Authors: F. Moen, K. Myhre, K. A. Andersen and M. Hrozanova

Corresponding Author:
Frode Moen
E-mail address: [email protected], Tel. : +47 932 487 50
Postal address: Department of Education and Lifelong learning, Norwegian University of Science and Technology, N-7491 Trondheim, Norway

Frode Moen is currently the head manager of the Olympic Athlete program in central Norway, where he also has a position as a coach / mental trainer for elite athletes and coaches. He also is an associate professor at the Department of Lifelong Learning and Education at the Norwegian University of Science and Technology. He previously has worked as a teacher in high school where sport was his major subject, and he has been a coach for the national team in Nordic combined in Norway for several years. Frode received his Ph.D. in coaching and performance psychology from the Norwegian University of Science and Technology. His research focuses mainly on coaching in business, coaching in sport, communication, performance psychology and relationship issues.

Emotions and Performance in Elite Women Handball

ABSTRACT
This article looks at how emotions are associated with performance in elite women handball in Norway. The results show that positive emotions such as joy (exemplified by feeling satisfied, pleased, and happy), serenity (exemplified by feeling calm, balanced, and hopeful), interest (exemplified by feeling curious, interested, and immersed) and ecstasy (exemplified by feeling exhilarated, enthusiastic, and convinced) are positively associated with subjective performance. On the other hand, negative emotions such as anger (exemplified by feeling aggressive and angry), fear (exemplified by feeling nervous and afraid), sadness (exemplified by feeling sad and depressed) and remorse (exemplified by feeling ashamed and guilty) were found to be negatively associated with subjective performance. The present results showed that joy, serenity, and remorse uniquely explained 51% of the variance in subjective performance.

In general, results showed that positive emotions were most intense when the female elite athletes experienced positive events during trainings and matches and that negative emotions were most intense when the athletes experienced too challenging and negative events during trainings and matches. Triggers that elicited positive emotional responses in female elite athletes in the current study were mostly proactive in nature. The results are discussed in regard of applied implications and possible future research.

Keywords: emotions, sport, handball, performance

INTRODUCTION
Norway has a long and successful history in women’s handball. In the last two decades, the national team has won the European championship seven times, the World championship three times and the Olympic games two times. Several variables may be used to explain success in handball, amongst them coaching, leadership, and physiological variables (15, 27, 34). Accordingly, adequate emotions are found to be important for optimal development and performance in sport (11, 25, 37). The relationship between emotions and performance in sport may be explained with the psychological effect emotions have (16, 28), and the biological reactions that acutely follow emotions and influence the biochemical processes of the body (26). Thus, emotions have the potential to positively or negatively influence performance in sport (1, 12, 24). The current study aims to investigate how emotions influence performance in woman handball and what stimuli that activate these emotions.

Emotions
Emotions are defined as rapid, complex, electrochemical bodily responses to an actual or imagined stimulus that lead to physiological, experiential, and behavioral changes (11). Thus, emotions involve a subjective experience of a stimulus, whereas it is the athlete’s perception and interpretation of that stimulus that activates the type and strength of consequential emotional response (25, 39). Therefore, emotional responses may be of different valence and of varying intensities.

Regarding valence, emotional responses are often categorized in three different categories. These categories play different roles in the regulation of sport behavior (2, 20, 41), and include hedonic, negative, and eudaimonic emotions. Firstly, hedonic emotions include positive emotions such as pleasure, happiness, and contentment. These emotions are typically salient when a given task is easy or when a difficult task is completed successfully (32). Furthermore, negative emotions include emotions such as sadness, sorrow, and depression, which are found to be a typical response to experiences of setbacks and performance impairments (11). Lastly, eudaimonic emotions are comprised of emotions such as engagement, interest, and inspiration. These emotions are typical responses in complex and demanding situations, where tasks are hard to understand and overcome (10, 19, 45). The eudaimonic model focuses on fulfilling one’s potential, and the extent to which an individual is fully functioning (44).

Emotions can be further classified into affect categories based on the model termed wheel of emotions (see Figure 1), developed by Plutchik (36). In this model, emotions are categorized into eight main groups, and each has three levels of intensity. Similar emotions are placed close together, while opposing emotions are placed facing one another. In order of decreasing intensity, the groups include: (1) ecstasy – joy – serenity; (2) admiration – trust – acceptance; (3) terror – fear – apprehension; (4) amazement – surprise – distraction; (5) grief – sadness – pensiveness; (6) loathing – disgust – boredom; (7) rage – anger – annoyance; and (8) vigilance – anticipation – interest. Furthermore, eight emotions are placed in between the main categories. These in-between emotions are a result of combining the primary categories. For instance, the emotion love comes about from a mixture of joy and trust.

Figure 1
Figure 1
A graphical depiction of the wheel of emotions, a model that classifies emotions into eight main affect categories with three levels of intensity and eight emotions that are a result of combining the primary emotions. Model was developed by Plutchik (36).
Image from Wikimedia Commons.

