Observed and predicted ages at peak height velocity in soccer players

Identifying Key Factors for Predicting the Age at Peak Height Velocity in Preadolescent Team Sports Athletes Using Explainable Machine Learning

Maturation is a key factor in sports participation and often determines the young athletes' characterization as a talent. However, there is no evidence of practical models for understanding the factors that discriminate children according to maturity. Hence, this study aims to deepen the understanding of the factors that affect maturity in 11-year-old Team Sports Athletes by utilizing explainable artificial intelligence (XAI) models. We utilized three established machine learning (ML) classifiers and applied the Sequential Forward Feature Selection (SFFS) algorithm to each. In this binary classification task, the logistic regression (LR) classifier achieved a top accuracy of 96.67% using the seven most informative factors (Sitting Height, Father's Height, Body Fat, Weight, Height, Left and Right-Hand Grip Strength). The SHapley Additive exPlanations (SHAP) model was instrumental in identifying the contribution of each factor, offering key insights into variable importance. Independent sample t-tests on these selected factors confirmed their significance in distinguishing between the two classes. By providing detailed and personalized insights into child development, this integration has the potential to enhance the effectiveness of maturation prediction significantly. These advancements could lead to a transformative approach in young athletes' pediatric growth analysis, fostering better sports performance and developmental outcomes for children.

Talent selection in 3 × 3 basketball: role of anthropometrics, maturation, and motor performance

Introduction

3 × 3 basketball is becoming more and more professionalized, which is leading to a growing interest in talent development and talent selection. Different studies have demonstrated relevant factors in the talent selection process of 5v5 basketball but not in 3 × 3 basketball. Therefore, this study investigated the main predictors in the talent selection process in 3 × 3 basketball athletes.

Methods

A total of 192 athletes (M age = 16.11 ± 0.45 years; n = 85 were female) 3 × 3 basketball athletes were assessed for various anthropometric and motor performance variables as well as maturity status. All assessments were carried out during selection camps for the German "under 17" youth national team. Binomial logistic regression was conducted to determine which variables predicted selection (either 'selected', n = 30 female and n = 34 male, or 'non-selected', n = 55 female and n = 73 male).

Results

The regression model was statistically significant in female athletes (χ² (3) = 26.86, p < .001). It explains 37.9% (Nagelkerke's R 2) of the variance in selection status and suggests that the general motor-performance component (p < .001) and the anthropometric- and maturation-related component (p = .004) seem to be relevant for being selected. In male athletes, the binomial logistic regression model was also statistically significant (χ² (3) = 11.38, p = .010) with explaining 14.2% (Nagelkerke's R 2) of the variance in selection status but only the anthropometric- and maturation-related component (p = .004) predict selection.

Discussion

Anthropometric conditions (such as body height, body weight, and wingspan) and the maturity status are particularly important in talent selection in 3 × 3 basketball for both sexes. Regarding motor-performance variables, we found a predictive value for talent selection only in females (without sprinting), but not in males which means that more 'athletic' female athletes seem to be favoured in talent selection. The results suggest that the talent selection process might be biased by maturation status even in middle adolescence. Therefore, coaches who decide on athletes' selection should be aware of the temporal advantages induced by earlier maturation when evaluating talented athletes and should consider strategies such as bio-banding to evaluate the real and potential value of talented athletes.

Changes in Muscle Mass and Strength in Adolescents Following High-Intensity Functional Training with Bodyweight Resistance Exercises in Physical Education Lessons

