Introduction

The relationship between motivating conditions and the fulfillment of psychological needs illustrates that players’ motivation is intricately linked to their commitment to basketball. Athletes’ motivation is enhanced, and their dedication to the sport is strengthened in environments that promote individual accomplishments and recognize achievements [1]. For example, basketball players who perceive recognition within their team dynamics often develop greater resilience, enabling them to better handle challenges [2]. This framework suggests that intrinsic drive is fostered through critical psychological needs: autonomy, competence, and meaningful relatedness. These factors further solidify players’ commitment to basketball [3]. Teixeira et al. emphasize that providing players with the ability to control their actions and participation enhances autonomy, competence is supported by acknowledging skill development, and relatedness is fostered through strong bonds with coaches and teammates [4]. When these psychological needs are adequately satisfied, players are more likely to draw motivation from self-improvement, which is vital for maintaining long-term commitment to basketball [4].

Intrinsic motivation also plays a crucial role in developing resilience and perseverance. Roberts et al. argue that athletes driven by an internal desire for self-betterment, rather than external rewards, demonstrate stronger commitment [5]. In competitive environments like basketball, where external rewards may be insufficient to sustain an athlete’s dedication, intrinsic motivation becomes essential [6]. This long-term commitment to basketball is rooted in intrinsic factors such as personal satisfaction and a passion for the sport [5]. Furthermore, athletes’ commitment is shaped by their mental competencies and motivational orientations [7]. Cucui and Cucui contend that athletes who develop mental skills aligned with their intrinsic motivation typically show enhanced focus and a greater commitment to self-improvement, reinforcing their engagement in the sport [6]. Similarly, Šimková and Válková find that junior basketball players’ loyalty to the sport is often strengthened through enjoyable experiences and a cooperative team environment [8]. Basketball players who thrive in supportive settings that address their needs for autonomy, competence, and relatedness are more likely to experience intrinsic motivation, ultimately leading to sustained commitment [1].

The performance and experiences of basketball athletes are influenced by a range of psychological factors, including motivation, mental preparedness, emotional regulation, and social support [9]. These factors shape athletes’ ability to overcome challenges, manage stress, and engage fully with their sport, especially in high-pressure competitive settings [10, 11]. Understanding and optimizing these psychological aspects are vital for maximizing athlete performance in both competitive and broader contexts [12].

Motivation, in particular, drives basketball players to persist, develop, and fully immerse themselves in their sport [13]. Environments that foster intrinsic motivation focusing on personal growth and skill development rather than mere victory enhance performance by promoting satisfaction and resilience [10]. Conversely, a competition-driven atmosphere that prioritizes outperforming others can increase anxiety and diminish satisfaction, especially in the face of adversity [14]. Basketball players with a strong inclination toward skill development and learning report higher levels of satisfaction and sustained performance, while those primarily motivated by outperforming peers may experience increased anxiety during competitions [10]. Furthermore, a focus on personal growth promotes resilience, enabling players to recover from setbacks and maintain a mindset oriented toward long-term improvement [15].

Mental readiness is another key psychological skill in basketball, requiring athletes to maintain focus, regulate emotions, and exhibit resilience in demanding situations. Techniques such as mental imagery, self-talk, and relaxation strategies are foundational for building confidence and concentration [11]. Mental visualization, in particular, allows athletes to mentally rehearse successful actions, boosting self-efficacy and reducing performance-related anxiety [9]. Athletes who practice these techniques are better equipped to handle pressure, maintain cognitive clarity, and recover quickly from mistakes [16]. Stress management, closely tied to mental readiness, is essential for maintaining consistency and adaptability in basketball. Stress can impair cognitive clarity and physical precision, making effective coping mechanisms critical for optimal performance under pressure [9]. Basketball players who use mindfulness and relaxation techniques manage emotions better, stay focused, and reduce mental barriers, resulting in improved performance and fewer mistakes [17].

