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Journal of Sports Sciences Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/rjsp20
Talent identification and selection process of outfield players and goalkeepers in a professional soccer club a
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Susana María Gil , Jon Zabala-Lili , Iraia Bidaurrazaga-Letona , Badiola Aduna , Jose b
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Antonio Lekue , Jordan Santos-Concejero & Cristina Granados
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Department of Physical Education and Sport, Faculty of Physical Activity and Sport, University of the Basque Country (UPV/EHU), Vitoria-Gasteiz, Spain b
Medical Services, Athletic Club, Bilbao, Spain
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UCT/MRC Research Unit for Exercise Science and Sports Medicine, University of Cape Town, Cape Town, South Africa Published online: 28 Nov 2014.
Click for updates To cite this article: Susana María Gil, Jon Zabala-Lili, Iraia Bidaurrazaga-Letona, Badiola Aduna, Jose Antonio Lekue, Jordan Santos-Concejero & Cristina Granados (2014) Talent identification and selection process of outfield players and goalkeepers in a professional soccer club, Journal of Sports Sciences, 32:20, 1931-1939, DOI: 10.1080/02640414.2014.964290 To link to this article: http://dx.doi.org/10.1080/02640414.2014.964290
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Journal of Sports Sciences, 2014 Vol. 32, No. 20, 1931–1939, http://dx.doi.org/10.1080/02640414.2014.964290
Talent identification and selection process of outfield players and goalkeepers in a professional soccer club
SUSANA MARÍA GIL1, JON ZABALA-LILI1, IRAIA BIDAURRAZAGA-LETONA1, BADIOLA ADUNA1, JOSE ANTONIO LEKUE2, JORDAN SANTOS-CONCEJERO3 & CRISTINA GRANADOS1 1
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Department of Physical Education and Sport, Faculty of Physical Activity and Sport, University of the Basque Country (UPV/EHU), Vitoria-Gasteiz, Spain, 2Medical Services, Athletic Club, Bilbao, Spain and 3UCT/MRC Research Unit for Exercise Science and Sports Medicine, University of Cape Town, Cape Town, South Africa (Accepted 3 September 2014)
Abstract The aim of this study was to analyse the talent identification process of a professional soccer club. A preselection of players (n = 64) aged 9–10 years and a final selection (n = 21) were performed by the technical staff through the observation during training sessions and matches. Also, 34 age-matched players of an open soccer camp (CampP) acted as controls. All participants underwent anthropometric, maturity and performance measurements. Preselected outfield players (OFs) were older and leaner than CampP (P < 0.05). Besides, they performed better in velocity, agility, endurance and jump tests (P < 0.05). A discriminant analysis showed that velocity and agility were the most important parameters. Finally, selected OFs were older and displayed better agility and endurance compared to the nonselected OFs (P < 0.05). Goalkeepers (GKs) were taller and heavier and had more body fat than OFs; also, they performed worse in the physical tests (P < 0.05). Finally, selected GKs were older and taller, had a higher predicted height and advanced maturity and performed better in the handgrip (dynamometry) and jump tests (P < 0.05). Thus, the technical staff selected OFs with a particular anthropometry and best performance, particularly agility and endurance, while GKs had a different profile. Moreover, chronological age had an important role in the whole selection process. Keywords: physical test, velocity, agility, power, strength, body size, RAE
Introduction Scientists have described four stages in the process of searching for excellence in sport (Williams & Reilly, 2000): talent detection, identification, selection and development. Thus, the technical staff of professional soccer clubs develop different kinds of programmes in order to discover those players who could benefit from specific training schedules and would potentially succeed in the club. Several attempts have been made to identify the characteristics of talented young soccer players. In this respect, some cross-sectional studies have compared groups of players of different levels such as elite versus nonelite or subelite players. It has been observed that elite players have less body fat and are taller than subelite players (Williams & Reilly, 2000). Also, many authors agree that elite players display a better performance in the physical tests (Vaeyens
et al., 2006; Williams & Reilly, 2000) and have several technical skills (Vaeyens et al., 2006). Moreover, selected players displayed better performance than nonselected in an U-14 selection team (Coelho E Silva, Figueiredo, et al., 2010). Nonetheless, they were also more experienced and mature, which may have accounted for the differences. One of the limitations of these cross-sectional studies is that usually the groups that are compared do not train together, and they may have different training histories; therefore, many of the differences may come from the training status rather than from the actual talent. Therefore, longitudinal studies overcome this problem by analysing the outcome of the athletes after a shorter or longer period of time. By this means, differences in body size and functional capacity were observed among players who discontinued participation and continued or moved to a
Correspondence: Susana María Gil, Department of Physiology, Faculty of Medicine and Dentistry, University of the Basque Country (UPV/EHU), Barrio Sarriena s/n, Leioa 48940, Spain. E-mail: [email protected] © 2014 Taylor & Francis
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higher level (Figueiredo, Gonçalves, Coelho E Silva, & Malina, 2009) and also between selected and nonselected players of a soccer club (Gil, Ruiz, Irazusta, Gil, & Irazusta, 2007; Gil, Gil, Ruiz, Irazusta, & Irazusta, 2007). Besides, height, body mass, maximal anaerobic power and maturity status varied among players who achieved amateur, professional or international level (Le Gall, Carling, Williams, & Reilly, 2010). It is noteworthy that the aforementioned studies either cross-sectionally compared teams of different levels or longitudinally followed the success of players during a certain period of time. Still, to our knowledge, there are no investigations about the actual talent identification process, defined as the procedure of recognising the most talented players (currently playing soccer) with the potential to become elite players and being incorporated into a club, in the context of professional soccer. Thus, the general objective of the present study was to analyse the process of talent identification of young soccer players in a professional soccer club. With this purpose, we analysed the characteristics of young players going through the different phases of the talent identification process of the club, in order to ascertain what the most relevant characteristics are. Also, our aim was to compare the anthropometric and performance characteristics of outfield players (OFs) and goalkeepers (GKs) involved in the above-mentioned selection process. Methods Each year, the technical staff of this particular club select soccer players to enter the youngest team in the club (players aged 9–10). The selection process goes through two phases. First, during the first months of the season, a number of players are selected from all the soccer players around the county belonging to around 300 teams (first selection). Second, between this first selection and the end of the season, players continue training in their original clubs, but attend one training session per week within the club’s facilities under the supervision of the club’s coaches. By the beginning of the following season, the technical staff make a small selection of players to definitely join the club (final selection). This selection of players is performed through the observation of training sessions and matches. This professional soccer club has a particular philosophy of employing only locally born players or players born elsewhere but trained from childhood/adolescence in the club. Thus, identifying players with the potential to become high-level professionals is a major issue for the technical staff. In the present study, these phases followed the same protocol. We undertook anthropometry,
performance and maturity measurements in the players first selected and also players of an open soccer camp (control participants), whereas statistical analysis was performed once the final selection was made. Thus, comparisons were made between players of the first selection (54 OFs and 10 GKs), players of the soccer camp (n = 34) and players finally selected (17 OFs and 4 GKs) versus the nonselected. Besides, differences between OFs and GKs were also analysed. The players in the open soccer camp also played soccer in clubs around the county but had not been preselected for this particular club and therefore would be representative of the soccer players of the county. All participants trained twice a week (1- to 1.5-h training/day) and played a match during the weekend. They all played in the same county league. Written informed consent was received from all players and parents after verbal and written explanation of the experimental design and potential risks of the study. The ethics committee of the University of the Basque Country for Research on Human Subjects approved this study. The measurements were performed according to the ethical standards of the Helsinki Declaration. Measurements were taken in the same sports hall and under the same external conditions: for the anthropometric measurements, players only wore shorts and for the performance tests they wore shorts, T-shirt and soccer boots, except in the jump test, during which they wore running shoes. The following tests were carried out on all players at the same time of the day and in the same order. Anthropometric measurements Height, sitting height (Añó Sayol, Barcelona, Spain) and body weight (Seca, Bonn, Germany) were measured. Leg length and the ratio between leg length and sitting height were calculated. The body mass index (BMI) was calculated from height and body weight (kg · m–2). Skinfold thicknesses (measured in mm) were measured at six sites (triceps, subscapular, abdominal, suprailiac, thigh and calf) using a skinfold calliper (Harpenden, England), and the sum of these six measurements was calculated (sum of skinfolds). The amount of fat in the extremities (limb fat) was calculated as the sum of the skinfolds of the extremities: triceps + thigh + lower leg. The amount of fat in the trunk (body fat) was calculated from the sum of the subscapular, abdominal and suprailiac skinfolds. The circumferences of the upper arm, thigh and lower leg (in cm) were measured using a tape measuring (Lufkin, Germany). Four diameters (in cm) were obtained using a calliper (Harpenden, England): biepicondylar of the humerus (elbow),
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bistyloid of the wrist, biepicondylar of the femur (knee) and bimalleolar of the ankle. Body composition (fat, bone and muscle percentages) (Faulkner, 1968; Rocha, 1975) and somatotype (endomorphy, mesomorphy and ectomorphy) were calculated (Heath & Carter, 1967). Due to the time constrictions, complete body composition and somatotype were not calculated for the players attending the soccer camp. All the measurements were taken following the guidelines outlined by the ISAK (International Society for the Advancement of Kinanthropometry) by the same researcher.
