Abstract
High-performance sport coaches are leaders in their field; therefore, they sometimes operate under ‘regular’ workplace leadership role requirements. However, they are also subject to highly uncertain and pressured environments. Thus, most coaching/leadership positions in high-performance sport may be both ‘normal’ and ‘unique’ in leadership role requirement. Consequently, understanding what high-performance sport leaders ‘look like’, behaviorally, would be valuable. This study aimed to 1) describe personality traits of coaches in high-performance sport, and 2) describe differences between high-performance sport coaches and other leaders. Hogan’s personality profile data was collected from fulltime coaches working in high-performance sport. Experienced and developing high-performance sport coaches were compared, and high-performance sport coaches were compared to other sector leaders. No differences exist between coaching groups for any personality traits. However, while high-performance sport coaches shared similar ‘light’, or ‘socially desirable’, traits to leaders in ‘regular’ workplaces they differed for some ‘dark’/maladaptive traits. That is, as is the case for leaders in sectors including business, finance and healthcare high-performance coaches may be experienced as being balanced, stable, calm under pressure, approachable, friendly, accessible, planful, responsible, and mindful of details. However, unlike leaders in ‘regular’ workplace environments, high-performance coaches may also be experienced as moody, hard to please, creative but unusual, risk-taking, and limit-testing; which is more similar to scientists and artists. In conclusion, coach personality traits were both similar and unique to leaders from ‘regular’ workplaces. Thus, leadership is context specific both within sectors and between sectors.
Keywords
Introduction
Coaches are leaders in the context of high-performance sport. In fact, in many cases they operate under ‘regular’ workplace leadership role requirements (e.g. articulating a vision, planning, organizing, motivating, and problem solving etc.)1–3 with the aim generally being the achievement of goal-directed outcomes through the building and maintenance of effective teams.4–6 However, leadership role holders in the high-performance sport domain may also face highly uncertain, pressured, and publicly scrutinized environments characterized by intense competition and ambiguous socio-political landscapes.7–9 Therefore, although they may be understood from a broad-based perspective of leadership and may contain degrees of commonality with equivalent role holders in ‘non-sport’ environments, 10 it should be acknowledged that most coaching positions in high-performance sport are distinctly unique. Having greater understanding of what an effective leader in high-performance sport ‘looks like’, specifically coaches, therefore demands further research. Some work has argued that successful coaches are conscientious, extraverted and low on neuroticism 11 ; and while this information is useful it is important to note that that work was limited to a homogenous sample of only 14 male coaches, and therefore potentially not truly representative of the entire high-performance coach workforce. To the authors’ knowledge no other substantial piece of work has been conducted in the area, further highlighting the requirement for additional investigation into the ‘make-up’ and behaviours of high-performance sport coaches. Especially also because of the often narrow window of time in which coaches get to demonstrate their ability to perform in this space (e.g. once every four years at an Olympic games, a season for a football coach etc.), the often high turnover of coaching roles in sport,12–14 and the fact the financial cost of recruiting to senior roles within an organization can be 90% to 200% of an individual wage. 15 In a broader sense, such research might also serve to highlight that leadership, and the ‘skills’ required to be effective in these roles, is context specific.
