Sport Performance Judgments From a Social Cognitive Perspective

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    Psychology of Sport and Exercise 7 (2006) 555575

    Sports performance judgments from a social cognitive

    perspective

    Henning Plessner, Thomas Haar

    Psychological Institute, University of Heidelberg, Hauptstrasse 47-51, 69117 Heidelberg, Germany

    Received 2 August 2005; received in revised form 22 March 2006; accepted 24 March 2006

    Available online 8 June 2006

    Abstract

    Objective: Judging ones own or others performance is a central task for most people involved in

    competitive sportseither as athletes, coaches, referees, or spectators. Social cognition is the general study

    of how people make sense of other people and themselves on the basis of an information processing

    framework. This paper presents a social-cognitive overview of empirical work on judging sport

    performance. It follows the basic steps of social information processing (i.e., perception, encoding/

    categorization, memory processes, and information integration).Conclusions: Ample anecdotal and empirical evidence indicates that sports performance judgments are at

    least as prone to systematic errors (biases) as other social judgments. Thus, achieving accurate performance

    evaluations can help to improve the quality of decision making on various levels of sport behavior (e.g.,

    referee decisions, strategy choice, team selection). The application of a social cognition approach provides

    insights into the processes that underlie biases in judgments of sport performance and, thus, some hints on

    how to prevent them. In addition, we propose possible future applications of social cognition concepts in

    sports judgment research.

    r 2006 Elsevier Ltd. All rights reserved.

    Keywords: Social cognition and sports; Sports performance judgments; Biases; Information processing

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    1469-0292/$ - see front matterr 2006 Elsevier Ltd. All rights reserved.

    doi:10.1016/j.psychsport.2006.03.007

    Corresponding author. Tel.: +6221 547700; fax: +6221 547745.

    E-mail address: [email protected] (H. Plessner).

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    Introduction

    Judgments of performance are prevalent in competitive sports. For example, the outcome of a

    sport competition can be assessed by either an objective measurement (e.g., time in swimming), anobjective score (e.g., goals in soccer), or a subjective judgment (e.g., points in figure skating).

    According to Stefani (1998), almost a third of all sports that are recognized by the International

    Olympic Committee (IOC) are considered to have a performance rating system in which judging

    plays a major role. But even when sport performance is assessed in an objective way, there is

    often a judgment of athletes performances beyond the objective values. For example, in an

    ambiguous tackling situation, a football referee has to decide whether to award a penalty.

    Similarly, a tennis player may judge her opponents performance during a game in order to choose

    an appropriate strategy, basketball coaches assess the abilities of athletes in order to select the best

    players for a team, and experts at betting agencies evaluate football teams in order to make

    promising stakes.Taken together, it is clear that performance judgments are an inherent part of competitive sport

    behavior. Moreover, people involved in sport typically aim to make accurate judgments, and thus

    avoid the negative outcomes of mistakes. For example, a wrongly awarded penalty can provoke

    unfriendly responses by players and yield a football referees dismissal; the underestimation of a

    tennis players form can lead to the choice of an unsuccessful strategy; the wrong assessment of a

    basketball players abilities can result in a substandard team; and the overestimation of a teams

    strength while making stakes can directly cause the loss of money. Therefore, it is important to

    study how the accuracy of performance judgments in sports can be enhanced.

    It is a well-known fact that judgments of sport performances areat least sometimesbiased.

    For example, in a classic study on group perception, Hastorf and Cantril (1954) studied

    evaluations of an exceptionally rough American football game between two university teams. Aweek after the game, students from each of the universities were asked for their reactions toward

    the game. Among others, they were asked to judge how clean and fair as opposed to dirty and

    rough the game was. The majority of the students from the university that won the game tended to

    evaluate the game as fair (and rough), while the students from the university that lost found the

    game rather dirty and rough. In their explanation of this effect, Hastorf and Cantril (1954)

    focused on the constructive nature of social judgments, wherein judgments of peoples behaviors

    are shaped by observers prior knowledge and values. In principle, this view is shared by the

    modern social cognition approach (Bless, Fiedler, & Strack, 2004; Fiske & Taylor, 1991) that

    provides the theoretical framework for our view on judgments of sports performance.

    Judgments of sports performance are typically concerned with one of three judgmentaldimensions: (a) inevaluative judgments, performance is judged on a goodbad scale (e.g., Roger

    Federer is the best tennis player ever); (b) injudgments of identification, people judge whether the

    when condition of a certain rule is present (e.g., recognizing a foul play as a prerequisite of

    awarding a free-kick); (c) in judgments of cause (causal attributions), people make judgments

    about the contribution of potential factors that led to certain outcomes (e.g., Federer won the

    match because his play is more sophisticated than his opponents). For pragmatic reasons, this

    article is confined to research on evaluative judgments and judgments of identification. Recent

    overviews concerning causal attributions in sports have been provided elsewhere, for example, by

    Biddle, Hanrahan, and Sellars (2001) and Rees, Ingledew, and Hardy (2005).

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    The majority of studies about evaluative judgments and judgments of identification in sports

    that are available so far are concerned with decisions by sport officials (e.g., referees, umpires,

    judges, linesmen). The reason for this is that their decisions are (or should be) mainly determined

    by their judgments, and many are more or less observable. This does not hold for other groupsinvolved in sports. For example, athletes are most likely to take the consequences of their

    decisions into account when making decisions. Accordingly, decisions by athletes have been

    studied on the basis of a general decision-making approach (e.g., Tenenbaum & Bar-Eli, 1993)

    rather than on a social cognition approach.

