An Introduction to Applied Cognitive Psychology - David Groome, Anthony Esgate, Michael W. Eysenck (2016)

Chapter 14. Sporting performance, pressure and cognition

Introducing attentional control theory: sport

Michael W. Eysenck and Mark R. Wilson


Pressure is playing for ten dollars when you don’t have a dime in your pocket.

– Lee Trevino

There is a burgeoning literature on the effects of pressure on sport performance (Wilson, 2008, 2012). Pressure is ‘any factor or combination of factors that increases the importance of performing well’ (Baumeister, 1984, p. 610). In sport settings, pressure has been linked to the ego-threatening nature of the competitive environment, and most research has focused on its negative effects on performance. Pressure also affects the individual sportsperson’s physiological functioning, including a systemic stress response influencing endocrine, cardiovascular and muscular systems (Wilson, 2012). In this chapter, however, we will argue that many major effects of pressure are on cognitive functioning. Specifically, we will discuss the role of cognitive biases in mediating the pressure–performance relationship and their influence on momentary state anxiety and subsequent attentional control.

While the effects of pressure on performance have been examined across various sports (Wilson, 2012), much research has been qualitative and somewhat descriptive. Most experimental studies examining the pressure–performance relationship have used self-paced, non-interactive sports tasks (e.g. darts, archery, golf), where performance is easy to measure and the relationship between cognitive functioning and sporting outcomes is more directly observable than in interactive sports (e.g. racquet and team sports). Additionally, self-paced sports are interesting from a cognitive perspective, as they provide sufficient thinking time for worry and attentional distractions to disrupt performance when pressure is raised. These performance disruptions have been colloquially termed ‘choking’.


Figure 14.1 Too messy for a scientific study? Football may be the beautiful game, but it is not ideal for psychological studies of sporting performance, because the performance of an individual player will depend on his teammates and on members of the opposing team. The penalty shoot-out provides a better opportunity to examine how players perform in an individual self-paced task, while sports such as golf and darts involve players making an individual performance which is not directly affected by the performance of others.

Source: copyright Natursports/

Choking has been defined as ‘the occurrence of inferior performance despite striving and incentives for superior performance’ (Baumeister and Showers, 1986, p. 361). This definition suggests that inferior performance via choking occurs when least wanted. However, it is too broad to say all inferior performance is a choke. Indeed, according to Mesagno and Hill (2013, p. 273), choking is ‘an acute and considerable decrease in skill execution and performance when self-expected standards are normally achievable, which is the result of increased anxiety under perceived pressure’. This definition clarifies the need for the drop in performance from expected standards to be significant, and also identifies the mediating role of increased anxiety. A recent fMRI study by Lee and Grafton (2015) found a negative correlation between frontal-motor functional connectivity and choking, suggesting choking is due to inadequate executive control resources in frontal regions. We will discuss the relation ship among pressure, anxiety and attentional control later.

Interestingly, some athletes actually perform better than usual under pressure. While most research has focused on the negative effects of pressure, there is increasing interest in ‘clutch’ performance, defined by Otten (2009, p. 584) as ‘any performance increment or superior performance that occurs under pressure circumstances’. Factors determining whether a given individual will exhibit choking or clutch performance are discussed later. First, we will outline common incorrect assumptions and limitations inherent in the (experimental) research examining the influence of pressure on sporting performance.


Experimental studies examining the pressure–performance relationship have tended to use similar methods. First, two conditions of varying levels of pressure are created: a low-pressure (control) condition and a high-pressure (experimental) condition, where a combination of instructions and feedback is designed to create incentives and evaluative threat (Wilson, 2008). Second, participants report their pre-competitive state anxiety symptoms before performing a block of trials under each condition (in a counterbalanced fashion). The influence of pressure on performance is then assessed by comparing objective measures of performance in each condition (e.g. see Hill et al., 2010 for a review). While findings have been somewhat equivocal, many studies have found that performance is significantly worse in the high-pressure condition (see Wilson, 2012 for a review). There are a number of assumptions inherent within this design that limit our ability to understand the complex relationships between pressure, anxiety and performance (discussed below).


According to conventional wisdom, sporting pressure (e.g. participating in an important competition) almost invariably produces increased anxiety. As predicted, pressure is typically associated with elevated levels of anxiety in sport performers (e.g. Causer et al., 2011; Cooke et al., 2010; Geukes et al., 2013; Williams et al., 2002a; Wilson et al., 2007). These studies have adopted a combination of manipulations (e.g. non-contingent feedback about poor performance, highlighting consequences of poor performance, performing in front of others, etc.) to maximise evaluative threat. However, the association between pressure and anxiety is often smaller than commonly assumed.

For example, Mesagno et al. (2011) compared the effects of several forms of pressure on elite hockey players. Cognitive and somatic anxiety both increased with pressure induced by the presence of an audience or video camera self-presentation and both forms of pressure led to impaired performance. However, pressure induced by performance-contingent monetary incentive did not increase either form of anxiety and was associated with enhanced performance.

The most important reason competitive pressure does not always lead to enhanced anxiety is because there are large individual differences in how such pressure is interpreted (Nieuwenhuys and Oudejans, 2012). We will discuss the role of cognitive biases in influencing an individual’s perceptions of ‘what is at stake’ in detail later.


As mentioned earlier, most research has involved comparing performance under high- and low-pressure conditions. Researchers have typically assumed (explicitly or implicitly) that pressure creates anxiety, leading to impaired performance. These assumptions represent substantial oversimplifications, for two main reasons. First, the pressure produced by a competitive situation typically does not remain constant throughout, as is assumed when comparing low- and high-pressure conditions. Consider a tennis player playing an important competitive match. Some points are much more important than others, and the pressure experienced by a tennis player is likely to vary considerably depending on the importance of any given point (Gonzalez-Diaz et al., 2012). For example, perceived pressure is likely to be much greater if a tennis player is serving at 5–6 down in a final set tie-break than if they are serving at 40–0 in a set they are leading 5 games to 0.

