Talent identification is vital to the unearthing of future sports stars [1
], and football is no exception to that rule. In the football world, sporting and economic objectives essentially dictate the way in which the processes for selecting football players from young ages [3
] are conducted. An example of the sporting objective is provided by F.C. Barcelona (named the best training club in a 2015 report by the CIES Football Observatory), which admits only 0.5% of the 10,000 children it watches every year to its La Masía academy [4
]. However, despite the small number of children who meet the club’s selection criteria, Guillermo Amor, one of the heads of its youth academy, says that “our intuition fails many us, and a lot” [4
] (p. 27). Meanwhile, at Real Madrid (which received an award from France Football
in 2008 for having the best youth setup in Europe) economic objectives are a cornerstone of its youth training policy [5
], with the club seeing “business opportunities in young football players” [5
] (p. 38).
Talent identification has thus become a key issue in the sport, for both the majority of the world’s clubs, in their desire to achieve their objectives, and for the families of players, given the rise in social status that footballers enjoy on reaching the elite [6
]. Regardless of the talent management model implemented by each club [7
], it goes without saying that the instruments used in processes for identifying football talent should be reliable, due to the considerable importance they have in sporting, economic and social terms.
Nonetheless, the various existing tests used to measure talent performance [8
] do not appear to be clearly defined [9
], mainly due to the lack of objective criteria for gauging player performance [10
]. The difficulty with the identification process lies in that fact that the successful selection of players requires looking beyond the point at which they are evaluated [4
]. The skill lies in identifying players who do not attract attention, but who have the potential to reach the elite. These players are the most difficult to spot. This is the main reason why football coaches pose a problem when it comes to setting criteria for the identification of the most talented players [11
], criteria that are based mainly on intuition [4
There have traditionally been two approaches to measuring talent performance [12
]. The first of them, the top-down approach, seeks to analyse, from a quantitative viewpoint, the characteristics of elite athletes, with the aim of assessing and predicting performance. The work carried out by Matthys et al. [13
], Torres-Unda et al. [14
] or Zhanel et al. [15
] are examples of such an approach, where the anthropometric, physical, physiological, technical, tactical and psychological characteristics of athletes are taken as reference points for assessing and predicting performance. There are football-specific studies that have sought to identify the differences between expert and novice players at an anthropometric [16
], physical, physiological [17
] and cognitive [18
] level. We have also come across studies that seek to identify the best performance predictors [20
] based on the functional capabilities of the footballer [21
] and their physiological characteristics [23
]. There are also training programmes that aim to respond to the individual needs of each player by working on skills such as physical speed, agility and speed of thought [25
]. These programmes are conducted with professional football players [26
] or as part of the personalised training sessions organised by the Fédération Internationale de Football Association (FIFA) for talented players [27
]. Finally, this approach obtains indicators of the performance of such players, both individually [28
] and collectively [29
Nevertheless, despite the potential advantages provided by this quantitative approach, it does involve two limitations. One stems from the type of study population, which is usually expert/novice, inherent in which is the subjective nature of the label “expert”. The other is the type of design. There is a lack of longitudinal studies [21
], which can mean that the results obtained at any given moment are conditioned by factors such as maturity or the relative age effect [30
The aim of bottom-up, the second of the two approaches to measuring talent performance, is to study the most qualitative aspects determining the training and development of football talent [19
]. This approach is a response to the difficulty of objectifying the identification process and the limitations posed by the quantitative approach [21
]. The importance of the qualitative study of performance lies in the individual knowledge possessed by each player, which, combined with practice, creates a unique path in the talent development process [31
]. The studies conducted by Bloom [32
] and Coté [33
] are examples of such work and involved interviews with athletes reaching the elite and with their families. Also notable in this respect is the work carried out by Fiorese Vieira, Lopes Vieira and Jornada Krebs [34
], who used a case study to chart the career path of an Olympic swimming champion; a study conducted by Sánchez Sánchez [35
], who interviewed professional basketball players; and the work of Cabanillas Cruz [36
], who reconstructed the life story of a professional karateka from a case study. Similar studies have been conducted in football, such as one undertaken by Matthew and Harwood [37
], who analysed the performance context of young English footballers by carrying out interviews with coaches, experts and players. In a similar vein, Pazo Haro, Sáenz-López Buñuel, Fradua Uriondo, Barata Figueiredo and Coelho e Silva [38
] used interviews to study the development of football players from the perspective of youth academy coordinators. These studies reveal the existence of myriad contextual factors, such as the family, practice opportunities, injuries and even luck, all of which can be crucial to achieving sporting success. The limitations of this approach arise mainly from the context in which research is carried out, due to the range of sports played, which varies according to the country of birth [39
], and the lack of transnational studies that would otherwise compensate for this limitation.
