Percentile Values of Specific Physical Performances in Tunisian Basketball Players Aged 9 to 21: Considering Maturity Status

Abstract

Background: Success in basketball is influenced by various factors, including biological maturation. Peak height velocity (PHV) is a key indicator of maturation, playing an important role in assessing the performance of basketball players. This study aimed to analyze the effects of maturational status, chronological age, and gender on anthropometric characteristics and physical performance parameters in Tunisian basketball players and to establish local percentile reference values for physical performance. Methods: A total of 470 basketball players (240 males and 230 females) were categorized into three maturity status groups: pre-PHV (n = 111), circa-PHV (n = 170), and post-PHV (n = 189). Anthropometric and physical fitness parameters were assessed to provide percentile reference values. Results: Our findings revealed significantly higher anthropometric and physical performance values in the post-PHV athletes compared to those in the pre- and circa-PHV groups. Additionally, male athletes outperformed females in most measured variables. Basketball-specific skills appeared to be more dependent on chronological age than on pubertal status. Conclusions: Percentile values were established for both boys and girls, offering valuable references for trainers to quantify and individualize training programs. These findings may assist practitioners in identifying potentially talented basketball players based on their maturation status.

1. Introduction

Basketball is a dynamic sport and is the second most popular sport in many countries around the world [1]. In basketball, success is determined by the individual performance of each player, as well as body dimensions, technical and tactical components, psychological development, and the physiological potential of players [2]. Therefore, physical fitness, including muscular strength, endurance, flexibility, and speed, as well as jumping and agility, all contribute to basketball performance [3,4]. Physical fitness tests should be based on multidirectional movements similar to those occurring during the game, such as dribbling, running, shuffling at different velocities, and jumping [5,6,7]. The ability to perform these movements involves both anaerobic and aerobic systems. Generally, basketball involves about 20% aerobic and 80% anaerobic [8] energy systems. In fact, during matches, players cover distances of between 4400 and 7500 m, consisting of jogging, jumping, sprinting, and changes in direction [9]. Aerobic capacity has been found to be essential for maintaining a high level of activity during the game and enhancing rapid recovery in basketball players [10]. However, the relative contribution of each energy source varies according to the intensity and duration of the exercise [8].

Muscular performance of the lower limbs is essential for functional capacity across various contexts [11,12]. Muscular strength improves with chronological age during middle childhood and adolescence, but the pattern of improvement is influenced by many components, such as gender, growth maturity, body size, height, mass, and, to a certain degree, motor competence and the level of physical activity. Neural, structural, and metabolic changes in the skeletal muscle occur during growth and development [13]. Notably, biological maturation in basketball is associated with adolescent growth and functional performance [14]. The age period from 11 to 14 years is a time of intense development for athletes and talent identification [15]. This period should take biological maturity into account.

Biological maturation has been described as the time required and the process of change until the adult stage of development is reached. Among the methods used to monitor biological maturation, the calculation of the age at peak height velocity (APHV) is one of the most used indicators. Indeed, peak height velocity (PHV) is an important non-invasive maturational event that occurs during adolescence. The mean age range for PHV in boys is from 13.8 to 14.2 years [16]. It is used to describe changes in body composition instead of chronological age. Biological maturation not only affects the physical performance of a player but is also a good predictor of a basketball team’s performance. The timing and tempo of maturation have been shown to exert significant effects on an athlete’s development and progression. For example, early-maturing players tend to be heavier, taller, possess greater lean mass, and perform better on physical tests compared to average- and late-maturing players [7]. However, early-maturing players do not demonstrate important basic basketball skills, such as shooting, dribbling, passing, and defensive movements [14]. In other studies, the findings favored late-maturing basketball players in some biological and physical performance parameters and technical skills [17,18].

In addition, in some studies and in studies across various sports, inter-individual differences in biological maturation are rarely considered. Significant differences were found in the physical and anthropometric parameters in favor of early-maturing players among male volleyball players [19]. In youth soccer players, early- and average-maturation groups were heavier, taller, and faster in sprints than a late-maturation group [20]. Moreover, the advancement of biological maturation increased levels of muscle power and sport performance in young swimming athletes [21]. Conversely, post-pubertal groups outperformed pre-pubertal groups in jumping, change in direction, and aerobic performance among Tunisian handball players. Additionally, this recent study provided maturity- and gender-specific reference values for physical performance in Tunisian handball players aged 13–19 years [22].

Previous and subsequent research has examined the effect of maturation on jump performance and anthropometric parameters in players classified by chronological age groups. In basketball, Gryko et al. [7] showed that average-maturing players obtained higher values in an endurance test compared to their early-maturing peers. Furthermore, maturity differentiation in under-14- and -15-year-old groups significantly affected body size, sprinting time, and the results of all jumping tests in male Polish basketball players aged 13 to 15 years. Guimarães et al. [23] found that differences in biological maturity affected muscular power and height but not technical skills in male Portuguese basketball players.

It is crucial to establish locally derived reference values of physical performance parameters for adolescent players. This allows coaches and other practitioners working with adolescent players to make informed decisions about a player’s physical performance in relation to their development stage. The relationships between maturation, gender, and performance capacities of adolescent players, as well as their implications for athlete selection, are discussed in the context of early talent identification and the prediction of success. Additionally, these insights can help individualize training programs that are relevant to the stages of biological development rather than being based solely on chronological age. Percentile values may also serve as a source of reference and comparison for performance in similar population. Therefore, we sought to examine how anthropometric and performances parameters varied when Tunisian players were classified by maturation status. To the best of our knowledge, no study has yet established percentile reference values for performance parameters relevant to the Tunisian population.

The aims of the study were as follows: (1) Evaluate the influence of maturity status on anthropometric parameters and physical characteristics of Tunisian basketball players. (2) Establish percentile values for physical performances in Tunisian basketball players according to maturity status and gender.

2. Materials and Methods

2.1. Participants

A total of 470 Tunisian basketball players (240 males and 230 females) were included in this study. We used a sample size calculation formula to determine the optimal sample size. Players aged between 9 and 21 years were randomly selected from various basketball teams across Tunisia, representing the northern, central, and southern regions. The sample included players who participated in the national championship leagues on a weekly basis. All players, in good health, were examined by the medical team and cleared for participation in team activities. Physical and physiological tests were conducted on 502 basketball players. Of these, 32 players who were unable to perform the tests adequately were excluded. As a result, 32 players (15 males and 17 females) were excluded from the initial sample of 502. Ultimately, the analysis included 240 males and 230 females. Prior to the study, the athletes and their parents were fully informed of the study’s aims, protocol, and procedures before signing a written consent form.

Prior conducting this research, the study protocol was approved (CEFMS: 213/2023) by the research Ethics Committee of the Faculty of Medicine of Sousse (Tunisia). The study adhered to the ethical standards of the Declaration of Helsinki of the World Medical Association, which was initially established in 1964 [24].