Emotions in sport
Interestingly for sport psychology, emotions are found to be predictive of performance in the sport setting (1, 12, 13). However, research does not give a unison answer to what effect emotions have on performance, and it is not completely clear which types of emotions are effective to enhance performance in sport (22, 29, 30, 33).

Previous research in sport psychology has mainly focused on how anxiety relates to performance (46). The Attentional Control Theory (ACT) has been used to explain that high anxiety has the potential to influence performance in a negative way, due to a reduced ability to flexibly and readily shift attention between relevant task demands (6). However, the potential negative effect depends on the degree of attentional control, and specifically the ability to execute inhibition and a shift in attention (7). Whether high anxiety impairs performance or not also depends on the use of the athletes’ compensatory strategies. Thus, researchers who build their argumentation on ACT also claim that other interactions decide the influence of negative emotions on performance.

Furthermore, the Functional Well-Being Approach (FWBA) in positive psychology claims that negative emotions such as anxiety, sadness, and aggression are negatively associated with performance (43). On the other hand, eudaimonic emotions such as interest, immersion, and enthusiasm have most influence in high-level performances (29). However, other studies have found that anxiety served its function in successful performances, too (5, 14, 16). Thus, empirical research has not yet reached consensus on which emotions are effective to influence performances in sport.

The experience and expression of emotions varies depending on the intensity of the specific emotions. There is a big difference in being angry and furious, or scared and scared to death. Negative emotions such as anger, fear, sadness, and remorse have a potential to influence athletes’ behavior. For instance, these negative emotions may lead to narrowing of athletes’ attention, or prompt athletes to avoid the situation that gives rise to the emotion. On the other hand, positive emotions such as joy, serenity, interest, and ecstasy have a potential to enhance the athletes’ experiences in positive ways (8, 9). Firstly, positive emotions have the potential to expand athletes’ attention, cognitive processes, and thoughts, so that they are open to new perspectives and possibilities. Secondly, positive emotions stimulate athletes’ durability. Via positive emotions, athletes are stimulated to keep up with their activities and maintain their motivation and focus. Table 1 gives an overview of important emotions, their functions, and reasons for their experience.

Table 1

At least two different approaches are used in sport psychology to explain the effects emotions have on performance (33). These include the hedonic emotion regulation and the instrumental approach.

Hedonic emotion regulation
Hedonic emotion regulation is one approach that is used to explain possible associations between emotions and performance (23). Hedonic emotion regulation focuses on the importance of pleasant (hedonic category) emotions such as joy, pleasure, and happiness, to effectively influence performance (13, 21). According to this approach, the presence of unpleasant (negative category) emotions such as fear, sadness, and nervousness, is claimed to hamper performance. Therefore, athletes and coaches who use this approach in sport to regulate their emotions are motivated to work to increase the intensity of pleasant (hedonic) emotions (joy, pleasure, happiness) and reduce the intensity of unpleasant (negative) emotions (fear, sadness, nervousness).

The instrumental approach
The instrumental approach in sport psychology explains the association between emotions and performance. Specifically, the instrumental approach elucidates how the experience of certain emotions can help an athlete to improve his or her performance (21). Athletes who use this approach to regulate their emotions seek to stimulate those specific emotions they believe will help them enhance their performance. Research has found that some athletes believe that emotions such as anxiety, fear, and anger might enhance their performance, while other athletes believe that such emotions might reduce their performance (10, 30). On the contrary, athletes who believe that anxiety, fear, and anger will hamper their performance will work to reduce the intensity of these emotions.

Proactivity and reactivity. Emotional and cognitive reactions may be characterized in many different ways, but one of the basic distinctions concerns proactivity and reactivity. Proactive reactions are based on proactive control, while reactive reactions are rooted in reactive control. Proactive control is prolonged and preparatory, while reactive control is momentary, short-lived, and typically arises in case of events that demand instant engagement of control (3). Reactive control engages top-down mechanisms, while proactive control engages bottom-up processes (40). In other words, a reactive emotional response is dependent on external factors that an individual has no control over, while a proactive emotional response is concerned solely with what is in control of the individual who is experiencing an event. In the athletic setting, reactive behaviors involve reacting to stressors, while proactive behaviors involve anticipating them (42).

The study by Tamminen and Holt (42) investigated whether the behavior and responses of female adolescent athletes were dominated by proactivity or reactivity. The study found that reactivity was more prominent in athletes’ behaviors and responses. Two factors were identified to be crucial in distinguishing between proactive and reactive coping. Firstly, proactive athletes tended to plan their coping in possible demanding situations. Secondly, they used feedback to evaluate their strategies consistently through the season. Therefore, if athletes learn how to reflect on their behavior and employ proactive mechanisms, including anticipation, planning, and evaluation of situations during trainings or matches, a shift from reactive to proactive reactions would be seen.

