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Article

Anthropometric and Performance Differences Between U16 and U18 Male Basketball Players in the Post-PHV Phase

by
Dan Iulian Alexe
1,
Cristina Ioana Alexe
2,*,
Nedim Čović
3,*,
Ensar Abazović
3,
Maria Cristina Man
4,
Elpidio Attoh-Mensah
5,
Ovidiu Dragoș
4 and
Denis Čaušević
3
1
Department of Physical and Occupational Therapy, “Vasile Alecsandri” University of Bacău, 600115 Bacău, Romania
2
Department of Physical Education and Sports Performance, “Vasile Alecsandri” University of Bacău, 600115 Bacău, Romania
3
Faculty of Sport and Physical Education, University of Sarajevo, 71000 Sarajevo, Bosnia and Herzegovina
4
Department of Physical Education, “1 Decembrie 1918” University of Alba Iulia, 510009 Alba Iulia, Romania
5
HAVAE—Disability, Activity, Aging, Autonomy and the Environment, University of Limoges, 87000 Limoges, France
*
Authors to whom correspondence should be addressed.
Appl. Sci. 2025, 15(18), 10038; https://doi.org/10.3390/app151810038
Submission received: 28 July 2025 / Revised: 8 September 2025 / Accepted: 11 September 2025 / Published: 14 September 2025
(This article belongs to the Special Issue Novel Anthropometric Techniques for Health and Nutrition Assessment)
Browse Figures
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Abstract

This study aimed to compare the anthropometric and performance characteristics of U16 and U18 male basketball players to better understand post-peak height velocity (PHV) developmental differences. A total of 31 athletes from the local international basketball academy participated in the research—15 from the U16 category (15.25 ± 0.86 years) and 16 from the U18 category (17.46 ± 0.34 years). Measurements included body composition, sprinting (with and without the ball), agility, and jump performance. The results revealed significant between-group differences in most anthropometric variables (p < 0.001), including body mass, BMI, skeletal muscle mass, fat-free mass, total body water, and segmental muscle mass. However, there were no significant differences in body height and body fat percentage. Performance comparisons showed that U18 players outperformed U16 players in agility (p = 0.026), 10 m and 20 m sprints (p = 0.045 and p = 0.016, respectively), and 20 m dribbling sprints (p = 0.011), while no significant differences were observed in jumping ability. These findings suggest that physical maturation strongly influences anthropometric parameters and partially affects performance characteristics. The results highlight the importance of age-appropriate training strategies that consider biological development stages in youth basketball.

1. Introduction

Basketball is a physically demanding sport characterized by short, intense bouts of activity, often performed at medium to high frequency [1,2]. Players are required to execute repeated sprints, jumps, acceleration and deceleration, and rapid changes in direction throughout the game [3,4]. These actions place significant demands on both aerobic and anaerobic energy systems, which must be well-developed to maintain high-intensity performance [5]. Consequently, the ability to perform intermittent high-intensity actions is essential for success in basketball [6].
Athletic performance, particularly in basketball, is highly influenced by physical characteristics. Although the physical and performance characteristics in senior basketball players are well documented [7,8,9], younger athletes’ characteristics can vary significantly based on the maturational stage and body size [10,11,12]. Maturation has a notable influence on growth and physical performance, with substantial differences observed between various age groups [13,14]. As players progress through developmental stages, structural and functional body changes occur, affecting their athletic performance [11]. This relationship highlights the importance of maturation in shaping physical capabilities and sports performance metrics [11,13].
A key indicator of maturational progress is peak height velocity (PHV), a growth spurt typically occurring around the age of 14 in boys [15]. PHV marks a period of rapid growth, followed by a gradual decline until adult stature is reached. This growth phase is often used to assess an athlete’s stage of maturation, providing insights into their developmental trajectory. Additionally, some authors previously stated that the period around the age of 14 (chronological) years is a critical period for training-related physiological development in youth [16,17,18]. Although PHV occurs around the age of 14, motor skills and morphological development continue to progress, albeit at a slower pace, throughout late adolescence.
PHV can be determined using different approaches, most commonly through predictive equations based on anthropometric variables such as age, standing height, sitting height, leg length, and body mass. The Mirwald [19] maturity offset method is widely applied in youth sport research because it offers a non-invasive way to estimate maturational timing. In basketball and other team sports (e.g., soccer, handball, ice hockey), boys generally reach PHV between 13 and 14 years, with some variation depending on biological and training factors [15,16,17,18]. This stage is considered crucial because it coincides with rapid increases in body size, muscle mass, and neuromuscular function [20,21].
Performance tests such as sprinting, jumping, change-of-direction agility, and endurance running are particularly relevant in this context because they are sensitive to growth- and maturation-related changes [22,23,24]. These tests reflect key attributes—speed, power, agility, and aerobic/anaerobic capacity—that are strongly influenced by maturation status. Assessing such tests in post-PHV players therefore provides valuable information on how physical performance evolves during adolescence and strengthens the rationale for comparing distinct age categories such as U16 and U18.
Despite increasing interest in the physical and technical development of youth basketball players [13,25,26] and talent identification processes [10], limited research has focused on comparing performance metrics between specific age categories, such as U16 and U18 [27]. Therefore, “post-PHV” comparisons are critical for understanding how motor abilities evolve during crucial developmental years. Such analyses can upgrade the training program design process, thus ensuring that interventions are tailored to the unique physical and performance demands of each age group.
The aim of this study is to compare performance and anthropometric characteristics between U16 and U18 male basketball players in order to examine how they evolve during the post-PHV developmental phase. By identifying age-related differences in key performance and morphology variables, this study seeks to provide evidence-based insights that can inform age-appropriate training program design and support effective long-term athlete development strategies.