Yo-yo intermittent recovery (Yo-yo IR1) test
Maturity
Handgrip (dynamometry) test
The time before peak height velocity, labelled maturity offset, was predicted using a formula (Malina, Coelho E Silva, Figueiredo, Carling, & Beunen, 2012; Mirwald, Baxter-Jones, Bailey, & Beunen, 2002). Predicted age at peak height velocity (APHV) in years was estimated as chronological age minus maturity offset (Malina et al., 2012). Adult height was predicted using the Khamis– Roche method (Khamis & Roche, 1994), and the height at the time of the measurements was calculated as the percentage of the predicted adult height.
To measure the strength of the upper extremities, soccer players performed a handgrip (HG, dynamometry) test. They squeezed the dynamometer (Jamar, Chicago, IL, USA) with a maximum isometric effort for 5 s. Maximum strength was registered (kp). With the exception of the yo-yo IR1 test, each test was performed three times, and for statistical analysis, the best performance in each was used.
Hormones: testosterone and dehydroepiandrosterone Saliva collection was not allowed within 60 min after eating a meal. Each player collected their saliva sample by passive drool in a plastic tube. Samples were refrigerated within 30 min and freezed below −20°C within 4 h of collection. Both hormones were measured by immunoenzymatic determination using a specific kit, following the manufacturer’s instructions (Salimetrics, LLC, Suffolk, UK).
Velocity test and agility test In the sports hall, on an artificial turf, soccer players performed a 30-m flat sprint test and the agility test. The latter was similar to the velocity test, but in the agility tests, 10 cones were positioned aligned with a distance of 3 m between each consecutive cone. Footballers had to run dodging the cones on the left and right consecutively, or vice versa. In both the velocity and the agility tests, running times were measured using electronic timing lights (Polifemo, Microgate, Italy) positioned at 15 m and 30 m. The starting position of the players was standup, 2 m before the first timing light.
The yo-yo intermittent recovery (IR, level 1) test was performed by all participants. Players ran until they could not keep pace, and the covered distance was measured in meters. Jump test In order to measure the explosive power of the lower extremities, participants performed a countermovement jump (CMJ). The height (cm) of each jump was measured using an optical measurement system (Optojump, Microgate, Italy).
Statistical analysis Anthropometric measurements and data from the performance tests were analysed and compared among the groups of players. Data were displayed as mean ± standard deviation. To identify significant differences in all the variables among the players, a Student’s t-test or a Mann–Whitney U-test was performed. To measure the effect size, Cohen’s d was evaluated. Threshold values for effect size statistics were 0.2, 0.5 and 0.8 for small, medium and large effect sizes, respectively (Cohen, 1988). Stepwise discriminant analysis was also used to determine which variable(s) best predicted group membership (preselection or soccer camp) using Wilk’s lambda. Statistical analyses of the data were performed using the Statistical Package for the Social Sciences 17.0 software package (SPSS). The level of significance was set at P < 0.05. The technical error of measurement was less than 0.5% for height and weight and within the range of 2.4–4.5% for the skinfolds. The coefficients of variation for the performance tests used in this study ranged from 1.2% to 5.5%. Results As it can be observed in Table I, preselected OFs were older (P < 0.01) and leaner (P < 0.001) than
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Table I. Descriptive variables of the preselected soccer players (outfield players and goalkeepers) and players of the soccer camp (CampP). Preselection
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Outfield players CA (years) Training years Weight (kg) Height (cm) Sitting ht (cm) Leg length (cm) Ratio of LL/sitting height BMI ∑skinfolds (mm) Limb fat (mm) Body fat (mm) Maturity offset (years) APHV (years) Velocity 15 m (s) Velocity 30 m (s) Agility 15 m (s) Agility 30 m (s) Yo-yo IR (m) HG (kg) CMJ (cm)
9.83 3.43 32.96 139.16 73.38 65.77 89.67 16.96 48.86 31.67 17.18 −3.79 13.62 2.59 4.96 2.88 5.81 617.95 18.46 29.07
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.27** 1.21 4.28* 5.44 2.85 3.22 3.60 1.43* 15.50** 10.30** 5.76*** 0.32 0.25 0.10*** 0.21*** 0.12*** 0.28*** 233.24** 2.89 3.27**
Cohen’s d
Goalkeepers 9.91 2.66 38.13 143.44 75.08 68.36 91.06 18.50 63.28 38.64 24.64 −3.59 13.51 2.64 5.05 3.03 6.07 408.88 19.60 27.43
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.13*** 1.19† 3.72†† 5.35† 2.48 3.63† 4.11 1.08 14.72†† 9.28† 6.59††† 0.25 0.22 0.11*** 0.20*** 0.15***†† 0.35**† 79.44††† 2.27 1.87†
Soccer camp 9.63 3.00 35.45 140.27 73.84 66.18 89.89 17.89 66.16 40.81 25.35 −3.22 13.03 3.01 5.53 3.32 6.38 463.52 18.12 26.87
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.29 1.41 6.43 7.03 2.84 3.39 3.69 2.01 29.75 16.61 13.54 0.42 0.36 0.14 0.30 0.14 0.32 223.27 3.04 3.07
OFs − CampP
GKs − CampP
GKs − OFs
0.713 0.327 −0.455 −0.176 −0.262 −0.059 −0.606 −0.533 −0.730 −0.661 −0.785 −0.077 −0.029 −3.452 −2.201 −3.374 −1.895 0.676 0.114 0.693
1.245 −0.260 0.510 0.507 −0.161 0.623 0.299 0.378 −0.122 −0.161 −0.066 −1.193 −1.060 −2.938 −1.882 −1.998 −0.924 −0.326 0.551 0.220
−0.377 0.782 −1.301 −0.793 −0.636 −0.754 −0.359 −0.533 −0.954 −0.710 −1.205 0.696 0.476 −0.475 −0.438 −1.104 −0.820 1.199 −0.438 0.615
Notes: CA = chronological age; LL = leg length; BMI = body mass index (kg · m–2); ∑ skinfolds = sum of skinfolds; APHV = age at peak height velocity; yo-yo IR = yo-yo intermittent recovery test; HG = handgrip; CMJ = countermovement jump; OFs = outfield players; GKs = goalkeepers. *P < 0.05, **P < 0.01; ***P < 0.001, difference between preselected players and soccer camp. † P < 0.05, ††P < 0.01, †††P < 0.001, difference between goalkeepers and outfield players. Mean values, standard deviations and Cohen’s d are provided.
players of the soccer camp; however, training history, height and maturity were similar. Moreover, preselected OFs performed better in the velocity (P < 0.001), agility (P < 0.001), endurance (P < 0.01) and jump tests (P < 0.01). GKs were older than players of the soccer camp (P < 0.001). They were also slightly heavier and taller with a medium effect size (P > 0.05, Cohen’s d = 0.510 and d = 0.507, respectively) and had longer legs (P > 0.05, d = 0.623, medium effect size). GKs performed better in the 15-m and 30-m (both P < 0.001) velocity and the 15-m (P < 0.001) and 30-m (P < 0.01) agility tests than players of the soccer camp. Regarding the differences between the OFs and the GKs, the latter were heavier (P < 0.001), were taller (P < 0.05) and had longer legs (P < 0.05) (Table II). They also had been training for less years (P < 0.05). Besides, their sum of skinfolds (P < 0.01), limb (P < 0.05) and body fat (P < 0.001) and the fat percentage (P < 0.001) were greater (Tables I and II). The somatotype was different in both groups (Table II). GKs were more mesomorphic (P < 0.05), but they were endomorphic–ectomorphic balanced, whereas OFs had a larger ectomorphic component (P < 0.05) and a smaller endomorphy (P < 0.01). Also, predicted height was higher in the GKs compared to the OFs
(P < 0.05). On the other hand, OFs had better performance in the agility 15-m (P < 0.01) and 30m (P < 0.05) tests, the endurance test (P < 0.001) and the CMJ (P < 0.05, Table I). Regarding the final selection of OFs (Table III), the players that joined the team were older (P < 0.05) and had a lower predicted height (P < 0.05); however, they performed better in the 15-m (P < 0.01) and the 30-m (P < 0.001) agility tests and the yo-yo IR test (P < 0.05). Due to the small amount of GKs in each group, the differences were not statistically significant; however, the effect sizes were moderate to large in some of the variables (Table IV). In this line, finally selected GKs were older (d = 0.934), heavier (d = 0.744) and taller (d = −1.272) and had a larger body length (d = 0.904) but had particularly longer legs (d = 1.215), with a larger ratio of leg length/sitting height (d = 0.720). They also had a slightly larger sum of skinfolds (d = 0.507) and limb fat (d = 0.656). Ectomorphy was larger in the selected GKs (d = 0.887). Also, selected GKs had a higher predicted height (d = 1.173), and they were closer to their predicted height (d = 0.918). Furthermore, selected GKs for the team were closer to their maturity offset (d = 1.093) and had their APHV at a younger age (d = 0.670); also, their testosterone and DHEA were higher, but with a small effect size.
