Due to the financial benefits of being able to promote talented players from the youth ranks into the senior first team, the crucial role of a sports scientist employed by a professional soccer club is to help identify and develop future players. However, due to the multifaceted requirements of soccer match-play, no single characteristic can predict long term success in soccer . As elite players are often selected at a young age , information concerning the anthropometric and performance characteristics of players of varying age will have application to a large population, particularly coaches, sports scientists, talent scouts and the parents/guardians of aspiring young soccer players.
It has been reported that Olympic development players from an under 16s team were taller, heavier, and elicited significantly greater lower body power outputs (assessed by vertical jumping and linear sprinting) than players from an under 14s team that were enrolled in a youth soccer program in the United States . Similarly, chronological age has been reported to influence the performance characteristics of players from a French development center, with greater vertical jump heights and sprint speeds being attained by under 16s players over their under 14s counterparts . In fact, authors have reported differences due to age in anthropometric and/or performance variables in youth players competing all over the world; including clubs from Japan , Netherlands , Spain , Belgium , Denmark , Serbia , and Bosnia and Herzegovina .
However, such information is currently lacking in players competing within the UK as only two studies to date have performed a comprehensive battery of tests upon youth soccer players competing on behalf of English clubs [5, 19]. As these data did not discriminate between player age groups, information concerning the anthropometric and performance profiles of players of different chronological ages is currently unavailable in the UK. This is somewhat surprising considering that all teams playing professional soccer in the UK have Youth Academies and a number of other lower standard teams run Centers of Excellence, whereby teams that represent such establishments are classified according to chronological age (i.e., under 14, under 16, and under 18 years of age).
A number of authors have reported significant relationships between jump height and sprint performance [3, 27]. For example, Cronin and Hansen  observed significant correlation coefficients of -0.60, -0.62, and -0.56 between CMJ height and sprint times over 5, 10, and 30 m, respectively. Similarly, Wisloff et al  also reported significant correlations between CMJ height and 10 m (r=-0.72) and 30 m (r=-0.60) sprint times in senior players of the Norwegian men’s soccer team. Collectively, these findings indicate that an individual’s ability to produce greater peak power output (PPO) when jumping will predispose that individual to superior sprinting performances. However, limited data are currently available about the relationship that may exist between CMJ test performance and sprinting in youth soccer players that compete within the UK.
In summary, many studies have been published reporting the characteristics of professional soccer players of different ages from outside the UK. Likewise, many studies have identified relationships between indices of lower body power production and sprint ability. However, very few studies involving young soccer players competing on behalf of teams in the UK are currently available. With this in mind, the aim of this study was twofold: firstly, to investigate the anthropometric and performance characteristics of male soccer players who played on behalf of a professional UK-based club for the under 14s, under 16s, and under 18s age groups; and secondly, we aimed to clarify the relationships that exist between performance on CMJ and sprint tests and to determine whether the CMJ test can be used to differentiate between sprint performances.
MATERIALS AND METHODS
SUBJECTS AND PROCEDURES
Forty three players (age: 15 ± 2 years, height: 1.71 ± 0.08 m, mass: 63.9 ± 9.4 kg) from the youth department of a Championship soccer team (representing the second tier of professional soccer within the UK) participated in this study. All players participated in one match per week (played on Saturday mornings) and players aged 16 or under trained after school on two evenings per week for approximately 2 hours, a session consisting of: a warm-up (15 min), individual technical training (30 min), team tactical training (30 min), small sided games (40 min), and a cool down period (5 min). Within each team, all players trained together irrespective of the positional role except for the goalkeepers who received specialist position-specific technical training. Players aged 16 or under did not participate in any specific strength and conditioning program (either in season or off-season) whereas the remaining players were within the maintenance phase of their competitive season (for specific details see Russell and Pennock ). In accordance with the University ethics policy, written informed consent was obtained from both players and parents/guardians prior to any form of participation.