Leadership in sport has traditionally been thought of as either a set of traits one was ‘born’ with, or was not. 16 However, in domains other than sport trait characteristics have been shown to be minimally predictive for leadership effectiveness, and the expression of leadership behaviors is context specific.17–19 In personality psychology several integrative theories have emerged that can be applied to leadership which situate both the inherited personality alongside the environmental presses people experience. (e.g. socio analytic theory).20,21 Therefore, leadership in sport may benefit from exploring similar integrative views at redressing “… the behavior-cognition balance.” 7
Traits are distinguishing characteristics unique to each person which often predicates patterns of thinking, feeling, and behaving. They are not always distinct from behaviors per se, although distinctions can exist.20,22 For example, research has shown that business executives can appear altruistic, where in actual fact they are ambitious – they disguise ‘getting ahead’ with ‘getting along’. In this example being altruistic is not a trait (ambition is the trait), rather it is a trait-like behavior. 23 This suggests leadership behaviors may have the characteristics of, and can be classified under, broad-based personality trait terminology, but are not necessarily trait-based in foundation.24–26 Thus, trait language is pragmatically functional as an organizing schema for leadership behavior.25,27 Specifically, ‘trait schema’ have practical implications in terms of how we choose to assess, measure, describe, predict, and develop consequential aspects of personality on leadership expression (and effectiveness) – regardless of domain. In the context of high-performance sport, for example, it may be possible to use common trait schema to describe leadership behavior of elite coaches however it remains to be seen whether they share a similar set of trait schema to business executives, engineers, scientists etc. or if leadership behavior in coaches is more effectively described using a combination of traits from several different domains.
By exploring leadership from a socio analytic perspective, recent research in sport has begun examining the functional attributes and the application of various effective leader trait-like behaviors. 7 The strategic use of socially desirable traits (that is, light traits) 28 and less socially desirable traits (that is, dark traits), 29 or light and dark trait-like behaviors, in the pursuit of performance objectives in high-performance sport has been of particular interest (e.g., Olympic or top-tier professional code). 30 This work presents additional perspective to more dominant positions currently prevalent in the field. For instance, a current ‘popular’ form of leadership is transformational leadership; it includes idealized influence, inspirational motivation, intellectual stimulation, and individual consideration. 31 Transformational types of leadership, often used in the business sectors (e.g. charismatic, shared, or strategic leadership), 30 are characterized by emphasis on overtly light trait-like behaviors and actions and have generally been positioned as the aspirational standard for high function and effectiveness.31,32 However, given the potential nuance to prevailing leadership theory in high-performance sport, 33 there is value in extending explorations beyond pursuing excellence in light trait-like behavior in this context. Specifically, understanding better the presence, use, and effectiveness of balancing light and dark trait-like behaviors of successful and experienced coaches in high-performance sport contexts could enable implementation of development initiatives for less experienced coaches to enhance relevant trait-like behaviors. Additionally, this could prove useful in coach recruitment as well as highlight the point that effective leadership is absolutely context dependent; both in terms of the sector and in terms of acute environments within sectors.
Leadership effectiveness is likely to be a function of both traits and trait-like behaviors which are relevant to, or driven by, the context in which the leaders must operate. Therefore, identifying trait schema common amongst experienced and successful coaches in the high-performance sports sector could be useful for reasons including development and implementation of initiatives to enhance effective leadership in coaches, and to assist with coach talent identification and recruitment. Consequently, the aims of this study were to 1) describe common personality traits amongst coaches in the high-performance sport context - both experienced and successful coaches, and coaches displaying potential for success; and, 2) to a lesser extent, we also wanted describe differences in common trait schema for high-performance sport coaches and leaders in other professions.
Methods
Overview
This was an observational study of coaches in the high-performance sport system in Australia. Personality profile data was collected and analyzed/described from Olympic, Paralympic, professional-code, and national sporting organization (NSO) coaches via a range of activities undertaken by the Australian Institute of Sport (e.g. in support of recruitment processes, development initiatives etc.). The potential varied utility of such approaches is suggested through similar work in other domains. 34
Participants
Participants were employed throughout the Australian high performance sport system as contractors, part and full-time employees of NSOs, clubs of professional code sports, and/or the network of state/regional sporting institutes that exists to support most Olympic, Paralympic, and Commonwealth Games sports in the country (n = 73; 52 males [71.23%] and 21 females [28.77%]). While data was collected across a number of varied roles important to the high-performance sport system (e.g. coaches, CEOs, performance directors, etc.), the analyses presented here focusses on two distinct coaching categories; ‘experienced coaches’ and ‘developing coaches’. The chosen categories were adopted because they most clearly aligned with the typical, common leadership allocation and effectiveness measures (e.g., competition performance and ranking) indicated in high-performance sport contexts and those measures often have consequential impacts on leaders occupying coaching roles in the high-performance sport system in Australia.
