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Abstract

Jake plays in a central-midfield role on his soccer team. He plays at the very heart of the field and all moves, both offensive and defensive, bypass Jake. He has a multitude of decisions to make. Jake is young and prone to over arousal and constant errors. He pays equal attention to all the features of the soccer field and is limited in his capacity to process the most relevant information; thus, he often makes the wrong decisions. Coaches, parents, and teammates are upset with Jake; he is physically talented, but under time and event pressure he consistently chooses the wrong course of action. This research-paper addresses the main issues related to Jack’s limited cognitive capacity, which prevents him from making the right moves at the right time. The article addresses the required cognitive skills for proficient decision making and action execution. Several examples from different sports are provided to illustrate the research and theoretical issues.

Outline

Introduction
Nonsport Perspectives on DM
DM in Sport: The Dynamics and Mechanisms
DM in Teams
Affective States and DM
Summary: A Holistic View of DM in Sport

1. Introduction

Decision making (DM) is a process by which an individual, a group, or an organization selects one preferred action from among two or more possible actions within a specific situation. This research-paper focuses mainly, but not conclusively, on the procedures involved in an individual athlete’s DM processes. In sport, the DM process depends largely on the environmental and temporal conditions and rules under which a decision maker operates. These conditions vary with the nature of the sport. For example, in open-type sports such as basketball and soccer the environment is dynamic and consistently changing. The DM process in such sports requires the athlete to make a response selection (RS) based on past, present, and anticipated actions that may change through the course of time. Under such variable environmental conditions, the decision pertains to (i) which type of response/action to choose and (ii) at which time to execute the selected motor response. In contrast, closed skills, such as shooting and archery, which are performed within predetermined environmental constraints, require the decision maker to attend to his or her own proprioceptive sensory signals and decide when in the course of time to implement the decision.

In all sport environments, the DM process consists of three sequential phases: a preparation phase (i.e., visual search, selective attention, and anticipation); DM and RS through information processing (i.e., working long-term memory elaboration); and an action evaluation phase, in which DM and RS may be altered if new information is available at this stage. These stages are illustrated in Fig. 1. This information-processing model assumes that DM occurs under cognitive control. In cases in which the sport environment triggers a response under severe time constraints (i.e., less than 150 ms, which is the required reaction time under cognitive control), DM may occur under self-organized rules. In such circumstances, decisions may come ‘‘naturally, without thinking.’’ Generally, this self-organized DM process is more likely to occur among highly skilled and experienced athletes.

RS is typical to all sports, although the number of internal and environmental stimuli varies. The RS is more challenging when the number of stimuli increases, the temporal conditions shorten, and the athlete’s affective state (i.e., anxiety) becomes less tolerable. The prevailing viewpoint in DM research in sport is that the process occurs within the context of both cognitive and affective systems, which operate simultaneously. The multifaceted perspective of DM in sport situations is presented in this research-paper.

2. Nonsport Perspectives On DM

The traditional approach to DM was developed in the economics/statistics domain. The prescriptive approach viewed the person as an ‘‘outcome’’ seeker who pursues a desired goal. Accordingly, decision makers attempt to maximize a certain ‘‘expected value’’ and they process information in a manner that is targeted toward this ultimate end. The process is governed by comparing one’s alternatives to an ideal solution that in many cases is unknown and speculative. One application of this approach accounted for gambling behaviors, where the unknown product necessitated a probabilistic estimation of utility. Despite their appeal, the prescriptive theoretical normative models were largely unsuccessful because they had limited ecological validity. Since human beings often make decisions that incorporate more considerations than just the expected value of their choice, these components needed to be identified and taken into account.

Cognitive-oriented researchers have examined the capabilities necessary for DM under certain environmental constraints. Also, cognitive capacity was believed to be a major constraint. Studies by DeGroot, Simon, Chase, and others in the early 1970s demonstrated that repeated exposure, experience, and skill level are associated with task-specific capabilities that enable the decision maker to use strategies and integrate information beyond the previously believed cognitive constraints. For example, expert chess players were able to recognize patterns in situations specific to chess in order to overcome limitations in working memory, although their overall cognitive capacities were not superior to those of nonexperts.

Decision Making in Sport Research Paper FIGURE 1 Stages of information processing and decision making in sport.

