Does Emotional Intelligence Predict Athletes’ Motivation to Participate in Sports?

Abstract

The relationship between emotional intelligence (EI) and successful athletic performance has been previously recognized, but there remains a need to investigate how EI impacts athletes’ sports motivation. This cross-sectional study investigated how different EI dimensions related to athletes’ motivation among 239 adult basketball players (129 females) aged 18-34 years. Our research participants completed questionnaires that included the self-reported Emotional Intelligence Scale and Sport Motivation Scale II. We found significant correlations between total EI and intrinsic, integrated, identified, and introjected regulation. Higher EI was negatively related to athletes’ amotivation. More specifically, the self-reported abilities to perceive emotion and manage others’ emotions were significantly related to intrinsic, integrated, and identified regulation, and only managing one’s own emotions negatively related to athletes’ amotivation.

Keywords

trait emotional intelligence sport motivation basketball players

Introduction

Sport provides an environment in which individuals must motivate themselves intensely to achieve their goals. As a result, athletes experience both positive and negative emotions in their sport competitions when facing stress and rivalry tension (Campo et al., 2017; McCarthy, Allen, & Jones, 2013). Thus, athletes’ abilities to understand and control their own emotions and those of other sport participants are important and are related to emotional intelligence (EI; Ciarrochi, Forgas, & Myer, 2001). EI refers to individual responses to intrapersonal or interpersonal emotional information, and it encompasses the identification, expression, understanding, and regulation of personal or others’ emotions (Mayer & Salovey, 1997). It should be noted that EI has been conceptualized both as an ability (Mayer, Caruso, & Salovey, 1999) and a trait (Petrides, 2009). Although the EI ability model may provide the best fit within applied sport psychology (Myer & Fletcher, 2007), trait-based EI is also predominant in sports research (Laborde, Dosseville, & Allen, 2016).

Over the past decade, there has been an increase in EI research in the context of sports activities (Laborde, Dosseville, et al., 2016). Although the EI construct is important for both coaches and athletes, athletes’ EI has received more research attention. This is not surprising, since the capacity to recognize and regulate emotions enables athletes to perform better (Crombie, Lombard, & Noakes, 2009; Zizzi, Deaner, & Hirschhorn, 2003). Studies have revealed that EI affects sport performance satisfaction in that athletes with higher EI treat stressful situations as less stressful (Laborde, Dosseville, Guillen, & Chavez, 2014) and may be able to tolerate more stress without a decrease in performance (Tok, Binboğa, Guven, Çatıkkas, & Dane, 2013). Furthermore, recent findings have indicated a negative relationship between individual and team sports athletes’ anxiety and EI (Castro-Sánchez, Zurita-Ortega, Chacón-Cuberos, López-Gutiérrez, & Zafra-Santos, 2018; Lu, Li, Hsu, & Williams, 2010). Research in relationships between trait EI and changes in emotional states over the course of a six-day endurance event showed that trait emotional intelligence was associated with pleasant emotions, including more calmness and happiness, coupled with less anger, confusion, depression, fatigue, and tension (Lane & Wilson, 2011). A study with student athletes showed that EI correlated with pleasant emotional states before both optimal and dysfunctional performance (Lane et al., 2010).

Higher EI levels among athletes were associated with such other psychological skills as self-talk, goal-setting, imagery, and relaxation skills in competition and practice (Lane, Thelwell, Lowther, & Devonport, 2009). A recent study of marathon runners also supported a relationship between athletes’ results expectations and trait EI (Rubaltelli, Agnoli, & Leo, 2018). Furthermore, studies found a positive relationship between athletes’ trait EI and the quality of their decisions (Vaughan, Laborde, & McConville, 2018), meaning that higher EI enables athletes to evaluate situations more effectively by viewing risks as opportunities rather than threats and then making better decisions on risk-related tasks (Panno, 2016). Through its association with the level of athletes’ mental toughness, EI helps athletes assess and respond to challenges they face and predicts more favorable sport outcomes (Cowden, 2016).