The present study
Since the emotional response depends on the subjective experience of a stimulus, it is of interest for sport psychology to investigate what stimuli lead to certain emotions and how these emotions are associated with subjective performance. The current study aims to examine the relationship between emotions and subjective performance among female elite level handball players from Norway. Since emotions are connected to the subjective experience of a stimulus, the current study also aims to examine the experienced stimulus that is connected to the activated emotion.

METHOD
Eleven female elite handball players from an elite team in Norway were randomly invited and accepted to voluntarily participate in this project, where they were asked to document their experienced emotions during trainings and matches over a period of 14 days in 2017. The 11 players who contributed to the data collection had a mean age of 22.4 years, ranging from 19 to 31 years.

For the data collection, a diary based on the theoretical arguments presented in the introduction of this paper was developed. The diary was printed in paper format and given to the athletes. In the diary, athletes were asked to retrospectively document their emotional states in both general and specific episodes. The general episodes covered each training session or match, and the specific episodes during the trainings and matches during the 14 days of data collection. In addition, participants also reported their perceived performance during each episode.

DRM (Day Reconstruction Method)
In the current study, an adjusted and compressed version of the day reconstruction method (DRM) was used (18). The DRM is a research strategy that has been developed to measure individuals’ feelings within everyday life. The version used in this study was customized to decrease the time required to complete the registration, and thereby also decrease the risk of missing data. In the DRM scheme used in this study, athletes were asked to reflect upon their daily training or match, and write reports in form of one general summary, and one to two specific events experienced during the training/match. These different parts are defined as “general episodes” and “specific episodes”. In each episode, athletes reported three types of information. These included a qualitative description of the episode, an evaluation of different emotions experienced during the episode, and an evaluation of their subjective experienced performance.

Emotions. Emotions were categorized into eight groups, based on the Plutchik’s wheel of emotions (36). The included affect categories, with the specific emotions that were believed to be most relevant for elite athletes in the current setting are presented in Table 2.

Table 2

For each episode, athletes reported the degree to which they experienced each of eight different classes of emotions; two hedonic (positive), two eudaimonic (positive) and four negative. The set of emotion items were introduced with the phrase: “During this episode I felt….”. This was followed by the emotions categorized into the following groups: 1) satisfied/ pleased/ happy, 2) calm/ balanced/ hopeful, 3) curious/ interested/ immersed, 4) exhilarated/ enthusiastic / convinced, 5) aggressive/ angry, 6) nervous/ afraid, 7) sad/ depressed and 8) ashamed/ guilty. Athletes responded on a Likert-scale ranging from 0 (“Not at all”) to 6 (“Extremely much”).

Performance. For each episode, athletes were asked to consider how well they performed in this episode from a subjective point of view, on a Likert-scale ranging from 1 (“Very bad”) to 7 (“Very good”). This variable was defined subjective performance.

Classification of emotion triggers during episodes
To investigate possible triggers for different emotions a qualitative interpretation of the description of what the athletes experienced in each episode was carried out. Athletes’ description of each episode was used to qualitatively classify episodes into different groups, based on the focus or type of occurrence. This was done to investigate the types of stimuli that triggered the different emotions, to various intensities.

Upon qualitative classification, episodes were placed into different classes depending on the focus or type of occurrence in that specific episode. Similar descriptions, focus or type of occurrences were placed in a similar class of episodes, based on the idea of sorting episodes into distinct classes (16). In addition, general and specific episodes were differentiated. Based on the participants’ description of each of the 167 general episodes, eleven distinct classes of general episodes were found (see Table 3), while eight different classes of specific episodes were found based on the participants’ description of each of the 264 reported specific episodes (see Table 4).

Table 3

Table 4

Data analysis procedures
All data were tested for a normal distribution using a Shapiro-Wilk test and are presented as mean and standard deviation. Accordingly, correlation analysis between variables was conducted using the parametric Pearson´s correlation coefficient. Independent samples t-tests were conducted to investigate possible differences in intensity of emotions between episodes where athletes were satisfied with their performance (scores equal to or above mean on subjective performance variable) as compared to episodes where athletes were dissatisfied (scores less than mean on subjective performance variable). Thereafter, data was analyzed using logistic hierarchical multiple regression to investigate how the different emotions were associated with the subjective performance variable. Finally, the mean and standard deviation of each emotion in relation to the different types of general and specific episodes were calculated. All statistical analyses were performed using the Statistical Package for the Social Sciences (SPSS) 23.0 software for Windows (SPSS Inc, Chicago, IL).

RESULTS
Descriptive statistics and bivariate correlations
Table 5 contains correlations between the different emotions and subjective performance as well as possible maximum scores, statistical means, and standard deviations of these variables. The zero order correlations between the study variables show mainly large positive or negative relationships (4). Positive correlations were found between subjective performance and positive emotions as well as between the different positive emotions and negative emotions, respectively. Negative correlations were found between subjective performance and negative emotions, and between positive and negative emotions.