(1) Background: The growing prevalence of obesity, diabetes, hypertension, and declining physical fitness among children and adolescents due to sedentary lifestyles has increased attention toward preventive intervention to tackle this issue. This study investigated the age-related effects of high-intensity functional training (HIFT), based on bodyweight resistance exercises conducted during physical education lessons, on muscle mass and strength improvement. (2) Methods: Adolescent males (n = 116) were allocated to four HIFT experimental groups (EGs) and four standard physical education program control groups (CGs) according to age (15, 16, 17, and 18 years [y]). The changes in muscle mass (absolute and relative to height [SMI]), hand-grip strength (HGS), sit-ups (SUs), and standing broad jump (SBJ) were analyzed using two-way analysis of variance (ANOVA) with Bonferroni tests. (3) Results: HIFT significantly increased muscle mass and scores in all strength tests (p < 0.01), while chronological age was significant for HGS (p < 0.01). Interactions between HIFT and chronological age categories were observed for HGS (p = 0.01) and SBJ (p < 0.03). Detailed post hoc tests revealed improvement in muscle mass across all chronological age categories for both approaches (p < 0.05). The 18y-EG group improved HGS over their control peers (p < 0.01), the EG groups significantly improved their SU results (p < 0.01), and SBJ improved in the 15y-EG and 18y-EG groups compared to their control (p < 0.01). (4) Conclusions: This research highlights the effectiveness of a school-based HIFT program in promoting muscle mass gains and enhancing muscle strength among adolescents. The findings offer valuable insights for implementing bodyweight exercises during physical education classes.

Sex-specific relationship patterns between body morphology and maturity status with change of direction and agility in elite adolescent volleyball players

This study explored sex-specific patterns in the relationship between maturity, body morphology, and change of direction (COD) and agility (AG) in adolescent volleyball players. The sample comprised 22 males and 24 females aged 15-17 with at least 4 years of sports experience. Measurements included body height, weight, muscle and fat mass, leg length, and center of mass. The study determined the Age of Peak Height Velocity (APHV) and evaluated sensorimotor ability through pre-planned COD and not-planned AG five-time shuttle runs, measuring the time difference as the index of reactivity. Positive correlations were found between COD and AG with fat mass index (FMI) in boys, while negative relative lower limb length (rLL) correlated with COD. In females, age of peak height velocity (APHV) showed a significant negative relationship with sensorimotor ability. Linear and polynomial regressions confirmed predictive and curvilinear relationships, respectively. Cluster analysis identified different associations in boys and girls, emphasizing sex-specific patterns. Body fat percentage had a negative impact on COD-AG in boys, while the optimal lower limb length proportion positively influenced COD due to enhanced maneuverability. Maturation affected sensorimotor abilities in girls. The findings suggest a need for a tailored approach to COD-AG development based on sex-specific considerations in adolescent volleyball players.

Estimating Maturity Status in Elite Youth Soccer Players: Evaluation of Methods

PURPOSE

The objective of this study is to evaluate the concordance of predicted maturity status classifications (pre-, circa-, or post-peak height velocity (PHV)) relative to observed age at PHV in youth soccer players.

METHODS

Longitudinal height records for 124 male soccer players were extracted from academy records spanning the 2000 to 2022 seasons. Age at PHV for each player was estimated with the Superimposition by Translation and Rotation model. Players were classified as pre-, circa-, or post-PHV using both ±1- and ±0.5-yr criteria to define the circa-PHV interval. Maturity status was estimated with several prediction protocols: maturity offset (Mirwald, Moore-1, Moore-2), maturity ratio (Fransen), and percentage of predicted adult height (PAH%) using the Khamis-Roche and Tanner-Whitehouse 2 equations using several bands: 85% to 96%, 88% to 96%, 88% to 93%, and 90% to 93% for the circa-PHV interval, and visual evaluation of individual growth curves alone or with PAH% based on Khamis-Roche and Tanner-Whitehouse 2. Concordance of maturity status classifications based on complete growth curves and predicted estimates of maturity status was addressed with percentage agreement and Cohen's kappa.

RESULTS

Visual evaluation of the growth curves had the highest concordance (≈80%) with maturity status classifications (pre-, circa-, post-PHV) based on longitudinal data for individual players. Predicted maturity offset with the Mirwald, Moore-1, and Fransen equations misclassified about one-third to one-half of the players, whereas concordance based on PAH% varied with the band used, but not with the method of height prediction.

