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Psychological Factors and Performance in Basketball: The Relationship between Motivation, Basic Needs, and Commitment

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15 November 2024

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18 November 2024

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Abstract

This research investigates the intricate relationship among motivation, fundamental psychological needs, and commitment in basketball players, using a cross-sectional survey methodology. Data were gathered from a sample of athletes using standardized questionnaires that evaluated intrinsic and extrinsic motivation levels, psychological needs fulfilment, and other commitment characteristics. Findings demonstrate that moderate motivation levels are associated with enhanced resilience and a less likelihood of burnout, hence promoting continued participation in sports. Athletes indicated elevated levels of competence and relatedness, highlighting the significance of situations that satisfy fundamental psychological needs. Elevated commitment levels correlated with satisfaction, worthwhile opportunities, and social support, so strengthening their function in cultivating devotion. Gender-based differences indicated distinct motivational orientations, suggesting that customized assistance might improve performance and satisfaction for both male and female athletes. Differences in commitment across competition levels indicated that players in less competitive leagues exhibited greater dedication, presumably owing to reduced stressors. This study emphasizes the need of fostering psychological well-being and social support to maintain commitment and resilience, providing essential insights for coaches and sports psychologists in developing motivating environments that enhance athlete performance and long-term well-being.

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Subject: 
Social Sciences  -   Other