To sum up, what is striking in the football world is that while the motives for the correct identification of talent appear to be clear (mainly sporting and economic) [3
], there does not appear to be a clearly defined instrument enabling a quality talent identification process to be carried out [9
]. Furthermore, even in the physical tests used to identify talent, it has been shown that there is no correlation between their results and the final selection of athletes [40
]. One study confirming this finding was carried out by Lago-Peñas, Rey, Casáis and Gómez-López [20
]. It established the physical (speed, strength and stamina) and anthropometric profiles (height, weight, body mass index, six skin-folds, four diameters and three circumferences) of young football players in accordance with their position (16 goalkeepers, 26 central defenders, 29 full-backs, 34 defensive midfielders, 28 midfielders and 23 forwards) through physical tests such as the Yo-Yo Test, Sprint Test and Jump Test. At the end of the season, the coaching staff was asked to select which players should stay on in the team, with the rest being excluded. The results of the study confirm that body composition was similar in the two groups. Though the selected players had slightly better physical attributes, the statistical differences between them and the excluded players were not significant.
Educational sources are the only ones that provide any successful precedents regarding the use of objective instruments (nomination scales or intelligence tests) for measuring talent performance [41
], with it being noted that the triangulation of information from teachers, parents and teammates provides a very reliable means for identifying giftedness [42
]. It seems obvious to think that the teacher is an adequate agent to perform this type of detection, however, it has been demonstrated for decades that parents are good and effective identifiers of students with high intellectual abilities [44
], having been showed his reliability for these processes [45
]. Therefore, due to the findings found in these studies, current studies [46
] include the figures of the expert (teacher), parents and classmates in their processes of detection of students with high intellectual abilities, because these may contribute by informing the school of their child's abilities that cannot be detected by the teacher at school. This, together with the possible biases committed by the teachers [50
], give the rest of the parents and peers a great importance in this process.
Subsequently, just as is the case in the educational environment, where scales and intelligence tests are focused on measuring a specific aspect pertaining to a gifted student (a talent for mathematics, speaking, music etc.), in the football world it is the areas that are most crucial to becoming a talented footballer that must be identified first of all. In accordance with the rules and their internal logic, therefore, and as shown in the literature consulted, the most decisive aspects in identifying a talented footballer are technical/tactical aspects such as decision-making and positioning [51
], behavioural aspects such as discipline [53
], mental aspects such as game intelligence and attitude [11
], and social attributes such as the ability to engage with teammates [38
As a result, and in view of the above, the aim of this study is to design and validate an instrument that can be used to assess football players and that brings about an improvement in the football talent identification and development processes so that optimal use may be made of the resources football clubs allocate to this task.
shows the Content Validity Index (CVI) as proposed by Lashwe [56
] for each of the items on the original scale.
In accordance with Laswhe’s [56
] criteria, items 2, 10, 11, 16, 21, 22, 23, 24, 25, 26 and 27 were removed. Despite showing a lower value, items 1 and 13 were retained in the final scale because of their importance to the study and the wealth of literature on sport commitment [30
] as a decisive factor in football talent. Table 2
shows the final scale. It includes a brief explanation of each item, another recommendation made by the experts.
Secondly, an exploratory factor analysis of principal components with Varimax rotation (Table 3
) was carried out with the resulting 13 items in the calibration sample. As there is no suitable theory about the aspect under analysis, the aim being, therefore, to check the factor matrix of the scale.
