The measurement, tracking and development practices of English professional football academies

ABSTRACT

Tracking and measuring elements of performance is a well-established feature of practice in football academies. Player characteristics are considered, tracked, and measured using a variety of methods, with curricula often devised based on perceived importance and data interpretation. Against this breadth, our aim was to investigate the policies and systems in place at category one and two English football academies. Specifically, our objectives were (a) to understand what factors academies believe are important in the development of their players, (b) explore what academies are tracking and how they measure performance, and (c) analyse the extent to which these factors are integrated into the player’s curricula. A total of 15 participants with over 10 years’ experience across 40 Talent Development (TD) environments were recruited to participate in semi-structured interviews. Using Reflexive Thematic Analysis (RTA), generated themes suggest that academies perceive a differential weighting between performance factors, with greatest importance placed on technical, tactical and psychological factors. A lack of clear measurement systematisation was often apparent. Finally, we identified methods of player curricula integration. We conclude by offering implications for academies to optimise integration of systems and processes that measure and track their players development.

KEYWORDS:

• Performance pathway
• talent development
• talent system
• talent development environment
• talent identification

Introduction

Research points to the complex and multifaceted nature of TD processes (Abbott & Collins, 2004) with clear consensus that the development of ultimate high performance cannot be reduced to single factors (Araujo & Davids, 2011; Till & Baker, 2020; Williams et al., 2020). In practice, TD systems (Taylor et al., 2021) are increasingly recognised as needing to emphasise a breadth of developmental factors to support the player facing increasing socio- cultural pressures (Champ et al., 2018). Whilst, also developing participants for their lives beyond sport ensuring wellbeing, particularly in professional football (Sweeney et al., 2021).

Following the publication of the Lewis Report (Lewis, 2007), the Premier League implemented the Elite Player Performance Plan (EPPP) with the aim of developing a world-leading developmental system (The Premier League, 2011, p. 10). Key features included a requirement for players to spend greater time playing and being coached, improved quality of coaching provision, and the implementation of a system of effective measurement and quality assurance (The Premier League, 2011, p. 12). An approach that seems to have yielded significant results for clubs and players (The Premier League, 2022). Across academies, an approach to player tracking and measurement was adopted using the English Football Assoications “Four Corner Model” (FCM) (English Football Association, 2020). The FCM uses a holistic framework of technical/tactical, physical, psychological, and social “corners”, for the purpose of assessing player progress (Kelly & Williams, 2020). The strength of the framework being a representation of multiple factors, rather than individual determinants (Ryom et al., 2020).

At each club, a battery of systematic tracking and testing procedures including physiological and anthropometric testing (Noon et al., 2020) and club-specific frameworks to measure technical and tactical skills was adopted. Coinciding with an increased multidisciplinary (MD) (Raya-Castellano & Fradua, 2015) focus, initial EPPP recommendations encompassed forms of longitudinal assessment across all factors. Though, in practice many initial procedures focussed upon single test “snapshot” physical profiling and performance characteristics, a trend mirrored in the literature (Reilly et al., 2000).

More recently, research has highlighted various factors that influence the complex and multidimensional development process (Sarmento et al., 2018). Yet, there is limited empirical data that considers the multifaceted nature of progression across performance factors. For example, Huijgen et al. (2014) found a breadth of technical, tactical and physiological factors to discriminate between selected or deselected players. Corresponding results have emerged when investigating the overall weighting of holistic factors in performance development (Zuber et al., 2016). Similarly, Kelly et al. (2020) examined the range of multidisciplinary factors based on the FCM (i.e., technical/tactical, physical, psychological, social) that contributed towards player performance ratings and obtaining a professional contract. Yet, to this point, data has only been captured across a limited span of time and stage. Thus, there is a need for research that considers a breadth of factors throughout the full academy pathway.

As understood in education, effective assessment can be used to promote learning and development (Boud, 2000). If we take player learning as the core unit of emphasis when assessing their progress, it may steer us towards considering how measurement and assessment can productively influence the player development curriculum. This begs the question; what should we measure? Furthermore, are academies tracking and assessing the most valid factors for development?

Key factors – what research tells us about different aspects of development

Physical elements

Anthropometric tests are used to calculate height, body mass (Noon et al., 2020), maturation (Morris et al., 2018) and physical well-being, with the intention of longitudinally identifying areas that may require further attention; for example, to prevent illness and injury or maintain and improve performance. Fitness assessments methodically test speed, agility, power and endurance in an attempt to provide benchmarks, comparisons and, ultimately, offer explanations as to why academy footballers are successful or not (Carling & Collins, 2014). Notably, this extensive research has generated contrasting views. A review by Meylan et al. (2010) questioned the validity of using isolated physical measures in distinguishing the career progression of elite youth players. Despite this, physical performance fitness assessments (Rampinini et al., 2007) are often used by academy systems in this fashion, perhaps a result of their construct validity, reliability and objectivity as an assessment tool (Hulse et al., 2013). Of course, measuring physical factors in isolation has value for the monitoring of health and fitness status, however, physical elements are only a constituent feature of boarder biopsychosocial interactions in TD (Ford et al., 2011; Müller et al., 2023) . It is likely that other factors, such as psychological factors (and their interactions) offer greater validity for tracking and assessment, albeit being harder to measure.