1. Introduction

The relationship between motivating conditions and the fulfillment of psychological needs illustrates that players' motivation is intricately linked to their commitment to basketball. The motivation of athletes is augmented, and their dedication to the sport is intensified within environments that endorse individual accomplishments and acknowledge achievements [1]. For instance, basketball players who perceive recognition within their team dynamics frequently cultivate greater resilience, thereby enhancing their capacity to withstand challenges [2]. This model asserts that inherent drive is developed through crucial psychological demands, namely autonomy, expertise, and meaningful relationships. Such factors further bolster players' commitment to basketball [3]. Teixeira et al. highlight those enabling players to control their actions and participation in the sport promotes their autonomy, while competence plays a vital role in recognizing their development in skills, and affiliation contributes to the bonding experience with coaches and fellow teammates [4]. When these psychological needs are adequately fulfilled, players are more inclined to derive motivation from self-improvement, which is crucial for sustained commitment to basketball [4].
Moreover, intrinsic motivation cultivates resilience and perseverance. Roberts et al. claim that athletes influenced by an internal drive for self-betterment, rather than by external incentives, often reveal stronger commitment [5]. In competitive contexts such as basketball, where external incentives may be insufficient to maintain an athlete's allegiance, this form of motivation assumes critical importance [6]. Therefore, sustaining a player's long-term commitment to basketball necessitates intrinsic elements, including personal satisfaction and passion for the sport [5]. Additionally, the extent of athletes' commitment is profoundly influenced by mental competencies and specific motivational orientations [7]. Cucui and Cucui contend that athletes who cultivate mental skills congruent with their intrinsic motivation typically demonstrate enhanced focus and commitment to self-improvement, thereby fortifying their engagement in the sport [6]. Šimková and Válková suggest that junior basketball players' loyalty to the sport is often increased through motivating aspects like pleasure and a cooperative team environment [8]. Basketball players who flourish in a nurturing setting that addresses their needs for autonomy, competence, and connection are likely to experience intrinsic motivation, culminating in enduring commitment [1].
The effectiveness and experiences of basketball athletes are shaped by a range of psychological factors, including motivation, mental readiness, emotional management, and social support [9]. Each of these factors influences athletes' ability to tackle challenges, cope with stress, and engage competently with their sport, especially in high-pressure, competitive environments [10,11]. In this context, understanding and enhancing these psychological aspects is vital for maximizing athlete performance both in competitive settings and beyond [12].
Firstly, motivation serves as a vital component that drives basketball players to persevere, develop, and fully engage in their sport [13]. An environment that nurtures motivation, focused on skill development and personal growth (intrinsic motivation) rather than merely aiming for victory, significantly enhances performance by promoting satisfaction and resilience [10]. In contrast, a competition-oriented atmosphere, where the main emphasis is on outperforming others, can increase anxiety and reduce satisfaction, particularly when athletes face challenges [14]. Moreover, basketball players with a strong inclination towards personal skill enhancement and learning tend to experience greater satisfaction and sustained performance, while those primarily motivated by outperforming peers may face heightened anxiety in competitive situations [10]. Additionally, self-centered reasoning may lead to negative self-evaluation, especially if players perceive their skills as inadequate [14]. This focus on skill development also nurtures resilience, allowing players to recover quickly from setbacks and maintain a growth-oriented mindset that supports long-term improvement [15].
In addition, in the high-pressure domain of basketball, mental readiness stands out as a crucial psychological skill, requiring players to sustain focus, regulate emotions, and demonstrate resilience in challenging situations. Techniques such as mental imagery, self-talk, and relaxation strategies are fundamental to building confidence and concentration [11]. Mental visualization, in particular, enables athletes to mentally rehearse successful actions, thus enhancing self-efficacy and reducing performance-related anxiety [9]. Furthermore, when athletes practice mental visualization and self-regulatory techniques, they are more equipped to perform under pressure, maintain cognitive clarity, and quickly recover from mistakes [16]. In this regard, stress management, closely tied to mental preparedness, is essential for ensuring consistency and flexibility in basketball. As stress can impede both cognitive clarity and physical accuracy, athletes lacking effective coping mechanisms may struggle to perform optimally under pressure [9]. This factor is particularly important in basketball, where the ability to make swift decisions under duress can significantly affect game outcomes. Consequently, players who utilize mindfulness and relaxation techniques are better equipped to manage their emotions, stay focused, and avoid performance-related mental barriers, ultimately leading to fewer mistakes and improved overall performance [17].
Basketball players' motivation, dedication, and general well-being are greatly influenced by their social environment, which includes the support of coaches, teammates, and family members. A feeling of belonging is fostered by positive social support, and this is crucial for boosting resilience and drive. Players are more likely to stick with their sport and persevere through tough times if they feel their instructors are valuable and build relationships with their teammates [12]. Athletes whose fundamental psychological needs for autonomy, competence, and relatedness are fulfilled through support and interpersonal relationships generally exhibit enhanced well-being, motivation, and performance. This type of sporting environment improves individual performance and fortifies the overall dynamics of the team [18]. Individual performance is considerably improved by coaches, who also have a significant impact on team dynamics. A climate of trust is fostered by basketball coaches who deliver consistent, constructive feedback and emphasize open communication, thereby enhancing the learning experiences of players and reinforcing team cohesion [19]. Players demonstrate a strong sense of inclusion in the small community that their team has established, which results in increased motivation and performance as a result of their dedication and investment in the team's success overall [20].
Furthermore, enhancing emotional stability and mental toughness directly affects basketball players' capacity to manage stress and maintain consistent performance. Emotional management enables players to sustain focus and make rational decisions in high-pressure scenarios [21]. Learning to control your feelings helps athletes keep a level head during the ups and downs of professional sports, which is necessary for peak performance [22]. Mental toughness, which means being able to handle stress and keep going even when things get hard, is an important psychological skill in basketball. Mental toughness and emotional intelligence are crucial for players' capacity to maintain focus and react constructively to physical and psychological demands [23]. These abilities improve the agility and coordination of players, allowing them to move confidently in difficult game scenarios [17]. Players who effectively manage tension are more likely to maintain high performance levels in high-pressure situations. In order to facilitate precise decision-making and reduce mental fatigue during demanding moments in a game, players can employ techniques such as controlled breathing and relaxation training to maintain a sense of serenity [24]. Athletes who develop resilience via positive self-talk and goal setting tend to recover swiftly from errors and re-engage with confidence, which is crucial for sustaining agility and composure during competitions [25]. In basketball, resilience allows players to manage mistakes and concentrate on the game, converting potential failures into opportunities for learning [15].
The nexus between psychological well-being and athletic performance is pivotal for comprehending how basketball players can attain both individual fulfillment and optimal performance [26]. Key psychological mechanisms not only govern players' performances in challenging circumstances but also shape their overall sense of well-being and loyalty to the sport [27]. For basketball athletes, the relationship between psychological well-being and performance highlights the necessity of addressing mental processes in conjunction with physical training, thus ensuring a comprehensive strategy that fosters both competitive achievement and personal fulfillment [28].
