Emotional Intelligence in Sport: Theoretical Linkages and Preliminary Empirical Relationships from Basketball

Emotional Intelligence in Sport: Theoretical
Linkages and Preliminary Empirical
Relationships from Basketball

*Con Stough1, Mathilde Clements1,2 and Lena Wallish1

1
    Swinburne University of technology
2
    Mental Edge Consulting

*To whom correspondence should be addressed:

Brain Sciences Institute

Swinburne University

PO Box 218 Hawthorn Victoria, 3122

AUSTRALIA

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Recently there has been suggestions from within sports psychology (e.g., Meyer &

Fletcher, 2007) that there are substantial similarities in the use of psychological tools and

programs in the corporate and sporting worlds. Therefore it is somewhat surprising that

despite the growing body of research supporting emotional intelligence (EI) as an

important tool for identifying superior performance levels within the workplace, it is yet

to be the subject of rigorous research within other performance arenas such as the

sporting environment. The aim of this chapter is to explore the potential relationship

between EI and sport, with emphasis on the potential role of EI in separating athletes on

the basis of their type of sport. The chapter starts with a discussion of earlier conceptions

of emotions in sport, progresses to discuss the construct of emotional intelligence and

then provides some empirical data assessing the utility of at least one application of

emotional intelligence to the elite sporting arena. Throughout the chapter we propose

theoretical linkages between EI and elite sport variables which should be the focus of

future empirical research.

Emotions in Sports

Sports psychologists and professional athletes have started to evaluate the linkages

between emotion and competitive sporting performance, and in particular how

moderating and appropriately expressing the experience of emotions can facilitate

performance (Vallerand, 1983). To date a majority of research into the impact of

emotion on sporting performance has been focused on the control of the physical

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manifestation of emotions such as rage, frustration and how they impact on performance

rather than on the cognitive management of the emotions that caused the emotional

display (Vallerand, 1983). Only recently has research broadened to look at the more

cognitive side of emotion, with researchers such as Schachter (1964), Lazarus (1966) and

Weiner (1981) all proposing cognitive theories, in which both arousal and cognitions are

required in the experience of emotion. While it is generally well acknowledged that

emotions play an important role in the sporting arena (D’Urso, Andreina & Robazza,

2002), the exact nature of their role in sporting performance is still very under-

researched. It has been argued that not only is the expression of emotion highly prevalent

on the sporting field but an essential aspect of performance in all sports (Vallerand,

1983). For example, the inability to appropriately manage emotions experienced in

competitive situations may lead to such things as an inappropriate outburst of rage or

aggression and can often lead athletes to be penalized or excluded from competing.

While those who are able to effectively manage their emotions can channel their

emotions into the production of motivation and drive. It is therefore important that

athletes learn how to recognize these emotions, express them appropriately and manage

them effectively (Botterill & Brown, 2002).

While there has been difficulty providing a clear and precise definition of emotion

(Lazarus, 1991a), researchers have generally established three main components of

emotion: subjective experience, physiological changes, and observable behaviour

(Young, 1973), and in each individual study the researcher uses a variation of this basic

theory, identifying different guidelines for what constitutes each of the three stages.

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Many of the current theories on the role of emotion in sport are limited to one aspect of

emotion, such as optimal levels of arousal or balance between positive and negative

emotions, which means that while each individual theory adds to our understanding, there

is no one particular model that can be used to explain the complete relationship between

the full range of our emotions and sporting performance (D’Urso, Petrosso & Robazza,

2002). There has been an acknowledgement that there is a need for a model that

integrates the important contributions from each of the major theories (Crocker &

Graham, 1995).

Recently Hanin (2000) argued that there was a lack of research investigating the role of

emotion in sport. With most of the research being inclined to focus on anxiety-

performance relationships, what little research that has been done in this area has tended

to have a negative emotion bias. Yet recently there has been a growing movement

amongst researchers to examine the role of emotions in sporting performance (Hanin,

2000). Recent research by Hanin and Stambulova (2002) has identified the importance in

distinguishing a specific set of emotion content that is optimal or dysfunctional for an

athlete’s performance. The research has suggested that due to the dynamic nature of

emotional content that it would be useful to isolate temporal patterns of emotions

throughout a particular competition or several competitions so as to plan psychological

interventions and strategies for performance improvement (Hanin & Stambulova, 2002).