Technical and tactical elements

In this regard, technical and tactical factors seem to hold strong face validity, viewed as indispensable attributes for progression to the professional level (Mills et al., 2012; Ward & Williams, 2003). As highlighted by Mills et al. (2012), a broad range of game contextual technical characteristics, with and without ball performance actions (e.g., ball control, passing, dribbling, crossing, shooting, heading), are considered key indicators of long-term progression. Tactical skills “performing the right action at the right moment” (Kannekens et al., 2009) specifically, knowledge (Costa et al., 2009), vision (Jordet, 2005), perception (Aksum et al., 2021), reading the play (Helsen & Starkes, 2017), game understanding (Price et al., 2020) and decision-making (Larkin et al., 2016) are also viewed as fundamental tools for elite players (Ward & Williams, 2003). Indeed, integrating these elements with perceptual-cognitive skills that inform expert game contextual skilled decision-making is stressed by O’Connor and Larkin (2015) as a discriminatory factor in career success. This suggests that developing high-level tactical proficiency, obtaining divergent tactical thinking and game intelligence skills from an early age (Memmert, 2010) may contribute towards long-term performance success (Kelly et al., 2020). and tactical skills (Elferink-Gemser et al., 2005). As an example, contextual expertise (Serra-Olivares et al., 2016) is suggested to be fundamental for high-level performance (Kannekens et al., 2009), but unfortunately is underrepresented in the literature.

Psychological and social elements

A significant number of psychological constructs have been identified as contributing towards developmental outcomes and successful career progression of academy youth players (Kelly et al., 2020). Psycho-behavioural, characteristics, such as motivation (Maitland & Gervis, 2010), discipline, commitment, resilience and social support (Holt & Dunn, 2004), task orientation (Höner & Feichtinger, 2016), coping skills (Van Yperen, 2009) and coping strategies (Ivarsson et al., 2019) are considered important contributors.

Importantly, constructs such as the Psychological Characteristics of Developing Excellence (PCDEs) (MacNamara & Collins, 2013) include both the trait characteristics and the state-deployed skills that underpin various psychological outcomes. These outcomes for example, “grit” have been associated with a range of adaptive developmental outcomes Larkin et al. (2016). Other outcome models have also been developed, such as Lerner et al. (2000) “6C’s” of youth development: competence, character, connection, confidence, caring and ultimately, contributions and Harwood (2008) “5C’s” intervention framework, incorporating a focus on behaviour response associated with commitment, communication, concentration, control, confidence. Both sets of constructs share similarities with the psychosocial competencies viewed by (Holt & Dunn, 2004) as important for successful talent transition within youth football (Harwood et al., 2015).

Regardless of model, there is an agreed need for a breadth of psychological development to support player development (MacNamara et al., 2010a; MacNamara et al., 2010b). As the player progresses, they are faced with various challenges within the development pathway (MacNamara & Collins, 2013) that will test their psycho-behavioural skills (Holt & Dunn, 2004). Accordingly, PCDEs within a youth academy setting, can be deployed in various combinations to meet the needs of different challenges (MacNamara & Collins, 2013). Over the longer term, the development of psycho-behavioural skills appears to offer a level of predictive capability (Kelly et al., 2020) and, at the least, a valid means of understanding progression. Yet, research involving pre-elite level players remains limited (Figueiredo et al., 2009). The complexity of the psychological field highlights the challenges of identifying one single distinguishing variable, even though their collective worth is well established.

Social factors seem to reflect similar issues. Sociocultural factors (such as social and economic status, parents, siblings, peers, stakeholders) are considered to be highly impactful factors in Talent Development Environments (TDEs) (Henriksen & Stambulova, 2017; Martindale & Mortimer, 2011). Something reflected in debates surrounding identification, selection and development (Maguire & Pearton, 2000) with a strong influence on adaptive developmental behaviours (Gledhill et al., 2017). For example, the role played by the family, which Kay (2000) cites as potentially salient in providing a basis for wider sporting success and athletic development. Once again, however, are these factors sufficiently measured and applied in structures of academy systems?

Achieving an optimum Balance

For assessment to be truly impactful, academies need to identify which factors matter, in what ways and at which stages. There is also a need to evaluate which factors require minimum standards necessary for risk mitigation, such as injury prevention or being “good enough” at specific skills, against which ones are directly pertinent to the player’s ability to transition into and succeed at the highest level. Subsequently, then select appropriate measures to track multi-faceted performance and coherently (where elements of an athlete’s experience hold logical connection and are mutually reinforcing (Taylor et al., 2021)) decide how these are best used as part of the developmental process.

Why might this be useful? Developing curricula and shared mental models

The concept of curriculum encourages consideration of the broader experience of the athlete (Kelly, 2009). Thus, a truly developmental curriculum in the academy setting requires careful evidence-informed planning, in conjunction with significant individualisation in design. In short, coherence in implementation in addition to the “appropriateness” of the concepts employed.