Experienced coaches
The experienced coaching category included team and individual sport coaches who had been considered responsible for performance outcomes at significant international standard competition (e.g., Olympic, World Championship, or Commonwealth Games) (n = 33; 45.21%).
Developing coaches
The developing coaching category included team and individual sport coaches identified by their NSO as having potential to achieve ‘experienced coach’ status but not yet done so; that is, they were ‘talented’ developing coaches (n = 40; 54.79%).
Procedures
Approval was obtained from the AIS Human Research Ethics Committee to seek consent from participants for retrospective analysis of part of their personality profile data based on the Hogan Personality Inventory (HPI) and the Hogan Development Survey (HDS). 29 Invitations were sent to 177 sport leaders; five coaches (2.82%) declined participation, 13 (7.34%) were no longer engaged in the Australian sport system, while another 66 coaches (37%) did not respond. Thus, we were left with 93 coaches (52.54%) providing signed, informed consent for retrospective analysis. Twenty of the 93 that agreed to retrospective access and analysis (or 21.50% of those who agreed to participate) held roles outside of the two categories of interest described here and were therefore their data was excluded from the reporting.
Individual data profiles were accessed by two of the authors in order to ascertain and cross-reference connections with athlete or team performance measures. Such access was necessary to allocate participants into the categories distinguishing leadership role holders in the Australian sport system (e.g. developing and experienced). Aside from gender, demographic data was not included in the profiles and has therefore not been reported.
Note, profile assessments with coaches occurred between the years 2013 through 2018. Voluntary collection and associated activities (e.g. debriefing of results for participants) were conducted by trained, certified, commercial practitioners and were subject to strict confidentiality and privacy protocols.
Personality profile measurement instruments
The Hogan Personality Suite (HPS) was used to establish personality profile of participants. This is a widely used tool in organizational contexts across a broad range of industry sectors (e.g. law enforcement, health care, military, business),34–36 however applications in the sports sector have been limited to date. The Hogan Personality Inventory (HPI) is part of the HPS and is a 206-item measure of 44 underlying facets consolidated into seven broad-based personality domain categories. These categories are often characterized as ‘light’ traits. 34 The broad-based personality domain categories of the HPI include ‘adjustment’ (reflects the degree to which someone appears calm and self-accepting), ‘ambition’ (reflects the degree to which someone appears leader-like, competitive, and socially self-confident), ‘sociability’ (reflects the degree to which a person seems to need or enjoy interactions with others), ‘interpersonal sensitivity’ (perceptive, tactful, and socially-sensitive), ‘prudence’ (concerns conscientiousness, conforming, and dependable), ‘inquisitive’ (reflects the degree to which someone is perceived as bright, creative, and interested in intellectual matters), and ‘learning approach’ (reflects interest in education and the degree to which someone pursues development opportunities). 37
In addition to the HPI, the HPS includes the Hogan Development Survey (HDS) which was also used in this study. The HDS measures 11 maladaptive behavioral dimensions based on models of dark traits (also termed “derailers”). 29 The survey captures the extent of respondents’ agreement or disagreement with 154-items that measure the sub-clinical, dysfunctional dispositions on which working populations can be evaluated and that can affect leadership styles, response tendencies under pressure, and team effectiveness. The characteristics the HDS measures can be described as extensions of each end of the continuum of the five factor model personality dimensions (e.g., Conscientiousness in extension can be experienced as either perfectionism on one end of the continuum or as risk taking on the other). 37 These maladaptive traits include ‘excitable’ (concerns tendencies to unregulated emotional responses), ‘skeptical’ (concerns tendencies to mistrust and retaliation if perceived as slighted), ‘cautious’ (conservative, anxious about mistakes, and reluctant to take initiative), ‘reserved’ (concerns a dislike of working in teams and indifference to the moods and feelings of others), ‘leisurely’ (typically adhering to own timetables and performance standards), ‘bold’ (concerns tendencies to ignoring shortcomings and overestimating abilities), ‘mischievous’ (impulsive and non-conforming), ‘colorful’ (a desire to be noticed and the center of attention), ‘imaginative’ (concerns a tendency toward unusual, different, or odd thinking), ‘diligent’ (orderly and perfectionistic), and ‘dutiful’ (concerns a tendency toward being eager to please and gain approval).