Consistent with Self-Determination Theory (SDT), satisfying basic psychological needs (autonomy, competence, and relatedness) promotes intrinsic motivation, critical for an athlete’s well-being. Consequently, athletes who perceive these needs as fulfilled are more inclined to pursue mastery objectives, thereby augmenting their motivation and enjoyment in sports [28]. Moreover, athletes’ autonomy—particularly within the context of basketball, where team dynamics and individual accountability converge—facilitates their capacity to remain motivated over time, which is vital for both well-being and sustained performance [29]. In addition, the inner urge to excel significantly impacts a player's adherence to workout routines and dedication, connecting it to emotional fulfillment and the strength to recover both in sports and personal life [30]. By fostering a sense of internal control, players are better equipped to navigate stressors, sustain focus, and prevent burnout, all of which are crucial in high-pressure scenarios. This intrinsic drive is further reinforced by the fulfillment of basic psychological needs, which not only elevates motivation but also enhances a player's psychological resilience and long-term investment in basketball [31].
Furthermore, the manifestation of anxiety within high-performance basketball contexts can yield both advantageous and adverse outcomes, contingent upon players' management of it. In such scenarios, anxiety, if left uncontrolled, frequently diminishes self-confidence, culminating in impaired performance [27]. Conversely, when athletes sustain their confidence, anxiety can act as a motivational catalyst, amplifying focus and determination. Therefore, self-confidence holds particular significance under pressure, enabling athletes to harness anxious energy constructively rather than allowing it to detract from their concentration and mental acuity [32]. In addition, the reliability of psychological characteristics, like resilience and confidence in oneself, affects the handling of stress linked to performance. In essence, athletes possessing stable psychological characteristics are better equipped to confront the psychological adversities inherent in competitive basketball [32]. Thus, mental toughness is recognized as intricately linked to psychological well-being, serving as an essential component in assisting athletes in navigating both internal and external pressures, thereby promoting consistency and concentration during competitions [33].
Additionally, the ability to understand and regulate emotions is essential for optimising performance and preserving mental health. In 2019, Borysova et al. concluded that emotional intelligence improves team dynamics by facilitating enhanced communication and cohesiveness, as well as by assisting basketball players in maintaining composure under duress [34]. This theory posits that players who are more adept at self-evaluation and emotional control are more likely to succeed; this is due to their ability to manage failings in the game and maintain a positive attitude. Moreover, emotional intelligence aids athletes in building resilience by enabling them to manage their emotional peaks and troughs effectively, which is crucial in sports [35]. In basketball, resilience acts as a safeguard for mental health, as players must handle considerable physical and psychological stress. This capability helps them preserve their health and well-being amidst intense competition and tackle obstacles with optimism [36].
Another significant psychological process that significantly influences psychological health and performance is the correlation between mental fortitude and physical readiness. Practically, physical conditioning not only enhances endurance but also supports athletes’ mental readiness, allowing them to face physical and mental challenges with greater confidence [37]. So, a physically prepared athlete experiences lower levels of fatigue, which helps maintain cognitive sharpness and emotional control, both of which are necessary for optimal decision-making and resilience during games. Moreover, sports psychology therapies aimed at cultivating mental resilience and physical robustness lay the foundation for enhanced self-esteem and internal equilibrium, which in turn boosts well-being alongside performance. According to Khan-Vilkar and Vyas, taking all factors into account, better mental health allows athletes to find a balance among their competitive goals, long-term growth, and personal satisfaction [36]. Rodrigues et al. said that training programs must integrate psychological support, motivational techniques, and mental conditioning with physical exercise to optimize athletic performance [36]. Ugoani asserts that mental training is crucial for athletes to cultivate concentration, resilience, and stress management strategies, which profoundly influence performance [38]. In other words, mental techniques like goal-setting and self-talk are useful for boosting an athlete's confidence and poise, which are essential for optimal performance, particularly while under duress [39]. Nonetheless, coaches play a key role in establishing an atmosphere that encourages players' independence and drive for success.
So, athletes who perceive their coaches as supportive of their autonomy and skill development are more likely to adopt mastery-oriented goals [40]. Such a motivational climate encourages intrinsic motivation, as athletes feel that they are working toward personal growth and skill mastery rather than simply seeking external rewards. Therefore, coaches’ commitment is linked to positive team performance, suggesting a reciprocal relationship where both coach and athlete benefit from a supportive, athlete-centered approach [41].
Furthermore, fulfilling the fundamental psychological requirements of athletes—namely autonomy, competence, and relatedness—is crucial for their commitment and overall well-being. Consequently, athletes who perceive that their psychological needs are satisfied demonstrate elevated engagement levels and a diminished likelihood of experiencing burnout [42]. When coaches implement autonomy-supportive strategies and foster a sense of relatedness within the team, athletes are more inclined to remain dedicated to their training regimens. In addition, young athletes flourish when they receive encouragement from both coaches and peers, underscoring the significance of a unified team atmosphere in promoting sustained motivation and contentment [43]. In summary, the cultivation of psychological competencies such as adaptability, mental resilience, and concentration is imperative for athletes confronting competitive pressures. Under such circumstances, high-potential athletes derive substantial benefits from training regimens that integrate psychological skill enhancement into their routine practices [44]. Competitive scenarios and pressure simulations are methodologies that can help athletes improve their mental fortitude and adaptability, thereby enabling them to overcome the unpredictable challenges that arise during actual competitions. Training programs should prioritise the development of the necessary psychological preparedness to optimise athletes' performance across a variety of conditions, in addition to the development of physical capabilities, by emphasising this [45].
The triadic model of motivation suggests that athletes' commitment to performance is enhanced by a harmonic approach to internal and extrinsic motivation, therefore realizing this goal [38]. Therefore, coaches may foster this balance by providing positive comments that acknowledge work and development, therefore fulfilling players' extrinsic goals for recognition as well as their natural drive for personal success. Furthermore, athletes' ability to control performance anxiety and maintain good mental health depends much on the continuous help of their teammates [46]. Under this perspective, resilience, anxiety control, and self-efficacy are key psychological factors influencing performance outcomes; a strong support system will help athletes negotiate these obstacles. Similarly, social support bolsters both academic and athletic performance, indicating that a nurturing training environment can assist athletes in managing stress and maintaining concentration under duress [47]. In general, athlete engagement, characterized by enthusiasm, commitment, and immersion in training, is vital for consistent performance and enduring success [42]. Nevertheless, this specific degree of commitment is frequently jeopardized by burnout, a phenomenon that can be alleviated by addressing athletes’ fundamental psychological needs and organizing training schedules that facilitate rest and recuperation [48]. One of the most effective solutions within this paradigm may be the incorporation of psychological and motivational techniques into training programs that empower athletes to achieve peak performance while safeguarding their well-being [29]. Thus, coaches who align training methodologies with these athletes’ requirements foster an environment that cultivates motivation and resilience [35].
This study aims to examine the psychological processes that influence the experience and performance of basketball athletes, focusing on the interaction of motivation, basic psychological needs and commitment. The study seeks to investigate how these factors are related to intrinsic motivation, athlete well-being and commitment to the sport of basketball.