The pursuit of sports results requires much effort that does not always lead to success. Motives encouraging athletes to continue in sports participation remain important in contemporary sport (Lindahl, Stenling, Lindwall, & Colliander, 2015). As motives can be either antecedents or outcomes, athletes’ motivations may be intrinsic or extrinsic. In addition, the motivation process is dynamic, and it may vary, depending on the athlete’s gender (Kilpatrick, Hebert, & Bartholomew, 2005) or changing sports experience (Stenling, Lindwall, & Hassmén, 2015). A recent review of contemporary research on competitive sports motivation (Clancy, Herring, MacIntyre, & Campbell, 2016; Lindahl et al., 2015) showed that Self-Determination Theory has been a dominant motivational theory, with intrinsic or extrinsic components (Deci & Ryan, 2000). Extrinsic and intrinsic motivations are not discrete categories but represent points on a unique continuum (Deci & Ryan, 2002). Intrinsic motivation relates to motives arising from inherent satisfaction with the activity itself, while amotivation is related to a lack of motivation or tendencies to complete activities for neither intrinsic nor extrinsic reasons (Deci & Ryan, 2000). Between intrinsic motivation and amotivation, there are different extrinsic motivation types, ranging from no or low degrees of internalization (external regulation and introjected regulation) to high degrees of internalization (identified regulation and integrated regulation; Deci & Ryan, 2000). Studies in sport showed that self-determined motivation was associated with better sports performance (Gillet, Vallerand, & Patty, 2013), higher athletes’ interest and enjoyment, and a future intention to continue the sport (Iwasaki & Fry, 2013).

Motivation is not a sole reason for behavior; behavior can also be influenced by other variables, such as experiences of pleasure, joy, and competition (de Franco Tobar, Meurer, & Benedetti, 2013). Although negative emotions are experienced in sport, the ability to control them can enhance motivation for sports (Ramajayam, 2017). An interesting issue is the impact of EI on athletes’ motivation. Previous studies have supported the notion that motivation is a factor related to EI, but at the same time is not a component of the EI construct (Christie, Jordan, Troth, & Lawrence, 2007). Emotion is related to the individual’s internal processes and is also an important dimension of needs, plans, and goals and serves as a motivator of actions (Young, Paseluikho, & Valach, 1997). Some previous studies on EI and motivation found a relation between those two constructs (Magnano, Craparo, & Paolillo, 2016; Mega, Ronconi, & De Beni, 2014). Another study on achievement motivation also found that achievement motivation toward goals, tasks, and targets directly and indirectly depends on the EI level (Kumar, 2016). Persons with high EI are able to appropriately apply their emotions in different situations, and studies show that if the situation requires high motivation, emotional intelligence can enhance motivation (Jahroni & Ghaleh, 2015). Thus, studies suggest that EI can affect a person’s motivation.

As aforementioned studies on EI and motivation are not directly related to sport settings, it is not yet clear how much EI determines athletes’ motivation. Thus far, only a few studies have investigated this interface. A study with canoeists showed an interrelation of EI and motivation predicting sports performance (Arribas-Galarraga, Saies, Cecchini, Arruza, & Luis-De-Cos, 2017). To the best of our knowledge, only one study (Kajbafnezhad, Ahadi, Heidarie, Ashari, & Enayati, 2012) has directly considered the association between athletes’ EI and motivation. These researchers found that higher trait EI significantly predicted athletes’ success motivation, although the participant sample was comprised of only male athletes. Sparse research in this area encourages further investigation of EI and motivation among athletes, especially since an understanding of the relationship between EI and sports motivation among athletes should enhance our understanding of how athletes might better manage emotions to increase their sports motivation.

The present study investigated relationships between self-reporting measures of EI and sports motivation. In addition, we sought to analyze how different EI dimensions might predict athletes’ sports motivation. We focused on team sport athletes of different sports levels and experience. Since higher EI has been found to be related to better athletic performance (Crombie et al., 2009), more positive emotions (Lane et al., 2010; Lane & Wilson, 2011), and greater sports performance satisfaction (Laborde et al., 2014), we hypothesized that greater self-determined sports motivation among athletes would be positively associated with their higher trait EI. Concerning relationships between different dimensions of EI and sports motivation, we had no a priori hypotheses.

Method

Participants

Research participants were 239 adult basketball players, ranging from 18-34 years of age (129 females, 110 males; M_age = 21.81, SD = 3.09). They had been practicing their sport for an average of 10.18 years (SD = 4.19). We divided them into two experience groups by their median experience level of 10.0 years (less experienced group, n = 113; more experienced group, n = 126). All participants were involved in only one sport competitively, but participants competed at different levels of their sport: regional league (n = 82), national league (n = 46), and international league (n = 111).

