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Questions in the questionnaire, per section of the questionnaire.
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Scouts of soccer clubs are often the first to identify talented players. However, there is a lack of research on how these scouts assess and predict overall soccer performance. Therefore, we conducted a large‐scaled study to examine the process of talent identification among 125 soccer scouts. Through an online self‐report questionnaire, scouts wer...
Contexts in source publication
Context 1
... total, the questionnaire consisted of 8 questions (2 open-ended, 1 rank, and 5 multiplechoice questions) divided across three sections. Table 1 presents the different questions and response scales per section of the questionnaire. Participants completed the questionnaire at their own discretion. ...Context 2
... studies in other contexts (e.g. in job interviewing, Chapman & Zweig, 2005) found that applying structure was not a unidimensional construct, but consisted of different components. As such, we analysed the single-item scores, instead of treating the statements as one or multiple scales (see Table 1). ...Citations
... Multiple approaches exist within the current literature regarding TID and (de)selection processes, with data coming from a variety of multidisciplinary sources and assessment methods (e.g., signs, samples, subjective expert opinion; see. 3 However, minimal research exists exploring the information that coaches' may (sub)consciously utilise and combine in their decisionmaking processes. 4 Previous research has called into question the validity of TID and (de)selection judgements based on the subjective expert opinion (SEO) of high-level coaches, highlighting an absence of structure in (de)selection processes and a lack of specific criteria upon which decisions are based. 5 Research has highlighted that coaches often utilise their gut instinct, making choices based on their own experience, personal taste, and their perceived ability to improve a player, rather than exclusively considering player potential and performance. ...
... The process of identifying talent in soccer involves multiple factors, with technical proficiency often considered a key indicator of performance potential (for review, see (Sarmento et al., 2018). Research highlights the importance of technical skills, such as dribbling, passing, and shooting accuracy, as critical metrics for coaches and scouts to assess a player's abilities (Bergkamp et al., 2022;Huijgen et al., 2009;Waldron and Worsfold, 2010;Williams et al., 2020). The application of these technical skills in soccer requires players to adapt to the dynamic and ever-changing demands of the game environment (Araújo et al., 2019). ...
While motor and technical skills are typically assessed through field-based soccer tests, cognitive skills are usually evaluated in controlled laboratory environments. The Skills.Lab Arena is a newly developed testing and training device that enables motor, technical, and cognitive assessments in a soccer-specific setting. This study evaluated the reliability and usefulness of the Skills.Lab Arena technology. In a test-retest design (7 days, 1 month), 31 young soccer players (age, 13.5 ± 0.5 years) performed 10 trials of technical and motor-cognitive tests. Absolute and relative intersession reliability were determined using the in-traclass correlation coefficient (ICC) and coefficient of variation (CV). Bland-Altman analysis was used to assess agreement, mean differences, and limits of agreement (LoA). A repeated-measures ANOVA was applied to identify potential learning effects between test sessions. The smallest worthwhile change and typical error (TE) were calculated to assess the intersession usefulness of the tests. The Skills.Lab Arena tests demonstrated good relative and absolute intersession reliability, with ICC values ranging from 0.75 to 0.89 for time-based tasks and 0.71 to 0.91 for accuracy based tasks. Bland-Altman analysis revealed minimal mean differences with acceptable 95% LoA. CV values ranged from 1.78% to 4.5% for time-based tasks and were slightly higher, ranging from 8.08% to 19.87%, for accuracy-based tasks. Learning effects were observed in one ball-related agility test. In light of the results, the Skills.Lab Arena can be considered a reliable diagnostic tool for assessing motor-cognitive performance in young soccer players. However, despite its reliability, further validation is needed before it can be recommended for practical use.
... In sum, game intelligence is closely associated with executive functions and refers to the ability to execute appropriate decisions and effective actions in the soccer game (Mann et al., 2019;Williams and Jackson, 2019). Interestingly, tactical skills such as perceptualcognitive skills and game intelligence are in recent years claimed to be valid predictors of future success in soccer (Huijgen et al., 2014;Murr et al., 2018;Roca et al., 2018) and are therefore highlighted as especially important among coaches in talent identification (Larkin and O'Connor, 2017;Bergkamp et al., 2021;Roberts et al., 2019). ...