CONCLUSIONS

Visual assessment of the individual growth curves by an experienced assessor provides an accurate estimate of maturity status relative to PHV. Maturity offset prediction equations misclassify the majority of players, whereas PAH% provides a reasonably valid alternative.

Growth status and age at peak height velocity among youth participants in several sports: the Cracow longitudinal study

BACKGROUND

Studies addressing age at peak height velocity (PHV) in longitudinal samples of participants in sports are relatively limited.

PURPOSE

To compare the growth status and estimated ages at PHV of longitudinal samples girls and boys active in sport with peers not active in sport, and to compare estimated ages at PHV among longitudinal samples of Polish youth active in sport.

METHODS

Records from the Cracow Longitudinal Study, which measured youth annually from 8 to 18 years, were screened to identify individuals regularly active in sport. Participants in athletics (22 girls, 10 boys), soccer (12 boys), and other team (6 girls, 7 boys) and individual (6 girls, 9 boys) sports were identified; 107 girls and 172 boys were not active in sport. Heights and weights of participants in sports and non-involved peers were compared. Longitudinal height records of individuals were fit with the SITAR model to estimate age at PHV. Ages at PHV of boys and girls active in sport and peers not active in sports were compared with sex-specific ANOVAs.

RESULTS

Ages at PHV of boys participating in athletics and soccer were similar to age at PHV of boys not active in sport, while ages at PHV of boys in other team sports (basketball, volleyball, handball) and individual sports (skiing, gymnastics, acrobatics) were, respectively, slightly earlier and later. Among girls, age at PHV of participants in team sports (basketball, netball) was earlier, while ages at PHV among participants in athletics and other individual sports (equestrian, acrobatics, shooting) were slightly later compared to non-athlete peers.

CONCLUSION

Ages at PHV varied among participants in different sports and were consistent with estimates in other longitudinal samples of Polish youth athletes.

Growing up and reaching for the top: A longitudinal study on swim performance and its underlying characteristics in talented swimmers

The present study strived to gain a more profound understanding of the distinctions in development between swimmers who are considered to be on track to the elite level at late junior age (males aged 16; females aged 15) compared to those who are not. In this effort, swimmers were followed during their pubertal years (males aged 13-15; females aged 12-14), which marks a period when performance development aligns with maturation. Longitudinal data of 90 talented sprint and middle-distance swimmers on season best times (SBT) and underlying performance characteristics (anthropometrics, maximal swimming velocity, stroke index [SI] and countermovement jump [CMJ]) were collected over three swimming seasons. Based on their SBT at late junior age (males aged 16; females aged 15), swimmers were classified as high-performing late juniors or lower-performing late juniors. Retrospectively studying these swimmers, we found that all but two high-performing late juniors were already on track to the elite level at early junior age (males aged 13; females aged 12), evidenced with faster SBT throughout puberty compared to their lower-performing peers (p < 0.05). Independent sample t-tests revealed that high-performing late juniors significantly outscored their lower-performing peers when they were early juniors on maximal swimming velocity (males aged 13-15 and females aged 12-14), SI (males aged 13 and 14; females aged 12), CMJ (females aged 14) and height (females aged 13 and 14, p < 0.05). Additionally, multilevel models showed faster rates of development for high-performing late juniors on maximal swimming velocity (males and females) and SI (males) compared to lower-performing peers throughout puberty (p < 0.05). Higher initial levels of SBT and underlying performance characteristics at early junior age as well as the faster rates of development on SBT, maximal swimming velocity and SI (males only) during the pubertal years, may be crucial factors in maintaining the trajectory towards the elite level after puberty.