Selection process in a soccer club Table II. Body composition, somatotype and maturity in the preselected soccer players (outfield players and goalkeepers). Outfield players Fat (%) Bone (%) Muscle (%) Endomorphy Mesomorphy Ectomorphy Predicted height (cm) Percentage of predicted height Testosterone (pg · ml–1) DHEA (ng · ml–1)
9.84 20.04 46.00 1.83 6.03 3.26 179.36 77.50 19.21 29.30
± ± ± ± ± ± ± ± ± ±
1.25*** 1.43 1.21 0.61** 0.82* 0.87* 5.86* 1.45 9.88 14.45
Goalkeepers 11.30 19.38 45.21 2.45 6.74 2.64 183.88 78.34 21.00 32.55
± ± ± ± ± ± ± ± ± ±
1.35 1.13 1.41 0.64 0.72 0.70 4.16 1.22 9.35 10.66
Cohen’s d −1.222 0.512 0.601 −0.991 −0.920 0.785 −0.889 −0.626 −0.186 −0.255
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Notes: DHEA = dehydroepiandrosterone. *P < 0.05, **P < 0.01; ***P < 0.001, difference between outfield players and goalkeepers. Mean values, standard deviations and Cohen’s d are provided.
Table III. Descriptive variables in the group of preselected soccer outfield players: the finally selected players and the nonselected players. Selected CA (years) Training years Weight (kg) Height (cm) Sitting height (cm) Leg length (cm) BMI Sum skinfolds (mm) Limb fat (mm) Body fat (mm) Fat (%) Bone (%) Muscle (%) Endomorphy Mesomorphy Ectomorphy Predicted height (cm) Percentage of predicted height Testosterone (pg · ml–1) DHEA (ng · ml–1) Maturity offset (years) APHV (years) Velocity 15 m (s) Velocity 30 m (s) Agility 15 m (s) Agility 30 m (s) Yo-yo IR test (m) HG (kg) CMJ (cm)
9.95 3.65 33.35 138.49 118.35 60.39 17.32 50.15 32.28 17.81 9.94 19.91 46.03 1.91 6.33 2.97 176.58 78.02 19.09 3.67 −3.74 13.70 2.55 4.89 2.80 5.68 725.71 19.52 29.22
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.29* 1.02 4.38 5.48 2.88 3.40 1.17 12.87 8.77 4.92 1.09 1.12 1.02 0.54 0.61 0.61 6.25* 1.41 10.65 2.42 0.33 0.25 0.07 0.16 0.08** 0.27* 226.73* 3.37 3.33
Nonselected 9.78 3.55 32.78 139.46 118.39 61.07 16.80 48.27 31.39 16.87 9.80 20.10 45.99 1.80 5.89 3.39 180.36 77.31 19.26 3.28 −3.81 13.59 2.60 4.99 2.91 5.86 574.85 17.91 29.01
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.25 1.22 4.29 5.48 2.87 3.11 1.52 16.70 11.03 6.14 1.33 1.56 1.30 0.64 0.88 0.94 5.46 1.44 9.68 2.23 0.31 0.25 0.11 0.22 0.12 0.27 224.62 2.55 3.30
Cohen’s d 0.627 0.064 0.131 −0.177 −0.014 −0.208 0.383 0.126 0.089 0.180 0.118 −0.152 0.030 0.181 0.581 −0.530 −0.650 0.498 −0.016 0.164 0.209 0.410 −0.543 −0.519 −1.039 −0.667 0.668 0.518 0.063
Notes: CA = chronological age; BMI = body mass index (kg · m–2); sum skinfolds = tricipital + subscapular + abdominal + suprailiac + thigh + lower leg; limb fat = tricipital + thigh + lower leg; body fat = subscapular + abdominal + suprailiac; DHEA = dehydroepiandrosterone; APHV = age at peak height velocity; yo-yo IR test = yoyo intermittent recovery test; HG = handgrip (dynamometry); CMJ = countermovement jump; OF = outfield players. *P < 0.05, **P < 0.01: differences between selected and nonselected. Mean values, standard deviations and Cohen’s d are provided.
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S. M. Gil et al. Table IV. Descriptive variables in the group of preselected soccer goalkeepers: the finally selected and the nonselected goalkeepers.
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Selected CA (years) Training years Weight (kg) Height (cm) Sitting height (cm) Leg length (cm) Ratio of LL/sitting height BMI Sum skinfolds (mm) Limb fat (mm) Body fat (mm) Fat (%) Bone (%) Muscle (%) Endomorphy Mesomorphy Ectomorphy Predicted height (cm) Percentage of predicted height Testosterone (pg · ml–1) DHEA (ng · ml–1) Maturity offset (years) APHV (years) Velocity 15 m (s) Velocity 30 m (s) Agility 15 m (s) Agility 30 m (s) Yo-yo IR test (m) HG (kg) CMJ (cm)
9.98 2.75 39.82 147.17 76.30 70.87 92.83 18.34 68.10 42.40 25.70 11.64 19.49 44.76 2.68 6.53 2.99 186.31 78.96 22.90 36.23 −3.45 13.43 2.62 5.01 2.99 5.99 400.00 20.75 28.40
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.09 0.95 4.38 6.09 1.65 4.58 4.26 0.88 18.88 10.76 9.01 1.87 1.31 1.90 0.85 0.39 0.58 3.79 1.67 14.66 18.61 0.19 0.14 0.12 0.24 0.23 0.53 86.40 2.98 2.36
Nonselected 9.87 2.60 37.00 140.95 74.26 66.68 89.88 18.61 60.06 36.13 23.93 11.07 19.30 45.51 2.30 6.88 2.41 181.95 77.84 19.48 30.71 −3.69 13.57 2.66 5.08 3.07 6.13 416.00 18.83 26.66
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.14 1.47 3.09 3.27 2.73 1.67 3.92 1.26 12.05 8.17 5.29 1.00 1.11 1.07 0.49 0.88 0.72 3.64 0.43 2.69 5.57 0.24 0.26 0.11 0.19 0.06 0.16 82.94 1.47 1.06
Cohen’s d 0.934 0.120 0.744 −1.272 0.904 1.215 0.720 0.248 0.507 0.656 −0.239 0.380 0.151 −0.486 0.547 0.514 0.887 1.173 0.918 0.324 0.401 1.093 0.670 −0.320 −0.331 −0.441 0.367 0.188 0.817 0.951
Notes: CA = chronological age; LL = Leg length; sum skinfolds = tricipital + subscapular + abdominal + suprailiac + thigh + lower leg; limb fat = tricipital + thigh + lower leg; body fat = subscapular + abdominal + suprailiac; APHV = age at peak height velocity; yo-yo IR test = yo-yo intermittent recovery test; HG = handgrip (dynamometry); CMJ = countermovement jump; GK = goalkeepers. Mean values, standard deviations and Cohen’s d are provided.
Finally, selected GKs performed better (large effect size) in the HG test (d = 0.817) and the CMJ (d = 0.915).
Discussion The present study analysed the process of talent identification in a professional club. Preselected OFs were older and lighter and had lower BMI and amount of body fat compared to players of the soccer camp. Besides, they performed better in most performance tests (velocity, agility, endurance and jump tests). Moreover, discriminant analysis showed that the velocity and agility tests (both 15 m and 30 m) were the most important parameters to discriminate between the preselected players and players of the soccer camp. Both agility and speed have been cited as the most important features in soccer players, particularly in high-level players (Williams & Reilly, 2000).