    The social cognition perspective

    Social cognition research is concerned with the social knowledge and the cognitive processes

    that are involved when individuals construct their subjective reality; it is the study of how peoplemake sense of other people and themselves (Fiske & Taylor, 1991). Social cognition follows an

    information processing framework and, thus, investigates how social information is perceived,

    encoded, transferred to and recalled from memory, and what processes are involved when people

    make judgments, attributions, and decisions (Bless et al., 2004). In an effort to understand social

    information processing, social cognition researchers have identified quite a number of systematic

    errors (biases) in social judgments. For example, Funder (2003) counted 39 different biases that

    are reported in the social cognition literature (e.g., confirmation bias, halo effect, fundamental

    attribution error). Given the assumption that judging sport performances follows the general

    principles of social judgments (e.g., Gilovich, 1984a; Plessner, 2005), one can expect these biases

    to occur in the sport domain as well. The study of biases and their underlying processes can, thus,

    help to develop ideas about how accuracy in judgments of sport performances can be improved.Bless et al. (2004) introduced a sequence of information processing as a framework for the

    analysis of social judgments (see Fig. 1). It differentiates between several subtasks or steps of

    information processing that link an observable input (e.g., a tackle in football) to a persons overt

    behavior (e.g., a referee sending a player off the field). At first, a stimulus has to be perceived (e.g.,

    the referee needs to attend to the tackle situation). Next, the perceived stimulus is encoded and

    given meaning (e.g., it is categorized as a forbidden attack on the opponent). This second step

    relies heavily on prior knowledge (e.g., the referee must retrieve the decision criteria for forbidden

    tackles from memory). In addition, the encoded episode will be stored (automatically) in memory

    and may influence future judgments, just as retrieved episodic memories influence current

    processing (e.g., the referee remembers that the attacking player has been warned before). In afinal step, the perceived and encoded information is put together with the retrieved memories and

    other information that is available or inferred, and is integrated into a judgment that is expressed

    as a decision (e.g., awarding a free-kick and sending the attacking player off). When this

    framework is applied to the judgment of sport performance, it becomes obvious that an erroneous

    decision can stem from smaller errors or incorrect information from different steps of information

    processing (Plessner, 2005; Plessner & Raab, 1999). For example, a referees erroneous decision to

    send off a player can be caused by his misperception that the player hit his opponents leg instead

    of the ball, or by the false memory that the player has persistently infringed the rules of the game

    before this situation.

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    The different sources of error in the information processing steps of sport performance

    judgment was illustrated, for example, by Plessner (1999). In this study, expectancy effects in

    gymnastic judging were attributed to either categorization processes or information integration

    processes, depending on the social judgment situation. This was possible by using gymnastic

    judges written protocols as an online measurement of cognitive processes that allows for the

    differentiation between these steps.

    In this paper, we present an overview of empirical work that investigates biases in judgments ofsport performances from a social cognitive perspective. Our overview is structured according to

    the steps of (1) perception, (2) categorization, (3) memory processes, and (4) information

    integration. Most authors do not explicitly relate their work to these steps, therefore we have

    categorized these studies according to what we considered the main focus of investigation (see

    Table 1). Additionally, we differentiate between work that is concerned with localor withglobal

    judgments. Local judgments are judgments about performances that are limited in time and space

    (e.g., Roger Federer played this ball brilliantly). Global judgments, on the other hand, are

    concerned with performances in a more extended period of time (e.g., Roger Federer is the best

    tennis player of the last four years). Whereas local judgments in sports are typically concerned

    with episodes during a competition or with the performance within one competition orcompetitive unit, global judgments typically go beyond the observation of a performance in one

    competition. Furthermore, global judgments tend to be more dispositional (e.g., referring to traits

    or abilities) than local judgments (e.g., referring to features of the situation).1 Local and global

    judgments should be understood as categories with a rather fuzzy boundary between them rather

    than dichotomous. However, as will be evident from our overview, this distinction influences the

    different aspects of social information processing that have been addressed in the literature on

    judgments of sport performance.

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    memory, organized knowledge

    (the laws of the game, prior episodes with the attacking player)

    categorization

    (as a foul)

    information integration

    (assessing the severity)

    perception

    (attending to the tackle)

    behavioral response

    (free kick and red card)

    stimulus events

    (a players tackle)

    Fig. 1. The sequence of social information processing (Bless et al., 2004) applied to the example of a football referees

    decision task.

    1For a similar distinction see, for example, Warr and Knapper (1968).

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    Perception

    Local judgments

    If a judgment of performance is intended to mirror the true performance of an athlete,

    performance must first be perceived accurately, so that the relevant information can be fed

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    Table 1

    Empirical work on biases in judgments of sport performance by steps of information processing (main focus)

    Local judgments Global judgments

    Perception Distorted visual input(Baldo et al., 2002; Ford

    et al., 1995; Ford et al., 1997; Helsen et al.,

    2006; Oudejans et al., 2000, 2005; Plessner &

    Schallies, 2005)

    Sampling bias (Fizel & Ditri, 1996;

    Plessner et al., 2001)

    Categorization Influence of uniforms color(Frank & Gilovich,

    1988; Tiryaki, 2005)

    Influence of stereotypes (Eccles et al.,

    2000; Freeman, 1988; Jacobs & Eccles,

    1992)

    Order effect (Ansorge et al., 1978; Plessner,

    1999; Scheer, 1973; Scheer & Ansorge, 1975,

    1979; Wilson, 1977)

    Influence of body language and clothing

    (Greenlees, Greenlees, Buscombe et al.,

    2005; Greenless, Bradley et al., 2005)

    Reputation bias (Findlay & Ste-Marie, 2004;

    Jones et al., 2002; Rainey et al., 1989)