Table 5

Differences in intensity of emotions in relation to performance
Using an independent samples t-test, possible differences in intensity of emotions were investigated in relation to episodes where athletes were satisfied with their performance compared to episodes where they were dissatisfied. The mean score of the subjective performance variable (4.29) was used as a cut-off point. Thus, episodes where athletes rated their subjective performance higher or equal to the mean were placed in the Subjective performance more or equal to mean group, while episodes where athletes rated their subjective performance below the mean were placed in the Subjective performance below mean group. Figure 2 shows group-comparisons of emotions during the documented episodes, in relation to subjective performance.

Figure 2
Figure 2.
This figure shows mean values for emotions during different episodes, separated in two groups. The dark grey graphs are the mean scores for episodes where athletes scored a subjective performance above or equal the total mean score (n=202) (i.e. when they were satisfied with their performance). The light grey graphs are the mean scores for the episodes where athletes scored a subjective performance less than mean score (n=210) (i.e. when they were dissatisfied with their performance). Note. ** p<.01. Estimates are based on the observed data.

As shown in Figure 2, significant differences were found between the two groups of subjective performance categories on all observed emotions. Positive emotions generally had the highest score in both groups. However, negative emotions that fell into the categories anger and sadness were almost at the same level as the positive emotions in episodes where athletes performed below the mean. To further investigate if some of these emotions were uniquely associated with performance, a regression analysis on the observed data was performed.

Regression analysis
Table 6 shows the regression statistics from the four step linear regression analysis. The subjective performance variable was entered as a dependent variable. The different emotions measured in the study were entered as independent variables, in four steps.

Table 6

Joy, exemplified by satisfied/ pleased/ happy emotions, contributed significantly to all four models in the regression analysis, with B being .36 (p < .001), 38 (p < .001), .35 (p < .001) and 26 (p < .01) for subjective performance. Serenity, exemplified by calm/ balanced/ hopeful emotions, also contributed significantly to all four models in the regression analysis, with B being 34 (p < .001), .37 (p < .001), .31 (p < .001) and .27 (p < .001) for subjective performance. Fear, exemplified by nervous/ afraid emotions, contributed significantly when entered in model three, with B being -.16 (p < .001) for subjective performance. However, the same variable did not contribute significantly in model four, when sadness, exemplified by sad/depressed and remorse, exemplified by feeling ashamed/guilty were entered in the model. Instead, remorse contributed significantly when entered in model four, with B being -.21 (p < .001) for subjective performance. In total, the variables entered in the model uniquely explained 51% of the variance in Subjective performance.

Emotion triggers
The various general and specific episodes that were reported by athletes, categorized into classes of episodes (see Table 3 and 4), were used in a statistical analysis that comprised the different affect categories investigated in the study (see Table 2). For each class of episodes, mean, and standard deviation of each emotion was calculated.

There were 167 reported general episodes. The number of instances each general episode were experienced is as follows: tired, n=30; prepared, n=16; indifferent, n=16; positive challenge, n=10; too big of a challenge, n=3; good training, n=10; bad training, n=19, positive atmosphere in team, n=5; negative atmosphere in team, n=2; positive trigger, n=21; negative trigger, n=6. Among all the reported general episodes, 65 were proactive and 73 were reactive in nature. The results of statistical analysis of athletes’ emotional states during general episodes are presented in Table 7.

Table 7

In Table 7, instances in which the affect reaction was equal to or higher than the mean are highlighted in bold. For positive emotions, the mean shows the value of subjective performance when athletes were satisfied with it. For negative emotions, the mean represents the value of subjective performance when athletes were dissatisfied with it. Thereby, the experience of being prepared for training or match was associated with values higher than the mean for affect categories joy, serenity, and ecstasy. Positive challenge during training or match was associated with values higher than the mean for affect categories serenity, interest, ecstasy, and interestingly, fear. Negative challenge was associated with values higher than the mean for all the negative affect categories. Furthermore, good training was associated with values higher than the mean for affect categories interest and ecstasy. Positive atmosphere during training or match was associated with values higher than the mean for all the positive affect categories. Negative atmosphere during training or match was, on the other hand, associated with values higher than the mean for affect category sadness. Having experienced a positive trigger during training or match was associated with values higher than the mean for affect categories serenity, ecstasy, and interest, while having experienced a negative trigger was associated with values higher than the mean for all the negative affect categories. Interestingly, feeling tired, indifferent, and experiencing bad training were not associated with values higher than the mean for any of the affect categories.

Furthermore, there were 264 reported specific episodes, which were categorized into eight different groups as shown in Table 4. The number of instances each specific episode were experienced is as follows: success, n=97; failure, n=68; positive feedback, n=19; negative feedback, n=18; unfair, n=21; bad training, n=10; good training, n=25; injury, n=6. Among all the reported specific episodes 35 were proactive in nature and 229 were reactive in nature. The results of statistical analysis of athletes’ motional states during specific episodes are presented in Table 8.