Physical performance has been closely related to chronological age. Thus, it has been observed that older players display better results in the velocity, the agility and the jump tests and in the yo-yo IR level 1 than younger players born in the same year (Gil et al., 2013). On the other hand, it is well known that body fat is negatively related to the performance of soccer players (Figueiredo, Coelho E Silva, & Malina, 2011) and to the selection of players. Therefore, probably both an advanced chronological age and a leaner body make preselected players excel in their soccer performance while they are training and playing, and consequently they are identified as talented by the technical staff. In fact, age and adiposity were primary predictors of functional capacity in soccer players aged 11–12 years (Figueiredo et al., 2011). Nonetheless, there were fewer observed differences between the finally selected and the nonselected players. The statistically significant differences were found in the chronological age
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Selection process in a soccer club (selected players were older), lower predicted height and better agility and endurance. Again, chronological age is a determinant factor in the selection process, probably due to the fact that older players demonstrate better performance in various physical tests than their younger peers (Gil et al., 2013). Agility is an important characteristic for playing many sports, but it is particularly relevant to soccer. It has been mentioned as a discriminating factor in the selection process of players (Gil, Ruiz, et al., 2007; Huijgen, Elferink-Gemser, Post, & Visscher, 2009). Also, the finally selected players outperformed the nonselected players in the endurance test. In this line, a longer total distance covered by the retained players during matches was compared with that by the released players by a Soccer Academy (Goto, Morris, & Nevill, 2013), which implies that endurance is an important feature for high-level soccer players even from young ages. It is interesting to note that the results of the yo-yo IR level 1 test of the finally selected OFs were very similar to those observed in elite young soccer players from firstdivision soccer clubs from Belgium aged 9.7 years and born at the beginning of the year (739 ± 270 m) (Deprez, Vaeyens, Coutts, Lenoir, & Philippaerts, 2012), proving that the selected players of the present study are correctly classified as high-level players. There is less information in the literature about soccer GKs compared to the information about other positions. To our knowledge, this is the first time that the process of identification of talented GKs has been analysed. In the present study, we observed more differences between the preselected GKs and the OFs than in the players of the soccer camp. In this respect, preselected GKs were significantly older than participants of the soccer camp, and also the OFs. Moreover, the finally selected players’ age was higher than that of the nonselected GKs (large effect size). This is probably related to the fact that older players are taller and also display better performance (Gil et al., 2013), and both are important for goalkeeping. GKs had especially distinct anthropometric characteristics compared to the OFs. In this sense, they were taller, heavier and had a bigger amount of fat, particularly the finally selected ones. This anthropometric pattern has already been described in adult and adolescent soccer GKs (Ziv & Lidor, 2011). It is reasonable that these players should have a large body size (including long limbs and body) in order to stop the ball from entering the goal (Ziv & Lidor, 2011). It is also noticeable that predicted height was higher in the preselected GKs (184 cm) compared to the OFs (179 cm), but this measure was even higher
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in the finally selected GKs (186 cm). Should these selected players attain this potential height in the future, they would reach the height of high-level GKs (Ziv & Lidor, 2011), demonstrating the adequacy of the selection process of this particular club in this matter. OFs performed better in most of the performance tests compared to the GKs. However, it is remarkable that players of both positions outperformed the players of the soccer camp in velocity, implying a good performance in the running sprints in the preselected players, in the OKs and also in the GKs. In this sense, comparisons in the velocity between the GKs and OKs have shown inconclusive results (Aziz, Mukherjee, Chia, & Teh, 2008; Gil, Gil, et al., 2007; Ziv & Lidor, 2011). However, GKs showed a worse performance in the agility test than the OFs, similar to the results by Taşkin (2008) and Gil, Gil, et al. (2007). Agility is a characteristic a GK must have; however, perhaps the agility test of the present study was not as accurate to measure GKs’ specific agility. It would be very interesting if other kinds of tests to measure the specific agility of the GKs were designed. On the other hand, it has been widely described that GKs have a low endurance capacity (Gil, Gil, et al., 2007; Ziv & Lidor, 2011). In the present study, GKs displayed the worst results in the yo-yo IR1 test. A large aerobic capacity is probably not essential, but a moderate capacity is beneficial (Ziv & Lidor, 2011), and this should be kept in mind by the coaches when designing training sessions. It has been observed that GKs exhibit higher jumps (Sporis, Jukic, Ostojic, & Milanovic, 2009), similar to the rest of the players (Arnason et al., 2004). In the present study, OFs showed better results in the CMJ than the GKs. However, the finally selected players had better explosive power of the legs than the nonselected ones (28.4 cm vs 26.66 cm, d = 0.951) comparable to the results of Rebelo et al. (2013) in which elite players displayed higher jumps than nonelite ones. Good vertical jump skills are important for GKs, as they are often required to leap vertically to catch or deflect a ball (Ziv & Lidor, 2011). Finally, selected players exhibited higher strength in the arms in the HG test (d = 0.817) compared to nonselected GKs and also the rest of the participants, and they were also the tallest. The literature provides evidence that in prepubertal boys, height is a good predictor of HG strength (Jürimäe, Hurbo, & Jürimäe, 2009). Last, the earlier maturity offset and age at the peak height velocity and higher percentage of the predicted height observed in the finally selected GKs (large effect size) together with the higher levels of testosterone and dehydroepiandrosterone (small
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effect size) suggest a trend for an advanced maturity in this group of players. We could not find any studies about the maturational status and GKs, but it is reasonable that more mature players are selected due to the fact that it has been demonstrated that they are taller, are stronger and have better performance particularly in strength measurements (Coelho E Silva, Moreira Carvalho, et al., 2010). One of the limitations of the present study was that some measurements, that is, a complete anthropometry, were not undertaken in the players of the soccer camp, and their somatotype could not be calculated. The reason is that the participants attended the soccer camp for a short period of time (1 week), and the procedures could not take up a lot of time for their activities. Consequently, it was decided to undertake the most relevant measurements in this group of players. Also, it would have been interesting to assess soccer-specific skills used by the players in the tests such as Loughborough Soccer Passing Test and the Loughborough Soccer Shooting Test as suggested by Ali (2011) in all the participants. Nonetheless, the selection of the players was made based on their playing performance on the soccer field, and soccer skills tests are indeed designed to evaluate this performance. Another limitation is that there were no specific tests for the GKs. It would be interesting that in future investigations, specific tests for GKs are utilised in order to differentiate finally selected GKs from nonselected ones (Knoop, Fernandez-Fernandez, & Ferrauti, 2013) to describe talent identification programmes for this particular positional role. It is important to underline that the technical staff did not know the results of our study when they made the selection of the players. This selection was done based on the coaches’ and observers’ expertise in this matter and through the observation and analysis of the physical appearance and technical and tactical skills of the players while they trained and played matches. By this means, the preselected OFs were older, leaner, fast and agile and with a good endurance and explosive power, whereas in finally selected players the distinctive parameters were age, agility and endurance. Besides, GKs had a specific anthropometric and performance pattern. They had larger body sizes and more strength of the upper extremities and legs’ explosive power, resembling the characteristics of the adult GKs. Undoubtedly, selected OFs and GKs had appropriate anthropometric and fitness features to excel in performance; in fact, they were the best performers. Yet, it will be very interesting to follow their achievements in the future. On the other hand, to our knowledge, the present study for the first time analysed the process of talent identification within a
professional club. It would be very interesting that similar studies in clubs of different levels and countries are designed to confirm these results.
Funding This study was partially supported by the Basque Government [grant number IT700-13].
References Ali, A. (2011). Measuring soccer skill performance: A review. Scandinavian Journal of Medicine and Science in Sports, 21, 170–183. Arnason, A., Sigurdsson, S. B., Gudmundsson, A., Holme, I., Engebretsen, L., & Bahr, R. (2004). Physical fitness, injuries, and team performance in soccer. Medicine and Science in Sports and Exercise, 36, 278–285. Aziz, A. R., Mukherjee, S., Chia, M. Y., & Teh, K. C. (2008). Validity of the running repeated sprint ability test among playing positions and level of competitiveness in trained soccer players. International Journal of Sports Medicine, 29, 833–838. Coelho E Silva, M. J., Figueiredo, A. J., Simões, F., Seabra, A., Natal, A., Vaeyens, R., … Malina, R. M. (2010). Discrimination of U-14 soccer players by level and position. International Journal of Sports Medicine, 31, 790–796. Coelho E Silva, M. J., Moreira Carvalho, H., Gonçalves, C. E., Figueiredo, A. J., Elferink-Gemser, M. T., Philippaerts, R. M., & Malina, R. M. (2010). Growth, maturation, functional capacities and sport-specific skills in 12-13 year-old-basketball players. Journal of Sports Medicine and Physical Fitness, 50, 174–181. Cohen, J. (1988). Statistical power analysis for the behavioural sciences. Hillsdale, NJ: Lawrence Erlbaum Associates. Deprez, D., Vaeyens, R., Coutts, A. J., Lenoir, M., & Philippaerts, R. (2012). Relative age effect and Yo-Yo IR1 in youth soccer. International Journal of Sports Medicine, 33, 987–993. Faulkner, J. A. (1968). Physiology of swimming and diving. Human exercise physiology. Baltimore: Academic Press. Figueiredo, A. J., Coelho E Silva, M. J., & Malina, R. M. (2011). Predictors of functional capacity and skill in youth soccer players. Scandinavian Journal of Medicine and Science in Sports, 21, 446–454. Figueiredo, A. J., Gonçalves, C. E., Coelho E Silva, M. J., & Malina, R. M. (2009). Characteristics of youth soccer players who drop out, persist or move up. Journal of Sports Sciences, 27, 883–891. Gil, S., Ruiz, F., Irazusta, A., Gil, J., & Irazusta, J. (2007). Selection of young soccer players in terms of anthropometric and physiological factors. Journal of Sports Medicine and Physical Fitness, 47, 25–32. Gil, S. M., Badiola, A., Bidaurrazaga-Letona, I., Zabala-Lili, J., Gravina, L., Santos-Concejero, J., & Granados, C. (2013). Relationship between the relative age effect and anthropometry, maturity and performance in young soccer players. Journal of Sports Sciences, 32, 479–486. Gil, S. M., Gil, J., Ruiz, F., Irazusta, A., & Irazusta, J. (2007). Physiological and anthropometric characteristics of young soccer players according to their playing position: Relevance for the selection process. Journal of Strength and Conditioning Research, 21, 438–445. Goto, H., Morris, J. G., & Nevill, M. E. (2013). Match analysis of U9 and U10 English premier league academy soccer players using a global positioning system: Relevance for talent identification and development. Journal of Strength and Conditioning
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Selection process in a soccer club Research. Advance online publication. doi:10.1519/ JSC.0b013e3182a0d751 Heath, B. H., & Carter, J. E. L. (1967). A modified somatotype method. American Journal of Physical Anthropology, 27, 57–74. Huijgen, B. C., Elferink-Gemser, M. T., Post, W. J., & Visscher, C. (2009). Soccer skill development in professionals. International Journal of Sports Medicine, 30, 585–591. Jürimäe, T., Hurbo, T., & Jürimäe, J. (2009). Relationship of handgrip strength with anthropometric and body composition variables in prepubertal children. HOMO – Journal of Comparative Human Biology, 60, 225–238. Khamis, H. J., & Roche, A. F. (1994). Predicting adult stature without using skeletal age: The Khamis-Roche method. Pediatrics, 94, 504–507. Knoop, M., Fernandez-Fernandez, J., & Ferrauti, A. (2013). Evaluation of a specific reaction and action speed test for the soccer goalkeeper. Journal of Strength and Conditioning Research, 27, 2141–2148. Le Gall, F., Carling, C., Williams, M., & Reilly, T. (2010). Anthropometric and fitness characteristics of international, professional and amateur male graduate soccer players from an elite youth academy. Journal of Science and Medicine in Sport, 13, 90–95. Malina, R. M., Coelho E Silva, M. J., Figueiredo, A. J., Carling, C., & Beunen, G. P. (2012). Interrelationships among invasive and non-invasive indicators of biological maturation in adolescent male soccer players. Journal of Sports Sciences, 30, 1705– 1717.