We obtained ethical approval for the study from the University Research Ethics Committee. Participants were recruited from different Lithuanian regional basketball teams. Researchers attended training sessions and described the study's aim to the athletes, who were then given the option to participate. Participants were informed that they were not obligated to respond to all questions and were reminded that they could terminate their participation in the study at any time. After oral informed consent, participants were asked to complete the EI and Sport Motivation Scale II (SMS-II) scales. In addition, participants were asked to answer a question about the duration of their sport experience in their current sports. Participants needed 20-25 minutes, on average to complete the questionnaire.

Measures

Emotional intelligence

We used the Schutte et al. (1998) self-report EI scale to measure EI. We chose this scale because it is one of the most commonly used instruments for EI assessment (Laborde, Dosseville, et al., 2016), and it was previously validated in the Lithuanian language (Malinauskas & Šniras, 2010). The Scale contains 33 self-referencing statements and requires participants to rate the extent to which they agree or disagree with each statement on a scale from 1 (strongly disagree) to 5 (strongly agree). Schutte et al. (1998) recommended the use of the total sum score of all items as a single factor. However, other studies suggested a four-factor subscale factor analytic solution of the EI construct: perception of emotion, managing one’s own emotions, managing others’ emotions, and utilization of emotion (Ciarrochi, Chan, & Bajgar, 2001). Most recent studies in Lithuania, where the EI scale was applied, use four subscale analyses (Malinauskas, Dumciene, Sipaviciene, & Malinauskiene, 2018; Terentjeviene et al., 2018). In our study, we used total sum score of EI, and average scores for all four of these EI subscales. Cronbach’s α for the EI subscales were: perception of emotions, 0.74; managing one’s own emotions, 0.68; managing other’s emotions, 0.76; and utilization of emotion, 0.71; and total EI was 0.85.

Sport motivation

Athletes’ motivation was assessed with the self-report instrument, SMS-II (Pelletier et al., 2013). This scale is a modified version of the SMS (Pelletier et al., 1995), which was also validated in the Lithuanian language (Grajauskas & Razmaite, 2017). The SMS-II consisted of 18 items measuring six types of motivation (intrinsic, integrated, identified, introjected, external, and amotivated). Participants’ motivation was assessed using a seven-point scale ranging from 1 (does not correspond at all) to 7 (corresponds completely). In the current study, Cronbach’s α for the SMS-II were: intrinsic, 0.85; integrated, 0.82; identified, 0.81; introjected, 0.69; external, 0.87; amotivated, 0.70; and the oveall was 0.84.

Data Analysis

We first reviewed the data distribution for normality. We conducted the Pearson correlation analysis to measure relationships between trait EI and motivation. Next, we applied analyses of variance (ANOVAs) to investigate differences in the global EI score according to gender, sports experience, and sports level. We ran multivariate analyses of variance to investigate differences in EI subscales and motivation using gender, sports experience, and sports level. Finally, in order to answer our main research question, the effect of EI on motivation of athletes, we performed Multiple Regression Analyses. We used the SPSS version 24.0 software package for statistical analysis and set statistical significance a p < .05.

Results

Descriptive Statistics and Correlations

Means, standard deviations, and correlations among study variables are presented in Table 1. As can be seen, the highest mean value among EI subscales for these participants was for managing one’s own emotions; the lowest score was for emotion perception. We found positive significant correlations between total EI and motivation subscales of intrinsic, integrated, and identified regulation. Regarding all types of EI, there were also positive significant correlations with intrinsic, integrated, and identified regulation. Amotivated regulation was significantly negatively correlated with total EI and perception and with managing one’s own emotions.

Table 1.

Descriptive Statistics, Correlations Between EI and Sport Motivation.