2.2. Anthropometric Measurements

Subjects were weighed in minimal clothing using a digital scale (Harpenden Balance Scale, International Trade Instruments Ltd (ITI), Harpenden, UK) with precision to the nearest 0.1 kg. Standing and sitting heights were collected using a stadiometer (Harpenden Portable Stadiometer, UK), and lengths were measured with a non-elastic measuring tape to the nearest 0.1 cm. The difference between standing and sitting heights was used to calculate leg length. Body mass index (BMI) was determined by dividing weight (kg) by the square of height (meters). Lower-body impedance was measured using a Tanita TBF-604 Body Fat Monitor/Scale (Tokyo, Japan). This device required input data, including the subject’s body mass, standing height, and gender. The subject then stood on the scale, which had source and detector electrodes on the plantar surfaces of both feet, to measure lower-body impedance and calculate body fat percentage.

Absolute body fat weight was calculated using the following formula: fat weight (kg) = %fat × (weight/100). Fat-free weight (kg) was determined by subtracting fat weight from total body weight.

Wingspan was measured using a tape measure, from fingertip to fingertip, with the arms held parallel to the ground. Players stood upright with their backs against a wall and their arms extended to the sides, perpendicular to their bodies [25].

Leg muscle volume of the dominant leg, which refers to the leg a basketball player prefers to use and that provides greater stability and control during various competitive activities such as rebounding, blocked shots, and lay-ups at higher positions, was estimated anthropometrically using the method described by Jones and Pearson [26]. This method involves summing the volume of truncated cones. Seven circumferences were measured at pre-determined sites: the maximum gluteal furrow, maximum mid-thigh, minimum above the knee, maximum knee, minimum below the knee, maximum calf, and minimum ankle. Heights were measured above the floor level for each circumference. Moreover, anterior and posterior skinfold thicknesses were measured at the second circumference (thigh) and the sixth circumference (calf) [26].

All anthropometric measurements were performed in the afternoon at the end of the week.

2.3. Procedure

The experimental part of this study was conducted during a 3-day vacation period in March of the previous competitive season. All participants completed two preliminary familiarization sessions to minimize learning effects and to receive pretest instructions. Prior to the experiments, players were instructed to refrain from strenuous physical workout for 24 h before the tests and to avoid heavy meals and caffeinated beverages for at least 4 h before testing. The performance tests, including the sprint, jump, agility, and aerobic tests, were conducted indoors, with the ambient temperature ranging from 18 to 20 °C and relative humidity between 35% and 50%. Participants wore the same type of standard sports shoes and indoor sportswear to ensure consistency and minimize any variation in test performance due to differences in footwear or clothing. Before each test, participants performed a standard 20 min warm-up. All tests were conducted in a single afternoon (4 pm) session to control for potential circadian rhythm effects on performance. This timing was selected based on studies showing that anaerobic performance peaks in the late afternoon [27,28]. The aerobic test, however, was conducted in a separate session. The test–retest intra-class correlation coefficients (ICC) of the testing procedure variables used in this study ranged from 0.98 to 0.99 ICC with the within-trial variation (CV = 1.1–1.9%).

2.3.1. Jump Assessments

All jumping data were collected using an Optojump Next device (Microgate SRL, Bolzano, Italy) (connected to a portable computer. All basketball players performed the squat jump (SJ) and countermovement jump (CMJ) with and without an arm swing under the supervision of the same investigator. The players were given two practice jumps before the specific jump tests were conducted. For the SJ, the players were instructed to sink into a 90-degree knee-bent position and hold it for three seconds before jumping as high as possible. The CMJ assessment required the athlete to start in a standing position, then sink as quickly as possible and jump as high as possible. These tests were conducted either with or without the use of an arm swing. Performing a CMJ and SJ with an arm-swing action has been shown to increase performance by 10% or more [29]. All jumps were performed according to the guidelines given by Komi and Bosco [30]. The best of three attempts, measured to the nearest centimeter, was recorded.

2.3.2. Five-Jump Test (5JT)

A multiple-5-jump test was used to assess horizontal jumping. The target of this test was to perform five consecutive double-leg hops as far as possible. The participants started by standing behind a line with their feet shoulder-width apart. When ready, they performed five consecutive broad jumps without stopping, using a combination of forward and vertical jumps to maximize distance [31].

2.3.3. Modified Agility t-Test

The modified agility test, commonly used to assess an athlete’s ability to change direction rapidly by moving forwards, backward, and side to side, was timed using a Photocells Witty system (Microgate). To perform the modified agility t-Test, a player runs 5 m forward from the start point to point one, sidesteps to point two, then sidesteps to point three, sidesteps back to point one, and finally runs back to the finish. The process is then repeated, starting by sidestepping in the opposite direction. The fastest time is recorded on an assessment form and used as a baseline for future performance comparisons. Besides testing an individual’s ability to move quickly in all directions, it also evaluates agility [32].

2.3.4. Sprint Tests

Running speed tests were conducted during 5 m, 10 m, and 20 m linear sprint tests both with and without the ball. Sprint times were recorded using photocell gates from the Witty System, a portable timing system from Microgate (Bolzano, Italy). The starting position for each sprint was standardized by placing the dominant foot at the front. All athletes performed the linear sprints three times with a 1 min passive recovery period between each set to ensure reliable results. The best sprint time was used for further analysis [33].

2.3.5. Flexibility

The flexibility test was carried out using a digital anteflexion meter (TKK-5403, Takei, Niigata, Japan) to assess the flexibility of the hamstring and lower back muscles. A TKK-5403 FLEXION-D, a digital device specifically designed for measuring forward body bending, displayed each measured value and the larger of two measurements, with a range from −20.0 cm to +35.0 cm. Players performed the test barefooted, with their legs extended and feet close together while standing on a platform. They were instructed to bend forward to their maximum range of motion, keeping their knees, arms, and fingers extended for at least 2 s during the test [34].

2.3.6. Aerobic Power Test: Twenty-Meter Shuttle Run Test

The 20 m shuttle run test, described by Léger and Lambert, involves continuous running between two lines 20 m apart, timed to recorded beeps [35]. Participants start behind one line, facing the other, and begin running when instructed by the recording. The initial speed is set at 8.5 km·h⁻¹. Participants run between the lines, turning when signaled by the beeps. Approximately every minute, a sound indicates an increase in speed, with beeps becoming closer together. The athlete’s score is based on the level and number of shuttles (20 m) completed before they can no longer keep up with the recording. This level score can be converted to maximal oxygen uptake (VO_2max), expressed in milliliters of oxygen consumed per kilogram of body mass per minute [36]. Maximal aerobic speed (MAS) is defined as the lowest running speed at which the maximum oxygen uptake (VO_2max) is achieved [37].

2.4. Maturity Status

Biological maturity was assessed using the maturity offset equation developed by Mirwald et al. [38], which is a simple and non-invasive method. This method estimates the years from the peak height velocity (PHV) as a measure of maturity offset, combining anthropometric parameters with the player’s chronological age. The regression equations are as follows [38]:

• For males: Maturity offset = −9.236 + (0.0002708 × leg length × sitting height) − (0.001663 × age × leg length) + (0.007216 × age × sitting height) + (0.02292 × weight by height ratio).
• For females: Maturity offset = −9.376 + (0.0001882 × leg length × sitting height) + (0.0022 × age × leg length) + (0.005841×age × sitting height) − (0.002658 × age × weight) + (0.07693 × weight by height ratio).
• A maturity offset value of >−1 years was classified as pre-PHV, −1 to 1 years indicated that the player was circa-PHV, and a score of >1 years indicated that the player was post-PHV [38].
• A total of 470 Tunisian basketball players (boys and girls) were categorized among the maturity groups (n = 111 pre-PHV, n = 170 circa-PHV, and n = 189 post-PHV).