2. Materials and Methods

The methodological approach employed in this research was quantitative, as obtaining precise measurements and objective data was essential for establishing correlations among the variables under investigation. The variables examined pertained to the motivation, commitment, and fundamental needs of the athletes. Additionally, the study utilized a correlational design to examine the interrelationships among the variables and was synchronic in nature, with data collection taking place at a single point in time [49]. The study specifically targeted basketball athletes across various levels of competition. The sampling method utilized was convenience sampling, aimed at swiftly assembling a readily accessible sample. However, it is important to note that a convenience sample, which lacks probability, cannot be deemed representative [50]. Nonetheless, within the parameters of this study, the sample was deemed sufficiently adequate. The study encompassed a total of 423 basketball athletes.
Data for the survey were gathered through a Google Forms questionnaire. Initially, the questionnaire comprised six closed-ended demographic inquiries. These questions solicited information regarding gender, age, educational attainment, marital status, competitive classification, and years of participation in a basketball team. Next, 33 closed-ended questions on a 5-point Likert scale ranging from 1-Agree to 5-Agree were used to measure motivation. To measure the athletes' basic needs, 20 closed-ended questions on a 7-point Likert scale from 1-Agree to 7-Agree were used to measure the athletes' basic needs [51]. The questions led to the scales: competence, Choice, Internal perceived locus of casualty (IPLOC), Volition and Relatedness. To measure Commitment, 55 closed-ended questions were used on a 5-point Likert scale from 1-Agree to 5-Agree. The questions led to the scales Sports Commitment, Valuable Opportunities, Other priorities, Personal Investments-Loss, Personal Investments-Quantity, Social constraints, Social Support-Emotional, Social Support-Informational, Excel-Mastery Achievement, Desire to Excel-Social Achievement, Enthusiastic Commitment and Constrained Commitment.
The data collection was done in the period from August to October 2024. The survey was online and participants completed the questionnaire through a special link. Responses were collected on the Google Forms platform and then, after completion, were saved in an Excel file for analysis. It should be noted that participants were informed before taking part in the survey through an information form and participated voluntarily and knowingly after giving their own consent.
Data analysis was performed using SPSS 25.0.0. First, responses were coded and questionnaire variables were generated. Next, descriptive statistical analysis was performed and tables and graphs were produced to present the demographic data and levels of the survey variables. Then, a reliability test was performed through Cronbach's alpha and a distribution test through Kologorov-Smirnov test. For the first and second research question, a correlation analysis was performed through Spearman's s index s for the first and second research question. For the third research question, Mann-Whitney U test and Kruskal Wallis test were used. The significance level was 0.05.

3. Results

According to the analysis, the survey sample was based on 423 people in total. Out of this total, 279 people (66%) reported being male and another 144 people (34%) reported being female. When asked about the category in which the participants participated during the 2023-2024 sports season, 50.4% (n = 213) stated that they participated in the A2 Elite League Women. At the same time, however, 17% (n = 72) stated that they participated in the A1 Basket League Women and 14.7% stated that they participated at the amateur level. Finally, the sample was asked to indicate the years they participated in basketball teams. According to the analysis, 64.5% (n = 273) responded that they were a member of a basketball team from 11 to 15 years. Also, 13% (n = 55) noted that they were a member from 6 to 10 years and 13.2% (n = 56) noted that they were a member from 1 to 5 years, as shown in Table 1.
Cronbach's alpha was used for the reliability of the survey variables. The index should be above 0.7 to result in levels of satisfactory reliability. For the Motivation variable, the index returned a value equal to 0.887, which is very satisfactory. For the Basic needs in sports variable, five factors were used, all of which had reliability [53]. For the Sports Commitment variable, 12 factors were used, which indicated a reliable result overall. (Table 2).