The naturalistic/descriptive approaches to DM assume that the DM process involves both rational and irrational processes and incorporates personal values, morals, motivation, and emotional level in the DM process. From a naturalistic standpoint, DM consists of defining the problem, seeking alternative solutions (some of which may not be available at a given moment), and then choosing an alternative. According to these approaches, the DM process can be compromised under various conditions, such as those imposing psychological pressure. Several theoretical models, such as image theory, explanation-based theory, recognition-primed DM, and cue retrieval of action, were introduced to account for the human DM process.

Contemporary models within the naturalistic/descriptive approach concentrate on how people make decisions rather than on how they should make decisions. Mechanisms in the form of heuristics are offered to account for the quality of decisions as well as the processes by which decisions are made. These models, which consider the real-world conditions under which decisions are made, have largely replaced the more mechanistic prescriptive models.

The recognition-primed model (RPD) developed by Klein assumed that past experience in similar situations governs the DM process. Klein suggested that DM consists of cue identification, situational goals, alternative action generations, and expectations for possible alterations, all of which can be enhanced with increased experience. The complexity of the situation generates more adjustments or alterations, when time permits. Mental representations, which are established through experience and repetitions, guide the DM process. RPD was found to be valid in chess playing, and this approach is closely related to current concepts and models in sport-related DM processes.

The naturalistic method is a knowledge-driven discourse (i.e., domain-specific declarative and procedural information processes) that according to Lipshitz has not been given its deserved attention. Recent studies emphasize the role that domain and content-specific features play in utilizing decision strategies under varying environmental conditions. In sport, however, knowledge base in the form of expertise and deliberate practice is well documented, thus advancing the naturalistic conceptualization of DM in simple and complex conditions.

3. DM In Sport: The Dynamics And Mechanisms

DM in sport constitutes a set of adaptive behaviors that enable an athlete to operate effectively within the competitive environment under conditions that vary with regard to emotional, mental, and temporal demands. The efficiency of this capacity is influenced by the richness and the variety of perceptions, as well as one’s ability to process information, at a given time. Sport-related tasks are unique in nature and, therefore, encoding relevant information for further processing requires specific perceptual and attentional resources and mechanisms. Depending on the situation at any given moment, a shift between serial and parallel processing of environmental stimuli is required to allow an efficient RS process. Under unconstrained time conditions, information is fed forward for further processing, responses in the form of neural codes are selected and maintained ‘‘on alert,’’ and a preferred action is selected at a given time while others remain activated to some degree until decayed. For example, a golfer may consider the weather and the terrain when selecting a particular club while awaiting his next shot. In contrast, under restricted time constraints the DM process operates under direct perception-action rules, which depend on knowledge structure and schemas stored in long-term memory (LTM). A ‘‘fast break’’ in basketball is a common example of this type of condition.

DM in sport can be viewed as a sequence of decisional processes rather than one RS. This sequence starts at an early stage when the athlete observes his or her opponents on a video film or uses his or her visualization skills. While watching the rival athlete’s or athletes’ style, weaknesses, strengths, and so on, the athlete plans potential actions, which are stored in memory in the form of representations that can be retrieved easily when required. The more the player is aware of the context, the more he or she can anticipate and alter his or her opponent’s action even before stepping into the playing court. While competing, however, the first decision is related to the selection of relevant (and elimination of irrelevant) cues in the environment through the use of different visual strategies. A sequence of events in the performing environment is similar to a ‘‘mental chronometry’’ introduced by Posner, Nissen, and Odgen in which warning signals draw attention until an imperative signal triggers a response. During the preparation period, the athlete attends to the visual field and anticipates upcoming events through the elaboration between working and long-term memory systems. The decisions at the anticipatory stage pertain to what actions the opponent intends to perform and with what probability (e.g., a tennis player anticipates the location of her opponent’s serve). The next decision in the sequence regards what response to select from several alternative responses and when to execute it (where and when to move on the court). This decision has both quality and timing components. Last in the sequence is the decision about response alteration when conditions require or impose a change. This decision relies on a quick modification process, which controls the system’s adaptation level to the changing and dynamic environment (how the player might recover if the serve goes in an unanticipated direction). The success rate of DM depends to a large extent on different mechanisms operating simultaneously and in mutual interaction. To clarify these processes, the main mechanisms affecting DM in sport are introduced next.