    Influence of stereotypes(Coulomb-Cabagno et

    al., 2005; Souchon et al., 2004; Stone et al.,

    1997)

    Memory processes Prior processing effect (Ste-Marie, 2003; Ste-

    Marie & Lee, 1991: Ste-Marie & Valiquette,

    1996; Ste-Marie et al., 2001)

    Sampling bias (Unkelbach et al., 2006)

    Constructive memory illusions (Walther et al.,

    2002)

    Availability heuristic (Young & French,

    1998)

    Information

    integration

    Hot hand phenomenon (Burns, 2004; Gilovich

    et al., 1985)

    Sophomore slump (Gilovich, 1984b;

    Taylor & Cuave, 1994)

    Home bias (Balmer et al., 2005; Nevill et al.,2002; Sutter & Kocher, 2004)

    Thinking too much (Halberstadt &Levine, 1999)

    Sequential effect (Brand et al., 2006; Damisch

    et al., 2006; Plessner & Betsch, 2001)

    Ingroup favoritism and international bias

    (Ansorge & Scheer, 1988; de Fiore & Kramer,

    1982; Hastorf & Cantril, 1954; Lehman &

    Reifman, 1987; Mohr & Larsen, 1998; Ste-

    Marie, 1996; Seltzer & Glass, 1991; Snibbe et

    al., 2003; Sumner & Mobley, 1981; Whissel et

    al. 1993)

    Norms and conformity (Rainey & Larsen,

    1988; Rainey et al., 1993; Scheer et al., 1983;Vanden Auweele et al., 2004; Wanderer, 1987)

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    into the processing system. Therefore, it is important to take a look at the information a judge

    attends to before he or she evaluates a performance or makes decisions about rule

    applications. Ideally, all stimuli that are relevant for judging a performance are processed.

    However, because the human capacity to process information is limited, a judge needs to selectwhich stimuli should undergo further processing. At best, judges know how to allocate their

    attention. For instance, expert judges in gymnastics have been shown to differ from novices in

    their visual search strategies (Bard, Fleury, Carrie` re, & Halle , 1980). By and large, this research

    shows that expert judges in sports develop effective anticipatory strategies that help to improve

    their decision making (e.g., MacMahon & Ste-Marie, 2002; Paull & Glencross, 1997; Ste-Marie,

    1999, 2000).

    The influence of perceptual processes on judgment and decision making in sports is also evident

    in a number of studies concerning the visual perspective from which the athletes behavior is

    observed. For example, Schmidt and Bloch (1980) found in a case study that many differences in

    the evaluation of critical basketball situations between referees, coaches, and observers are due totheir different viewing positions. It is therefore important to understand if expert judges in sports

    are aware of the potential biasing influence of their viewing position and are able to control for it.

    The results of a number of studies on this issue provide a rather pessimistic answer. For example,

    Oudejans et al. (2000) found that the high percentage of assistant referees errors in offside

    decisions in football mainly reflects their viewing position. Although they should stand in line with

    the last defender, on average they are positioned too far behind. By considering the retinal images

    of referees, Oudejans et al. (2000) predicted a specific relation of frequencies in different types of

    errors (wrongly indicating offside vs. not indicating an actual offside) depending on the area of

    attack (near vs. far from the assistant referee and inside or outside the defender). In an analysis of

    several videotaped matches, this prediction was confirmed, thus demonstrating that assistant

    referees decisions directly reflect the situations as they are projected on their retinas (see alsoBaldo, Ranvaud, & Morya, 2002; Helsen, Gilis, & Weston, 2006; Oudejans et al., 2005). In a

    similar vein, Plessner and Schallies (2005) found gymnastic judges evaluations of the cross on

    ringsa static strength elementto be influenced by their viewing position (see also Ford,

    Goodwin, & Richardson, 1995, on ball-strike judgments in baseball). In order to prevent biases

    that stem from imperfect viewing positions, one can, for example, calculate positions that fulfill

    most of the perceptual demands of a judgment task and fix these positions (e.g., Ford, Gallagher,

    Lacy, Bridwell, & Goodwin, 1997). Another possibility is to provide judges with proper feedback

    training, which has been found to help overcoming perceptual limitations, for example, in the

    domain of in/out decisions in tennis (Jendrusch, 2002) and leg-before-wicket judgments in cricket

    (Craven, 1998).

    Global judgments

    When social cognition researchers study perception they do not necessarily investigate the

    actual process of perceiving (e.g., the working of the visual system). More often, they refer to the

    more general influence of the stimulus input on social judgments. According to the cognitive-

    ecological sampling approach to social judgments (Fiedler, 2000), the quality of the stimulus input

    can sufficiently explain many judgment biases that are typically attributed to later stages of social

    information processing, such as illusory correlations and confirmation biases. The sampling

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    approach assumes that most judgments are based on samples of information that are, for

    example, collected from the environment. These samples are virtually never random (Fiedler,

    2000, p. 660) and may, therefore, be biased in many different ways. It has been found for several

    judgment tasks, that people lack the awareness (and the ability) to correct biased samples, andthey, therefore tend to base their judgments directly on the sampled information as if it was drawn

    randomly (e.g., Fiedler, Walther, Freytag, & Plessner, 2002).