The scale for the HPI and HDS ranges from 0–100. Scores of 30–70 for both instruments are generally regarded as representative of a normal adult working population range. 37 The HPI is reported to have good construct validity as indicated by strong correlations between this tool and several criterion methods which measure cognitive ability, motives and interests, normal personality, and career derailers. 38 It has test-retest reliability coefficients that range between 0.69 and 0.87 37 Similarly, HDS is reported to have established construct validity as indicated by strong and significant correlations between this tool and criterion methods which measure cognitive ability, personality measures and values/needs/motives/interest inventories. 39 The HDS has test-retest reliability coefficients that range between 0.64 and 0.75. 37 Factorial validity of the HPI and HDS tools specific to sport is unknown because no other studies have yet utilized it, however it is established in other sectors such as business, finance executives etc.37,38
Statistical analysis
All data satisfied the assumptions for parametric statistical analysis, therefore a series of two-way ANOVA’s with interactions were performed to establish if there were any significant differences between coaching groups or between genders for each of the HPI and HDS dimensions (α = 0.05). Descriptive data for average scores on both the HPI and HDS for each of the two coach categories was also explored relative to population norms. Frequency histograms of scores on the light traits (e.g. HPI) and dark traits (e.g. HDS) were also plotted separately for the two categories of coaches (e.g. experienced and developing coaches) using bins of 15 from the test scale. Skewness was calculated (0 = none, 1 = very skewed), with all light and dark scores included. In the scales used, practical use regards scores between 30 and 70 as normal strength and does not seek to further break this down.37,39 All statistical analyses were performed using Statistical Package for the Social Sciences software version 19.0 (IBM, New York, NY).
Results
Group comparisons
No differences were seen between males and females for any of the dimensions on the HPI or HDS (p > 0.06). Additionally, no differences were observed between coaching groups for any of the dimensions (p > 0.13). There was, however, a significant interaction observed for gender*coaching group on the adjustment scale (F(1,88) = 5.97, p = 0.02) with developing male coaches typically scoring higher on this scale than developing female coaches, and experienced male coaches typically scoring lower than experienced female coaches.
Developing coaches’ comparison to population norms
Light traits
All of the developing coaches were within the typical described population range for light traits (Figure 1). However, the ‘ambition’ dimension was slightly higher than their ‘adjustment’, ‘interpersonal sensitivity’, ‘prudence’, ‘inquisitive’, and ‘learning approach’ dimensions, and nearing being greater than the norm (i.e. > 70). Figure 2 shows no skewness in the results.

Developing coaches (i.e. coaches identified by their national sporting organization as having potential to be successful coaches) dark and light characteristics summary scores (Mean + SEM). Orange bars = Hogan’s development survey (HDS)/dark traits/maladaptive behavioral dimensions. Blue bars = Hogan’s personality inventory (HPI)/light traits/bight side or adaptive personality dimensions. Typical population range for both light and dark traits is 30–70.

Developing coaches light traits and dark traits frequency distribution. Bin size = 15. Each bar represents the number of scores from participants in each bin. For example, for the Hogan’s Personality Inventory (HPI), or the scale which measures light traits, there are 206 questions and approximately 40–45 of all responses scored between 0 and 15. No clear skewness for light traits can be seen, however there is a clear skewness to the right for dark traits, or scores toward the higher end on the scale.