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Based on Hanin’s Individual Zones of Optimal Functioning (IZOF) model, it has been

proposed that the function of emotions in the sporting arena be studied through five basic

dimensions; form, content, intensity, time and context (Crust, 2002). Acknowledging that

a wide range of emotions, other than anxiety, characterize sporting experience, Hanin’s

model (2000) suggests that a range of positive and negative emotions can both facilitate,

as well as inhibit, performance. The model suggests that positive and negative emotions

may exert beneficial or detrimental effects depending on their idiosyncratic meaning and

intensity. That is, a specific emotion may be beneficial for one athlete but may be

detrimental for another, depending on the meaning the individual attaches to that

emotion.

Importantly the IZOF model suggests that different intensities of an emotion may result

in improved or impaired performance in the same athlete. Each athlete differs on the

interaction of affect hedonic tone (positive or negative) and functional impact (facilitating

or inhibiting) (Hanin, 2000). Because of the interactive effects of emotions the functional

impact of emotions upon performance can be best explained by resource-matching

(Robazza & Bortoli, 2002). That is, facilitating-positive and –negative emotions will

reflect the availability of resources and their effective recruitment and use. To sustain

mental and physical effort in achieving goals, facilitating-positive emotions would help

the athlete to produce energy and organize functions. Conversely, facilitating-negative

emotions would result in energy production than utilization (Robazza & Bortoli, 2002).

In keeping with this concept, inhibiting-positive and –negative emotions will reflect a

lack or loss of resources or the inefficient recruitment and utilization of them. Inhibiting-

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positive emotions will reflect a decreased effort or energy loss, whereas inhibiting-

negative emotions will result in an inadequate energy production and utilization (Robazza

& Bortoli, 2002). The model assumes that the total impact of emotion upon performance

can be predicted on the basis of interactive rather than separate effects of energy

mobilization and energy utilization functions (Hanin, 2000).

Mayer and Salovey’s Ability Model of Emotional Intelligence

Salovey and Mayer first coined the term ‘emotional intelligence’ (Salovey & Mayer,

1990). Formulating the term as a challenge to intelligence theorists, who have historically

considered arousal of affect as disorganizing cognitive activity, Salovey and Mayer

(1990) described Emotional Intelligence as a form of social intelligence. Consistent with

earlier research on social intelligence (Ford & Tisak, 1983) and Gardner’s (1983)

intrapersonal and interpersonal intelligences, Salovey and Mayer’s (1990) original

conceptualization of EI viewed the ability to process affective information as an

intellectual aptitude. In keeping with Sternberg’s (1997) definition that ‘intelligence

comprises the mental abilities necessary for adaptation to, as well as shaping and

selection of, any environmental context’, Mayer and Salovey (1997) developed an ability

model that suggests that EI abilities develop with age and experience similar to

crystallized intellectual abilities. Their model emphasizes four cognitive components: the

capacity to perceive emotion, to integrate it in thought, to understand emotion, and to

manage emotion.

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Within this model EI refers to a form of intelligence that involves the ability to monitor

one’s own and others’ emotions, to discriminate among them, and to use the information

to guide one’s thinking and actions (Salovey & Mayer, 1990). It has been suggested that

individuals predominantly react and interrelate within an environment because of the way

they feel and think, rather than on rationality alone. Notably, it has been argued that the

competencies underpinning emotional intelligence, which enable people to demonstrate

intelligent use of their emotions in managing themselves and working effectively with

others, relate to workplace performance (Gardner & Stough, 2001). Yet, perhaps what is

most attractive about this construct to the corporate world is that, unlike traditional

models of intelligence and personality, it has been hypothesized that an individual can

develop Emotional Intelligence through awareness and emotional competency programs

(e.g., see Gardner & Stough, 2002).

Mixed Model of Emotional Intelligence

Bar-On’s (1997) mixed model of emotional intelligence, like those of previous theorists

such as Goleman (1995), considered Emotional Intelligence to be comprised of emotional

aspects along with other aspects that were more traditionally associated with personality.