Coherence of experience in TD has become an increasing topic of interest in both practice and research (Webb et al., 2016) and has led to multiple investigations across contexts that have considered the extent to which the different features of an athlete’s experience hold logical connection (e.g., Curran et al., 2021; Martindale et al., 2007; Sweeney et al., 2022). This coherence can be horizontal, across a level of performance, or vertical, over the longer term, building towards the players’ individual long-term developmental needs (Taylor & Collins, 2021). Additionally, one of the mechanisms by which coherence may be generated, is via the integration of people, systems and processes in TD systems (Taylor et al., 2021). A proposed mechanism to support this process is the evolution of Shared Mental Models (SMMs), described as “an organized understanding or mental representation of knowledge that is shared by team members” (Mohammed et al., 2000) both within and beyond the organisational setting (Taylor et al., 2022). In this sense, SMMs might desirably encompass three elements. Firstly, the target profile of what we are aiming for; secondly, how we best help a player get there (the curriculum) and thirdly, the respective roles and systems (integration). Thus, if SMMs are to be effectively leveraged as a source of shared understanding to enhance adaptive action, there is a need to understand where each player’s development status is, establishing role clarity within the players curricula.

As the sections above demonstrate, there is a plethora of research constructed to identify factors, systems and practice measures that can be used to inform player development within football academies. Yet to this point, no literature has considered how different approaches to profiling (tracking and assessment) can inform the content (syllabus) and the influence on player experience (curricula). There is, therefore, a need to understand the holistic picture of player development in the academy setting with the aim of achieving an informed basis for future practice.

Consequently, the aim of this study was to investigate the TD policies and systems in place at high level English football academies. The specific research objectives were (a) to understand what factors academies believe are important in the development of their players, (b) explore what academies are tracking and how they measure performance, and (c) analyse the extent to which these factors are integrated with the player’s curricula.

Methodology

Research philosophy

The present study used a pragmatic research philosophy, one grounded in the belief that the value of new knowledge is determined by the difference it makes to actual practice (Giacobbi et al., 2005). The primary objective being to generate knowledge that is practically meaningful(Denzin & Lincoln, 2008) for the individuals and groups that it studies, plus the practitioners who support them (Badley, 2003), addressing the need for academies to justify their practice against theoretically sound empirical evidence (Cruickshank & Collins, 2017). Pragmatism, requires researchers to identify processes and mechanisms that shape common experiences in specific settings at specific times (Giacobbi et al., 2005). Epistemologically, pragmatism is based on the idea that research can focus on “practical understandings” of concrete, real-world issues (Patton, 2002). Given the practical need for coaches to develop systems and processes of tracking and measuring performance and the social context of these processes, there is a need to better understand coaches and the unique experiences of coaches and practitioners within academy football. Aligned to this pragmatic focus and the need to understand the meaning making of practitioners, Reflexive Thematic Analysis (RTA) was used to explore coaches experiences (Braun & Clarke, 2022). The researchers’ backgrounds as experienced coaches, coach developers and researchers were considered a strength and a resource to inform Thematic Analysis (TA) (Braun & Clarke, 2021). RTA was used to analyse the data within a pragmatic paradigm.

Coherent with the pragmatic lens, rather than biases to mitigate against, the experiences and the positions of the research team were seen as an advantage when taking an active and interpretive lens during data analysis (Bourke, 2014). The first author holds a senior position within a high-level youth academy with over 17 years’ experience working in academy football. The second author has substantial experience working as a coach developer in the football academy setting. The third author is an active scientist – practitioner across TD and elite sport, including an 11-year period at a category 1 football academy.

Interview schedule

Prior to the conduct of interviews, a semi-structured interview guide was developed with targeted questioning and follow-up probes (available from the first author on request). The interview guide was designed via a combination of the existing TD literature and the professional experiences of the research team in academy football. This enabled a consistent line of questioning, aiding comparison, and cross referencing of subsequent answers; information that would provide context and comparison. Prior to participant recruitment, two pilot interviews were conducted with participants who met the participant criteria of the main study, average age (M = 43, SD = 1). As a result of the pilot testing, a number of questions were changed to ensure participant understanding. Specifically, three questions were altered. For example, the lead question: “now can you give me details about your player development systems at the academy?”, “what factors do you systematically look at year on year as a player progresses through the pathway? and “we have 5 areas/what factors do you assess players on? Clarity of meaning was provided of terms “systems”, “systematic” and “factors”. Interview durations ranged from 35 to 75 minutes (M = 58.24+SD = 15.33).

Participants

Following ethical clearance from the University of Edinburgh, a homogenous sample of 15 professionals were purposively sampled to participate in the interview process (Lavrakas, 2008). Participants were invited based on over 10 years’ experience in “high end” category 1 and 2 football academies and youth player development setting, a current position as a senior member of staff, experience of the full player development pathway and a track record of creation and development of academy policy. Participant career status is offered in Table 1 although, to ensure anonymity, no further participant demographics are made available.