3.1. Levels of Variables

According to the analysis, the motivation variable had a minimum value of 1 and a maximum value of 5. The mean value of the variable reached 3.43 points with a standard deviation of 0.47 points. Therefore, the motivation levels of the athletes in the study sample were mainly moderate. Five factors were used for the variable Basic needs in sports.
For the Competence factor, it was found that the relevant variable had a minimum value of 1 and a maximum value of 7. The average value of the variable reached 5.15 points with a standard deviation of 1.30 points. Therefore, levels for the Competence variable in the athletes in the survey sample were slightly high primarily. For the Choice factor, the minimum was 1 and the maximum was 7. The average was 4.29 points with a standard deviation of 1.41 points. Thus, Choice's levels were modest. For Internal perceived locus of causality (IPLOC), the minimum value reached 1 and the maximum reached 7. The average price stood at 5.38 points with a standard deviation of 1.46 points. Therefore, Internal perceived locus of causality (IPLOC) levels were slightly high. For Volition, its minimum value was 1 and maximum 7. The average price reached 4.75 points and the standard deviation 1.02 points. Based on these values, Volition's levels were moderate.
For the Sports Commitment variable, 12 factors were used. For the Sport Enjoyment factor, its average price reached 4.20 points with a standard deviation of 0.92 points. Therefore, the levels of Sport Enjoyment were high.
For Valuable Opportunities, the minimum value was 1 and the maximum was 5. The mean was 4.03 points and the standard deviation 0.92 points. So, the levels for Valuable Opportunities were high.
For the Other priorities factor, the average reached 3.04 points with a standard deviation of 0.97 points. Therefore, the levels for other priorities were modest.
For the Personal Investments-Loss factor, the average price reached 3.67 points with a standard deviation of 0.91 points. Therefore, Personal Investments-Loss levels were modest. The Personal Investments-Quantity factor had a minimum value of 1 and a maximum value of 5. The mean value was 4.13 points and the standard deviation 0.88 points. Thus, Personal Investments-Quantity levels were high. The Social constraints factor had a minimum value of 1 and a maximum value of 5. The average value of the variable reached 3.12 points with a standard deviation of 0.91 points. Therefore, social constraint levels in athletes were mostly modest.
For the Social Support-Emotional factor, the minimum was 1 and the maximum was 5. The average price reached 3.84 points with a standard deviation of 0.96 points. Therefore, Social Support-Emotional levels were slightly high in the sample. The Social Support-Informational agent had a minimum value of 1 and a maximum value of 5. The average value was 3.56 points with a standard deviation of 0.82 points. So Social Support-Informational levels were slightly high.
For the Desire to Excel-Mastery Achievement factor, the average value reached 4.00 points. Therefore, the Desire to Excel-Mastery Achievement levels for the sample were high. For the Desire to Excel-Social Achievement factor, the minimum value was 1 and the maximum value was 5. The average reached 3.90 points with a standard deviation of 0.85 points. Therefore, Desire to Excel-Social Achievement levels were high. The Enthusiastic Commitment factor had a mean of 3.94 points and a standard deviation of 0.87 points. Thus, Enthusiastic Commitment levels were high. For the Constrained Commitment agent, the minimum value reached 1 and the maximum value reached 5. The mean was 2.49 points with a standard deviation of 0.96 points. Therefore, Constrained Engagement levels were moderate to slightly low (Table 3).

3.2. Checking the Distribution of Variables

The Kolmogorov-Smirnov test was used to test the distribution of variables. The sample was larger than 50 subjects in total and hence this test was chosen. Note that in case of non-statistically significant results, the distribution of the data of the tested variable is considered to approximate normal. According to the results, the Motivation variable does not follow the normal distribution (K-S(N = 423) = .139, p < .01). In all cases of the factors of the Basic needs in sports variable, a statistically significant result was returned (p < .01). Therefore, the data for all factors of the Basic needs in sports variable do not follow the normal distribution. In all cases of the factors of the Basic needs in sports variable, a statistically significant result was returned (p < .01). Therefore, the data of all the factors of the variable Basic needs in sports do not follow the normal distribution. According to the results, in all cases of the factors of the variable Sports Commitment, a statistically significant result was returned (p < .01). Therefore, the data of all factors of the variable Sports Commitment do not follow the normal distribution (Table 4 and Table 5).

3.3. Correlations Between Motivation and Commitment

Spearman's s rho was used to investigate the Commitment correlation, as all the related variables did not follow the normal distribution. According to the results, in all cases of the correlations between the Motivation variable and the factors of the Commitment variable, a statistically significant result was returned (p < .05). The correlations were positive and weak. Therefore, it is concluded that as the levels of the Motivation variable increase, the levels of the Commitment variable increase and vice versa (Table 6).

3.4. Correlations Between Motivation and Basic Needs in Sports

Spearman's s index was used to investigate the Commitment correlation, as not all relevant variables followed the normal distribution. According to the results, in all cases of correlations between the motivation variable and the factors of the Basic needs in sports variable, a statistically significant result was returned (p < .01). The associations were positive and weak. Therefore, it is concluded that as the levels of the Motivation variable increase, so do the levels of the variable Basic needs in sports and vice versa (Table 7).

3.5. Gender Influence on Basic Needs in Sports and Commitment Variables

To investigate whether there are differences in the levels of factors of the variables Basic needs in sports and Commitment depending on gender, the Mann Whitney U test was used. According to the results, gender has a statistically significant influence on the Internal perceived locus of causality (IPLOC) factor (U = 16850.5, p = .006) and the Relatedness factor (U = 17153.5, p = .013) with respect to the variable Basic needs in sports. Also, gender has a statistically significant influence on Valuable opportunities (U = 17393.0, p = .021), Personal Investments-Quantity (U = 15426.5, p < .001), Social Support-Emotional (U = 17126.5, p = .012), Desire to Excel-Mastery Achievement (U = 17720.0, p = .046) and Constrained Commitment (U = 17521.5, p = .031) on the Commitment variable (Table 8).
In addition, it is observed that women's levels of Basic needs in sports: 1) Internal perceived locus of causality (IPLOC), 2) Relatedness and factors of the variable Commitment: 1) Valuable Opportunities, Personal Investments-Quantity, 2) Social Support-Emotional, 3) Desire to Excel-Mastery Achievement, 4) Constrained Commitment were statistically significantly higher, compared to men. In contrast, men's levels of the Commitment: Constrained Commitment factor were statistically significantly higher than women (Table 9).