Ages at peak height velocity in male soccer players 11-16 years: relationships with skeletal age and comparisons among longitudinal studies

Estimated ages at take-off (TO) and at peak height velocity (PHV) based on two models and maturity status based upon age at PHV and skeletal age (SA) were compared in a longitudinal sample of male soccer players. In addition, estimated ages at PHV in 13 longitudinal samples of soccer players were compared. The longitudinal height records of 58 players of European ancestry, measured annually on four or five occasions between 11 and 16 years, were modeled with Superimposition by Translation and Rotation (SITAR) and Functional Principal Component Analysis (FPCA) to estimate ages at TO and PHV. SAs were assessed with the Fels method. Ages at PHV in 13 longitudinal samples of soccer players (Europe 7, Japan 6) were evaluated with meta-analysis. Estimated ages at TO, 11.2 ± 0.8 (SITAR) and 11.0 ± 0.8 (FCPA) years, and at PHV, 13.6 ± 0.9 (SITAR) and 13.7 ± 0.0 (FCPA) years, were similar. An earlier age at PHV was associated with advanced skeletal maturity status (rho = -0.77 at ~14 years). Ages at PHV among European players indicated a north (later) - south (earlier) gradient, and were later than ages at PHV among Japanese players. In summary, ages at TO and PHV were similar with SITAR and FPCA, and ages at PHV were most strongly correlated with SA at ~14 years. Mean ages at PHV showed a north-south gradient among European samples, and were later compared to Japanese samples.

Preece-Baines 1 model validation for cross-sectional data in male soccer players according to maturity status

AIM

The aim of the present study was to compare the Preece-Baines 1 (PB1) model fit between longitudinal and cross-sectional data in male soccer players and to adjust the height growth curve by maturity status.

METHODS

A final sample of 57 male Portuguese soccer players from professional soccer academies was included. Longitudinal height records were measured between 8 and 17 times in each subject from 2-8 years to 14-17 years. Additionally, longitudinal height records were used as cross-sectional data along with 1087 cross-sectional height records taken from 602 Portuguese soccer players. Skeletal age was estimated by Tanner-Whitehouse III method from a left hand-wrist radiograph. Age at peak height velocity (PHV) was estimated by PB1 model for longitudinal and cross-sectional data and by maturity status.

RESULTS

No significant differences were found between all the longitudinal estimates of 57 players and the random cross-sectional samples for, S1 parameter and for growth velocity at PHV, at TO, and for age at PHV. The age at PHV in early, on-time, and late maturers were 12.26, 12.9, and 13.58 years, respectively.

CONCLUSION

PB1 adjusted the height growth of Portuguese male soccer players from cross-sectional data, obtaining an estimate PHV very similar to that found from longitudinal data. A maturity time difference of ≈0.6 years was found between the age at PHV of on-time, early, and on-time and late maturity state.

Methods to predict the timing and status of biological maturation in male adolescent soccer players: A narrative systematic review

The aim of this review was to summarise the methods used to predict and assess maturity status and timing in adolescent, male, academy soccer players. A systematic search was conducted on PubMed, Scopus, Web of Science, CINAHL, Medline and SPORTDiscus. Only experimental studies including male, academy players aged U9-U18 years registered with a professional soccer club were included. The methodological quality of the included studies was assessed using guidelines from the Framework of Potential Biases. Fifteen studies fulfilled our inclusion criteria. Studies were mainly conducted in European countries (n = 12). In total, 4,707 players were recruited across all 15 studies, with an age range of 8-18 years. Five studies were longitudinal, two studies were mixed-method designs and eight studies were cross-sectional. Due to high heterogeneity within the studies, a meta-analysis was not performed. Our findings provided no equivalent estimations of adult height, skeletal age, or age at PHV. Discrepancies were evident between actual and predicted adult height and age at PHV. The Bayley-Pinneau [1952], Tanner-Whitehouse 2 [1983] and Khamis-Roche [1994] methods produced estimates of adult height within 1cm of actual adult height. For age at PHV, both Moore [2015] equations produced the closest estimates to actual age at PHV, and the Fransen [2018] equation correlated highly with actual age at PHV (>90%), even when the period between chronological age and age at PHV was large. Medical imaging techniques (e.g., Magnetic Resonance Imaging, X-Ray, Dual energy X-ray Absorptiometry) demonstrated high intra/inter-rater reliability (ICC = 0.83-0.98) for skeletal maturity assessments. The poor concordance between invasive and non-invasive methods, is a warning to practitioners to not use these methods interchangeably for assessing maturational status and timing in academy soccer players. Further research with improved study designs is required to validate these results and improve our understanding of these methods when applied in this target population.

