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Article contents

Coaching behavior and effectiveness in sport and exercise psychology.

• Ronald E. Smith Ronald E. Smith Department of Psychology, University of Washington
•  and  Frank L. Smoll Frank L. Smoll Department of Psychology, University of Washington
• https://doi.org/10.1093/acrefore/9780190236557.013.188
• Published online: 19 December 2017

Coaches occupy a central role in sport, fulfilling instructional, organizational, strategic, and social relationship functions, and their relationships with athletes influence both skill development and psychosocial outcomes of sport participation. This review presents the major theoretical models and empirical results derived from coaching research, focusing on the measurement and correlates of coaching behaviors and on intervention programs designed to enhance coaching effectiveness.

A strong empirical literature on motor skill development has addressed the development of technical sport skills, guided in part by a model that divides the skill acquisition process into cognitive, associative, and autonomous phases, each requiring specific coaching knowledge and instructional techniques. Social-cognitive theory’s mediational model, the multidimensional model of sport leadership, achievement goal theory, and self-determination theory have been highly influential in research on the psychosocial aspects of the sport environment. These conceptual models have inspired basic research on the antecedents and consequences of defined coaching behaviors as well as applied research on coach training programs designed to enhance athletes’ sport outcomes. Of the few programs that have been systematically evaluated, outcomes such as enjoyment, liking for coach and teammates, team cohesion, self-esteem, performance anxiety, athletes’ motivational orientation, and sport attrition can be influenced in a salutary fashion by a brief intervention with specific empirically derived behavioral guidelines that focus on creating a mastery motivational climate and positive coach-athlete interactions. However, other existing programs have yet to demonstrate efficacy in controlled outcome research.

• coaching behaviors
• leadership measurement
• behavioral assessment
• motor skill development
• social cognitive theory
• multidimensional leadership model
• achievement goal theory
• self-determination theory
• coaching behavior interventions
• psychosocial outcomes

Introduction

Coaches occupy a central role in sport, fulfilling instructional, organizational, strategic, and social relationship functions. Athletes’ skill acquisition, success, enjoyment, continued participation, and physical and psychological well-being are all strongly influenced by coaching behaviors. Not surprisingly, therefore, research on coaching behaviors and their consequences have been a strong focus of research in sport and exercise psychology. This body of scientific literature illustrates important reciprocal linkages between theory, research, and practice. This review focuses on three central facets of this research literature: measurement of coaching behaviors; relations between coaching behaviors and other variables, and interventions designed to enhance coaching practices.

Measurement and Correlates of Coaching Behaviors

Theory and measurement are intimately related. Theoretical models cannot be tested without measures that provide operational definitions of the model’s constructs, and the constructs provide the basis for the content of the measures, whether the measurement model involves questionnaire items completed by coaches and athletes or systematic observation and coding of actual coaching behaviors. Within sport and exercise psychology, several theoretical models have guided research on coaching behaviors. They are considered in their historical order of appearance.

Social-Cognitive Learning Theory: The Mediational Model

Direct observation of behavior is a hallmark of behavioral approaches, including social cognitive learning theory (Mischel, 1973 ; Bandura, 1986 ). The fact that coaching behaviors occur in a public context where they can be directly observed, categorized, and quantified inspired the development of behavioral coding systems beginning in the 1970s. An early example was the use of a ten-category system to assess the coaching behaviors of legendary University of California, Los Angeles basketball coach John Wooden (Tharp & Gallimore, 1976 ). Based on more than 30 hours of observation during team practices, the data showed that Wooden spent approximately 50% of his time giving verbal instruction, 12.7% in admonitions to hustle, and about 7% giving either encouragement and compliments or scolds, respectively. They also described stylistic aspects of his coaching, such as giving very brief and specific instructions and demonstrations that seldom lasted more than 5 seconds.

At about the same time, the Coaching Behavior Assessment System (CBAS) was developed as a research tool to permit the direct observation and coding of coaches’ actions during practices and games (Smith, Smoll, & Hunt, 1977 ). The CBAS contained 12 categories divided into two major classes of behaviors. Reactive (elicited) behaviors are responses to immediately preceding athlete or team behaviors, while spontaneous (emitted) behaviors are initiated by the coach and are not a response to a discernible preceding event. Reactive behaviors are responses to either desirable performance or effort (i.e., reinforcement, nonreinforcement), mistakes and errors (i.e., mistake-contingent encouragement, mistake-contingent technical instruction, punishment, punitive technical instruction, ignoring mistakes), or misbehaviors on the part of athletes (i.e., keeping control). The spontaneous class includes general technical instruction, general encouragement, organization, and general communication (unrelated to the current situation). The system thus involves basic interactions between the situation and the coach’s behavior. Use of the CBAS in observing and coding coaching behaviors in a variety of sports has shown that (a) the scoring system is sufficiently comprehensive to incorporate the vast majority of overt leader behaviors, (b) high interrater reliability can be obtained, and (c) individual differences in behavioral patterns can be discerned (Smith, Smoll, & Christensen, 1996 ).

The CBAS was developed within a cognitive-behavioral mediational model that involved interactions between the situation, coaching behaviors, the athlete’s perceptions of the behaviors, and the athlete’s reactions to the behavior (Smoll & Smith, 1989 ). The athlete’s reactions are assumed to be mediated by the athlete’s encoding and perception of the coach’s behavior. This assumption led to the development of a questionnaire (CBAS Perceived Behaviors sScale) for athletes, asking them how frequently their coach engaged in each of the CBAS categories. The latter consists of definitional items that provide examples of prototypic categorical behaviors. For example, the preface to a question on mistake-contingent encouragement may include the following: “A coach may say: ‘Sometimes players goof and make mistakes.’ Some coaches give their players support and encouragement after they make a mistake. For example, they may say, ‘That’s OK. Don’t worry about it; you’ll get ‘em next time.’ Other coaches don’t give much encouragement after mistakes.” Then the survey follows with “How often did your coach encourage you after you made mistakes?” In a study involving 51 youth baseball coaches, 542 athletes, and 57,213 coded behaviors, team-level bivariate correlations between observed and perceived behaviors were variable, with the highest levels of agreement occurring for the categories involving the coaches’ responses to mistakes (+.54 for punishment, +.37 for punitive technical instruction, and +.31 for mistake-contingent technical instruction). Canonical correlation analyses of the observed and perceived behaviors revealed dimensions that correlated +.89 with one another and were both related to attitudes toward the coach, assessed at the end of the season. Both behavioral and perceived dimensions had their highest loadings on the supportive (i.e., positive reinforcement and mistake-contingent encouragement) and the punitive behavioral categories. Notably, however, although the level of agreement reflects as much as 30% common variance, the level of agreement allows for substantial lack of correspondence between observed behaviors and athlete perceptions, and for variation in athletes’ perceptions of a particular coach. Also in accord with the mediational model, athlete-perceived coaching behaviors were more highly and consistently related to their attitudes toward the coach than were observed behaviors. Five behaviors (i.e., mistake-contingent encouragement, general encouragement, punishment, punitive technical instruction, and general technical instruction) were correlated with positive evaluations of the coach at values between .34 and .43, with the punitive categories being negatively correlated with attitudes toward the coach (Smith, Smoll, & Curtis, 1978 ).

A companion self-report CBAS questionnaire modeled on the athlete perception form was also created for coaches. Research showed that, consistent with the mediational model, athlete-perceived coaching behaviors were more strongly related to outcome variables than were the observed behaviors. Furthermore, athletes’ reports were more strongly related to the observed behaviors than were the coaches’ self-reports, indicating that except with regard to punitive behaviors, coaches have limited awareness of how they behave (Smith et al., 1978 ).

Factor analyses of the CBAS revealed three major factors that account for approximately 75% of the behavioral variance: (a) supportiveness (comprised of reinforcement and mistake-contingent encouragement), (b) instructiveness (general technical instruction and mistake-contingent technical instruction versus general communication and general encouragement), and (c) punitiveness (punishment and punitive technical instruction). Relations between coaches’ scores on these behavioral dimensions and athletes’ postseason attitude measures indicated that players responded most favorably to coaches who engaged in higher percentages of supportive and instructional behaviors (Smith et al., 1978 ). Athletes on teams whose coaches created a supportive environment also liked their teammates more. A somewhat surprising finding was that the team’s win-loss record was essentially unrelated to how well the players liked the coach and how much they wanted to play for the coach in the future. This finding that coaching behaviors were far more important predictors of liking for the coach than was win-loss record was replicated in another study involving youth basketball (Cumming, Smoll, Smith, & Grossbard, 2007 ). Notably, however, winning assumed greater importance beyond age 12, although it continued to be a less important attitudinal determinant than coaching behaviors.

As the mediational model predicts, athlete’s reactions to coaching behaviors are influenced by both athlete and situational characteristics. For example, athletes with low in self-esteem are especially responsive to variations in supportive and instructional behaviors in terms of their liking for coaches, preferring coaches who are high on both dimensions, whereas children with high self-esteem are less influenced by how supportive or instructive the coach is (Smith & Smoll, 1990 ). Situational characteristics also matter. In one study in which score of the baseball games were assessed each half inning, factor scores on the supportiveness, punitiveness, and instructiveness dimensions revealed that the rate of supportive behaviors that coaches delivered while their team was winning correlated highly with athlete’s postseason liking, whereas supportive behaviors that occurred while the team was losing bore no relation to liking for the coach. The opposite occurred for punitive behaviors, which were strongly and negatively related to liking when delivered in losing situations, but were only weakly related when given during winning situations. Instructiveness was not differentially affected by the score at the time it occurred (Smith, Shoda, Cumming, & Smoll, 2009 ).

The CBAS has been used in many studies, particularly within youth sports, to develop behavioral profiles of coaches, to assess relations between coaching behaviors and other variables, such as evaluative reactions to the coach, team cohesion, and sport attrition, as well as athletes’ anxiety and self-esteem. It has also been used to measure behavioral changes that occur as a result of coach training (e.g., Smith, Smoll, & Curtis, 1979 ; Conroy & Coatsworth, 2004 ; Lewis, Groom, & Roberts, 2014 ). The CBAS has given impetus to the development of other behavioral coding systems containing similar or related behavioral categories (Morgan, Muir, & Abraham, 2014 ). One recent example, the Coach Analysis and Intervention System (Cushion, Harvey, Muir, & Nelson, 2012 ) uses computer technology to code a wide variety of verbal and nonverbal behaviors and the circumstances under which they occur, to whom they are directed, and how they are combined when a coach exhibits several behaviors simultaneously. Another valuable tool allows for the coding of both coach and athlete behaviors, permitting an analysis of coach-athlete interaction patterns (Erickson, Cộté, Hollenstein, & Deakin, 2011 ). These recent developments promise to build upon the research base derived from the CBAS over the past four decades.

Multidimensional Model of Sport Leadership

The study of leadership has a long history in mainstream psychology, spanning social psychology, industrial-organizational psychology, and military psychology (VanVactor, 2013 ). Drawing upon the many theories of leadership, Chelladurai ( 1993 , 2012 ) advanced a multidimensional model of leadership that includes situational characteristics, leader characteristics, and member characteristics. To measure leader characteristics, Chelladurai focused on five dimensions of coaching behavior: (a) training and instruction; (b) democratic behavior (allowing athletes a voice in team decisions); (c) autocratic behaviors (decisions restricted to the coach); (d) social support (expressing personal concern for individual athletes); and (e) positive feedback for good performance. These dimensions are measured by a 40-item leadership scale for sports (LSS), which assesses athletes’ preferences for specific behaviors, their perceptions of their coach’s behaviors, and coaches’ perceptions of their own behavior. The scale has acceptable psychometric properties and has been used in many studies of coaches.

The multidimensional model predicts that athlete performance and satisfaction will be greatest when required (situationally elicited) behaviors, preferred leader behaviors, and actual leader behaviors are aligned. Although support has been found for this hypothesis (Chelladurai, 1984 , 2012 ), results have been inconsistent, with congruent findings for some subscales and not for others, and with inconsistent patterns across studies. In general, however, low discrepancies between training and instruction, social support, and positive feedback tend to be more often related to satisfaction, while autocratic behaviors that exceed preferences are aversive and related to dissatisfaction.

Clearly, other variables interact with the congruence measure in ways as yet undetermined. Of particular interest in this regard is the fact that preferred leader behaviors can vary among athletes. For example, athletes with high anxiety prefer more social support and positive feedback behaviors than do athletes with low anxiety, and athletes with low levels of motivation prefer autocratic behaviors that apparently substitute for internal motivation (Horn, Bloom, Berglund, & Packard, 2011 ). Older and more accomplished athletes prefer coaches who are both autocratic and socially supportive. Males prefer training and instructional and an autocratic style more than women do, whereas women tend to prefer a more democratic style. Studies have also shown marked differences across different nations and cultures (Chelladurai & Reimer, 1998 ). Thus, within this model, there is no “one size fits all” preferred coaching pattern. Rather, coaches who are flexible and can adapt their coaching behaviors to the situation and to the preferences of individual athletes are likely to be most successful.

Given the substantial amount of research involving the LSS, it is puzzling that although many positive findings have occurred in terms of differences between groups of athletes and support has been found for the importance of alignment between preferred and actual coach behaviors, relations between hypotheses derived from the multidimensional model and objective measures of performance have proven to be weaker than expected, and at times inconsistent with expectations (Chelladurai & Reimer, 2012 ). Objective performance is an understandably challenging target variable, as it is affected by many factors beyond leadership style, including athletic talent, unforeseen injuries, strength of opponents, and an array of psychological factors that are largely beyond the coach’s influence. Also, quantitative measures of broad classes of behavior, whether coded with the CBAS or reported, do not necessarily reflect important qualities of the behavior (e.g., instructional adequacy or encouragement delivered in a sarcastic fashion), a fact that can reduce relations to performance. Moreover, there is evidence that coaches are perceived as responding differentially to more and less successful athletes. In a study of collegiate football players, for example, higher-performing athletes (starters) rated their coaches as engaging in significantly higher levels of training and instruction, as having a more democratic and a less autocratic decision-making style, as being more socially supportive, and as offering more positive feedback than did lower-status athletes labeled “survivors” by their coaches. The latter perceived their coaches as more autocratic and as low on the other four behavioral dimensions. Additionally, longitudinal evidence exists that LSS behaviors are not stable over the course of a season, with instructional, democratic, and positive feedback showing the largest changes (Fletcher & Roberts, 2013 ). Temporal invariance could therefore affect perceived behavior scores on the LSS and cloud relationships of the LSS with other variables across studies.

Finally, the multidimensional model is complex, with many “moving parts.” It is possible that complex and as yet undiscovered interactions among mediating factors remain hidden, as in the mediation model, where nonsignificant overall relations between CBAS observed behaviors and attitudes toward the coach when behaviors were aggregated across game situations suddenly became highly significant when the game situation variable was taken into account.