EXPERIMENTAL APPROACH TO THE PROBLEM
A cross-sectional approach was taken to examine the relationship that age has upon anthropometry and performance characteristics using a testing battery similar to that previously employed in youth soccer players . The tests employed when investigating the physiological responses of young players must be congruent with the demands of match-play; in this respect, 30 m sprint tests have previously been found to discriminate between playing standards of youth soccer players aged between 10 and 16 years old [7, 19] and the distances covered at high intensity are representative of those covered during soccer match-play [1, 18]. Moreover, information concerning the acceleration phase of sprinting is of benefit . Maximal jump tests have been found to discriminate between players of different positions  and a maximal aerobic capacity (VO2 max) in excess of 60 ml•kg-1•min-1 has been reported to predispose an individual to success in elite soccer . Therefore, the testing battery employed in the current study required the players to perform assessments of maximal lower body explosive power (countermovement jump; CMJ), sprinting acceleration (15 m sprint time), peak sprint velocity (30 m sprint time), and VO2 max (multistage fitness test).
For the investigation into the relationship that age has upon anthropometric and performance characteristics, the players were grouped according to the team for which they played at the end of the 2009/2010 competitive season. Specifically, based upon age recorded as integer values, the players were categorised as under 14s (12 ≤ age in years < 14), under 16s (14 ≤ age in years < 16 years), or under 18s (16 ≤ age in years < 18 years), with each category being exclusive to all others. To examine the relationship between jumping and sprint performance the players were classified as a whole group (n=43) and the ability of a jump test to discriminate between sprint performances was investigated in a manner similar to that employed by previous researchers  by classifying the players’ jumping performances as being either “high” or “low” (see below for the selection criteria).
Testing was performed throughout the month of April in the later stages of the 2009/2010 competitive season. One testing session took place per age group (i.e., under 14s, under 16s, and under 18s) with no longer than 10 days separating consecutive sessions and each player attended the laboratory on one occasion. In the two days before testing, players were asked to refrain from strenuous physical activity and to maintain a hydrated state. All players gave verbal confirmation that they had complied with these instructions upon completion of the study.
MAIN TRIAL PROCEDURES
Upon arrival at the laboratory the players emptied their bowels and provided a mid-flow urine sample. Urine osmolality was subsequently measured by freezing point depression (Gonotec Cryoscopic Osmometer Osmomat 030; YSI Limited, UK: Intraassay coefficient of variance = 0.2%) and it was confirmed that players did arrive in a hydrated state, being: 376 ± 255 mOsmol•kg H20 (the effect of age group: P=0.768). Near-nude body mass was determined using digital scales (model 770; Seca Ltd, Birmingham, UK; sensitive to nearest 0.1 kg) while the players were dressed in minimal clothing (i.e., wearing only playing shorts). Free standing height was determined using a portable stadiometer (Portable Stadiometer; Holtain Ltd, Wales, UK) to the nearest 0.001 m. The participants maintained an upright posture with the head positioned in the Frankfort plane, by standing with their feet together and heels touching the base of the stadiometer while the head board was lowered to the vertex of the head. Upon re-dressing, players then remained in a rested state for approximately 10 min before a standardized 20 min warm-up (that included jogging, multidirectional movements, dynamic stretches, and progressive sprints) was performed prior to undertaking the battery of tests. All players performed each test in a single session and in the following order: mass, height, CMJ, linear sprinting, maximal aerobic capacity. The lead investigator administered all tests so that the potential variation in the instructions given prior to each test was minimized and all tests were conducted in an indoor training facility that was maintained at an air temperature between 16 and 18 ºC.
To minimize the influence of fatigue, at least 7 min of recovery separated each different test. The testing battery used was standardized across all ages and has routinely been implemented by the lead investigator (who is also a Certified Strength and Conditioning Specialist: National Strength and Conditioning Association) in his role as sports scientist with the club. Fluid breaks were provided midway and upon completion of the warm-up and prior to commencing the multistage fitness test.