Second, there is the issue of causality. A causal sequence is assumed in which pressure causes anxiety, which causes impaired performance. However, the reality is much more dynamic and interactive and this cannot be determined using blocked conditions where mean values for anxiety and performance are compared. The individual sportsperson’s perceived pressure and anxiety level typically depend in part on whether their current performance is successful or unsuccessful. Thus, the relationship between pressure and sport performance is bi-directional rather than uni-directional: pressure influences performance, but performance also influences perceived pressure.


We have suggested that pressure is not constant and that there is a complex bi-directional relationship between perceived pressure and performance, based on feedback loops relating current performance to desired performance. The first important consideration is the degree to which an individual’s performance over time exhibits independence or dependence: to what extent can we predict an individual’s current performance based on his/her immediately preceding performance? Prediction is only possible provided that performance over trials exhibits dependence; if it exhibits independence, previous success or failure is irrelevant to present performance.

The issue of independence vs dependence is controversial. A study by Gilovich et al. (1985) persuaded many researchers that sport performance exhibits independence. They investigated the notion that successful throws at basketball increase the probability of subsequent successful throws (the ‘hot hand’ effect), and reported the hot hand as a myth. However, re-analysis of their data showed clear evidence of the hot hand (Wadrop, 1995). Subsequent basketball research has found other evidence of the hot hand. Yaari and Eisenmann (2011) analysed free-throw data from the National Basketball Association (NBA) based on over 300,000 attempts. The success rate with the second free throw was higher when preceded by success rather than failure at the first attempt. There is compelling evidence that performance in many sports often exhibits dependence (see Iso-Ahola and Dotson, 2014 for a review).


Figure 14.2 Serving for the match. The pressure might cause most of us to choke under similar circumstances, but it seems to make Serena Williams play better.

Source: copyright Neale Cousland/

The importance of considering individual patterns of performance was shown convincingly by Gonzalez-Diaz et al. (2012), who analysed detailed information from twelve US Open tennis tournaments. When comparing tennis players of similar ability, they found that some performed relatively better on high-pressure points than low-pressure ones across these twelve tournaments, whereas others showed no effect of pressure or exhibited the opposite pattern. Those performing relatively better on high-pressure points generally had greater overall career success than those who did not.

The finding that sport performance often exhibits dependence is of importance with respect to research examining the influence of pressure on sporting performance. The typical paradigm, in which overall performance under low- and high-pressure conditions is compared, is appropriate provided individual performance within each condition exhibits independence. If (as we have seen) dependence is generally found, then much of interest and importance is lost by averaging across all trials in any given condition. Given the existence of dependence in sport performance, it remains to establish the reasons for its existence. As we will see later, some progress has been made in doing precisely that.


The development of expertise leads to several important changes in the nature of processing on most tasks (Eysenck and Keane, 2015). It is often assumed that sport expertise depends initially on explicit or conscious processes and gradually comes to depend on implicit or ‘automatic’ processes (e.g. Masters and Maxwell, 2004, 2008). For example, Beilock and Gray (2012, p. 1474) argued as follows: ‘As learning progresses, information is restructured into “procedures” or “programs”…This new “proceduralised” skill representation does not mandate the same degree of attention and control that was necessary at lower levels of practice.’

Self-focus theories of choking (Beilock and Carr, 2001; Masters, 1992) predict that pressure situations raise anxiety and self-consciousness about performing successfully, which in turn increase the attention paid to skill processes and their step-by-step control. The proposed mechanism of disruption is therefore the effortful allocation of attention to previously automated processes. As Toner and Moran (2014, p. 1) pointed out, these theories argue that ‘any form of conscious involvement during on-line skill execution is likely to prove deleterious to movement and performance proficiency’. According to this theoretical approach, the introduction of an attentionally demanding concurrent task should impair novice sport performance more than that of experts. However, instructions directing participants’ attention towards aspects of skilled performance typically outside the conscious awareness of expert performers should impair their performance more than that of novices.

There is support for both the above predictions across several sports (Beilock and Gray, 2012). However, the finding that instructing expert performers to adopt a skill focus leads to impaired performance does not necessarily mean that this is a major determinant of sub-standard performance under pressure in real-life competitions. Consider the following thought experiment. Suppose expert sportspersons were instructed to close their eyes while performing a motor skill under pressure. That would undoubtedly impair their performance. However, it would not show that sportspersons choke under competitive pressure because they close their eyes! Indeed, research by Oudejans et al. (2011) has revealed that thoughts related to focusing on skill mechanics rarely appear in athletes’ accounts of choking. They asked elite performers in several different athletic events to indicate their thoughts when under high pressure. Only 4.1 per cent of these thoughts related to skill focus, causing the authors to conclude that, ‘Skill-focused attention rarely occurs naturally when athletes perform under pressure’ (Oudejans et al., 2011, p. 70).

The self-focus theoretical approach accounts for many findings in experimental settings, but provides an oversimplified view of expert sport performance, for two reasons. First, it assumes that elite athletes’ performance is fully automatic and, second, it assumes that a self-focus is always detrimental. If experts’ performance is ‘automatic’, we would expect considerable consistency in all motor components when a given action (e.g. dart throwing; driving at golf) is repeated. There is typically reasonably high consistency, but less than expected of a totally automatised skill, with experts exhibiting variability in final posture and earlier movement components (Yarrow et al., 2009). For example, Kenny et al.’s (2008) study of elite golfers’ driving found significant intra-subject variability in swing mechanics (club head velocity) and performance (carry and dispersion).

Additionally, Burke and Yeadon (2009) found that inaccurate throwing by a competitive darts player and a recreational player was due primarily to variations in release timing. Of interest, the competitive player was moreinconsistent than the recreational player with respect to release timing. His performance was significantly more accurate because he used more effective compensatory techniques (e.g. coordinated movements of the shoulder and elbow).