To check that the data matrix is suitable for conducting an EFA [51
], Bartlett and Kaiser, Meyer and Olkin’s test (KMO) of sphericity was carried out, with appropriate values being obtained in the replies of the coaches (0.871), parents (0.825) and players (0.777).
An EFA was then conducted to check the number of factors in the scale, with the answers being separated into different categories: coaches, parents and players. Table 3
shows how the items are distributed in each factor in accordance with the coaches’ answers.
shows the factor loads in accordance with the answers given by the parents of the players.
shows the factor loads in accordance with the answers given by the players themselves.
The factor analysis pointed to the existence of three factors that explain the variance of the matrix. The first factor corresponds to game intelligence (technical/tactical aspects). The second factor relates to motivational aspects. The third factor corresponds to psychological aspects.
The internal consistency of the scale was calculated using Cronbach’s alpha coefficient. The questionnaire delivered to the coaches revealed a total coefficient of 0.906 for Factor 1, 0.911 for Factor 2, and 0.848 for Factor 3. The internal consistency of the general scale for coaches was 0.914.
In the case of the players’ parents, the internal consistency of the scale revealed values of 0.838 for the first factor, 0.758 for the second factor, and 0.583 for the third factor. The internal consistency of the general scale for the players’ parents was 0.869.
Finally, the internal consistency of the scale in accordance with the answers given by the players revealed values of 0.784 for Factor 1, 0.745 for Factor 2, and 0.659 for Factor 3. The internal consistency of the general scale for the players was 0.852.
Thirdly, a confirmatory factor analysis was conducted with the validation sample, using Amos 21.0 software. The maximum likelihood method was used to estimate the parameters. The following fit indices were used: X2
, the Standardized Root Mean Squared Residual (SRMR), the Root Mean Square Error of Approximation (RMSEA), the Tucker-Lewis Index (TLI), and the Comparative Fit Index (CFI). The results are shown in Table 6
These values indicate that, in general, the model fits the data, thus confirming the theoretical structure proposed.
Fourthly, for the purposes of assessing the convergent validity of the NSIFT, a correctional analysis was made of the scores awarded by the three groups studied (coaches, parents and players) and the relation with the final result (nomination as a talented player). The results are shown in Table 7
shows a significant (p
< 0.001), moderate (between 0.41 and 0.6) and positive correlation between the results obtained for the coaches and the players (0.434). Furthermore, the three groups correlate significantly with the nomination of football talent, with the relation with parents being moderate (0.499), the relation with coaches high (between 0.61 and 0.8, in this particular case 0.711) and the relation with players very high (between 0.81 and 1, in this particular case 0.847).
Finally, Table 8
shows the correlations between the three factors of the matrix.
shows how, in the case of coaches and players, all the relations between factors are positive and moderate (between 0.41 and 0.6). With regard to the players, however, the relation between their factors is slightly lower. Regarding the parents, meanwhile, the relations are negative and their intensity is low and moderate.
The bibliographical search for precedents with regard to the identification of football talent underlines the argument put forward by [9
], who hold that it is unclear which tests are suitable for satisfactorily measuring talent performance in football. With that in mind, the aim of this study was to design and validate an evaluation instrument (NSIFT) for identifying football talent, the objective being to improve the processes whereby footballers are identified so that full use can be made of the resources allocated by clubs to this task, which is one of great importance [6
In designing the NSIFT, the study’s researchers drew on the prior literature consulted, and identified the technical/tactical dimension [51
], character [53
], mental approach [11
] and social attributes [38
] as the most decisive aspects with regard to football players. The scale was then validated by the judgment of 16 experts (eight doctors from the field of physical activity and sports sciences and eight football coaches) with a view to determining if these items fit in with the reality measured, that of football talent. Lashwe’s [56
] criteria were followed in obtaining the CVI of each item from the answers of each expert individually in a table of specifications.