Given the degree of conceptual overlap between the mediational and multidimensional models of coaching behavior, it is interesting to assess relations between the CBAS and the LSS. A study of high school athletes that related LSS scores to scores on the CBAS athlete form revealed strong relations between scores on the two scales, and both LSS and CBAS scores accounted for substantial and similar amount of variance in positive attitudes toward the coach (Cumming, Smith, & Smoll, 2006 ). For example, the CBAS categories accounted for 39% of the variance, and the LSS scales accounted for 37% of the variance in the amount of enjoyment experienced while playing for the coach. In accord with predictions made by Chelladurai ( 1993 ), the LSS positive feedback scale was highly correlated with the CBAS categories of reinforcement and general encouragement and negatively related to nonreinforcement. However, the same pattern was shown for the LSS social support scale and, in general, all of the positively toned CBAS behaviors correlated well with all of the LSS scales, except autocratic, the only scale that correlated positively with the punitive CBAS categories. In general, therefore, convergent validity greatly exceeded discriminant validity in the LSS-CBAS relations. High positive correlations among the training, democratic, positive feedback, and social support scales of the LSS add to the discriminant validity issue.

Achievement Goal Theory

No theory has had a greater impact on sport psychology over the past two decades than achievement goal theory (AGT). Originally developed to study motivation within the educational domain (Nicholls, 1989 ; Ames, 1992 ), the relevance of the theory to motivational issues in sport soon became apparent, inspiring a substantial amount of sport psychology research.

Achievement goal theory focuses on the function and the meaning of goal-directed actions, based on how participants define success and how they judge whether or not they have demonstrated competence. The two central constructs in the theory are individual goal orientations that guide achievement perceptions and behavior, and the motivational climate created within achievement settings. The theory posits two separate conceptions of success represented in mastery (task) and ego achievement goal orientations. In mastery orientation, success is self-referenced, defined in terms of personal improvement, enjoyment, effort, and learning from mistakes. In ego orientation, success is other-referenced, achieved through besting others or equaling their level of performance using minimal effort (Ames, 1992 ; Roberts, 2001 ).

According to AGT, how an individual defines success and competence is influenced by interacting dispositional and environmental factors. Environmental conditions that emphasize and reinforce mastery or ego success criteria comprise the motivational climate. Achievement goal theory posits two types of motivational climates that promote either mastery or ego conceptions of success. A mastery climate emphasizes enjoyment, giving maximum effort, and personal improvement as indicators of success, stresses the importance of each team member and promotes mutual support and cooperative learning. Mistakes are viewed not as something to be dreaded but as a natural consequence of learning and as providing the feedback needed to improve performance; coaches provide encouragement and corrective instruction when they occur.

In an ego climate, there is a strong emphasis on outcome. Success is defined as winning out over others; differential attention is focused on the best athletes; intrateam rivalry is promoted by comparing athletes favorably or unfavorably with one another; and mistakes are negatively evaluated and often punished (Ames, 1992 ; Roberts, 2001 ).

Achievement goal theory has inspired the development of sport-specific measures designed to assess differences in both achievement goal orientations and in motivational climates created by coaches, parents, and peers. The most widely employed coach-initiated motivational climate scale is the Perceived Motivational Climate in Sport Questionnaire-2 (PIMCSQ-2; Newton, Duda, & Yin, 2000 ), which is appropriate by its reading level for adolescents and adult populations. An adaptation designed for children down to ages 8 or 9 is the Motivational Climate Scale for Youth Sport (MCSYS; Smith, Cumming, & Smoll, 2008 ). Both scales have separate mastery (task) and ego-climate subscales, but the PIMCSQ-2 also measures underlying facets of the task climate (i.e., cooperative learning, effort-improvement emphasis, and an important role for all participants) and ego climate (i.e., intrateam rivalry, unequal recognition, and punishment for mistakes). Most studies use the superordinate task and ego scales. The MCSYS mastery and ego scales correlate −.38, indicating that coaches engage in both classes of behavior. Sample mastery scale items are (a) “The coach told players to help each other get better,” (b) “The coach made players feel good when they improved a skill,” and (c) “Coach said that all of us were important to the team’s success.” Sample ego-scale items are (a) “Winning games was the most important thing for the coach,” (b) “Players were taken out of games if they made a mistake,” and (c) “The coach paid most attention to the best players.”

The motivational climate created by coaches has been shown to be related to a wide array of sport outcomes (Duda & Treasure, 2015 ; McArdle & Duda, 2002 ). As in educational settings, a strong body of empirical evidence shows that a mastery climate is linked to a wide array of positive outcomes, including enhanced enjoyment and satisfaction, higher levels of perceived competence and performance, lower performance anxiety, higher levels of self-esteem, and higher levels of intrinsic motivation for sport participation. A mastery environment fosters the belief that effort, which is controllable, is the key to sport success, whereas athletes in an ego climate place greater emphasis on ability. A mastery climate promotes greater goal persistence and sustained effort, and athletes tend to adopt adaptive achievement strategies such as selecting challenging tasks, giving maximum effort, persisting in the face of setbacks, and taking pride in personal improvement. In contrast, an ego-involving climate promotes social comparison as a basis for success judgments, whereas an ego environment yields discouragement when a positive outcome is not achieved. In a mastery climate, athletes show more positive and prosocial moral attitudes, whereas an ego climate is associated with greater willingness to cheat or do whatever is necessary to win. Finally, a mastery climate fosters greater team cohesion, attraction among team members, positive evaluations of the coach, and lower rates of sport attrition compared with an ego climate. Consistent with AGT, a large body of research shows that mastery and ego climates promote and strengthen corresponding goal orientations (Duda & Treasure, 2015 ). Over the course of a sport season, youth athletes exposed to a mastery climate exhibit increases in mastery goal orientation scores and decreases in ego goal orientation, whereas those in an ego climate show increases in ego goal orientation (Smith, Smoll, & Cumming, 2009 ).

Notably, behaviors associated with mastery and ego climates are not mutually exclusive; rather, they are a matter of emphasis. Most coaches engage in a mixture of mastery- and ego-oriented behaviors, particularly during competition, when the orientation is likely to shift the outcome. The same is true of athletes’ goal orientations. Highly successful athletes often have an overall mastery orientation but shift into an ego-oriented state during competition, when the focus is on winning.

One indicator of the influence of the motivational climate comes from studies comparing its effects on athletes’ reactions to their sport experience with team success (win-loss record). In a study of 10- to 15-year-old athletes, their team’s winning percentage was positively related to athletes’ judgments of their coaches’ perceived knowledge and teaching ability, but motivational climate accounted for far more variance than did winning percentage in terms of how much they liked playing for the coach and wished to do so in the future (Cumming et al., 2007 ). In a later study of adolescent basketball players, motivational climate exhibited stronger and more pervasive relations to the athletes’ attitudes toward the coach, teammates, and the sport experience than did winning (Breiger, Cumming, Smith, & Smoll, 2015 ). For both boys and girls, winning percentage was related to enjoyment derived from playing the sport and intention to continue participation the following season. Likewise, for both boys and girls, mastery climate scores were positively and significantly related to enjoyment playing on the team, liking for the coach, and perceived liking by the coach. However, the results also showed that gender influences athletes’ responses to both winning and to the motivational climate. An ego climate clearly had a more negative impact on girls, with ego climate scores being negatively related to how much girls liked the sport, how much fun they had playing on their teams, and how much they believed the coach liked them.

An ego climate also affected the importance of win-loss record in ways a mastery climate did not. For both boys and girls, significant relations were found between winning percentage and liking for the sport, personal importance of winning, and intention to return the following year. Nonetheless, gender differences also occurred. In an ego climate, liking for and desire to again play for the coach, liking for teammates and enjoyment playing on the team were positively related to winning record for boys, but not for girls. Enjoyment playing on the team and desire to play for the coach again were positively and significantly related to winning record for boys, but not for girls. It thus appears that winning within an ego climate is more important than it is in a mastery climate, but that winning may affect different attitudes and aspects of the experience for boys than for girls.

Motivational climate research has focused attention on the coach-athlete relationship. Building upon this foundation, several new conceptual models have appeared that focus on the quality of the relationship that is to be found particularly within a mastery climate. Relational coaching (Jowett, 2009 ) focuses on four important aspects of the coach-athlete relationship: (a) mutual closeness, (b) commitment to the relationship, (c) complementarity (ability to work cooperatively), and (d) co-orientation (the ability to view the relationship from both one’s own and the other’s perspective). The Coach-Athlete Relationship Questionnaire is used to measure these aspects of the relationship, and research using this measure shows that relationships that are high on these factors produce the most enjoyable and productive coach-athlete climate.

Another derivative conception, again related to the mastery climate but not identical with it, is the caring environment, where individuals are made to feel a sense of belonging and in which participants treat one another with kindness and mutual respect. Research on the caring environment has shown that the positive emotions produced by such an environment mediate positive well-being in athletes (Fry, Guivernau, Kim, Newton, Gano-Overway, & Magyar, 2012 ).

All of the AGT results cited so far are based on athlete perceptions of the motivational climate, using either the PMCSQ or the MCSYS instruments. This is an entirely defensible approach, for as the mediational model described earlier emphasizes, it is the athlete’s perceptions of the climate that mediate the effects of coach behaviors on outcome variables. Nonetheless, the need to assess the actual climate-relevant behaviors of coaches from both methodological and theoretical perspectives has repeatedly been cited (N. Smith et al., 2015 ). A new theoretical advance integrating AGT and self-determination theory, described in the following section, has inspired the development of a new observation system tied to the expanded model.

Self-Determination Theory

A recent theoretical advance integrates AGT with another prominent motivational theory that has special relevance to sport-related motivation (Duda, 2013 ). Self-determination theory (SDT; Deci & Ryan, 2000 ) focuses on factors that influence the development of motivation, particularly intrinsic and extrinsic motivation. The relative strength of intrinsic and extrinsic motivation determines an individual’s sense of autonomy, the extent to which behavior is viewed as self-governed. Together with competence (the perceived mastery over behavior) and relatedness (the perceived sense of belonging), autonomy is considered a basic need that facilitates psychological well-being (Deci & Ryan, 2000 ). SDT proposes that the social environment influences the extent to which these basic needs are satisfied.

SDT holds that internal and external behavioral goals are distributed on a continuum of self-determination. On the self-determined end lies intrinsic motivation, where actions are performed in the service of inherent enjoyment of the activity. The continuum also contains three different variants of extrinsic motivation. From higher to lower self-determination, these are termed (a) identified regulation (in which behavior is related to other goals, such as engaging in the sport to lose weight or improve conditioning), (b) introjected regulation (in which behavior functions to avoid a negative emotion or for ego enhancement), and (c) external regulation (in which the behavior is performed for external reasons, such as tangible rewards or the avoidance of punishment). SDT also retains the concept of amotivation, in which behavior loses all reinforcement value and occurs largely out of habit (e.g., “I’m not sure why I swim any more.”). Generally, because behavior is guided more by external incentives or becomes amotivated, positive qualities of human nature are hindered, whereas greater self-determination or autonomy allows positive qualities to flourish (Deci & Ryan, 2000 ). An imposing literature both within and outside of sport supports this contention and demonstrates superior well-being (i.e., high feelings of autonomy, competence and relatedness) under conditions that foster high intrinsic motivation (e.g., Deci & Ryan, 2000 ; Duda, 2013 ; Amorose & Anderson-Butcher, 2015 ).

The integration of AGT and SDT was inspired by clear conceptual overlap between a mastery motivational climate and situational factors identified in SDT research that promoted the satisfaction of autonomy, relatedness, and competency needs, as well as strong evidence that a mastery motivational climate had salutary effects on the need variables within SDT. Moreover, in the prediction of meaningful sport outcomes, concurrently applying AGT and SDT measures as predictor variables accounted for overlapping but also independent sources of variance (Quested & Duda, 2010 ), and they also related differentially to important aspects of athlete well-being and quality of functioning. Duda ( 2013 ) advanced a hierarchical multidimensional model of empowering and disempowering motivational climates. An empowering environment is mastery-oriented, socially supportive, and autonomy supportive of internal self-regulation. A disempowering climate is ego oriented, punitive, nonsupportive, and controlling.

Although applications of the model are in their relative infancy, both perceived and behavioral-observation measures of the integrated motivational climate have been developed. A 30-item Empowering and Disempowering Motivational Climate Questionnaire-Coach (EDMCQ-C; Appleton, Ntoumanis, Quested, Viladrich, & Duda, 2016 ) allows athletes to rate their coach’s climate relevant behavior on an agree-disagree scale and is used to measure five dimensions of the perceived motivational climate: (a) task involved, (b) ego involved, (c) controlling, (d) autonomy supportive, and (e) socially supportive.

A behavioral observational system, the Multidimensional Motivational Climate Observation System (MMCOS; N. Smith et al., 2015 ) provides a measure used to rate the measure the coach’s observed behaviors in relation to the theoretical model. It is a complex system, consisting of two superordinate dimensions (empowering and disempowering) seven environmental dimensions (autonomy support, controlling, task-involving, ego-involving, relatedness support, relatedness thwarting, and structure), and 32 lower-order coaching strategies that are checked off and used to rate the higher-order dimensions. The system is used to code temporally or event-defined segments (e.g., 5-minute segments in a soccer match). The MMCOS is clearly more complex than the CBAS and provides a more nuanced behavioral profile. However, unlike the CBAS and other behavioral coding systems, it is not a quantitative measure of the frequency with which observed behaviors actually occur; rather, it is a set of observer ratings.

Initial assessment of the construct validity of the perceived and observed behavior measures have been conducted with large multinational samples of athletes representing a variety of sports. One study that assessed relationships between athlete-perceived (EDMCQ-C) and observed (MMCOS) behaviors as well as the relations of both measures to athlete indices of autonomous (internal), externally controlled motivation, and amotivation (N. Smith, Tessier, Tzioumakis, Fabra, Quested, Appleton et al., 2016 ). None of the correlations between athlete-perceived and observed behaviors providing indices of the five empowering and disempowering dimensions exceeded .09, reflecting less than 1% common variance, a figure far lower than that obtained with the CBAS categories derived from social learning theory in a youth sport sample similar in age. Likewise, relationships between the MCCOS behavior measures and the theoretically related athlete motivation measures were quite low, ranging from −.01 to .09 and accounting for less than 1% of the motivational outcome variance. Correlations of the athlete-perceived EDMCQ-C measures with the athlete motivation variables were more favorable, with correlations exceeding .30 found between coach controlling and ego-oriented behaviors and athletes’ externally controlled motivation and amotivation. These results lend stronger evidence for the construct validity of the athlete-perceived measure than those reported for the observational measure. In another study, empowering climate scores on the EDMCQ-C were positively related to enjoyment and self-esteem and negatively related to reduced accomplishment, devaluation, and physical health symptoms, whereas a disempowering climate was negatively related to enjoyment and self-esteem, and positively related to athlete burnout and negative health symptoms (Appleton & Duda, 2016 ). However, a more sophisticated analysis that simultaneously assessed the interactive effects of empowering and disempowering motivational climates accounted for only about 1% of the variance in these targeted outcome variables. Buffering the effects of disempowering coach behaviors required a very high level of empowering behaviors. This result is consistent with CBAS findings that although punitive behavior categories occur with far less frequency than do the positive behaviors (also shown in the observational data of N. Smith et al., 2016 ), they have a disproportionate negative impact on athletes by creating an aversive sport environment.

Enhancing Coaching Effectiveness

There has never been any question that coaches occupy a central role in sports, exerting key influence on sport outcomes through their roles as teachers and strategic planners, and in the relationships they form with athletes and parents. Understandably, therefore, enhancing their pedagogical, strategic, and interpersonal capabilities has long been a focus within sport and exercise psychology. Two lines of emphasis are evident that, historically, have occurred along relatively independent tracks. The first involves instruction in motor learning principles and strategic techniques designed to develop athletes’ physical skills and optimal strategic decision making by coaches. The second emphasis, of more recent origin, is focused on helping coaches to create a psychosocial sport environment that enhances outcomes for athletes. As empirical evidence, such as that reviewed in the previous section, has accumulated showing consistent relationships between coaching behaviors and their impact on athletes and team functioning, coach interventions addressing this domain have been developed.