2.5. Statistical Analysis

Descriptive statistics, including mean and standard deviations, were calculated for all anthropometric and physical performance parameters. Data from males and females were analyzed separately. The normality of all anthropometric and physical performance parameters was checked by the Shapiro–Wilk test. Comparisons between boys and girls at the same maturity status were carried out using Student’s unpaired t-tests. Comparisons between maturity status groups were analyzed using one-way ANOVA with Bonferroni’s correction. A repeated-measures multivariate analysis of variance (MANOVA) was applied to analyze within-subject changes and interaction effects (chronological age × maturity status) [39]. Effect sizes for the MANOVA test results were calculated in terms of eta squared values (η²) and categorized as follows: <0.06 as a low effect, 0.06 to 0.14 as a moderate effect, and >0.14 as a high effect. Percentile analyses were computed separately for boys and girls according to maturity status, calculating the 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles. All statistical procedures were performed using SPSS for Windows (version 26.0). A 0.05 probability level was used for statistical significance.

3. Results

3.1. Differences in Anthropometric Variables Based on Maturity Status and Gender

Based on the maturity status classification, 36.17% of both boy and girl players were classified as “on-time-maturing”, 23.61% as “early-maturing”, and 40.21% as “late-maturing” (Figure 1 and Figure 2).

The means and standard deviations of the body composition parameters in the Tunisian basketball players are presented in

Table 1. Anthropometric parameters in Tunisian basketball players categorized by maturity status and gender.

Maturity Status		Early-Maturing	p Values a	On-Time-Maturing	p Values a	Late-Maturing	p Values a	p Values b
Chronological age (years)	Boys	* 12.58 ± 1.48	0.049	* 13.96 ± 0.90	0.001	* 17.34 ± 1.75 †	0.043	0.001
	Girls	12.90 ± 1.02		14.79 ± 1.07		17.86 ± 1.73 £		0.001
Body mass (kg)	Boys	* 49.02 ± 9.35	0.043	* 62.30 ± 10.53	0.006	* 78.61 ± 11.54 †	0.001	0.001
	Girls	49.85 ± 8.51		57.97± 9.61		65.36 ± 10.49 £		0.001
Standing height (cm)	Boys	* 155.26 ± 6.98	0.038	* 170.85 ± 7.48	0.001	* 187.56 ± 8.51 †	0.001	0.001
	Girls	157.25 ± 5.95		163.79 ± 5.29		168.22 ± 6.31 £		0.001
Sitting height (cm)	Boys	* 74.66 ± 4.49	0.034	* 83.21± 2.71	0.016	* 91.37 ± 4.46 †	0.001	0.001
	Girls	76.44 ± 3.50		82.20 ± 2.70		86.33 ± 2.93 £		0.001
Leg length (cm)	Boys	* 80.60 ± 8.30	0.048	* 87.63 ± 6.22	0.001	* 96.19 ± 6.00 †	0.001	0.001
	Girls	81.46 ± 7.58		81.59± 4.89		82.10 ± 4.98		0.764
Body mass index (kg·m−2)	Boys	20.25 ± 3.22 *	0.044	21.34 ± 3.47	0.654	22.33± 2.92 †	0.118	0.001
	Girls	20.08 ± 2.61		21.57 ± 3.11		23.07 ± 3.24 £		0.001
Fat mass (kg)	Boys	8.94 ± 4.27	0.413	* 9.44 ± 3.75	0.028	12.77 ± 4.86 †	0.406	0.001
	Girls	8.39 ± 2.74		10.58 ± 2.89		12.05 ± 5.95 £		0.001
Fat-free mass (kg)	Boys	* 40.08 ± 6.56	0.042	* 52.86 ± 8.18	0.001	* 65.84 ± 8.80 †	0.001	0.001
	Girls	41.46 ± 6.43		47.39 ± 7.32		53.30 ± 6.75 £		0.001
Body fat percentage (%)	Boys	* 17.61 ± 6.09	0.038	* 14.83 ± 4.38	0.001	* 15.99 ± 4.51 †	0.002	0.006
	Girls	16.38 ± 3.01		17.84 ± 2.42		17.60 ± 2.45 £		0.003
Wing span (cm)	Boys	* 161.28 ± 10.12	0.042	* 175.50 ± 9.28	0.001	* 192.07 ± 8.87 †	0.001	0.001
	Girls	161.35 ± 8.18		168.53± 7.09		171.85 ± 8.03 £		0.001
Leg muscle volume (mL)	Boys	* 3678.22 ± 1473.80	0.040	* 5451.95 ± 2012.74	0.001	* 5148.17 ± 2036.57 †	0.036	0.001
	Girls	3454.95 ± 1301.91		4461.39 ± 1926.49		4544.82 ± 1930.79 £		0.001

Note: Early-maturing (−3 years > −1 years from PHV); on-time-maturing (−1 to +1 years from PHV); late-maturing (>1 to +3 years from PHV). “†”: Significant difference between early-maturing, on-time-maturing, and late-maturing boys (p < 0.05). “*”: Significant difference between boys and girls in the same category; “£”: Significant difference between early-maturing, on-time-maturing, and late maturing girls (p < 0.05). p values ^a: values of significance between genders in the same maturity status; p values ^b: values of significance between maturity status for boys and girls.

. All players were categorized as early-, on-time-, and late-maturing. Regardless of gender, an increase in anthropometric parameters was observed across the early-, on-time-, and late-maturity status groups. Additionally, there were significant differences in most anthropometric parameters between the sexes (p < 0.05) across the different maturity status groups, except for body mass index. Boys were significantly taller and heavier compared to girls (see Table 1). For example, post hoc analysis indicated that anthropometric variables were significantly higher in late-maturing players compared to early- and on-time-maturing players.

3.2. Differences in Physical Performance Variables Based on Maturity Status and Gender

All subjects performed all exercise tests, and their physical performance results are summarized in

Table 2. Physical and physiological performances in basketball Tunisian players classified by age and gender.