    While the viewing position obviously limits the representativeness of an information sample,

    people are even less aware of many other sources that can lead to biased stimulus input. For

    example, Plessner, Hartmann, Hohmann, and Zimmermann (2001) investigated the well-studied

    phenomenon of base-rate neglect2 in the judgment of a football players quality. Their approach

    explained this finding as a sampling error in inductive judgments, resulting from the confusion of

    predictor and criterion sampling in probability judgments (Fiedler, Brinkmann, Betsch, & Wild,

    2000). For example, when given the task to judge the conditional probability of being assigned to

    a doping test after the use of doping measures, it makes a tremendous difference if a sample isdrawn depending on the predictor (using doping) or the criterion (assignment to a test). The latter

    sampling process would lead to an overestimation of the conditional probability (and the

    deterrence effect of doping tests), because the still rather rare criterion event test is

    overrepresented and the large number of people who use doping measures but are not assigned

    to a test are not considered. Plessner et al. (2001) applied this logic to the judgment of a football

    teams probability of winning a game, given a certain player participated in a game. The

    environment they provided was such that the team hardly ever won a game. When participants

    coaches from various team sportssampled information from a record of one hundred games by

    the criterion, the teams success, they overestimated the conditional probability and therefore the

    quality of the player, just because they did not preserve the low environmental base rate of

    victories in their sample; that is, most cases where the team lost and the player participated as wellwere not considered. This bias did not show up when the coaches sampled by the predictor, the

    players participation, which leads in this case to a representative sample of victories and losses

    and therefore to a fair estimate of the conditional probability. However, when interviewed about

    their judgment strategies none of the coaches reported an awareness of the potential sampling

    trap.

    In the world of sports, one can easily imagine several other factors that lead to biased

    samples of performance information, for example, the selective attention of media to successful

    players, or managers attention to absolute as opposed to relative success in the evaluation

    of coaches efficiency (e.g., Fizel & Ditri, 1996). The examples presented in this section

    have demonstrated that biases in the stimulus input are likely to flow over to judgmentsand decisions in sport. Therefore, a careful observation of the information that is perceived

    by a judge can already explain a large number of existing biases in judgments of sport

    performance.

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    2Many studies on probabilistic reasoning (e.g., Bar-Hillel, 1980) demonstrate that information about base rates

    receives less weight than it deserves if people would apply the Bayes theorem which is a rule for revising a prior

    probability (the base rate) into a posterior probability after new data have been observed.

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    Categorization

    Local judgments

    Once information about an athletes performance is perceived, a judge encodes and interprets

    the information by giving it meaning. In order to encode and categorize new information, it must

    be related to prior knowledge stored in memory. For example, a floor routine in gymnastics may

    appear as a random sequence of strange movements to an inexperienced observer. A gymnastic

    expert, on the other hand, will easily be able to recognize several categories of elements that differ

    in difficulty. While prior knowledge about judgment criteria in a sport and adequate

    categorization systems are necessary requirements for accurate performance judgments

    (MacMahon & Ste-Marie, 2002; Paull & Glencross, 1997; Ste-Marie, 1999, 2000), we focus our

    overview on research about bad or inappropriate knowledgethat is, knowledge that has a

    distorting or biasing influence on judges cognitive processes and subsequent decisions (cf.Plessner, 2005).

    It is a widely shared assumption in social cognition that our social knowledge is organized in

    complex structures, such as categories, schema, and scripts, and that these structures are

    interconnected in a so-called associative network (Bless et al., 2004). Which knowledge is applied

    when encoding a stimulus depends, for example, on its accessibility and applicability (Higgins,

    1996). The accessibility of knowledge is affected by the recency and the frequency with which it, or

    an associated structure has been used in the past; it can also be activated (primed) by

    environmental cues. Based on this assumption, Frank and Gilovich (1988) were able to show that

    even culturally shared knowledge that is seemingly irrelevant for a judgment of a performance can

    have an influence on sport decisions. They assumed that in most cultures there is a strong

    association between the color black and aggression. The black uniform of a sports team could,therefore, serve as a prime that automatically activates the concept of aggression, thus, increasing

    its accessibility. In two studies and one experiment, evidence was found that players perceived

    themselves as more aggressive and behaved accordingly when they were dressed in black as

    opposed to other colors. In an additional experiment, Frank and Gilovich (1988) found that

    American football referees were more likely to penalize a team wearing a black uniform than a

    team wearing a white uniform. However, this effect seems not to be valid for all cultures. In a

    study with Turkish football referees, Tiryaki (2005) found no comparable influences of black

    uniforms.

    The encoding of information about sport performances has also been found to be influenced

    by categories that evolve directly from the competitive environment. For example, ingymnastics the fact that gymnastics coaches typically place their gymnasts in rank order from

    poorest at the beginning to best at the end in a team competition leads to different perfor-

    mance expectancies. These expectancies have been found to exert a biasing influence on the

    evaluation of exercises in gymnastics (Ansorge, Scheer, Laub, & Howard, 1978; Scheer, 1973;

    Scheer & Ansorge, 1975, 1979) and synchronized swimming (Wilson, 1977). In an experiment

    following this line of research, Plessner (1999) investigated the cognitive processes underlying

    expectancy effects in gymnastics judging. Among others, he found the categorization of perceived

    value parts (i.e., the attributed difficulty to single gymnastic elements) to be biased by judges

    expectancies.

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    Other sources of expectancies that have been found to influence local judgments of sport

    performance are the reputation of an athlete or a team (Findlay & Ste-Marie, 2004; Jones, Paull,

    & Erskine, 2002; Lehman & Reifman, 1987; Rainey, Larsen, & Stephenson, 1989) and stereotypes

    about gender (Coulomb-Cabagno, Rascle, & Souchon, 2005; Souchon, Coulomb-Cabagno,Traclet, & Rascle, 2004) and race (Stone, Perry, & Darley, 1997). Although these influences have

    been treated in the literature as unwelcome so far, it should be remembered, however, that

    expectancies which mirror true differences can also improve accuracy in complex judgment tasks

    (Jussim, 1991).