2. Materials and Methods

2.1. Participants

Thirty-one male basketball players who were selected from the international basketball “KK Bosna” academy volunteered to participate in the present research, from which 15 athletes (age: 15.25 ± 0.86 (yrs ± SD)) were competing at the U16 level and 16 athletes (age: 17.46 ± 0.34 (yrs ± SD)) were competing at the U18 competition level. All participants had experience in national-level competitions within the past two years and were consistently engaged in a weekly training regimen that comprises five 120 min basketball practice sessions and one game. The day before testing, participants were instructed to avoid intense training, alcohol, and caffeine and to maintain their normal diet and sleep routine. Prior to testing, participants completed a 10 min standardized warm-up, including light jogging, dynamic stretching, and movement-specific drills. All athletes had prior experience with similar testing protocols. All participants, including their parents and coaches, were thoroughly briefed on the objectives and experimental methods of the study and provided their informed consent to participate. All athletes were medically cleared by the sports medicine team to participate in team activities. No athlete indicated any musculoskeletal injuries that might restrict or hinder testing procedures. The testing procedures carried out in this study adhered to the Declaration of Helsinki.

2.2. Measurements

All the measurements were performed by experienced personnel from the Institute of Sport at the Faculty of Sport and Physical Education, University of Sarajevo. The testing protocols used in this study included body composition assessment, followed by the measurement of performance indicators such as sprinting, dribbling sprint, agility, and jumping performance. The testing was conducted on the same day during the pre-season period on the first day of the international basketball academy. Both groups of athletes were tested at approximately the same time of day (i.e., 09:00–12:00 h). A recovery period of 2–3 min was provided between consecutive attempts of the same test, and a minimum break of 5–10 min was allowed between different tests to minimize fatigue effects.

2.2.1. Anthropometric Measurement

Standing height was assessed with a digital stadiometer (InBody BSM 370; Biospace Co., Ltd., Seoul, Republic of Korea). Body mass, fat-free mass (FFM), skeletal muscle mass (SMM), body fat percentage (PBF), and total body water (TBW), as well as segmental FFM of the upper and lower limbs and trunk, were determined using a multifrequency, segmental bioelectrical impedance analyzer (InBody 720; Biospace Co., Ltd., Seoul, Republic of Korea). The accuracy and reproducibility of this device have been well established in earlier studies [28]. During the assessment, participants were barefoot and dressed only in underwear to ensure standardization. Body mass index (BMI) was computed as body weight divided by the square of height (kg/m2).

2.2.2. Speed (Without and with the Ball)

The assessment of running speed involved participants performing 20 m maximal sprints, and split times were recorded at 5 and 10 m, both with and without the ball. Each participant first completed two sprints without the ball, followed by two sprints with the ball. Each sprint began from a stationary standing position, with the athlete’s self-selected lead foot (preferred starting foot) positioned 20 cm behind the initial photocell. Four photocells (Witty, Microgate, Bolzano, Italy) were used to measure 5 m, 10 m, and 20 m maximal sprint times (in seconds) (Figure 1). Photocells were placed at a height of 120 cm. Each participant completed two attempts. In the case of a failed attempt (dropping the ball), the participants retook the test following a suitable recovery interval (two- to three-minute pause). The best result was used for analysis, and all tests were conducted on a standard indoor basketball court with a wooden parquet surface.