Maturity Status		Early-Maturing	p Values a	On-Time-Maturing	p Values a	Late-Maturing	p Values a	p Values b
VO2max (ml·min−1·kg−1)	Boys	* 40.85 ± 2.66	0.001	* 42.93 ± 3.68	0.001	* 44.95 ± 4.13 †	0.001	0.001
	Girls	37.05 ± 2.91		38.33 ± 4.17		39.88 ± 3.28 £		0.001
MAV (km·h−1)	Boys	* 11.67 ± 0.76	0.001	* 12.26 ± 1.05	0.001	* 12.84 ± 1.18 †	0.001	0.001
	Girls	10.58 ± 0.83		10.97 ± 1.15		11.40 ± 0.90 £		0.001
SJ height (cm)	Boys	20.56 ± 5.17	0.782	* 26.03 ± 6.18	0.001	* 30.78 ± 5.53 †	0.001	0.001
	Girls	20.33 ± 3.37		19.88 ± 4.40		20.89 ± 3.55		0.233
CMJ height (cm)	Boys	21.54 ± 5.59	0.487	* 27.57 ± 6.14	0.001	* 31.77 ± 6.08 †	0.001	0.001
	Girls	20.89 ± 4.11		21.25 ± 4.51		21.97 ± 4.04		0.282
SJ height-S (cm)	Boys	24.56 ± 6.55	0.265	* 32.30 ± 7.41	0.001	* 35.47± 6.51 †	0.001	0.001
	Girls	23.41± 4.27		24.83 ± 5.63		25.41± 4.48£		0.048
CMJ height-S (cm)	Boys	25.03 ± 6.94	0.417	* 33.60 ± 7.59	0.001	* 36.86 ± 7.08 †	0.001	0.001
	Girls	24.14 ± 4.35		26.07 ± 5.55		26.39 ± 4.60 £		0.017
SJ Power (W·kg−1)	Boys	10.72 ± 1.54	0.439	* 12.30 ± 1.76	0.001	* 14.40 ± 2.37 †	0.001	0.001
	Girls	10.53 ± 1.10		10.42 ± 1.44		10.81 ± 1.04		0.104
CMJ Power (W·kg−1)	Boys	11.11 ± 1.81	0.732	* 13.01 ± 1.92	0.001	* 15.74 ± 3.51 †	0.001	0.001
	Girls	11.01 ± 1.32		10.90 ± 1.32		11.23 ± 1.44		0.288
SJ Power-S (W·kg−1)	Boys	11.79 ± 1.68	0.111	* 13.79 ± 2.01	0.001	* 15.21± 2.02 †	0.001	0.001
	Girls	11.34 ± 1.26		11.66 ± 1.46		11.73 ± 1.20		0.189
CMJ Power-S (W·kg−1)	Boys	12.02 ± 1.76	0.710	* 14.27 ± 2.11	0.001	* 15.90 ± 2.66 †	0.001	0.001
	Girls	11.92 ± 1.04		12.29 ± 1.56		12.17 ± 1.37		0.278
Five-Jump test (m)	Boys	8.57 ± 1.31	0.054	* 9.95 ± 1.45	0.001	* 11.82 ± 1.30 †	0.001	0.001
	Girls	8.17 ± 0.73		8.67 ± 0.84		8.69 ± 0.66 £		0.001
5 m sprint time (s)	Boys	* 1.30 ± 0.22	0.003	* 1.19 ± 0.12	0.001	* 1.19 ± 0.17 †	0.001	0.001
	Girls	1.46 ± 0.31		1.39 ± 0.20		1.30 ± 0.10 £		0.001
10 m sprint time (s)	Boys	* 2.17 ± 0.33	0.001	* 2.01± 0.19	0.001	* 1.97 ± 0.24 †	0.001	0.001
	Girls	2.63 ± 0.45		2.39 ± 0.34		2.27 ± 0.14 £		0.001
20 m sprint time without the ball (s)	Boys	* 3.96 ± 0.37	0.025	3.53 ± 0.34	0.074	* 3.38 ± 0.27 †	0.001	0.001
	Girls	4.12 ± 0.38		4.52 ± 4.98		3.81 ± 0.23		0.304
20 m sprint time with the ball (s)	Boys	* 4.23 ± 0.39	0.001	* 3.85 ± 0.40	0.001	* 3.74 ± 1.00 †	0.001	0.001
	Girls	4.62 ± 0.44		4.40 ± 0.53		4.15 ± 0.26 £		0.001
Agility test (s)	Boys	* 12.37 ± 0.77	0.001	* 11.85 ± 1.33	0.001	* 10.91 ± 0.86 †	0.001	0.001
	Girls	13.85 ± 1.13		13.27 ± 1.32		12.87 ± 0.89 £		0.001
Flexibility (cm)	Boys	−2.61 ± 8.11	0.275	* −2.41 ± 7.44	0.015	* −0.09 ± 9.88	0.008	0.122
	Girls	−4.43 ± 9.41		0.82 ± 9.45		3.29 ± 7.82 £		0.001

Note: VO_2max: maximum oxygen uptake; MAV: maximum aerobic velocity; SJ: squat jump; CMJ: counter movement jump; height-S: counter movement jump with arm swing; Power-S: relative power with arm swing. “*”: Significant difference between boys and girls in the same age category (p < 0.05). “†”: Boys: Bonferroni’s test for age category vs. previous age category (p < 0.05). “£”: Girls: Bonferroni’s test for age category vs. previous age category (p < 0.05). p values ^a: values of significance in the same maturity status; p values ^b: values of significance between maturity status for boys and girls.

. Our results revealed significant differences between the three maturity categories for all performance parameters (p < 0.05), except for SJ height, CMJ height, SJ power, CMJ power, and 20 m sprints, both with and without the ball, for girls (see Table 2). Higher values for most physical parameters were observed in the late-maturing groups, indicating higher activity levels compared to average- or early-maturing groups. For example, faster sprint times over 5 m, 10 m, and 20 m, as well as better agility test results, were measured for the later-maturing players compared to the earlier-maturing players. Student’s unpaired t-tests showed no significant sex differences in the early-maturing groups.

3.3. Pearson’s Correlation Coefficients Among Anthropometric and Physical Performance Parameters and Chronological Age

Pearson’s correlation coefficients were calculated to assess and measure the influence of the interaction between chronological age and anthropometric and vertical jumping parameters. Pearson’s correlations of the anthropometric variables and chronological age in the basketball players are displayed in

Table 3. Coefficients of correlation between anthropometric parameters and chronological age.

Anthropometric Parameters	Gender	Chronological Age	p
Body mass (kg)	Boys	0.625	0.001
	Girls	0.360	0.001
Standing height (cm)	Boys	0.749	0.001
	Girls	0.420	0.001
Sitting height (cm)	Boys	0.682	0.001
	Girls	0.559	0.001
Leg length (cm)	Boys	0.658	0.001
	Girls	0.044	0.502
Body mass index (kg·m−2)	Boys	0.159	0.014
	Girls	0.238	0.001
Fat mass (kg)	Boys	0.222	0.001
	Girls	0.167	0.011
Fat-free mass (kg)	Boys	0.685	0.001
	Girls	0.404	0.001
Body fat percentage (%)	Boys	−0.157	0.015
	Girls	0.039	0.561
Wingspan (cm)	Boys	0.692	0.001
	Girls	0.301	0.001
Leg muscle volume (mL)	Boys	0.001	0.985
	Girls	0.086	0.195

. Anthropometric variables were significantly and positively correlated with chronological age, except for body fat percentage in boys (r = −0.15; p < 0.05). The basketball players presented statistically significant correlation coefficients (p < 0.05) with all the measured physical and physiological parameters except the times for agility and the 5 m, 10 m, and 20 m sprints both with and without the ball, which correlated negatively with age (−0.275 < r < −0.09; p < 0.05) (

Table 4. Coefficients of correlation between performance parameters and chronological age.