The second limitation reflects the assumption that experts do not flexibly deploy attention to various targets during performance. Even if certain phases of a sporting skill may be relatively automatic, other phases (e.g. planning) will require attention. The findings discussed so far (especially those of Burke and Yeadon, 2009) suggest that expert sport performance involves more than simply running off automatic skills while avoiding the involvement of conscious attention. As Toner and Moran (2014, p. 1) argued persuasively, ‘expert performers in motor domains (e.g. sport, music) can strategically deploy conscious attention to alternate between different modes of bodily awareness … during performance’. For example, Nyberg (2014) showed elite free skiers videos of themselves and asked them to indicate what they were thinking and doing. These skiers adopted a flexible approach: they monitored their rotational velocity while in the air and made conscious motor adjustments if that velocity was not what was intended. More generally, they often changed the focus of attention deliberately to control motor problems.

The preceding discussion has identified some assumptions and limitations in the current state of knowledge and has also alluded to the importance of attentional control in mediating the pressure–performance relationship. The rest of the chapter will build towards a new theory to address these limitations and better explain this complex relationship. This theory shares many predictions with its ‘parent’, attentional control theory (ACT; Eysenck et al., 2007), with respect to the importance of attentional control in explaining how anxiety impairs performance.


The context for the new theory consists of two closely related theories that the first author (with the invaluable assistance of various colleagues) put forward. Processing efficiency theory (PET; Eysenck and Calvo, 1992) was superseded by ACT (Eysenck et al., 2007). In what follows, the emphasis will be on ACT’s most important theoretical assumptions: the totality of the theory is discussed in Eysenck et al. (2007).

A central assumption of ACT is that there is an important distinction between performance effectiveness and processing efficiency. Performance effectiveness is the quality of performance (e.g. the percentage of items correct). In contrast, processing efficiency is based on the relationship between performance effectiveness and the resources used to achieve that performance level. Processing efficiency can be reduced by task-irrelevant thoughts such as worries or performance concerns. A crucial prediction is that anxiety impairs processing efficiency more than performance effectiveness. This occurs because anxious individuals often try to compensate for the negative effects of anxiety on processing efficiency by utilising additional processing resources or effort.

Another central assumption of ACT is that we should distinguish between two attentional systems (Corbetta and Shulman, 2002). One is a goal-directed attentional system used in the top-down control of attention and involving the prefrontal cortex (e.g. the dorsolateral prefrontal cortex). The other attentional system is a stimulus-driven attentional system involved in the bottom-up control of attention. It ‘is recruited during the detection of behaviourally relevant sensory events, particularly when they were salient and unattended’ (Corbetta and Shulman, 2002, pp. 201–202). In essence, anxiety increases the influence of the stimulus-driven attentional system and reduces that of the top-down attentional system. These assumptions have been copied by other theorists (e.g. Sylvester et al., 2012). The change in the balance between the two attentional systems produced by anxiety has various consequences, of which the most important is to increase distractibility from task-irrelevant stimuli.

A final assumption is that many negative effects of anxiety on processing efficiency are mediated by the working memory system (Baddeley, 1986, 2001). The most important component of this working memory system is the central executive. It is an attention-like, domain-free system and is of crucial importance with respect to the top-down attentional system. Miyake et al. (2000) identified three executive functions of the central executive: the inhibition function; the shifting function; and the updating function. The first two are of most relevance to attentional control theory. The inhibition function is concerned with preventing irrelevant stimuli or responses from influencing performance and so is related to resistance to distractibility; it can be regarded as negative attentional control. The shifting function is concerned with the optimal allocation of attention within and between tasks (positive attentional control).

Wilson (2008, 2012) showed very clearly that PET and ACT are both applicable to sport performance. This is unsurprising, given that individuals use the same attentional systems regardless of the task or situation. However, there are various important differences between the research literature on the effects of anxiety on cognitive processing and performance and that on the effects of pressure on sport performance. We will consider these differences before putting forward attentional control theory: sport (ACTS).

Two major factors are much more prominent in research on sport performance than research on cognitive performance. First, there is a major emphasis in the sport literature on the effects of high pressure (vs low pressure) on performance. This is important because individuals’ anxiety and motivational levels are strongly influenced by pressure. Second, sport research often compares and contrasts the performance of expert performers and non-expert ones. This is important because the former have acquired ‘automatic’ response patterns and ways of minimising anxiety under pressure.


In sport research, it has typically been assumed that performers’ anxiety will be greater in high-pressure situations than low-pressure ones. Thus, a theory of sport performance needs to consider factors within individual sportspersons determining the extent to which high pressure creates anxiety. In contrast, the emphasis in research on cognitive performance has been on between-participants’ differences in the level of trait anxiety (a personality dimension).

Performance success and failure are often more obvious and important in high-pressure, competitive sport situations than cognitive tasks. In many sport situations, failure is instantly identifiable (e.g. a short putt is missed; a dart misses the winning double). In addition, sport failure can have great importance (e.g. preventing a professional sportsperson from achieving their life ambition). Thus, an emphasis on reactions to success and failure is of more central importance to a theory of sport performance than one of cognitive performance.

Manipulations of pressure in sport research have direct implications for motivation on the plausible assumption that high pressure typically produces greater motivation than low pressure in sport performers. In contrast, ACT considers mostly indirect effects of motivation (e.g. poor performance often leads to compensatory effort).


The emphasis in sport research on comparing expert and non-expert performers has various implications. First, as mentioned already, expert sport performers typically possess various motor skills that can be performed in a relatively ‘automated’ fashion. As a consequence, the performance of expert performers is often affected much less than that of non-experts by manipulations designed to reduce the available resources of the central executive. For example, using a dual-task situation in which participants are required to perform a cognitively demanding task concurrently with a sport task typically has no adverse effect on expert performance but significantly impairs non-expert performance (e.g. Beilock et al., 2004; Gray, 2004; Koedijker et al., 2011).