Assessment of Countermovement Jump Performance
Maximal CMJ height was determined using an electronic timing mat (Just Jump System, Probotics Inc., Huntsville, Alabama, USA). Players began the test from a standing position and performed a preparatory crouching action before explosively jumping out of the dip for maximal height. Hands were isolated at the hips for the entire movement to eliminate any influence of arm swing which has previously been found to affect results . Using pressure sensors, the timing mat system determined the flight time which was subsequently converted to the jump height according to the following equation: 1/8(gt2); where g is the acceleration due to gravity and t is the flight time. To minimise the likelihood of error, the timing mat was placed on a concrete surface in which preliminary investigations using an electronic laser device confirmed was level. As performance using a timing mat can also be influenced by body position during flight, the subjects were instructed and carefully observed to maintain straight legs while airborne. If the knees were bent or raised the attempt was discarded and the player repeated the trial following a 4 min rest period. Each player had previously performed the arms isolated CMJ as a routine part of their training and five sub-maximal attempts occurred prior to undertaking the test. Any abnormalities regarding technique were addressed in this period. Athletes performed three repetitions with the best (highest) measurements used for statistical analysis. A minimum of 4 min of recovery was provided between repetitions to reduce the influence of fatigue. Absolute (W) and relative (W∙kg-1) PPO was calculated using the validated Sayers equation .
Assessment of 15 and 30 m Sprint Times
Linear sprint speed was evaluated over 30 m. Infrared timing gates (Brower Timing, Utah) were positioned at the start line (0 m) and at 15 m and 30 m at a height of approximately 0.5 m off the ground. Participants commenced the test from a standing start at a distance of 0.3 m behind the first timing gate before initiating the test following a countdown from the lead investigator. Players were instructed to run at maximal speed throughout the full duration of the sprint test. To prevent a reduction in sprint speed on approach to the 30 m gate, a member of the coaching staff who stood on a marker 2 m beyond the final timing gate provided verbal encouragement throughout each attempt. Players were instructed to maintain maximal speed until passing the marker on which the coach stood. Timing started and finished when the lasers of the first (0 m) and last (30 m) gates were broken, respectively. Athletes performed three repetitions with the best (fastest) times used for statistical analysis. A minimum of 4 min of recovery were provided between repetitions.
Assessment of Maximal Aerobic Capacity
VO2 max was estimated using the multistage fitness test as described by Ramsbottom et al . Players performed repeated 20 m shuttles interspersed with 180 degree turns as dictated by audio signals from a CD. Subjects were instructed to complete as many stages as possible and the test stopped when the participant reached volitional exhaustion or failed to complete two successive stages within the allotted time. To minimize the likelihood of error, test administrators were positioned at each end of the 20 m course and assisted with identifying failed shuttles. VO2 max data is represented relative to body mass (i.e., ml•kg-1•min-1).
Statistical analyses were carried out using SPSS software (Version 16.0; SPSS Inc., USA). All data are presented as Mean ± Standard Deviation (SD) and the level of statistical significance was set at p≤0.05. One-way analyses of variance (ANOVA) were used to examine the differences between each age group for each variable measured. Pairwise comparisons using Bonferroni confidence interval adjustment were used to identify the location of differences whereas Pearson product moment correlation coefficients were used to assess the magnitude of the relationship between selected variables. In accordance with methods outlined by Hori et al , data were categorised according to “high” or “low” relative PPO achieved in the CMJ. Distinctions between categories were made on the basis of a 50% split in data once the middle point was excluded (due to the odd number of players involved in the study). An independent samples t-test was performed to examine differences between sprint times as a function of the “high” and “low” groupings. The reliability of each test was assessed by the coefficient of variance (CV%) and retrospective power analyses were performed using commercially available software (G*Power version 3.0.10). The sample size used was sufficient for 80% statistical power to be achieved for the identification of differences between the players categorised as “high” and “low” in the CMJ test.