Enhancing Strategic and Instructional Capabilities

Motor skill learning is highly sport specific, but a strong science base has emerged on general principles involved in learning, maintaining, and improving such skills (Coker, 2013 ; Magill, 2013 ). The dominant model divides the motor learning process into three phases: the cognitive, associative, and autonomous phases. Each of these requires different coaching techniques. In the cognitive phase, explanations and demonstrations by the coach allow athletes to develop a motor program, a set of internal representations, and self-instructions to guide the movement. With practice and feedback, both from the athlete’s sensory systems and from the coach, the motor program is revised, corrected, and refined so that the skill is executed in an increasingly synchronized fashion. The coach designs exercises and practice routines, adjusts instruction depending on the progress being shown, gives corrective feedback, and provides encouragement to facilitate the process.

Once the athlete can execute the skill in the way it was demonstrated, the associative phase begins. In this intermediate phase of learning, the learner has moved from having a general idea of how to perform the skill to being able to perform it accurately and consistently. Speed, accuracy, coordination, and consistency improves even further and the athlete develops an implicit “feel” for the activity based on a more autonomous motor program and the ability to self-correct when errors occur. The coach’s role is now to utilize the skill in actual sport situations and to plan strategy, largely by designing effective practices that allow the athlete to apply the skill to simulated or real competitive situations. Error correction requires the ability to detect increasingly subtle errors and to provide demonstrations and feedback in a manner that can be used for further refinement and skill application. In closed skills (e.g., bowling or free throw shooting), the environment is fairly constant, and consistency of movement is the primary focus. In open skills, where the environment is diverse and unpredictable (e.g., in golf), the coach must help the athlete diversify the movement to meet environmental demands and teach the athlete which environmental cues are key to planning and making adjustments. The provision of effective feedback continues to be an important function of the coach during this phase.

In the autonomous or advanced phase of skill learning, the motor program is run off with little conscious thought or attention to the movement. Indeed, conscious attention to the movement can degrade performance by disrupting the automaticity of the highly developed skill sequence. As Baseball Hall of Famer Yogi Berra once said, “You can’t think and hit at the same time.” The phrase “paralysis by analysis,” popular among coaches and athletes, captures the phenomenon. Performance slumps are perpetuated by cognitive interference with the normal flow of skill execution. During this phase, the major demands on the coach involve highly refined practice routines, subtle error correction, and encouragement and motivational overtures where needed. At this level, exquisite understanding of the skill and ability to communicate effectively are prime requisites for effective coaching. Excellent resources are available to help coaches at all levels of sport refine their sport-specific teaching and strategic skills (e.g., Coker, 2013 ; Martens, 2012 ). Among the newer additions to the coach’s performance enhancement tool kit is instruction in utilizing and teaching athletes not only motor and strategic skills, but also empirically supported psychological skills such as systematic goal setting, attention control, stress management, self-talk, confidence, and mental rehearsal procedures (e.g., Burton & Raedeke, 2008 ).

Enhancing Psychosocial Outcomes in Athletes

Increased awareness of the manner in which the coach-athlete relationship can positively or adversely affect not only skill development but also a wide range of psychosocial outcomes in athletes of all ages is attributable to an enormous body of empirical research. Coaching behaviors have been shown to influence athletes’ self-esteem, motivation, performance anxiety, attitudes toward their sport experience, peer relationships, burnout, psychological skills development, physical well-being, and sport attrition. Concerns about athletes’ well-being, an alarming sport dropout rate exceeding 30% per year in young athletes (Gould, 1987 ) and, in some cases, formal legislation requiring training for youth sport coaches, has stimulated the development of many training programs for coaches over the past four decades. Unfortunately, development has far outstripped systematic evaluation of their effects.

Coach Effectiveness Training/Mastery Approach to Coaching

Widespread concerns about adult-created problems in youth sports prompted the Youth Enrichment in Sports program of research and application. The aims of the project, carried out in two phases were (a) to study relations between coaching behaviors and young athletes’ reactions to their youth sport experience and (b) to use the empirical results as the basis for an evidence-based intervention for coaches (Smith et al., 1978 ). Cognitive social learning theory (Bandura, 1986 ; Mischel, 1973 ) formed the basis for instrument development (e.g., the CBAS) and the intervention procedures, which involved modeling and role playing of desirable behaviors and coach self-monitoring of their behaviors to enhance awareness. A more comprehensive discussion of cognitive-behavioral principles and techniques used in conducting psychologically oriented coach training programs appears elsewhere (Smoll & Smith, 2015 ). Essentially, however, the intervention is designed to influence observed and athlete-perceived coaching behaviors, and these changes, are thought to mediate other effects of the training on young athletes.

Data derived from two large-scale phase 1 studies provided clear links between the CBAS dimensions of supportiveness, instructiveness, and punitiveness and athletes’ reactions to their coach, their teammates, and other aspects of their experience. Phase 2 involved the development and evaluation of a brief and highly focused intervention for youth sport coaches based on the evidence-based phase 1 findings. The intervention initially was called Coach Effectiveness Training (CET). With the development of AGT a decade later, it became clear that the CET guidelines (particularly its conception of success) were entirely consistent with the mastery motivational climate described by AGT, and a later version of the intervention formally introduced motivational climate content. The 75-minute intervention was therefore renamed the Mastery Approach to Coaching (MAC).

The MAC program incorporates two major themes. First, it strongly emphasizes the distinction between positive versus aversive control of behavior (Smith, 2015 ). In a series of coaching “do’s and don’ts” derived from the foundational phase 1 research on coaching behaviors and their effects, coaches are encouraged to increase four specific behaviors: (a) positive reinforcement, (b) mistake-contingent encouragement, (c) corrective instruction given in a positive and encouraging fashion, and (d) sound technical instruction. Coaches are urged to avoid nonreinforcement of positive behaviors, punishment for mistakes, and punitive technical instruction following mistakes. They are also instructed how to establish team rules and reinforce compliance with them to avoid discipline problems, and to reinforce socially supportive behaviors among team members. These guidelines, which are summarized in Table 1 , are designed to increase positive coach-athlete interactions, enhance team solidarity, reduce fear of failure, and promote a positive atmosphere for skill development.

The second important MAC theme is a conception of success as giving maximum effort and becoming the best one can be, rather than an emphasis on winning or outperforming others. Derived from Coach John Wooden’s definition of success as “the sense of self-satisfaction from knowing that you did your best to become the best that you are capable of becoming,” (Wooden & Carty, 2005 , p. 12), MAC-trained coaches are thus encouraged to adopt a four-part philosophy of winning (Smith & Smoll, 2012 , pp. 27–28):

Winning isn’t everything, nor is it the only thing . Young athletes cannot get the most out of sports if they think that the only objective is to beat their opponents. Although winning is an important goal, it is not the most important objective.

Failure is not the same thing as losing . It is important that athletes do not view losing as a sign of failure or as a threat to their personal value.

Success is not equivalent to winning . Neither success nor failure need depend on the outcome of a contest or on a win-loss record. Winning and losing pertain to the outcome of a contest, whereas success and failure do not.

Athletes should be taught that success is found in striving for victory (i.e., success is related to commitment and effort). Athletes should be taught that they are never “losers” if they give maximum effort.

This philosophy, which is highly congruent with a mastery motivational climate, is designed to maximize young athletes’ enjoyment of sport and their chances of deriving the benefits of participation, partly as a result of combating competitive anxiety. Although seeking victory is encouraged as inherent to competitive sports, the ultimate importance of winning is reduced relative to other participation motives. In recognition of the inverse relation between enjoyment and postcompetition stress (Smith, Smoll, & Passer, 2002 ), fun is highlighted as the paramount objective. The philosophy also promotes separation of the athlete’s feelings of self-worth from the game’s outcome, which serves to help overcome fear of failure. The mastery-oriented coaching guidelines and philosophy of winning are thus consistent with the procedures successfully designed by Ames ( 1992 ) and Epstein ( 1988 ) to create a mastery learning climate in the classroom. The behavioral guidelines that form the core of the MAC intervention are shown in Table 1 . The MAC workshop, together with supporting materials, is now available online at www.y-e-sports.org .

Table 1. Summary of Mastery Approach to Coaching Guidelines

Note . Excerpted from the manual given to MAC workshop participants (Smoll & Smith, 2009 ).

A notable finding from observational studies is that coaches have very limited awareness of how they behave, as indicated by low correlations between observed and coach-rated behaviors (N. Smith et al., 2016 ; R. Smith et al., 1978 ). Because behavior change does not occur without awareness of one’s behavior, MAC coaches are taught the use of two proven behavioral-change techniques, namely, behavioral feedback and self-monitoring. To obtain feedback, coaches are encouraged to work with their assistants as a team and share descriptions of each others’ behaviors. Another feedback procedure involves coaches soliciting input directly from their athletes. With respect to self-monitoring, the workshop manual includes a brief Coach Self-Report Form, containing nine items related to the behavioral guidelines that coaches complete after practices and games (Smoll & Smith, 2009 , p. 25). On the form, coaches are asked how often they engaged in the recommended behaviors in relevant situations.

The CET/MAC intervention has been evaluated numerous times in experimental and quasi-experimental studies since its development (for more detailed reviews, see Smith & Smoll, 2011 ; Smoll & Smith, 2015 ). The outcomes supporting the efficacy of the coach-training program are summarized here:

Differences between experimental and control group coaches occurred in both observed and athlete-perceived coach behaviors in accordance with the behavioral guidelines (Smith et al., 1979 ; Smoll, Smith, & Cumming, 2007 ; Lewis et al., 2014 ).

Trained coaches were better liked and rated as better teachers; and their athletes reported more fun playing the sport, and a higher level of attraction among teammates. Increases in athletes’ perceptions of both task-related and social group cohesion have also been reported for youngsters who played for trained versus untrained coaches (Smith et al., 1979 ; McLaren, Eys, & Murray, 2015 ).

Athletes’ reports of their team’s coach-initiated motivational climate clearly supported the efficacy of the intervention. In this regard, trained coaches received significantly higher mastery-climate scores and lower ego-climate scores on the MCSYS climate measure compared with untrained coaches. Moreover, in accord with AGT, male and female athletes who played for trained coaches exhibited increases in mastery goal orientation scores and significant decreases in ego orientation scores. In contrast, athletes who played for control group coaches did not change in their goal orientations from preseason to late season. Paralleling the significant difference between intervention and control groups in sport-related mastery scores, a significant group difference was found on the mastery score of an academic achievement goal scale as well, suggesting generalization of achievement goals (Smoll et al., 2007 ).

Consistent with a self-esteem enhancement model, children with low self-esteem who played for trained coaches show significant increases in feelings of self-worth. Youngsters with low self-esteem in the control group did not change (Smith et al., 1979 ; Smoll, Smith, Barnett, & Everett, 1993 ; Coatsworth & Conroy, 2006 ).

Athletes who played for trained coaches showed significant decreases in sport performance anxiety over the course of the season (Smith, Smoll, & Barnett, 1995 ; Conroy & Coatsworth, 2004 ; Smith, Smoll, & Cumming, 2007 ).

Attrition in youth sports is a pervasive concern that has negative health and psychosocial implications. With the win-loss record controlled, children who played for untrained youth baseball coaches dropped out of all sports the following season at a rate of 26%, whereas those who played for trained coaches had only a 5% dropout rate (Barnett, Smoll, & Smith, 1992 ).

Traditionally, CET/MAC training has been offered in a workshop format. However, many sport psychologists work with individual coaches. A recent and promising adaptation is the Individualized Program for Counseling Coaches (Sousa, Smith, & Cruz, 2008 ; Cruz, Mora, Sousa, & Alcaraz, 2016 ). This individualized intervention combines MAC principles and behavioral guidelines with behavioral feedback and systematic goal setting to help coaches modify their behavior in accordance with their own behavioral objectives.

The intervention occurs in six steps. First, the CBAS is used to code the coach’s behaviors during a series of practices and matches to provide an average of 250–400 coded behaviors, thereby providing baseline data to help coaches become more aware of their coaching pattern and to assess postintervention changes. Next, a 60-minute session is held to go over basic principles concerning the motivational climate and its effects on athletes. In a second 60-minute session, the behavioral guidelines shown in Table 1 are presented in an interactive fashion. In the following session, the coach is presented with his or her behavioral profile derived from the CBAS observations, summarized in terms of the three factorial dimensions of supportiveness, punitiveness, and instructiveness, together with feedback on which behaviors would best be increased or decreased to optimize the coach’s effectiveness. The coach is then asked to select three CBAS categories that they want to increase or decrease. Finally, role playing is used to help the coach rehearse the target behaviors with the guidance of the trainer. The coach is encouraged to self-monitor during subsequent practices and matches and are given guidelines and reminders. CBAS data as well as athlete and coach reports are then collected during two subsequent practices and two matches as at baseline.

The results of the intervention have been very encouraging. In separate single-subject studies involving a total of 5 coaches, the trained coaches have exhibited behavior changes in accordance with their goals in most instances, increasing desirable behaviors and reducing negative ones (Sousa et al., 2008 ; Cruz et al., 2016 ). Of additional interest, generalization effects have been shown in behavior categories that were not specifically targeted by the coach, yielding a more positive behavioral profile overall following the intervention. For example, coaches who chose to increase positive reinforcement and encouragement showed a concomitant drop in punitive behaviors. These behavior changes were in most cases consistent with athlete’s perceptions of the coach’s behaviors on the athlete perception CBAS questionnaire. The encouraging results obtained in these single-coach studies indicate that this adaptation is worthy of further investigation and that its use of feedback and individualized goal setting, both of which have strong empirical support, is a significant feature of the training program.

Despite the rapid proliferation of coach education programs since the early 1970s, almost all of the systematic outcome research on the efficacy of coach training has been done with the CET/MAC program (Langan, Blake, & Lonsdale, 2013 ). Evidence for the efficacy of the intervention has now been provided by five different research groups. Based on the outcome studies, it appears that the empirically derived behavioral principles can be readily applied by coaches and that their application has salutary effects on a range of psychosocial outcome variables in young male and female athletes. However, there is a need for further research, particularly follow-up studies to assess the longer-term impact of the intervention on both coaches and athletes.

Empowering Coaching

The integration of AGT with SDT (Duda, 2013 ) is a major theoretical advance that has resulted in the concept of empowering and disempowering motivational climates. In an empowering climate, athletes strive for mastery goals, feel a sense of belonging, and believe they have a choice over how they behave. In a disempowering environment, the emphasis is on ego goals, punishment is applied, and athletes feel controlled by their coach.