Table 8

In Table 8, instances in which the affect reaction was equal to or higher than the mean are highlighted in bold. For positive emotions, the mean shows the value of subjective performance when athletes were satisfied with it. For negative emotions, the mean represents the value of subjective performance when athletes were dissatisfied with it. Thereby, the experience of success during a specific episode in training or match was associated with values higher than the mean for all the positive affect categories. On the other hand, having experiences of failure was associated with values higher than the mean for all the negative affect categories. Positive feedback was associated with values higher than the mean for affect categories ‘serenity’ and interest, while negative feedback was associated with values higher than the mean for all the negative affect categories. The experience of an unfair event was associated with values higher than the mean for affect categories anger, fear, and sadness. Bad training was associated with values higher than the mean for affect categories anger and sadness. Good training, on the other hand, was associated with values higher than the mean for all the positive affect categories. Last but not least, having experienced an injury during a specific episode of a training or match was associated with values higher than the mean for affect categories anger, sadness, and fear.

DISCUSSION
The current study aimed to examine the relationship between emotions and performance among female elite handball players from Norway. Furthermore, athletes’ perception of triggers that activated the respective emotions was investigated. The findings of this study bring novel insight into the emotional experiences of female elite handball players, and how these influence performance. Furthermore, the present findings elucidate how the different emotions experienced by athletes are mutually related.

Emotions and subjective performance
Firstly, the current study found that emotions such as joy (exemplified by feeling satisfied, pleased, happy), serenity (exemplified by feeling calm, balanced and hopeful), interest (exemplified by feeling curious, interested, immersed) and ecstasy (exemplified by feeling exhilarated, enthusiastic, convinced) were significantly positively correlated with subjective performance (Table 5). In addition, the intensity of positive emotions was found to be significantly higher than the intensity of negative emotions (Figure 2).

Positive emotions. The results showed that female elite handball players who scored higher on subjective performance had significantly higher intensity of positive emotions (Figure 2). Therefore, positive emotions, both hedonic and eudaimonic were found to be positively associated with subjective performance. These findings support previous research, which showed that the ideal emotions for good performance include feelings such as happiness, calmness and an abundance of energy (1, 12, 24). Interestingly, this state includes a contradictive mixture of emotions that result in high energy levels (joy, interest, and ecstasy), while at the same time involving feelings of calm, balance, and hope. The combination of high energy levels from the electrochemical responses and being calm in the situation may seem to be a difficult state to reach, but a necessary one to stimulate performance positively.

Further, according to the FWBA approach, hedonia is associated with easier situations that require less energy and intense focus, and moments of being victorious when goals are reached (29). Eudaimonia, on the other hand, is associated with demanding situations and complex activities (32). The present results might therefore be contradictive when compared to the FWBA in positive psychology. However, emotions might appear in one moment and rapidly fluctuate and change in another moment. Thus, according to the results in the current study, both eudaimonic and hedonic emotions seem to work together to influence performance. When being totally engaged in an activity, up to a point of being lost in it, the female elite handball player will receive feedback from doing the task at hand and experiencing smaller or larger victorious moments with hedonic emotional responses (joy, satisfied, pleased, happy), and then being lost in the activity again. Earlier research also documented positive correlations between eudaimonic and hedonic emotions (32). A female elite handball player might be fully occupied by paying attention to the movements of her teammate and opponent players, and pass the ball perfectly to a teammate who is in a good position to score. This is a state of being fully occupied with the task at hand, where emotions such as interest and ecstasy might be salient, following by the emotion joy because of the successful pass. This might explain why both hedonic and eudaimonic emotions are associated with subjective performance.

On the other hand, negative emotions such as anger (exemplified by feeling aggressive or angry), fear (exemplified by feeling nervous or afraid), sadness (exemplified by feeling sad or depressed) and remorse (exemplified by feeling ashamed or guilty) were found to be negatively associated with subjective performance. Results in the current study showed that these emotions were significantly negatively correlated with subjective performance (Table 5), and that the intensity of these emotions were found to be significantly lower than the positive emotions when compared to subjective performance (Figure 2). The present results also showed that female elite handball players who scored lower on subjective performance had significantly higher intensity of negative emotions (Figure 2). These results therefore further support the notion that emotions have a powerful influence over players’ performance (1, 12, 24). Specifically, the present results are in direct support of the findings in Nicholls, Polman and Revy’s study (35), which found positive emotions to be positively associated with subjective performance, and negative emotions to be negatively associated with subjective performance.

Interestingly, the present results showed that joy, serenity, and remorse uniquely explained 51% of the variance in subjective performance. Thus, high levels of joy and serenity and low levels of remorse seem to be important for performance. A possible explanation of the reason why the eudaimonic emotions did not significantly contribute to the variance in subjective performance is the high correlation found between the hedonic and eudaimonic variables that were entered in the model (Table 5).