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Mirwald, R. L., Baxter-Jones, A. D., Bailey, D. A., & Beunen, G. P. (2002). An assessment of maturity from anthropometric measurements. Medicine and Science in Sports and Exercise, 34, 689–694. Rebelo, A., Brito, J., Maia, J., Coelho-E-Silva, M. J., Figueiredo, A. J., Bangsbo, J., & Seabra, A. (2013). Anthropometric characteristics, physical fitness and technical performance of under19 soccer players by competitive level and field position. International Journal of Sports Medicine, 34, 312–317. Rocha, M. S. (1975). Peso osseo do Brasileiro de ambos sexos de 17 a 25 años. Arquivo De Anatomia E Antropologia, 1, 445–451. Sporis, G., Jukic, I., Ostojic, S. M., & Milanovic, D. (2009). Fitness profiling in soccer: Physical and physiologic characteristics of elite players. Journal of Strength and Conditioning Research, 23, 1947–1953. Taşkin, H. (2008). Evaluating sprinting ability, density of acceleration, and speed dribbling ability of professional soccer players with respect to their positions. Journal of Strength and Conditioning Research, 22, 1481–1486. Vaeyens, R., Malina, R. M., Janssens, M., Van Renterghem, B., Bourgois, J., Vrijens, J., & Philippaerts, R. M. (2006). A multidisciplinary selection model for youth soccer: The Ghent Youth Soccer Project. British Journal of Sports Medicine, 40, 928–934. Williams, A. M., & Reilly, T. (2000). Talent identification and development in soccer. Journal of Sports Sciences, 18, 657–667. Ziv, G., & Lidor, R. (2011). Physical characteristics, physiological attributes, and on-field performances of soccer goalkeepers. International Journal of Sports Physiology and Performance, 6, 509–524.
Journal of Sports Sciences Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/rjsp20
Talent identification and selection process of outfield players and goalkeepers in a professional soccer club a
a
a
a
Susana María Gil , Jon Zabala-Lili , Iraia Bidaurrazaga-Letona , Badiola Aduna , Jose b
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Antonio Lekue , Jordan Santos-Concejero & Cristina Granados
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Department of Physical Education and Sport, Faculty of Physical Activity and Sport, University of the Basque Country (UPV/EHU), Vitoria-Gasteiz, Spain b
Medical Services, Athletic Club, Bilbao, Spain
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UCT/MRC Research Unit for Exercise Science and Sports Medicine, University of Cape Town, Cape Town, South Africa Published online: 28 Nov 2014.
Click for updates To cite this article: Susana María Gil, Jon Zabala-Lili, Iraia Bidaurrazaga-Letona, Badiola Aduna, Jose Antonio Lekue, Jordan Santos-Concejero & Cristina Granados (2014) Talent identification and selection process of outfield players and goalkeepers in a professional soccer club, Journal of Sports Sciences, 32:20, 1931-1939, DOI: 10.1080/02640414.2014.964290 To link to this article: http://dx.doi.org/10.1080/02640414.2014.964290
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Journal of Sports Sciences, 2014 Vol. 32, No. 20, 1931–1939, http://dx.doi.org/10.1080/02640414.2014.964290
Talent identification and selection process of outfield players and goalkeepers in a professional soccer club
SUSANA MARÍA GIL1, JON ZABALA-LILI1, IRAIA BIDAURRAZAGA-LETONA1, BADIOLA ADUNA1, JOSE ANTONIO LEKUE2, JORDAN SANTOS-CONCEJERO3 & CRISTINA GRANADOS1 1
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Department of Physical Education and Sport, Faculty of Physical Activity and Sport, University of the Basque Country (UPV/EHU), Vitoria-Gasteiz, Spain, 2Medical Services, Athletic Club, Bilbao, Spain and 3UCT/MRC Research Unit for Exercise Science and Sports Medicine, University of Cape Town, Cape Town, South Africa (Accepted 3 September 2014)
Abstract The aim of this study was to analyse the talent identification process of a professional soccer club. A preselection of players (n = 64) aged 9–10 years and a final selection (n = 21) were performed by the technical staff through the observation during training sessions and matches. Also, 34 age-matched players of an open soccer camp (CampP) acted as controls. All participants underwent anthropometric, maturity and performance measurements. Preselected outfield players (OFs) were older and leaner than CampP (P < 0.05). Besides, they performed better in velocity, agility, endurance and jump tests (P < 0.05). A discriminant analysis showed that velocity and agility were the most important parameters. Finally, selected OFs were older and displayed better agility and endurance compared to the nonselected OFs (P < 0.05). Goalkeepers (GKs) were taller and heavier and had more body fat than OFs; also, they performed worse in the physical tests (P < 0.05). Finally, selected GKs were older and taller, had a higher predicted height and advanced maturity and performed better in the handgrip (dynamometry) and jump tests (P < 0.05). Thus, the technical staff selected OFs with a particular anthropometry and best performance, particularly agility and endurance, while GKs had a different profile. Moreover, chronological age had an important role in the whole selection process. Keywords: physical test, velocity, agility, power, strength, body size, RAE
Introduction Scientists have described four stages in the process of searching for excellence in sport (Williams & Reilly, 2000): talent detection, identification, selection and development. Thus, the technical staff of professional soccer clubs develop different kinds of programmes in order to discover those players who could benefit from specific training schedules and would potentially succeed in the club. Several attempts have been made to identify the characteristics of talented young soccer players. In this respect, some cross-sectional studies have compared groups of players of different levels such as elite versus nonelite or subelite players. It has been observed that elite players have less body fat and are taller than subelite players (Williams & Reilly, 2000). Also, many authors agree that elite players display a better performance in the physical tests (Vaeyens
et al., 2006; Williams & Reilly, 2000) and have several technical skills (Vaeyens et al., 2006). Moreover, selected players displayed better performance than nonselected in an U-14 selection team (Coelho E Silva, Figueiredo, et al., 2010). Nonetheless, they were also more experienced and mature, which may have accounted for the differences. One of the limitations of these cross-sectional studies is that usually the groups that are compared do not train together, and they may have different training histories; therefore, many of the differences may come from the training status rather than from the actual talent. Therefore, longitudinal studies overcome this problem by analysing the outcome of the athletes after a shorter or longer period of time. By this means, differences in body size and functional capacity were observed among players who discontinued participation and continued or moved to a
Correspondence: Susana María Gil, Department of Physiology, Faculty of Medicine and Dentistry, University of the Basque Country (UPV/EHU), Barrio Sarriena s/n, Leioa 48940, Spain. E-mail: [email protected] © 2014 Taylor & Francis
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higher level (Figueiredo, Gonçalves, Coelho E Silva, & Malina, 2009) and also between selected and nonselected players of a soccer club (Gil, Ruiz, Irazusta, Gil, & Irazusta, 2007; Gil, Gil, Ruiz, Irazusta, & Irazusta, 2007). Besides, height, body mass, maximal anaerobic power and maturity status varied among players who achieved amateur, professional or international level (Le Gall, Carling, Williams, & Reilly, 2010). It is noteworthy that the aforementioned studies either cross-sectionally compared teams of different levels or longitudinally followed the success of players during a certain period of time. Still, to our knowledge, there are no investigations about the actual talent identification process, defined as the procedure of recognising the most talented players (currently playing soccer) with the potential to become elite players and being incorporated into a club, in the context of professional soccer. Thus, the general objective of the present study was to analyse the process of talent identification of young soccer players in a professional soccer club. With this purpose, we analysed the characteristics of young players going through the different phases of the talent identification process of the club, in order to ascertain what the most relevant characteristics are. Also, our aim was to compare the anthropometric and performance characteristics of outfield players (OFs) and goalkeepers (GKs) involved in the above-mentioned selection process. Methods Each year, the technical staff of this particular club select soccer players to enter the youngest team in the club (players aged 9–10). The selection process goes through two phases. First, during the first months of the season, a number of players are selected from all the soccer players around the county belonging to around 300 teams (first selection). Second, between this first selection and the end of the season, players continue training in their original clubs, but attend one training session per week within the club’s facilities under the supervision of the club’s coaches. By the beginning of the following season, the technical staff make a small selection of players to definitely join the club (final selection). This selection of players is performed through the observation of training sessions and matches. This professional soccer club has a particular philosophy of employing only locally born players or players born elsewhere but trained from childhood/adolescence in the club. Thus, identifying players with the potential to become high-level professionals is a major issue for the technical staff. In the present study, these phases followed the same protocol. We undertook anthropometry,