Physical Performance Parameters	Gender	Chronological Age	p
VO2max (ml·min−1·kg−1)	Boys	0.506	0.001
	Girls	0.346	0.001
MAV (km·h−1)	Boys	0.506	0.001
	Girls	0.353	0.001
SJ height (cm)	Boys	0.590	0.001
	Girls	0.217	0.001
CMJ height (cm)	Boys	0.581	0.001
	Girls	0.253	0.502
SJ height-S (cm)	Boys	0.448	0.001
	Girls	0.267	0.001
CMJ height-S (cm)	Boys	0.443	0.001
	Girls	0.276	0.011
SJ Power (W·kg−1)	Boys	0.660	0.001
	Girls	0.205	0.002
CMJ Power (W·kg−1)	Boys	0.686	0.001
	Girls	0.195	0.003
SJ Power-S (W·kg−1	Boys	0.501	0.001
	Girls	0.188	0.004
CMJ Power -S (W·kg−1)	Boys	0.509	0.001
	Girls	0.124	0.061
Five-Jump test (m)	Boys	0.744	0.001
	Girls	0.338	0.001
5 m sprint time (s)	Boys	−0.275	0.001
	Girls	−0.298	0.001
10 m sprint time (s)	Boys	−0.349	0.001
	Girls	−0.417	0.001
20 m sprint time without the ball (s)	Boys	−0.550	0.001
	Girls	−0.090	0.173
20 m sprint time with the ball (s)	Boys	−0.210	0.001
	Girls	−0.465	0.001
Agility test (s)	Boys	−0.573	0.001
	Girls	−0.396	0.001
Flexibility (cm)	Boys	0.250	0.001
	Girls	0.252	0.001

Note: VO_2max: maximum oxygen uptake; MAV: maximum aerobic velocity; SJ: squat jump; CMJ: counter movement jump; height-S: counter movement jump with arm swing; Power-S: relative power with arm swing.

).

3.4. Anthropometric and Physical Parameters According to Chronological Age and/or Maturity Status Within Each Test Cluster

MANOVA (multivariate analysis of variance) was used to analyze the differences in anthropometric and performance parameters according to chronological age and/or maturity status within each test cluster. The results of the main and interaction effects, as well as effect sizes (η²), are presented in Table 3 and Table 4. The output of the MANOVA indicates that effect sizes (η²) less than 0.06 are considered small effects, those between 0.06 and 0.14 as moderate effects, and those greater than 0.15 as large effects for anthropometric and physical parameters.

3.4.1. Interaction Effects of Chronological Age and Maturity Factors

The results demonstrated a significant interaction between age and maturity in certain anthropometric variables, including standing height, sitting height, leg length, fat-free mass, wingspan, and leg muscle volume (as shown in

Table 5. Results of MANOVA analyses examining the difference in anthropometric variables according to age category and/or maturity status per test cluster.

		MANOVA Age × Maturity		MANOVA Age		MANOVA Maturity
		[F (p)]	η2	[F (p)]	η2	[F (p)]	η2
Body mass (kg)	Boys	1.694 (0.124)	0.044	2.506 (0.005) *	0.112	20.458 (0.001) *	0.157
	Girls	2.445 (0.035)	0.055	4.121 (0.001) *	0.177	5.727 (0.004) *	0.051
Standing height (cm)	Boys	1.874 (0.086)	0.049	2.993 (0.001) *	0.131	21.008 (0.001) *	0.161
	Girls	3.146 (0.009) *	0.069	3.636 (0.001) *	0.159	3.904 (0.022) *	0.036
Sitting height (cm)	Boys	3.528 (0.002) *	0.088	3.071 (0.001) *	0.134	84.000 (0.001) *	0.434
	Girls	2.650 (0.024) *	0.059	3.785 (0.001) *	0.165	35.415 (0.001) *	0.251
Leg length (cm)	Boys	4.269 (0.001) *	0.105	5.236 (0.001) *	0.208	0.062 (0.940)	0.001
	Girls	3.173 (0.009) *	0.070	6.349 (0.001) *	0.249	15.942 (0.001) *	0.131
Body mass index (kg·m−2)	Boys	0.871 (0.517)	0.023	1.776 (0.060) *	0.082	5.270 (0.006) *	0.046
	Girls	1.742 (0.126)	0.040	2.661 (0.003) *	0.122	2.685 (0.071)	0.025
Fat mass (kg)	Boys	0.556 (0.765)	0.015	0.710 (0.728)	0.034	6.358 (0.002) *	0.055
	Girls	1.918 (0.093)	0.043	3.170 (0.001) *	0.142	3.262 (0.040) *	0.030
Fat-free mass (kg)	Boys	2.439 (0.027) *	0.063	4.597 (0.001) *	0.188	24.238 (0.001) *	0.181
	Girls	2.551 (0.029) *	0.057	3.115 (0.001) *	0.140	4.899 (0.008) *	0.044
Body fat percentage (%)	Boys	0.815 (0.559)	0.022	1.443 (0.155)	0.068	2.570 (0.079)	0.023
	Girls	2.049 (0.073)	0.046	3.666 (0.001) *	0.160	3.045 (0.050) *	0.028
Wing span (cm)	Boys	2.571 (0.020)*	0.066	3.016 (0.001) *	0.132	15.024 (0.001) *	0.121
	Girls	1.205 (0.308)	0.028	4.004 (0.001) *	0.173	2.583 (0.078)	0.024
Leg muscle volume (mL)	Boys	2.945 (0.009)*	0.075	1.718 (0.071)	0.079	4.863 (0.009) *	0.043
	Girls	1.083 (0.371)	0.025	3.012 (0.001)*	0.136	1.959 (0.144)	0.018

Note: multivariate F statistics. *—p < 0.05.

). In contrast, no age-by-maturity interactions were observed for any physical performance parameters (p > 0.05) (refer to

Table 6. Results of MANOVA analyses examining the difference in physical performances according to age category and/or maturity status per test cluster.