Triggers of emotions
The current study indicated that both positive and negative emotions were differentially associated with certain events experienced during trainings and matches. In general, results showed that hedonic and eudaimonic emotions were most intense when the female elite handball players experienced positive events during trainings and matches. On the other hand, negative emotions were most intense when female elite handball players experienced too challenging and negative events during trainings and matches.

First of all, the experiences of preparedness, positive challenges, good training with activities relevant for the players, positive atmosphere in the team, and experiencing success during a training- or matches (positive trigger) were events that elicited all the investigated positive emotions: joy, interest, ecstasy, and serenity. Interestingly, out of these five triggers, it is reasonable to argue that four of them are proactive in nature (prepared, positive challenge, good training, positive atmosphere in team), and one of them is reactive (positive trigger).

Triggering positive emotions. Triggers that elicited positive emotional responses in female elite handball players in the current study were mostly proactive in nature. Thus, female elite handball players had the opportunity to influence these states by controlling the events that elicit the positive emotions. The female elite handball players were themselves in control of spending time to get prepared before trainings or matches. The coaches were, in general, in control of facilitating activities and situations that would be perceived as relevant for the female elite handball players and that would pose optimal challenges. However, the female elite handball players had the ability to influence this by giving feedback to the coaches about the relevance of activities, situations, and level of difficulty. The optimal coach-athlete relationship is often described as a mutual relationship where both parts are responsible for the process of athlete development (31). Therefore, the female elite handball players could control these events to some extent. Further, the female elite handball players also had control over their effort to stimulate the team atmosphere in a positive or negative way. These findings prompt the discussion whether the female elite handball players in the current study proactively regulated their emotions to stimulate the specific emotions they believed would help them enhance their performances. If so, this approach shares important similarities with the instrumental approach in sport psychology (21).

The reactive emotional responses are dependent on external factors that the female elite handball players had no control over. Experiencing a positive trigger in women elite handball was found to stimulate positive emotions, and this experience is dependent on players’ opponents and teammates as well as themselves.

Triggering negative emotions. Results in the current study showed that negative emotions were most profound when female elite handball players, dissatisfied with their performance, experienced negative challenges, negative triggers, negative feedback, and failure. These events elicited all the negative emotions investigated in this study: anger, fear, sadness, and remorse. Furthermore, the experience of unfair events or injury was a strong trigger for negative emotions, eliciting anger, fear as well as sadness.

The reactivity also spanned negative emotions that were a response to events such as tiredness, indifference, positive or negative challenges, bad training, and positive or negative triggers. When investigating the triggers experienced during specific episodes during trainings and matches, the findings show that six out of eight events were reactive in nature. Specifically, events that triggered reactive emotional responses included players’ perception of success, failure, positive or negative feedback, unfair events, and injury. The results of this study are largely in accordance with the study by Tamminen and Holt, which also found reactivity to be dominant in the behaviors and responses of female adolescent athletes (42). All in all, a large majority of the events that were documented in the current study, both through the general and specific episodes, were reactive in nature. The present results suggest that the female elite handball players in the current study have a potential to use their proactivity even more to stimulate positive emotions.

Interestingly, the experience of positive challenges was found to trigger fear. This finding suggests that the association between triggers and emotions should not be oversimplified. Positive events may under certain circumstances trigger emotions with negative valence. This is largely dependent on the athlete’s own appraisal of the situation (17). When experiencing a challenging situation and engaging maladaptive appraisal strategies, the perception of threat may arise. In an athletic setting, threat has been found to be accompanied by a lack of control (35). Thus, it is hereby suggested that it is the lack of control, perceived via the female players’ appraisal strategies that may trigger the feeling of fear in a challenging situation. These results are greatly in accordance with the framework of affect, function, and triggers presented in Table 1. The experience of both hedonic emotions allows the well-being of the female elite handball players to flourish, while negative emotions have mostly detrimental functions.

CONCLUSION
The results in this study show that both hedonic emotions, such as joy and serenity, and eudaimonic emotions, such as interest and ecstasy, seem to play an important role in the female elite handball players’ struggle to perform at their best, whereas these emotions were experienced at high levels when they were more satisfied with their performance. Interestingly, the triggers that stimulate these emotions are mainly controllable for the female elite handball players, and they can therefore be proactive in their work to perform at their optimal level. Negative emotions such as anger, fear, sadness, and remorse, were found to be negatively associated with subjective performance. The triggers that were found to stimulate these emotions were mainly found to be reactive in nature. Since a great majority of the episodes that were documented in this study were found to be reactive in nature, it is reason to believe that the female elite handball players have a potential to use their proactivity in their work to perform at their best even more. This is in accordance with the instrumental approach in sport psychology.

The present study has several limitations. In order to report a precise emotional state through a self-reporting system, the female elite handball players need to have developed their emotional awareness. There is no control if this was the case in this study. Furthermore, emotions are present in the moment, and should optimally be reported directly when they are accessible (38). In the current study the female elite handball players reported their emotions in different sequences of the training or match when looking back at what they just experienced. Future studies should take this into consideration.