In addition, many expert sport performers have devoted thousands of hours to developing their skills (Baker and Young, 2014). Such prolonged practice (and experience of competition) typically leads to the development of cognitive processes and strategies designed to facilitate optimal performance levels. The effects of heightened anxiety on these individuals would be expected to be very different from the experience of the typical participants in mainstream anxiety research (i.e. high trait anxious individuals).



At the risk of over-simplification, there are two central issues to be addressed by any adequate theory of pressure and sport performance. First, there is the issue of how pressure (based on the context and per formance level) influences the individual’s levels of anxiety and motivation. Second, there is the issue of how those levels of anxiety and motivation influence performance. In essence, ACT focuses primarily on the second issue rather than the first, whereas ACTS focuses squarely on both issues.

Three key theoretical assumptions of ACT (discussed earlier) relate to the effects of anxiety on performance and are directly applicable to ACTS. First, it is assumed that anxiety impairs processing efficiency more than performance effectiveness. Second, it is assumed that anxiety reduces the efficiency of the inhibition function (negative attentional control). Third, it is assumed that anxiety reduces the efficiency of the shifting function (positive attentional control).

ACT (and ACTS) emphasise the important role played by attentional control in outstanding performance. An implication is that expert performers should have attentional control superior to that of non-expert ones. In a meta-analysis, Gegenfurtner et al. (2011) compared eye movements of experts and non-experts in several domains (e.g. sport, medicine and transportation). In all these domains, experts had faster first fixations on task-relevant information and fewer fixations on task-irrelevant visual areas, suggestive of more efficient attentional control.


According to ACTS, it will typically be the case for sportspersons that any adverse effects of competitive pressure will be greater on processing efficiency than performance effectiveness. In research on sport performance (across ability levels), processing efficiency has sometimes been assessed by relating performance effectiveness to self-reported effort.

For example, Cañal-Bruland et al. (2010) had novice players throw darts at a target under low- and high-anxiety conditions. Anxiety had no effect on performance accuracy, but participants in the high-anxiety condition reported much greater mental effort. These findings are consistent with the prediction that anxiety impairs processing efficiency more than performance effectiveness.

Wilson et al. (2007) found similar results when assessing putting performance in mid-handicap golfers in low- and high-pressure conditions. Self-reported effort was significantly higher in the high-pressure condition than the low-pressure one, but there were non-significant effects of pressure on performance for low trait anxious performers. Finally, a study by Causer et al. (2011) on shooting per formance of elite shotgun skeet shooters found that performance was worse under high-anxiety (competitive) conditions than low-anxiety ones. Of direct relevance here, retrospective self-reports revealed that the mean level of mental effort expended was significantly greater under anxious than non-anxious conditions. Thus, anxiety impaired processing efficiency more than performance effectiveness.

A self-report measure is simple to obtain but may provide distorted evidence. For example, anxious individuals may exaggerate the amount of effort they used. Therefore it is important also to examine other, more objective measures of processing efficiency. In sport settings, efficiency of movement can be assessed using movement kinematics and muscle activity, and some researchers have examined the effects of anxiety on these processes. For example, Cooke et al. (2010) examined the influence of pressure on novice golf putting performance. These authors found that forearm muscle activity and putter kinematics were less efficient in a pressure, compared with a control, condition and that these changes mediated the pressure-induced drop in performance (Cooke et al., 2010).

It is important to emphasise at this point that competitive pressure often impairs both processing efficiency and performance effectiveness when skilled sportspersons use extra effort to engage in counter productive skill focus. As was discussed earlier, skilled sport performance is typically impaired by skill focus in which the performer activates ‘conscious, explicit, rule-based knowledge … to control the mechanics of [his/her] movements during motor output’ (Masters and Maxwell, 2004, p. 208). In this case, the use of additional processing resources actually impairs performance rather than enhancing it. Thus, we need to consider the precise relationship between the processes necessary for good sport per formance and those activated as a result of the application of additional effort.


Figure 14.3 Aiming for success. While darts may not require supreme physical conditioning, the top players are able to maintain fine motor control when the pressure is on.

Source: copyright © Leo Mason sports photo/Alamy Stock Photo.


According to ACTS, anxiety produced by pressure impairs the efficiency of the inhibition function (negative attentional control). This leads to the prediction that adverse effects of pressure and anxiety on sport performance should often depend on distractibility. Relevant evidence was reported by Oudejans et al. (2011). Elite performers in several different athletic events indicated their thoughts when under high pressure. Of most relevance here, 25.9 per cent of these thoughts related to distraction and the inhibition function and a further 5.78 per cent related to positive monitoring and were loosely related to the shifting function.

In a follow-up experimental study, Englert and Oudejans (2014) asked semi-professional tennis players to serve into a predefined target area under low- and high-anxiety conditions. The negative effects of anxiety on performance were mediated by reported level of distraction but not at all by self-reported skill focus.

So, why might a focus on the mechanics of an action be so disruptive to performance under pressure (e.g. Gray, 2004; Beilock and Gray, 2012; Flegal and Anderson, 2008), and why might this not occur as readily in real competition? The primary mechanism for skill-focused disruption is the interference produced by requiring sportspersons to use conscious control during the performance of mostly implicit, non-conscious skills (Masters and Maxwell, 2004, 2008; Beilock and Gray, 2012). Skill focus involves attending to task-disruptive information, which competes with experts’ stored procedural memories for their motor skills. This competition is not present in non-expert sportspersons and so skill focus does not impair their sport performance.

Accordingly, we might speculatively argue that attending to such task-disruptive, skill-focused information involves (at least in part) inefficiency in the inhibition function. Athletes might not report this skill-focused disruption in their choking experiences in competition, as it may simply be experienced as part of a general sense of distractibility (Oudejans et al., 2011).

An alternative method of assessing the role of inhibition function efficiency in sport performance is by considering individual differences. For example, we would expect the inhibition function to be more efficient in expert than in non-expert performers. Support for this prediction comes from a review of the literature on sporting expertise and attentional control by Memmert (2009). For example, Voss et al. (2010) found that expert athletes surpassed non-athletes in a task assessing susceptibility to distraction.