2.2.3. Agility

The ability to quickly change direction without the ball was assessed using the Lane Agility Drill. Players began at the left corner of the extended free-throw line, where the timing sensors were positioned (Photocells, Witty, Microgate, Bolzano, Italy). The timer started as soon as the player moved from the set stance. They sprinted forward to the baseline cone (5.79 m), then side shuffled to the right to reach the next cone (4.87 m), back stepped to the top of the free-throw line (5.79 m), and side shuffled to the left to return to the starting point (4.87 m) (Figure 2). This sequence was repeated in reverse order (shuffle right, sprint forward, shuffle left, run backward). The timing device was automatically halted when the player reached the initial position. Test time was recorded in seconds, and each player was allowed two attempts, separated by a recovery period of two to three minutes. The best result was used for analysis. The Lane Agility Drill has demonstrated good validity and high test–retest reliability in basketball players (r = 0.9, p = 0.05) [24].

2.2.4. Jumping Performance

Vertical jump ability was assessed using two protocols: the countermovement jump (CMJ) and the countermovement jump with free arm swing (CMJ free arms) (Figure 3). Each jump was performed two times and measured with the Optojump Next system (Microgate, Bolzano, Italy), whose validity and reliability have been confirmed in previous studies [29]. Players began in an upright standing position with feet shoulder-width apart and hands placed on their hips to prevent arm swing for CMJ and hands next to the body for arm swing for CMJ free arms. Then, they performed a countermovement to a self-selected depth by bending at the hips and knees, followed by an immediate extension of the hips and knees to execute a vertical jump. After the jump, the players returned to their initial position. A trial was deemed invalid if knee flexion occurred upon landing or if arm swing was detected (for CMJ), in accordance with previously published protocols [30]. Each player completed two attempts per condition, with a recovery period of two to three minutes between attempts. The CMJ (hands on hips) was always performed first, followed by the CMJ free arms condition. The best result from the two trials was used for analysis.

2.3. Statistical Analysis

Descriptive statistics were expressed as mean values with corresponding standard deviations for each variable. The distribution of data was examined using the Kolmogorov–Smirnov test, while Levene’s test was applied to assess the assumption of homogeneity of variances. Group differences between U16 and U18 athletes in anthropometric and performance variables were analyzed using independent samples t-tests. Effect sizes (ES) were computed according to Cohen’s d, with thresholds interpreted as small (>0.2), moderate (>0.5), large (>0.8), and very large (>1.3) [31]. The level of statistical significance was predetermined at p < 0.05. All analyses were performed using SPSS software (Version 21.0; IBM Corp., Armonk, NY, USA).

3. Results

The Levene’s and Kolmogorov–Smirnov tests indicated that homogeneity and normality of data distribution were adequate for all tests.

3.1. Anthropometric Measures

The results showed significant differences in most anthropometric variables (Table 1), providing insights into the physical development between U16 and U18 players. ** Specifically, for U18 players, body mass (kg) was 18.3 ± 1.1% higher (p = 0.001; ES = 1.69) than in U16 players, indicating notable growth in overall body size. BMI (kg/m2) was 13.9 ± 5.3% higher (p = 0.001; ES = 1.58), reflecting increased mass relative to height. Skeletal muscle mass (SMM (kg)) was 18.8 ± 7.0% greater (p = 0.001; ES = 2.34), highlighting substantial muscle development in older athletes. Fat-free mass (FFM (kg)) increased by 17.2 ± 7.0% (p = 0.001; ES = 2.20), while total body water (TBW (l)) was 17.0 ± 7.0% higher (p = 0.001; ES = 2.13), consistent with increased lean tissue. Upper limb FFM showed the largest relative differences, with the left and right arm FFM increasing by 21.4 ± 9.0% (p = 0.001; ES = 2.06) and 23.1 ± 10.0% (p = 0.001; ES = 2.36), respectively. Leg FFM also increased, though to a smaller extent (left: 11.6 ± 10.2%, p = 0.001; ES = 1.19; right: 11.9 ± 10.0%, p = 0.001; ES = 1.22). Trunk FFM increased by 17.7 ± 7.8% (p = 0.001; ES = 2.24). These differences indicate that the progression from U16 to U18 is associated with substantial gains in muscle mass, particularly in the upper body, which may contribute to improved strength and performance in sport-specific movements.