Combining emotion and personality into a single construct, Bar-On considered there to

be five components of emotional intelligence, each containing numerous competencies.

Bar-On’s mixed model proposed that emotional intelligence consisted of Intrapersonal

intelligence, interpersonal intelligence, adaptability, stress management, and general

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mood (Bar-On, 1997). Each of these five components consists of a number of

competencies. Intrapersonal intelligence, or internal intelligence, included emotional self-

awareness, assertiveness, self-regard, self-actualization and independence. Interpersonal

intelligence, or external intelligence, consists of empathy, social responsibility, and

interpersonal relationships. The third component, adaptability, consists of reality testing,

flexibility and problem solving, with stress management comprising of stress tolerance

and impulse control. The final component of Bar-On’s theory, general mood, comprised

of traits usually considered to be part of personality such as optimism and happiness.

While many of Bar-On’s (1997) components equate to those developed in the ability

models his concept of EI is much broader. There are also significant differences in the

measurement and assessment of EI within these models. The Bar-On measure like many

self-report measures are often referred tounder the umbrella of mixed models of Ei and

include a range of traits, dispositions, beliefs and behaviors.

It is beyond the scope of the current chapter to review and critically comment on the

different models of EI. This has recently been done in a sports psychology journal by

Meyer and Fletcher (2007) and elsewhere in this book. However, it is noteworthy to point

out that there are different models, conceptualizations and measures of EI, although there

is to date no consensus as to which of these models and measures of EI are most

appropriate and useful in predicting real life criteria. There are current scientific debates

regarding the construct validity which may or may not be resolved in the near future.

There also appears to be a clear distinction between scientific discussion on for example

the construct validity of a scale of EI and the actual popularity and use of the scale in the

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workplace. Sports psychologists will use models and measures which allow elite sports

people to grasp and run with theories and ideas and which allow the quickest and most

efficient hand over of information from coach or mentor to athlete. Whether a variety of

different measures may work together in a synergistic manner by providing new and

useful but independent understandings of the construct or simply to repeat information is

not yet understood.

Theoretical Linkages Between EI and Sports Psychology

In attempting to link sports psychology variables to a model for both practice and

research requires the adoption of a single model of EI in the first instance. Below we

describe some of our thoughts in this regard with the Swinburne University Emotional

Intelligence test (SUEIT). The SUEIT also referred to as GENOS EI in a previous

chapter in this book (see the chapter by Palmer et al). Due to the considerable amount of

overlap in theoretical content and structure of the existing theories, Palmer and Stough

(2001) conducted a large factor analytic study using a population representative sample.

The study involved six of the current predominant measures of emotional intelligence

including the MSCEIT, the Bar-On EQI, the Trait Meta-Mood scale, the twenty-item

Toronto alexythmia scale-II, the scale by Schutte et al (1998) and finally the scale by Tett

et al. (1997). These 6 scales are highly representative of all the different models in

Emotional intelligence (Palmer & Stough, 2001).

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The test provides scores on five factors;

   1. emotional recognition and expression:

   2. emotional reasoning

   3. understanding emotions of others

   4. emotional management (self and others)

   5. emotional control:

Having acknowledged the excess of anecdotal reports regarding the similarities between

successful leaders and organizations in the sport and business arenas (Weinberg &

McDermott, 2002), we draw theoretical linkages between the workplace and the sporting

environment when evaluating the Emotional Intelligence literature. Similarly to the

workplace, sport is a highly-charged and emotional environment, and one in which

inappropriate emotions may hinder performance. Yet despite bold statements such as

“emotional intelligence is directly related to performance” (Abraham, 1999, p.4.) and

“emotional competence is a learned capability based on emotional intelligence that

results in outstanding performance at work” (Goleman, 2001, p.1.), there has been no

significant theoretical links proposed between EI and sporting performance.

       It is often noted by coaches, sport scientists and psychologists, and the athletes

themselves that the most technically gifted athletes do not always end up as the best

performers (Morgan, 2003). Typically, coaches have suggested these athletes possess

abilities that their less successful colleagues lack, such as supreme self-confidence,

mental toughness, unshakeability and strong will (Morgan, 2003). While these qualities

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have traditionally been categorized as attributes of a ‘true sportsperson’, perhaps a more

appropriate classification, considering the growing body of literature about performance

in the corporate environment, would be under the label of EI.