Dark traits
Four of the maladaptive behavioral dimensions, or dark traits, were greater than the typical population range; they were ‘imaginative’, ‘mischievous’, ‘reserved’ and ‘excitable’ (Figure 1). Further, the ‘excitable’ dimension for this group was greater than their ‘skeptical’, ‘cautious’, ‘leisurely’, ‘bold’, ‘colorful’, ‘diligent’, ‘dutiful’, and ‘reserved’ dimensions. Their ‘imaginative’ dimension was greater their ‘cautious’, ‘leisurely’, ‘bold’, ‘colorful’, and ‘dutiful’ dimensions. Finally, the ‘reserved’ dimension equaled the ‘mischievous’ dimensions for this group, and both appeared greater than their ‘bold’, ‘colorful’, and ‘dutiful’ dimensions. There was marked skewness in the data toward the right; that is a skewness toward scoring higher on these scales (Figure 2).
Experienced coaches comparison to population norms
Light traits
As with the developing coaches, all of the experienced coaches sat within the typical population range on the HPI scores (Figure 3). Their ‘ambition’ dimension appeared higher than their ‘adjustment’, ‘prudence’, and ‘learning approach’ dimensions and was also trending toward being greater than the norm. Further, and also similarly to the developing coaches, the frequency histogram (Figure 4) showed no skewness for the experienced coach group.

Experienced coaches (i.e. coaches responsible for the performance of athletes at major international standard competitions) dark and light characteristics summary scores (Mean + SEM). Orange bars = Hogan’s development survey (HDS)/dark traits/maladaptive behavioral dimensions. Blue bars = Hogan’s personality inventory (HPI)/light traits/bight side or adaptive personality dimensions. Typical population range for both light and dark traits is 30–70.

Experienced coaches light traits and dark traits frequency distribution. Bin size = 15. Each bar represents the number of scores from participants in each bin. For example, for the Hogan’s Personality Inventory (HPI), or the scale which measures light traits, there are 206 questions and approximately 30–40 of all responses scored between 2 and 17. No clear skewness for light traits can be seen, however there is a clear skewness to the right for dark traits, or scores toward the higher end on the scale.
Dark traits
For experienced coaches, three of the maladaptive behavioral dimensions, or dark traits, were greater than the typical population range; they were ‘imaginative’, ‘mischievous’, and ‘excitable’ (Figure 3). Note, these three traits were also higher than the typical population range for developing coaches (Figures 1 and 3). Further, in the experienced coaching group the ‘excitable’ dimension was greater than their ‘skeptical’, ‘cautious’, ‘reserved’, ‘leisurely’, ‘bold’, ‘mischievous’, ‘colorful’, ‘imaginative’, ‘diligent’, and ‘dutiful’ dimensions. The ‘imaginative’ dimension for this group was greater than the ‘leisurely’, ‘bold’, ‘colorful’, ‘dutiful’, and ‘diligent’ dimensions. However, this difference appeared slightly lower than the developing coaching group. For the experienced group, ‘mischievous’ aggregated the same as the developing group, being greater than their ‘bold’, ‘colorful’, and ‘dutiful’ dimensions. Finally, and similarly to the dark traits for developing coaches, there was marked skewness in the data toward the right; that is, a skewness toward scoring higher on these scales (Figure 4).