3.2. Sprinting, Agility, and Jumping

Performance differences between age groups were less pronounced than anthropometric changes, suggesting that growth alone does not fully account for improvements in speed and agility (Table 2). For the 5 m sprint and dribbling, 10 m dribbling sprint, as well as countermovement jump (CMJ) and CMJ free arms jump height, no significant differences were observed (p > 0.05) between U16 and U18 players, indicating that these short-distance and vertical jump capacities may develop earlier or be influenced more by technique than age alone.
Conversely, U18 players exhibited significantly better results in longer sprint and agility measures: 10 m sprint (3.3 ± 0.3% faster; p = 0.045; ES = 0.78), 20 m sprint (3.5 ± 0.3% faster; p = 0.016; ES = 0.95), 20 m dribbling sprint (6.0 ± 0.7% faster; p = 0.011; ES = 1.03), and Lain agility test times (5.2 ± 0.6% faster; p = 0.026; ES = 0.90). These results suggest that while basic speed and jump performance may plateau in mid-adolescence, more complex sprint and agility tasks benefit from continued physical maturation and likely from sport-specific training adaptations (Figure 4).

4. Discussion

This study aimed to investigate the differences in (a) performance and (b) anthropometric measures between U16 and U18 male basketball players. The results showed U18 players were not significantly taller (but practically relevant) and had significantly more muscle and segmental fat-free mass. They also outperform younger players in sprint (10 m and 20 m), dribbling (20 m dribbling), and agility performance (Lain agility). No age-group differences were observed for body fat percentages and the 5 m sprint, the 5 and 10 m dribbling sprint, or jump performance.
The observed results for anthropometric measures and performance were similar to those found by Drinkwater et al. [32] for national-level players and Androutsopoulos et al. [33] for the extended national roster. However, these authors had no between-age-group comparisons. To date, only Cabarkapa et al. [27] have compared U16 and U18 basketball players; however, their study focused exclusively on female athletes. Our results therefore add novel insights by examining differences specifically in male athletes in the post-PHV developmental stage, a period that has been underrepresented in basketball literature.
The findings of this study reveal no significant differences in body fat percentages between younger and older players. Similar results were reported by Cabarkapa et al. [27] in their study on female basketball players, where the authors attributed these differences to biological changes driven by variations in growth dynamics. Furthermore, the aforementioned researchers noted that muscle mass and segmental fat-free mass did differ between two groups, which is also the case in the present study. This indicates that gender does not affect the observed pattern of differences across these age groups. Importantly, this reinforces the idea that muscle mass rather than fat mass is a key driver of performance improvements during adolescence.
The observed differences in body composition between U16 and U18 basketball players can be attributed to the natural physical and hormonal changes associated with male adolescence, as well as the increased training loads typically introduced during the later stages of puberty [27,28,34,35]. This also underlines the fact that this age period is important in male athletes’ development, namely because adolescents’ response and adaptation to training stimulus is increased. From a practical standpoint, this suggests that strength- and hypertrophy-oriented training should be strategically emphasized during and immediately after PHV, when players show the greatest responsiveness to training stimuli.
Along with higher muscle mass, older players had better speed and agility performances, respectively. Quantity of muscle mass is related to better power abilities, possibly arising from the determined differences for some sprint and agility tests between U16 and U18 players [27,32,36]. Furthermore, a significant correlation exists between players’ aging and increased playing time [36], likely contributing to performance improvements supported by an already enhanced training load with age. Furthermore, chronologically older players were heavier and had more muscle mass, which contributed to better sprinting, dribbling, and agility performance. Since previous studies mainly investigated the topic of talent ID based on anthropometrics [37,38], the findings of this study suggest performance indicators should be included in selection criteria development, talent identification, and team composition, particularly since physical maturity often correlates with superior performance. However, not all performance measures improved equally (e.g., jump performance showed no difference), suggesting that certain motor abilities may plateau earlier, while others continue to develop through late adolescence. This highlights the need for differentiated training approaches across age groups.
In addition to the observed differences in sprinting, dribbling, agility, and jump performance between U16 and U18 players, it is important to consider how these test results translate to actual in-game performance. Faster sprint times and greater agility are likely to enhance a player’s ability to react to dynamic situations, execute fast breaks, and maintain defensive positioning during games [20,21]. Similarly, higher jump performance (CMJ and CMJ with free arms) may improve effectiveness in rebounding and shot-blocking [39]. By linking these standardized tests to specific in-game actions, coaches can better identify areas of strength and development needs, thereby tailoring training programs to improve performance under competitive conditions. Future studies should aim to integrate match analysis to quantify these relationships more precisely and to confirm the ecological validity of the field tests.
While studies on age-related differences in body size and performance may appear less relevant as the effects diminish with advancing age and higher playing levels, understanding these phenomena is essential due to several reasons. Firstly, detection of the differences is critical for talent identification, helping to differentiate early developers from late bloomers, minimizing selection biases toward early-maturing athletes, and better evaluating long-term potential [40]. Secondly, they enable performance benchmarking, allowing for the assessment of player progression, identification of contributing factors, monitoring of growth and maturation rates, sport-specific development, and training load optimization [41]. Thirdly, our findings add to the growing evidence that post-PHV development is not homogeneous: while some attributes (e.g., agility, sprinting) continue to progress between U16 and U18, others (e.g., jumping) may stabilize. This nuance has direct implications for tailoring training priorities across adolescence.
This cross-sectional study is limited by its single-season sample and its reliance on “controlled” tests rather than on-court performance simulations or, additionally, power assessments such as force-platform jumps, and the lack of control over complementary training, such as muscle strengthening, which was not systematically assessed. Additionally, dietary supplement intake was not recorded or used as an inclusion/exclusion criterion, which could influence body composition and physical performance outcomes. Future longitudinal investigations should track athletes through puberty in order to distinguish growth- versus training-induced performance gains and adaptations. Finally, the bioelectrical impedance analyzer uses a proprietary algorithm that cannot be adjusted for specific populations, which may limit the accuracy of body composition measurements. Despite these limitations, the present study provides one of the few post-PHV comparisons of U16 and U18 male basketball players and offers actionable insights for coaches, talent scouts, and sport scientists working with adolescent athletes.