Table 1. Participant demographics.

Participant Number	Career History Status	Years Experience
Participant 1	Academy Director	15
Participant 2	Academy Manager	13
Participant 3	Youth Coach Educator	21
Participant 4	Academy Manager	14
Participant 5	Head of Coaching	13
Participant 6	Head of Recruitment	11
Participant 7	Head of Coaching	12
Participant 8	Youth Coach Educator	22
Participant 9	Academy Manager	23
Participant 10	Head of Talent ID	23
Participant 11	Head of Coaching	24
Participant 12	Assistant Head of Coaching	11
Participant 13	National Lead Coach	18
Participant 14	Head of Coaching	12
Participant 15	Head of Player Development	13

As such, participants were able to provide a range of views on practice across category 1 and 2 football academies where all were working on a day-to-day basis. Potential participants fitting the inclusion criteria were contacted through the professional network of the research team and subsequently provided information about the purpose of the study. The first author then followed up initial communication with further contact to ensure that each participant was fully informed as to the aims and objectives of the study. Each participant was provided with ethical information and assured of anonymity, for this reason, no further demographic information is stated. All those who were contacted agreed to be interviewed and completed informed consent prior to interview.

Data analysis

All interviews were transcribed verbatim and analysed using a TA approach using NVivo (QSR International, Melbourne, Australia) software. TA comprises a six-step process, initially outlined by (Clarke & Braun, 2013). TA explicitly recognises that analysis can neither be purely inductive or deductive (Malterud, 2015). Analysis was deductively informed by existing theory, specifically by the theoretical stances outlined in the introduction and the applied experience of the research team. The first author took the lead the process of data collection, with both first and second authors developing the analysis. At the first stage, both the first and second authors read and re-read each transcript several times to familiarise themselves with the data. This immersion enabled both to begin identifying and noticing commonality of themes and patent of meaning. The second stage began with the first author generating initial codes across the dataset. The coding was deductively informed by existing theory, specifically by the theoretical stances outlined in the introduction and the applied experience of the research team, and inductively informed through participant data. Codes were both semantic (capturing surface meaning) and latent (capturing underpinning meaning) (Braun & Clarke, 2021). Once this had been completed for the full dataset, the second author acted as a critical friend to review initial code generation (McGannon et al., 2021). The second author deliberately adopting the stance of ensured multiple readings of the data with code generation being questioned and that the deductive stance was appropriate to the dataset (Braun & Clarke, 2022). The third stage generated initial themes, connected codes were clustered into candidate themes and a thematic map was created to explore patterns across the wider dataset. For example: (a) Measuring and tracking processes, (b) Deliberate effort to build SMMs. The fourth stage involved the whole research team reviewing generated themes to check coherence against (a) coded extracts and (b) the entire dataset. At this point, following reflexive engagement with the dataset, several themes were renamed, for example: (a) Top Down (the requirements of the game at the highest level), (b) Technical and Tactical, Physical, (c) Psychological. Prior to the write up, the fifth stage of analysis involved the first author generating a definition of each theme and naming themes based on the overall concept of the analysis (Braun & Clarke, 2021). The sixth stage concluded with a full report of the findings.

Trustworthiness

We undertook several procedures during collection and analysis to optimise the trustworthiness of the data collected. To better inform the conduct of each interview, the lead author developed knowledge of participant career history and context. In addition, a reflexive journal was kept by the first author for the purpose of reflecting on dynamics of and during data collection. An audit trail was used to document methods, interpret data and elicit the valued data in line with coding themes (Nowell et al., 2017), thus, ensuring reflexivity and facilitating critical thinking (Lietz et al., 2006). The flexible approach challenged theme generation and meaning making. Throughout the analytic process, the second author acted as a critical friend, challenging the generation of themes, subthemes and assigned coding. Constant comparison analysis (Beynon, 2008) between participants (Corbin & Strauss, 2008) was undertaken with the aim of informing consistent methods. The voice of the participant is retained by the use of thick descriptive quotations throughout the results section and direct quotations are used as extensively as possible (Patton, 2002).

Finally, member reflections were solicited via email at fourth stage of data analysis and prior to the final naming of themes aiming to generate additional data and insight related to participants interpretation of generated themes (Smith & McGannon, 2018). Participants were sent draft thematic tables with 9 out of 15 participants choosing to engage in follow-up interviews, the process being enhanced by “lessons learned” identified by Cavallerio et al. (2020). Firstly, by remaining respectful and empathic to participants and preparing for a lack of agreement; secondly, outlining to participants the ways in which the themes had been generated and thirdly ensuring that the first author was available to address questions and concerns about the analysis in an individual setting. These insights were carried forward to further enhance trustworthiness and balance of ongoing analysis. For example, participants perceived results to be reflective of and influenced by the emphasis on participants really understanding risk factors of family background, thus later interviews asked participants to reflect on this theme to see if coherence was evident amongst participants and clubs.