Based upon some of the theoretical links between attentional style and sport type and

studies examining Hanin’s Individual Zones of Optimal Functioning model (Hanin &

Stambulova, 2002), it is possible to make some tentative hypotheses relating the

dimensions of the SUEIT to the three sport categories (closed-skill, individual open-

skilled and team open-skilled sport). These hypotheses are tentative, and therefore require

empirical testing, as this is the first theoretical article of its type to link dimensions of the

SUEIT or even any dimensions of EI to sporting classifications. Despite this, it is

suggested that the EI dimension from the SUEIT, ‘understanding the emotions of others’,

is best related to Nideffer and Bond’s (1990) finding that ‘awareness’ significantly

contributes to the equation separating athletes on the basis of their sport type. The

‘understanding of the emotions of others’ dimension measures an individual capacity to

recognize how others’ respond to their surrounding environment (Palmer & Stough,

2001). In Table 1 we propose some theoretical linkages between the 5 dimensions of the

SUEIT and their relative importance for different types of sports.

Table 1 About Here

According to Palmer and Stough (2001), high scores on the ‘understanding the emotions

of others’ dimension reflect the recognition and acknowledgement of how emotions

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influence organizational dynamics, as well as the ability to identify the emotional

‘overtones’ of the environment. Therefore, within the sporting environment, an individual

who reports high competency on this Emotional Intelligence factor may be able to read

their teammate’s or opponents’ emotional response to the atmosphere of the competition.

Furthermore, a high score on this dimension suggests that the athlete has a good

understanding of why others in the competition are responding in a particular way and

how it affects the individual or team’s performance. Nideffer and Bond (1990) found that

the ‘awareness’ scores were least predictive of the closed-skilled sport category but most

predictive of the individual open-skilled sport type. Thus it is hypothesized for future

research, as shown in Table 1, that athletes performing open-skilled individual and team

sports will be most likely to report using ‘emotional understanding’ but athletes in the

closed-skill category least likely.

In the example of tennis, an open-skilled individual sport, ‘reading’ the emotions of your

opponent is crucial to successful performance (Anshel, 1990; Orbach, Singer, & Price,

1999). The ability to identify that your opponent is experiencing ‘negative’ emotions

such as anxiety and self-doubt, allows an athlete to capitalize on their opponent’s

weaknesses (Anshel, 1990). For example in tennis, the athlete may force play around the

baseline having recognized that their opponent has shown frustration throughout the

match at points played around this area of the court (Anshel, 1990; Orbach, et al, 1999).

Conversely, by acknowledging that their opponent is experiencing ‘positive’ feelings an

athlete can re-evaluate their own game-plan so as to change the dynamics of the match.

Additionally, by understanding the appropriateness of an emotional response to a

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linesman’s call for example, an athlete is able to recognize the emotional overtones of the

game. By understanding the emotional dynamics of the competition, the player is able to

adapt his or her play suitably.

High scores on the ‘emotional reasoning’ dimension may indicate that some individuals

make intuitive decisions based on feelings rather than on pure fact while others make

decisions based more on analytical information (Palmer & Stough, 2001). This dimension

is suggested to be similar to Nideffer and Bond’s (1990) ‘analytical’ attentional style, a

characteristic found to be predictive of sport types. Therefore, athletes who score high on

‘analytical’ attentional style may score lower on the ‘emotional reasoning’ dimension of

the SUEIT, indicating that they do not incorporate emotions into decisions regarding

sporting performance. Speculatively we propose that scores on the ‘emotional reasoning’

dimension will be most predictive of the open-skilled team classification and least

predictive of closed-skilled and open-skilled individual sports as shown in Table 1. In

keeping with this hypothesis, in the open-skilled team sport of basketball it is

hypothesised that it will be beneficial to performance for an athlete to incorporate

emotions into decision-making when competing (Madden, Summers & Brown, 1990).

Basketball requires an athlete to play intuitively and to be flexible in adapting game-plans

depending on the emotions within the competitive environment (Madden, et al, 1990).