THE RELIABILITY OF TEST PERFORMANCE
Attempts at vertical jumping (CV≤3.1%; n=43) and sprinting (15 m sprint test CV≤1.0%; n=43, 30 m sprint test CV≤0.8%; n=43) demonstrated a high degree of repeatability. Due to the testing performed, the repeatability of the VO2 max test could not be determined; however, previous studies had demonstrated the reliability of this protocol in terms of the bias ± 95% limits of agreement, being: -0.4 ± 2.7 ml•kg-1•min-1 .
THE EFFECT OF AGE ON TEST PERFORMANCE
Figure 1 illustrates that significant correlations were identified between chronological age and each of the variables measured.
THE RELATIONSHIP BETWEEN JUMPING AND SPRINT PERFORMANCE
Mean data (n=43) for each variable examined are shown in Table 2. CMJ height was negatively correlated to 15 m (r=-0.623, p<0.001) and 30 m (r=-0.667, p<0.001) sprint times. Similarly, absolute and relative PPOs in the CMJ were negatively associated with 15 m (r=-0.592, p<0.001; r=-0.549, p<0.001, respectively) and 30 m (r=-0.652, p<0.001; r=-0.569, p<0.001, respectively) sprint times.
THE ABILITY OF VERTICAL JUMP PERFORMANCE TO DIFFERENTIATE BETWEEN SPRINTING ABILITY
Classification of players according to “high” or “low” relative PPO produced two distinct groups, each consisting of 21 players (high, low: 64.6 ± 3.8 W•kg-1, 57.0 ± 2.8 W•kg-1; p<0.001), that were significantly different in terms of 15 m (high, low: 2.38 ± 0.06 s, 2.44 ± 0.11 s; p=0.015) and 30 m (high, low: 4.18 ± 0.12 s, 4.32 ± 0.22 s; p=0.016) sprint times.
DISCUSSION AND CONCLUSION
Using young male soccer players who competed on behalf of a UK-based Championship club, this study confirmed previous findings while also providing new information about this population. Specifically, youth soccer players varied significantly in their anthropometry and performance according to the age group for which they competed (i.e., under 14s, under 16s, or under 18s) and significant inverse relationships were confirmed between indices of CMJ performance and 15 m and 30 m sprint times. Finally, when CMJ performances were classified as being either “high” or “low” according to relative PPO produced, significant differences in sprint performances between groups were observed. Such findings may have important implications for the organization of training and the utility of performance tests between players of different ages at clubs in the UK.
The first aim of this study was to investigate the anthropometric and performance characteristics of three age groups of players enrolled in the Youth department of a UK-based Championship soccer club using age classifications that represent those employed in the field (i.e., under 14 years old, under 16 years old, or under 18 years old). This approach was taken as previous investigations into the differences in characteristics of youth soccer players between age groups had either neglected the players from the UK [6, 7, 9, 11, 12, 13, 15, 23, 25, 26], examined differences between playing levels within a given age group , and/or used a wide player age range that does not represent those classifications employed by soccer clubs in the UK . As one would expect, and based upon previous findings, our data suggest that players in the under 18s age group differed significantly in their anthropometry and performance characteristics from players of the under 14s team. However, an interesting finding of the present study was that such differences were absent between under 14s and under 16s players. Consequently, the application of such tests in their ability to differentiate between age groups in players from the UK may differ with age. Although caution should be exercised when interpreting the results due to the small subject number used, the data presented in this study is unique and possesses ecological validity (defined as the extent to which research emulates the real world; Thomas et al ), because this is the first study to document the characteristics of male youth soccer players competing on behalf of UK-based teams that are differentiated by the age of the player.
The finding in the present study that a lack of differences occurred between players in the under 14s and under 16s age groups contradict those observed previously  and may reflect similarities in biological age between these cohorts. Moreover, the homogeneity in training that the players in the under 14s and under 16s age groups undertake may also contribute to the results obtained; for example, in these age groups players participate in training on a part time basis (i.e., after school and on weekends), whereas players in the under 18s age group are enrolled in a full time training and education program. Referring to data collected at the under 16s level, Vanderford et al  proposed that coaches may share and consequently implement similar training regimes, resulting in similar training outcomes being achieved in this age group of players.