Variables	M	SD	1	2	3	4	5	6	7	8	9	10	11
1. Overall EI	122.23	15.90
2. Perception of emotion	3.56	0.47	.75**
3. Utilizing emotion	3.73	0.60	.75**	.52**
4. Managing own emotions	3.82	0.64	.82**	.54**	.50**
5. Managing others’ emotions	3.68	0.60	.83**	.56**	.67**	.60**
6. Intrinsic regulation	5.75	1.20	.26**	.22**	.19**	.16*	.26**
7. Integrated regulation	5.77	1.07	.45**	.41**	.29**.	.37**	.40**	.63**
8. Identified regulation	5.50	1.15	.42**	.31**	.35**	.25**	.46**	.56**	.65**
9. Introjected regulation	5.27	1.17	.24**	.12	.23**	.17*	.26**	.45**	.58**	.54**
10. External regulation	3.74	1.62	.11	.06	.08	.03	.09	.14*	.18**	.04	.40**
11. Amotivated regulation	2.87	1.90	−.19**	−.22**	−.02	−.25**	−.10	−.16*	−.28**	−.12	−.14*	.33**	−

Note. M = mean; SD = standard deviation; EI = emotional intelligence.

*p < .05. **p < .01.

EI and Sport Motivation Differences According to Participant Gender, Sport Experience, and Sport Level

A one-way ANOVA showed that females, compared to males, scored significantly higher on total EI, F(1, 239) = 3.88, p < .05, partial η²= .02. In comparing EI by athletes’ sport experience, no significant difference emerged. A two-way ANOVA did not reveal any significant total EI and sport level effect. The mean and standard deviation values for total EI scores by gender, sport experience, and sport level are reported in Table 2.

Table 2.

Mean and Standard Deviation Scores for EI and Sport Motivation by Gender, Sport Level, and Sport Experience.

Variables	Gender		Sport level			Sport experience
	Male	Female	Regional	National	International	≤ 10 year	>10 year
	M (SD)	M (SD)	M (SD)	M (SD)	M (SD)	M (SD)	M (SD)
Overall EI	120.05 (17.60)	124.09 (14.09)	120.73 (16.79)	119.25 (11.33)	123.68 (15.98)	121.88 (16.52)	122.54 (15.37)
Perception	3.44 (0.51)	3.66 (0.42)	3.47 (0.46)	3.54 (0.37)	3.62 (0.49)	3.51 (0.48)	3.60 (0.46)
Utilizing	3.67 (0.62)	3.77 (0.59)	3.65 (0.60)	3.57 (0.43)	3.80 (0.630	3.72 (0.56)	3.73 (0.64)
Managing own	3.78 (0.59)	3.85 (0.54)	3.79 (0.75)	3.70 (0.42)	3.85 (0.61)	3.83 (0.76)	3.81 (0.52)
Managing others’	3.56 (0.63)	3.78 (0.56)	3.56 (0.57)	3.65 (0.55)	3.76 (0.62)	3.71 (0.63)	3.66 (0.58)
Intrinsic	5.96 (1.07)	5.57 (1.28)	5.99 (0.98)	5.68 (1.67)	5.61 (1.21)	5.84 (1.01)	5.66 (1.35)
Integrated	5.78 (1.01)	5.76 (1.120	5.67 (0.96)	5.69 (1.18)	5.84 (1.12)	5.74 (0.98)	5.79 (1.15)
Identified	5.58 (0.92)	5.42 (1.29)	5.48 (0.99)	5.21 (1.39)	5.55 (1.19)	5.54 (1.07)	5.45 (1.22)
Introjected	5.43 (0.89)	5.14 (1.35)	5.33 (0.87)	5.32 (1.28)	5.22 (1.31)	5.23 (1.07)	5.31 (1.25)
External	3.92 (1.71)	3.60 (1.71)	3.74 (1.47)	3.47 (1.78)	3.80 (1.84)	3.32 (1.63)	4.13 (1.70)
Amotivated	3.14 (1.81)	2.63 (1.87)	2.70 (1.69)	2.79 (1.81)	2.99 (2.04)	3.02 (1.90)	2.72 (1.90)

M = mean; SD: standard deviation; EI = emotional intelligence.