performance and maturity measurements in the players first selected and also players of an open soccer camp (control participants), whereas statistical analysis was performed once the final selection was made. Thus, comparisons were made between players of the first selection (54 OFs and 10 GKs), players of the soccer camp (n = 34) and players finally selected (17 OFs and 4 GKs) versus the nonselected. Besides, differences between OFs and GKs were also analysed. The players in the open soccer camp also played soccer in clubs around the county but had not been preselected for this particular club and therefore would be representative of the soccer players of the county. All participants trained twice a week (1- to 1.5-h training/day) and played a match during the weekend. They all played in the same county league. Written informed consent was received from all players and parents after verbal and written explanation of the experimental design and potential risks of the study. The ethics committee of the University of the Basque Country for Research on Human Subjects approved this study. The measurements were performed according to the ethical standards of the Helsinki Declaration. Measurements were taken in the same sports hall and under the same external conditions: for the anthropometric measurements, players only wore shorts and for the performance tests they wore shorts, T-shirt and soccer boots, except in the jump test, during which they wore running shoes. The following tests were carried out on all players at the same time of the day and in the same order. Anthropometric measurements Height, sitting height (Añó Sayol, Barcelona, Spain) and body weight (Seca, Bonn, Germany) were measured. Leg length and the ratio between leg length and sitting height were calculated. The body mass index (BMI) was calculated from height and body weight (kg · m–2). Skinfold thicknesses (measured in mm) were measured at six sites (triceps, subscapular, abdominal, suprailiac, thigh and calf) using a skinfold calliper (Harpenden, England), and the sum of these six measurements was calculated (sum of skinfolds). The amount of fat in the extremities (limb fat) was calculated as the sum of the skinfolds of the extremities: triceps + thigh + lower leg. The amount of fat in the trunk (body fat) was calculated from the sum of the subscapular, abdominal and suprailiac skinfolds. The circumferences of the upper arm, thigh and lower leg (in cm) were measured using a tape measuring (Lufkin, Germany). Four diameters (in cm) were obtained using a calliper (Harpenden, England): biepicondylar of the humerus (elbow),
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Selection process in a soccer club
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bistyloid of the wrist, biepicondylar of the femur (knee) and bimalleolar of the ankle. Body composition (fat, bone and muscle percentages) (Faulkner, 1968; Rocha, 1975) and somatotype (endomorphy, mesomorphy and ectomorphy) were calculated (Heath & Carter, 1967). Due to the time constrictions, complete body composition and somatotype were not calculated for the players attending the soccer camp. All the measurements were taken following the guidelines outlined by the ISAK (International Society for the Advancement of Kinanthropometry) by the same researcher.
Yo-yo intermittent recovery (Yo-yo IR1) test
Maturity
Handgrip (dynamometry) test
The time before peak height velocity, labelled maturity offset, was predicted using a formula (Malina, Coelho E Silva, Figueiredo, Carling, & Beunen, 2012; Mirwald, Baxter-Jones, Bailey, & Beunen, 2002). Predicted age at peak height velocity (APHV) in years was estimated as chronological age minus maturity offset (Malina et al., 2012). Adult height was predicted using the Khamis– Roche method (Khamis & Roche, 1994), and the height at the time of the measurements was calculated as the percentage of the predicted adult height.
To measure the strength of the upper extremities, soccer players performed a handgrip (HG, dynamometry) test. They squeezed the dynamometer (Jamar, Chicago, IL, USA) with a maximum isometric effort for 5 s. Maximum strength was registered (kp). With the exception of the yo-yo IR1 test, each test was performed three times, and for statistical analysis, the best performance in each was used.
Hormones: testosterone and dehydroepiandrosterone Saliva collection was not allowed within 60 min after eating a meal. Each player collected their saliva sample by passive drool in a plastic tube. Samples were refrigerated within 30 min and freezed below −20°C within 4 h of collection. Both hormones were measured by immunoenzymatic determination using a specific kit, following the manufacturer’s instructions (Salimetrics, LLC, Suffolk, UK).
Velocity test and agility test In the sports hall, on an artificial turf, soccer players performed a 30-m flat sprint test and the agility test. The latter was similar to the velocity test, but in the agility tests, 10 cones were positioned aligned with a distance of 3 m between each consecutive cone. Footballers had to run dodging the cones on the left and right consecutively, or vice versa. In both the velocity and the agility tests, running times were measured using electronic timing lights (Polifemo, Microgate, Italy) positioned at 15 m and 30 m. The starting position of the players was standup, 2 m before the first timing light.
The yo-yo intermittent recovery (IR, level 1) test was performed by all participants. Players ran until they could not keep pace, and the covered distance was measured in meters. Jump test In order to measure the explosive power of the lower extremities, participants performed a countermovement jump (CMJ). The height (cm) of each jump was measured using an optical measurement system (Optojump, Microgate, Italy).
Statistical analysis Anthropometric measurements and data from the performance tests were analysed and compared among the groups of players. Data were displayed as mean ± standard deviation. To identify significant differences in all the variables among the players, a Student’s t-test or a Mann–Whitney U-test was performed. To measure the effect size, Cohen’s d was evaluated. Threshold values for effect size statistics were 0.2, 0.5 and 0.8 for small, medium and large effect sizes, respectively (Cohen, 1988). Stepwise discriminant analysis was also used to determine which variable(s) best predicted group membership (preselection or soccer camp) using Wilk’s lambda. Statistical analyses of the data were performed using the Statistical Package for the Social Sciences 17.0 software package (SPSS). The level of significance was set at P < 0.05. The technical error of measurement was less than 0.5% for height and weight and within the range of 2.4–4.5% for the skinfolds. The coefficients of variation for the performance tests used in this study ranged from 1.2% to 5.5%. Results As it can be observed in Table I, preselected OFs were older (P < 0.01) and leaner (P < 0.001) than
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Table I. Descriptive variables of the preselected soccer players (outfield players and goalkeepers) and players of the soccer camp (CampP). Preselection
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Outfield players CA (years) Training years Weight (kg) Height (cm) Sitting ht (cm) Leg length (cm) Ratio of LL/sitting height BMI ∑skinfolds (mm) Limb fat (mm) Body fat (mm) Maturity offset (years) APHV (years) Velocity 15 m (s) Velocity 30 m (s) Agility 15 m (s) Agility 30 m (s) Yo-yo IR (m) HG (kg) CMJ (cm)
9.83 3.43 32.96 139.16 73.38 65.77 89.67 16.96 48.86 31.67 17.18 −3.79 13.62 2.59 4.96 2.88 5.81 617.95 18.46 29.07
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.27** 1.21 4.28* 5.44 2.85 3.22 3.60 1.43* 15.50** 10.30** 5.76*** 0.32 0.25 0.10*** 0.21*** 0.12*** 0.28*** 233.24** 2.89 3.27**
Cohen’s d
Goalkeepers 9.91 2.66 38.13 143.44 75.08 68.36 91.06 18.50 63.28 38.64 24.64 −3.59 13.51 2.64 5.05 3.03 6.07 408.88 19.60 27.43
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.13*** 1.19† 3.72†† 5.35† 2.48 3.63† 4.11 1.08 14.72†† 9.28† 6.59††† 0.25 0.22 0.11*** 0.20*** 0.15***†† 0.35**† 79.44††† 2.27 1.87†
Soccer camp 9.63 3.00 35.45 140.27 73.84 66.18 89.89 17.89 66.16 40.81 25.35 −3.22 13.03 3.01 5.53 3.32 6.38 463.52 18.12 26.87
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.29 1.41 6.43 7.03 2.84 3.39 3.69 2.01 29.75 16.61 13.54 0.42 0.36 0.14 0.30 0.14 0.32 223.27 3.04 3.07
OFs − CampP
GKs − CampP
GKs − OFs
0.713 0.327 −0.455 −0.176 −0.262 −0.059 −0.606 −0.533 −0.730 −0.661 −0.785 −0.077 −0.029 −3.452 −2.201 −3.374 −1.895 0.676 0.114 0.693
1.245 −0.260 0.510 0.507 −0.161 0.623 0.299 0.378 −0.122 −0.161 −0.066 −1.193 −1.060 −2.938 −1.882 −1.998 −0.924 −0.326 0.551 0.220
−0.377 0.782 −1.301 −0.793 −0.636 −0.754 −0.359 −0.533 −0.954 −0.710 −1.205 0.696 0.476 −0.475 −0.438 −1.104 −0.820 1.199 −0.438 0.615
Notes: CA = chronological age; LL = leg length; BMI = body mass index (kg · m–2); ∑ skinfolds = sum of skinfolds; APHV = age at peak height velocity; yo-yo IR = yo-yo intermittent recovery test; HG = handgrip; CMJ = countermovement jump; OFs = outfield players; GKs = goalkeepers. *P < 0.05, **P < 0.01; ***P < 0.001, difference between preselected players and soccer camp. † P < 0.05, ††P < 0.01, †††P < 0.001, difference between goalkeepers and outfield players. Mean values, standard deviations and Cohen’s d are provided.