Results

Generated themes and data are presented below using a table format containing direct quotations. Each objective is considered as a separate item. Data analysis generated themes across all three objectives.

Objective 1: factors important for player development

Several factors appeared to be perceived as important for player development in the long term. All four factors from the FA Model (technical and tactical, physical, and psychological) were represented. Notably, the emphasis seemed differentially weighted (see Table 2).

Table 2. What matters? Factors seen as important for player development.

Theme	Raw data exemplars
Top Down (the requirements of the game at the highest level)	I think that that core technical base is important, not just for our first team, probably most of someone else’s first team (P5) The style type of play first and foremost, the identity of all academy teams and club on and off the pitch and then filter that into the player profile and what we look for (P2)
Bottom up – against player needs	The kid had done really well and then suddenly then hit a ceiling. They collapse and fall apart because they’ve not been used to that challenge of having to fight for every inch that they can gain and don’t have the [mental] ability to cope with it (P3)
Physical Factors	I don’t know if we’ve come away from that [technical/tactical] a bit in recent years looking more for physical qualities (P14) In my opinion we should wipe out the players on the physical part of any decision because we have no idea what that’s going to look like in the future (P2)
Technical and Tactical Factors	We can’t get away from the importance of a real solid foundation, a technical foundation competency, your receiving skills, your ability to pass the ball, your ability to travel with the ball (P8) Midfielders need the ability to scan with game understanding and awareness, with the technical ability to execute (P14)
Psychological Factors	Underpinning everything is the mentality. Without that you won’t give yourself I think the best chance to maximise your potential (P14) Now you’re at the business end of the academy at 15/16 and as you go into the 18/23 that mindset as an elite player is so vital is the most important thing (P11)

Our results suggest that academies consider a wide range of factors (Sarmento et al., 2018), yet with differential weighting and emphasis. Some participants perceived physical factors as being important throughout, whilst others see physical aptitude as being overweighted, especially prior to biological maturation. Irrespective of the perceived balance, however, there was an expressed need for “all round” technical and tactical skills competency to achieve sustained success at the highest level. In short, equipping the player to be sufficiently adaptable to manage forthcoming challenges: “players that I’ve witnessed go through often have one outstanding attribute, but they’ve probably not fulfilled their full potential because of their all-round game” (P6).

The weighting of importance placed upon technical and tactical factors seems to be a consistent theme throughout an academy: “technical aspects just stay with them throughout their journey” (P2). This focus appeared especially strong at the FP, with participants reflecting on the importance of developing a foundation of technical competency. Importantly, the adaptability of, and interaction between technical and tactical traits were evident, and were seen as potentially critical factors supporting the players ability to successfully progress through the academy pathway. In parallel, psychological skills were concurrently promoted as important components underpinning the player’s ability to progress: “you’ve got to have a really strong mindset” (P2) and were perceived as significant in contributing to the acceleration of other important, perhaps discriminatory skills, such as specific tactical efficacy. This assertion was based on possession of a breadth and depth of tactical skills: “the rare occasion where a player has those intuitive and scanning skills and anticipation, they have become the superstars” (P3).

As expressed above, the need for psychological skills was seen as important, but often only to strengthen the player’s ability to manage the challenges of more senior environments: “the ones that I think probably transitioned easiest are the ones who got a strong mindset, sort of dealt with setbacks challenge, you know, and can deal with those sorts of challenging moments” (P5). In short, there was evidence of a top-down approach, with reference made to a changing of player needs over time but with some factors only emerging later.

In summary, there appears general agreement between participants on the weighting of developing broad technical competency from the early stages of the academy pathway, underpinning the player’s ability to discriminate themselves amongst their peers and successfully progress. The notion of tactical adaptability is also noteworthy, considering the long-term goals and potential for correlated experiences the player will encounter across multiple environments and contexts. However, there are also some factors which, for some participants, are perceived to become important at the later stages of the pathway. Evidence of a top-down (needs of the context and game) approach throughout the system, but also bottom-up understanding where the player is now and their changing needs over time. Integrated consideration of both would appear judicious.

Objective 2: what and how performance is being measured

There was variety apparent in the tracking of player performance over time and how this was achieved (see Table 3).

Table 3. What is being tracked and how is performance being measured.

Theme	Raw data exemplar
Use of data	We measure [physical] through data driven analysis (P5) It’s [physical] become data driven at the PDP phase (P11)
Coach observation	We provide match reports. We have score scores summary, strivers, strugglers (P12)
Multidisciplinary monitoring	We apply six technical criteria and have different criteria for tactical, physical, and psychological. We audit the players against our criteria for each one (P5)
Player self-review	We measure that through player performance reviews, or how they reflect on how they’re doing (P5)
Differential weighing of measurement	Foundation phase, we measure the six key technical areas only (P5) At PDP, we monitor physically what each player doing, you know, in a certain position, how does that compare to first team? And against players in his position (P11)
Application of game context	Let’s keep looking at the context, what influence can this player have on the game, not how many times they use their left foot, or how many shots they had from outside the box, let’s look at their impact (P13)