Introduction
Executive functions (EFs)—including working memory, cognitive flexibility, inhibitory control, and planning—are essential for adaptive decision-making in dynamic environments like elite soccer. This scoping review explores the relationship between EFs and game intelligence in adult elite soccer players.
Methods
A systematic search was conducted across six major databases: Scopus, Web of Science, SportDiscus, PubMed, PsycInfo, and ERIC. Fifteen peer-reviewed empirical studies published between 2000 and 2023 were identified and analyzed for inclusion.
Results
The review reveals a strong association between EFs and players’ ability to process complex game situations, anticipate opponents’ actions, and make strategic decisions under pressure. Evidence also points to possible variations in EF demands across playing positions. Additionally, several studies suggest that EFs may be trainable through perceptual-cognitive interventions, although this area remains underexplored.
Discussion
Despite promising findings, the studies exhibit substantial methodological heterogeneity, particularly in the operationalization of both EFs and game intelligence. This variability limits the comparability and generalizability of results. The review underscores the need for more standardized methodologies, longitudinal research designs, and integrative approaches that account for both cognitive and personality factors to better understand elite soccer performance.
... This may also result from a multidimensional concept of talent (e.g., Baker et al., 2019) and different sport-specific performance criteria in various sports (e.g., Bergkamp et al., 2018). For example, Bergkamp et al. (2022) used a questionnaire to understand which criteria are used to select players. Although the majority of scouts stated that they use different criteria to This document is copyrighted by the American Psychological Association or one of its allied publishers. ...
... The adaptive toolbox includes a lot of different heuristics, for example, take-the-best or recognition heuristic (Gigerenzer et al., 1999;Pilat & Sekoul, 2021). While coaches report to use different criteria when selecting athletes, they also report to make their decisions based on an overall impression (Bergkamp et al., 2022;Ludin et al., 2023). Bradbury and Forsyth (2012) reported that coaches often support the use of methods from human resource management like implementing decision rules. ...
The iCodes model by Jekel et al. (2018) states predictions about the information search in decision-making processes. Previous research validated the attraction search effect in various nonsport scenarios. This investigation explores coaches’ decision making in athlete selection contexts using the iCodes model’s main hypotheses. Hypothesis 1 states that the probability of coaches searching for a particular criterion regarding an athlete increases with the criterion’s validity. Hypothesis 2 states that when information is available, information search will be directed toward the more attractive athlete as an option (i.e., the attraction search effect). Moreover, a third hypothesis is added: The information search process differs between coaches from different sports. Seventy-five coaches were confronted with 52 option-information boards. In each trial, coaches opened athletes’ criteria and selected one athlete as “most talented.” After completing all trials, coaches ranked the criteria regarding their validity for athlete selection. Results showed evidence in favor of Hypotheses 1 and 3 but indeterminate regarding Hypothesis 2. Overall, this study presents an extension of the iCodes model and contributes to a better understanding of the underlying mechanisms of the coach’s eye.
... Additionally, by considering the athlete as a complex and dynamic system, it is essential to recognize the non-linear interactions among physical, psychological, technical, social, and cultural factors McLean et al. [11], integrating different fields of knowledge and fostering dialogue between sports sciences, psychology, sociology, anthropology, and other relevant disciplines O'Sullivan et al. [10]. Across different sports, investigation tends to be shown that athletes develop in different -often nonlinear-ways, and that reliable indicators of future elite performance are often not yet present or developed in young players Bergkamp et al. [12], reinforcing the idea that its urgent to shift our notions about this issue. ...
... What seems mostly assumed is that it's the relation between these factors that can make it possible to coherently explain the concept of talent and provide the basis for the construction of development paths for it. Moreover, since the attributes needed for excellence are often unstable, develop non-linearly over time, and may not even be present in young players Bergkamp et al. [12], it's necessary to be particularly aware of the complex and dynamic character of this relation. The sources also point to areas that require greater investment by research. ...
