KINANTHROPOMETRY Effect of Maturity Status and Relative Age Effect on Anthropometrics and Physical Performance of Soccer Players Aged 12 to 15 Years

Introduction: There is a growing interest in the relationship between biological maturation, relative age effect, and soccer sports performance. Based on their cohort's relative age effect and maturation, relatively older soccer players can be favored to be selected for high-level teams. Therefore, the current study examined the effect of maturity and relative age on anthropometric and physical performance tests. Methods: A cross-sectional study involving 82 boys (M age: 13.4 ± 1.1; M body mass: 51.9 ± 9.9; body height: 162 ± 10.5; body fat%: 9.7 ± 1.1) were assessed for anthropometric, flexibility, hand, and leg strength, and countermovement jump performance. Peak height velocity (PHV) determination was used for maturity status estimation. The birthdate distributions were categorized into four quartiles (January-March, Q1; April-June, Q2; July-September, Q3; October-December, Q4). MANOVA analysis was performed on all anthropometric and physical performance assessments to examine differences within age groups and maturity status groups. Differences among all groups were revealed, with high scores in the older group (U-15). Results: Biological maturation influences the differences in the anthropometric and physical performance assessment with a significant effect on the early matured soccer players compared to the late matured. Early matured players were overrepresented and statistically had better anthropometric and physical performance results.


Introduction
In soccer, clubs aim to identify players that will potentially succeed at an early age to ensure they receive specialized coaching and training to accelerate the development process (Shahidi, Kingsley, & TAŞKIRAN, 2022). However, relative age and biological maturity are two factors that impact player selection and deselection (Zuber et al., 2016). To guarantee fair competition and reflect age-related development, youth athletes in many sports are separated into competition categories by chronological age (Trecroci et al., 2019;Viero et al.,2020). Relative age is the difference in chronological age between the oldest and youngest individuals within an age group determined by the date of birth and age group cut-off dates (Boucher & Mutimer, 1994;Jakobsson et al., 2021). The relative age effect (RAE) is a selection bias in favor of those born earlier in the election year, whereby those born toward the start of the selection year (1st January) who are chronologically older than those born toward the end of the selection year (31st December), are disproportionately overrepresented within talent pathways (Smith et al.,2018;Werneck et al., 2016). The relative age effect describes a phenomenon whereby those players born early in the selection year are more likely to be represented and succeed in youth sports programs (Kelly et al., 2020). Therefore, based on the RAE, the birthdate distributions have been categorized into four quartiles (January-March, Q1; April-June, Q2; July-September, Q3; October-December, Q4) (Cobley et al., 2009;Gil et al., 2014). A recent study showed that a significantly higher proportion of soccer players, from youth to professional levels, are born in the first quarter of the birth year (Pérez-González et al., 2021). Therefore, from a talent development perspective, older players (Q1, Q2) may hold the greatest potential for success at the senior level than the young player (Q3, Q4), a phenomenon termed the "underdog hypothesis" (Götze & Hoppe, 2021). A recent study (2022) examined the birth date of 20401 soccer players participating in 47 different tournaments from 2006 to 2019, showing the selection process was associated with the RAE, with the strongest effect among males U-17 years old. In contrast to chronological age, biological age or biological maturation refers to the progression toward the mature state, defined in timing, tempo, and intensity (Shahidi et al., 2021). Inter-individual variation in growth and maturation is considerable during childhood and especially adolescence. Individual variation in maturation is determined by hereditary and environmental factors (Christopher et al., 2022). Children of the same chronological age have been shown to vary by as much as five to six years in biological age. For example, a child with a chronological age of 12 could have a biological age between 9 and 15 years (Segueida-Lorca et al., 2022;Chris & Cumming, 2022). Advanced biological maturity within single-year chronological age groups of males from late childhood through mid-adolescence (about 9 -16 years of age) is associated with advantages in body size, body height, fat-free mass, and physical fitness including muscular strength, power, aerobic capacity, and speed (Chris et al., 2021). The estimation of the age of peak height velocity (APHV) or percentage of final estimated adult stature attainment (%EASA) is typically used to inform the training process in young athletes (Götze & Hoppe, 2021). In youth soccer, maturity-related changes in anthropometric and physical fitness characteristics are diverse among individuals, particularly around PHV (Albaladejo-Saura et al., 2021). Indeed, a significant difference between the distribution of early, normal, and late maturing groups was found when dividing players into maturity groups based on estimated age at peak height velocity (APHV) (Chris et al., 2021). Early maturing males tend to be taller and heavier than normal or later maturing males and are stronger, faster, and more powerful (Johnson et al., 2022;Pedersen et al., 2022). Late-maturing soccer players are more likely to be overlooked or excluded from soccer academies, denying them access to specialist coaching, training resources, and high levels of challenge and competition (D'Hondt et al., 2011;Heilmann et al., 2022). Therefore, the relative age effect (RAE) and biological maturation are critical factors in youth soccer player selection and deselection. Finally, the assessment of maturity status is also an essential factor in explaining anthropometric differences among peers. A cross-sectional study on 191 boys aged from U-12 to U-15 that examined the effect of maturity level using the Mirwald equation on anthropometrics in soccer players demonstrated that maturation status affects physical dimensions and body composition (Toselli et al., 2021). Therefore, individual differences in relative age effect and biological maturation, directly and indirectly, influence player selection and deselection.
The current study examined the RAE and the effects of maturation on anthropometrics and physical performance in young Turkey adolescent male soccer players aged from U-12 to U-15 years old. It was hypothesized that players born in the first half of the year (Q1, Q2) and advanced in biological maturity status (early maturity) would have better anthropometric and physical performance compared to the second half of the year (Q3, Q4) and less matured (late maturity) players.