    Taken together, the encoding and categorization of a perceived performance has been found to

    be systematically influenced by the activation of various types of prior knowledge, even when this

    knowledge has no performance-relevant value in judging an athletes performance. It is clear that

    these influences increase in likelihood as judging situations increase in ambiguity. However, such

    situations seem to occur quite often in sport competitions. For example, Nevill, Balmer, and

    Williams (2002) asked referees to make assessments for 47 typical incidents taken from an EnglishPremier League match. One of the findings was that none of these challenges resulted in a

    unanimous decision by all qualified referees participating in the study (see also Teipel, Gerisch, &

    Busse, 1983). Therefore, athletes, referees, coaches, and spectators should be aware of potential

    judgment biases via the activation of inappropriate knowledge. Again, (video-based) feedback

    training has been suggested as a measure to improve accuracy in categorization tasks, such as

    recognizing a players offense in football (Helsen & Bultynck, 2004; Mascarenhas, OHare, &

    Plessner, 2006).

    Global judgments

    While gender stereotypes can already have an influence on local evaluations of aggressivebehaviorsfor example, Souchon et al. (2004) found that female handball players were granted

    more penalties in similar situations than male playerstheir influence can be even more dramatic

    when it comes to the global evaluation of boys and girls abilities in sports. For example, the

    work by Eccles and colleagues (Eccles, Freedman-Doan, Frome, Jacobs, & Yoon, 2000; Jacobs &

    Eccles, 1992) showed that parents beliefs and stereotypes influence their judgments and

    expectations of their children. Among others, it has been found that mothers who endorsed the

    traditional gender-role stereotyped belief that boys are naturally better in sports than girls

    distorted the perception of their childs competence in sports in the gender-role stereotyped

    direction. That is, if they were talking about a female child, their perception of their childs ability

    was lower than what would have been predicted with more objective criteria (i.e., teachersratings). In addition, these expectancies were found to affect the opportunities that parents give

    their children to develop sport skills and, thus, not only childrens self-perceptions but also, as a

    self-fulfilling prophecy (Merton, 1948), their actual performances. The influence of stereotypes on

    global judgments may be even more pronounced when sports are involved that have a stronger

    association with typical male rather than typical female characteristics, such as boxing or

    bodybuilding (e.g., Freeman, 1988).

    As mentioned, an advantage of categorical thinking is that the application of an adequate

    category can be a helpful guide in adjusting peoples behavior to the behavior of their interaction

    partners (Fiske & Taylor, 1991). Categories, such as a person schema, typically include knowledge

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    that allows inferences beyond the information given in a certain situation. For example, when we

    play a tennis match against an opponent for the first time, the prior information that she belongs

    to the category of serve-and-volley players allows us to predict what she will do after her service

    and to take adequate counter-measures in order to attain our goal of winning the match (e.g., toconcentrate on a sharp return). Accordingly, just as in general people seek actively for

    information that allows them to form accurate impressions of other people when they engage in

    social interactions, it can be assumed for competitions in sports that athletes look for cues that

    facilitate appropriate categorizations of their opponents. Therefore, it is surprising that the

    impression formation process among athletes has received little attention in the corresponding

    literature so far. In two recent studies, however, Greenlees and colleagues examined the influence

    of an opponents body language and clothing on the first impressions formed by observers in

    tennis (Greenlees, Buscombe, Thelwell, Holder, & Rimmer, 2005) and in table-tennis (Greenlees,

    Bradley, Holder, & Thelwell, 2005). Body language and clothing were chosen as variables because

    other researchers have suggested that they are important interpersonal cues. While the influence ofclothing is not obvious in both studies, there is strong evidence that body language exerts an

    influence on the impression formation process of athletes even when playing performance is

    viewed. Players that displayed positive body language (e.g., erect posture) were rated, for example,

    as more assertive, competitive, experienced, confident, and fitter than players displaying negative

    body language (e.g., hunched posture). In addition, participants reported higher expectations of

    success against tennis players displaying negative body language than against tennis players

    displaying positive body language (Greenlees, Buscombe et al., 2005). Accordingly, the authors

    argue that the development of performance expectancies in the observation of a players body

    language in the warm-up can directly affect his opponents performance. Although it is evident

    from these studies that body language influences impression formation among athletes beyond the

    directly observed performances, this does not necessarily lead to wrong assessments of anopponents strength. After all, a positive body language can indeed be an indicator of a self-

    confident good tennis player. However, the knowledge of the influence of these cues on an

    opponents impression can also cause an athlete to use them in a strategic or even deceptive way

    (Gilbert & Jamison, 1994; Hackfort & Schlattmann, 2002). Thus, a promising direction for future

    research would be to study the validity of the different categorical cues that athletes use in

    competitions in order to form accurate impressions of their opponents.

    Memory processes

    Local judgments

    While the studies reported so far demonstrate that judgments of performance are potentially

    biased by the activation of general memory structures, there is also some evidence for direct

    memory influences on the judgment of sport performances. Such influences have been studied in

    an impressive series of experiments by Ste-Marie and colleagues (Ste-Marie, 2003; Ste-Marie &

    Lee, 1991; Ste-Marie & Valiquette, 1996; Ste-Marie, Valiquette, & Taylor, 2001). They

    investigated how the memory of prior encounters with an athletes performance can influence

    actual performance judgments. In these experiments, a paradigm was developed that mirrors the

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    warm-up/competition setting in gymnastics. In the first phase of the experiment, judges watched a

    series of gymnasts perform a simple element and decided whether the performance was perfect or

    flawed. The judges task was the same in the second phase that followed, except that the gymnastic

    elements shared a relationship with the items shown in the first phase. Some of the gymnasts wereshown during the second phase with the identical performance as in the first phase (e.g., both

    times perfect), and others were shown with the opposite performance (e.g., first perfect and then

    flawed). In the condition where the performance in the first and second phases differed, perceptual

    judgments were less accurate than in the conditions where performances were the same for both

    phases (Ste-Marie & Lee, 1991). These memory-influenced biases occurred even with a week break

    between the first and second phases (Ste-Marie & Valiquette, 1996) and irrespective of the

    cognitive task the judges had to perform during the first phase (Ste-Marie, 2003). The robustness

    of this effect supports the authors assumption that perceptual judgments, such as in judging

    gymnastics, inevitably rely on retrieval from memory for prior episodes. Thus, the only way to

    avoid these biases would be to prevent judges from seeing the gymnasts perform before acompetition (Ste-Marie & Lee, 1991).