3.1. Visual–Spatial Attention

An athlete uses visual–spatial attention to select and discriminate among cues in the playing environment. In many sport settings, a vast array of stimuli, some relevant and some irrelevant, are available to the athlete, and a major aim here is to minimize environmental uncertainty and to enable smooth detection, recognition, recall, and selection of relevant stimuli for higher level processing necessary for RS. The visual system has two main characteristics: fixation, the target toward which visual attention is directed, and duration, the time lag between two shifts in fixation. Scientific evidence indicates that among athletes who play fast ball games, with increases in experience and skill level, the number of eye fixations decreases, whereas fixation duration increases. In other words, more experienced players tend to have fewer shifts in visual–spatial attention.

Visual scanning operates via two possible strategies: the target control strategy, which consists of scanning individual targets in a sequence until one is located that is compatible with a representation stored in LTM, and the context control strategy, which is initiated by memory representations not sensitive to individual objects but rather to a pattern in the visual display. Scanning the environmental stimuli under context control is of greater advantage in open and dynamic settings because it reduces the information-processing load, increases visual attention efficiency, and simplifies the elaboration between working and long-term memory.

Novice players for whom the environment is not fully familiar adopt a target control strategy, whereas with increased experience and skill level a context control strategy becomes more prominent. With the shift from a target to context visual control strategy comes a reduction in eye fixations and an increase in the duration of fixations. In fast ball games, eye fixation location depends on the visual scan sequence. One first fixates on the large features in the display, such as the entire court in racket sports, then moves to the racket (tennis, badminton, and squash) during the later sequence before a RS is made. Such a synthetic strategy enables the player to integrate information from the core sources of reference at once instead of relying on serially analytic chronological order scan, which is time-consuming and inefficient.

Cueing and priming are also key features in the sport realm that are integral in visual attention. When an athlete anticipates that a move will occur with high certainty, his or her response is faster as a consequence of this ‘‘priming a response.’’ When the environment causes greater uncertainty, response time is slower. While visually scanning the stimuli display, late cuing experiments in sport have shown faster reaction times to cue-primed locations than to unusual and unanticipated ones. However, sport-specific studies have shown that the cueing effect depends on the time interval between the warning and imperative stimuli. Reaction times increased with the time delay between the warning and imperative stimuli. However, in dynamic and fast-changing environments, perceptual motor integration works differently from that reported for naive subjects in laboratory situations. As Cave and Bichot claim, the visual system is powerful in detecting and selecting objects in parallel to guide a response, and an object’s location in the display is another criteria for DM. However, once extensively practiced, the probabilities assigned to upcoming events become the knowledge base of the athletes in the form of neural codes, from which they anticipate that events will occur. They thus become better equipped to prepare an appropriate action regardless of the time and space constraints of the environment. An example of this process is a batter in baseball who, through experience in detecting specific cues, learns which particular pitch (e.g., curve ball or fast ball) is most likely to be thrown in a certain situation.

An extensive knowledge base enables the athlete to minimize the costs associated with shifting attention from narrow to large areas. When distracters in the space are cued, they interfere with the identification of a designated target and lead to an increase in reaction time. It is argued that when skilled athletes are exposed to several sources of information at one time, each carries with it a ‘‘probability value’’ for upcoming moves. When an anticipated action carries with it a high probability value, it enables the athlete to process the information efficiently and effortlessly and to subsequently make an adequate decision at the time. In contrast, an athlete who lacks such a capability pays the costs in the form of increased time for processing as well as less appropriate responses.

Finally, despite early beliefs that attention cannot be allocated or split among various sources simultaneously, recent research showed that attention could be divided when two targets were discriminated from each other by a given property or when all stimuli were suddenly presented. In open and dynamic environments such as ball games, anticipatory processes simplify the selection process by allocating visual attention to the more expected location and, at the same time, by using a context control strategy, which leaves other attention channels on alert for possible unexpected imperative stimuli to arrive. In such a manner, the skilled player secures a response with higher probability for success and at the same time leaves room for modification and refinement if circumstances require. These mechanisms help to explain how, for example, an elite basketball player can prepare to shoot a layup and, at the last moment, notice a defender’s position, alter his decision, and pass the ball to a teammate.