Within a one-way multivariate analysis of variance with the four EI scales as the dependent variables and gender as the independent variable, there was a significant primary effect for gender, Pillai’s Trace = .09, F(4, 237) = 5.57, p < .001, partial η²= .09. Subsequent univariate analysis showed a significant gender difference on two EI subscales: perception of emotion, F(1, 237) = 13.47, p < .001, partial η²= .05; and managing other emotions, F(1, 237) = 7.99, p < .001, partial η²= .04. Multivariate analysis with the EI subscales as dependent variables and sport level as the independent variable revealed no significant effects, making further univariate analyses with these variables unnecessary. Similarly, there were no significant effects between EI subscales and sport experience. The mean and standard deviation values for the EI subscales by gender, sport level, and sport experience are reported in Table 2.

Multivariate analysis, with the use of the six sport motivation types as dependent variables and gender as the independent variable revealed significant multivariate effects between sport motivation and gender, Pillai’s Trace = .08, F(6, 239) = 3.10, p < .01, partial η²= .07. Follow-up analysis of variance revealed significant differences only on the subscales of intrinsic, F(1, 239) = 6.10, p < .01, partial η²= .03, and amotivated regulation, F(1, 239) = 4.37, p < .05, partial η²= .02. Multivariate analysis also revealed significant effects of sport level on sport motivation, Pillai’s Trace = .12, F(12, 239) = 2.20, p < .01, partial η²= .05, but univariate analysis revealed no significant differences on any specific sport motivation subscales. Finally, multivariate analysis with sport experience as an independent variable revealed a significant effect, Pillai’s Trace = .13, F(6, 239) = 4.83, p < .001, partial η²= .11, and follow-up univariate analysis revealed a significant difference only for the external regulation subscale, F(1, 239) = 13.98, p < .001, partial η²= .06. The mean and standard deviation values for sport motivation by gender, sport level, and sport experience are reported in Table 2.

Emotional Intelligence and Sport Motivation

Multiple regressions were conducted to investigate the influence of EI on sport motivation, using total EI as the predictor variable and sport motivation as dependent variables while controlling for gender, sport level, and sport experience (see Table 3). Six regression analyses for each type of sport motivation (intrinsic, integrated, identified, introjected, external, and unmotivated) were statistically significant. Analysis showed that gender (β = –.15, p < .05) and total EI (β = .29, p < .001) were statistically significant predictors of intrinsic regulation. A significant effect of EI (β = .45, p < .001) was only a significant predictor of integrated regulation. Gender (β = −.18, p < .01) and EI (β = .43, p < .001) were significant predictors of identified regulation. Gender (β = −.16, p < .05) and EI (β = .25, p < .001) were also significant predictors of introjected regulation. For the external regulation, the effect of EI was not established, but gender (β = −.15, p < .05) and sport experience (β = .25, p < .001) were significant predictors. Analyses showed that gender (β = −.23, p < .01), sport level (β = .24, p < .01), and EI (β = −.18, p < .01) were significant predictors for amotivated regulation.

Table 3.

Multiple Linear Regression Analysis for EI Prediction on Sport Motivation.

Variable	Intrinsic regulation		Integrated regulation		Identified regulation		Introjected regulation		External regulation		Amotivated regulation
Variable	SE	β	SE	β	SE	β	SE	β	SE	β	SE	β
Gender	.18	−.15*	.15	−.11	.16	−.18**	.18	−.16*	.26	−.15*	.28	−.23**
Sport level	.10	−.08	.08	.09	.09	.11	.10	.01	.14	.03	.16	.24**
Sport experience	.15	−.04	.13	−.01	.14	−.05	.15	.05	.22	.25***	.25	−.11
Overall EI	.02	.29***	.01	.45***	.01	.43***	.02	.25***	.02	.12	.01	−.18**
Model F	7.37***		15.56***		14.48***		5.18***		5.44***		5.78***
R ²	.11		.21		.20		.08		.09		.09

Note. EI = emotional intelligence.

*p < .05. **p < .01. ***p < .001.

Second, several regression analyses were conducted to investigate the influence of EI types on sport motivation. All regressions were statistically significant (Table 4). Gender was also significantly associated with all types of sport motivation. When examining intrinsic regulation as a specific type of motivation, the two EI subscales of perception of emotion (β = .19, p < .05) and managing others’ emotions (β = .25, p < .01) were significant predictors. For the motivation scale of integrated regulation, again two of the four EI predictor variables were statistically significant, with perception of emotion showing a higher Beta value (β = .28, p < .001) than managing others’ emotions (β = .23, p < .01). These two predictor variables were also statistically significant for predicting the motivation subtype of identified regulation, with the EI subscale of managing others’ emotions Beta value (β = .44, p < .001) higher than that of perception of emotion (β = .15, p < .05). Further analyses showed that only the EI subscale of managing others’ emotions (β = .20, p < .05) significantly predicted introjected regulation. Results revealed that the EI subscale of managing one’s own emotions negatively predicted amotivated regulation (β = –.28, p < .001).