Based on this model, an Empowering Coaching TM intervention was developed, applied, and evaluated in five European countries. The intervention is of 6 hours duration and educates coaches about the tenets of AGT and SDT relating to task and ego climates and intrinsic-extrinsic motivation and offers guidelines for increasing the empowering climate and reducing its disempowering aspects. Video clips and reflective exercises are designed to engage coaches in the content of the workshop (for a more detailed descriptions of the project and the intervention, see Duda, 2013 ; Project PAPA, 2016 ). The program’s emphasis differs somewhat from the CET/MAC empirically based behavioral guidelines approach:

Furthermore, this education programme is not about providing coaches with a “laundry list” of strategies or responses they can and should employ when interacting with their athletes . . . Rather, . . . the aim is to develop coaches’ conceptual understanding of motivation, motivation processes and their consequences. It is assumed that this enhanced “working knowledge” will make it more likely that a more empowering approach to coaching will be adopted, maintained, and generalized to different situations (Duda, 2013 , p. 315).

The intervention was tested in the largest experimental trial undertaken to date, involving 175 clubs, 854 teams, and 7,769 children in five European countries. Outcome variables involved athletes’ perceptions of empowering and disempowering aspects of the motivational climate using the behavioral EDMCQ-C measure, as well as measures of self-esteem, enjoyment, anxiety, and intentions to drop out. Some children wore accelerometers to record activity level during the week, and a subset of coaches was filmed so that their behaviors could be coded using the MCCOS observational instrument.

Several positive results were obtained. Behavioral observations in a subset of trained coaches revealed a more empowering and less disempowering climate over the course of the season. Children who played for trained coaches viewed their motivational climate as less disempowering (but not more empowering) and rated themselves as less likely to drop out of their program. However, no statistically significant positive outcomes have been reported for other important athlete variables, including autonomy, competence, and relatedness need satisfaction, enjoyment, self-esteem, anxiety, athlete burnout, and increased physical activity (Project PAPA, 2016 ). Possibly, the Empowering Coaches TM programs’ heavy emphasis on theoretical and conceptual content interfered with the development of the kind of rule-governed behavior that has been shown to result from adherence to specific behavioral guidelines (Baldwin & Baldwin, 2001 ). A more focused approach with greater emphasis on clear and specific behavioral guidelines may prove more efficacious while at the same time resulting in a more time-limited intervention.

Undoubtedly, coaches play a vital role in the athletic environment, and their behaviors influence the technical, cognitive, strategic, and psychosocial development of athletes. There is a wealth of empirical support for methods of teaching technical skills. The same is not the case in the psychosocial domain. Despite the substantial number of coach intervention programs developed over the past 30 years designed to enhance psychosocial outcomes, it is rather astounding that only a few of these programs have undergone any evaluation of efficacy. Coach training, particularly in the area of youth sports, has become a large-scale commercial enterprise in the United States. The American Sport Education Program , the National Youth Sports Coaches Association , and the Positive Coaching Alliance are among the most visible. Unfortunately, however, although their content does not deviate from what has been established empirically as producing a positive athletic climate, virtually nothing is known about what effects these specific programs actually have on coaches and athletes and how well they achieve their objectives. This absence of empirical attention is understandable, as developers of existing programs have been focused primarily on development, marketing, and dissemination rather than evaluation, and they have not had the benefit of research grants to support evaluation research. However, evaluation research is not only desirable, but essential to providing coaches with the quality of evidence-based training that will have the most salutary impact on their athletes. In the words of Lipsey and Cordray ( 2000 ), “the overarching goal of the program evaluation enterprise is to contribute to the improvement of social conditions by providing scientifically credible information and balanced judgment to legitimate social agents about the effectiveness of interventions intended to produce social benefits” (p. 346).

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Coaching in Sports: Implications for Researchers and Coaches

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Sports Coaching research continues to develop, although with a narrow spread of publication, mainly within Sports Psychology, and small impact across Sports Science journals. Nevertheless, Sports Coaching research potentially investigates an array of basic and applied research questions. Hence, there is an opportunity for improvement. Moreover, there is an increased awareness in several scientific areas, including Sports Science, about several problems pertaining to design, transparency, replicability, and trust of research practices. Particularly in Sports Coaching research, these problems include limited or inadequate validation of surrogate outcomes and lack of multidisciplinary designs, lack of longitudinal and replication studies, inappropriate data analysis and reporting, limited reporting of null or trivial results, and insufficient scientific transparency. In this chapter, we initially discuss the trends of publication in Sports Coaching, highlighting research problems as they pertain to their treatment in other disciplines, namely psychology. Lastly, we illustrate an example applied to Sport Coaching research with a repeated measures design and an interdisciplinary approach as a recommendation to promote transparency, replicability, and trust in Sports Coach research.

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Carvalho, H.M., Gonçalves, C.E. (2020). Coaching in Sports: Implications for Researchers and Coaches. In: Resende, R., Gomes, A.R. (eds) Coaching for Human Development and Performance in Sports. Springer, Cham. https://doi.org/10.1007/978-3-030-63912-9_22

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Sport Coaching Research and Practice

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Research shapes our understanding of practice in powerful and important ways, in sports coaching as in any other discipline. This innovative study explores the philosophical foundations of sport coaching research, examining the often implicit links between research process and practice, descriptions and prescriptions.

Arguing that the assumptions of traditional single-disciplinary accounts, such as those based in psychology or sociology, risk over-simplifying our understanding of coaching, this book presents an alternative framework for sports coaching research based on critical realism. The result is an embedded, relational and emergent conception of coaching practice that opens new ways of thinking about coaching knowledge. Drawing on new empirical case study research, it demonstrates vividly how a critical realist-informed approach can provide a more realistic and accountable knowledge to coaching stakeholders. This knowledge promises to have important implications for coaching, and coach education and development practices.

Sport Coaching Research and Practice: Ontology, Interdisciplinarity and Critical Realism is fascinating reading for any student or researcher working in sports coaching, sport pedagogy, physical education, the philosophy or sociology of sport, or research methodology in sport and exercise.

TABLE OF CONTENTS

Chapter 1 | 31  pages, a new approach for sport coaching research, chapter 2 | 27  pages, psychologized approaches to sport coaching research, chapter 3 | 36  pages, sociologized approaches to sport coaching research, chapter 4 | 33  pages, disciplinary agreements and disagreements about sport coaching, chapter 5 | 41  pages, interdisciplinarity, ontology and critical realism, chapter 6 | 39  pages, a critical realist-informed sport coaching ontology for interdisciplinary thinking and research, chapter 7 | 27  pages, undertaking critical realist-informed interdisciplinary research on sport coaching, chapter 8 | 38  pages, an ethnographic case study of kayak slalom performer development coaching, chapter 9 | 29  pages, reflections on sport coaching and sport coaching research.

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Leadership: Athletes and Coaches in Sport

Authors: Dr. Sharon P. Misasi*, Dr. Gary Morin and Lauren Kwasnowski

Dr. Sharon P. Misasi is a Professor of Exercise Science at Southern Connecticut State University. Dr. Gary Morin is a Professor of Exercise Science, Assistant Athletic Trainer and Program Director of the Athletic Training Education Program. Lauren Kwasnowski is a Research assistant for this study, undergraduate student in the Allied Health Program at the University of Connecticut and a member/captain of the UCONN Division I Lacrosse team.

*Corresponding Author: Sharon P. Misasi PhD, AT. Southern Connecticut State University 501 Crescent Street PE 002B New Haven CT 06515 [email protected]

ABSTRACT This study investigated the interpersonal aspects and perceptions of the coach-athlete relationship as it pertains to collegiate athletes at Division I and II universities and athletes and coaches of different genders. Electronic surveys were emailed to 50 NCAA Division I and 50 Division II head coaches in the Northeast. Coaches were requested to respond to the survey and email the athlete survey to their respective athletes. These surveys were completed by both coaches and athletes: Coach-Athlete Relationship Questionnaire (CART-Q), Leadership Scale for Sports (LSS). The final instrument, Coaching Behavior Scale for Sports (CBS-S), was completed by only the athletes. There were no significant differences found with the CART-Q. The LSS illustrated several areas of significances in the categories of Training, Democratic Behavior, Autocratic Behavior and Social Support. Although there was no significance found in Positive Feedback there was an interesting finding in that female coaches felt they were less likely to provide positive feedback than their male counterparts. The CBS-S has subscales which include: physical training and planning, technical skills, mental preparation, competition strategies, personal rapport and negative personal rapport. Statistical significance was found in the following subscales: competition strategies, personal rapport and negative personal rapport. The coach is a meaningful person in the lives of athletes and the role they play is vital in the athlete’s sport experience. Our results indicate that the level of competitive division appears to play a role in how athletes perceive their coaches and how coaches perceive themselves. In addition, gender differences among coaches’ affect responses of the athletes and the coaches. Leadership is not a simple process. There is no one way to lead and what works for one may not work for all. Therefore, the best one can do is get to know their athletes and work hard to understand their goals, motivations and needs.

KEYWORDS : Coaching, Effective Leadership, Successful Leadership

INTRODUCTION Sport plays a vast and important role in the lives of many. Athletes of all ages are directed by coaches, giving them a significant impact on the athletes. However, the level of impact is unknown, along with the expectations of what athletes want from coaches and how do coaches perceive themselves. The coach’s role is considered to be a highly complex process. Coaches in most settings must complete a variety of tasks such as planning practices and game strategies, organizational tasks and mentoring athletes which does in fact include more than teaching fundamental skills and tactics (Challadurai, 1984; Williams & Krane, 2015; Anshel, 2012; Murphy, 2005; Cox, 2012; Lyle, 2002 and Cote, Yardley, Hay, Sedwick, & Baker, 1999).

There is a difference between an effective leader and a successful leader (Williams & Krane, 2015; Anshel, 2012; Murphy, 2005 and Cox, 2012). A coach’s successful leadership changes an athlete’s behavior as a function of the coach’s effort and gets others to behave as the manager/coach intends them to behave. The task may be completed and the coach’s needs may be satisfied, but the players’ needs are ignored (Cribben, 1981). Effective leadership in coaching occurs when athletes perform in accordance with the coach’s intentions while finding their own needs satisfied. Effective coaches are concerned with maintaining good relations with team members and winning a specific contest (Williams & Krane, 2015; Anshel, 2012; Murphy, 2005; and Cox, 2102). Horn (2002) states that effective coaching behaviors result in the athletes reaching: personal achievements, performance goals and positive psychological outcomes. Cote and Gilbert (2009) define coaching as “the consistent application of integrated professional, interpersonal, and intrapersonal knowledge to improve athletes’ competence, confidence, connection and character” (p. 316). Another important aspect (Horn, 2002) is the athletes’ perception of coaching behaviors. Smoll and Smith (1989) state that athlete’s perception and recall determine coaching effectiveness. Each athlete gives meaning to overt coaching behaviors which creates the athlete’s attitude toward the coach and the sport experience. One’s perception of another’s behavior is more important than the behavior itself when considering one’s feelings toward that person (Shaver, 1975).

As noted, the coach is a very significant person in the lives of athletes and the role they play is key in the athletes’ sport experience (Williams, Kenow, Jerome, Rogers, Sartain, & Darland, 2003; Kavussanu, Boardley, Jutkiewicz, Vincent & Ring, 2008). Central to the coaching process is the coach-athlete interpersonal dynamics (Jowett & Poczwardowski, 2007). Most coaches attempt to act in ways that they believe will develop their athletes’ success and personal enhancement. Horn (2002) states that coaches can positively impact athletic performance, behavior as well as the psychological and emotional well-being of the athlete. The coach-athlete relationship is an important factor affecting sport performance (Serpa, 1999). Jowett and Cockerill (2002) discuss this relationship further. The coach and the athlete interaction is unique with the goal to bring about successful performance outcomes and satisfaction. Olympiou, Jowett & Duda (2008) suggested that an athlete’s perception of the coach-athlete relationship has motivational significance. If the coach-athlete relationship is in sync, successful outcomes can be accomplished (Coe, 1996). Kenow and Williams (1999) recommend that coaches should create positive coach-athlete interactions which will allow the coach to gain insight into the thoughts and emotions of their athletes. Phillips and Jubenville (2009) stated that the coach-athlete relationship is important to both groups’ performance and both must evaluate the other to enhance performance.

Not all relationships are effective and some coaches take negative tactics in their approach to the athletes. These approaches lead to inadequate coach-athlete relationships (Martens, 1987; Smoll & Smith, 1989). These coaches tend to be strict, regimented and even militaristic. Ironically, they tend to be labeled as successful coaches but only seek to have their ambitions realized. They do not care if their athletes are injured, depressed or even burned out (Williams & Krane, 2015; Anshel, 2012; Murphy, 2005; and Cox, 2012; Smoll and Smith, 1989; Jowett & Cockerill, 2002). These negative coaches are arrogant and may even betray the athlete’s trust despite its importance in the relationship (Ryan, 1996).

Williams et al. (2003) stated that there is little research identifying optimal coaching behaviors and those factors that influence the effectiveness of particular behaviors. Included is the need to identify how athletes perceive their coach’s actions and effectiveness. This study investigated the interpersonal aspects and perceptions of the coach-athlete relationship as it pertains to collegiate athletes at Division I and II universities and teams of different genders.

METHODOLOGY After obtaining approval from the Southern Connecticut State University’s Institutional Review Board, contact was made via email to the coaches. The lead researcher sent two emails to the head coaches of NCAA Division I and II varsity sport programs at northeast colleges and universities (n= # of schools). The varsity sport programs included all male and female sports that were sponsored by the selected institutions. The first email was directed to the coaches and offered a series of questions that addressed their perceived behaviors to their athletes. The second email included a request that the attached survey link be forwarded to the athletes on their roster. In total, the two emails were emailed to 50 Division I team coaches and 50 Division II team coaches.

Coaching and athlete survey participants were requested to provide certain demographic information regarding their gender, sport and collegiate level. Each athlete was provided a weblink to the survey instrument, which was distributed through SNAP technology. The instrument consisted of a single survey that was in fact the combination of three distinct devices. All instruments were adjusted to use a 5 point scale. Athletes were asked to rate each item strongly disagree, disagree, neutral, agree and strongly agree. This was done to maintain scoring consistency on all instruments as they were combined into one survey for coaches and one for athletes.

Instrumentation

The first instrument was the Coach-Athlete Relationship Questionnaire (CART-Q). This instrument measures affective, cognitive and behavioral interpersonal aspects in the coach-athlete relationship such as closeness, commitment and complementarity (Jowett and Ntoumanis, 2004).

The second inventory was the Leadership Scale for Sports (LSS). This scale was developed to measure leadership behaviors of sport coaches. A coach’s version permitted participants to self-identify perceptions of their own behavior. The second version allowed the athletes’ to identify their preferences for specific behaviors, and the athletes’ perceptions of the coaches’ behavior. The scale has five dimensions: instructional (training) behavior, democratic behavior, autocratic behavior, social support behavior, and motivational behavior (in the form of positive feedback given) (Chelladurai & Saleh, 1980).

The final instrument was the Coaching Behavior Scale for Sports (CBS-S). This instrument was completed only by the athlete participants. Athletes responded to statements based upon their perception of their coach’s involvement in a particular area. This scale has 47 items that are divided into 7 different constructs: physical training and planning; technical skills; mental preparation; competition strategies; personal rapport; and negative personal rapport (Cote, et al., 1999).

RESULTS Surveys were emailed to 50 Division I (DI) and 50 Division II (DII) universities. Fifty-five female coaches (51%) and 52 male coaches (49%) responded to the survey. There were a total of 61 DI coaches (58%) and 45 DII coaches (43%). Three hundred and ten athletes responded to the survey with 209 female athletes (68%) and 99 (32%) male athletes. There were 135 DI athletes (44%) and 169 DII athletes (56%).