The results obtained from the answers given by the experts in validating the NSIFT confirm the importance attached in the prior literature to cognitive [51
], psychological and social [38
] and mental dimensions [59
] in identifying a talented prospect in this field, which supports the findings of Miller, Cronin and Baker [60
], as it is not entirely clear that the physical dimension is an accurate indicator of football talent [20
Secondly, exploratory and confirmatory analyses were conducted with a calibration and validation sample respectively, chosen at random from the sample used for this study. The aim was to determine the structure of the factor matrix of the scale and thereby ascertain the factors into which the instrument was divided, and to check if these results coincided with the prior literature consulted and the expert judgment. The results of the analysis confirmed that the factor structure of the scale is comprised of three factors, which tie in with those proposed by the experts: game intelligence (cognitive aspects), motivational aspects and psychological aspects. It should be pointed out that the lack of prior scales of this type in football means that a comparison could not be made. Furthermore, and continuing with the statistical analysis of the instrument, an internal reliability analysis was carried out (Cronbach’s alpha) with the aim of determining its reliability. The results of the analysis indicated high reliability values (all above 0.8) for the three aforementioned groups (coaches, parents and players). The literature indicates that all instruments with a value lower than 0.7 can be seen as being largely unreliable [57
]. The results obtained in this study therefore reveal a high consistency between the variables in the scale. This confirms the importance of including coaches, parents and players in football talent identification processes, as stated in the only precedents from the educational environment [41
]. If this were not the case, these processes would be based solely on the intuition of the expert [4
]. The use of nothing but expert opinion would result in a large number of footballers with potential talent being left out of the “talent pool”, as Renzulli and Gaesser [44
] call it.
The convergent validity of the NSIFT revealed statistically significant relations between the nomination made by the players and the coaches. This is not the case with the parents. This can be explained by the fact that it is the coaches and team members who possess greater knowledge of the players, as they spend more time with them in the football environment. Another of the study’s findings confirming this is the fact that the players are best able to identify talented teammates, achieving a higher correlation (0.847) than that obtained by coaches and parents, which indicates that the people who spend the most time together in this environment are able to more clearly identify who stands out in each facet of the game. This finding confirms the precedents found in the educational environment, in which in most of the instruments designed for the nomination of gifted students—though it is true that they consider the triangulation of information from teachers, classmates and parents [45
]—the first step in the screening process involves ascertaining the opinion of teaching staff. This is the case, for example, in Renzulli’s Identification System for Gifted Programming Services (RIS/GPS) [42
], in which teacher and test-based nomination are the first two steps in creating the talent pool, due to their importance.
Finally, a correlational analysis of the scale was conducted with the aim of finding out the relation between each of the three factors identified in the factor matrix, according to the answers given by the coaches, parents and players. The results showed that the relation between the factors of the players and coaches was similar. However, with regard to the parents, the relation between Factor 1 (game intelligence) and Factor 2 (mental aspects) is negative, which indicates that as the cognitive abilities (game intelligence) of a football player increase, their motivation to play football decreases. This can be explained by the change in the role of families in the development of talented players, given that, and in accordance with the Developmental Model of Sport Participation (DMSP) proposed by Coté [33
], as the athletes' sport commitment increases, so the coach takes on an increasingly prominent role, with the role of the family decreasing. In light of these findings, and bearing in mind that it is parents who are least capable of identifying football talent, we can conclude that the rather remote vision they possess provides an explanation as to why they think that as a player progresses in their age group, their motivation with regard to the sports environment can fall away, this aspect being vital for sport performance [61
In short, this study confirms the reliability of the scale proposed for the processes of identifying and developing football talent, and emphasises the importance of including both parents and players in the process, with it being shown that teammates are best equipped to identify football talent, followed by coaches (experts) and parents. As a result, these identification processes cannot be based almost exclusively on the intuition of the expert [4
], given that their intuition can “fail” many of them and on many occasions, as Amor states [4
] (p. 27). Furthermore, these results confirm those of the sources from the educational environment, in which the triangulation of information has been used for many decades to identify gifted students. An example of this is the study conducted by Sánchez López [62
], the objective of which was to identify gifted students at schools through the opinion (scales) of teachers, parents and classmates. Another is Renzulli and Gaesser’s aforementioned model [44