinematics and ground reaction forces. J Appl Biomech 30: 514–520, 2014. 38. Spiteri T, Newton RU, Binetti M, Hart NH, Sheppard JM, and Nimphius S. Mechanical determinants of faster change of direction and agility performance in female basketball athletes. J Strength Cond Res 29: 2205–2214, 2015. 39. Spiteri T, Newton RU, and Nimphius S. Neuromuscular strategies contributing to faster multidirectional agility performance. J Electromyo Kinesiol 25: 629–636, 2015.

40. Spiteri T and Nimphius S. Relationship between timing variables and plant foot kinetics during change of direction movements. J Aus Strength Cond (Suppl 1): 103–109, 2012. 41. Spiteri T, Nimphius S, Specos C, Hart NH, Sheppard J, and Newton R. The contribution of strength characteristics to change of direction and agility in female basketball athletes. J Strength Cond Res 28: 2415–2423, 2014. 42. Vaeynes R, Lenoir M, Williams AM, and Philippaerts RM. Mechanisms underpinning successful decision making in skilled youth soccer Players: An analysis of visual search behaviours. J Mot Behav 39: 395–408, 2007. 43. Veale JP, Pearce AJ, and Carlson JS. Reliability and validity of a reactive agility test for Australian football. Int J Sports Physiol Perf 5: 239–248, 2010. 44. Wheeler KW and Sayers MG. Modification of agility running technique in reaction to a defender in rugby union. J Sport Sci Med 9: 445–451, 2010. 45. Wulf G, Chiviacowsky S, Schiller E, and A´vila LTG. Frequent external focus feedback enhances motor learning. Front Psychol 1: 190–198, 2010. 46. Wulf G, Shea C, and Lewthwaite R. Motor skill learning and performance: A review of influential factors. Med Ed 44: 75–84, 2010.

Agility Cognitive

Recommend Documents