Methods Participants
A total of 100 Turkish youth male soccer players aged 12-15 in Istanbul, Turkey, were recruited in a crosssectional experimental research study. Before enrollment, the participants and their parents were informed about the experimental procedures and the study's risks. Healthy, active children involved in a soccer training program without any injury or disease were recruited for the study. Goalkeepers and players who dropped out of the program were excluded. Additionally, without a complete data set, the participant's data were excluded from the data analysis. The participants were free to withdraw at any time. Written informed consent and assent were obtained from the participants and their parents, respectively. The ethical committee of Istanbul Gedik University approved the study protocol.

Experimental design
Data were collected at the Istanbul Gedik University laboratory. All the anthropometric data were collected on the first testing day. On the second testing day, the test battery was performed following a 10-minute cardiovascular warm-up in the second testing session. The warm-up and performance testing duration was approximately 45 minutes per player.

Anthropometric Measurements
Height and sitting height were measured to the nearest 0.1 cm using a stadiometer (Seca 213 Portable Stadiometer, Seca, Germany), and leg length was derived by subtracting sitting height from standing height. Players removed their shoes and socks to measure their standing height, with their heels, buttocks, shoulders, and head in contact with the stadiometer. For sitting height, players sat on a 40 cm chair with their hips, shoulders, and head as close as possible to the stadiometer. Body weight was measured to the nearest 0.1 kg (wearing light indoor clothing, without shoes) using a calibrated analog scale (0.1 kg, Seca©, Hamburg, Germany). Anthropometric assessments were undertaken following the International Society for the Advancement of Kinanthropometry (ISAK) standards. Anthropometric variables included the sum of eight skinfolds -∑8SF (Biceps, Triceps, Subscapular, Suprailiac, Supraspinal, Abdominal, Front thigh, and Medial calf), five girths (upper arm relaxed, upper arm flexed and tensed, waist, gluteal and maximum calf), and two breadths (Humerus bi-epicondylar and Femur bi-epicondylar. Skinfolds were taken using the Slim-guide skinfold calliper (CH, Plymouth Mich, USA) to the nearest 0.5 mm (Ackland et al., 2009), and the girths were performed with a flexible metallic tape measure (Lupkin W606PM, Mexico), with a precision of 1 mm completed by a single certified investigator (ISAK Level 1). Skinfolds were taken two times, and the mean value was recorded for further analysis. Somatotype was determined according to the Heath and Carter somatotyping method (Carter, & Heath, 1990). The technical error of measurement (TEM) was always lower than 7.5% for each skinfold region and lower than 1.5% for the remaining measurements, which were acceptable (Perini et al., 2005). A third measurement was taken if two measurements at any site were greater than the technical error of measurement (TEM). Given the importance of accurate anthropometric measures, the test-retest reliability for a sample of 20 soccer players (12-15 years) separated by 7-days was established (