That is, a successful basketballer is hypothesized to be able to quickly evaluate how

different game strategies will affect play by incorporating the technical information

provided to her or him during practice drills, together with the athlete’s ‘gut-feeling’ on

the correct choice of play.

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Palmer and Stough (2001) suggested that the ‘emotional management’ factor assesses the

extent to which an individual is able to foster and maintain beneficial positive moods and

emotions so as to effectively manage stress within oneself and others. By effectively

managing one’s own emotions an individual is better able to remain task focused and

avoid external and internal distractions. According to Nideffer (1990), by shifting the

focus of attention from a negative internal or external source to a more positive internal

focus, an athlete is less likely to perform an error. This finding is supported by Hanin’s

IZOF model (2000) that states that facilitating-positive emotions help an athlete to

produce energy aiding performance. Theoretically, high competency levels of ‘emotional

management’ within a sporting environment will reflect an athlete’s ability to foster

positive moods within themselves and their teammates, as well as effectively manage

competitive anxiety levels. If making theoretical assumptions based on Nideffer and

Bond’s (1990) findings, the high competency on this dimension would be most predictive

of high performance in closed-skill sports and least predictive performance in open-

skilled team category. Notably ‘emotional management’ has also been shown to be an

important attribute of leadership within the workplace (Gardner & Stough, 2002), and

therefore likely to be a dimension of EI reported by team captains. As indicated in Table

1, ‘emotional management’ is also hypothesized to be predictive of athletes who compete

as individuals. Successful performance in individual closed-skill sports requires the

athlete to effectively manage their own moods and anxiety levels as there is no team-mate

support available. For example in the closed skill sport of diving, an athlete is assessed on

the total score of a series of dives (Orlick & Partington, 1988). Hence, a diver would need

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to effectively manage negative feelings of self-doubt and anxiety after an initial poor

diving performance so as to mentally re-prepare for the following dives (Orlick &

Partington, 1988).

It may be argued that strong expressions of emotions such as anger, frustration, sadness

and hostility are not constructive in the context of the workplace and can damage

interpersonal relationships. Similarly, Hanin’s IZOF model suggests that facilitating-

negative emotions cause energy production rather than utilization, and subsequently

results in poorer athletic performance. Hence it is theorized that athletes who score high

on the ‘emotional control’ dimension would be able to inhibit strong emotions, such as

anger and hostility, from detrimentally affecting their thoughts and performance during

competition.

Nideffer and Bond (1990) found that the interpersonal style, ‘control’, was most

predictive of individual open-skilled sport types but least predictive of open-skilled team

sports. Therefore we propose that scores on the ‘emotional control’ dimension of the

SUEIT will be predictive of athletes performing open-skilled individual sports but not of

the open-skilled team category. In keeping with this hypothesis, it could be assumed that

the open-skilled individual sport of wrestling requires the athlete to control the impact of

strong emotions from detrimentally affecting their performance (Mahoney, 1989;

Morgan, 1984). Undoubtedly the one-on-one competition of wrestling would elicit strong

emotions such as anger and frustration, however it could be presumed that the successful

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athlete inhibits such feelings from affecting their thoughts, actions and behaviors while

competing (Mahoney, 1989).

Palmer and Stough (2001) suggested that the ‘emotional recognition and expression’

dimension assesses how well you perceive your own emotions and how effectively you

express your feelings to others. Therefore within the sporting environment athletes who

indicate high scores on this dimension will be conscious of their emotions while

competing and be able to express these emotions suitably and accurately within the

performance arena. According to Hanin’s IZOF model (2000), to sustain mental and

physical effort in achieving goals, facilitating-positive emotions helps the athlete to

produce energy and organize functions. By accurately assessing one’s own emotions and

effectively communicating those feelings, it could be assumed that an athlete is suitably

organizing their emotion content to benefit performance (Hanin, 2000). Likewise by

accurately displaying emotions during performance, an athlete presumably contributes to

the development of a better team environment as teammates can more effectively respond

to one another’s display of feelings. Druskat and Wolff (2001) suggested that team spirit

is an important component of team building within the workplace. In a study of team

dynamics within the workplace, Druskat and Wolff (2001) found that within the more

effective teams, individuals are able to suitably express their feelings to one another and

thus collaborate unreservedly. It would therefore seem that the advantages of accurately

expressing one’s emotions would appear to be greater for athletes competing within a

team environment as team members competent in ‘emotional recognition and expression’

would be better able to articulate issues important towards building the team’s

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capabilities. As illustrated in Table 1 it is hypothesized that scores on this dimension

would be more predictive of the open-skilled team classification and least predictive of

athletes performing closed-skill sports.