		MANOVA Age × Maturity		MANOVA Age		MANOVA Maturity
		[F (p)]	η2	[F (p)]	η2	[F (p)]	η2
VO2max (mL·min−1·kg−1)	Boys	1.712 (0.119)	0.045	2.950 (0.001) *	0.130	0.442 (0.643)	0.004
	Girls	1.242 (0.291)	0.029	1.262 (0.248)	0.062	0.696 (0.500)	0.007
MAV (km·h−1)	Boys	1.712 (0.119)	0.045	2.950 (0.001) *	0.130	0.442 (0.643)	0.004
	Girls	1.262 (0.282)	0.029	1.301 (0.225)	0.064	0.786 (0.457)	0.007
SJ height (cm)	Boys	0.494 (0.812)	0.013	2.740 (0.002)*	0.122	0.883 (0.415)	0.008
	Girls	0.358 (0.877)	0.008	1.571 (0.109)	0.076	1.010 (0.366)	0.010
CMJ height (cm)	Boys	0.769 (0.595)	0.021	3.462 (0.001) *	0.149	1.130 (0.325)	0.010
	Girls	1.363 (0.239)	0.031	1.870 (0.045) *	0.089	1.198 (0.304)	0.011
SJ Power (W·kg−1)	Boys	0.823 (0.553)	0.022	4.529 (0.001) *	0.187	0.961 (0.384)	0.009
	Girls	0.228 (0.950)	0.005	0.962 (0.483)	0.048	0.674 (0.511)	0.006
CMJ Power (W·kg−1)	Boys	0.636 (0.701)	0.017	5.566 (0.001) *	0.220	0.982 (0.376)	0.009
	Girls	1.345 (0.246)	0.031	1.638 (0.090)	0.079	1.384 (0.253)	0.013
SJ height-S (cm)	Boys	0.673 (0.672)	0.018	2.767 (0.002) *	0.123	1.976 (0.141)	0.018
	Girls	0.703 (0.622)	0.016	1.496 (0.135)	0.073	2.472 (0.087)	0.023
CMJ height-S (cm)	Boys	0.808 (0.565)	0.022	2.596 (0.004) *	0.116	1.288 (0.278)	0.012
	Girls	1.641 (0.150)	0.038	1.342 (0.203)	0.066	3.767 (0.025) *	0.035
SJ Power-S (W·kg−1)	Boys	0.403 (0.876)	0.011	2.187 (0.016) *	0.100	0.917 (0.401)	0.008
	Girls	0.334 (0.892)	0.008	1.235 (0.265)	0.061	1.794 (0.169)	0.017
CMJ Power -S (W·kg−1)	Boys	0.364 (0.901)	0.010	2.391 (0.008) *	0.108	0.930 (0.396)	0.008
	Girls	0.884 (0.492)	0.021	1.049 (0.405)	0.052	2.556 (0.080)	0.024
Five-Jump test (m)	Boys	1.196 (0.309)	0.032	8.010 (0.001) *	0.289	0.148 (0.863)	0.001
	Girls	1.478 (0.198)	0.034	1.255 (0.253)	0.062	1.906 (0.151)	0.018
5m sprint time (s)	Boys	0.342 (0.914)	0.009	1.633 (0.091)	0.076	0.876 (0.418)	0.008
	Girls	0.517 (0.763)	0.012	0.519 (0.889)	0.026	0.344 (0.709)	0.003
10 m sprint time(s)	Boys	0.243 (0.961)	0.007	1.501 (0.133)	0.071	1.358 (0.259)	0.012
	Girls	0.843 (0.520)	0.020	1.517 (0.127)	0.074	0.722 (0.487)	0.007
20 m sprint time without the ball (s)	Boys	3.567 (0.002) *	0.090	4.600 (0.001) *	0.189	1.335 (0.265)	0.012
	Girls	0.318 (0.902)	0.008	0.162 (0.999)	0.008	0.072 (0.931)	0.001
20 m sprint time with the ball (s)	Boys	0.378 (0.892)	0.010	1.098 (0.364)	0.053	0.182 (0.834)	0.002
	Girls	3.122 (0.010) *	0.069	0.941 (0.502)	0.047	0.213 (0.808)	0.002
Agility test (s)	Boys	1.266 (0.274)	0.034	4.021 (0.000) *	0.169	0.293 (0.746)	0.003
	Girls	0.638 (0.671)	0.015	1.955 (0.034) *	0.093	0.074 (0.929)	0.001
Flexibility (cm)	Boys	0.963 (0.452)	0.026	2.277 (0.012) *	0.103	0.555 (0.575)	0.005
	Girls	0.514 (0.766)	0.012	0.668 (0.768)	0.034	0.729 (0.484)	0.007

Note: multivariate F statistics. * indicates significant results (p < 0.05) VO_2max: maximum oxygen uptake; MAV: maximum aerobic velocity; SJ: squat jump; CMJ: counter movement jump; height-S: counter movement jump with arm swing; Power-S: relative power with arm swing.

).

3.4.2. Effects of Chronological Age

The main effects of chronological age were observed for all anthropometric variables (p < 0.05; η² ranging from 0.01 to 0.43), except for body fat percentage, fat mass, and leg muscle volume (as indicated in Table 5). However, significant effects of chronological age on physical parameters were observed, except for those in girls (as shown in Table 6).

3.4.3. Effects of Maturity Status

The main effects of maturity were observed for all anthropometric parameters (p < 0.05), except for body fat percentage and leg length in boys and body mass index, wingspan, and leg muscle volume in girls (p > 0.05) (as seen in Table 5). In contrast, maturity status had no effect on any physical performance parameters, except for CMJ height in girls (as shown in Table 6).

3.5. Percentile Values Based on Maturity Status and Gender

Table 7. Percentile values for physical performance based on maturity status and gender.