Maturity Status
An estimation of the years from peak height velocity (PHV), an indicator of the adolescent growth spurt, was determined using the equation for boys by Mirwald et al. (2002), where Maturity Offset = −9.236 + 0.0002708*Leg Length and Sitting Height interaction −0.001663*Age and Leg Length interaction + 0.007216*Age and Sitting Height interaction + 0.02292*Weight by Height ratio (Mirwald et al., 2002). Based on the prediction equation used, the approximation of the age at PHV (APHV) is often lower in younger children who are not yet in their adolescent growth spurt and higher in older participants who already passed their adolescent growth spurt. Age-specific z-scores were used in the present study to classify players according to their maturity status to counter this potential age-dependent over and underestimation of APHV. The predicted APHV was used to calculate z-scores within each specific age category (U12-U15; N = 82). Based on these age specific-scores of the predicted APHV, players were then classified as 'earlier' (z < −1), "on time" (−1 ≤ z ≤ 1), or "later" (z > 1) maturing (Hill, Scott, Malina, McGee, & Cumming, 2020).

Physical Performance Battery Test
The players performed a battery of fitness tests at the beginning of the competitive season, before the preseason training period, and as part of their respective training programs. One minute of rest was allowed between two attempts, and the mean of two trials was used for further analysis. Flexibility was assessed using a custom sit and reach box (32.4 cm high and 53.3 cm long) to assess the flexibility of the lower back and hamstring muscles with no shoes. Hand grip dynamometry (Takei Scientific Instruments Co., Ltd., Tokyo, Japan) was used to assess the maximal isometric strength of the forearm and hand muscles on both sides. The maximal strength of the lower body muscle was assessed using leg dynamometry (Takei Scientific Instruments Co., Ltd., Tokyo, Japan). Explosive strength power was determined through countermovement jump testing with arm swing using photoelectric cells (Microgate, Bolzano, Italy).
All the measurements were performed twice, and the mean of the two measurements was recorded. If the measurements varied more than 0.05, a third measure was taken, and the median score was recorded. All data collection was completed within an indoor environment at İstanbul Gedik University exercise physiology laboratory. Participants were encouraged to refrain from vigorous activity for 24-48 h prior to testing.

Statistical analyses
Descriptive statistics were calculated and reported as mean ± standard deviation (SD) for continuous variables, while the frequency of appearance (percentage, %) was determined for qualitative variables (RAE and maturity status). The variables' distribution was checked via scatter plots and box plots and verified using the Shapiro-Wilk test. The Chi-square test was used to compare the expected distribution (reference population) and observed distribution (soccer players) of birth quartiles. Multivariate analysis of variance (MANOVA) was used to examine the effects of RAE and maturity on anthropometric and physical performance. The anthropometrical variables and the physical performance test were used as dependent variables. Bonferroni post hoc was conducted following multivariate analysis to examine univariate effects between each dependent variable. Effect sizes using partial eta squared (η 2 ) were calculated and interpreted using the benchmarks provided by Cohen (0.01 = small, 0.06 = medium, and 0.14 = large) (Cohen, 1988). The significance level adopted for all analyses was p ≤ 0.05. Statistical analyses were carried out using SPSS 25.0.

Results
Data from 4 goalkeepers and 8 participants were excluded from the statistical analysis due to incomplete anthropometric or physical performance testing data, with data from 82 participants used in the final analysis. The distribution for chronological age, anthropometric, somatotype, and maturity timing appears in Table and Figure 1. The presence of late and early maturation was observed in U-12 (late: 78.6%), U-13 (late: 47.1), U-14 (early: 9.1%), and U-15 (early: 65.5%) year groups ( Table 2). The late mature soccer players just have seen in the U-12 and U-13 years groups. When analyzing the variation of soccer players for chronological age, significant differences were observed in the U-15 group compared to the U-14, U-13, and U-12 groups for anthropometric and physical performance tests (Wilks A = 0.139, F (48, 188) = 3.70, p<0.001, η 2 = 0.483, observed power 1; Table 4).

Birth Date Distribution
The birthdate distribution by quarter for each subgroup is shown in Table 2.