    Prior processing effects are side effects of the rather positive memory feature of enhancing

    perception through automatic learning processes (Jacoby, 1983). A comparable rather negative

    feature of human memory is its susceptibility to intrusion errors and presupposition effects (e.g.,

    Fiedler, Walther, Armbruster, Fey, & Naumann, 1996; Loftus, 1975). Such constructive memory

    effects have been studied in the domain of sports by Walther, Fiedler, Horn, and Zembrod (2002).

    In their experimental study, football experts and non-experts were presented with various scenes

    from a videotaped European-Cup match. Among other manipulations, half of the participants

    were told after the video presentation that the team dressed in yellow won the match while the

    other half received the information that this team lost. Afterwards they were asked to rate the

    observed performance of the teams in yellow on various dimensions (e.g., ability and fight). It wasfound that experts were even more susceptible to the result-manipulation than non-experts. For

    example, when they believed that the yellow team won they were more likely to reconstruct the

    match in accordance with their implicit theory that a win on this level is rather due to an

    advantage in fighting than in ability. When they believed that the yellow team lost they rated its

    ability higher and its fighting during the game lower. Together, this study demonstrates that post-

    event information can exert an important influence on the evaluation of sport performance from

    memory.

    Global judgments

    A similar effect has been studied by Unkelbach, Plessner, and Fiedler (2006) in another

    experimental application of the sampling approach (Fiedler, 2000) to global judgments of sports

    performance, that is, the rating of a football players ability. While most empirical work on the

    sampling approach is concerned with information sampling from the environment (e.g., Plessner

    et al., 2001), this approach can also account for effects of selective sampling from memory. In

    order to test this assumption, Unkelbach et al. (2006) used a well-documented effect in social

    cognition research, the category-split effect: When people estimate the frequency of instances in a

    social category, the overall estimate is higher when the category is split into smaller sub-categories

    (Fiedler & Armbruster, 1994). The basic idea was that splitting a positive feature (e.g., excellent

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    technical skills) of a player should result in a more favorable judgment when a negative feature

    (e.g., a lack of physical fitness) is not split and vice versa when the negative features are split and

    the positive features are not. In the experiment, sport coaches attended to a presentation about a

    player, which, besides some background information about age, former clubs, and so forth,contained an equal amount of positive and negative information, the former always related to his

    technical skill, the latter always related to his lacking fitness. After participants saw this

    presentation, the crucial category-split manipulation followed. Half of the participants were

    assigned to a positive split condition, and were asked about the players pass-game, dribbling,

    shots and ball-security, all items that fell under the general category technical skill. In

    comparison, they were asked about his physical fitness in general. The remaining participants

    were assigned to a negative split condition and evaluated his technical skill in general, whereas

    the category physical fitness was split into the instances of speed, jump, stamina and

    aggressiveness. In the final overall evaluations, it was found that the player was evaluated more

    positively when the positive category was split and more negatively when the negative categorywas split. As in the study by Plessner et al. (2001), coaches were blind for this sampling

    manipulation and did not correct their judgments accordingly.

    The only other memory effect that has been studied in the domain of global judgments of sports

    performance so far refers to the use of the availability heuristic (Tversky & Kahneman, 1973).

    This heuristic allows people to base, for example, frequency judgments on the ease with which

    events can be retrieved instead of retrieving and counting all relevant instances. While this

    heuristic provides good results under many circumstances, it can also bias judgments if factors

    unrelated to the actual number of occurrences influence the retrieval process. For example, the

    ease with which the first (sensational) victory of Boris Becker in Wimbledon can be retrieved may

    lead to a relative overestimation of his weeks as world number one in comparison to the record of

    a player with less salient victories (e.g., Jim Courier). Indeed, Young and French (1998) foundrankings of the greatest heavyweights of all time by noted boxing historians to be biased in line

    with the use of an availability heuristic, that is, fighters from more recent years were

    overrepresented in comparison to fighters who had their greatest time before the birth of the

    historians. One can easily imagine similar effects of availability on more short time rankings such

    as FIFA World Player of the Year.

    Information integration

    Local judgment

    In the final step of social information processing, information about an athletes performance

    that has been encoded and categorized, together with information that has been retrieved from

    memory, are integrated into a judgment. Ideally, a judge considers all the relevant information for

    a judgment task at hand and integrates this information in the most appropriate, analytical way.