Relationship Between Body Size and Skeletal Age with Muscle Damage in Young Soccer Players

This study verified the relationship between body size and skeletal age (SA) with the behavior of blood markers of muscle damage and delayed onset muscle soreness (DOMS) after a soccer match in the U-13 and U-15 categories. The sample consisted of 28 soccer players in the U-13 and 16 in the U-15 categories. Creatine kinase (CK), lactate dehydrogenase (LDH), and DOMS were evaluated up to 72 h after the match. Muscle damage was elevated at 0 h in U-13, and from 0 h to 24 h in U-15. DOMS increased from 0 h to 72 h in U-13 and from 0 h to 48 h in U-15. Significant associations of SA and fat-free mass (FFM) with muscle damage markers and DOMS were observed only in U-13, specifically at time 0 h, when SA explained 56% of CK and 48% of DOMS and FFM explained 48% of DOMS. We concluded that in the U-13 category, higher SA is significantly associated with muscle damage markers, and increase in FFM is associated with muscle damage markers and DOMS. Furthermore, U-13 players need 24 h to recover pre-match muscle damage markers and more than 72 h to recover DOMS. In contrast, the U-15 category needs 48 h to recover muscle damage markers and 72 h to recover DOMS.

Intra-observer reproducibility and inter-observer agreement of Fels skeletal age assessments among male tennis players 8-16 years

BACKGROUND

Skeletal age (SA) is an estimate of biological maturity status that is commonly used in sport-related medical examinations. This study considered intra-observer reproducibility and inter-observer agreement of SA assessments among male tennis players.

METHODS

SA was assessed with the Fels method in 97 male tennis players with chronological ages (CA) spanning 8.7-16.8 years. Radiographs were evaluated by two independent trained observers. Based on the difference between SA and CA, players were classified as late, average or early maturing; if a player was skeletally mature, he was noted as such as an SA is not assigned.

RESULTS

The magnitude of intra-individual differences between repeated SA assessments were d = 0.008 year (observer A) and d = 0.001 year (observer B); the respective coefficients of variation were 1.11% and 1.75%. Inter-observer mean differences were negligible (t = 1.252, p = 0.210) and the intra-class correlation coefficient was nearly perfect (ICC = 0.995). Concordance of classifications of players by maturity status between observers was 90%.

CONCLUSION

Fels SA assessments were highly reproducible and showed an acceptable level of inter-observer agreement between trained examiners. Classifications of players by skeletal maturity status based on assessments of the two observers were highly concordant, though not 100%. The results highlight the importance of experienced observers in skeletal maturity assessments.

Age and Maturation Matter in Youth Elite Soccer, but Depending on Competitive Level and Gender

This study aimed to explore the relevance of the relative age effect (RAE), maturity status and anthropometry, and their influence on coaches' assessment of players' performance, analyzing both genders and different types of academies (elite vs. non-elite). The sample included 603 soccer players (385 male), from the under 12 (U12), under 14 (U14) and under 16 (U16) categories, belonging to elite and nonelite teams. Coaches' assessment of players' performance, chronological age, anthropometric characteristics, maturity offset (MO) and peak height velocity (PHV) were registered. Our results showed that RAE was present in both genders within the elite, but not in the nonelite academies. Early maturity players were overrepresented in the male elite, but not in the female academies. No relationship was found between RAE and anthropometry in male elite academies. Male elite players showed better anthropometric characteristics than nonelite players, while this pattern of results was not found for female players. The coaches' assessment on players' current performance was not influenced by the chronological age nor anthropometry, but it was linked to the PHV. Coaches from nonelite academies rated better in current assessment of performance the taller players. Our findings suggest that maturity status and RAE play an independent and important role in the talent selection process.