The findings of the present study agree with those of previous authors [25, 26] in that performance characteristics vary according to player age. Our data suggest that each of the performance tests employed, namely: the CMJ, 15 m and 30 m sprinting, and the multistage fitness test can discriminate between players who compete at the under 14s and under 18s age groups. Interestingly, at least one measure of CMJ performance was also able to differentiate between players at the under 16s and the under 18s age groups whereas all other tests performed could not. Previous authors had reported that technical skill was the most distinguishable characteristic between elite and non-elite under 14s players, while cardiorespiratory endurance was more important in under 16s players . Consequently, it had been suggested that discriminating characteristics of fitness change with competitive age levels  and our data would appear to substantiate that assumption. However, it is unclear as to whether the combination of tests performed in the current study was optimal to detect differences between the age groups sampled as previous authors had also identified differences between playing standards in agility, repeated-sprint ability, and cognitive components of soccer match-play . Therefore, further investigation is warranted into the utility of specific performance tests at different ages in UK-based soccer players. Such information may aid in the development of a comprehensive database against which performance data from aspiring young players can be compared.
The relative age effect (RAE) has become an area of interest in youth soccer , with authors generally reporting that players born in the first quarter of the selection year account for a disproportionate number of players selected in a squad of a given age. Explanations for the RAE in youth soccer tend to relate to physical characteristics as those born early in the year are generally taller and heavier than players born later in the year. Data concerning the RAE in the soccer players examined in this study were not available as players categorised according to their birth month distribution within the age groups studied would have produced findings low in statistical power due to the small subject numbers involved. Nevertheless, chronological age (which in this study and that of others was found to influence markers of maturity; Vanderford et al ) was found to differentiate between players in the youngest and oldest age groups, and to be significantly related to both anthropometric and performance characteristics. Consequently, although comment on the RAE in this group of youth soccer players is unavailable, the greater size, speed, and aerobic capacity of an individual may offer an advantage to male players who are older or more advanced in maturity status within their age group. However, if such an approach is adopted coaches should be aware that there is the risk of players who are equally talented but physically less mature at younger ages being dismissed on the basis of their physical characteristics and not on their adult potential .
The second aim of this study was to clarify the relationship between CMJ performance and sprinting ability. The significant inverse correlations of -0.55 and -0.57 determined in the current study between relative PPO and 15 m and 30 m sprint times respectively, are in agreement with the findings of multiple studies using older participants [3, 27]. Consequently, these data appear to indicate that factors in addition to age have profound influences upon the relationship between CMJ and sprinting performance. In support of this, classification of players according to “high” or “low” relative PPO in the CMJ differentiated between groups in relation to sprint times observed over 15 m and 30 m. Such information demonstrates the rationale for both CMJ and sprint testing in youth soccer players; however, the ability of the tests to differentiate between players of differing age should also be acknowledged when examining lower body power performances of youth soccer players. Moreover, the methods employed (i.e., CMJ data and the Sayers equation) have been reported to be the most precise in estimating actual PPO in a comparable population of athletes .
By characterizing the anthropometric and performance characteristics of soccer players who represented a UK-based Championship club in teams classified by their chronological age, this study confirms previous findings while also providing data that can be used as a bench mark for future research within similar populations from the same country. In support of previous research which characterizes players that compete outside the UK, our data suggest that the age of the player significantly influences these characteristics. Specifically, players in the under 18s age group were heavier, taller, faster, and elicited a greater VO2 max compared to their under 14s counterparts. However, players from the under 14s and under 16s teams were similar in terms of anthropometry and test performance in all indices measured. A secondary aim of this study was to provide further information concerning the relationships that exist between CMJ performance and sprinting (15 m and 30 m) in youth soccer players. In support of previous research we identified that significant correlations exist between both absolute and relative indices of CMJ performance and sprinting. Notably, when youth players were classified according to their relative PPO, players who elicited high values in the CMJ test outperformed those players scoring less high in the same test when sprinting. Collectively, these findings may have implications for the organization and provision of training at professional clubs within the UK.
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