Abstract
The purpose of this study was to compare the differences in physical fitness between different ranked and age youth basketball players. 382 youth basketball players (U18: n = 190; U17: n = 192) participated in the study. Players` sprint, vertical jump, standing long jumps, sit-ups, sit-and-reach and shuttle run were tested before National Tournament Camp. And players were divided into the top 50% and bottom 50% based on team ranking in the tournament table. Independent T test with effect size was used for analysis. Overall, physical fitness profiles were largely similar between U17 and U18 players. U17 players were significantly faster than the U18 players in sprint and shuttle run (p < 0.05, d=-0.60 to -0.87), and their vertical jump was significantly lower than that of U18 players (p < 0.05, d=-0.31). Regarding different rankings, the U17 top ranking players were significantly faster than the bottom ranking players in sprinting speed (p < 0.05, d=-0.29) and had a significantly higher vertical jump height (p < 0.05, d = 0.36) than the bottom ranking players. Besides, all physical abilities were significantly different between positions (p < 0.05) except for sit-and-reach (p > 0.05). These findings indicate that physical fitness characteristics are broadly comparable between elite U17 and U18 basketball players, suggesting that major physical development may have largely stabilized by late adolescence. Positional demands appear to exert a stronger influence on fitness profiles than chronological age or team ranking at this stage.
Keywords: Strength and conditioning, Team rank, Performance, Sprint, Post-pubertal
Introduction
Basketball is a high-intensity intermittent team sport requiring players to repeatedly perform sprinting, jumping, and rapid changes of direction while executing technical and tactical actions [1, 2]. Physical fitness therefore represents a fundamental prerequisite for basketball participation [3, 4] and is widely assessed in youth talent identification and development systems. Previous research has documented differences in physical fitness according to age, playing position, and competitive level in youth basketball players [5–8].
However, most available studies have focused on early- to mid-adolescence (≤ U16), when biological maturation strongly influences physical performance [9, 10]. In contrast, late adolescence (U17–U18) represents a distinct developmental stage in which many athletes have reached or are approaching post-pubertal maturity, and annual improvements in physical fitness may be reduced [11, 12]. Consequently, it remains unclear whether meaningful physical fitness differences persist between adjacent post-pubertal age groups such as U17 and U18, particularly among elite players.
Playing position further shapes physical fitness profiles due to differences in movement demands and tactical roles [13, 14]. While positional differences are well established in adult basketball [15], limited evidence exists regarding whether age-related differences during late adolescence are consistent across positions. Examining age and position simultaneously may therefore clarify how physical development aligns with positional specialization in elite youth players.
Assessing performance in basketball is inherently complex because match outcomes depend on collective team behavior rather than individual output [16, 17]. Although technical and tactical factors are central, physical fitness underpins players’ capacity to repeatedly perform high-intensity actions during competition [2]. Accordingly, team ranking has been used as a pragmatic proxy for competitive performance in youth team sports [6], allowing group-level comparisons without assuming a direct relationship between individual fitness and match success.
A key limitation in youth research is biological maturation, as indicators such as peak height velocity or skeletal age substantially influence physical fitness and positional allocation [9, 18]. However, such data are often unavailable in large-scale testing environments. Therefore, large-sample studies focusing on elite post-pubertal players remain valuable, provided that maturation-related limitations are explicitly acknowledged.
Thus, the purpose of this study was to compare the physical fitness profiles of elite U17 and U18 male basketball players according to playing position and team ranking using a large national-level sample. By jointly examining age group, position, and competitive ranking, this study aims to clarify whether physical fitness continues to differentiate players and teams during late adolescence and to provide applied reference data for coaches working in high-performance youth basketball.
Methods
Sample and variables
Three hundred eighty-two youth basketball players (U18: n = 190, age = 17.0 ± 0.7; U17: n = 192, age = 15.9 ± 0.7) at the highest level in their age categories from 32 teams (16 teams for each age group) who participated in the National Tournament Camp participated in the study. All players came from the national level. Due to the relative ambiguity of the youth players’ positions, they were categorized into only 3 positions, namely center, forward, and guard [19]. All players completed a series of physical fitness and skill tests prior to the tournament, including sprint, vertical jump, standing long jumps, sit-ups, sit-and-reach and shuttle run. Subjects were informed of the risks and benefits of the fitness tests and informed consent was obtained from all subjects or their guardians. The experiment complied with the Declaration of Helsinki, and the protocol was approved by the Ethics Committee of the local university (CQUE-LL20250301003).