Kasper et al. (2012) reported evidence suggesting that an efficient inhibition function can facilitate sport performance. They assessed the inhibition function (resistance to distraction) in individuals with no previous experience of playing golf. The participants then performed a putting task. Some were given external focus instructions (e.g. ‘Position the ball between your feet and in front of you’; ‘Accelerate the club head straight through the ball’). Kasper et al. found that accuracy of putting performance was strongly correlated with efficiency of the inhibition function.

A limitation with most research in this area is that the direction of causality cannot be determined: it is unclear whether an efficient inhibition function enhances sport performance or the development of sport expertise enhances the inhibition function. Some of the strongest evidence for the importance of the inhibition function in sport performance therefore comes from a recent study by Derakshan et al. (submitted). They provided recreational tennis players with training in attentional control focusing on the inhibitory function. This training enhanced the players’ subsequent tennis performance, over and above that of a control group (who received similar computer-based training).


Successful vs unsuccessful performance in several sports depends on the duration of the ‘quiet eye’. The term was proposed by Vickers (1996, p. 342), who defined quiet eye as ‘the final fixation on a location that is within 3° of visual angle for a minimum of 100 ms’. Performance in many sports, including archery, darts, golf, football, shooting, ice hockey, and tennis, is more effective when the quiet-eye period is of sufficient length to ensure effective motor programming and online control (Wilson, 2012). For example, Klostermann et al. (2013) experimentally manipulated quiet-eye duration on a throwing task. Accuracy of throwing performance was significantly greater when quiet-eye duration was longer, provided task demands were reasonably high.

Maintaining a steady gaze for a relatively long period of time requires good within-task attentional control (i.e. shifting function) and resistance to distraction (i.e. inhibitory function). Thus, ACTS predicts that anxiety should reduce the duration of the quiet eye and so impair performance. Much evidence supports that contention. For example, Behan and Wilson (2008) manipulated anxiety in a simulated archery task and found that anxiety reduced quiet-eye duration and reduced performance.


Figure 14.4 Eye of the Tiger. But is it a quiet eye? Anxiety has been found to reduce quiet-eye duration and performance, and Tiger Woods may have had a few worries to distract him from his shot.

Source: copyright Tony Bowler/

More direct evidence that quiet-eye duration causally influences sport performance has been obtained from studies involving quiet-eye training. Vine et al. (2011) studied putting performance in elite golfers. Some received quiet-eye training designed to enhance attentional control, while the control group simply received video feedback of their gaze behaviour. The duration of quiet eye prior to the start of the backswing predicted 43 per cent of the overall variance in putting performance. The golfers receiving quiet-eye training holed almost twice as many putts as the non-trained group during the high-pressure session. Finally, trained golfers had longer quiet eye under high pressure than in an initial low-pressure session, whereas control golfers showed the opposite pattern. Thus, quiet-eye duration played a causal role in influencing performance in the laboratory and this also transferred to performance on the course (see also Causer et al., 2011 for similar effects in elite shotgun shooters).

We have discussed how skilled sport performers often have impaired performance when instructed to use skill or internal focus. Not only might this reflect impairment in inhibition of disruptive technique-related cues, but it may also reflect inefficient shifting between cues, which is important even with highly skilled motor actions (Toner and Moran, 2014). It could thus be that instructions to adopt a skill or internal focus disrupt the sequence of attentional fixations that skilled sportspersons have developed over the years. Thus, conscious control produced by skill focus instructions may disrupt conscious attentional processes (i.e. impairing the shifting and/or inhibition function) associated with skilled sport performance in even relatively ‘automatic’ motor skills.

An implication of ACT is that expert sport performers should have a more efficient shifting function than non-expert ones. Castiello and Umiltà (1992) found that professional volleyball players shifted attention faster than controls to cued visual targets. Han et al. (2011) compared starter and non-starter groups of professional baseball and soccer players (the starters were more expert than the non-starters). They used two measures of attentional shifting (perseverative errors on the WCST and the Trail Making Test). The starters exhibited attentional shifting superior to that of the non-starters.

Han et al. (2014) extended their previous study by comparing higher- and lower-ranking baseball players. The two groups did not differ in IQ, but the higher group had significantly fewer perseverative errors than the lower group on the Wisconsin Card Sorting Test. Thus, more successful players showed superior (more flexible) shifting function compared with the less successful ones.


ACTS is more explicit than ACT about (1) the initial determinants of anxiety; (2) the role of feedback loops based on performance failure and errors; (3) the role of motivation in moderating the deployment of effort or processing resources; and (4) the sporadic nature of attentional disruptions in trained sporting performers.


As mentioned previously, the successful creation of heightened anxiety is a crucial issue in sport research. Whereas mainstream psychologists rely on dispositional differences in trait anxiety between participants, sport psychologists manipulate the competitive environment to raise state anxiety. ACTS proposes that whether this increased pressure leads to heightened anxiety depends on how cognitive biases alter the perceived probability and cost of poor performance. This relationship is in turn influenced by fluctuations in the individual sportsperson’s tendency to engage in performance monitoring.

Cognitive biases

Much is known about the effects of anxiety on cognitive processing (Eysenck and Calvo, 1992; Eysenck et al., 2007). Of particular importance are attentional bias and interpretive bias. Attentional bias occurs when an individual attends disproportionately to a threat-related stimulus rather than a neutral one (Bar-Haim et al., 2007). Interpretive bias occurs when an individual interprets an ambiguous situation as threatening. High anxiety is associated with attentional and interpretive biases (Eysenck, 1997; Eysenck et al., 2007) and cognitive bias training can reduce anxiety (MacLeod and Clarke, 2013).