The social environment, including support from coaches, teammates, and family, significantly influences basketball players’ motivation, commitment, and well-being. Positive social support fosters a sense of belonging, which is essential for building resilience and drive. Athletes who perceive their coaches as supportive and who develop strong bonds with teammates are more likely to remain committed to their sport and persevere through challenges [12]. When players’ psychological needs for autonomy, competence, and relatedness are fulfilled through social support, they generally demonstrate higher levels of well-being, motivation, and performance. Such supportive environments enhance individual performance and strengthen team dynamics [18]. Coaches, in particular, have a significant impact on both individual athletes and the overall team. By providing consistent and constructive feedback and fostering open communication, basketball coaches create a climate of trust that enhances players’ learning experiences and reinforces team cohesion [19]. Athletes often develop a strong sense of inclusion within their teams, which translates into increased motivation and improved performance as they become more dedicated to the team’s collective success [20].

Emotional stability and mental toughness directly influence basketball players’ ability to manage stress and maintain consistent performance. Emotional regulation helps athletes sustain focus and make rational decisions under pressure [21]. The ability to manage emotions is crucial for navigating the highs and lows of competitive sports, as maintaining composure is essential for peak performance [22]. Mental toughness, characterized by the ability to endure stress and persist through adversity, is a vital psychological skill in basketball. It enhances players’ ability to meet both physical and psychological demands with confidence and agility [23]. Players who manage stress effectively are more likely to sustain high performance in challenging situations. Techniques such as controlled breathing and relaxation training can help athletes maintain calmness, supporting precise decisionmaking and reducing mental fatigue during critical moments [24]. Resilience, fostered through positive self-talk and goal setting, enables athletes to recover quickly from errors and reengage with confidence, which is vital for maintaining agility and composure in competitive scenarios [25]. In basketball, resilience allows players to focus on the game despite mistakes, turning potential failures into opportunities for growth [15].

The connection between psychological well-being and athletic performance is pivotal for understanding how basketball players can achieve both personal fulfillment and optimal performance [26]. Key psychological processes not only influence players’ performance under pressure but also contribute to their overall well-being and commitment to the sport [27]. For basketball athletes, addressing mental processes alongside physical training ensures a comprehensive approach that supports both competitive success and personal satisfaction [28].

Consistent with Self-Determination Theory (SDT), fulfilling basic psychological needs—autonomy, competence, and relatedness promotes intrinsic motivation, a critical factor for athletes’ wellbeing. When these needs are met, athletes are more likely to pursue mastery goals, increasing their motivation and enjoyment of the sport [28]. Autonomy, particularly within the context of basketball, where individual accountability and team dynamics converge, helps athletes remain motivated over time, which is essential for both well-being and sustained performance [29]. Additionally, intrinsic motivation drives players’ adherence to training routines and dedication, linking emotional satisfaction to their ability to recover both in sports and in life [30]. By fostering internal control, athletes are better equipped to navigate stress, maintain focus, and prevent burnout. Fulfillment of psychological needs not only enhances motivation but also builds resilience and long-term commitment to basketball [31].

Anxiety in high-performance basketball contexts can have both positive and negative effects on performance, depending on how it is managed. Uncontrolled anxiety often reduces self-confidence and impairs performance [27]. However, when athletes sustain their confidence, anxiety can serve as a motivational force, sharpening focus and determination. Self-confidence is particularly critical under pressure, enabling athletes to use anxiety constructively rather than letting it hinder their concentration and mental acuity [32]. Psychological traits such as resilience and self-confidence are essential for managing the stress of competitive performance. Athletes with stable psychological traits are better equipped to confront the mental challenges inherent in competitive basketball [32]. Mental toughness is thus a key factor in navigating both internal and external pressures, promoting consistency and focus during competition [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 KhanVilkar 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 masteryoriented 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, athletecentered 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 address critical gaps in the existing literature by focusing on the psychological processes that influence the experiences and performance of basketball athletes. While previous research has extensively highlighted the role of motivation, psychological needs, and commitment in sports performance, limited empirical studies have specifically examined how these factors interact within the unique context of basketball. By exploring the interplay between motivation, the fulfillment of basic psychological needs (autonomy, competence, and relatedness), and commitment, this study provides a nuanced understanding of the factors driving intrinsic motivation, athlete well-being, and sustained engagement in basketball. The findings of this research contribute to the literature in three significant ways: First, this study applies Self-Determination Theory (SDT) to basketball, elucidating the impact of psychological needs on motivation and commitment in high-pressure sports contexts. Furthermore, it provides actionable recommendations for coaches and sports psychologists to cultivate supportive environments that promote intrinsic motivation, resilience, and long-term athlete development. Lastly, by focussing specifically on basketball athletes, the research fills a gap in existing literature that frequently generalises findings across various sports without accounting for the distinct psychological and environmental challenges inherent to team-based sports like basketball. This study aims to connect theoretical frameworks with practical applications, offering evidence-based insights to enhance coaching techniques and athlete support programs.