players of the soccer camp; however, training history, height and maturity were similar. Moreover, preselected OFs performed better in the velocity (P < 0.001), agility (P < 0.001), endurance (P < 0.01) and jump tests (P < 0.01). GKs were older than players of the soccer camp (P < 0.001). They were also slightly heavier and taller with a medium effect size (P > 0.05, Cohen’s d = 0.510 and d = 0.507, respectively) and had longer legs (P > 0.05, d = 0.623, medium effect size). GKs performed better in the 15-m and 30-m (both P < 0.001) velocity and the 15-m (P < 0.001) and 30-m (P < 0.01) agility tests than players of the soccer camp. Regarding the differences between the OFs and the GKs, the latter were heavier (P < 0.001), were taller (P < 0.05) and had longer legs (P < 0.05) (Table II). They also had been training for less years (P < 0.05). Besides, their sum of skinfolds (P < 0.01), limb (P < 0.05) and body fat (P < 0.001) and the fat percentage (P < 0.001) were greater (Tables I and II). The somatotype was different in both groups (Table II). GKs were more mesomorphic (P < 0.05), but they were endomorphic–ectomorphic balanced, whereas OFs had a larger ectomorphic component (P < 0.05) and a smaller endomorphy (P < 0.01). Also, predicted height was higher in the GKs compared to the OFs
(P < 0.05). On the other hand, OFs had better performance in the agility 15-m (P < 0.01) and 30m (P < 0.05) tests, the endurance test (P < 0.001) and the CMJ (P < 0.05, Table I). Regarding the final selection of OFs (Table III), the players that joined the team were older (P < 0.05) and had a lower predicted height (P < 0.05); however, they performed better in the 15-m (P < 0.01) and the 30-m (P < 0.001) agility tests and the yo-yo IR test (P < 0.05). Due to the small amount of GKs in each group, the differences were not statistically significant; however, the effect sizes were moderate to large in some of the variables (Table IV). In this line, finally selected GKs were older (d = 0.934), heavier (d = 0.744) and taller (d = −1.272) and had a larger body length (d = 0.904) but had particularly longer legs (d = 1.215), with a larger ratio of leg length/sitting height (d = 0.720). They also had a slightly larger sum of skinfolds (d = 0.507) and limb fat (d = 0.656). Ectomorphy was larger in the selected GKs (d = 0.887). Also, selected GKs had a higher predicted height (d = 1.173), and they were closer to their predicted height (d = 0.918). Furthermore, selected GKs for the team were closer to their maturity offset (d = 1.093) and had their APHV at a younger age (d = 0.670); also, their testosterone and DHEA were higher, but with a small effect size.
Selection process in a soccer club Table II. Body composition, somatotype and maturity in the preselected soccer players (outfield players and goalkeepers). Outfield players Fat (%) Bone (%) Muscle (%) Endomorphy Mesomorphy Ectomorphy Predicted height (cm) Percentage of predicted height Testosterone (pg · ml–1) DHEA (ng · ml–1)
9.84 20.04 46.00 1.83 6.03 3.26 179.36 77.50 19.21 29.30
± ± ± ± ± ± ± ± ± ±
1.25*** 1.43 1.21 0.61** 0.82* 0.87* 5.86* 1.45 9.88 14.45
Goalkeepers 11.30 19.38 45.21 2.45 6.74 2.64 183.88 78.34 21.00 32.55
± ± ± ± ± ± ± ± ± ±
1.35 1.13 1.41 0.64 0.72 0.70 4.16 1.22 9.35 10.66
Cohen’s d −1.222 0.512 0.601 −0.991 −0.920 0.785 −0.889 −0.626 −0.186 −0.255
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Notes: DHEA = dehydroepiandrosterone. *P < 0.05, **P < 0.01; ***P < 0.001, difference between outfield players and goalkeepers. Mean values, standard deviations and Cohen’s d are provided.
Table III. Descriptive variables in the group of preselected soccer outfield players: the finally selected players and the nonselected players. Selected CA (years) Training years Weight (kg) Height (cm) Sitting height (cm) Leg length (cm) BMI Sum skinfolds (mm) Limb fat (mm) Body fat (mm) Fat (%) Bone (%) Muscle (%) Endomorphy Mesomorphy Ectomorphy Predicted height (cm) Percentage of predicted height Testosterone (pg · ml–1) DHEA (ng · ml–1) Maturity offset (years) APHV (years) Velocity 15 m (s) Velocity 30 m (s) Agility 15 m (s) Agility 30 m (s) Yo-yo IR test (m) HG (kg) CMJ (cm)
9.95 3.65 33.35 138.49 118.35 60.39 17.32 50.15 32.28 17.81 9.94 19.91 46.03 1.91 6.33 2.97 176.58 78.02 19.09 3.67 −3.74 13.70 2.55 4.89 2.80 5.68 725.71 19.52 29.22
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.29* 1.02 4.38 5.48 2.88 3.40 1.17 12.87 8.77 4.92 1.09 1.12 1.02 0.54 0.61 0.61 6.25* 1.41 10.65 2.42 0.33 0.25 0.07 0.16 0.08** 0.27* 226.73* 3.37 3.33
Nonselected 9.78 3.55 32.78 139.46 118.39 61.07 16.80 48.27 31.39 16.87 9.80 20.10 45.99 1.80 5.89 3.39 180.36 77.31 19.26 3.28 −3.81 13.59 2.60 4.99 2.91 5.86 574.85 17.91 29.01
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.25 1.22 4.29 5.48 2.87 3.11 1.52 16.70 11.03 6.14 1.33 1.56 1.30 0.64 0.88 0.94 5.46 1.44 9.68 2.23 0.31 0.25 0.11 0.22 0.12 0.27 224.62 2.55 3.30
Cohen’s d 0.627 0.064 0.131 −0.177 −0.014 −0.208 0.383 0.126 0.089 0.180 0.118 −0.152 0.030 0.181 0.581 −0.530 −0.650 0.498 −0.016 0.164 0.209 0.410 −0.543 −0.519 −1.039 −0.667 0.668 0.518 0.063
Notes: CA = chronological age; BMI = body mass index (kg · m–2); sum skinfolds = tricipital + subscapular + abdominal + suprailiac + thigh + lower leg; limb fat = tricipital + thigh + lower leg; body fat = subscapular + abdominal + suprailiac; DHEA = dehydroepiandrosterone; APHV = age at peak height velocity; yo-yo IR test = yoyo intermittent recovery test; HG = handgrip (dynamometry); CMJ = countermovement jump; OF = outfield players. *P < 0.05, **P < 0.01: differences between selected and nonselected. Mean values, standard deviations and Cohen’s d are provided.
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S. M. Gil et al. Table IV. Descriptive variables in the group of preselected soccer goalkeepers: the finally selected and the nonselected goalkeepers.
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Selected CA (years) Training years Weight (kg) Height (cm) Sitting height (cm) Leg length (cm) Ratio of LL/sitting height BMI Sum skinfolds (mm) Limb fat (mm) Body fat (mm) Fat (%) Bone (%) Muscle (%) Endomorphy Mesomorphy Ectomorphy Predicted height (cm) Percentage of predicted height Testosterone (pg · ml–1) DHEA (ng · ml–1) Maturity offset (years) APHV (years) Velocity 15 m (s) Velocity 30 m (s) Agility 15 m (s) Agility 30 m (s) Yo-yo IR test (m) HG (kg) CMJ (cm)
9.98 2.75 39.82 147.17 76.30 70.87 92.83 18.34 68.10 42.40 25.70 11.64 19.49 44.76 2.68 6.53 2.99 186.31 78.96 22.90 36.23 −3.45 13.43 2.62 5.01 2.99 5.99 400.00 20.75 28.40
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.09 0.95 4.38 6.09 1.65 4.58 4.26 0.88 18.88 10.76 9.01 1.87 1.31 1.90 0.85 0.39 0.58 3.79 1.67 14.66 18.61 0.19 0.14 0.12 0.24 0.23 0.53 86.40 2.98 2.36
Nonselected 9.87 2.60 37.00 140.95 74.26 66.68 89.88 18.61 60.06 36.13 23.93 11.07 19.30 45.51 2.30 6.88 2.41 181.95 77.84 19.48 30.71 −3.69 13.57 2.66 5.08 3.07 6.13 416.00 18.83 26.66
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.14 1.47 3.09 3.27 2.73 1.67 3.92 1.26 12.05 8.17 5.29 1.00 1.11 1.07 0.49 0.88 0.72 3.64 0.43 2.69 5.57 0.24 0.26 0.11 0.19 0.06 0.16 82.94 1.47 1.06
Cohen’s d 0.934 0.120 0.744 −1.272 0.904 1.215 0.720 0.248 0.507 0.656 −0.239 0.380 0.151 −0.486 0.547 0.514 0.887 1.173 0.918 0.324 0.401 1.093 0.670 −0.320 −0.331 −0.441 0.367 0.188 0.817 0.951
Notes: CA = chronological age; LL = Leg length; sum skinfolds = tricipital + subscapular + abdominal + suprailiac + thigh + lower leg; limb fat = tricipital + thigh + lower leg; body fat = subscapular + abdominal + suprailiac; APHV = age at peak height velocity; yo-yo IR test = yo-yo intermittent recovery test; HG = handgrip (dynamometry); CMJ = countermovement jump; GK = goalkeepers. Mean values, standard deviations and Cohen’s d are provided.