There was no significant difference found the CART-Q. There were significant differences found among certain categories of the LSS. The results of each are listed separately. The LSS is a survey designed to assess coaching behaviors. There are two forms that are used. One form is completed by coaches and serves as a self-assessment of coaching behavior. The second form is designed to be completed by the athletes and to evaluate their own coach’s behavior. Both forms consist of 40 questions which are placed into five domains. The domains of behavior: training, democratic behavior, autocratic, social support and providing positive feedback. A total of 290 athletes responded to the survey. One hundred ninety-eight (n=198) of these athletes were female and 92 athletes were male. There were 103 coaches who responded to the LSS coaching survey. The gender of the coaches was not determined or if they coached male or female sports.

Significant differences were identified across the training domain for responses by the coaches and the athletes (Table 1). Coaching responses differed based on the gender of the participant, with two of the questions identified as significantly different during the univariate analyses (Table 2). These two questions demonstrated that female coaches tended to plan out their activities more often but the male coaches were more insistent that player assignments were performed to “last detail”

The athletes’ responses did not differ by gender as did the coaches’ responses. Instead they differed based on the competitive division of the athletes. The subsequent univariate comparison identified a single significant question (Table 3). This question demonstrated that athletes of Division I institutions were more likely to “give specific instructions to each athlete on what should be done in every situation.”

Democratic Behavior

The second analysis assessed the democratic domain for both the coaches and athletes in terms of gender and competitive division (Table 4). Although coaches did not differ by gender, they did differ by competitive division. The subsequent univariate comparison of the coaches’ responses related to competitive division identified only one question as being significantly different. This specific question demonstrated that NCAA Division I coaches were less likely to let athletes “try their own way even if mistakes were made.” No significant differences were identified across the athlete surveys for gender or competitive division (Table 5).

Autocratic Behavior

The third domain is related to autocratic behaviors conducted by coaches. There was no significant difference between the two genders. There was a significant difference between coaches of NCAA Division I and II competitive programs (Table 6). The subsequent univariate analyses revealed one of the five questions was significantly different between competitive divisions with NCAA Division I coaches less likely to be inclined to explain their actions to their athletes. The athletes saw no significant difference based on gender or for competitive division in terms of autocratic behaviors (Table 7).

Social Support

The athlete’s gender played a role in the perceptions of coach support to team members. However, a similar difference was not identified among athletes based on their competitive division (Table 8). Two questions from the gender comparison were significant (Table 9). Female athletes felt that their coaches were more likely to help settle conflicts within the team than did male athletes. The female athletes also believed that their coaches were more likely to encourage informal relations with athletes. It should be noted, that although only two questions were significantly different, all of the questions related to social support showed that females felt their coaches were more likely to demonstrate acts of social support within the team. The perception of the coaches did not match those of the athletes. There was no significant difference on the perceptions of social support for either gender or competitive gender.

Positive Feedback

Regarding positive feedback there were no significant differences among the multivariate analyses for gender or competitive divisions. The means for the NCAA Division I and the Division II were comparable. Although the mean results demonstrated the female coaches were more likely to give positive feedback in the eyes of their athletes, the responses did not differ enough to demonstrate an overall statistical significance (Table 10). Ironically, although the results were not significant, female coaches felt they were less likely to provide positive feedback than their male counterparts.

Two hundred and ninety-four athletes responded to the Coaching Behavior Scale for Sport (CBS-S). The number of female athletes (n=198) was more than double of the male athletes (n=96). One hundred and thirty-two (n=132) athletes played sports at the NCAA Division I level while 162 participated as a NCAA Division II athlete.

The CBS-S consists of 47 questions that permitted the athletes to evaluate their coaches on behaviors beyond actual sport knowledge. The scale is subdivided into six sub-scales. These subscales include: physical training and planning, technical skills, mental preparation, competition strategies, personal rapport and negative personal rapport. Based on the results of the multivariate testing, no significant differences were identified for gender (Table 11) or competitive division (Table 12) for questions dealing with physical training and planning, technical skills and mental preparation.

However, there was a significant difference how the different genders perceived a coach’s development of competition strategies (Table 11) without a difference due to competitive division (Table 12). Univariate analyses were applied to each of the six subscale questions related to coaching competition strategy (Table 13). Two questions were identified as significantly different with higher scores for male athletes related to the use of goals in sports. It appeared that coaches of male athletes were more likely to monitor an athlete’s progress toward his goals and to help identify target dates to meet those goals.

The sub-scale examining personal rapport on a positive nature demonstrated significant differences based on gender, but once again not with competitive division (Table 11, 12). Five of the seven questions related to positive personal rapport demonstrated significant differences (Table 14). Although a common trait of coaches for both genders, male athletes demonstrated higher response scores. Males felt their coaches were more likely to prepare them to face different situations, were more likely to keep them focused and were more likely to maintain a consistent competition routine. Males also felt that their coaches were more likely to deal with their problems during the competition and display more confidence in their competitive performance.

The final subscale considered negative personal rapport, which consisted of questions examining the athletes’ perceptions of whether the coach was approachable and how likely the coach was to use negative behavior such as yelling, insults and intimidation as part of their actions. A significant difference was identified for these perceptions based on the athletes’ gender, but not with their competitive division (Table 11, 12). During the univariate analysis, individual questions were identified during the post-hoc testing as significantly different across gender (Table 15). Male athletes were more likely to perceive their coaches as being approachable about personal problems, but were also more likely to have their coaches yell at them when angry. For both genders, it should be noted these questions dealing with negative coaching tended to have low means demonstrating that these behaviors are more likely not to occur than to actually occur.

According to the CBS-S, the final summary revealed that there were no apparent differences in the perceptions of coaching behaviors when comparing NCAA Division I or II athletes. Comparisons based on gender demonstrated significant differences on those subscales primarily focusing on interpersonal relationships between coaches and athletes. During the univariate analyses of those subscales that were significantly different, several questions were significant and most cases the males were more likely to have the higher means.

DISCUSSION AND CONCLUSION Leadership is very important in sport. Leadership as provided by the coach plays a very significant role in the lives of athletes and in the athlete’s sport experience (Williams et al., 2003). However, the means by which a coach demonstrates leadership behaviors may vary from coach to coach. Coaches at different levels of competition may be expected to interact with athletes differently due to the different levels of athletic ability and possibly the greater pressure to win for employment security. Coaching attitudes and actions may also differ based on the athlete’s gender. This study attempted to examine if competition level and gender played a role in coaching leadership behavior.

Our results indicate that the level of competitive division appears to play a role in how athletes perceive their coaches and how coaches perceive themselves. Athletes of NCAA DI institutions reported that their coaches had higher expectations of their athletes in terms of carrying out assignments, and were less likely to permit their athletes to freelance in their sport. One would assume this to be the case, DI coaches are often pressured to win from many sources, and so they would want tasks done their way. The coaches of high profile sports, especially, must win and be successful, otherwise are often fired from their positions as the normal repercussion. The male sports of football and basketball typify this tendency and help to explain these results. As stated by Weinberg and Gould (2003) male athletes prefer autocratic styles while female athletes prefer a democratic style and one they can participate in. Additionally, with the higher availability of scholarship aid available, Division I coaches can expect to have a higher quality athlete affording coaches the ability to expect more in the form of results from the athlete.

Additionally, DI coaches were less likely to provide an explanation of their actions to their athletes. This demonstrates that the DI coaches tend to be more dictatorial in nature, but it is unknown if this trend is related to the greater threat of job termination, anticipated higher coaching experience and/or it is a personality type needed to work at this level. There is some evidence that males prefer more instructive behaviors and an autocratic style of leadership (Chelladurai & Saleh, 1978; Terry, 1984).

Females prefer more democratic coaching behaviors and a participatory coaching style that allows them to help make the decisions (Weinberg & Gould, 2003). However, it is important to note that there are more similarities than differences between male and female preferences for specific coaching behaviors (Horn, 2002). Regardless of level there was no difference in the perceived level of positive feedback given to the athletes.

Gender differences among coaches’ effect responses of the athletes and the coaches. Female coaches were more likely to plan ahead for training but seemed to be more forgiving if their athletes did not fulfill every aspect of their assignments. The level of social support provided by female coaches was higher than their male counterparts according to the athletes. Female coaches were perceived to be more involved in settling issues among team members and to encourage formal and informal relationships with the athletes. Unger and Crawford (1992) have stated that female-female friendships are more confiding, intimate and emotionally expressive than male-male therefore the female-female relationships are characterized by emotionality. Because of this, female coaches and athletes may be more likely to form highly interdependent and emotionally laden relationships in the athletic realm. The relationships between male coaches and male athletes may be based on the aim to achieve performance goals without the expression of feelings.

This study appears to support these findings. Female athletes felt that their coaches were more likely to help settle conflicts within the team than did male athletes. The female athletes also believed that their coaches were more likely to encourage informal relations with athletes. It should be noted, that although only two questions were significantly different, all of the questions related to social support had a consistent trend. It appears that female coaches tend to have a more personal connection with their athletes. Although not investigated in this study, female athletes discuss personal issues with female coaches. On the other hand, male coaches appear distant and do not have the direct emotional attachment with from their athletes. This is not to say they do not care or support their athletes, instead the male athletes are more interested in the goal minus the emotion. This was also supported by Miller, Ogilvie and Branch (2008) who stated male’s value feedback and technical instruction. Female athletes had a greater need for emotion.

A limitation to the study is that the athletes did not identify the coach’s gender as part of their responses. It is expected that a large majority of the male athletes had male coaches, however female sports do not have the same homogeneity of coaching genders. Frey, Czech, Kent and Johnson (2006) found that athletes (male and female) prefer a male coach instead of a female coach. Magnusen and Rhea (2009) found that male athletes (all football players) preferred a male strength and conditioning coach. These athletes were less comfortable with a female strength coach. As for female athletes, they did not have a gender preference. The female athletes wanted a qualified strength and conditioning coach regardless of gender whereas male athletes preferred a male irrespective of how qualified the female coach may be.

Further research should determine if male coaches of women’s teams take on those roles/interactions identified with the female coaches. So the question would be: does the athlete’s gender drive the actions of the coaches or does the coach’s gender drive how they deal with the athlete? In light of female coaches now entering the NFL or NBA, will female coaches change when dealing with male athletes and assume a more typical ‘male’ attitude?

Although there are more similarities than differences in the preferred leadership behaviors of men and women, one should note that Weinberg and Gould (2003) state that, ‘determining what makes effective sports leadership is clearly not a simple process’ (p. 213). Coaches are responsible for the whole development of the athlete: physical, mental, technical and tactical (Becker, 2009). This will enable the athletes to achieve their goals. However, the answer to the question what makes the athlete-coach interaction well-balanced does not seem so obvious.

Vince Lombardi was known for his intensity and passion but more importantly the expectations he placed upon his athletes. As a coach, Lombardi treated each player as an individual thereby having the ability to be flexible and meet their needs. It has been stated that Lombardi knew his players well. He knew which players would succeed by providing positive reinforcement and those that would respond to criticism (Kramer and Shaap, 1968).

In summary, leadership in sport is a fascinating topic. There is no one way to lead and what works for one may not work for all. Research can aid in assisting coaches with tried and true practices that will enable them to assist their athletes in becoming the best they can be.

APPLICATION IN SPORT In summary, leadership is sport in a intriguing topic. There is no one way to lead and what works for one may not work for all. Research can aid in assisting coaches with tried and true practices that will enable them to assist their athletes in becoming the best they can be. Illustrated in our research was the result that there is a difference in DI and DII. Coaches in DI were more authoritarian in nature and had higher expectations of their athletes. So athletes must understand this if their desire is to play at that level. So how does one apply this study? The most important concept a coach can apply is gaining an understanding and knowledge of your athletes first and foremost. Once you have gained that you will be able to assist them in reaching their goals.

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Women at the Olympics and Paralympics: Past, Present, and Future

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The Olympic and Paralympic Games have undergone a remarkable transformation since their inception in 1896 and 1960, respectively. From 0% and 3.5% of athletes being female, to today where female athletes will compete at the 2024 Paris Olympic and Paralympic Games in equal numbers compared with male athletes. While achieving gender parity in Olympic and Paralympic participation is a significant milestone, it is now critical to explore beyond this point and focus on ensuring that female athletes are competing at their highest potential. This involves not only addressing historical and ongoing challenges in sociology and economics but also recognizing that just a fraction of sports performance research is conducted exclusively in female participants, which highlights a critical gap in understanding and supporting their competitive success. The primary focus of this Research Topic is on celebrating the extraordinary achievements of female Olympians and Paralympians while also addressing the ongoing challenges that need to be overcome. We will delve into the factors driving the surge in women’s Olympic and Paralympic participation, spotlight recent advances such as progressive policies and advocacy initiatives, and explore how these developments are shaping a more inclusive Olympic landscape. This Research Topic seeks to highlight successful strategies and innovative interventions that are creating an environment where female athletes can thrive. We invite contributions that offer fresh perspectives and actionable insights into a variety of themes, including but not limited to: • Historical analyses of the evolution of women's participation in the Olympics and significant milestones achieved • Evaluations of gender equity policies and their impact on transforming the Olympic experience for women • Studies on media representation and its influence on public perception of female Olympic athletes • Investigations into socio-cultural and economic factors affecting women's engagement and performance in Olympic sports • Biological and training considerations specific to female athletes, addressing the underrepresentation of women in sports performance research. We encourage interdisciplinary research that bridges sociology, health and science, and economics and technology. This collection is dedicated to not only celebrating the athletes of today but also crafting a roadmap for future advancements in female athletic performance. Through this dialogue, we aim to amplify the achievements of female athletes and drive forward meaningful progress that ensures their continued success and representation on the Olympic stage. Join us in shaping the future of women in sport and celebrating their role in the ongoing Olympic legacy.

Keywords : women, sport, the olympics, athlete, exercise

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Raiders Fall To the Cowboys & We Have Everything Coach Antonio Pierce Said Post Game

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LAS VEGAS, Nev.—The Las Vegas Raiders completed their fourth week of the 2024 NFL Training Camp tonight by losing to the Dallas Cowboys at Allegiant Stadium in their second preseason exhibition game.Head coach Antonio Pierce stressed the importance of this game when discussing the looming quarterback battles between Aidan O’Connell and Gardner Minshew.

“The goal would be to hopefully make a decision after this game this Saturday. We got to get ready to play football. We got enough film and we'll have two games here to evaluate both quarterbacks to see how they'll play. And we haven't really made a decision on who's going to start or not. But either way, both with play a quarter."

Davante Adams did not dress for the game.  He said he preferred not to play in the preseason, and Coach Pierce said all healthy players would.

After the game, Pierce said of Adams’ injury that he had injured himself in earlier this week.

Gardner Minshew got the start at QB, and he was Minshew: 10/21 for 95 yards with zero interceptions and zero touchdowns for an unimpressive quarterback rating of 61%

Aidan O’Connell was 14/20 for 96 yards, had one interception, and one touchdown for a quarterback rating of 76%.

After the game, we met with Coach Antonio Pierce to discuss the contest.

You can watch everything that he said below.