Materials and Methods

Participants

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, including amateur, semiprofessional, and professional players. Participants were included based on the following criteria: (1) they were active basketball players at the time of data collection, (2) they had at least one year of continuous experience in competitive basketball, and (3) they were aged between 16 and 35 years. Athletes who were not actively competing or who had less than one year of basketball experience were excluded to ensure a focus on consistent engagement with the sport. 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.

Measures

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. The questions were based on the Perceived Motivational Climate in Sport Questionnaire-2 tool (PMCSQ-2). 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. The scales were measured using the Basic Needs Satisfaction in Sport Scale tool (BNSSS) [51]. 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 InvestmentsLoss, 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 questions were based on the Sport Commitment Questionnaire-2 tool [52].

Procedure

The data collection was done in November 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

Data analysis was done with SPSS 25.0.0. Initially, the answers were coded and the variables of the questionnaire were produced. Descriptive statistical analysis was then performed and tables and graphs were produced to present the demographics and levels of survey variables. Next, reliability testing was performed through Cronbach’s alpha index and distribution test via KolmogorovSmirnov test. For the first and second research questions, correlation analysis was performed through Spearman’s s index s. The choice of a nonparametric correlation index was made as it was found that the data of all variables did not follow the normal distribution. Thus, a non-parametric test was preferred, which does not require assumptions such as regularity and homoscedasticity. For the third research question, the Mann-Whitney U test and Kruskal Wallis test were used. Initially, it is noted that in the case of the third research question, non-parametric methods were selected since there was no normal distribution in the data. In addition, the Mann-Whitney test was used for demographic variables such as gender which contained up to two categories. Similarly, the Kruskal Wallis test was used for demographic variables such as sports category which contained more than two categories. The significance level was 0.05.

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).

Table 1: Demographics distribution.

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 Commit-ment variable, 12 factors were used, which indicated a reliable result overall (Table 2).

Table 2: Variable reliability.

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 sam-ple 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 InvestmentsQuantity 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 SupportEmotional 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 (Figures 1-3).

Figure 1: Histogram for Motivation

Figure 2: Simple Bar Mean of Competence, Choice, Internal perceived locus of causality (IPLOC), Mean of Volition, Mean of Relatedness by INDEX.

Figure 3: Simple Bar Mean of Sport enjoyment, Valuable Opportunities, Other priorities, Personal Investments-Loss, Personal InvestmentsQuantity, Social constraints, Social Support-Emotional, Social Support-Informational, Desire to Excel-Mastery Achievement, Desire to Excel-Social Achievement, Enthusiastic Commitment, Constraine Commitment.

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 (Tables 2,3).

Table 2: Checking the distribution of variables.

Table 3: Checking the distribution of variables.

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 4).

Table 4: Correlations between Motivation and Commitment (Spearman’s rho);**.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 ExcelSocial Achievement. EC = Enthusiastic Commitment; CC = Constrained Commitment.

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 5).

Table 5: Correlations of variables (Spearman’s rho);**.Correlation is significant at the 0.01 level (2-tailed).

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 6).

Table 6: Effects of gender influence on the variables Basic needs in sports and Commitment.

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 (Figure 4).

Figure 4: Clustered Bar Internal perceived locus of causality (IPLOC), Relatedness, Valuable Opportunities, Personal InvestmentsQuantity, Social Support-Emotional, Desire to Excel-Mastery Achievement, Constrained Commitment by Gender.

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 7).

Table 7: Kruskal Wallis results for the levels of Basic needs in sports based on the category of competence;a. Kruskal Wallis Test; b.Grouping Variable: Category of competence for athletic period 2023-2024.

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) (Figure 5).

Figure 5: Simple Boxplot of Relatedness by Category of competence for athletic period 2023-2024.

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 SupportInformational factor (H = 17.682, p = .001), and the Desire to Excel-Mastery Achievement factor (H = 11.229, p = .024) (Figure 6).

Figure 6: Kruskal Wallis results for the levels of Commitment based on the category of competence.