Table 4.

Multiple Linear Regression Analysis for EI Dimensions Prediction on Sport Motivation.

Variable	Intrinsic regulation		Integrated regulation		Identified regulation		Introjected regulation		External regulation		Amotivated regulation
Variable	SE	β	SE	β	SE	β	SE	β	SE	β	SE	β
Gender	.18	−.19**	.15	−.15*	.16	−.22**	.18	−.16*	.27	−.16*	.28	−.22**
Sport level	.10	−.10	.08	.09	.09	.07	.10	−.02	.14	.02	.15	.22**
Sport experience	.15	−.04	.13	.01	.14	−.03	.15	.07	.23	.25***	.24	−.10
Perception	.21	.19*	.18	.28***	.19	.15*	.21	−.02	.31	.01	.33	−.14
Utilizing	.17	−.01	.14	−.06	.15	.04	.17	.11	.25	.02	.27	.15
Managing own	.15	−.07	.13	.11	.14	−.10	.15	.02	.22	−.06	.24	−.28***
Managing others’	.19	.25**	.16	.23**	.17	.44***	.19	.20*	.28	.14	.30	.04
Model F	5.31***		10.17***		11.30***		3.46**		3.16**		5.65***
R ²	.14		.24		.26		.10		.09		.15

Note. *p < .05. **p < .01. ***p < .001.

Discussion

The primary aim of this paper was to investigate the relationship between athletes’ trait EI and their sports motivation. In support of our hypothesis, overall trait EI was positively associated with athletes’ more self-determined sport motivation. In a more detailed evaluation of these results, EI was previously found to be more positively correlated with autonomous or want-to motivation, which reflects a person’s genuine interest and values in an activity (Deci & Ryan, 2000). Thus, in prior research, higher EI among basketball players was related to their intrinsic motivation when motives for acting were derived from satisfaction in the behavior itself (Deci & Ryan, 2002). It should be noted that, among all the various components of sport motivation, higher EI significantly predicted two motivations subscales of integrated and identified regulations. These are the most autonomous types of extrinsic regulation. Integrated regulation means that athletes accept the behavior as part of themselves such that it is congruent with their goals, objectives, and needs. Identified regulation means that athletes’ behavior is experienced as personally important and worthwhile. Our findings are therefore in line with previous research showing that athletes’ successful performance was related to higher EI (Crombie et al., 2009). Athletes with higher EI are better able to control their emotions in stressful situations (Laborde et al., 2014) and they better respond to repeated bouts of hard exercise (Lane & Wilson, 2011). Thus, if a situation requires higher motivation, EI can enhance an athlete’s motivation. Commenting on our research findings, it is important that athletes with higher EI have been previously found to be more inclined to consider sport problems as learning opportunities (Jahroni & Ghaleh, 2015) and competition as more of a challenge than an obstacle (Laborde et al., 2014). In addition, past researchers found that if an athlete experiences fewer obstacles (Malyavskaya, Inzlicht, Hope, & Koestner, 2015), he/she feels more competent when faced with potentially threatening situations as a result of better emotional regulation (Weinstein, Deci, & Ryan, 2011). In this past research, EI was associated with more autonomous motivation, and that is in line with our results. The same association might explain our results regarding the negative relationship between athletes’ EI and their amotivated regulation. Within self-determination theory, amotivation is the least self-determined type of motivation (Deci & Ryan, 2002), and it is characterized by a lack of engagement and motivation. EI’s negative association with amotivation suggests that EI training may be effective in increasing emotional regulation skills and encouraging more autonomous motivation.