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Bears assistant Jennifer King was a successful basketball coach but couldn’t pass up NFL opportunity

FILE - Chicago Bears running back Ian Wheeler (33) celebrates with offensive assistant-running backs coach Jennifer King after scoring during the second half of a preseason NFL football game against the Buffalo Bills in Orchard Park, N.Y., Saturday, Aug. 10, 2024. (AP Photo/Adrian Kraus, File)

Chicago Bears coach Jennifer King gestures on the field in Canton, Ohio, Aug. 1, 2024, ahead of the Hall of Fame NFL football game against the Cleveland Browns. (AP Photo/Rob Maadi)

FILE - Jennifer King of the Chicago Bears NFL football team, posed Friday, Feb. 23, 2024, in Lake Forest, Ill. (AP Photo/File)

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Jennifer King was a champion women’s basketball coach when she made a tough decision to pursue a career in football.

She hasn’t had to look back.

Within three years of switching sports, King became the first Black female full-time coach in the NFL when Washington hired her in 2021 as an assistant running backs coach. She spent three seasons with the Commanders before joining Matt Eberflus’ staff with the Chicago Bears this year as an offensive assistant, focusing on running backs.

King is one of 15 women who are full-time coaches in the NFL this season, a new league record and most for any male professional sports league in the world.

King’s journey began in 2018 when she met then-Panthers coach Ron Rivera at the NFL’s Women’s Forum , an annual event that connects participants with owners, general managers, head coaches and club executives.

King had just led Johnson & Wales University-Charlotte to the United States Collegiate Athletic Association Division II title. But football was first in her heart. She played quarterback and safety on a women’s tackle football team and wanted an opportunity in coaching.

“I always liked football more,” King said. “But it was hard to leave basketball. We had won a championship. I was national coach of the year. Like, things were going really well for me. And to just leave was difficult, but I just felt it was something that I couldn’t pass up.”

King’s basketball team practiced close enough to the Panthers’ training facility that she could hear and watch them. When she met Rivera, he already knew who she was from her basketball pedigree. Rivera’s wife, Stephanie, was an assistant coach in the WNBA and she told him a woman who plays the game would do well in coaching.

“He invited me over for rookie minicamp,” King said. “I thought I’d be there for two days, but it turned into about four months.”

King spent the summer of 2018 as a coaching intern for the Panthers, working with wide receivers. She moved on to join Rick Neuheisel’s staff as an assistant wide receivers coach and special teams coach for Arizona in the short-lived Alliance of American Football.

King returned to Carolina to serve as a running backs coaching intern in 2019 and joined Dartmouth’s staff as an offensive assistant that fall.

When Rivera became the head coach in Washington in 2020, King again joined his staff as a coaching intern. He gave her a full-time job the following year.

“She had a drive about her that just really said she wanted to do this, and she also played the game,” Rivera said. “She talked about the little things that she learned in playing, showing how aware she is about the game. So I just thought that she had this desire, this drive to want to do this at the top level, and I wanted to create an opportunity.

“As we were going through the internship, the one thing I appreciated was she was smart enough to know what she didn’t know. And you could tell because she became really inquisitive. She asked good questions, she listened, and she didn’t pretend to know. Believe me, I’ve been around (male) coaches who pretend to know. And, when they do that, usually, they get it wrong. But she just listened when she didn’t know and that’s what truly intrigued me was that she was willing to just take a backseat, listen, take it in and ask questions.”

Over the past five years, there has been a 187% increase of women in football operation roles in the NFL. Since its inception in 2017, over 400 participants have gone through the Women’s Forum with over 250 opportunities emerging for women in all levels of football.

“The first Women’s Forum I attended, all of the women there, we had other jobs outside of football wanting to get into football,” King said. “I think this year almost everyone there was already working in football, which is incredible. So, I think we’re definitely heading in the right direction. It’s a lot of bright stars coming through the ranks on our way up.”

King said she hasn’t experienced challenges being one of the few female coaches in a male-dominated industry.

“I’ve been fortunate to work with some great staffs,” she said. “Coach Flus, we have a great staff here. It’s all about development, which is great. I love it. He’s big on leadership. So, the challenges haven’t been the same as possibly people would think. Like it hasn’t been a lot of: ‘Oh, it’s like a woman here.’ I haven’t really experienced any of that. It’s all about building those relationships and trust in the building with the players and the staff that you’re working with.

“I do think it’s cool now to see so many women doing great things in the league, not just coaching, all aspects, the business side, the team level, people doing great things all over the place. Obviously, the coaches are the ones that people see, but there’s a lot of great people doing cool things that you don’t see as well.”

Rivera, a two-time AP NFL Coach of the Year, has been a leader in diversity and inclusion throughout his career. He said he can envision the NFL having a female head coach in the future.

“I think it’s going to have to start with coordinator first, and as long as we keep putting women in position to have an opportunity to succeed or fail, until we give them that opportunity, we’ll never really know,” Rivera said. “But I do think we’ve created enough opportunities that eventually the right one is going to get the opportunity.”

Maybe that’ll be King.

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Effects of leadership style on coach-athlete relationship, athletes’ motivations, and athlete satisfaction

1 FIBA China, Beijing, China

Seungmo Kim

2 Department of Sport and Physical Education, Faculty of Social Sciences, Hong Kong Baptist University, Kowloon, Hong Kong SAR, China

3 Department of Kinesiology, Recreation, and Sport Studies, College of Education, Health, and Human Sciences, The University of Tennessee, Knoxville, Knoxville, TN, United States

4 College of Physical Education, Hebei Normal University, Shijiazhuang, Hebei, China

Associated Data

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Introduction

The current study investigated the impacts of autocratic and democratic leadership styles on the coach-athlete relationship, athletes’ motivations, and athlete satisfaction.

Survey data were collected from 298 student-athletes (male = 157; 52.7%, female = 141; 47.3%) from 20 different Chinese collegiate sports. The Structural Equation Model was used to test the hypothesized model.

The results indicated democratic leadership had a direct positive influence on the coach-athlete relationship, while autocratic leadership had no direct effect. Both leadership styles did not influence autonomous motivation. The coach-athlete relationship, meanwhile, had a full mediation effect between democratic leadership and athletes’ motivation and satisfaction. In addition, autonomous motivation had a partial mediation effect between the coach-athlete relationship and athlete satisfaction.

Ultimately, the findings of the current study underscore the need for coaches and administrators to understand the impact of different leadership styles and highlight the importance of democratic leadership in improving athletes’ psychological outcomes.

A variety of different leadership styles are widely used among leaders in business, sports, and politics ( Farh and Cheng, 2000 ). Leading a team of athletes entails unique complexities compared to other business and organizational contexts, and there has been an increased interest in research about the effectiveness of coaching leadership styles in recent years ( Castillo and Espinosa, 2014 ; Jowett, 2017 ). A successful sports team will need coaches to properly guide their athletes to maintain healthy relationships with fellow team members while also fostering a high level of performance ( Mallett, 2005 ). Numerous studies have found that coaches’ leadership behaviors can play a crucial role in athletes’ psychological development and satisfaction ( Weiss and Friedrichs, 1986 ), training efficiency and game outcomes ( Becker and Wrisberg, 2008 ), and team cohesion ( Jowett and Chaundy, 2004 ; Vincer and Loughead, 2010 ).

The Multidimensional Model of Leadership in Sport (MML) developed by Chelladurai and Saleh (1980) based on the unique demands of sport is a pioneering model of sports leadership. The model has been frequently discussed and explored by sport scholars ( Hampson and Jowett, 2014 ; Chia et al., 2015 ). The MML delineates three states of leadership behavior—required, actual, and preferred. Behaviors related to adhering to government regulations, conference compliance, and institutional structure are defined as required . Behavior based on the coach’s ability and philosophy, as well as other situational factors, reflect the actual leadership state. Last, preferred leadership behavior refers to meeting the goals and needs of athletes ( Dupuis et al., 2006 ). The degree of consistency of the three leadership behavior states is an indicator of team performance and athlete satisfaction, which is associated with coaching effectiveness ( Chia et al., 2015 ). According to the MML, to become an effective coach, one most adapt and adopt appropriate coaching styles in different situations. For instance, a coach who leads high school level teams may need to employ different coaching styles depending on the team’s goals (e.g., league championship or individual skill development), the familiarity and maturity of the players, and the schedule of a weekly training regimen.

Although the autocratic leadership style may achieve successful results in some cases, athletes’ ability level (e.g., mental development) and team conditions must be considered when coaches employ different leadership styles. Because autocratic leadership reduces the opportunity for athletes’ internal decision-making, it should be matched with a level of development from athletes to follow coaches’ commands and instructions. In other words, to achieve the functional purpose of different leadership styles (i.e., autocratic or democratic) an appropriate level of ability by athletes to follow leadership is crucial to avoid conflicts ( Yang and Jowett, 2010 ). For instance, if a coach seeks to exert assertive control over athletes, those who prefer a higher level of autonomy may feel and tense or strained relationship with the coach. On the other hand, imbalance may also occur when the coach tends to be democratic, yet some athletes prefer clear guidance from coaches and want instructions that create a highly structured setting with specific plans and goals. Such disparity can lead to dissatisfaction and poor performance among athletes on a team. As a result, different leadership styles may have an important impact in sports teams, and coaches must think carefully in selecting and implementing leadership behaviors.

A “centralized sports governance” system has been used in China to organize elite sports, including recruiting youth athletes and hosting major events ( Yang et al., 2015 ). Unlike the primarily free-market system of the US, the Chinese government maintains control of funding, training, and operations for the sport performance sector. Under this government-led system, leadership studies in China have largely focused on the relationships between leadership behavior and team performance and cohesion ( Cui, 2010 ; Li et al., 2017 ) rather than athletes’ psychological well-being. China’s centralized sports institutions and cultural background may encourage the adoption of autocratic leadership styles, as performance is valued above and beyond other interests, such as social development and health. For example, paternalistic leadership based on the cultural roots of confucianism tends to emphasize strict discipline and authority. The three components of paternalistic leadership are authoritarianism, benevolence, and moral leadership ( Farh and Cheng, 2000 ). In fact, some studies have focused on paternalistic leadership to analyze the leadership style of Chinese coaches given the cultural background factors ( Li and Li, 2021 ; Li et al., 2021 ).

Overall, there is a lack of coaching leadership research that explores the unique sport culture in China, which has a strong focus on performance and elite sport. Many young Chinese athletes may spend more time with their coaches than with their parents, making it particularly important to understand the impact of coaches, not only with respect to advancing athletes’ sports skills, but also influencing their education and holistic development ( Zhu et al., 2017 ). Hence, the current study was designed to investigate the influence of leadership behaviors, including both autocratic and democratic leadership, to enrich the theoretical framework and increase the range of understanding about coaching in Chinese universities. The current study can help practitioners better understand effective teaching methods in practice by examining the impact of coaches’ leadership. Most significantly, the study may assist coaches in choosing appropriate leadership styles to interact with their athletes throughout training and competition to improve their performance and holistic development. Therefore, the main purpose of the current study was to investigate the impacts of autocratic and democratic leadership styles on the coach-athlete relationship, athletes’ motivations, and athlete satisfaction in Chinese collegiate athletics.

Theoretical foundations

As shown in Figure 1 , the conceptual model of the current study includes four constructs: (a) leadership style (i.e., autocratic leadership and democratic leadership), (b) coach-athlete relationship (CAR), (c) autonomous motivation, and (d) athlete satisfaction.

Proposed research model.

Leadership in sport

The success of a sports team can depend on a coach’s leadership style, and research has identified several theories to determine the most effective coaching approaches ( Jowett, 2017 ). In particular, the comparative effectiveness of democratic and autocratic coaching styles has been a frequent topic of investigation ( Case, 1984 ). Many theories of situational leadership were developed in the 1960s and 1970s, which include contingency theory ( Fiedler, 1967 ), path-goal theory ( House, 1971 ), and the situational leadership model ( Hersey and Blanchard, 1982 ). A key principle of situational leadership in sport is the leader’s ability to adapt to the needs and situations of athletes ( Kim et al., 2021 ). Since athletes may experience ups and downs in their skill development and psychological growth, coaches need to think carefully about the overall dynamic relationship and find the most effective patterns with the athletes they mentor. Given that situational leadership does not involve only a single skill or approach, it can be difficult for coaches to master a diverse set of coaching behaviors for a variety of situations.

One of the most influential leadership frameworks in sport has been Chelladurai and Saleh’s (1980) MML, which was established based on the interactive behaviors of sports group members. To measure leadership styles within the MML, Chelladurai and Sarah developed the Leadership Scale for Sports (LSS). The LSS organized athletes’ perceived leadership style into five major categories: training and instruction, democratic behavior, autocratic behavior, social support, and positive feedback. Training and instruction referred to the essential roles of a coach in improving the performance level of athletes. Democratic behavior, meanwhile, reflected the extent to which the coach allows participation by athletes in the decision-making process. The third factor, autocratic behavior, indicated that “a coach keeps apart from the athletes and stresses his or her authority in dealing with them” ( Chelladurai and Saleh, 1980 , p. 41). Social support is evident when the coach is involved in satisfying the interpersonal needs of athletes. Last, positive feedback refers to the coach expressing appreciation and complimenting the athletes for their performance and contributions.

As oppositional decision-making styles, autocratic and democratic leadership approaches each have distinct advantages and limitations ( Chelladurai and Saleh, 1980 ). Autocratic behavior, one of the most demanding leadership styles, emphasizes the coach’s authority over athletes in sports environments. With autocratic leadership, the dominance of the coach’s decision-making and personal power may limit athletes’ freedom of action but also facilitates quick problem-solving, which is often necessary for competitive sport environments. Autocratic leadership behaviors may increase athletes’ focus, which could increase practice effectiveness in some situations ( Yang and Jowett, 2010 ). For example, Castillo and Espinosa (2014) found that individuals who were in the process of learning to master a dance skill were significantly impacted by autocratic teaching techniques. They discovered that, despite the limitations of the authoritarian approach, it set clear goals for achievement to lessen students’ loss of concentration during the learning process, which in turn led to a more efficient improvement in performance. However, due to the lack of encouragement associated with autocratic coaching behavior, autocratic leaders often impede athlete’s motivation from the psychological level, which may negatively impact the coach-athlete relationship ( Mallett, 2005 ). Autocratic coaching style may also have a negative impact on athletes’ intrinsic motivation and feelings of relatedness ( Hollembeak and Amorose, 2005 ). A higher level of autocratic behavior by coaches is associated with athletes who report higher levels of anxiety and burnout with lower levels of enjoyment and perceived competence ( Price and Weiss, 2000 ). Overall, while autocratic leadership styles may have positive effects with respect to skill acquisition and performance in some situations, they also tend to negatively impact athletes in important ways.

In a contrast with an autocratic approach, Gastil (1994) made an important distinction between leadership and authority. In particular, he defined democratic leadership as performing three functions: distributing responsibility, empowering, and aiding deliberation ( Gastil, 1994 ). In sports, implementing democratic leadership behaviors may entail the head coach sharing authority with a team captain or position group leader, allowing them to take some responsibility for the team’s progress and skill development. Under democratic leadership styles, athletes have more power to decide how they train and compete ( Cruz and Kim, 2017 ). Higher levels of democratic leadership have been linked to more positive and less negative psychological outcomes for athletes ( Price and Weiss, 2000 ). However, highly democratic approaches may also engender conflicts with athletes as well as disrespect and disobedience ( Foels et al., 2000 ). A coach’s choices about the extent to which to employ democratic or autocratic leadership behavior may be influenced by factors such as gender ( Wałach-Biśta, 2019 ), competition level, and sports type (e.g., team sports or individual sports). For instance, Terry and Howe (1984) discovered that coaching effectiveness was highly correlated with task dependence in the sport, and team sports that require a high level of teamwork and interaction (e.g., basketball) favored more authoritarian leadership styles.