5. Conclusions

In summary, the present study reveals that substantial differences exist between U16 and U18 male basketball players across a wide range of anthropometric, motor, and functional variables. The superior performance observed in the older U18 cohort can be primarily attributed to interrelated factors such as more advanced biological maturation, greater training experience, and increased exposure to competitive environments. U18 players demonstrated greater height, muscle mass, and superior sprint and agility performance compared to their U16 peers, while body fat percentage, short-distance dribbling, and jump capacities remained largely comparable.
These findings underscore the importance of incorporating maturity-adjusted anthropometric data alongside performance testing, particularly for talent identification and for recognizing sensitive periods for strength and power development in young male athletes. Acknowledging these developmental discrepancies allows coaches and practitioners to implement training programs that are not only age-specific but also maturity-sensitive, ensuring that performance development is aligned with the biological stage of the athlete. Rather than general statements on long-term health and injury prevention, our results specifically highlight the need to adapt training loads and performance expectations according to maturation stage, thereby optimizing both immediate performance outcomes and long-term player development.

Author Contributions

Conceptualization, D.I.A., D.Č. and C.I.A.; methodology, D.Č., N.Č., C.I.A. and D.I.A.; software, D.Č., N.Č. and O.D.; validation, O.D., M.C.M., E.A., E.A.-M. and C.I.A.; formal analysis, D.Č. and N.Č.; investigation, D.I.A., D.Č. and N.Č.; resources, M.C.M., O.D., C.I.A. and E.A.-M.; data curation, E.A.-M., O.D. and E.A.; writing—original draft preparation, D.I.A., D.Č., N.Č. and E.A.-M.; writing—review and editing, D.I.A., E.A., D.Č., C.I.A., E.A.-M., N.Č., M.C.M. and O.D.; visualization, E.A.-M., C.I.A., E.A. and M.C.M.; supervision, D.I.A., D.Č. and E.A.; project administration, D.I.A., D.Č. and M.C.M.; funding acquisition, O.D. and M.C.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the Faculty of Sports and Physical Education, University of Sarajevo (0101-678-1/24 dated 20 January 2024).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available upon reasonable request from the corresponding author.

Acknowledgments

Dan Iulian Alexe and Cristina Ioana Alexe thank the “Vasile Alecsandri” University of Bacău, Romania, for their support and assistance.