In the example of volleyball, it is assumed that perceiving your teammate’s feelings, as

well as communicating your own emotions, would be crucial to successful performance

(Leslie-Toogood & Martin, 2003; Mahoney, Gabriel & Perkins, 1987). As volleyball

requires the reading of hand-signals to determine strategies of play a successful

volleyballer may be particularly conscious of all their movements and expressions to their

teammate (Mahoney, et al, 1987), including being overtly aware of their emotional

expression. After a successful point in volleyball competition, teammates often express

positive displays of emotion to one another by patting each other on the back etc (Leslie-

Toogood & Martin, 2003). In doing so, they consciously indicate feelings of elation and

encouragement to one another. Equally, it could be hypothesized that successful

volleyballers would be very aware of how they were communicating their feelings, so as

not to allow their opponents to effectively respond to their weaknesses.

Potentially, Emotional Intelligence could provide additional information about sporting

performance to other psychological models offering a comprehensive description about

the role of emotions in competitive performance and training. Yet, perhaps what makes

EI a useful addition to other psychological constructs to date is that it proposes ways to

improve an athlete’s capacity to deal effectively with their own and other’s emotions.

Unlike traditional intelligence theories and personality models, EI has been hypothesized

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as a key construct that can be developed through specific emotion focused training

(Greenberg, 2002). Therapeutic and preventive training programs are already in place

that could be helpful in preparing elite athletes for emotional problems that could intrude

on, facilitate competitive performance, prevent them, or correct them when they occur

(Lazarus, 2000). Therefore it is conceivable that in the near future, sporting bodies will

integrate EI into traditional sports psychology and mental training programs so as to gain

that competitive edge over competitors.

Another potential role of EI within the sporting arena is in the development and training

of athletes for post-sport careers. The importance of EI within a successful corporate

environment is increasingly being supported be organizational psychology research

(Gardner & Stough, 2002). As the authors foresee that the basic skills of EI will be

similar regardless of the environment, transferring those skills from one arena to another

will have obvious benefit to the athlete. Recent research in the area of Athlete Career

Transition supports the idea that skills learnt within the sporting environment are valuable

for an athlete’s successful transition into the workforce (Lavallee & Wylleman, 2000).

Obviously there is the need for a large body of empirical study to be conducted so as to

establish whether there is evidence for the utility of EI in predicting performance in sport.

Yet on the basis of the research examining EI and workplace performance, investigation

into the relationship seems warranted. Many researchers investigating EI within the

workplace have acknowledged the potential avenue of study that the sporting arena

provides. However to date there has been no published work examining the relationship

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between EI and sport. Therefore, although the above hypotheses provide potential

direction for future investigation, the possible research avenues examining the role of EI

in sport are seemingly numerous. Several potential areas of particular focus could be in

the areas of talent identification, emotional profiles for specific sports and profiling

specific positions of play within team sports.

Empirical relationships between EI and Sports Psychology

The above section has described some potential theoretical linkages between EI and

sports psychology variables. Now we turn our attention to some linkages (albeit

preliminary) between EI and sports variables in the game of professional basketball. We

propose, based on linkages between EI and workplace performance as well as some of

our pilot work a number of hypotheses. It was predicted that those individuals who have

higher levels Emotional Management and Emotional Control, would perform better under

the stresses of competitive situations. It was hypothesized that those individuals who

have higher accuracy in shooting from the field, three point line and free throw line

would show higher levels of Emotional Control and Emotional Management. It was also

predicted that those individuals who made more defensive plays throughout the season

would show higher levels of Understanding Emotions, shown in their ability to read the

opposition through body language, enabling a greater number of steals, turnovers and

blocked shots.