3.2. Priming, Attentional Flexibility, and Dimensions of Attention

In the typical sport environment, cues are assigned a probability value in terms of response priming. That is, based on the visual information received, one response is given a higher probability of selection than the others. Responses are primed when their associated stimuli are detected. The primed response provides a ‘‘benefit’’ in terms of the reduced time required to process and select it, whereas the ‘‘cost’’ is that it then takes longer to process and prepare an alternative response for unexpected stimuli. The cost–benefit ratio determines the flexibility of the attention process.

Research using the expert–novice paradigm in sport has shown that the higher the skill level of the athlete, the more one is able to optimize this effect (i.e., to decrease the cost and increase the benefit of the stimuli-associated information processing). Precueing has a positive effect on the RS process because priming increases an athlete’s awareness of upcoming events as well as response readiness. Scientific evidence also suggests that athletes can use automatic and voluntary signal detection modes and can shift between the two when required. With increasing expertise, the athlete acquires both a ‘‘smoother’’ shift and more pronounced flexibility process. In sport, the type and intensity of priming are essential for RS. In competitive situations, athletes choose the priming options that have the highest utility value; that is, they select those that ensure the best chances of triggering the appropriate responses at the proper times.

Because different sports require different attentional processes, no single strategy is ideal for all situations. Some sports (e.g., archery and golf) consist largely of stationary positions, requiring the athlete to focus attention on both internal and external signals. Sports that are more open and dynamic (e.g., basketball and football) require a wider and more flexible attentional style. Moreover, some sports include conditions that require a wide, external attention (e.g., a playmaker in basketball) but others that require a narrow internal attention focus (e.g., shooting a free throw). In these sports, attentional flexibility, which is the ability to alter one’s focus, is a major asset. Neidefer’s model of attentional style accounts for the requirements and shifts of attention needed in various sport contexts. Accordingly, he recognizes two dimensions of attention: (i) width, from wide to narrow, and (ii) direction, from internal to external. Athletes must acquire the skill of adopting the appropriate attentional width and direction that enables them to make effective decisions. Failure to shift attention increases the probability of missing the relevant information needed for optimal DM.

3.3. Anticipatory Mechanisms

The attentional system, which detects the most salient environmental cues, enables the athlete to anticipate events in advance. Repeated responses to game maneuvers enhance the athlete’s perceptual anticipatory capability, which allows for a quick elaboration with the stored program representations in LTM. Fast access to one’s knowledge base becomes possible with only partial information. Because practice in the form of task-specific skill develops ready-access scenarios, these preexisting schemes are available for access even when a limited amount of the information contained in the game situations ‘‘yet to be’’ is captured by the visual system. This anticipatory capability becomes automated and effortless with the development of expertise. For example, an elite volleyball player may notice the movement of just one of six players on the opposing team. However, since she has a complex set of stored schema developed through experience, she is able to predict or anticipate the movements of the remaining players.

Scientific studies of fast ball games have demonstrated the advantage of expert athletes over their novice counterparts in anticipatory decisions. Advanced anticipatory capability reduced the time required for a response, particularly when temporal conditions were extremely short. Anticipatory capability stems from both knowledge structure and advanced visual attention strategies. During the initial stages of scanning the environment for relevant stimuli, anticipatory decisions alter depending on the events taking place at the time. In expert athletes, visual attention is directed to pattern recognition through enduring eye fixations, and fast eye movements occur only under certain environmental constraints. At this stage, attention is simultaneously diverted to several sources of information, including the opponent’s moves, teammates’ locations, and time left on the play clock. Lack of experience and target types of visual scan result in impaired anticipatory capability. At the final stages of the anticipatory process, the novice athlete is engaged in decisions about what and where moves and actions will be performed, whereas the expert makes decisions about what action to perform in response to the opponent’s moves and/or situational demands. A novice wrestler, for example, decides where his opponent might step, whereas the expert selects the move he will use to score a takedown because he ‘‘knows’’ where the opponent’s leg will be. Finally, RS appropriateness depends not only on the cognitive process but also on the proficiency of the motor system and the confidence one has in his or her ability to carry out the response. In the example cited previously, the wrestler must possess sufficient strength, quickness, and confidence for the decision to be effective.