Finally, selected GKs performed better (large effect size) in the HG test (d = 0.817) and the CMJ (d = 0.915).
Discussion The present study analysed the process of talent identification in a professional club. Preselected OFs were older and lighter and had lower BMI and amount of body fat compared to players of the soccer camp. Besides, they performed better in most performance tests (velocity, agility, endurance and jump tests). Moreover, discriminant analysis showed that the velocity and agility tests (both 15 m and 30 m) were the most important parameters to discriminate between the preselected players and players of the soccer camp. Both agility and speed have been cited as the most important features in soccer players, particularly in high-level players (Williams & Reilly, 2000).
Physical performance has been closely related to chronological age. Thus, it has been observed that older players display better results in the velocity, the agility and the jump tests and in the yo-yo IR level 1 than younger players born in the same year (Gil et al., 2013). On the other hand, it is well known that body fat is negatively related to the performance of soccer players (Figueiredo, Coelho E Silva, & Malina, 2011) and to the selection of players. Therefore, probably both an advanced chronological age and a leaner body make preselected players excel in their soccer performance while they are training and playing, and consequently they are identified as talented by the technical staff. In fact, age and adiposity were primary predictors of functional capacity in soccer players aged 11–12 years (Figueiredo et al., 2011). Nonetheless, there were fewer observed differences between the finally selected and the nonselected players. The statistically significant differences were found in the chronological age
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Selection process in a soccer club (selected players were older), lower predicted height and better agility and endurance. Again, chronological age is a determinant factor in the selection process, probably due to the fact that older players demonstrate better performance in various physical tests than their younger peers (Gil et al., 2013). Agility is an important characteristic for playing many sports, but it is particularly relevant to soccer. It has been mentioned as a discriminating factor in the selection process of players (Gil, Ruiz, et al., 2007; Huijgen, Elferink-Gemser, Post, & Visscher, 2009). Also, the finally selected players outperformed the nonselected players in the endurance test. In this line, a longer total distance covered by the retained players during matches was compared with that by the released players by a Soccer Academy (Goto, Morris, & Nevill, 2013), which implies that endurance is an important feature for high-level soccer players even from young ages. It is interesting to note that the results of the yo-yo IR level 1 test of the finally selected OFs were very similar to those observed in elite young soccer players from firstdivision soccer clubs from Belgium aged 9.7 years and born at the beginning of the year (739 ± 270 m) (Deprez, Vaeyens, Coutts, Lenoir, & Philippaerts, 2012), proving that the selected players of the present study are correctly classified as high-level players. There is less information in the literature about soccer GKs compared to the information about other positions. To our knowledge, this is the first time that the process of identification of talented GKs has been analysed. In the present study, we observed more differences between the preselected GKs and the OFs than in the players of the soccer camp. In this respect, preselected GKs were significantly older than participants of the soccer camp, and also the OFs. Moreover, the finally selected players’ age was higher than that of the nonselected GKs (large effect size). This is probably related to the fact that older players are taller and also display better performance (Gil et al., 2013), and both are important for goalkeeping. GKs had especially distinct anthropometric characteristics compared to the OFs. In this sense, they were taller, heavier and had a bigger amount of fat, particularly the finally selected ones. This anthropometric pattern has already been described in adult and adolescent soccer GKs (Ziv & Lidor, 2011). It is reasonable that these players should have a large body size (including long limbs and body) in order to stop the ball from entering the goal (Ziv & Lidor, 2011). It is also noticeable that predicted height was higher in the preselected GKs (184 cm) compared to the OFs (179 cm), but this measure was even higher
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in the finally selected GKs (186 cm). Should these selected players attain this potential height in the future, they would reach the height of high-level GKs (Ziv & Lidor, 2011), demonstrating the adequacy of the selection process of this particular club in this matter. OFs performed better in most of the performance tests compared to the GKs. However, it is remarkable that players of both positions outperformed the players of the soccer camp in velocity, implying a good performance in the running sprints in the preselected players, in the OKs and also in the GKs. In this sense, comparisons in the velocity between the GKs and OKs have shown inconclusive results (Aziz, Mukherjee, Chia, & Teh, 2008; Gil, Gil, et al., 2007; Ziv & Lidor, 2011). However, GKs showed a worse performance in the agility test than the OFs, similar to the results by Taşkin (2008) and Gil, Gil, et al. (2007). Agility is a characteristic a GK must have; however, perhaps the agility test of the present study was not as accurate to measure GKs’ specific agility. It would be very interesting if other kinds of tests to measure the specific agility of the GKs were designed. On the other hand, it has been widely described that GKs have a low endurance capacity (Gil, Gil, et al., 2007; Ziv & Lidor, 2011). In the present study, GKs displayed the worst results in the yo-yo IR1 test. A large aerobic capacity is probably not essential, but a moderate capacity is beneficial (Ziv & Lidor, 2011), and this should be kept in mind by the coaches when designing training sessions. It has been observed that GKs exhibit higher jumps (Sporis, Jukic, Ostojic, & Milanovic, 2009), similar to the rest of the players (Arnason et al., 2004). In the present study, OFs showed better results in the CMJ than the GKs. However, the finally selected players had better explosive power of the legs than the nonselected ones (28.4 cm vs 26.66 cm, d = 0.951) comparable to the results of Rebelo et al. (2013) in which elite players displayed higher jumps than nonelite ones. Good vertical jump skills are important for GKs, as they are often required to leap vertically to catch or deflect a ball (Ziv & Lidor, 2011). Finally, selected players exhibited higher strength in the arms in the HG test (d = 0.817) compared to nonselected GKs and also the rest of the participants, and they were also the tallest. The literature provides evidence that in prepubertal boys, height is a good predictor of HG strength (Jürimäe, Hurbo, & Jürimäe, 2009). Last, the earlier maturity offset and age at the peak height velocity and higher percentage of the predicted height observed in the finally selected GKs (large effect size) together with the higher levels of testosterone and dehydroepiandrosterone (small
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S. M. Gil et al.
effect size) suggest a trend for an advanced maturity in this group of players. We could not find any studies about the maturational status and GKs, but it is reasonable that more mature players are selected due to the fact that it has been demonstrated that they are taller, are stronger and have better performance particularly in strength measurements (Coelho E Silva, Moreira Carvalho, et al., 2010). One of the limitations of the present study was that some measurements, that is, a complete anthropometry, were not undertaken in the players of the soccer camp, and their somatotype could not be calculated. The reason is that the participants attended the soccer camp for a short period of time (1 week), and the procedures could not take up a lot of time for their activities. Consequently, it was decided to undertake the most relevant measurements in this group of players. Also, it would have been interesting to assess soccer-specific skills used by the players in the tests such as Loughborough Soccer Passing Test and the Loughborough Soccer Shooting Test as suggested by Ali (2011) in all the participants. Nonetheless, the selection of the players was made based on their playing performance on the soccer field, and soccer skills tests are indeed designed to evaluate this performance. Another limitation is that there were no specific tests for the GKs. It would be interesting that in future investigations, specific tests for GKs are utilised in order to differentiate finally selected GKs from nonselected ones (Knoop, Fernandez-Fernandez, & Ferrauti, 2013) to describe talent identification programmes for this particular positional role. It is important to underline that the technical staff did not know the results of our study when they made the selection of the players. This selection was done based on the coaches’ and observers’ expertise in this matter and through the observation and analysis of the physical appearance and technical and tactical skills of the players while they trained and played matches. By this means, the preselected OFs were older, leaner, fast and agile and with a good endurance and explosive power, whereas in finally selected players the distinctive parameters were age, agility and endurance. Besides, GKs had a specific anthropometric and performance pattern. They had larger body sizes and more strength of the upper extremities and legs’ explosive power, resembling the characteristics of the adult GKs. Undoubtedly, selected OFs and GKs had appropriate anthropometric and fitness features to excel in performance; in fact, they were the best performers. Yet, it will be very interesting to follow their achievements in the future. On the other hand, to our knowledge, the present study for the first time analysed the process of talent identification within a
professional club. It would be very interesting that similar studies in clubs of different levels and countries are designed to confirm these results.
Funding This study was partially supported by the Basque Government [grant number IT700-13].
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