Considering the importance of rebounding in team and individual performance, and due

to the fact that rebounding involves an understanding of opposition players, it was

predicted that those individuals who had did the majority of the rebounding, both

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defensively and offensively, would show greater ability in understand emotions in others

and the environment.

Participants

The sample consisted of 49 elite basketball players which comprised 31 male basketball

players with ages ranging from 11 and 35 years (M= 18.26, SD=6.32), and 18 female

basketball players with ages between 15 and 27 (M=18.06, SD= 2.26). Players were

recruited from the South Australian Sports Institute, and several teams from the Victorian

Basketball League including the Frankston Blues, Kilsyth Cobras, Bulleen Academy, and

Sanderingham Sabres. Each participant was required to be either part of an elite

development squad or to be playing at representative level in the VLB/SEABL 9both of

which are semi-professional leagues)

Materials

Emotional Intelligence was measured using the Swinburne University Emotional

Intelligence Test (SUEIT) (ά = 0.83), developed by Palmer and Stough in 1999. The

SUEIT is a self-report inventory, which indexes the way people typically think, feel, and

act with emotions according to the five factor model of the SUEIT.

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Results and Discussion

Descriptive statistics including means and standard deviations for the emotional

intelligence measures and the five subscales, age and shooting performance accuracies

are presented in Table 2 below.

                                    Table 2 About Here

All of the collected variables were then correlated in order to determine whether any

relationships exist between any of the basketball performance measures and emotional

intelligence. Because the focus of the present research was player performance and not

actual court time, correlations were calculated between performance variables and EI

whilst controlling for the number of games played and the average minutes on court, as

players who play more games and spend more time on court are likely to show better

performance outcomes in terms of outcome variables such as total points scored etc.

Table three shows the calculated correlations for all of the variables.

                                    Table 3 About Here

Emotional Intelligence and Shooting Performance (Offense)

To test for the prediction that players with higher levels of emotional intelligence would

show greater accuracies when shooting from the field, from the three point line, and from

the foul shot line, each of the three shooting accuracies were correlated with overall EI.

The results indicated that there was no significant relationship between the three

measures of shooting accuracy and overall emotional intelligence. Additionally shooting

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accuracies were also correlated with the individual dimensions of emotional intelligence,

and while it was predicted that emotional management and emotional control would both

show positive relationships with all three shooting accuracies, only weak correlations

were observed. These results may be due to the fact that the results were based on a

limited number of games, with some players playing as little as 5 games. The results may

also be dependent on the number of participants, and as the sample size was relatively

small, there was insufficient statistical power to show significant relationships. While the

shooting accuracies were the main indicators of player shooting performance, the number

of shots taken along with the number of shots made were also correlated with EI, as there

are times when performance is indicated not only by the accuracy of the shots taken, but

also by the number of shots taken. When correlated with the number of field shots taken

Emotional management showed a moderate correlation (r= .44, p= .01), indicating that

players who take more shots from the field tend to have greater emotional management.

Similarly when correlated with field shots taken emotional control showed a moderate-

strong correlation (r= .59, p=.000), indicating that players who take more shots from their

field also tend to show greater emotional control. It was also found that Emotional

Management(r= .41, p= .015) and emotional control (r= .62, p=.00) both showed

moderate correlations with the number of field shots made, indicating that those who are

better able to control and manage their emotions make more shots from the field

throughout the season.

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When assessing the relationship between emotional intelligence, the components of

emotional intelligence and shots from the three-point line it was evident that the

relationships were similar to those found for field shots.

The final measure of shooting performance was that of the free throw shot accuracy.

Again, contrary to predictions, accuracy from the free throw line showed no significant

relationships with any of the components of emotional intelligence. Emotional control (r=

.43, p= .011) and emotional management (r= .43, p=.012) on the other hand did show

significant correlations with the number of shots taken from the free throw line indicating

that players who have the ability to control and manage their emotions generally take

more shots from the three point line. Similarly, as would be expected, those who have

higher levels of emotional control (r= .47, p=.005) and emotional management (r= .49,

p=.004) are significantly more likely to score more points from the free throw line.