Discussion
The aim of this study was to describe common leadership/personality traits of the high-performance sports coaching workforce in Australia. We compared experienced and successful coaches to emerging or developing coaches who showed potential to be successful, and vice versa; and compare those traits of sports coaches to other professions. Our results showed regardless of whether coaches were developing or experienced coaches, they may typically be experienced as balanced, stable, and calm under pressure, approachable, friendly, accessible, planful, responsible, and mindful of details amongst a range of similar characteristics. This is indicated by the fact that many of the personality traits of the coaches fell within the ‘norms’ for most ‘light’ traits (Figures 1 and 3); and the distribution of ‘scores’ appeared consistent across personality dimensions as evidenced by no skewness for light traits for either groups (Figures 2 and 4). These results also suggest both developing and experienced coaches share similar ‘light traits’ to the leaders in ‘regular’ workplaces including managers and technical experts from the business and finance sectors, healthcare etc. (while acknowledging nuances: adjustment, ambition, interpersonal sensitivity, and prudence are broadly predictive of leadership type role performance across contexts). 37 However, with respect to light traits it may be speculated that where coaches differed from leaders in some regular workplaces, and from each other, was that they were reasonably high on ‘ambition’ suggesting they will also often be described as hard-working, energetic, leader-like, driven, persistent, focused on results and success, and competitive. Given the significant gender*coach interaction on the ‘adjustment’ scale it could be speculated that in a group of less experienced coaches, males appear more ‘calm under pressure’ than female coaches, while at the experienced and successful level with triage of coaches those females in this group appear more ‘calm under pressure’ than male coaches. Alternatively, it is likely that this observation could simply be a bias of the samples.
Data from this study suggests that, although similar with respect to light-traits, high-performance sport coaches differ to leaders in ‘regular’ working populations (e.g. business executives and other technical experts) in terms of their ‘dark traits’, or how they perform on maladaptive behavior scales. Specifically, coaches typically scored higher on subscales which represent trait-behaviors considered less socially desirable, and which are typically expected from scientists and artists.37,40 (Figures 1 and 3). Therefore, our results suggest that when under pressure the coaches in both of our categories of high-performance sport leaders are susceptible to displaying behaviors that may be observed as being moody, hard to please, creative but unusual, risk-taking, and limit-testing as indicated by their highest HDS scores being in the ‘excitable’, ‘mischievous’ and ‘imaginative’ dimensions. Additionally, data from our developing coach group suggests that when under pressure there is some susceptibility for them to also be experienced as aloof, uncommunicative, and indifferent to the feelings of others; indicated by also having a typically high score in the HDS ‘reserved’ dimension. It may be theorized that while these traits are atypical in comparison to ‘regular’ workplace leaders they could be the norm, or essential, for success as a high-performance coach.
Findings from this study supports the notion that the working context of those in leading roles in the high-performance sport system in Australia may be both ‘normal’ and unique. Behavioral characteristics likely to support success in this context are therefore likely be reflective of the high-performance sports coaching commonality to ‘regular’ working environments, and its originality. However, a somewhat novel aspect to this study was the fact that both the experienced coaches and developing coaches shared many similarities in personality traits; meaning the developing coaches have potential (behaviorally) to become ‘‘experienced’ coaches - recognizing that an appropriate large mix of other relevant variables must also be present for this to occur successfully. Further, it is possible that coaches with high potential may demonstrate the capability and capacity to be successful early in their career; it may not be entirely learnt. Thus, by bringing coaches in the high-performance sport context into regular leadership personality realms developmental initiatives which originate from broad-based perspectives on leadership, coupled with associated measures common across other industries, may be applied in this context; facilitating passage from developing coach to experienced coach. It is worth noting, however, that given the developmentally responsive aspects to some of the dark/maladaptive traits which can be potentially dysfunctional characteristics (e.g., they can be regulated with the right support), 34 the behaviors represented in the ‘reserved’ dimension may be a useful focal point in assisting developing coaches to moderate impacts of these tendencies on those they lead and work with (both developing and experienced coaches were, on average, similar in scores on this domain, however developing coaches scored higher than population norms whereas podium coaches did not). Indeed, all of the potential maladaptive behaviors (when expressed situationally) captured through the Hogan’s inventories (when expressed situationally) are susceptible to interventions with regard to developing appropriate compensation and coping skills to effectively manage impact.34,39,41,42 The emphasis being on the functional modification of these types of behaviors, rather than attempts at elimination. Thus, support or developmental initiatives, for high-performance sport coaches should remain cognizant that a broad behavioral repertoire (e.g. a mix of light and dark) is possibly useful for the effectiveness of coaching leaders in their specific context.4,7,30 This is in contradiction with advocacy for over-emphasis on bright-type leadership approaches suggested elsewhere (e.g., transformational leadership), although consistent with comments made in the introduction of this paper. 31