3.6. Impact of Category of Competence on the Variables Basic Needs in Sports and Commitment

To investigate whether there are differences in factor levels of the Basic needs in sports variable depending on the category of competence, the Kruskal Wallis test was used. According to the results, the category of competence statistically significantly affects the Competence factor (H = 12,430, p = .014), the Choice factor (H = 12,430, p = .014), the Internal perceived locus of causality (IPLOC) factor (H = 15,529, p = .004), the Volition factor (H = 23,999, p < .01) and the Relatedness factor (H = 9,825, p = .043) (Table 10).
More specifically, it was found that satisfaction in the Competence factor ranged at statistically significantly higher levels in the A2 League Men and Women category, compared to the A1 League Men and Women category. Also, satisfaction in the Choice factor ranged at statistically significantly higher levels in the A2 League Men and Women category and the National League 1 Men category, compared to the A1 League Men and Women category. Meanwhile, satisfaction in the Internal perceived locus of causality (IPLOC) factor ranged at statistically significantly higher levels in the A2 League Men and Women and National League 1 Men categories, compared to the A1 League Men and Women category. In addition, satisfaction in the Volition factor ranged at statistically significantly higher levels in the A2 League Men and Women category, compared to the A1 League Men and Women category. Finally, satisfaction in the Relatedness factor ranged at statistically significantly higher levels in the A2 League Men and Women category, compared to the A1 League Men and Women category.
To investigate whether there were differences in the levels of the Commitment variable factors by category of competence, the Kruskal Wallis test was used. According to the results, the category of competence has a statistically significant effect on the Sport enjoyment factor (H = 12.041, p = .017), the Other priorities factor (H = 19.867, p = .001), the Personal Investments - Loss factor (H = 12. 383, p = .015), the Personal Investments-Quantity factor (H = 18.879, p = .001), the Desire to Excel-Mastery Achievement factor (H = 15.572, p = .004), and the Desire to Excel-Social Achievement factor (H = 16.835, p = .002) (Table 11).

3.7. Impact of Years as a Basketball Team Member on the Variable Commitment

To investigate whether there are differences in the levels of the factors of the Commitment variable according to Years as a basketball team member, the Kruskal Wallis test was used. According to the results, Commitment has a statistically significant effect on the Personal Investments-Loss factor (H = 14.483, p = .006), the Social Support-Emotional factor (H = 11.804, p = .019), the Social Support-Informational factor (H = 17.682, p = .001), and the Desire to Excel-Mastery Achievement factor (H = 11.229, p = .024) (Table 12).
Specifically, it was found that commitment to the Personal Investments-Loss factor was statistically significantly higher in athletes with 6-10 years as basketball team members, compared to athletes with 20+ years as basketball team members. Also, commitment to the Social constraints factor ranged at statistically significantly higher levels in athletes with 11-15 years as basketball team members, compared to athletes with 15-20 years as basketball team members. Meanwhile, commitment to the Social Support-Emotional factor ranged at statistically significantly higher levels in athletes with 11-15 years as basketball team members, compared to athletes with 15-20 years as basketball team members. In addition, commitment to the Social Support-Informational factor ranged at statistically significantly greater levels in athletes with 1-5 and 11-15 years as basketball team members, compared to athletes with 15-20 years as basketball team members. Still, commitment to the Desire to Excel-Mastery Achievement factor ranged at statistically significantly greater levels in athletes with 11-15 years as basketball team members, compared to athletes with 15-20 years as basketball team members.

4. Discussion

4.1. Motivation Levels

There was a mid-range level of intrinsic and extrinsic motivation among the athletes in the study sample, as shown by their usually moderate motivational levels. These results are supported by earlier study, which found that players in organized sports situations often exhibit moderate motivation [54]. Moderate motivation levels may assist sustain performance without the burnout risk associated with high motivation levels, according to Vallerand et al. [55]. This is in line with Mohamed [1], who highlighted that settings that encourage personal achievement and acknowledgement cultivate intrinsic drive, fostering resilience and sustained dedication to sports. Athletes' performance, general well-being, and level of happiness with their athletic pursuits may all be impacted by the balance between intrinsic and extrinsic motivation. Finding this balance may result in longer-lasting sports careers where people are engaged and happy instead of feeling overburdened by the demands of competitiveness.

4.2. Basic Needs in Sports

The levels for the variable Competence among athletes in the sample were generally slightly high. For the Choice and Volition variables, levels were moderate, indicating an average sense of autonomy and volitional action among athletes. The variable Internal Perceived Locus of Causality (IPLOC) demonstrated slightly high levels, as did the Relatedness variable, suggesting that athletes generally felt a slightly enhanced sense of internal motivation and connection within their sports environment. This is consistent with Self-Determination Theory [56], which stresses the importance of competence and relatedness in the maintenance of an athlete's internal motivation. Standage et al. have also conducted research that supports the notion that motivation and positive psychological outcomes can be improved by a high level of perceived competence and relatedness [57]. Teixeira et al. [4] substantiate this assertion by demonstrating that autonomy, competence, and meaningful relationships not only increase motivation but also foster a long-term dedication to athletics, which is consistent with the results of the present study. The significance of establishing supportive environments that promote these elements is emphasized by the interplay of factors, which ultimately results in improved athlete performance and contentment. Effective coaching practices, team dynamics, and community support can be employed to cultivate such environments, which collectively contribute to an athlete's sense of belonging and purpose within their sport.

4.3. Sports Commitment

Athletes exhibited high levels in the variables Sport Enjoyment, Valuable Opportunities, Personal Investments-Quantity, Desire to Excel-Mastery Achievement, Desire to Excel-Social Achievement, and Enthusiastic Commitment. Moderate levels were observed for Other Priorities, Personal Investments-Loss, and Social Constraints, indicating that these factors were present but less pronounced. Notably, the variable Constrained Commitment was primarily moderate to slightly low, reflecting a reduced obligation-driven commitment. Social Support—both emotional and informational—also displayed slightly high levels, underscoring the athletes’ perception of support in their sporting context. In alignment with the findings of Weiss and Weiss [58], it is evident that factors such as enjoyment and valuable opportunities frequently serve as the impetus for athletes' continued engagement in sports. In a similar vein, Scanlan et al. [59] noted that substantial personal investments and emotional support serve as critical indicators of an athlete's commitment. According to Roberts et al. [5], self-improvement-focused intrinsic motivation results in persistent commitment, particularly in competitive environments when outside incentives may not be enough. The importance of supporting surroundings in maintaining athletic commitment was further supported by the rather high levels of social support, both informational and emotional [8].