... In summary, the combination of references presented here seems to provide a sufficiently solid basis for understanding that multiple factors may contribute to the definition of the concept of talent, its identification Bergkamp et al. [12] and its development in sport. It's crucial to recognize the dynamic interaction between these different influential factors, namely individual, task and contextual factors for an adequate conceptualization of the term that allows, as a consequence, the structuring of profitable paths to promote sporting excellence. ...
... To this end, TID research consistently highlights the limitations of early selection (e.g. Bergkamp et al., 2022), especially when underpinned by a deterministic assumption that an athlete's future performance can be predicted by their current performance (Güllich & Barth, 2023). More recent literature (e.g., Morganti et al., 2023) has pointed to alternative approaches, such as probabilistic reasoning, which suggests the potential for TID to be responsive to what an athlete could become, i.e. the interdependence of selection and development, influenced by socio-cultural, individual and environmental factors. ...
Decision making related to the future potential of athletes has become a significant area of research attention. Talent selection decisions in sport are considered complex, highly nuanced, and influenced by a multitude of factors. The purpose of this study was to explore individual and systemic factors influencing talent selection decision making in team sports. Twelve experienced recruitment professionals, across three professional male team sports, participated in semi-structured interviews. Findings suggest that organizational and contextual factors influence both individual judgements and the wider selection process. These factors are considered through micro (individual), meso (organization) and macro (system) lenses. There was an appreciation that not all selection decisions are the same, carrying different degrees of uncertainty based on the stage of the talent system. The context of decisions varied between systems, with a variety of processes being used to manage the inherent uncertainty of selection. In addition, systems aimed to reduce the consequences of "non-selection" and reduction in the use of "one-off" selections. Because of this complexity, there is a need for research to consider the wider system in which selection decisions are taken. In practice, we suggest that talent systems are shaped in a manner that encourages more "hedge-trimming" type decisions (allowing for continuing opportunity), rather than "tree-felling" (in or out) decisions.
... For instance, when comparing players of different competition levels, elite soccer players reported to be better at dribbling and ball retention during games (Waldron & Murphy, 2013). In addition, superior technical skills, such as dribbling, short/long passing, and shooting (Huijgen et al., 2014;Leyhr et al., 2018;Waldron & Worsfold, 2010) provide relevant information for talent identification systems and/or predicting later performance (Bergkamp et al., 2022;Koopmann et al., 2020;Sarmento et al., 2018). Tactical skill levels during developmental years seem to be a good predictor of future performance at the professional level (Huijgen et al., 2014;Kannekens et al., 2011). ...
... 9 Research using this model on talent development and identification usually seeks to identify what sport pathway and developmental activities contribute most to participation in elite performance. 1,10 It usually shows that sports participation in soccer has a major influence of cultural aspects, such as players born in different countries and continents. Studies carried out in England, Norway and Germany [11][12][13] showed that hours accumulated in soccerspecific team practice and play in childhood are associated with expert levels of achievement. ...
The purpose of this study was threefold: (1) to compare the engagement in various types and amounts of soccer activities during childhood and adolescence between Brazilian and Spanish elite youth soccer players; (2) to test what talent development pathway characterizes youth development in elite soccer in Brazil and Spain and (3) to compare the practice structure between elite youth soccer in Brazil and Spain. Participants were 131 U-18 elite male soccer players from Brazil (n = 68) and Spain (n = 63) competing in the national league. The Participant History Questionnaire was used to measure the soccer activities undertaken by players. Developmental activities were analyzed for two age periods: childhood (6–12 y/o) and early adolescence (13–15 y/o). In Spain, players started their involvement in practice and competition in soccer earlier compared to Brazilian players (p < .05). Brazilian players were more involved in structured activities, such as practice in soccer and futsal, and participated in a greater number of sports in childhood and early adolescence (p < .05). We found a very similar percentual practice structure (individual, pair, drills, group tactics and collective tactics activities) between Spain and Brazil, although Brazilian players accumulated a greater practice volume. It is concluded that Spanish and Brazilian U-18 elite youth male soccer players were differentiated by their milestones in soccer and their engagement in practice activities during childhood and early adolescence. Talent development pathway of male soccer players in Spain was characterized by the early engagement pathway, while the Brazilian system was characterized by the specialized sampling model.