		Boys							Girls
Variables	Maturity Status	5%	10%	25%	50%	75%	90%	95%	5%	10%	25%	50%	75%	90%	95%
VO2max (ml·min−1·kg−1)	Early	36.75	36.78	38.50	40.95	42.00	45.32	46.13	33.25	34.47	35.00	36.75	38.50	41.65	43.57
	On-Time	35.63	36.75	40.25	43.75	45.50	47.25	47.25	31.50	33.25	35.00	38.50	40.60	43.75	46.09
	Late	36.75	40.25	42.00	45.50	47.77	50.75	50.75	35.00	35.00	38.50	40.25	42.00	44.03	46.48
MAV (km·h−1)	Early	10.50	10.51	11.00	11.70	12.00	12.95	13.18	9.50	9.85	10.00	10.50	11.00	11.90	12.45
	On-Time	10.18	10.50	11.50	12.50	13.00	13.50	13.50	9.07	9.50	10.00	11.00	11.60	12.50	13.17
	Late	10.50	11.50	12.00	13.00	13.65	14.50	14.50	10.00	10.24	11.00	11.50	12.00	12.58	13.06
SJ height (cm)	Early	13.08	14.70	16.20	20.40	24.30	28.37	31.00	13.99	16.10	18.40	19.90	22.40	24.44	26.96
	On-Time	16.79	17.10	22.40	26.40	30.72	35.74	36.77	11.81	14.16	16.52	19.95	23.20	25.38	26.72
	Late	20.91	22.64	27.30	30.60	33.60	37.48	39.00	15.10	15.36	18.80	20.80	22.70	25.80	27.12
CMJ height (cm)	Early	13.85	14.90	17.10	20.05	25.27	29.09	31.40	14.50	16.70	17.70	20.20	24.10	27.44	28.50
	On-Time	18.10	18.78	22.64	28.10	32.90	35.01	38.00	12.99	15.75	18.07	21.00	24.60	26.57	28.84
	Late	21.90	22.42	28.80	32.50	34.38	39.50	41.10	15.30	16.20	19.10	21.70	24.80	27.20	29.96
SJ Power (W·kg−1)	Early	8.41	9.00	9.49	10.69	11.60	12.99	13.40	8.44	8.92	9.95	10.41	11.28	11.73	12.87
	On-Time	9.08	9.94	11.23	12.27	13.47	14.80	15.08	7.73	8.38	9.37	10.60	11.45	12.03	12.76
	Late	11.13	11.55	12.80	14.18	15.50	16.87	20.30	9.10	9.19	10.04	10.84	11.79	12.13	12.77
CMJ Power (W·kg−1)	Early	8.64	9.49	9.72	10.73	12.45	13.30	14.22	9.01	9.70	10.10	10.72	11.84	13.14	13.57
	On-Time	9.88	10.38	11.63	13.08	14.24	15.47	16.70	8.54	8.96	9.96	10.99	12.00	12.57	12.94
	Late	11.47	12.17	13.58	14.74	16.86	20.77	23.91	8.96	9.58	10.12	11.10	12.50	13.14	13.54
SJ height-S (cm)	Early	14.13	16.50	20.00	23.70	30.20	32.10	38.07	16.39	17.38	19.80	23.50	25.40	29.60	33.17
	On-Time	19.29	22.00	26.42	32.78	37.25	41.75	44.38	13.42	17.43	21.97	25.06	27.57	32.07	35.01
	Late	25.44	28.20	32.02	34.00	38.90	44.88	46.68	17.62	19.26	22.60	25.40	28.60	30.93	33.10
CMJ height-S (cm)	Early	15.17	16.20	19.70	23.30	30.90	33.40	39.56	18.50	19.20	20.78	23.10	27.35	31.00	33.30
	On-Time	19.92	23.30	27.87	33.80	38.24	42.85	47.03	16.27	17.59	22.87	25.68	29.92	33.16	35.25
	Late	24.94	27.00	33.18	34.80	41.37	47.50	50.59	18.50	19.48	23.20	26.90	29.40	32.60	33.83
SJ Power-S (W·kg−1)	Early	8.82	9.85	10.63	11.45	12.78	14.03	14.90	9.42	9.63	10.39	11.31	12.15	13.29	13.37
	On-Time	10.12	10.65	12.42	14.05	15.14	16.28	16.89	8.66	9.97	10.86	11.75	12.52	13.66	14.05
	Late	12.70	13.17	13.97	14.85	16.21	17.89	18.88	9.63	10.04	11.04	11.74	12.77	13.43	13.55
CMJ Power -S (W·kg−1)	Early	9.13	9.58	10.85	11.92	13.49	14.29	15.10	10.36	10.48	11.10	12.15	12.53	13.31	13.89
	On-Time	10.92	11.30	13.07	14.62	15.53	16.83	17.94	9.42	9.93	11.47	12.33	13.11	14.19	14.90
	Late	12.64	13.09	14.49	15.45	16.98	18.93	21.04	9.71	10.06	11.28	12.12	13.00	13.57	14.43
Five-Jump test (m)	Early	6.88	7.30	7.90	8.50	8.95	9.39	10.22	6.52	7.40	7.80	8.10	8.60	9.10	9.31
	On-Time	7.38	8.00	9.00	9.90	10.97	11.80	12.33	7.20	7.73	8.17	8.70	9.20	9.91	10.18
	Late	9.63	10.26	11.07	11.94	12.55	13.10	13.80	7.54	7.88	8.10	8.80	9.20	9.42	9.60
5m sprint time (s)	Early	0.86	0.88	1.19	1.38	1.41	1.55	1.80	1.15	1.19	1.30	1.39	1.55	1.67	2.55
	On-Time	0.98	1.02	1.11	1.20	1.29	1.37	1.43	1.12	1.19	1.26	1.36	1.50	1.60	1.72
	Late	0.95	1.01	1.10	1.16	1.27	1.34	1.49	1.11	1.16	1.24	1.30	1.39	1.42	1.47
10 m sprint time (s)	Early	1.28	1.45	2.06	2.28	2.37	2.45	2.52	2.01	2.09	2.22	2.73	2.98	3.13	3.55
	On-Time	1.67	1.77	1.89	2.03	2.12	2.28	2.38	2.05	2.12	2.20	2.30	2.46	3.00	3.20
	Late	1.66	1.71	1.83	1.96	2.13	2.22	2.33	2.08	2.10	2.16	2.25	2.38	2.48	2.51
20 m sprint time without the ball (s)	Early	3.21	3.46	3.77	3.95	4.20	4.43	4.51	3.58	3.71	3.86	4.04	4.36	4.69	5.00
	On-Time	3.02	3.08	3.27	3.49	3.73	4.05	4.16	3.51	3.60	3.74	3.94	4.14	4.59	4.76
	Late	3.02	3.13	3.23	3.34	3.49	3.78	3.82	3.42	3.49	3.68	3.80	3.90	4.16	4.24
20 m sprint time with the ball (s)	Early	3.40	3.69	3.99	4.27	4.53	4.78	4.81	3.98	4.07	4.24	4.62	5.00	5.19	5.38
	On-Time	3.35	3.39	3.48	3.78	4.13	4.42	4.72	3.79	3.86	4.06	4.31	4.63	4.99	5.88
	Late	3.20	3.27	3.40	3.48	3.71	3.98	4.88	3.67	3.85	4.00	4.19	4.27	4.47	4.65
Agility test (s)	Early	10.76	10.92	11.89	12.40	12.95	13.45	13.50	11.58	12.64	13.14	13.68	14.54	15.21	16.55
	On-Time	9.69	10.30	11.03	11.80	12.46	13.74	14.26	10.53	11.69	12.48	13.30	14.28	14.80	15.50
	Late	9.79	10.01	10.36	10.77	11.39	12.03	12.87	11.34	11.70	12.20	12.88	13.51	14.06	14.41
Flexibility (cm)	Early	−18.80	−13.90	−10.25	0.00	0.50	6.35	12.00	−20.00	−16.40	−11.00	−4.00	1.00	6.90	10.90
	On-Time	−15.00	−15.00	−8.00	0.00	3.00	5.05	7.00	−21.10	−12.40	−5.00	2.50	7.00	9.00	14.00
	Late	−18.95	−15.00	−3.87	0.00	6.75	10.90	14.90	−14.60	−9.00	0.00	5.00	8.00	11.00	14.20

Note: VO_2max: maximum oxygen uptake; MAV: maximum aerobic velocity; SJ: squat jump; CMJ: counter movement jump; height-S: counter movement jump with arm swing; Power-S: relative power with arm swing.

presents the 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentile values for physical and physiological performance categorized by gender and maturity status for Tunisian basketball players.

4. Discussion

The main results of the current study were as follows: (i) the anthropometric and physical performance variables significantly improved with consecutive maturity status from early, to average, to late maturity status, with late-maturing boys tending to achieve significantly higher values than their female counterparts; (ii) the interaction between maturity status and chronological age had no significant effect on the physical performance parameters. This research established percentile values for physiological and physical performance based on maturity status and gender in Tunisian basketball players aged 9–21 years.

4.1. Anthropometric and Physical Parameters According to Maturity and Gender

This research showed that most of the players’ anthropometric parameters significantly increased across consecutive maturity statuses for both sexes. This result aligns with the literature reporting similar findings in Tunisian adolescent handball and soccer players [22,40]. As expected, maturity status influenced the anthropometric profile and body composition of the basketball players. The statistical analysis indicated higher values in most of the measured body size parameters, particularly in the post-PHV group compared to the pre- and circa-PHV groups.

Biological maturation is closely associated with adolescent growth and functional performance. The adolescent growth spurt, characterized by an accelerated increase in body size, height, and skeletal dimensions, has significant implications for basketball performance. During growth, the same hormones regulate skeletal, somatic, and sexual maturation. In addition, environmental and genetic factors are implicated, as well as societal and cultural factors. Consistent with our results, prior to adolescence, leg length influences sprint performance [41]. For example, males generally have shorter legs than females during pre-PHV period. However, adolescent females have shorter legs relative to their height compared to males of the same stature. Furthermore, participants with longer legs tend to have faster sprint times [42]. Similarly, a longer wingspan provides an advantage in tests where the arms are used, aligning with our findings in this research.