4.4. Correlation Between Motivation and Commitment

Statistically significant positive correlations (p < .05) were observed between motivation and the factors of commitment, though these were weak. This indicates that as motivation levels increase, commitment levels also tend to rise, albeit marginally, and vice versa. This finding is supported by research that suggests motivation and commitment are interconnected, with higher motivation often fostering stronger commitment [60]. Mohamed [1] noted that intrinsic motivation, particularly when linked to autonomy and meaningful relationships, promotes long-term commitment to sports. The findings highlight the importance of comprehending the impact of psychological factors on athletes' performance, as well as the necessity for coaches and sports psychologists to create an environment that enhances intrinsic motivation and meets essential psychological needs. Creating such an atmosphere helps players stay involved and passionate about their activity over time, in addition to encouraging improved performance [8]. By using a more comprehensive strategy, athletes may have more sustainable careers where they are not just focused on short-term results but also on their own development and satisfaction in their chosen field [1].

4.5. Correlation Between Motivation and Basic Needs in Sports

Similarly, positive and statistically significant correlations (p < .01) were found between motivation and the factors of basic needs in sports, though these correlations were weak. This suggests that higher motivation levels are associated with greater satisfaction of athletes' basic needs in sports, indicating a mutually reinforcing relationship. This aligns with Self-Determination Theory [54], which posits that satisfying fundamental demands for competence, autonomy, and relatedness is crucial for motivation in sporting contexts. Abou Elmagd [9] underscores that mental preparedness, emotional management, and social support are essential for optimizing athlete engagement and performance in demanding circumstances. This underscores the need to establish supportive settings that cultivate these fundamental needs, thereby enhancing both motivation and performance among athletes.

4.6. Gender Influence on Basic Needs and Commitment

Female athletes demonstrated statistically significant higher levels in the basic need’s factors of IPLOC and Relatedness, as well as in the commitment factors Valuable Opportunities, Personal Investments-Quantity, Social Support-Emotional, and Desire to Excel-Mastery Achievement, compared to male athletes. Conversely, males exhibited higher levels of Constrained Commitment, indicating a greater sense of obligation-driven commitment among them. Research by Gill [61] and Choi et al. [62] indicates that female athletes often exhibit elevated levels of relatedness and social support, aligning with community incentives that foster resilience and intrinsic motivation [10]. Research indicates that gender differences in motivation and commitment may greatly affect athletes' performance and overall sports experience, underscoring the need for tailored support networks for both male and female athletes. To cultivate an inclusive atmosphere that enhances the distinct motivations of each athlete and elevates performance and enjoyment for athletes of all genders, coaches and sports organizations must possess a comprehensive awareness of these dynamics [63].

4.7. Influence of Competence Category on Basic Needs and Commitment

Athletes in the A2 League (both men and women) displayed significantly higher satisfaction levels in the factors of Competence, Choice, IPLOC, Volition, and Relatedness when compared to those in the A1 League. Additionally, commitment levels in Sport Enjoyment, Other Priorities, Personal Investments-Loss, Personal Investments-Quantity, and both Desire to Excel-Mastery and Social Achievement were significantly higher among A2 League athletes than those in the A1 League. These findings are consistent with studies by Ames and Archer [64], which show that athletes in leagues where there is less pressure to compete tend to be more committed and psychologically satisfied since their attention is diverted more towards internal incentives. Therefore, the idea that less rivalry always results in better psychological outcomes is called into question since the environment of competition has a significant impact on psychological aspects and performance [65]. Although athletes in the A2 League demonstrated elevated satisfaction and commitment levels, this observation may not be applicable across all sports or competitive contexts. There are some big differences between the leagues that could affect the results. For example, players in the A1 League may face tougher tasks, which can help them do better and be stronger even when they are hard. Smith and Smoll [66] say that competitive pressure may make top athletes more dedicated and driven. This could lead them to adopt coping mechanisms that are less critical outside of competition. Focusing on internal rewards might also result in A2 League players becoming complacent, as there is little incentive to perform at a peak level in the absence of high-stakes competition. Players in the A1 League are used to dealing with a lot of stress and competition, so this could slow their long-term growth. So, the competitive setting has a big effect on achievement and mental health, which calls into question the idea that less competition always leads to better mental health [65].

4.8. Influence of Years as a Basketball Team Member on Commitment

Athletes with 6-10 years as basketball team members exhibited significantly higher levels in Personal Investments-Loss than those with over 20 years of membership. Those with 11-15 years as team members reported significantly higher levels in Social Constraints, Social Support-Emotional, and Desire to Excel-Mastery Achievement compared to athletes with 15-20 years. Furthermore, for Social Support-Informational, athletes with 1-5 and 11-15 years as team members recorded higher levels than those with 15-20 years. This trend corroborates the results of Clancy et al. [67], indicating that intermediate levels of experience correlate with heightened emotional and social investments, signifying a period in which athletes reconcile commitment with social and motivational adaptations within their teams. Cucui & Cucui [6] similarly emphasise that intrinsic motivation, strengthened by skill development and social support, fosters longevity in sports, hence corroborating the present results on the significance of mental resilience in team sports such as basketball.

4.9. Limitations-Future Recommendations

A limitation of the survey is based on the sample, which was large but cannot be considered representative. This element can be addressed by future sample composition through probability sampling. The collection of replies using a questionnaire is intrinsically limited by the inability to authenticate the veracity of the submitted answers. Alongside the constraints related to sample representation and the reliability of questionnaire responses, further potential limitations may include the influence of social desirability bias, whereby participants may provide answers they believe to be more socially acceptable or favorable, rather than articulating their true sentiments. Understanding these limits is essential for appropriately understanding the results and ensuring that future research frameworks include approaches designed to mitigate such biases, thereby enhancing the validity of the findings. Utilizing mixed-method approaches, such as integrating qualitative interviews with quantitative surveys, may provide deeper insights and facilitate data triangulation to more effectively address these difficulties. The tactics used enhance the credibility of research findings and promote a deeper understanding of participant perspectives, eventually yielding more comprehensive conclusions that may more effectively guide both practice and policy.

5. Conclusions

This research substantiates the hypothesis that motivation and commitment among basketball players are significantly affected by the satisfaction of fundamental psychological needs: autonomy, competence, and relatedness. Moderate levels of intrinsic and extrinsic motivation maintain engagement and mitigate burnout, supporting the notion that settings that promote individual success and acknowledgement foster intrinsic motivation and resilience. Research indicates that the equilibrium between inner drive and external recognition promotes athletes' enduring commitment and contentment with their activity. Moreover, pleasure, social support, and chances for personal development were recognized as significant factors influencing commitment, particularly among athletes with intermediate experience, underscoring the importance of supporting surroundings. Disparities by gender imply that tailored strategies might improve both male and female athletes' performance and well-being. Despite limitations related to sample size and self-reporting, this study emphasizes the importance of environments that meet athletes' psychological needs, promoting long-term motivation, resilience, and happiness in competitive sports.