Literature regarding situational leadership theory generally supports the idea that the coach should be flexible and adopt different leadership styles dependent upon the context. The adaptability of leaders is a critical principle in situational leadership in sports and has been identified as a key component of coaching mastery ( Kim et al., 2021 ). Coaches in a setting such as collegiate sport must work with players who have varied levels of understanding due to their distinct educational backgrounds, athletic ambitions, and training experiences. Such factors make it challenging for coaches to maintain positive coach-athlete relationships and athlete satisfaction. Given the complexity involved in situational leadership, further research is required to understand the relationship between various leadership styles and important outcomes in sport, such as the coach-athlete relationship and athlete satisfaction.

Outcomes of leadership style

Coach-athlete relationship.

Athletes have interpersonal relationships with a variety of people in sport, including teammates, parents, coaches, and staff members. Given the fact that young athletes may spend more time with coaches than their parents in some elite sport contexts, the relationship quality with the coach is highly important, directly affecting the athletes’ skill development and competitive performance ( Jowett, 2017 ). Jowett and Poczwardowski (2007) defined the coach-athlete relationship as “a situation in which a coach’s and an athlete’s cognitions, feelings, and behaviors are mutually and causally interconnected” (p. 4).

Examining behavioral, affective, and cognitive elements involved in leadership are important to understanding social behavior, such as the coach-athlete relationship ( Jowett and Ntoumanis, 2004 ). Investigating the dynamic nature of CAR is essential for strengthening coaching effectiveness and fostering optimal physical and psychological performance of athletes ( Jowett, 2017 ). Research regarding the influence of relationship quality indicates that CAR can impact important outcomes, such as moral disengagement ( Chen et al., 2016 ) and social environment ( Jowett, 2007 ). In fact, athletes’ relationships with coaches may have a significant impact on psychological outcomes and long-term stability, effecting not only their sport performance, but also their holistic development ( Kim et al., 2020 ).

Given the important influence of a coach, it is essential to understand how different leadership styles may affect the relationships between coaches and athletes. In the context of sports in China, Zhu et al. (2017) found that the authoritarian behavior of coaches was the factor that athletes perceived as most detrimental to team effectiveness. Gao et al. (2021) similarly discovered that autocratic behavior appeared to have substantial detrimental impacts on athlete engagement and CAR. Relatively few studies, however, have investigated the connection between different leadership styles and the coach-athlete relationship ( Jowett and Chaundy, 2004 ; Hampson and Jowett, 2014 ), particularly in the context of East Asia.

Motivation has been extensively studied as a crucial factor influencing athletic success ( Vallerand, 2007 ). Understanding and promoting athlete motivation has been demonstrated to have a significant influence on athletes’ performance ( Mallett, 2005 ), cognition ( Ryan and Deci, 2000 ), and behaviors ( Li et al., 2021 ). Due to the importance of motivation in sports performance, much research has investigated the ways in which coaches’ behaviors, such as decision-making style, reward distribution, and feedback methods, are essential factors affecting athletes’ motivation ( Mageau and Vallerand, 2003 ).

The two most well-known theories of motivation in sports psychology are self-determination theory (SDT; Deci and Ryan, 1985 ; Ryan and Deci, 2000 ) and achievement goal theory (AGT; Nicholls, 1989 ). SDT focuses on intrinsically motivated psychological behavior based on three basic needs—competence, relatedness, and autonomy ( Deci and Ryan, 1985 ). On the other hand, AGT places more emphasis on goal orientations, particularly task and ego orientation ( Nicholls, 1989 ). The principles of intrinsic and extrinsic motivation are important areas of focus within SDT. The model expands on the three fundamental requirements (i.e., competence, relatedness, and autonomy) to form a continuous and unified structure that can locate and illuminate various factors impacting athletes’ motivation ( Spray et al., 2006 ).

Deci and Ryan (1985) developed a motivation continuum that segmented motivation into six components. From highest to lowest, the levels of self-determination were labeled intrinsic, integrated, identified, introjected, external, and amotivation. The term intrinsic motivation (IM) referred to instances in which an activity is done for inherent reasons. Extrinsic motivation (EM), meanwhile, included a group of motivations with varying degrees of autonomy—integrated, identified, introjected, and external. Last, amotivation (AM) indicated a lack of autonomy. In sports, an athlete’s actions may reveal their motivation. For instance, athletes who feel satisfaction in the sport or find their value by participating in sport are more likely to be motivated by internal factors. In contrast, engaging in sport to escape punishment and guilt or seek praise and approval from others tends to be influenced by extrinsic motivations, which reflect non-autonomous intentions ( Amorose and Anderson-Butcher, 2007 ).

Existing research evaluating IM and EM to determine the quality of motivational orientations has identified the differentiation between autonomous and controlled motivation as being important ( Ratelle et al., 2007 ). Whereas autonomous behavior is typically self-initiated, controlled motivation occurs when an action results from external influence. To calculate controlled motivation, researchers have often used the mean score of external and introjected motivation ( Sheldon and Elliot, 1998 ). Conversely, investigators have identified autonomous motivation as a mix of intrinsic and identified motivation ( Fenton et al., 2014 ). Koestner et al. (2008) found that increasing autonomous motivation was more successful than decreasing controlled motivation when examining the relative role of the two in the achievement of personal goals.

Coaches’ decision-making styles, autocratic or democratic, can have substantial implications with respect to athletes’ motivations. Creating an autonomy-supportive motivational climate has been found to serve an essential role in supporting athletes to develop strong commitment and interest in sports ( Mallett, 2005 ). Hollembeak and Amorose (2005) established that autocratic and democratic styles were the two behaviors that had a substantial indirect effect on autonomy in all five categories of leadership styles under the LSS ( Chelladurai and Saleh, 1980 ). Democratic leader behavior has received positive feedback from athletes at all levels, including elementary ( Fenton et al., 2014 ), secondary ( Spray et al., 2006 ), high school ( Amorose and Anderson-Butcher, 2007 ), club teams ( Vincer and Loughead, 2010 ), and college. Autonomy supportive coaching behaviors, such as encouragement, may have significant benefits in boosting intrinsic motivation and engagement of athletes ( Hollembeak and Amorose, 2005 ). In contrast, autocratic behavior has been found to hinder athletes’ initiative ( Hollembeak and Amorose, 2005 ).

The motivational model of the coach-athlete relationship, presented by Mageau and Vallerand (2003) , illustrated the positive effect of coaches’ autonomy supportive behavior on CAR and motivation of athletes. Wu et al. (2014) found that authoritarian behavior was negatively related to autonomy, relatedness, and intrinsic motivation, whereas democratic behavior had the opposite impact on these outcomes in Chinese collegiate sports. Consequently, to improve coaching effectiveness in China, it may be useful to advance the autonomous motivation of athletes as a key to developing effective coaching behavior and healthy coach-athlete relationships.

Athlete satisfaction

Athletes’ satisfaction has been observed as a key reflection of many coaching characteristics, including coaches’ personality ( Yang et al., 2015 ), physical behaviors ( Davis et al., 2019 ), and leadership style ( Kim et al., 2020 ). Therefore, considering athletes’ satisfaction is an important practice for coaches to achieve successful performance and training efficiency by valuing the effect of different leadership styles. Riemer and Toon (2001) revealed that an athlete’s ability level affected their preference for types of leadership behavior and level of satisfaction. Weiss and Friedrichs (1986) , meanwhile, found that the democratic leadership style positively impacted satisfaction among college athletes. Many studies on the coach-athlete relationship have found associations among CAR, motivation, and satisfaction ( Lorimer and Jowett, 2009 ). Multiple studies ( Koestner et al., 2008 ; Grant and Berg, 2011 ) have shown that autonomous motivation, controlled motivation, and satisfaction interacted with each other. Jowett (2017) , meanwhile, asserted that CAR was central to coaching effectiveness, and its quality greatly impacted athletes’ levels of satisfaction, pleasure, and wellbeing. Davis et al. (2019) similarly found relationships between the quality of CAR and athletes’ experiences of sport satisfaction.

In the past decade, research on coaches’ leadership styles in China has concentrated on the connection between team cohesion and team effectiveness for college athletes ( Cui, 2010 ; Chen et al., 2016 ; Li et al., 2017 ; Zhu et al., 2017 ; Gao et al., 2021 ). Thus, the current study attempted to fill a gap in Chinese coaches’ research on the impact of autocratic and democratic leadership styles among Chinese coaches on athletes’ satisfaction levels and enhancing coaching efficiency through CAR and motivation. Specifically, it was hypothesized that CAR and motivation would mediate the association between coaching style and satisfaction. Overall, the following hypotheses were proposed based on the aforementioned research background:

Hypothesis 1: Leadership style (H1a: autocratic leadership, H1b: democratic leadership) will influence coach-athlete relationship.

Hypothesis 2: Leadership style (H2a: autocratic leadership, H2b: democratic leadership) will influence autonomous motivation.

Hypothesis 3: Coach-athlete relationship will mediate the relationship between leadership style (H3a: autocratic leadership, H3b: democratic leadership) and autonomous motivation.

Hypothesis 4: Coach-athlete relationship will mediate the relationship between leadership style (H4a: autocratic leadership, H4b: democratic leadership) and athlete satisfaction.

Hypothesis 5: Autonomous motivation will mediate the relationship between leadership style (H5a: autocratic leadership, H5b: democratic leadership) and athlete satisfaction.

Hypothesis 6: Autonomous motivation will mediate the relationship between coach-athlete relationship and athlete satisfaction.

Materials and methods

Participation and survey procedure.

The population of the current study was composed of current college athletes in China. An online survey with a convenience sampling method was used to collect data. The researchers sent an initial WeChat message with a link to the survey to athletes from a variety of sports at the collegiate level in China to recruit participants. The data collection period was from April 22 to May 1, 2022. In addition to inviting them to complete the questionnaire, recipients were also asked to forward the link to other student-athletes in their networks. Two follow-up e-mail reminders were sent to encourage participation. A total of 157 male (52.7%) and 141 female (47.3%) athletes from 20 different sports, including volleyball ( n = 109; 36.6%), basketball ( n = 54; 18.1%), track and field ( n = 39; 13.1%), football ( n = 33; 11.1%), table tennis ( n = 13; 4.4%), and other sports completed the questionnaire. The majority of participants were first-class athletes ( n = 138; 46.3%) and second-class athletes ( n = 138; 46.3%) according to the Chinese Athletes Technical Classification Standard ( General Administration of Sport of China, 2010 ). Participants were primarily between 16 and 24 years old ( n = 276; 92.6%), and the majority ( n = 207; 69.5%) had trained for between 5 and 10 years in their sport. More demographic information is shown in Table 1 .

Demographic profile of participants ( n = 298).

Instruments

Forty-one items from previously validated scales were used to measure autocratic coaching style (five items), democratic coaching style (five items), coach-athlete relationship (eleven items), motivation (nine items), athlete satisfaction (five items) and demographic information. The 10 items measuring autocratic and democratic coaching behaviors were adopted from the LSS ( Chelladurai and Saleh, 1980 ). Each item began with the statement “my coach…” and included items such as “refuses to compromise on a point” and “speaks in a manner not to be questioned” for autocratic behavior and “let his/her athletes share in decision making” and “encourages athletes to make suggestions on conducting practices” for democratic behavior. These items were scored using 7-point Likert-type scales ranging from 1 (strongly disagree) to 7 (strongly agree). To measure an athlete’s perception regarding the relationship with his/her coach, Coach-Athlete Relationship Questionnaire (CART-Q; Jowett and Ntoumanis, 2004 ) was used. The scale included 11 items, such as “I appreciate the sacrifices my coach has experienced in order to improve performance,” “I am committed to my coach,” and “I am ready to do my best.” The items were also scored using a 7-point Likert-type scale ranging from 1 (strongly disagree) to 7 (strongly agree). Nine items from the Sport Motivation Scale (SMS-II), developed by Pelletier et al. (2013) were utilized to examine autonomous motivation. The items included “Because it gives me pleasure to learn more about my sport” and “Because participating in sport is an integral part of my life.” Athlete satisfaction was measured using job satisfaction scales developed by Judge et al. (1998) , modified to be used in the context of sports. The items included “I feel fairly satisfied with my team” and “Each day at practice seems like it will never end (reversed coded).”

In developing the questionnaire, the survey was initially written in English because the scales of the four concepts that the current research adopted were originally developed in English. The English version was then translated into Chinese, as all the participants in the current study were native Chinese speakers. The translation was conducted by two individuals with a graduate degree in business and communication data science who were familiar with organizational behavior literature and fluent in English and Mandarin. The Chinese version was then back-translated into English by another individual, who was a Ph.D. candidate in sports psychology with similar language qualifications to the previous translators. Finally, 10 athletes in China were recruited for a pilot study to assess the survey’s ease of use and clarity.

Data analyses

The current study sequentially conducted a confirmatory factor analysis (CFA) to evaluate the measurement model and structural equation model (SEM) analysis to examine the research model based on Anderson and Gerbing’s (1988) two-step approach using AMOS 27. For both the CFA and SEM, the present study used indexes [i.e., chi-square, the Steiger-Lind Root Mean Square Error of Approximation (RMSEA), Standardized Root Mean Squared Residual (SRMR), Comparative Fit Index (CFI), and Tucker-Lewis fit index (TLI)] to assess an overall fit of structure since the indexes are often recommended to evaluate structural equation models ( Browne and Cudeck, 1992 ; Hu and Bentler, 1999 ; Kline, 2015 ). In addition, Cronbach’s α coefficients were calculated to verify the internal consistency of each measurement scale’s components. Descriptive statistics were compiled to provide relevant demographic information about the sample as well as the means and standard deviations of each construct. Next, SEM was used to test the proposed model. The bootstrapping method was used to test the mediating effects of the proposed model, which may provide additional implications for leadership style, CAR, autonomous motivation, and athlete satisfaction. The research model also was assessed by the same indexes previously used for the CFA.

Measurement model

The results of an initial CFA showed unacceptable model fit [Chi-square statistic = 2,089.045, df = 550, CFI = 0.863, TLI = 0.852, RMSEA = 0.097, and SRMR = 0.068] since TLI and CFI should be equal to or greater than 0.9 ( Hair et al., 2010 ) and RMSEA and SRMR should be equal to or less than 0.08 ( Tabachnick et al., 2007 ) to be acceptable. Further, Parsimonious Fit Indices (PNFI and PCFI) were 0.761 and 0.798, respectively. Thus, the investigators removed four items (two for autocratic coaching style and two for athletic satisfaction) due to low factor loadings (below 0.4). The removed items were “My coach works relatively independent of the athletes” and “My coach does not explain his/her action” for autocratic leadership, as well as “Each day at practice seems like it will never end (Reversed Code)” and “I consider my team and my sport rather unpleasant (Reversed Code)” for athlete satisfaction. Since negatively phrased items may be associated with respondent errors ( Sonderen et al., 2013 ), reversed codes may have contributed to the low factor loadings in. After dropping those items, the results of the CFA indicated an acceptable fit for the measurement model [Chi-square statistic = 1,199.304, df = 414, CFI = 0.927, TLI = 0.918, RMSEA = 0.080, and SRMR = 0.060] with Parsimonious Fit Indices (PNFI and PCFI) of 0.796 and 0.826, respectively. Convergent validity of the measures was established because construct reliability (CR) and average variance extracted (AVE) were greater than 0.7 and 0.5, respectively ( Ahmad et al., 2016 ). Discriminant validity was also established since correlation coefficients among latent variables were smaller than the square roots of AVEs. The results of convergent and discriminant validity along with the results of the correlation analysis are shown in Tables 2 , ​ ,3. 3 . In terms of internal consistency, Cronbach’s α for autocratic leadership, democratic leadership, coaching-athlete relationship, motivation, and athlete satisfaction were 0.715, 0.818, 0.864, 0.882, and 0.904, respectively ( Lance et al., 2006 ).