It was also found that there was a strong correlation between emotional control and the

total points scored and a moderate-strong correlation between emotional management and

total points scored, indicating that players with higher levels of emotional control (r= .63,

p= .000) and emotional management (r= .44, p= .009) are significantly more likely to

score throughout the season.

Emotional Intelligence, Rebounding and Defensive Plays (Defense)

                                             23

While the main performance measure in basketball is the ability to score points, the

ability to limit the number of points scored by the opposition is important. It was

predicted that those who are better at understanding the emotions of others and the

environment would have better defensive performance as they have the ability to read

others facial expressions, body movements allowing them to predict the next move.

Contrary to this expectation, there were no correlations between Understanding Emotions

and the defensive plays such as defensive rebounding, blocked shots and steals.

Interestingly, individuals who made more blocked shots (r=-.417, p=.014) and more

steals (r=-.356, p=.031) were less able to recognize and express emotions within

themselves.

While it was predicted that those who are better able to understand emotions in others

and the environment would show higher rebounding rates, both defensive (r= .311, p=

.053) and offensive (r=.427, p=.012) rebounding correlated positively with Emotional

Management, suggesting that players who are better at managing their emotions make

more offensive and defensive rebounds throughout the season.

As this was the first study linking basketball statistics and performance with EI, there

were a number of tentative hypotheses. Despite this there were a number of statistically

significant relationships between different EI dimensions and basketball statistics that

suggest that EI assessment and training may be useful in elite basketball performance.

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Table 1

Summary of Hypothesized relationship between dimensions of the SUEIT

and the three sporting categories.

                 Emotional         Emotional        Understanding     Emotional    Emotional
Sport            Recognition and   reasoning        the emotions of   Management   Control

                 Expression                         others

Type

Open-skilled             -                -                  +             +            +

Individual

Open-skilled            +                +                   +             -             -

Team

Closed-skilled           -                -                  -             +             -

                                               25

TABLE 2
Means and Standard Deviations of Emotional Intelligence, Age and Performance
Indicators
Measure                                                Mean      Standard Deviation
Age                                                    18.18     5.175
Emotional Intelligence                                 209.94    20.98
Emotional Recognition and Expression                   36.63     4.73
Understanding Emotions External                        70.12     8.42
Emotional Reasoning                                    36.04     4.97
Emotional Management                                   39.18     5.24
Emotional Control                                      27.95     5.05
Field Shot Accuracy                                    39.42     8.82
Three point Accuracy                                   18.01     16.41
Free Throw Accuracy                                    62.02     13.87
Total Points Scored                                    159.80    147.44

                                        26

Table 3.: Correlations for each of the measured variables
          EREXP        UEX          EDC           EM        EC        EI
AGE       .0032        .0907        .1081         .0948     .3043     .0053
SEX       -.0441       -.3142       -.1362        -.1829    .1843     -.1570
FLDT      .1715        .2715        -.1010        .4358*    .5886**   .3758*
FLDM      .0337        .1440        -.1451        .4088*    .6240**   .2913
FLDA      -.2579       -.2545       -.0782        .0810     .3076     -.0680
TPST      .2068        .0047        -.0182        -.1169    -.0273    .0045
TPSM      .1701        .0179        -.0481        -.0661    .0479     .0270
TPSA      .1933        -.0472       -.0308        -.1350    .0906     .0049
FTST      .2211        .2452        -.1410        .4271*    .4313*    .3249*
FTSM      .2479        .2917        -.0606        .4868*    .4736*    .3921*
FTSA      .1717        .2576        .3045         .1380     .0177     .2410
OREB      -.0058       .1879        .1015         .4274*    .2856     .2735
DREB      -.1577       -.0523       -.2020        .3114     .2712     .0498
TREB      -.0998       .0519        -.0791        .3833*    .2950     .1532
PTST      .1280        .1945        -.1467        .4420*    .6310**
PPG       -.0087       .0760        -.1936        .2875     .4998*    .1834
ASS       -.0090       -.0060       -.0831        -.1418    -.0938    -.1031
BLK       -.4175*      -.1729       -.1850        .1151     .1516     .1264
STL       -.3565*      -.1410       -.1549        -.1661    -.2640    -.2724
TNR       .1418        .1165        -.0041        .2137     -.0530    .1131
Note * p

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