... Turner et al. [14] recommended that multidisciplinary coaching staff in team sport settings align on a holistic indication of an individual's athleticism to help inform selection and development. However, in team sport contexts, determining whether a specific participant is a good 'athlete' usually reflects the relationship between performance attributes and positive outcomes [16]-not an individual's need to perform a specific athletic task well in isolation (i.e., sprinting, jumping). In other words, the focus is on whether an individual can use a specific athletic attribute to positively influence outcomes (i.e., speed of transition from defense to attack, goal threat from set pieces), usually regardless of the attribute's relevance for future long-term development. ...
A clearer understanding of, and tighter boundaries between, terms are important for researchers designing studies as well as for other sport stakeholders creating evidence-informed policies. This article considers the terms ‘athlete’, ‘talent’, and ‘player’ from psychological and sociocultural perspectives and in different sporting communities to highlight the importance of terminological clarity in sport research. We present considerations to clarify the use of these terms within different contexts and how the use of specific terms may affect knowledge mobilization in diverse sporting populations. A conceptual discussion is provided to help operationalize development-related terminology and its associated stages, to better reflect contemporary academic thought, and enhance practical interpretations. Importantly, we also call for greater transparency from researchers when presenting findings and encourage practitioners to clearly define key terms when working in sport. Our intention in this paper is to energize readers to consider how we use language in athlete identification and development contexts, to stimulate deeper thought and discourse around the possible implications these terms may have at any point of an individual’s development in sport. Greater deliberation, identification, and acknowledgment of the drawbacks accompanying these terms will be needed before more confident assertions can be made on how researchers and practitioners could (or even should) implement certain terminology across youth sport contexts moving forward. This paper adds to a growing literature on the importance of clarity in terminology and acts as an impetus for those working in specific sports to co-design key terms used by researchers, practitioners, and policy makers.
... 10 This also relates to the complexity involved in the development of meaningful feedback to improve performance, something that has been addressed in previous research regarding the delivery of videofeedback. 11,12 In this regard, recent studies have addressed several themes and stakeholders within the performance analysis domain, such as scouts 13 and analysts 4 as well as looking at quantitative parameters, 6 key performance indicators 12,14 and several other predictive and outcomespecific parameters in the performance-related context. 10 While this contributes to our understanding of the performance analytical process, there are still open questions regarding the process of developing information and feedback, such as the need to further understand aspects like coach learning, contextual factors, as well as applied performance analysis practices. ...
... To ensure that the data collected from match analyses is helpful and not a hindrance in this endeavor, we consider it essential that future research and applied practice starts to scrutinize on some of the day-to-day work in this field, such as the use of video data in opposition analyses. While recent work has investigated several components of performance analysis such as the adoption of key performance indicators 14,30,31 as well as the subjectivity in the talent identification process, 13 there are still questions that remain unanswered regarding the process by which meaningful information is created for players, specifically while maintaining the structure of daily tasks that are critical in the delivery of applied performance analysis. 4,5,11,12 Furthermore, it also approaches the use of data in football from a domain-specific perspective by asking tactical and descriptive answers to coaches at varying levels of experience. ...
Using video data is a widespread procedure in the preparation for an upcoming opponent across all levels of football, but the way coaches interpret this data and use it for player feedback is still not fully understood. Three studies were conducted to investigate the level of agreement between football coaches on tactical questions regarding the opponent when interpreting the same video data. In Study 1 (scouting feed; N =15) and 2 (tactic view feed; N =24), different video viewing angles of the same match were provided to coaches, followed by simple questions regarding the viewed team (e.g., team formation, most striking player in the opening play of the attacking team). Response analyses using descriptive statistics and Fleiss-Kappa statistics showed great diversity regardless of the angle of the feed. Study 3 was a replication study (scouting feed; N =16) using the identical approach as before but used a different match to introduce greater variety of video stimuli. Across all studies there was a high degree of diversity in coach responses and little consensus on basic questions like the adopted formation or the most striking player in the opening play (Fleiss-Kappa coefficients between -.036 [poor agreement] and .236 [fair agreement]). The present research shows that it is problematic to treat information from video feeds as being objective when preparing for the next opponent, as different coaches derive different interpretations from the same data source. Implications for use of video data, and related contributions to coaching research are discussed.