Mapping the youth soccer: A bibliometrix analysis using R-tool

In recent years, there has been an increase in the scientific production of youth soccer. However, a panoramic map of research on this subject does not exist. The aim of this study was to identify global research trends in youth soccer over time, among the main levels of analysis: sources, authors, documents, and keywords. The bibliometric software Biblioshiny was used to analyze 2606 articles in Web of Science (WoS) published between 2012 and 2021. The main conclusion is that US and UK scholars dominate the research; the topics of research are changing with the real needs, and research on the topic of performance has been of interest to scholars; talent identification and development, performance, injury prevention, and concussion are the studies of interest to scholars in this area. This finding, which offers a global picture of youth soccer research over time, can help future research in this or similar domains.

Does maturity estimation, 2D:4D and training load measures explain physical fitness changes of youth football players?

OBJECTIVES

The purpose of the present study was two-fold: (1) To analyse physical fitness changes of youth football players after a full-season; and (2) to examine whether physical fitness changes are explainable by estimated maturity status, 2digit:4digit ratio (2D:4D) from each hand and training load (TL) measures.

METHODS

Twenty-seven youth elite Under-15 football players were daily monitored for training load measures during 38 weeks. At the beginning and at the end of the season, all players were assessed for physical fitness. Also, the maturity status estimation and the length of the second and fourth digits of both hands were collected at the beginning of the season.

RESULTS

Significant differences were found for all physical fitness measures after the season. The second and fourth digits of left and right hands had negative moderate correlations with change of direction (COD) changes (r=-.39 to - 0.45 | p = .05 to 0.02). Also, the maturity offset measure had negative moderate correlations with COD changes (r=-.40 | p = .04). From the reported significant correlations, the maturity offset, Left 4D, Right 2D and Right 4D significantly predicted the Mod.505 COD test changes (β = 0.41, p = .04; β = -0.41, p = .04; β = -0.45, p = .02; and β = -0.44, p = .03, respectively).

CONCLUSION

The maturity offset and the 2D:4D measures have the potential to predict COD performance changes over-time in youth football players. Given the lack of associations between the maturity estimation, 2D:4D and training load measures, with the overall physical fitness measures, coaches should rely only at COD changes.

Reliability of biological maturation analyses performed by equations predicting skeletal age and peak height velocity with hand and wrist X-ray results

BACKGROUND

Hand-wrist radiography is the gold standard for the assessment of skeletal age (SA) and the assignment of biological maturation (BM) status. However, its practical use in the field is questioned, prompting the development of anthropometric equations to estimate BM. However, there is no consensus on the reliability of these equations in relation to hand-wrist X-rays.

OBJECTIVE

To test the reliability of the BM estimated from predictive equations with the results of hand-wrist X-rays.

METHODS

One-hundred forty-four young athletes (38%-males, 62%-females; 12.3 ± 1.4 years) were recruited. SA was assessed by analyzing X-rays of the hand-wrist using the Greulich-Pyle protocol. SA was predicted using the anthropometric equations of Cabral and Macêdo. By subtracting chronological age from SA, a measure of BM or biological age (BA) was computed. In addition, a BA of years from peak height velocity (PHV) was predicted using the anthropometric equations of Mirwald and Moore.

RESULTS

Relative to X-ray, Cabral's equations showed high reliability in estimating BM in both sexes (p < .0001) while Macêdo's equations showed substantial reliability or males (p < .0001) only. Mirwald and Moore's equations showed weak reliability (p < .05 and p = .043, respectively).

CONCLUSION

The prediction of SA using anthropometric equations was found to be reliable in categorizing individuals as late, synchronized, and/or early maturers in both sexes. However, the predictive equations of years from PHV only reliably categorized late and synchronized maturation stages in males and the synchronized maturers in females.