Data collection procedures seemed to be predominantly focussed on physical elements, whilst observational methods appear to be aimed toward technical and tactical factors. In addition, there was a clear variability in what was being tracked, with the differential weighting of factors, once again, apparent at different times. At earlier stages of a pathway, some academies used relatively rigid technical assessment frameworks. As we highlighted earlier, and contrasting with a truly multifactor consideration, the difficulty in measuring psychological skills was discussed: “you can measure it (psychological skills) up to a point, but those triggers that are going on in that player’s head are personal to them” (P3). Participants expressed a level of scepticism regarding the validity of some physical measures: “I would rather look at the player’s ability to influence an impact a game of football, than try to say, this could be improved if he got fitter” (P13). Appropriately considering the integration of factors attributing to the players ability to influence and impact a game, rather than focussing attention solely on isolated physical measurement seems a well-guided approach but, once again, differential across participants and systems. For example, positional Key (physical) Performance Indicators (KPIs) and the application of Individual Development Plans (IDPs) seem to form the framework from which the assessment of performance at the Youth Development Phase (YDP) (12/13–16) and Professional Development Phase (PDP) (17–21) is made: “we have stage specific KPIs, and it comes down to subjective opinion and experience when we assess the players performance” (P14). Participants discussed how various rating constructs are assigned to both match day and training performance over time. This premise appears to be built upon identifying and tracking the performance of the players strengths, yet the means of such observational-based performance measurement was often seen as lacking reliability: “we used to score the players three, six and nine, what I found was there wasn’t any real disparity between the top performer, middle of the road and the ones struggling” (P7). It was perceived that the “result” of the game was noted as often overly influencing coaches’ judgement on performance, emphasising the potential lack of stability in the performance environment from which to make valid assessment.

Objectivity in tracking was much more evident in physical fitness measures. For several participants, using a battery of standardised physical tests drives baseline physical reference data which may be of limited long-term performance validity: “their energy systems are not developed or mature enough to have the kind of physical responses that somebody who’s gone through puberty would have to the same kind of fitness testing or physical regime” (P13). Indeed, when administered in isolation, these methods lacked maturation and game context and interactional consideration that was noted by several participants. Thus, may lose validly when assessing the players ability to perform and develop game-related physical skills. In parallel, a range of psychological characteristics, were perceived to be distinguishing factors that requires attention “things like a players resilience against different challenges and opponents would be good to properly keep an eye on” (P11). Notably, however, limited monitoring and tracking measures were used, with assessments commonly made (if at all) via observation of expected consequences rather than through direct measurement: “I’ve also seen, less advanced stuff like just observational based grading systems that are 1–10 or traffic lights” (P8).

The initiation of observational “rating” methods analysing technical and tactical strengths was often systematically deployed over time. This formula of performance measurement provides the basis for informed player feedback methods: “player progression charts where kids are improving on their potential grade or regressing, we’ll get feedback subjectively” (P15). Once again, however, these approaches were acknowledged as lacking objectivity by several participants: “we do three or four times a season, The players get feedback on the red, amber, green on the ILP (Individual Learning Plan) every six weeks, but it’s all opinion based” (P4).

Objective 3: how are factors integrated into a curriculum – differences between performance and development

These data are summarised in Table 4.

Table 4. Integration of factors into a curriculum.

Theme	Raw data exemplar
Informing Individual Development Plans (IDP)	An individual coach analyst provided the data for the IDPs as well. It gave us another bit of information, informed our practice feedback and our decision making (P2) They’ll look at what games are coming up in the next six weeks, it will all be based on the level of challenge, how much do we support them for them to get through and develop? (P14)
Deliberate effort building and “promoting” SMMs	There’s no room for a coach who doesn’t like that element of the game and doesn’t teach it (P7) The terminology being used, I’m feeling that there is that alignment in terms of terminology, the culture is those four values that we created. So that’s really what the golden thread is (P4)
Challenge of conflicting club and individual needs	We had a player at 17, they put them in the 18s and he wasn’t really ready for it, and he didn’t he didn’t cope mentally with the challenges and that affected him technically. Then he was bumped into the first team out of necessity, but nobody really had a conversation with him, which affected his training. So, in three years because he had a five-year contract, he tried to go out on loan but failed. He didn’t really do very well just sat in the U23s. and now he’s just been released (P11)
Differential weighting of factors curricular weighting	Our programme is heavily focused on technique and that’s from sort of the extreme technique at the foundation level, even right the way through to sort of U18, and U21 (P1) We really focus on the key skills or core technical skills for each position (P11)
Stage of curriculum	The foundation phase syllabus is fixed is because we know, when a boy comes out of our program at U11, he’s had the same amount of time protecting the ball, finishing, and passing and receiving, travelling with the ball, defending 1v1 and defending 2v2 (P7) We were quite aligned, the language and the demands will be different [between academy and senior], but it shouldn’t be a shock from a technical point of view, what’s going on in the [senior team] sessions should have some familiarity (P9)

The FCM seemed to be the predominant means of systematic assessment, measuring and coach feedback. In some cases, the curriculum superseded by the “force majeure” of high potential: “in setting the agendas, we work backwards from the most important player in that group” (P9). Indeed, a lack of long-term curricula design and coherence was stated as a factor affecting the players transition through the stages of the academy system and critically, into senior environments: “(player name) was always pushed to play up because physically he was always more advanced. However, technically he was miles behind if I’m honest and psychologically, he didn’t have the skills to cope” (P14).