    However, because the human capacities to process information are limited and social situations

    often introduce constraints such as time pressure, people frequently use short cuts to cope with

    complex judgment situations. An example of these shortcuts, as mentioned, is the availability

    heuristic or the use of schematic knowledge, which is classified as top-down processing (e.g., Fiske

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    & Neuberg, 1990). Unfortunately, little is known about when and why judges in sports switch

    between bottom-up and top-down processing. Research on information integration processes in

    sports performance judgments typically focuses on the more or less deliberate use of information

    beyond the observable performance. An important question that arises from this research is, howadaptive is the use of this information? For example, the hot hand phenomenon in sports like

    basketball, where a particular player is on a shooting streak and thus should be given more

    shots, has been shown to be a fallacy (Gilovich, Vallone, & Tversky, 1985). The same is true for

    many other myths or irrational illusions in sports (Ayton, 1998; Gilovich, 1984a; Russel, 2001). In

    a recent analysis, however, Burns (2004) was able to show that streaks are valid cues for deciding

    to whom a player should pass the ball in order to maximize the teams scoring potential. Thus,

    using the belief in the hot hand may be an adaptive decision strategy even when it is normatively

    wrong. An important question that follows from this assumption is, which are the non-

    performance cues that judges in sports typically use in their decisions and how adaptive is their

    usage?Nevill et al. (2002) investigated whether crowd noise has an influence on soccer referees

    decisions concerning potential foul situations. They assumed that referees have learned to use

    crowd noise as a decision cue because in general it may serve as a useful indicator for the

    seriousness of the foul. However, because the reaction of a crowd is usually biased against the

    away team, the use of this knowledge may be inappropriate and contribute to the well-confirmed

    phenomenon of a home advantage in team sports (Courneya & Carron, 1992). In an experiment,

    referees assessed various challenges videotaped from a match in the English Premier League. Half

    of the referees observed the video with the original crowd noise audible, whereas the other half

    viewed the video in silence. This presence or absence of crowd noise had a strong effect on

    decisions made by the referees. Most importantly, referees who viewed challenges in the noise

    condition awarded significantly fewer fouls against the home team than those observing the videoin silence. The authors concluded that this effect might be partly due to heuristic judgment

    processes in which the salient, yet potentially biased, judgment of the crowd served as a decision

    cue for referees. In addition, this study demonstrates how biased referees decisions can contribute

    to the phenomenon of a home advantage in sports (see also Balmer, Nevill, & Lane, 2005; Sutter

    & Kocher, 2004).

    Recent studies showed that referees are not only influenced by situational cues but by their own

    prior decisions. In an experimental study, Plessner and Betsch (2001) found a negative

    contingency between football referees successive penalty decisions concerning the same team,

    that is, the probability of awarding a penalty to a team decreased when they had awarded a

    penalty to this team in a similar situation before and increased when they had not. The oppositeeffect occurred with successive penalty decisions concerning first one and then the other team.

    Similar results have been found with basketball referees when contact situations were presented in

    their original game sequence but not when they were presented as random successions of

    individual scenes (Brand, Schmidt, & Schneeloch, 2006). Thus, these effects may be partly due to

    referees goal of being fair in the management of a game (Mascarenhas, Collins, & Mortimer,

    2002; Rains, 1984).

    Sequential effects point also to the fact that social judgments are comparative in nature

    (Mussweiler, 2003). The judgment of an athletes performance is frequently based on the

    comparison with other athletes, or with prior judgments of other athletes performance,

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    respectively. Accordingly, several studies show that social comparisons determine evaluative

    processes in judging athletes in various sports (e.g., Ebbeck, 1990; Gotwals & Wayment, 2002;

    Sheldon, 2003; Van Yperen, 1992). Recent research suggests that the consequences of such

    comparisons are produced by the selective accessibility mechanism of similarity and dissimilaritytesting (Mussweiler, 2003). That means, starting the comparison process with the focus on

    similarities increases the likelihood of an assimilation judgment toward the standard of

    comparison. The focus on dissimilarities, however, is more likely to end up in a contrast effect

    away from a standard. These assumptions were recently applied to the sequential judgment of

    gymnastic routines on vault by experienced judges (Damisch, Mussweiler, & Plessner, 2006). Two

    athletes were introduced to the judges as belonging either to the same national team (similarity

    focus) or to different teams (dissimilarity focus). The routines of both gymnasts had to be

    evaluated in a sequence. While the second routine was the same in all conditions, half of the

    participants first saw a better routine (high standard), while the other half first saw a worse

    routine (low standard). As predicted, the second gymnasts score was assimilated toward thestandard when both gymnasts were introduced as belonging to the same team. The opposite effect

    occurred when the judges believed the gymnasts belonged to different teams.

    While most of the reported biases so far are due to the functioning of the cognitiveinformation

    processing system, it is clear that many biases in judgments or sport performance also have amotivationalbackground. Starting with the work by Hastorf and Cantril (1954), there is plenty of

    evidence that group membership has a distorting influence on the judgment of sport performances

    (Ansorge & Scheer, 1988; de Fiore & Kramer, 1982; Markman & Hirt, 2002; Mohr & Larsen,

    1998; Seltzer & Glass, 1991; Ste-Marie, 1996; Whissel, Lyons, Wilkinson, & Whissel, 1993). Thus,

    achieving accuracy is not the only motivation that should be taken into account when studying

    biases in the judgment of sport performance. To conform to a norm may be just another goal

    (Rainey & Larsen, 1988; Rainey, Larsen, Stephenson, & Olson, 1993; Scheer, Ansorge, &Howard, 1983; Vanden Auweele, Boen, De Geest, & Feys, 2004; Wanderer, 1987). So far, only

    one study has directly assessed whether influences like these are automatic or unconscious (Ste-

    Marie, 1996). However, no support was found for the hypothesis of unconscious influences.

    Global judgments

    A belief that many people involved in sports share is that athletes who started with an

    outstanding first season are susceptible to the so called sophomore slump. The sophomore slump

    is a significant decline in performance during the second year (Taylor & Cuave, 1994). As with the

    hot-hand phenomenon, it has been argued that the sophomore slump does not really exist but is acognitive illusion based on a lack of understanding of regression to the mean (Gilovich, 1984b).