Critically, pressure often (but not invariably) leads to increased anxiety. ACTS suggests the experience of anxiety is determined by whether or not a performer exhibits attentional and/or interpretational biases under competitive pressure. We would expect sportspersons to make more negative interpretations in high-pressure than in low-pressure situations, but the extent and impact of these biases will vary across individuals. An increased attentional bias might cause a performer to pay more attention to threat cues (e.g. difficult challenges ahead, errors they have made, good performance from an opponent) and an interpretive bias might cause a performer to interpret errors as having an impact on how they will perform subsequently. Both are likely to raise the level of competitive anxiety; ‘an unpleasant psychological state in reaction to perceived threat concerning the performance of a task under pressure’ (Cheng et al., 2009, p. 271).

Sportsmen and sportswomen who interpret pressure or competitive situations as non-threatening experience less anxiety and are generally more successful. Consider Walter Hagen, a golfer who won eleven major championships. He expected to make seven mistakes in his average round of golf and interpreted each mistake as follows: ‘When I make a bad shot, I don’t worry about it. I figure it’s just one of the seven.’

Nicholls et al. (2005) asked elite golfers to complete a daily diary. They reported many more stressors during an important competition than at other times, with the most common stressors being physical errors (29.5 per cent), mental errors (24 per cent) and observing an opponent playing well (13 per cent). We would predict that such threat interpretations should be related to inferior performance. Moore et al. (2013) examined the cognitive appraisals of experienced golfers prior to an important competition. Evaluating it as a challenge was associated with superior performance compared with evaluating it as a threat.

There is a further point. It has typically been assumed implicitly that attentional and interpretive biases are independent. However, some evidence indicates that cognitive biases can influence each other. White et al. (2011) found that using a training procedure to increase attentional bias led to increased interpretive bias. Amir et al. (2010) found that training to reduce interpretive bias reduced aspects of attentional bias.

Why is it important to consider interactions between attentional and interpretive biases? One implication is that a training intervention that eliminates one of these cognitive biases (attentional or interpretive) for threat-related stimuli in competitive situations should reduce the other bias even in the absence of training.

From a cognitive perspective, superior sport performance depends in part on the individual sportsperson not having an attentional bias or interpretive bias for threat-related stimuli or situations. More precisely, successful sportspersons may well have opposite cognitive biases (i.e. they attend less than most individuals to threat-related situations and interpret such situations in non-threatening ways). Opposite cognitive biases can be regarded as one specific form of cognitive coping strategy (cognitive processes designed to minimise or eliminate the negative effects of stressful events). These opposite cognitive biases facilitate performance because they reduce the amount of anxiety experienced in pressure situations. This increases the probability that the top-down attentional system will dominate over the bottom-up attentional system.

We saw earlier that Moore et al. (2013) found that expert golfers with no interpretive bias for a forthcoming golf competition performed better than those having an interpretive bias. This study was limited in that the researchers did not allocate golfers to interpretive conditions at random. This limitation was not present in a second study by Moore et al. in the same article. In this study, experienced golfers randomly received challenge or threat instructions before a competitive golf putting task. The challenge group performed better, reported less anxiety, less conscious processing, and had longer quiet-eye durations (reflecting enhanced attentional control).

Hill et al. (2010) compared cognitive biases in elite golfers who frequently choked or excelled under pressure. Those who excelled had more positive cognitions than those who choked: they had increased perceived control, less evaluation apprehension and reduced performance expectations. In contrast, the golfers who choked were highly self-critical of poor performance, and experienced high evaluation apprehension, an inability to control their cognitions and high performance expectations.

Mesagno and Marchant (2013) studied netball shots under low and high pressure with follow-up interviews. Those who excelled had task-focused attention and avoidance cognitive coping strategies (e.g. blocking out distractions and the video cameras; positive self-talk). In contrast, chokers had emotion-focused attention and approach-cognitive coping strategies.

Brooks (2014) argued that how individuals interpret their anxiety in pressured situations is also important. Participants in such situations were instructed to try to calm down or to reappraise their anxiety as excitement. Participants who reappraised anxiety as excitement performed much better.

Other research has focused on different aspects of the interpretation of anxious symptoms. Hanton et al. (2004) conducted semi-structured interviews with elite athletes. When low in self-confidence, they indicated that increased competitive anxiety was perceived as beyond their ability to control and as having a negative effect on performance. When high in self-confidence, in contrast, they felt that increased competitive anxiety could be controlled and was facilitative of performance.

Mellalieu et al. (2006) confirmed that self-confidence was important in determining whether anxious symptoms were perceived as debilitative or facilitative. In addition, facilitative interpretations typically required high levels of self-confidence combined with low levels of anxious symptoms.


Figure 14.5 The greatest? Like many outstanding athletes, Muhammad Ali was supremely self-confident. Studies show that self-confidence helps to direct anxiety towards more positive and facilitative outcomes, as Ali is helpfully explaining here to his opponent Sonny Liston.

Source: copyright © Bettmann/Corbis.


The research by Nicholls et al. (2005) suggests that increased error monitoring plays a significant role in the experience of pressure for sports people. Cognitive neuroscience research supports such a contention. Aarts and Pourtois (2012) used event-related potentials to assess error-related negativity (ERN) in low- and high-anxious individuals as they performed a cognitive task, finding that anxiety selectively disrupted the evaluative component of performance monitoring. A recent meta-analysis (Moser et al., 2013) revealed that anxiety (and especially the worry component of anxiety) was associated with enhanced ERN. The implication is that high-anxious individuals engage in more error monitoring than low-anxious ones. This increased error monitoring may act as a trigger for compensatory processes designed to reactivate goal focus.

The extent to which error monitoring occurs in sport will also likely be influenced by the cognitive biases outlined above. First, performers will be more likely to ‘notice’ physical and mental errors due to an enhanced attentional bias for threat cues. They will, therefore, be more aware of thoughts related to failure, and associated arousal symptoms will become more noticeable. Second, performers will be more likely to interpret any difference from homeostasis (or an ‘ideal’ comparator) as being negative for performance. For example, not only may they be more aware of the mechanics of their movements, but also any differences noted will be perceived as being a problem (whereas we discussed earlier that even elite performers reveal functional variability in their movements). As such, cognitive biases will increase the role of conscious error monitoring, making perceived error detection more likely.