In contrast, however, there is some evidence of clubs aiming to develop a top-down approach and build SMM constructs, with clear methods used to improve the level of coherence: “clarity of message and the clear vision for everyone, understanding what goals have been set, so that we can work towards them and that will hopefully align coaches’ behaviours” (P14). Despite these efforts, there were challenges which limited the impact of a coherent approach. Potential conflicts were cited as impacting the efficacy of informed player profiling, citing disparity between club and long-term individuals needs analysis and coaching practice: “because it becomes so structured, it becomes a catalyst of poor practice results, creating a robotic player who can’t make decisions for himself (P2).

Notably, the intended curricula appeared to be more structured at younger ages, coaches perceived this as being necessary to build what they saw as foundational skills. For participant 7 there was a view that ages 9–12 needed: “a systematic program where it’s prescribed providing a broad range of technical and tactical skills”. Indeed, participants strongly perceived the need for systematic structure in the FP. There was a consistent theme of systematic structure found within the FP, mostly aiming to specifically develop technical skills in a coordinated fashion. This common focus of curricula was apparent across all participants, even though the weighing of focus did fluctuate amongst clubs, suggesting that such curricula design was based upon age and stage rather than a whole academy philosophy.

Psychologically, and as highlighted in earlier sections, there was evidence of a shift towards mental elements as the player progresses towards the PDP. As players enter this phase, curricula are increasingly designed aiming to equip the player with the psychological skills to enable effective transition into the first team environment:

At the PDP stage, to further enhance their tactical understanding, we move away a bit from the technical and really look at the mentalities that they possess that are going to allow them to be a success in the in the in the professional game. (P14)

As players age, participants perceived a greater need for increasing individualisation for players. In some instances, this seemed to contrast with the approaches taken to tracking and monitoring with a risk that individual needs were missed by a more general approach. As participant 13 suggests:

We must be mindful of what the end game is for each player and how we maximise the development at each stage regarding age and maturity, so that we maximise the development for each player regarding where they are on their own journey?

For the participants, this notion of increasing coherence via a top-down approach and build of SMM seemed to be particularly relevant in supporting the design and implementation of a truly effective player curricular. A curriculum that was perceived to require an increasingly individualised focus as players age.

Discussion

The aim of this study was to investigate the TD policies and systems in place at high level English football academies, specifically understanding (a) what factors academies believe to be important in the development of their players, (b) explore what academies are tracking and how they measure performance, and (c) analyse the extent to which these factors are integrated with the player’s curricula. Our findings suggest it would appear judicious for academies to take an explicit note of “what matters most” both collectively and individually, from the point of identification, to ensure they are working on the most valuable aspects for each player. Coherently developing players with a range of skills and capabilities to meet the demands of the game at the highest level, as well as the needs of the club. From the academy perspective, it seemed clear that the integration of top-down club needs and bottom-up individual needs, was an appropriate means of shaping player curricula (Taylor et al., 2022). In some contexts, it seemed that the weighting of more generalised intended curricula and tracking could be a risk factor for individual players. For this reason, building a criteria upon the most important skills within and across each performance factor, whilst maintaining and monitoring other general elements could be an efficacious approach.

Although some physical characteristics (i.e., agility) were perceived to be important, using measures derived from adult needs may provide an unrealistic benchmark for effective developmental comparison. A considered and contextualised approach of good (rather than best) practice, one that individualises longitudinal tracking of physical characteristics may be more appropriate. For example, utilising important metrics as suggested by Saward et al. (2020), performing comparisons after systematically controlling for biological maturity and body size. As Carling and Collins (2014) suggest, in turn, mitigate the potential for observational bias influenced by growth and maturation (Morris et al., 2018) and other factors known to confer relative advantage or disadvantage (Sweeney et al., 2021).

Such approaches may provide a means through which to contextually inform from the top-down, built upon the needs of an individual club and professional football . From the bottom-up, using profiling to understand an individual’s needs, and those of the group. Optimally, this approach would prioritise player development aligned to the factors that most distinguish their capacity to meet the demands of the sport at future stages and at the highest level, for example,technical competency (Forsman et al., 2016) (e.g., receiving, passing, dribbling, turning, 1v1 attacking/defending), perceptual cognitive skill, tactical adaptability (Price et al., 2020) (e.g., awareness, decision-making), and a broad range of psychological skills. Tracking of these factors could provide a means in which to assess progression and support individual needs (Bradley et al., 2018).