3.4. Memory Representations, Information Delivery, and Knowledge Structure

When an athlete’s knowledge base is rich, environmental distracters have limited impact on the DM process. A limited knowledge base considers these distracters as relevant information, resulting in slowed DM via inhibition of the athlete’s information processing. The seminal studies of DeGroot and Chase and Simon on chess players in the 1960s and 1970s, and follow-up studies on a variety of sports since then, demonstrated how information is encoded, processed, and retrieved as a function of skill level and duration of visual exposure. It was assumed in these studies that recall accuracy following a short exposure to structured and unstructured situations would be a reliable indicator of both the visual attention strategy and the knowledge structure of the participants. Differences were consistent in that more skilled athletes could more accurately recall structured/logical/meaningful positions presented in a relatively short time than could unskilled athletes. The ‘‘chunking hypothesis’’ emerged as an explanation for this advantage in memory representation. This hypothesis rests on the premise that experience in the form of knowledge base and structure enables the player both to capture larger chunks of information in the form of logical patterns and to use these patterns as retrieval paths in a later stage. The chunking hypothesis was used to account for many research results, although recent scientific evidence from dancers and musicians has demonstrated significant memory superiority of skilled performers not only in meaningful information structures but also for memorizing random peaces of information. Thus, the chunking hypothesis has been called into question. In 1995, Ericsson and Kintsch proposed the existence of long-term working memory (LTWM), which may account for unusual memory capability in experts that is task-specific and cannot be generalized to other domains.

Short-term memory appears to have limited influence on experts’ memory capabilities, and working memory was considered a constraining factor because only small amounts of information could be temporarily stored while other information was processed. The concept of LTWM overcomes the notion that memory storage capacity is limited and decays immediately after stimulus onset. The constraint of a limited capacity working memory system seems to be irrelevant in expert memory performance, wherein concurrent activity seems to present limited interference. The new LTWM conceptualizes that when one becomes an expert in a given domain, such as sport, he or she can utilize LTM as a means for expanding short-term working memory.

LTWM develops through the creation of a domain-specific retrieval structure that is used to enhance storage and to maintain information in a more accessible and less interference-prone state. A specific knowledge base is developed through practice, which enables task-specific memory traces to be rapidly and efficiently retrieved. The advantage of LTWM is that it relies on fast encoding and storing processes in a ready retrieved form from LTM. Domain-specific stored information in LTM is used as a retrieval cue that allows one to ‘‘unpack’’ the requested retrieval structure. Although decisions in sport are required, these same memory traces are used to retrieve a response and keep another response alternative on alert for possible and immediate alteration, refinement, or modification. When the stored information is richer and readily accessible, the DM process is smoother and of higher quality.

For a RS process to be efficient, task-specific declarative and procedural knowledge should be structured in a form that allows for easy and fast access. French and McPherson explored the network of conceptual knowledge required to make and execute tactical decisions in the dynamic and changing environments of ball games. The knowledge base consists of memory representations for action profiles, game situation prototypes, competitive scripts, and sport-specific strategies. The knowledge base is structured hierarchically and consists of macro and microlevel routes. The microlevel is managed by the working memory and enables the athlete to attend to ongoing events in the sport environment. Advanced environmental visual scanning and anticipatory capabilities enhance the flow of information for further processing. The macro knowledge level refers to action plan profiles and specific event profiles, which enable the athlete to control and regulate the sensory systems and efficiently select and execute a response.

3.5. Decision Alteration

Several studies incorporating overt (e.g., reaction time, choice reaction time, and accuracy) and covert behaviors (e.g., evoked potentials) simultaneously have indicated that correct and incorrect decisions can be detected in brain activity and described in neural codes. Although not examined in actual competitive situations, these results can be extrapolated into the sport realm. It is suggested that with practice and experience, the athlete incorporates a decision strategy so that he or she can successfully replace one response by another response when the conditions necessitate such an endeavor (i.e., decision alteration). The psychophysiological research clearly indicates that beyond a given neural activation threshold, response alteration is almost impossible. Nevertheless, to reduce the probability of error, the expert athlete holds alternative decisions ‘‘on alert’’ and activates them when an alternative decision is required. Thus, expert athletes, unlike their nonelite counterparts, activate alternative pathways that allow an ‘‘effortless’’ alteration process, which occurs mainly in complex and time-limited conditions.