Measurement model.

Discriminant validity.

Values on the diagonal denote square root of the AVEs. CAR, coach-athlete relationship; AM, autonomous motivation; AS, athlete satisfaction.

*** p < 0.001; ** p < 0.01; * p < 0.05.

Descriptive statistics

Table 4 shows the means and standard deviations of each construct in terms of the gender of the sport and the sample as a whole. These data revealed that male and female athletes showed similar outcomes. For example, all the means for each construct were above the mid-point of the scale (4.00), with the exception of autocratic leadership. The means from both men and women were below the midpoint of the scale for autocratic leadership. Regarding the outcomes of coach leadership style, the means for the outcome variables ranged from 5.94 (athlete satisfaction) to 6.65 (coach-athlete relationship). The levels of all outcomes approached or exceeded 6 out of 7, which indicates athletes perceive a good relationship with their coaches and are satisfied with their current athletic careers overall.

Descriptive statistics.

Structural model

The structural model consisting of autocratic leadership, democratic leadership, CAR, and athlete satisfaction was tested using the maximum likelihood estimation method. The model fits of the revised structural model were acceptable [Chi-square statistic = 1,242.421, df = 446, CFI = 0.927, TLI = 0.919, RMSEA = 0.079, and SRMR = 0.059] with Parsimonious Fit Indices (PNFI and PCFI) of 0.801 and 0.834, respectively. Figure 2 shows the results of the revised structural model. The results indicated that autocratic leadership had no direct effect on the coach-athlete relationship, which rejected hypothesis 1a, whereas democratic leadership had a direct positive influence on coach-athlete relationship (β = 0.651, SE = 0.073, p < 0.001), which supported Hypothesis 1b. However, both leadership styles did not influence autonomous motivation, which rejected Hypothesis 2a and 2b.

Proposed structured research model with path coefficients.

The mediating effects to examine the internal mechanism among the variables in the proposed model were tested using the bootstrapping method; 5,000 bootstrap samples were generated using random sampling with replacement from actual data. Although the proposed model consisted of seven indirect paths to test the hypotheses, we tested only three direct paths because several direct paths to the proposed mediators were not supported. With respect to the mediation effects of ç between democratic leadership and outcomes (autonomous motivation and athlete satisfaction), the mediation effects were significant (Democratic leadership → CAR → autonomous motivation (β = 0.505, SE = 0.064, p < 0.001), Democratic leadership → CAR → athlete satisfaction (β = 0.558, SE = 0.054, p < 0.001). Therefore, the coach-athlete relationship had a full mediation effect between only democratic leadership and the outcome variables, which supported Hypothesis 3b and 4b but rejected Hypotheses 3a, 4a, 5a, and 5b. In addition, the mediation effects of autonomous motivation between CAR and athlete satisfaction showed a partial mediation effect with the indirect effect (CAR → autonomous motivation → athlete satisfaction: β = 0.327, SE = 0.075, p < 0.001) and the direct effect (CAR → athlete satisfaction: β = 0.490, SE = 0.097, p < 0.001). Therefore, Hypothesis 6 was rejected. Table 5 provides detailed results with respect to the direct and indirect effects.

Direct and indirect effects using bootstrapping method.

CAR, coach-athlete relationship; AM, autonomous motivation; AS, athlete satisfaction.

This study aimed to discover the impacts of autocratic and democratic leadership style along with democratic leadership on coach-athlete relationships, autonomous motivation, and athletes’ satisfaction in Chinese collegiate athletics. A total of eleven hypotheses were developed based on the MML ( Chelladurai and Saleh, 1980 ) and associated research on the relationships between coaches and athletes. Among the proposed hypotheses, three hypotheses were supported. The findings of this study help provide a more comprehensive understanding of the impact of coaching style on the coach-athlete relationship and athletes’ motivation and satisfaction in Chinese collegiate athletics.

The descriptive statistics of this study illustrated that collegiate athletes in China reported average mean scores of 3.82 for autocratic leadership, 5.57 for democratic leadership, 6.65 for coach-athlete relationships, 6.03 for autonomous motivation, and 5.94 for athlete satisfaction (on a 7-point scale). The average mean scores of male and female athletes were comparable, implying that gender has less influence on the perception of coaching leadership style in this context. A trend had been apparent in prior research in that athletes in Western countries perceived low levels of autocratic leadership among their coaches ( Jowett and Chaundy, 2004 ; Hampson and Jowett, 2014 ), whereas studies in East Asian countries, such as China ( Cui, 2010 ) and Korea ( Cruz and Kim, 2017 ), found higher levels of authoritarian leadership among coaches. The results of the current study, however, revealed that athletes’ perceived levels of autocratic leadership among coaches to be below the midpoint of the scale. Due to selections for Chinese national teams being typically made from among athletes in the professional team system, coaches in collegiate sports may be under less pressure to perform and utilize less authoritarianism compared to those at the professional and elite levels. On the other hand, the average score for democratic leadership was 5.57, higher than that found in other studies in East Asia, suggesting that democratic leadership may be becoming more regularly applied in the Chinese university context. Given the high scores of CAR (6.65), autonomous motivation (6.03), and satisfaction (5.94), the findings highlight important relationships between different coaching styles and these three variables.

Academic implications

There are three key findings to highlight from the SEM analysis in this study. First, with respect to hypothesis 1a and 2a, the effects of autocratic leadership on CAR and autonomous motivation were found to be insignificant in this study. These results are notable because prior research has frequently found autonomous motivation to have a direct or indirect relationship with autocratic coaching styles. Hollembeak and Amorose (2005) , for example, found that authoritarian and democratic styles had significant indirect effects on autonomy, while Wu et al. (2014) study on the motivation of Chinese college athletes determined that authoritarian behavior had a significant negative relationship with autonomy and intrinsic motivation. However, the results of the current study showed that the autocratic leadership style did not have a significant relationship with autonomous motivation. Grant and Berg (2011) suggested that since the two motivations, autonomous and controlled, often coexist, examining the simultaneous action of both motivations is worthwhile. The fact that autocratic leadership only had a minimal effect on autonomous motivation might be explained by the coexistence and ambivalence of different types of motivation. For example, the nature of the coach-athlete relationship varies depending on different cultural norms in different countries ( Yang et al., 2015 ), and respect for those in positions of authority (i.e., coaches) is considered a traditional norm in Chinese culture. However, athletes’ respect for a coach may develop differently and be affected by varying factors in different (e.g., Western) cultural contexts. Culture norms for respecting authority figures may have influenced the sensitivity of Chinese college athletes toward autocratic behaviors, which in turn led to a non-significant relationship between CAR and autonomous motivation ( Lee, 2017 ). Furthermore, the findings revealed no link between autocratic leadership and CAR, either positive or negative, similar to the results of Li and Li (2021) in a study among Chinese youth soccer players.

Secondly, with respect to hypothesis 1b, the democratic coaching approach directly and positively impacted the quality of relationships between coaches and athletes. Moreover, with respect to hypothesis 2b, democratic leadership had an indirect influence on autonomous motivation and athlete satisfaction through CAR. These results are largely in line with previous research findings on such relationships. Through more democratic leadership behaviors, coaches appear to build trust and a sense of respect with their athletes ( Gao et al., 2021 ). Mageau and Vallerand (2003) , p. 886 identified specific behaviors that contributed to the autonomy-supportive climate, including “providing choice to their athletes within specific limits and rules” and “providing the opportunity for athletes to take initiative and act independently.” In addition, Mageau and Valler and highlighted how the autonomy-supportive conduct of coaches improved the quality of CAR and boosted players’ motivation. The results of the current study confirm the mediating role of CAR in the association between democratic leadership style and autonomous motivation and satisfaction. In alignment with Jowett (2017) , CAR appears to be at the core of coach effectiveness. The outcomes of the current study (i.e., CAR, autonomous motivation, and athletes’ satisfaction) have been frequently recognized as important influences for enhancing performance in sports psychology ( Vallerand and Losier, 1999 ; Jowett, 2017 ). Therefore, the current study provides further support to the findings of prior studies regarding the effects of autocratic and democratic coaching styles ( Jowett and Chaundy, 2004 ) by confirming that democratic leadership behaviors had a more positive influence on athletes’ psychological outcomes in Chinese collegiate athletics than autocratic leadership behaviors.

Finally, with respect to hypothesis 6, the current study discovered a partial mediating effect of autonomous motivation between CAR and athlete satisfaction, confirming the association between these three variables observed in previous studies ( Koestner et al., 2008 ; Grant and Berg, 2011 ). The results demonstrated that a number of criteria, including the quality of CAR and the athlete’s internal motivation, can be used to explain athlete satisfaction. Previous results had demonstrated that coaches employing democratic coaching behavior and encouraging athletes to make decisions for themselves improve team cohesion and overall satisfaction ( Weiss and Friedrichs, 1986 ). Athletes who feel trusted and have a strong emotional attachment with their coaches tend to show increased positive motivation and encouragement of feedback from their teammates ( Watson and Kleinert, 2019 ). Ultimately, fostering autonomous motivation among athletes appears to be an important area on which coaches should focus their attention.

Practical implications

The current study’s findings supported the hypotheses that different leadership coaching approaches, particularly democratic leadership, can affect athletes’ satisfaction levels, interpersonal relationships, and motivation. It is crucial for coaches and college sports team administrators to thoroughly understand the ways in which different coaching styles may increase the quality of connections with players and affect their behaviors. The findings of the current study demonstrated that by maintaining a good relationship with the coach and having a high level of autonomous motivation, athletes’ higher levels of satisfaction could be vital to their performance ( Weiss and Friedrichs, 1986 ). The situational leadership model emphasizes the importance of coaches’ flexibility in applying different leadership techniques in accordance with athletes’ needs and goals ( Hersey and Blanchard, 1982 ). Since the autocratic leadership style did not significantly impact athletes’ relationships and autonomous motivation in the current study, Chinese athletes may have a high tolerance for autocratic behaviors due to cultural influences. While Chinese college coaches have the discretion to use an authoritarian approach to achieve efficient results in the preseason or during short-term intensified training, relying solely on autocratic actions would be unlikely to improve the quality of relationships or increase autonomous motivation, despite the fact that China has a “centralized sports governance” system ( Yang et al., 2015 ), and paternalistic leadership is a common leadership style in Chinese culture ( Wu et al., 2014 ). Conversely, coaches should involve the athletes in preparing training plans and developing strategies in competition to avoid monotony and repetition in offseason training. Democratic behaviors that coaches adopt, when appropriate, can make athletes feel respected and trustworthy and satisfy their psychological needs. In responding to the coaches’ effort and care, college athletes would be likely to show more initiative by cultivating healthy relationships with their coaches in response to democratic approaches.

The results of the current study confirmed that both the quality of the coach-athlete relationship and autonomous motivation had a significant positive impact on athlete satisfaction, which may deliver an important message to a sports team. Respect for and obedience toward coaches and other authority figures has been a traditional component of Chinese culture. Athletes, as subordinates, have tended to obey coaches’ demands and refrain from expressing their true feelings to a coach. The conventional view of coaches as authoritarian team leaders has also prevented them from developing the practice of encouraging communication ( Lee, 2017 ). Therefore, it is critical for coaches and team managers to maintain effective two-way communication. The connection and confidence between coaches and athletes should be boosted and supervised to maintain a long-term healthy relationship ( Gao et al., 2021 ). Coaches, as leaders, should regularly and effectively seek to understand athletes’ emotional and psychological changes to evaluate their status and interpersonal relationships. At the same time, the managers of sports teams should foster an environment in which athletes have the opportunity to express their feelings and thoughts to the coach freely. Additionally, maintaining open lines of communication makes it easier for the coach to select the best coaching approach during practice and competition based on the status of the athletes and the team.

Limitations and future research directions

Although this study contributes to the literature regarding the impacts of various leadership styles on Chinese college athletes, there are some important limitations. First, the current study only examined the influences of coach leadership styles based on the perspective of athletes. Price and Weiss (2000) explain that different leadership styles may also contribute to coaches’ burnout, which affects the coach-athlete relationship as well as the team’s long-term performance. In addition, coaches’ leadership style preferences are not immutable ( Hersey and Blanchard, 1982 ), and the decision-making process for coaches differs from athletes’ considerations and motivation. At the same time, coaches’ perspectives can help further explain the interactive relationship when analyzing the connection between athletes and coaches. Additionally, the data for this study were collected through online surveys. Compared with face-to-face methods, the number of unqualified questionnaires through the online collection is greater ( Heerwegh, 2009 ), further demonstrating the value of multiple methodological approaches when investigating this topic.

Although the current study adds to the base of information on Chinese coaching styles by analyzing the relationship between motivation and satisfaction among CAR, further investigation is required to more comprehensively identify additional factors that impact training effectiveness. The current study emphasized the impact of leadership style, particularly democratic leadership, on athlete outcomes in Chinese collegiate athletics. Of course, the authoritarian leadership style may also be useful in some contexts, such as with novice athletes who wish to improve their skills quickly ( Castillo and Espinosa, 2014 ). Hypothetically, if Chinese youth athletes generally accept an authoritarian leadership style, they may prefer a less stressful or inexperienced democratic leadership style when competing in college. Building from the current study, a more comprehensive sample of athletes, including high school and youth athletes, can provide insight into satisfaction with different coaching leadership styles at different stages of development. Such insight may assist coaches in choosing appropriate leadership styles in different situations at various stages of athletes’ development in order to enhance athletes’ satisfaction and performance.

Finally, the current study is one of relatively few investigations into leadership style and its effect on athletes’ psychological outcomes in China. Such research in the context of China is particularly important, given that many young Chinese athletes may spend more time with their coaches than with their parents due to the high-stakes nature of sport in the country, affecting their sports skills, education, and holistic development ( Zhu et al., 2017 ). While the bulk of research on coaching leadership has been conducted in Western nations, differing cultural norms may impact the nature of the coach-athlete relationship in different national contexts ( Yang et al., 2015 ). In turn, additional cross-cultural research that compares leadership style, CAR, and related outcomes in East Asia and other regions will provide a valuable contribution to the field.

Data availability statement

Ethics statement.

The studies involving human participants were reviewed and approved by Research Ethics Committee from Hong Kong Baptist University. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.

Author contributions

HJ designed the computational framework and got involved in every part of the research. SK helped to develop the framework, analyzed the data, and wrote the results. AL helped to write the “Introduction” and “Discussion” of this research. YJ and JZ were in charge of data collection and also helped to write the literature reviews. All authors contributed to the article and approved the submitted version.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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