Suggested means of technical and tactical development

Academies appear to construct a variety of frameworks to measure the technical and tactical performance of their players. Given their perceived centrality, technical and tactical factors seem to be widely measured via observational means. There is a danger that without shared understanding of , that includes contextual references (e.g., the game and maturation), consideration of club and individual needs that monitoring and tracking methods may be invalid. As such, lacking mulit-factor integration and not providing an appropriate picture of the player’s profile.

Accordingly, it would appear prudent to monitor and track the development of psychological skills using such concepts as the PCDE framework (MacNamara et al., 2010a). Psychological Characteristics of Developing Excellence Questionnaire version 2 (PCDEQ2) provides talent a valid and reliable measure from which to base effective psycho-behavioural interventions (Hill et al., 2019). Thus, measuring the psychological dimensions of development and ultimately improving the effectiveness of the academy processes. In turn, focussing attention on developing individual strengths across the factors, such as the understanding and metacognitive knowledge that facilitates tactical and strategic adaptation (Price et al., 2020) and technical competency (Forsman et al., 2016).

In order to operationalise this multifaceted approach, there is a need for academies to truly integrate with a shift from a multi to interdisciplinary orientation focus that has long been encouraged in performance settings (Alfano & Collins, 2021). We would suggest that the building of SMMs hold the opportunity to support this integration (Taylor & Collins, 2021). A coherent SMM model of broader player curricula, facilitating what the individual player actually needs at each stage of their pathway, holds clear merit. Aligned to the findings of Laureys et al. (2023) across alternative TDE settings and that of Price and Collins (2022) study in an English high-level youth academy, we would suggest that significant value can be found by academies in developing SMMs to facilitate the player’s pathway. This type of approach could involve implementing processes such as discussion-based workshops to evolve greater coherence and understanding of key performance factors(e.g., game understanding). This may also help coaches understand why there may be a weighting towards a particular factor at a given point and this might contribute to later development. In essence, supporting the coaching teams’ ability to rationalise and project the needs of players over time to generate a genuinely developmental curriculum that is integrated and operationally coherent. This may help both player and coach tackle the key challenges of transitioning through phases, for example, from small-sided to 11v11 games, or most critically, movement from the academy to the senior game.

Limitations

Clearly, the present study is not without limitations. As is the case in any interview-based data collection, there is also the potential for a variety of participant biases, based upon participants’ specific factors of interest, historical observations, and areas of skill. Similarly, whilst study size is not considered a limitation in qualitative research (Vasileiou et al., 2018) and, whilst widespread generalisation is not an aim of this study, grounded generalisations (Smith, 2018) are made based on the data presented. The number of participants relative to the extent of the developmental system in academy football should be taken into account. Therefore, the findings cannot be taken as wholly representative of every academy setting, especially internationally. Indeed, given the coaching and leadership background of all participants, it may be the case that alternative disciplinary backgrounds might bring different perspectives. To this end, we ask the reader to judge transferability based on the context of the participants working in English Premier League academies (Smith, 2018).

Conclusion

Using a high-level sample of football academy professionals, this study considered what academies are measuring and benchmarking and how they are tracking the progression of their players. Furthermore, exploring how standardised and club-specific assessment and measuring processes are integrating within their player development structures. Whilst academies appear to be considerate of a breadth of factors, each club grant a differing weighting of emphasis to each factor. Technical and tactical attributes are seen as key components, yet are primarily measured and tracked using observational-based methods. That might be sensible, but empirical data or rationale to support these differences is, as yet, not apparent. For example, it was interesting to note that clubs’ weighting, and predominant use of physical data seemed to vary in parallel with their player demographics. Isolated, adult themed physical assessments appeared to be overly utilised towards the purpose of single point-in-time benchmarking and comparison. For a variety of reasons, if used as a means of comparison, this is likely ineffective for youth players. Singular factor assessment, whilst limited, might be sensible, but it is the monitoring and tracking of multifaceted progression and development over time that holds significant potential within youth settings. As such, an effective tracking process should aim for deliberate integration with player curricula, acting to promote the development of desirable characteristics. Overall, we suggest that academies should be aiming towards building coherent SMMs of player development with the aim of promoting and supporting both club and individual needs.

Article highlights

• Academies consider a wide range of technical, tactical, physical, and psychological factors, yet with differential weighting and emphasis.

• The Football Association’s four factor: technical/tactical, psychological, physical and social model was the predominant means for systematic assessment, measuring and coach feedback.

• There was a perception that adult driven physical assessments were overly utilised for the purpose of benchmarking and if used incorrectly, might provide an invalid benchmark for effective developmental comparison.

• Implementing frameworks to monitor and track the development of other factors holds significant potential, especially if integrated with player curricula.

• We suggest the need for academies to develop coherent Shared Mental Models of the broader curriculum, which use tracking and assessment processes to promote individual player needs at each stage.

Disclosure statement

The authors acknowledge the organisations they represent and their support for conducting research. However, there was no financial support or inducement that impacted the results of this investigation. Matthew Layton by Swansea City Football Club, Jamie Taylor/Dave Collins employed by Grey Matters Performance UK.

Additional information

Funding

This work was not supported by any funding.