An explication of decision alteration among experts was presented in Shallice’s ‘‘selection process’’ theory. According to this explanation, two attentional mechanisms control DM and action: contention scheduling (CS) and supervisory attentional system (SAS). The CS is automatic in nature and selects responses for action. The multiple schematic responses are activated and are in mutually inhibitory competition for selection. The final selection of a response is made when one of the alternative decisions is activated beyond a given threshold. The SAS mechanism can access the neural representations in the form of an intention for execution. When the selected response by the CS is proved to be inadequate during the time sequence, SAS modifies, stops, or, if not too late, alters the RS. Research shows conclusively that despite the advanced anticipatory capabilities of the expert athlete, RS is taking place only in the last stage of the process when uncertainty is minimized so that decision alteration can be made without tremendous processing costs. When an alternative response is ready and required, the alteration takes place.

4. DM In Teams

One key advantage that a team has over an individual is a greater supply of human resources available for DM. For example, teams have an advantage over individuals on some measures of information processing (e.g., storage) owing to the extra information processing capabilities provided by multiple team members. Accordingly, in teams, the cognitive labor associated with DM tasks can be distributed over team members. Thus, the team can be considered as a cognitive system in itself. However, the cognitive properties of a team are more than just the sum of the cognitive properties of the team’s constituent members; information processing is affected by the way the team communicates and is coordinated and organized. Consequently, DM efficacy increases to the extent that a team invests effort into establishing strategies for efficient communication, coordination, and organization.

Evidence supports the notion that the more a DM task requires intramember information exchange between team members, the more important are effective communication strategies for performance. However, studies have revealed a tendency for teams that are under time pressure or that are newly formed to discuss only information shared by all team members and not information unique to individual team members. Teams may be subject to DM biases under these conditions. Similarly, studies on crew communication during ship navigation and subsequent use of computer simulations of communication have shown how confirmation bias, a phenomena known to affect DM in individuals, can be accentuated in teams. In 1991, Hutchins showed that even while holding the cognitive properties of individuals constant, groups may display quite different cognitive properties depending on how communication is organized within the group and over time. In summary, DM benefits from the extra resources a team can provide only to the extent that teams factors such as coordination, organization, and communication are taken into account.

5. Affective States AND DM

DM in practice or competitive situations often occurs in the presence of psychological pressure and under conditions that elicit physiological arousal. Therefore, the cognitive process that leads to RS depends on the (i) perceived stress experienced at the time, (ii) coping strategies and self-regulations used to cope with the emotional and physical stress, and (iii) confidence the athlete has in successfully anticipating and selecting a response.

5.1. Perceived Stress and DM

DM is strongly affected by the perceptions of stress (i.e., anxiety) the athlete experiences during competition. Both somatic and cognitive anxieties affect the attention processes, which are vital for the DM to be effective. Under an excessively low-anxiety state, attention is directed internally, which may result in the athlete ignoring or avoiding crucial cues that, under an ideal state, would trigger a response. Under a high anxiety state, attention narrows to a level at which important environmental cues are missed. The detrimental effects of an elevated anxiety level are most prominent in complex, open, and dynamic situations in which a plethora of environmental stimuli are required for effective DM. In closed and explosive type sports, such as Olympic weight lifting, high levels of perceived anxiety are less harmful and, indeed, can even be beneficial.

In line with major theories of cue utilization and attention narrowing under conditions of high perceived anxiety, various studies have shown that DM under low anxiety relies on processing relevant and irrelevant cues alike. Under such conditions, the most important cue is not always primed to trigger a response. Thus, selectivity under such a condition is unfocused and unlimited. Under high-arousal conditions, the opposite is true. That is, an athlete’s attention is narrowed, and DM occurs with too few cues. Under moderate levels of anxiety, attention processes are optimal in that only the most relevant cues are primed for processing and DM. Highly anxious athletes more frequently conduct ‘‘false alarm’’ DM errors, (i.e., make unnecessary decisions), whereas athletes with low arousal levels conduct both false alarms and correct RS. Moderate anxiety levels also limit the problems that many athletes have concerning sustained alertness (i.e., vigilance). Optimal anxiety levels are associated with ‘‘alertness preservation’’ (i.e., high concentration) over a given period of time. Thus, when mental alertness is optimal, it enables one to process the environmental stimuli so that no major stimulus is missed.