Failure (bi-directional nature of pressure–performance relationship)

One of the most potentially threatening aspects of a pressured sporting situation is failure (moments of poor performance such as missing a short putt or hitting a golf shot into the water). The perception of failure is a critical component of ACTS in terms of understanding how state anxiety might be influenced under pressure. Not only would we expect that failures would often be interpreted by an error-monitoring system as anxiety-provoking, but this mechanism also reveals the bi-directional nature of the pressure–performance relationship: previous performance failure can increase the pressure on subsequent performance attempts. There is considerable support for the contention that failure is threatening from research using cognitive tasks (Eysenck, 1982; Eysenck, 1997; Eysenck and Keane, 2015). Of importance, the adverse effects of failure on internal processes and performance (cognitive and motor) are greater among individuals with anxious personalities (Saltz, 1970; Weinberg, 1978).

In a sport setting, Allen et al. (2013) asked participants to imagine their reactions in the most important competition of the season when performing above their normal level and when playing slightly below their normal level. Anxiety was higher and excitement was lower when participants’ performance was below their normal level (and thus there was increased probability of failure and losing). In addition, reported concentration disruption was greater when performance was poor than when it was good. High anxiety was associated with greater concentration disruption in both conditions, and excitement was associated with less concentration disruption in the poor performance condition only.

Calmeiro et al. (2014) studied the thoughts of elite and non-elite trapshooters during critical periods (poor performance and/or stressful moments) and non-critical periods while engaged in competition. Both groups had fewer thoughts during non-critical periods than during critical ones. An important difference between the elite and non-elite trapshooters is that the former group was more likely to follow negative appraisals with various coping strategies, whereas the latter group often failed to use any cognitive coping strategy.

Perceived costs and probability of performance failure

According to ACTS, heightened error monitoring due to attentional and interpretational biases influences perceptions of threat, leading to the experience of anxiety (e.g. Berenbaum, 2010; Berenbaum et al., 2007). Berenbaum’s two-phase model of worry suggests that anxiety (and its cognitive component, worry) are influenced by the perceived probability and perceived costs of future undesirable outcomes (e.g. Berenbaum, 2010; Berenbaum et al., 2007). In sporting contexts, losing is obviously an undesirable outcome, and the costs of losing are greater in high-pressure situations than low-pressure ones because more is at stake. Equally obviously, the perceived probability of losing increases as a function of the number of failure experiences during a match or competition and decreases as a function of the number of success experiences.

We have seen that negative interpretations often increase anxiety in competitive sport situations. We can also predict that anxiety should increase attentional sensitivity and interpretive bias for failure, meaning that there are bi-directional influences between cognitive biases and anxiety. In essence, anxiety will not necessarily be greater under high-pressure than low-pressure conditions, provided the individual sportsperson does not interpret the high-pressure condition as threatening. This can be achieved in various ways, including the following: (1) specific failures during a competitive event are not interpreted as increasing the probability of losing; (2) high-pressure conditions are not interpreted as meaning that losing would have high costs.

In sum, failure in the course of competition has important effects on sportspersons’ cognitions, leading to increased anxiety, increased task-irrelevant cognitions and more attempts at cognitive coping. These major differences in the reactions to failure and non-failure events further strengthen the argument that sport performance is typically characterised by dependence. The relationship between failure and anxiety is bi-directional in that anxiety can increase negative cognitive reactions to failure.


The adverse effects of anxiety as discussed above typically cause the individual to utilise extra effort or processing resources to compensate for these effects, and so it is important to consider the temporal dynamics of attentional control during sport performance. What is involved resembles the two mechanisms identified by Braver (2012): proactive and reactive control. Proactive control resembles the goal-directed attentional system and is ‘associated with sustained and/or anticipatory activation of lateral PFC [prefrontal cortex], which reflects the active maintenance of task goals. This goal maintenance activity serves as a source of top-down bias’ (Braver, 2012, p. 106).

In contrast, reactive control (which resembles the stimulus-driven attentional system) ‘is reflected in transient activation of lateral PFC, along with a wider network of additional brain regions. This transient activity might reflect the bottom-up reactivation of task goals’ (Braver, 2012, p. 106). There is evidence that anxiety is associated with impaired sustained activation in the brain network associated with proactive control but increased transient activation in the brain network associated with reactive control (Fales et al., 2008).

Jimura et al. (2010) argued that proactive control demands a high level of processing resources because it requires continuous goal maintenance. As a consequence, proactive control is most likely to be maintained over time in individuals who are highly motivated. As predicted, Jimura et al. found that their participants showed more sustained dorsolateral prefrontal activation (reflecting proactive control) when rewards were available than when they were not. This effect was greater in individuals high in reward sensitivity.

Kouneiher et al. (2009) compared the effects of low and high incentive on performance. The medial prefrontal cortex was involved in motivation whereas the lateral prefrontal cortex was involved in selecting behaviours. Motivational processes in the medial prefrontal cortex energised the cascade of top-down control processes in the lateral prefrontal cortex.

As was discussed earlier, increased motivation by no means always enhances the performance of highly skilled sportspersons. This is especially the case when high levels of motivation lead sport experts to invest processing resources in skill focus even though this typically impairs performance (Masters and Maxwell, 2004).


A key assumption within ACT (Eysenck et al., 2007) is that anxiety impairs the efficiency of attentional control. However, an issue not addressed explicitly in that theory is whether this inefficiency is omnipresent (i.e. occurs on every trial) or whether it is sporadic (i.e. occurs on a smallish fraction of trials). In contrast, it is assumed within ACTS that inefficient attentional control is sporadic and is most likely to occur at those points in sport performance associated with the highest levels of anxiety (e.g. immediately after a specific failure; immediately after an opponent has achieved an unexpected specific success).