Growth and maturation process are related, and both significantly influence physical performance. In basketball, the period from 11 to 14 years (which corresponds to the early and average maturity status in our study) is marked by intense athletic development. Talent identification should be identified at these two biological maturity groups. The timing of puberty varies, and recent studies indicate that puberty onset occurs earlier in girls compared to boys [43]. Gender differences in athletic performance typically begin to emerge around ages 12–13 years and reach an adult plateau in the late teenage years, corresponding to an increase in circulating testosterone hormone in males during puberty [44]. As discussed below, physical activity during puberty can be influenced by many factors. These findings are in accordance with a study performed by Benedit et al. [45], which demonstrated that early-maturing girls tend to have excess body weight and greater height, while late-maturing girls show a lower prevalence of excess weight and reduced height [45]. In contrast with the above studies, heavier and taller table tennis players tend to be in an advanced maturity status [46].

Our results are in contrast with the study of Adami et al. [47], who reported that adolescent boys and girls in the early stages of pubertal development exhibited higher percentages of fat adiposity. Specifically, among females, a decrease in the percentage of excess adiposity was observed alongside a reduced occurrence of early pubertal development stages. In contrast, our findings align with those of Zheng et al. [48], who presented a negative association between fat percentage and early puberty for boys. However, positive associations were found between body fat percentage and early puberty in girls. Our findings emphasize the gender differences in the relationship between body composition and pubertal stages.

Gender-based differences in the development of physical performance may be attributed to variations in neuromuscular patterns and maturation development from childhood through adolescence. In the current study, faster sprint times, greater jump heights, and increased power were observed in late-maturing boys compared to their early- and average-maturing peers. These findings align with a study by Radnor et al. [49], which demonstrated moderate differences between early- and average-maturing adolescents, as well as between average- and late-maturing adolescents, with moderate-to-large differences between early- and late-maturing adolescents in the majority of jump and sprint parameters. These differences may be explained by variations in muscle architecture across consecutive maturity status groups. More precisely, post-PHV (peak height velocity) boys presented larger muscle architecture variables compared to pre-PHV boys, including increases in muscle mass, volume, tendon cross-sectional area, and tendon stiffness. Moreover, they also displayed greater thickness, angle of pinnation, and fascicle lengths in the gastrocnemius medialis and vastus lateralis muscles compared to less mature boys [50]. These studies suggest that an increase in muscle size resulting from athletic training could be an additional mechanism for enhancing muscle strength in players.

Many sports systems assume that physical maturity directly correlates with athletic ability, but this does not always apply to female athletes [41]. Female athletes experience significant biological and physiological changes during puberty, which occur at different times for everyone. These changes can greatly influence performance. Because the rate of maturation varies, the developmental trajectories of female athletes can differ significantly. For example, an early-maturing athlete may peak earlier, while a late-maturing athlete may continue to improve well into their late teens or early twenties. Although they may show slower progress at younger ages, late-maturing athletes can surpass others as they continue to develop physically, affecting their ability to perform at the same level during adolescence. These varying developmental trajectories affect not only short-term performance but also long-term potential, with some athletes ultimately achieving greater success despite slower early progress [51].

Tracking developmental trajectories involves observing how an athlete’s performance evolves over time in relation to their maturation status. An athlete who appears to underperform in their early teens may be on a positive developmental path that will lead to greater success later. On the other hand, early performance peaks do not always predict future success, as early maturity can sometimes lead to a plateau once physical growth stabilizes. By focusing on developmental trajectories alongside performance metrics, we can create a more inclusive environment for female athletes, acknowledging the wide range of physical and psychological experiences they face during maturation. When evaluating female athletes, it is important for coaches and sports organizations to distinguish between their performance at a specific point in time and their long-term developmental trajectory [52].

4.2. Interaction Effects of the Factors Age and Maturity Status

There was an effect of the interaction between maturity and age, as well as the interaction between chronological age and maturity, on most anthropometric parameters. In contrast, the basketball skills assessed appeared to be independent of pubertal status and the interaction between maturity and age, being more dependent only on chronological age. This finding is further supported by the significant bivariate correlations found between chronological age and anthropometric and physical performance parameters. Moreover, our results are in accordance with research conducted by Tounsi et al. [40] and, more recently, by Aouichaoui et al. [22], who reported a significant effect of the interaction between age and maturity on anthropometric and certain physical performance parameters in Tunisian football and handball players. However, De la Rubia et al. [53] indicated that physical performance parameters in young handball players were more influenced by biological maturity status than by relative age.

4.3. Reference Values Based on Maturity Status and Gender

There is limited research available on different sports populations that simultaneously consider maturity status and gender. A few studies have provided gender- and maturity- or age-specific normative values for children and adolescents in European [54,55,56] and Chinese populations [57].

In terms of established maturity- and gender-specific percentile reference values for physical tests, there is a lack of studies providing such values specifically for basketball players in Tunisia. Normative values have only been established for healthy adolescents and athletic players in general [40,58,59]. More recently, Aouichaoui et al. [22] established normative data for jumping performance in handball players.

The percentile values for Tunisian players allow us to compare local physical performance parameters with those from other countries that have conducted the same physical fitness tests. Additionally, these reference values are useful for assessing performance and evaluating training and interventions, helping to identify players with higher or lower performance. In this context, the percentile values were provided based on internationally comparable standards, which have proven to be successful in measuring physical fitness.

5. Practical Applications

The established percentile values for performance in jumping and sprinting may not directly guarantee future success within the national team program, but they can serve as valuable indicators of an athlete’s potential. High performance in these areas suggests that the athlete possesses the physical attributes necessary to succeed at higher levels of competition. However, these values should not be seen as the sole predictors of future success. Other factors, such as skill development, mental resilience, and tactical understanding, also play a critical role in determining long-term success. These percentile values can help identify basketball athletes who have the physical foundation required to compete at the national level. Additionally, they can serve as a selection tool, ensuring that only athletes who meet certain performance thresholds are given the opportunity to progress to the national team program. However, ongoing development and performance assessments are essential to fully evaluate an athlete’s potential for success at the highest level. These values ensure that training plans are maturity-appropriate, promoting long-term growth and preventing injury.

6. Strengths and Limitations

This research establishes normative performance values based on gender- and maturity-specific benchmarks for Tunisian young basketball players, helping to deepen the understanding of their potential and development. By considering maturity as a factor in performance, we can reduce the risk of disadvantaging or misjudging athletes who may be on a slower, but ultimately more successful, developmental trajectory. More precisely, understanding the developmental trajectory of female athletes is vital for creating effective training programs. Moreover, the large sample size enhances the reliability of the reference values, reinforcing their applicability across different maturity statuses and gender groups. One limitation of this study is its focus on a specific population—Tunisian youth basketball players—which may limit the generalizability of the results to other populations with different training practices and social, ethnic, and genetic factors. Moreover, while this study includes basic anthropometric and performance parameters, future research could benefit from incorporating more advanced psychological and physiological parameters to provide a more comprehensive view of athletic development. Lastly, as a cross-sectional study, it does not account for longitudinal changes within individuals, which would be important for understanding the development of physical performance over time.

7. Conclusions

In conclusion, our study revealed that advanced maturation status in Tunisian basketball players is correlated with more favorable anthropometric and physical fitness parameters. The percentile values based on gender and maturity status offer a potentially valuable reference, which could aid coaches and trainers in quantifying and optimizing training protocols for individual basketball players. Moreover, these references could enhance the selection process for young elite athletes in basketball. Federations and clubs should utilize these reference values to avoid biased selection and the exclusion of potentially talented players due to chronological limitations. These findings underscore the importance of patience in developing less mature, yet talented, players, allowing them the time needed to reach their full potential.