Conflicts of Interest

The authors declare no conflicts of interest.

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Applsci 15 10038 g001
Figure 1. Speed 20 m (without and with the ball) split times at 5 and 10 m.
Figure 1. Speed 20 m (without and with the ball) split times at 5 and 10 m.
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Figure 2. Lane agility test.
Figure 2. Lane agility test.
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Figure 3. Jumping performance ((a)—CMJ; (b)—CMJ free arms).
Figure 3. Jumping performance ((a)—CMJ; (b)—CMJ free arms).
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Figure 4. Statistically significant differences in speed and agility tests—U16 vs. U18.
Figure 4. Statistically significant differences in speed and agility tests—U16 vs. U18.
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Table 1. Descriptive statistics and between-group comparisons of anthropometric characteristics.
Table 1. Descriptive statistics and between-group comparisons of anthropometric characteristics.
VariablesU16
(n = 15)		U18
(n = 16)		p-ValueES
MeanSDMeanSD
Age (years)15.250.8617.460.34--
Body height (cm)191.297.66195.525.860.0970.64
Body mass (kg)72.799.7189.149.620.0011.69
BMI (kg/m2)20.021.9823.252.090.0011.58
SMM (kg)36.793.3145.263.790.0012.34
PBF (%)9.804.4811.233.640.3470.36
FFM (kg)65.305.8178.866.360.0012.20
TBW (l)47.954.2457.754.650.0012.13
FFM of Left Arm (kg)3.650.464.640.480.0012.06
FFM of Right Arm (kg)3.640.454.730.460.0012.36
FFM of Left Leg (kg)11.581.3513.091.200.0031.19
FFM of Right Leg (kg)11.631.3313.201.230.0031.22
FFM of Trunk (kg)28.402.7134.482.700.0012.24
BMI—body mass index; ES—effect size; FFM = fat-free mass; PBF = body fat percentage; SD = standard deviation; SMM—skeletal muscle mass; TBW—total body water.
Table 2. Descriptive statistics and between-group comparisons for performance variables.
Table 2. Descriptive statistics and between-group comparisons for performance variables.
VariablesU16
(n = 15)		U18
(n = 16)		p-ValueES
MeanSDMeanSD
5 m sprint (s)1.080.051.030.070.1860.50
10 m sprint (s)1.830.061.770.070.0450.78
20 m sprint (s)3.200.103.090.110.0160.95
5 m dribbling sprint (s)1.050.111.040.120.7970.09
10 m dribbling sprint (s)1.850.111.820.100.5110.24
20 m dribbling sprint (s)3.340.233.140.150.0111.03
Lain agility (s)12.900.7112.370.480.0260.90
CMJ (cm)36.245.9338.026.030.4310.29
CMJ free arms (cm)44.365.9345.114.170.6870.15
CMJ—countermovement jump.
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MDPI and ACS Style

Alexe, D.I.; Alexe, C.I.; Čović, N.; Abazović, E.; Man, M.C.; Attoh-Mensah, E.; Dragoș, O.; Čaušević, D. Anthropometric and Performance Differences Between U16 and U18 Male Basketball Players in the Post-PHV Phase. Appl. Sci. 2025, 15, 10038. https://doi.org/10.3390/app151810038

AMA Style

Alexe DI, Alexe CI, Čović N, Abazović E, Man MC, Attoh-Mensah E, Dragoș O, Čaušević D. Anthropometric and Performance Differences Between U16 and U18 Male Basketball Players in the Post-PHV Phase. Applied Sciences. 2025; 15(18):10038. https://doi.org/10.3390/app151810038

Chicago/Turabian Style

Alexe, Dan Iulian, Cristina Ioana Alexe, Nedim Čović, Ensar Abazović, Maria Cristina Man, Elpidio Attoh-Mensah, Ovidiu Dragoș, and Denis Čaušević. 2025. "Anthropometric and Performance Differences Between U16 and U18 Male Basketball Players in the Post-PHV Phase" Applied Sciences 15, no. 18: 10038. https://doi.org/10.3390/app151810038

APA Style

Alexe, D. I., Alexe, C. I., Čović, N., Abazović, E., Man, M. C., Attoh-Mensah, E., Dragoș, O., & Čaušević, D. (2025). Anthropometric and Performance Differences Between U16 and U18 Male Basketball Players in the Post-PHV Phase. Applied Sciences, 15(18), 10038. https://doi.org/10.3390/app151810038

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