This work has shown that the assessment of coaches in high-performance sport environment using regular, and valid, workplace measures and concepts at a normative level has a degree of utility not otherwise clearly evidenced in the field. It should be noted that the HPI was adopted because it contains a number of advantages over other measures. First, personality is conceptualized from an evolutionary perspective and is framed interpersonally. Such an approach is relevant to group functioning and a key characteristic in high-performance sport contexts, particularly from a workforce perspective (e.g., even athletes competing in individual-based sports at the elite level have teams of people working in functional roles that surround and support them). Second, traits are characterized as behaviors and behaviors are guided by intentions, purposes, and agendas, which are useful to understand in social (and occupational) contexts. Third, hundreds of validity studies suggest the HPI is useful in predicting success in numerous job domains. Finally, the HPI has been used extensively in the assessment and measurement of leadership specifically.34,43 Use of the HDS was also considered advantageous because it evaluates common behavioral expressions everyone has susceptibility to, particularly under pressure. Given the (relatively) unique component of pressure that operates in the high-performance sport context and the implications of leader derailment on team (and individual) performance, such factors were considered key components of coaching leadership assessment. 43
Finally, it is important that the results of this study are evaluated with knowledge of its limitations. First, the data provided is descriptive only and limited to a specific level of generality; we did not explore, expand, or report on the subscale nuances of the instruments used in the profiling of our coaches. These subscales are key components in any personality assessment approach. 37 Furthermore, we have not linked the dark traits observed on the Hogan’s inventories to other frameworks such as the ‘big five’ 44 or ‘dark triad’. 45 To do so would be purely academic and would not change the outcome of our results. The novelty of this work (i.e. that it describes traits unique to high-performance coaches with a relatively large and diverse sample) is its strength and therefore results should be considered valuable enough to provide some utility for development programs of for recruitment initiatives for coaches working in the high-performance sport system. It also highlights the importance of context specific leadership development initiatives, although they may lend from components of typical leadership realms. Secondly, the study was limited to the Australian high-performance sporting system context. While we have advocated value in broad-based perspectives to elements of leadership and personality, we also maintain agreement with requirements to contextualize appropriately before being overly general in conclusions or applicability from findings. Work in other high-performance sporting systems could appreciably add to a collective body of knowledge in this area. In a similar vein, matches with exact job family validities are not reported. The predictive power of well-constructed personality measures is substantially enhanced through the appropriate match of dimension and underlying construct relevant to job characteristics. 5 Notwithstanding evidence of synthetic validity findings in other fields, 37 specific job analysis investigations conducted in the high-performance sporting sphere is warranted. Finally, what also cannot be deduced from our work (but that may add further useful nuance) is the mix of socialization versus attraction in terms of personality orientations and role or industry characteristics. That is, this piece of work provides no insight as to whether successful trait-like behaviors are a function of the high-performance sports environment, or if people with those trait-like behaviors are attracted to coaching in the high performance sport system. Similar work has been conducted in other settings (albeit using different conceptually based measures), and further research in this context would be beneficial. 46
Conclusion
Using trait schema from personality psychology this study described the personality traits of coaches in the high-performance sport sector in Australian sport. We found that the personality types of coaches were both similar and unique in personality to leaders from ‘regular’ workplaces. For example, light traits, or socially desirable traits, were similar for coaches and leaders from other sectors; however coaches were also susceptible to dark traits, or less socially desirable trait behaviors, including being moody, hard to please, creative but unusual, risk taking and limit testing. Additionally, developing coaches were also susceptible to being experienced as aloof, uncommunicative and indifferent to the feelings of others. Thus, in addition to showing differences in personality traits between high-performance sport coaches and in comparison to similar role holders in different professions, this study supports the notion that the traits required for leadership effectiveness is context dependent; both between and within sectors.
Footnotes
Declaration of conflicting interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.