APPLICATIONS IN SPORT
Emotions in sport have the potential to influence performance both positively and negatively. Athletes would be more competitive if they learned how their emotions affected their performance and how they can take control and stimulate positive emotions to enhance their performances. This study shows that positive emotions are related to subjective performance, while negative emotions must be at low levels.

ACKNOWLEDGMENTS
This study was done in cooperation with the Olympic department in middle-Norway and the Center for Elite Sports Research, Norwegian University of Science and Technology. We are extremely grateful to the women elite handball players who participated in the current study.

REFERENCES
1. Beedie, C. J., Terry, P. C., & Lane, A. M. (2000). The profile of mood states and athletic performance: Two meta-analyses. Journal of Applied Sport Psychology, 12(1), 49-68.

2. Biederman, I., & Vessel, E. (2006). Perceptual pleasure and the brain a novel theory explains why the brain craves information and seeks it through the senses. American Scientist, 94(3), 247-253.

3. Braver, T. S., Gray, J. R., & Burgess, G. C. (2007). Explaining the many varieties of working memory variation: Dual mechanisms of cognitive control. Variation in Working Memory, 76-106.

4. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). New Jersey: Lawrence Erlbaum.

5. Devonport, T. J., Lane, A. M., & Hanin, Y. L. (2005). Emotional states of athletes prior to performance-induced injury. Journal of Sports Science & Medicine, 4(4), 382.

6. Eysenck, M. W., & Calvo, M. G. (1992). Anxiety and performance: The processing efficiency theory. Cognition & Emotion, 6(6), 409-434.

7. Eysenck, M. W., Derakshan, N., Santos, R., & Calvo, M. G. (2007). Anxiety and cognitive performance: Attentional control theory. Emotion, 7(2), 336.

8. Fredrickson, B. L. (1998). What good are positive emotions? Review of General Psychology, 2(3), 300.

9. Fredrickson, B. L. (2002). Positive emotions. Handbook of Positive Psychology, 120-134.

10. Fredrickson, B. L., Grewen, K. M., Coffey, K. A., Algoe, S. B., Firestine, A. M., Arevalo, J. M., Ma, J., & Cole, S. W. (2013). A functional genomic perspective on human well-being. Proceedings of the National Academy of Sciences, 110(33), 13684-13689.

11. Hanin, Y. L. (2000). Successful and poor performance and emotions. In Y. Hanin (Ed.), Emotions in Sport (pp. 257-289). Champaign, IL: Human Kinetics.

12. Hanin, Y. L. (2003). Performance related emotional states in sport: A qualitative analysis. Paper presented at the Forum Qualitative Sozialforschung/Forum: Qualitative Social Research.

13. Hanin, Y. L. (2010). Coping with anxiety in sport. In A. R. Nicholls (Ed.), Coping in sport: Theory, methods, and related constructs (pp. 159-175). Hauppauge, NY: Nova Science.

14. Hanin, Y. L., & Stambulova, N. B. (2002). Metaphoric description of performance states: An application of the IZOF model. The Sport Psychologist, 16(4), 396-415.

15. Hemmestad, L. B., & Jones, R. L. (2017). Deconstructing high performance Nordic sport: The case study of women’s handball (the ‘team as method’). Sport in Society, 1-18.

16. Jones, M. V., Mace, R. D., & Williams, S. (2000). Relationship between emotional state and performance during international field hockey matches. Perceptual and Motor Skills, 90(2), 691-701.

17. Jones, M., Meijen, C., McCarthy, P. J., & Sheffield, D. (2009). A theory of challenge and threat states in athletes. International Review of Sport and Exercise Psychology, 2(2), 161-180.

18. Kahneman, D., Krueger, A. B., Schkade, D. A., Schwarz, N., & Stone, A. A. (2004). A survey method for characterizing daily life experience: The day reconstruction method. Science, 306 (5702), 1776-1780.

19. Keyes, C. L., Myers, J. M., & Kendler, K. S. (2010). The structure of the genetic and environmental influences on mental well-being. American Journal of Public Health, 100(12), 2379-2384.

20. Kopperud, K. H., & Vittersø, J. (2008). Distinctions between hedonic and eudaimonic well-being: Results from a day reconstruction study among Norwegian jobholders. The Journal of Positive Psychology, 3(3), 174-181.

21. Kowal, J., & Fortier, M. S. (1999). Motivational determinants of flow: Contributions from self-determination theory. The Journal of Social Psychology, 139(3), 355-368.

22. Lane, A. M., Beedie, C. J., Devonport, T. J., & Stanley, D. M. (2011). Instrumental emotion regulation in sport: Relationships between beliefs about emotion and emotion regulation strategies used by athletes. Scandinavian Journal of Medicine & Science in Sports, 21(6), 445-451.