A concern arises when ‘‘choking’’ under pressure is evident even in the expert athlete. Two theories account for DM and performance decrements under psychological pressure conditions. Distraction theory claims that once under pressure, shifting attention to task-irrelevant cues results in a move from automatic to conscious attention control, resulting in poor DM. Alternatively, self-focus theory or explicit monitoring theory proposes that pressure causes the performer to pay attention to and control the automaticity of the skill. When a skill is learned and is best executed under automatic control, a shift to intentional control negatively affects DM and motor response processing, resulting in choking. In short, the athlete ‘‘thinks too much.’’ Increased arousal levels result in a narrowing and self-focused attention that shifts away from the relevant cues and ultimately affects the DM process. Furthermore, choking seems to be most evident in tasks that require procedural knowledge and less so in tasks that primarily consists of an explicit knowledge base.

A recent development with regard to the emotions– performance linkage indicates that RS depends on a larger range of emotions than merely cognitive and somatic anxiety. It is the individual’s perceptions of the intensity, pleasantness, and functionality of emotions that determine the specific resources recruited, which generate energy required for optimal DM. When such an emotional state is not experienced, DM, and subsequently performance, may decline. Thus, each individual has a unique emotional-related performance zone within which the probability of making sound decisions and implementing them is highest. In other words, optimal, moderate, and distracted decisions are more probable under different emotion zones for each athlete. These performance zones may overlap to some degree and may change with experience and skill level.

5.2. Coping Strategies and Self-Regulation

When emotions are elevated, coping strategies are used automatically as part of the process of protecting the self. Thus, different emotions produce different hormonal reactions, which trigger certain responses to cope efficiently with current conditions.

The methods athletes use to regulate themselves through the use, misuse, or avoidance of coping strategies determine how emotions are appraised and, by extension, the effectiveness and efficiency of the DM process. Repeated exposure to similar physically and emotionally stressful situations enables an athlete to better tolerate and monitor processes of attention and DM under pressure. Successful self-regulation can be attained and has been proven through the measurement of electroencephalographs, heart rate/pulse, and other physiological responses of the autonomic nervous system. Sustained alertness has been enhanced by avoidance of sleep deprivation; supplementation with nutritional ingredients; elevated physical conditioning; task-related strategies, such as breathing control, relaxation, imagery, and stress inoculation techniques; and conscious control over one’s actions.

Coping has two basic forms: emotion-focused and problem-focused. Both strategies are aimed at changing the individual’s appraisal of the current situation. An appraisal change results in a new meaning given to the situation, and attentional processes change as a result. Therefore, strategies such as avoidance, denial, and distancing imply one’s intention to disengage from interfering stimuli to promote efficient use of visual attention, information processing, and other components necessary for effective DM. In other cases, when emotions are extremely elevated, such strategies may detract from information processing efficiency. Instead, approach strategies may be more

helpful through the use of mental techniques such as relaxation, imagery visualization, and the setting of process and outcome goals. Research has consistently shown that the approach coping strategies are more helpful in monitoring the appraisal process under high perceived pressure, enabling the cognitive system to make decisions more efficiently. The more complex and dynamic the situation, the more beneficial their effect.

5.3. Self-Efficacy and DM

The social cognitive theory, particularly Bandura’s self-efficacy theory, has important implications in sport DM. The beliefs athletes hold in their ability to make the right decision at the right time can be viewed as a coping strategy for handling decisions under competitive conditions. Self-efficacy in the context of sport DM has two dimensions: (i) the confidence one has in successfully anticipating and selecting the right response and (ii) the efficacy one has in executing the selected response. The limited research in this area leaves much to speculation. Current research indicates that self-efficacy in anticipatory decisions differs among novice, intermediate, and expert athletes. In fast ball games, experts display moderate levels of self-efficacy in their anticipatory decisions at early stages of response preparation. After the racquetball contact, anticipatory self-efficacy increases sharply. In novice and intermediate players, anticipatory self-efficacy remains moderate throughout the full duration of the task. These findings appear to support the notion that highly skilled athletes hold several alternative anticipatory decisions on alert under extremely short visual exposure frames, although this alters with the course of time—a pattern not typical of less skilled athletes.