    According to this position, outstanding performances in the first year are just as likely to regress

    toward their actual level of ability as the statistical tendency of extreme scores to move toward the

    group means. However, in a careful analysis of the performance of 83 hitters and 22 pitchers who

    had an outstanding first year in the Major Baseball League, Taylor and Cuave (1994) found a

    significant decline in the second year in the number of home runs. This trend is consistent with the

    assumption of a real sophomore slump. The results of other performance measures (batting

    average and runs batted in) were also consistent with the sophomore slump as with the regression

    to the mean explanation. Thus, peoples failure to understand statistical tendencies together with

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    some real declines in performances may jointly produce a stronger belief in the sophomore slump

    than would be warranted on the basis of the actual career development of outstanding first-year

    athletes alone.

    The accurate assessment of an athletes or a teams strength is also of interest for the increasingnumber of people who invest their money in the betting market. Several recent studies explore the

    quality of experts predictions of the outcomes of sporting events and their use of information in

    making these predictions (e.g., Andersson, Edman, & Ekman, 2005). So far, however, a rather low

    quality of expert predictions has been reported in these studies and little is known about the

    factors that can help to improve prediction accuracy. While in general one can assume that

    predictions are less prone to biases the more people think about their judgments and the more

    performance relevant information they gather and integrate in an analytic way (Vertinsky,

    Kanetkar, Vertinsky, & Wilson, 1986), there is also evidence that a less analytical judgment style

    can improve predictions of sports events. Halberstadt and Levine (1999) asked basketball experts

    to make predictions for the outcomes of actual basketball games. Half of the participants wereasked to analyze reasons for their predictions before making them, the other half was asked to rely

    on their spontaneous feelings. The reasoners were found to predict fewer winners of the games

    than the nonreasoners, that is, analytical thinking led to a decrease in prediction accuracy. A

    possible explanation for this effect is that deliberation hinders the use of potentially valid decision

    cues, such as the feelings that are associated with a teams strength. Furthermore, these feelings

    may accurately reflect the entire information about a teams strength that an expert had

    encountered before (Betsch, Plessner, & Schallies, 2004). Therefore, one could argue that the use

    of affective responses deserves greater attention in future studies on performance judgments in

    sports.

    Conclusions and outlook

    We presented an overview of empirical work on biases in judgments of sport performance (see

    Table 1). It is evident that many biases that have been documented in the social cognition

    literature are well and alive in the world of sports. Moreover, some research on judgments of sport

    performance discovered unique judgment phenomena, such as the belief in the hot hand

    phenomenon (Gilovich et al., 1985) and sequential effects in penalty decisions (Plessner & Betsch,

    2001), that can stimulate theory development in the social cognition literature. By taking a social

    cognitive perspective, we were able to identify different cognitive processes at different stages of

    social information processing that underlie the formation of biased judgments of sportperformance. These analyses can help to develop useful measures to improve decision making

    in sports. For example, if the source of a judgment bias is clearly identified on the processing stage

    of perception, the accuracy can be improved by determining better viewing positions (e.g., Ford et

    al., 1997) and by the application of training techniques that help judges to overcome perceptual

    limitations (e.g., Craven, 1998; Jendrusch, 2002). Problems that arise from the activation of

    inappropriate knowledge structures on the stage of encoding/categorization can be addressed by

    the development of specific video-based feedback training (Helsen & Bultynck, 2004;

    Mascarenhas, OHare, & Plessner, 2006). However, it will be more difficult to prevent biases

    that stem from unrepresentative information samples and memory intrusions. Normally, people

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    do not recognize biased information samples either from the environment or from memory and

    have no insight into the danger of the sampling trap (Fiedler & Wa nke, 2004). Therefore,

    increasing sports judges awareness and sensibility for these sources of biased performance

    judgments would be at least a first step. It is even more problematic to propose measures thatwould prevent supposed biases that stem from different processes of information integration.

    First, one has to prove for every reported influence of non-performance factors if their

    consideration in a judgment does not serve a legitimate goal beyond the aim for accuracy and,

    thus, mirrors an adaptive decision strategy.

    Altogether, the application of a social cognition perspective is promising in the goal of gaining

    further understanding of sports performance judgments. Although our overview is based on a

    reasonable number of studies, the social cognition perspective provides many more links and new

    developments that can help to improve the understanding of sport behavior. For example, many

    social judgment biases have recently been found to depend on judges cultural background. In a

    football field study, Snibbe, Kitayama, Markus, and Suzuki (2003) found an intergroup bias asreported in the study by Hastorf and Cantril (1954) only for European American students, but not

    for Japanese students. Thus, culture seems to be an important factor that has to be taken into

    account in future studies on the evaluation of sport performances (see also Tiryaki, 2005).

    Another promising development for the study of judgments in sports is the increasing interest of

    social cognition researchers in implicit as opposed to explicit representations (e.g. Greenwald &

    Banaji, 1995). Implicit structures, such as implicit attitudes, are assumed to be activated

    automatically and to exert an influence on spontaneous responses. Judgments in sports are

    frequently executed under time pressure and with limited control. Therefore, implicit structures

    may play an important role in the formation of performance judgments. These are just two

    examples of recent developments in social cognition that can have an additional stimulating effect

    on the study of sports performance judgments.

    Acknowledgments

    We thank Clare MacMahon for her helpful comments on an earlier draft of this manuscript.

    Financial support is gratefully acknowledged from the Deutsche Forschungsgemeinschaft via the

    Sonderforschungsbereich 504 (TP A10) to the first author.

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