Influence of Maturity Status on Kinanthropometric and Physical Fitness Variables in Adolescent Female Volleyball Players

The aim of this research was to analyze differences in kinanthropometric characteristics and physical performance in relation to maturity status, as well as to determine if age, maturity offset or kinanthropometric variables could predict better performance in physical fitness tests. A total of 152 female volleyball players (14.16 ± 1.25 years old) underwent a kinanthropometric assessment, followed by a physical fitness assessment composed of different tests. The age at peak height velocity (APHV) was calculated, and the sample was divided according to biological maturation into three groups. Significant differences were observed in kinanthropometric variables (p < 0.001–0.026), with early maturers showing higher values. Age, body mass, Cormic index, relative arm span, ∑8 skinfolds, fat mass, corrected arm and thigh girths, muscle mass and biacromial and biiliocristal breadths were the variables that best predicted performance in the physical tests (p < 0.001–0.024). The more mature players showed higher values in most of the kinanthropometric variables, with the more remarkable differences being in body mass, height, arm span and sitting height, and those related to adiposity and absolute body composition, and with structural variables being the most influential on the physical tests. Age had a determinant influence on the differences found between groups in strength and power-related test performance.

Influence of biological maturation status on selected anthropometric and physical fitness variables in adolescent male volleyball players

Background

The identification of sport talent among adolescent athletes is a topic that in recent years has been a major focus of interest for both the scientific community and sport managers. Both anthropometry and physical performance through fitness tests have demonstrated to be key elements. Biological maturation, due to its influence on anthropometric variables and physical fitness, has also been studied in relation to sport talent identification.

Objective

To analyse differences according to biological maturation status in anthropometric characteristics and performance in physical fitness tests, and to determine which variables predict better performance in physical fitness tests in adolescent volleyball players.

Methods

A cross-sectional design was followed to collect the data. A total of 48 male sub-elite volleyball players (14.17 ± 0.73 years) completed a socio-demographic and sports ad hoc questionnaire. Anthropometric variables were measured following the guidelines of the International Society for the Advancement in Kinanthropometry (ISAK) including four basic measurements (body mass, height, sitting height and arm span); eight skinfolds (triceps, biceps, subscapular, iliac crest, supraspinale, abdominal, thigh and calf); four girths (arm relaxed, flexed and tensed arm, middle thigh and calf); five breadths (biacromial, biileocrestal, humerus, femur and bi-styloid); three lengths (acromiale-radiale, radiale-stylion and stylion-medio dactilion); and a height (ilioespinale). Physical fitness was assessed, including the sit-and-reach, back scratch, long jump, medicine ball throw, counter movement jump (CMJ), 20 meters sprint, and agility tests. Furthermore, maturity offset and age at peak height velocity (APHV) was calculated.

Results

Significant differences were found in the body mass (Mean Difference, MD = 20.86-30.75), height (MD = 11.72-19.09), sitting height (MD = 4.27-10.27), arm span (MD = 12.91-20.78), body mass index (MD = 3.72-5.63), upper limb length (MD = 7.76), corrected muscle girths (MD = 2.06-9.31), ∑6 and 8 skinfolds (MD = 3.67-50.21) fat mass and percentage (MD = 0.30-11.58), muscle (MD = 4.13-10.64) and bone mass (MD = 1.61-3.54) (p < 0.001-0.030), showing higher values the early maturers. In the physical fitness tests, significant differences were observed in the medicine ball throw (MD = 1.26-2.80) and in CMJ power (MD = 156.71-379.85) (p < 0.001). Regression models identified fat mass percentage predicted worse physical test performance (p < 0.001), while age, maturation offset, muscle and bone variables were predictors of better physical performance (p < 0.001).

Conclusions

Significant differences based upon the stages of biological maturation were found in the anthropometric and physical condition variables in favor of the players whose maturation process was more advanced, with the variables related to fat and adipose, muscle and bone development conditioning their performance in the physical condition tests.