Author Contributions

Conceptualization, T.R. and N.K.; methodology, T.R.; validation, T.R., N.K. and E.A.; formal analysis, N.M.; investigation, N.K and E.A..; data curation, N.K.; writing—original draft preparation, N.K.; writing—review and editing, T.R and N.M..; visualization, E.A.; supervision, N.K. and E.A.; project administration, N.K and E.A.

Funding

This research received no external funding.

Informed Consent Statement

Not applicable.

Conflicts of Interest

The authors declare no conflicts of interest.

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Table 1. Demographics distribution.
Table 1. Demographics distribution.
Demographic Percentage (%) Frequency (N)
Gender
Male 66.0 279
Female 34.0 144
Age (years)
16-22 66.2 280
23-27 14.2 60
28-32 9.0 38
33-37 5.2 22
37+ 5.4 23
Educational level
High school diploma 76.8 325
Diploma of Vocational Education and Training / Accreditation 3.5 15
University degree 9.6 83
Marital status
Single 90.5 383
Married 8.0 34
Divorced 1.4 6
Category of competence for athletic period 2023-2024
A1 Basket League Women 17.0 72
A2 Elite League Women 50.4 213
National League 1 12.8 54
National League 2 5.2 22
Amateur level 14.7 62
Years as a basketball team member
1-5 13.2 56
6-10 13.0 55
11-15 64.5 273
16-20 5.9 25
20+ 3.3 14
Table 2. Variable reliability.
Table 2. Variable reliability.
Factor Cronbach's Alpha N of Items
Motivation .887 33
Competence .928 5
Choice .873 4
IPLOC .881 3
Volition .776 3
Relatedness .923 5
Enjoyment .911 4
Valuable Opportunities .857 4
Other priorities .869 5
Personal Investments-Loss .880 5
Personal Investments-Quantity .871 3
Social constraints .744 4
Social Support-Emotional .878 4
Social Support-Informational .757 5
Desire to Excel-Mastery Achievement .890 6
Desire to Excel-Social Achievement .873 5
Enthusiastic Commitment .837 5
Constrained Commitment .804 5
Table 3. Location Measures and measures of variability.
Table 3. Location Measures and measures of variability.
N Minimum Maximum Mean Std.Deviation
Motivation 423 1.00 5.00 3.4318 .47330
Valid N (listwise) 423
Competence 423 1.00 7.00 5.1489 1.30280
Choice 423 1.00 7.00 4.2937 1.40787
Internal perceived locus of causality (IPLOC) 423 1.00 7.00 5.3814 1.46040
Volition 423 1.00 7.00 4.7478 1.01980
Relatedness 423 1.00 7.00 5.3626 1.38872
Valid N (listwise) 423
Sport Enjoyment 423 1.00 5.00 4.2080 .91566
Valuable Opportunities 423 1.00 5.00 4.0290 .92293
Other priorities 423 1.00 5.00 3.0408 .97296
Personal Investments-Loss 423 1.00 5.00 3.6652 .90867
Personal Investments-Quantity 423 1.00 5.00 4.1269 .88247
Social constraints 423 1.00 5.00 3.1241 .90628
Social Support-Emotional 423 1.00 5.00 3.8428 .96139
Social Support-Informational 423 1.00 5.00 3.5556 .82042
Desire to Excel-Mastery Achievement 423 1.00 5.00 3.9965 .82996
Desire to Excel-Social Achievement 423 1.00 5.00 3.9092 .85248
Enthusiastic Commitment 423 1.00 5.00 3.9400 .87019
Constrained Commitment 423 1.00 5.00 2.4922 .95427
Valid N (listwise) 423
Table 4. Checking the distribution of variables.
Table 4. Checking the distribution of variables.
Kolmogorov-Smirnov
Statistic df Sig.
Motivation .139 423 .000
Choice .063 423 .000
Internal perceived locus of causality (IPLOC) .146 423 .000
Volition .208 423 .000
Relatedness .119 423 .000
Table 5. Checking the distribution of variables.
Table 5. Checking the distribution of variables.
Kolmogorov-Smirnov
Statistic df Sig.
Sport Enjoyment .194 423 .000
Valuable Opportunities .146 423 .000
Other priorities .083 423 .000
Personal Investments-Loss .119 423 .000
Personal Investments-Quantity .178 423 .000
Social constraints .072 423 .000
Social Support-Emotional .149 423 .000
Social Support-Informational .099 423 .000
Desire to Excel-Mastery Achievement .131 423 .000
Desire to Excel-Social Achievement; .115 423 .000
Enthusiastic Commitment .147 423 .000
Constrained Commitment .108 423 .000
Table 6. Correlations between Motivation and Commitment (Spearman’s rho).
Table 6. Correlations between Motivation and Commitment (Spearman’s rho).
M SO VO OP PIL PIQ DC SSE SSI DTEM DTES EC CC
M Correlation Coefficient 1.000 .265** .327** .176** .353** .314** .236** .199** .268** .333** .390** .272** .104*
Sig. (2-tailed) . .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .032
SO Correlation Coefficient .265** 1.000 .723** -.022 .454** .672** .193** .584** .501** .717** .629** .829** -.347**
Sig. (2-tailed) .000 . .000 .646 .000 .000 .000 .000 .000 .000 .000 .000 .000
VO Correlation Coefficient .327** .723** 1.000 .127** .600** .727** .360** .533** .520** .721** .702** .705** -.100*
Sig. (2-tailed) .000 .000 . .009 .000 .000 .000 .000 .000 .000 .000 .000 .039
OP Correlation Coefficient .176** -.022 .127** 1.000 .270** .104* .335** .144** .186** .135** .175** -.007 .556**
Sig. (2-tailed) .000 .646 .009 . .000 .032 .000 .003 .000 .005 .000 .879 .000
PIL Correlation Coefficient .353** .454** .600** .270** 1.000 .618** .514** .431** .482** .613** .573** .566** .239**
Sig. (2-tailed) .000 .000 .000 .000 . .000 .000 .000 .000 .000 .000 .000 .000
PIQ Correlation Coefficient .314** .672** .727** .104* .618** 1.000 .334** .588** .518** .767** .703** .683** -.082
Sig. (2-tailed) .000 .000 .000 .032 .000 . .000 .000 .000 .000 .000 .000 .091
SC Correlation Coefficient .236** .193** .360** .335** .514** .334** 1.000 .342** .490** .349** .371** .353** .480**
Sig. (2-tailed) .000 .000 .000 .000 .000 .000 . .000 .000 .000 .000 .000 .000
SSE Correlation Coefficient .199** .584** .533** .144** .431** .588** .342** 1.000 .635** .602** .517** .635** -.040
Sig. (2-tailed) .000 .000 .000 .003 .000 .000 .000 . .000 .000 .000 .000 .411
SSI Correlation Coefficient .268** .501** .520** .186** .482** .518** .490** .635** 1.000 .610** .552** .696** .137**
Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000 .000 . .000 .000 .000 .005
DTEM Correlation Coefficient .333** .717** .721** .135** .613** .767** .349** .602** .610** 1.000 .808** .765** -.087
Sig. (2-tailed) .000 .000 .000 .005 .000 .000 .000 .000 .000 . .000 .000 .073
DTES Correlation Coefficient .390** .629** .702** .175** .573** .703** .371** .517** .552** .808** 1.000 .658** -.019
Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 . .000 .697
EC Correlation Coefficient .272** .829** .705** -.007 .566** .683** .353** .635** .696** .765** .658** 1.000 -.208**
Sig. (2-tailed) .000 .000 .000 .879 .000 .000 .000 .000 .000 .000 .000 . .000
CC Correlation Coefficient .104* -.347** -.100* .556** .239** -.082 .480** -.040 .137** -.087 -.019 -.208** 1.000
Sig. (2-tailed) .032 .000 .039 .000 .000 .091 .000 .411 .005 .073 .697 .000 .
**. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed). M = Motivation. SO = Sport Enjoyment. VO = Valuable Opportunities. OP = Other Priorities. PIL = Personal. Investments-Loss. PIQ = Personal Investments-Quantity. SC = Social Constraints. SSE = Social Support-Emotional. SSI = Social Support-Informational. DTEM = Desire to Excel -Mastery Achievement. DTES = Desire to Excel-Social Achievement. EC = Enthusiastic Commitment. CC = Constrained Commitment.
Table 7. Correlations of variables (Spearman's rho).
Table 7. Correlations of variables (Spearman's rho).
Motivation Competence Choice Internal perceived locus of causality (IPLOC) Volition Relatedness
Motivation Correlation Coefficient 1.000 .374** .231** .312** .205** .305**
Sig. (2-tailed) . .000 .000 .000 .000 .000
Competence Correlation Coefficient .374** 1.000 .541** .675** .405** .524**
Sig. (2-tailed) .000 . .000 .000 .000 .000
Choice Correlation Coefficient .231** .541** 1.000 .538** .356** .385**
Sig. (2-tailed) .000 .000 . .000 .000 .000
Internal perceived locus of causality (IPLOC) Correlation Coefficient .312** .675** .538** 1.000 .553** .574**
Sig. (2-tailed) .000 .000 .000 . .000 .000
Volition Correlation Coefficient .205** .405** .356** .553** 1.000 .415**
Sig. (2-tailed) .000 .000 .000 .000 . .000
Relatedness Correlation Coefficient .305** .524** .385** .574** .415** 1.000
Sig. (2-tailed) .000 .000 .000 .000 .000 .
**. Correlation is significant at the 0.01 level (2-tailed).
Table 8. Effects of gender influence on the variables Basic needs in sports and Commitment.
Table 8. Effects of gender influence on the variables Basic needs in sports and Commitment.
Internal perceived locus of causality (IPLOC) Relatedness Valuable Opportunities Personal Investments-Quantity Social Support-Emotional Desire to Excel-Mastery Achievement Constrained Commitment
Mann-Whitney U 16850.500 17153.000 17393.000 15426.000 17126.500 17720.000 17521.500
Wilcoxon W 55910.500 56213.000 56453.000 54486.000 56186.500 56780.000 27961.500
Z -2.733 -2.471 -2.316 -3.982 -2.501 -1.995 -2.159
Asymp. Sig. (2-tailed) .006 .013 .021 .000 .012 .046 .031
Table 9. Mean ranks for the Commitment variable per gender.
Table 9. Mean ranks for the Commitment variable per gender.
Gender N Mean Rank Sum of Ranks
Internal perceived locus of causality (IPLOC) Male 279 200.40 55910.50
Female 144 234.48 33765.50
Total 423
Relatedness Male 279 201.48 56213.00
Female 144 232.38 33463.00
Total 423
Valuable Opportunities Male 279 202.34 56453.00
Female 144 230.72 33223.00
Total 423
Personal Investments-Quantity Male 279 195.29 54486.00
Female 144 244.38 35190.00
Total 423
Social Support-Emotional Male 279 201.39 56186.50
Female 144 232.57 33489.50
Total 423
Desire to Excel-Mastery Achievement Male 279 203.51 56780.00
Female 144 228.44 32896.00
Total 423
Constrained Commitment Male 279 221.20 61714.50
Female 144 194.18 27961.50
Total 423
Table 10. Kruskal Wallis results for the levels of Basic needs in sports based on the category of competence.
Table 10. Kruskal Wallis results for the levels of Basic needs in sports based on the category of competence.
Competence Choice Internal perceived locus of causality (IPLOC) Volition Relatedness
Kruskal-Wallis H 12.430 15.529 23.999 12.928 9.825
df 4 4 4 4 4
Asymp. Sig. .014 .004 .000 .012 .043
a. Kruskal Wallis Test. b. Grouping Variable: Category of competence for athletic period 2023-2024.
Table 11. Kruskal Wallis results for the levels of Commitment based on the category of competence.
Table 11. Kruskal Wallis results for the levels of Commitment based on the category of competence.
Sport enjoyment Other priorities Personal Investments - Loss Personal Investments-Quantity Desire to Excel-Mastery Achievement Desire to Excel-Social Achievement
Kruskal-Wallis H 12.041 19.867 12.383 18.879 15.572 16.835
df 4 4 4 4 4 4
Asymp. Sig. .017 .001 .015 .001 .004 .002
Table 12. Kruskal Wallis results for the levels of Commitment based on the category of competence.
Table 12. Kruskal Wallis results for the levels of Commitment based on the category of competence.
Personal Investments-Loss Social constraints Social Support-Emotional Social Support-Informational Desire to Excel-Mastery Achievement
Kruskal-Wallis H 14.483 10.094 11.804 17.682 11.229
df 4 4 4 4 4
Asymp. Sig. .006 .039 .019 .001 .024
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