The second main aim of our study was to measure how different aspects of athletes’ sport motivation are associated with different dimensions of emotional intelligence. First, among the various EI factors, only emotion perception positively related to greater autonomous motivation among these athlete participants. Managing others’ emotions (which describes the aspect of EI in relation to others) also positively related to athletes’ motivation in sports but not for motivation subscales of external regulation and amotivation. This suggests that in addition to recognizing their own emotions, athletes’ ability to recognize others’ emotions is important to their want-to motives. This finding partially aligns with previous studies that established a positive relationship between EI and success motivation (Kajbafnezhad et al., 2012). It is important to consider that all athletes in this study were in team sports. Although previous studies did not reveal clear trait EI differences between athletes in individual and team sports (Laborde, Guillén, & Watson, 2017), some characteristics of team sports are important to interpreting these data. In contrast to individual sports, team sports athletes are involved with teammates and spend time training together and interacting often with each other (Kajbafnezhad, Ahadi, Heidarie, Askari, & Enayati, 2011), which also allows the pressure felt by athletes during the training sessions and competitions to be shared between members of a team (Webster, Hardy, & Hardy, 2017). In addition, competition training and participation require both the ability to overcome stress and the ability to regulate one’s own emotions and those of others on the team (Laborde, Dosseville, et al., 2016; Laborde, Guillén, & Mosley, 2016). Thus, managing the emotions of others is particularly important in team sports and predicting players’ motivation. Interestingly, athletes’ sole management of their own emotions was negatively related to their amotivation, suggesting that lack of emotion control could be one factor that is related to lack of interest in the activity itself. Although this interpretation is controversial, it would seem important to compare different EI dimensions according to different types of sport and perhaps especially any differences related to team versus individual sport participation.

When analyzing EI and sport motivation data, sociodemographic characteristics of athletes also deserve attention. A previous systematic analysis highlighted the importance of gender differences in EI (Laborde, Dosseville, et al., 2016). Our findings support previous studies finding that females had higher levels of trait EI, relative to males (Schutte et al., 1998). Women also scored significantly higher than men on perception of emotion and managing others’ emotions, which contradicts another study (Laborde et al., 2014). Although men usually cope better with stress, in team sports, it is also important to consider others’ perspectives, and this consideration is more characteristic of women than of men. Previous studies showed that athletes with higher expertise levels coped better with stress (Laborde & Raab, 2013). Consistent with Laborde et al. (2014), however, we did not find expertise level differences in total EI and in EI dimensions.

In an overview of previous research, Clancy et al. (2016) suggested that intrinsic motivation is more prevalent in women than in men. This finding does not coincide with our research data, as we found that male players were more intrinsically motivated compared to women. However, we also found amotivation to be more common for men. Perhaps men have a greater desire to compete, but in team sports, these opportunities are not easily implemented, since, even on higher level teams, the excellence levels are not the same for all players. As previous studies showed, even successful elite athletes could be characterized by non-self-determined motivation (Gillet et al., 2013), consistent with our findings of no motivation differences according to competitive levels. We assume that athletes’ competitive level is not equally interpreted in different studies, and this variability is even more challenging with regard to team sports.

Some limitations of the current study include problems making causal inferences from cross-sectional correlative data. Longitudinal studies would allow a better assessment of how EI changes relate to sports motivation. We revealed links between these basketball players’ EI and sports motivation, and it would be useful to verify these associations among players in other sports teams. We used the four-factor EI structure that has not been confirmed in all previous studies. In addition, other studies sometimes used other trait EI evaluation tools (such as TEIQue) with a different factor structure. Caution is needed when comparing the results of these different studies. Also, this study did not evaluate the coach’s activity factor. Since the coach and the motivational environment created by him/her are particularly important in team sports, further research should focus on examining the role of coaching efficacy when studying athletes EI and motivation constructs. Finally, since this study was rare in its inclusion of women, and women and men differ in aspects of EI, it is unclear whether our findings with regard to EI and motivation were unique to our gender-integrated participant sample. Further research with greater numbers of women within participant groups can better delineate how men and women may differ both in EI and in its relationship to motivation.

In conclusion, the present study found that trait EI was positively associated with basketball players’ more self-determined sport motivation. We also found that different types of EI differently predicted athletes’ sport motivation. Specifically, perception of their own emotions and managing others’ emotions related more to self-determined motivation. Thus, team sports athletes’ ability to recognize their own and others’ emotions is important for their want-to motives.

Footnotes

Acknowledgments

The authors would like to thank the athletes who participated in this study.

Article Notes

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