If sporadic inefficiencies in attentional control are positively correlated with the level of anxiety experienced by sportspersons, we might expect that performance variability would be greater in high-pressure than low-pressure situations. More specifically, while performance most of the time is comparable under low- and high-pressure conditions, sub-standard performance will occur on a greater proportion of trials under high-pressure than low-pressure conditions.

Findings of possible relevance here were reported by Unsworth et al. (2013), who compared individuals differing in attentional control (high vs. low working memory capacity) on several tasks. Every individual’s performance on each trial was placed into five bins, each containing 20 per cent of his/her responses (i.e. top 20 per cent of trials; next 20 per cent of trials; and so on). The two groups did not differ in performance across the four best quartiles. However, the group with poor attentional control performed significantly worse than the one with good attentional control within the worst quintile.

Gray (2004) compared skilled baseball batters trying to hit under baseline and pressure conditions. They had 32 per cent fewer hits in the pressure condition. Of most direct relevance here, they had greater variability in the timing of the ratio of wind-up to swing phases in the pressure condition. Cooke et al. (2010) found that novice golfers holed fewer balls on a putting task when under pressure. Pressure caused an increase in the lateral acceleration of the putter, leading to increased variability in the putter-face angle at the point of contact. Causer et al. (2011) found that in elite shotgun shooters there was significantly greater gun-barrel variability in the horizontal axis in the high-pressure than the low-pressure condition.

Robinson and Tamir (2005) studied the effects of neuroticism (a personality dimension that correlates approximately +.6 –.7 with anxiety: Eysenck and Eysenck, 1985) on performance variability. They assessed performance on several different tasks (e.g. categorisation; Stroop task; go/no-go task; choice reaction time). Neuroticism correlated between +.27 and +.45 with performance variability.

In sum, there is diverse evidence suggesting that anxiety increases performance variability. However, it remains unclear whether such enhanced variability is common. It is also unclear whether any increased performance variability produced by heightened anxiety is due to impaired attentional control.


Our goal in writing this chapter was to provide a theoretical frame-work that might serve as the basis for enhancing our understanding of the ways in which pressure affects sport performance. Thus, ACTS as so far developed cannot be regarded as a fully fledged theory. Another limitation of ACTS is that its emphasis is on explaining the effects of pressure and anxiety on sport performance in terms of cognitive processes. However, we do not believe that cognitive processes are the only ones of relevance. For example, the effects of pressure on sport performance depend in part on physiological processes, especially when very precise motor movements are required for success. Robazza et al. (1998) found that high physiological arousal (indexed by heart rate) impaired performance in elite archers. Vaez Mousavi et al. (2011) found that increased arousal (indexed by skin conductance change) correlated negatively with performance in elite pistol shooters. However, it is entirely possible that impaired performance in these (and other similar) studies was due to interactions between cognitive and physiological processes rather than exclusively to physiological processes.


ACTS represents a development and extension of ACT to make it more directly applicable to sport performance under pressure. The theories overlap substantially in their accounts of the effects of anxiety on performance. The main difference is that ACTS focuses much more than ACT on the factors jointly determining an individual’s anxiety level in pressured situations. ACTS can be regarded as complementary (rather than antagonistic) to other theories in the area of pressure and sport performance. The evidence available to date has provided support for most of ACTS’ main theoretical assumptions and suggests it would be worthwhile to test the theory more thoroughly.

A central theme of ACTS is that there are dynamic interactions between competitive pressure and sport performance. As a consequence, it is important to adopt a microanalytic approach rather than the conventional macroanalytic one dominant hitherto. Regardless of the ultimate validity of ACTS, it is indisputable that fine-grain analyses of sport performance under pressure are much more informative than the traditional coarse-grain approach.


•  Pressure often leads to increased anxiety and impaired performance. The relationship between pressure and performance is bi-directional because performance influences perceived pressure.

•  Sport expertise initially depends on explicit or conscious processes but gradually depends more on implicit or automatic processes. However, sport performance rarely becomes fully automatic and typically continues to involve flexibly deployed attention.

•  According to attentional control theory (ACT), we should distinguish between the inhibition function (negative attentional control to prevent irrelevant stimuli and responses influencing performance) and the shifting function (positive attentional control allocating attention within and between tasks). Both functions become less efficient when someone is anxious. The theory also assumes that anxiety impairs processing efficiency more than performance effectiveness.

•  The main assumptions of ACT have been incorporated into attentional control theory: sport (ACTS). These assumptions have been supported in sport research. For example, successful per formance in several sports depends on a relatively long ‘quiet eye’ duration involving attentional control. Anxiety reduces quiet-eye duration and impairs sport performance.

•  As predicted by ACTS, expert sport performers have more efficient inhibition and shifting functions than non-expert ones.

•  According to ACTS, pressure will generally impair performance if it leads to increased anxiety via attentional and interpretive biases for threat-related information (e.g. indications of failure). Sport performers lacking these biases (or even having biases in the opposite direction) typically outperform those possessing the biases. This happens in part because such performers do not interpret high-pressure conditions as meaning that losing would have high costs, nor do they interpret specific failures during competition as increasing the probability of losing.

•  A final assumption of ACTS is that anxiety leads to impaired attentional control sporadically rather than throughout pressured performance. Further research is needed to test this assumption adequately.

•  ACTS emphasises the role of cognitive processes in explaining the effects of anxiety on sport performance. It remains for the future to consider the role of other processes (e.g. physiological) in accounting for anxiety’s effects.


•  Masters, R. (2012). Conscious and unconscious awareness in learning and performance. In S. Murphy (ed), The Oxford handbook of sport and performance. Oxford: Oxford University Press.

•  Moran, A. (2012). Concentration, attention and performance. In S. Murphy (ed), The Oxford handbook of sport and performance. Oxford: Oxford University Press.

•  Wilson, M. R. (2012). Anxiety, attention, the brain, the body, and performance. In S. Murphy (ed), The Oxford handbook of sport and performance. Oxford: Oxford University Press.