Maturity on Anthropometrics and physical performance tests
The MANOVA revealed a significant effect of maturity on the dependent variables (Wilks A = 0.150, F (30, 130) = 6.862, P < 0.001, η 2 = 0.613, observed power = 1; Table 5 . Therefore, the evidence shows that the dependent variables differ between maturity types. The effect size was large, with an observed power of 1.00, indicating a 100% chance that the results could have been significant. Note; Early (n=21), Normal (n=41), Late (n=20); M ± SD: Mean ± Standard Deviation; MD ± SE: Mean Difference ± Std. Error; APHV: Age at peak high velocity (years); R: Right; L: Left

Discussion
This research examined the presence of biological maturation and relative age-associated selection biases and the relationships between maturation, relative age, anthropometry and physical fitness characteristics. In particular, we focused on how these relationships varied across age categories. A statistically significant maturation difference was found with large effect sizes across all included players. The distribution of normal, early and latematuring soccer players significantly differed from the expected normal distribution in all groups, while the birth quartile was not a discriminating factor for better anthropometric and physical performance. We also assessed whether anthropometric or performance advantages were conferred to relatively older players and by what likely mechanisms, via null-hypothesis significance testing, with a statistical model that recognized the confounding influence of chronological age group and maturation upon the dependent variables (i.e., anthropometric and fitness characteristics). Without considering the biological status in all anthropometric traits and physical performance tests, older soccer players (U-15) achieved higher values and better results. Considering only the chronological age of soccer players, the results in individual age categories were parallel to other studies (Fragoso et al., 2015;Lovell et al., 2015), emphasizing the importance of anthropometric (i.e., body height, body weight, sitting height) and performance (i.e., sit and reach, hand grip left and right, leg strength, and countermovement jump) characteristics of young soccer players. In a recent systematic review (2021), youth soccer players with an advanced maturation profile had better anthropometric and physical performance (Albaladejo-Saura et al., 2021). According to the authors, children born in the first quartile had a maturation advantage and better physical performance.
The current study demonstrated no skewness or presence of RAE. Additionally, the post hoc analysis did not reveal any effect of relative age on anthropometric and physical performance characteristics. The current study's results align with Hirose (2009), who found no difference in anthropometric traits between birth's first and fourth quarters (Hirose, 2009). Helsen et al. found that coaches are looking to select children born in the first and second quarters because of physical performance advantages. However, they found no RAE effect or relationship with physical performance (Helsen et al., 2000). Children are routinely grouped by chronological age irrespective of biological maturity, with their biological maturity often misclassified. Differences in stage and rate of maturation disqualify chronological age as an accurate index of physical potential. It is currently accepted that maturity and birth age play an important role in young soccer players' body size and performance level (Toselli et al., 2022). In the present study, the biological maturation showed a statistically significant relationship with the anthropometric and physical performance tests. When a comparison between different maturation groups (earlynormallate) was performed, a tendency to obtain better results was observed when the maturation process was more advanced (early mature) compared to other groups. When analyzing the overall differences between maturation groups, significant differences were found in weight, height, sitting height, and hand grip right, hand grip left, leg strength, and countermovement jump, confirming our hypothesis of the impact of maturational status on anthropometric and physical performance.
Biological maturity and physical fitness measures were statistically has a positive significant relationship between stage of maturity and physical fitness performance (Jones et al., 2000), which is supported by the results of the current studies. Finally, it was hypothesized that the effect would stronger in the early mature compare to the others. On the other hand, the data revealed no skewed relative age effect in Turkey soccer players. The overall RAE for all included soccer players showed no difference in players born at the first of the year compared to the end of the year. This result does not align with the RAE of male players reported in several elite soccer leagues worldwide (Lovell et al., 2015;Pedersen et al., 2022;Vaeyens et al., 2005). It has been shown that various factors, such as physical, psychological, and cognitive, can influence RAE. Furthermore, the physical component are more nominate in team sports such as soccer and there is a skewed birth distribution of soccer players and a result could have effect on selection the athlete into the elite team (Hoppe et al., 2020). Possible explanations include the depth of competition, the interaction of maturation and biological difference, and the low number of participants, with previous studies showing that the RAE decreases after adolescence. When the advantages of early physical maturity fade DOI: 10.34256/ijk2317 away and the best players all have similar physical, technical-tactical skills and cognitive abilities could make the difference to produce successful outcomes (McCarthy & Collins, 2014).
In summary, assessing maturity status is fundamental in explaining anthropometric and body composition. In older soccer players (U-15), maturity timing influences anthropometric and physical performance during tests. Therefore, maturity has a significant impact with a big effect size on anthropometric and physical performance. In contrast, the result of the current study did not support the underdog hypothesis. Our results demonstrate that RAEs did not exist in this adolescent soccer study. Nevertheless, the results of the current study highlight the importance of early mature players within academy systems and challenging players who are advanced in maturation.