6. Summary: A Holistic View Of DM In Sport

DM in sport is a process of information processing in natural environments that impose unique constraints on the decision makers. When temporal conditions allow, the athlete relies on his or her experience and practice-related knowledge base to locate cues in the environment that are used for anticipatory DM. With experience and skill development, athletes shift from serial to parallel processing and from target to context visual strategies. These processes enable an athlete to identify patterns of essential stimuli, elaborate on them efficiently via stored motor programs, and retrieve a response while keeping other responses on alert for possible decision alteration when needed. This process is efficient when the appropriate attentional style is employed throughout variable environmental constraints. The process of DM is more efficient when the athlete perceives the pressure of the sport environment as facilitative and less efficient when debilitative pressure is perceived. Being in the optimal emotional performance zone and feeling a high sense of efficacy for anticipating decisions and selecting responses increase the probability of making the correct decision. To secure an efficient DM process, the successful athlete employs the appropriate methods and mechanisms that underlie a skillful performance.

References:

Abernethy, B. (2001). Attention. In R. Singer, H. A. Hausenblas, & C. M. Janelle (Eds.), Handbook of sport psychology (pp. 53–85). New York: Wiley.
Bloom, B. S. (1985). Developing talent in young people. New York: Ballantine.
Ericsson, K. A. (1996). The road to excellence: The acquisition of expert performance in arts and sciences, sports and games. Mahwah, NJ: Erlbaum.
Ericsson, K. A., & Charness, N. (1994). Expert performance: Its structure and acquisition. American Psychologist, 49, 725–747.
Ericsson, K. A., & Lehmann, A. C. (1996). Expert and exceptional performance: Evidence of maximal adaptation to task constraints. Annual Review of Psychology, 47, 273–305.
Fisher, A. C. (1984). Sport intelligence. In W. F. Straub, & J. M. Williams (Eds.), Cognitive sport psychology (pp. 42–50). Lansing, NY: Sport Science.
French, K. E., & McPherson, S. L. (1999). Adaptations in response selection processes used during sport competition with increasing age and expertise. International Journal of Sport Psychology, 30, 173–193.
Moran, A. P. (1996). The psychology of concentration in sport performers: A cognitive analysis. East Sussex, UK: Psychology Press.
Ripoll, H. (Ed.) (1991). Information processing and decision making in sport. International Journal of Sport Psychology, 3/4, 187–406.
Starkes, J. L. (2000). The road to expertise: Is practice the only determinant? International Journal of Sport Psychology, 31, 431–451.
Straub, W. F., & Williams, J. M. (Eds.) (1984). Cognitive sport psychology. Lansing, NY: Sport Science.
Tenenbaum, G. (Ed.) (1999). The development of expertise in sport: Nature and nurture [Special issue]. International Journal of Sport Psychology, 2, 113–301.
Tenenbaum, G. (2003). Expert athletes: An integrated approach to decision-making. In J. Starkes, & A. Ericsson (Eds.), Expert performance in sports: Advances in research on sport expertise (pp. 192–218). Champaign, IL: Human Kinetics.
Tenenbaum, G., & Bar-Eli, M. (1993). Decision making in sport: A cognitive perspective. In R. N. Singer, M. Murphey, & L. K. Tennant (Eds.), Handbook on research in sport psychology (pp. 171–192). New York: McMillan.
Tenenbaum, G., & Bar-Eli, M. (1995). Personality and intellectual capabilities in sport psychology. In D. Sakulufske,
& M. Zeidner (Eds.), International handbook on personality and intelligence (pp. 687–710). New York: Plenum.
Tenenbaum, G., Levy-Kolker, N., Bar-Eli, M., & Weinberg, R. (1994). Information recall among skilled and novice athletes: The role of display complexity, attentional resources, visual exposure duration, and expertise. Journal of Sport Psychology, 12, 529–534.
Tenenbaum, G., Levi-Kolker, N., Sade, S. S., Lieberman, D., & Lidor, D. (1996). Anticipation and confidence of decisions related to skilled performance. International Journal of Sport Psychology, 27, 293–307.
Tenenbaum, G., Sar-El, T., & Bar-Eli, M. (2000). Anticipation of ball locations in low and high skill performers: A developmental perspective. Psychology of Sport and Exercise, 1,117–128.
Tenenbaum, G., Tehan, G., Stewart, G., & Christensen, S. (1999). Recalling a floor routine: The effects of skill and age on memory for order. Applied Cognitive Psychology, 13, 101–123.
Williams, A. M., Davids, K., & Williams, J. G. (1999). Visual perception and action in sport. Routledge, London.

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