23. Lane, A. M., Beedie, C. J., Jones, M. V., Uphill, M., & Devonport, T. J. (2012). The BASES expert statement on emotion regulation in sport. Journal of Sports Sciences, 30(11), 1189-1195.

24. Lane, A. M., Devonport, T. J., Friesen, A. P., Beedie, C. J., Fullerton, C. L., & Stanley, D. M. (2016). How should I regulate my emotions if I want to run faster? European Journal of Sport Science, 16(4), 465-472.

25. Lazarus, R. S. (2000). How emotions influence performance in competitive sports. The Sport Psychologist, 14(3), 229-252.

26. LeDoux, J. (2003). The emotional brain, fear, and the amygdala. Cellular and Molecular Neurobiology, 23(4-5), 727-738.

27. Manchado, C., Tortosa-Martínez, J., Vila, H., Ferragut, C., & Platen, P. (2013). Performance factors in women’s team handball: Physical and physiological aspects—A review. The Journal of Strength & Conditioning Research, 27(6), 1708-1719.

28. McCarthy, P. J., Allen, M. S., & Jones, M. V. (2013). Emotions, cognitive interference, and concentration disruption in youth sport. Journal of Sports Sciences, 31(5), 505-515.

29. Moen, F., Firing, K., & Vittersø, J. (2016). No pain no gain: Feelings and performance in sport. Journal of Athletic Enhancement, 5(3), 1-7.

30. Moen, F., Myhre, K., & Sandbakk, Ø. (2016). Associations between emotions and performance in cross-country skiing competitions. Sport Journal. Journal, retrieved from: http://thesportjournal.org

31. Moen, F., & Sandstad, H. (2013). Subjective expectations among athletes about coaches in sport. Journal of Human Subjectivity, 11(1), 135-155.

32. Moen, F., & Vittersø, J. (2015). Emotions in sport: Contributions from hedonic and eudaimonic well-being. Athletic Insight, 7(3), 239-254.

33. Moen, F., Vittersø, J., Rasdal, V., Myhre, K., & Sandbakk, Ø. (2017). The role of emotions for four athletes in Nordic combined in ski jumping competitions in World Cup. Sport Journal. Journal, retrieved from: http://thesportjournal.org

34. Myklebust, G., Maehlum, S., Engebretsen, L., Strand, T., & Solheim, E. (1997). Registration of cruciate ligament injuries in Norwegian top level team handball. A prospective study covering two seasons. Scandinavian Journal of Medicine & Science in Sports, 7(5), 289-292.

35. Nicholls, A. R., Polman, R. C., & Levy, A. R. (2012). A path analysis of stress appraisals, emotions, coping, and performance satisfaction among athletes. Psychology of Sport and Exercise, 13(3), 263-270.

36. Plutchik, R. (2001). The nature of emotions human emotions have deep evolutionary roots, a fact that may explain their complexity and provide tools for clinical practice. American Scientist, 89(4), 344-350.

37. Robazza, C., Pellizzari, M., Bertollo, M., & Hanin, Y. L. (2008). Functional impact of emotions on athletic performance: Comparing the IZOF model and the directional perception approach. Journal of Sports Sciences, 26(10), 1033-1047.

38. Robinson, M. D., & Clore, G. L. (2002). Episodic and semantic knowledge in emotional self-report: Evidence for two judgment processes. Journal of Personality and Social Psychology, 83, 198-215.

39. Russell, J. A., & Barrett, L. F. (1999). Core affect, prototypical emotional episodes, and other things called emotion: Dissecting the elephant. Journal of Personality and Social Psychology, 76(5), 805-819.

40. Schmid, P. C., Kleiman, T., & Amodio, D. M. (2015). Neural mechanisms of proactive and reactive cognitive control in social anxiety. Cortex, 70, 137-145.

41. Silvia, P. J. (2006). Exploring the psychology of interest: Oxford university Press.

42. Tamminen, K. A., & Holt, N. L. (2010). Female adolescent athletes’ coping: A season-long investigation. Journal of Sports Sciences, 28(1), 101-114.

43. Vittersø, J. (2013). Functional well-being: Happiness as feelings, evaluations, and functioning. In I. Boniwell,. S. A. David., & A. C. Ayers (Eds.), Oxford handbook of happiness (pp. 227-244). Oxford, UK: Oxford University Press.

44. Vittersø, J., & Søholt, Y. (2011). Life satisfaction goes with pleasure and personal growth goes with interest: Further arguments for separating hedonic and eudaimonic well-being. The Journal of Positive Psychology, 6(4), 326-335.

45. Waterman, A. S. (2013). The best within us: Positive psychology perspectives on eudaimonia: American Psychological Association.

46. Woodman, T., Davis, P. A., Hardy, L., Callow, N., Glasscock, I., & Yuill-Proctor, J. (2009). Emotions and sport performance: An exploration of happiness, hope, and anger. Journal of Sport and Exercise Psychology, 31(2), 169-188.