Procedure
The fitness test was organized by the Chinese Basketball Association (CBA) and started at 9:00 a.m. 3 days prior to the tournament. The tests were conducted indoors and all the players were tested on the same day. All players had participated in the fitness test many times before and were very familiar with the process. Before the tests, a 15-minute warm-up, including jogging and dynamic stretching, was led by professional staff. The order of testing was as follows: sprint, standing long jump, vertical jump, sit-and-reach, sit-ups and shuttle run. All single tests were performed by the same testers indoor in the morning on the same day. To ensure data quality, all tests were conducted by the same experienced staff using standardaized protocols and calibrated equipment. And each test was performed twice except for the shuttle run and the best result was recorded. In addition, players were categorized into two groups based on their team’s league final table ranking (top 50% and bottom 50%) [20].
3/4 Court Sprint
The test was referenced from the NBA Draft Combine program. The test was conducted by timing photoelectric gates (Brower timing system, USA). Players were asked to sprint at full speed for a distance of 3/4 of the length of the court (22.2 m), starting from a standing start position 0.5 m from the start line to prevent accidental contact with the timing gate. Each athlete was tested twice and the best time will be taken. One minute break between each test. The results were measured in seconds to 2 decimal places.
Standing long jump
A standard measuring tape (validated for youth basketball fitness assessment, consistent with equipment specifications recommended by the Chinese Basketball Association) was used. The athletes jumped forward with both feet from behind the marking line, landed bipedally, and the test result was the distance from the marking line to the point of bipedal contact with the ground. And the unit is accurate to 0.1 cm. Before jumping, both feet are not allowed to step on the line, both feet must land at the same time, and after landing, no backward fall or hands on the ground. Each person will be tested twice, and the best result will be taken. One minute break between each test.
Vertical jump
The vertical jump test employed a standard touch height tester (validated for youth basketball fitness assessment, consistent with equipment specifications recommended by the Chinese Basketball Association). The athlete ran along the running line to the touchdown device, jumps quickly on one foot, raises one arm and touches the highest position of the height instrument with the fingertips (the height above the ground) to record the highest point, and the unit is accurate to 0.1 cm. Each person will be tested twice, and the best result will be taken. One minute break between each test.
Sit-and-reach
The tester sat down barefoot, with both feet against the front of the test device, feet 10–15 cm apart, both knees straight, fingers of one hand on the fingers of the other hand, the upper body flexed forward, tried to touch the device forward and hold on for 2 s, and the unit is accurate to 0.1 cm. Higher values indicate better test results. And positive values represent distances exceeding the toe, while negative values indicate distances gaping away from the toe. Each person will be tested twice, and the best result will be taken. One minute break between each test.
1 min sit-ups
Players on a sponge mat, supine lying flat and both knees curved closed, feet on the mat, hands crossed to hold the head at the back of the head position, into the ready position. Once the test started, players needed to complete as many sit-ups as possible, with requiring elbows must touch the knees, supine shoulder joints, back must be close to the mat into a ready position. The referee would count the number of times the athlete completes the movement in 1 min, and the movements that do not meet the standard will not be counted.
15 m × 17 shuttle run
This test selection is based on the need for repeated sprints during basketball games. The test was conducted on the basketball court. Subjects were asked to run from the sideline of the court to the other sideline (15 m) for 17 times. Upon reaching the sideline, the athletes were required to quickly complete a turn before running toward the opposite sideline. The players must have one foot on the sideline, otherwise, the attempt was considered be counted as a violation. Test results were recorded with a stopwatch and are accurate to 0.1s. All the test conductors have extensive experience in shuttle running test.
Statistical analysis
Data were expressed as mean ± standard deviation. Normality was tested using the Kolmogorov-Smirnov test combined with Q-Q plots. Independent samples t-tests were used to compare differences by age and by ranking. One-way ANOVA and LSD post hoc tests were used to analyze differences between positions. Cohen`s d was used to assess effect sizes on the following rating scale: 0 to 0.19 is trivial, 0.2 to 0.49 is small, 0.5 to 0.79 is middle, and 0.8 or more is large. Pearson correlation coefficients (r) were used to determine the associations between the tests results. The correlation coefficients were ratings as follows: r = 0.1–0.29 = small, 0.3–0.49 = medium, 0.5–0.69 = large, 0.7–0.89 = very large, 0.9–0.99 = almost perfect, and 1 = perfect [21]. Statistical processing was performed using SPSS 26.0 (IBM, Chicago, USA). The level of significance was set at p < 0.05.
Results
Table 1 shows the results of comparisons in different age groups. The U17 players were significantly faster than the U18 players in sprint and shuttle run (p < 0.05, d=-0.60 to -0.87), and their vertical jump was significantly lower than that of U18 players (p < 0.05, d=-0.31). There was no significant difference between the two groups in other indexes.
Table 1.
Comparison of different age groups
| U17 | U18 | P | Cohen`s d | 95%CI | Rating | ||
|---|---|---|---|---|---|---|---|
| Lower | Upper | ||||||
| Height (cm) | 188.2 ± 16.7 | 190.2 ± 7.7 | 0.133 | -0.15 | -0.35 | 0.05 | trivial |
| Weight (kg) | 80.5 ± 19.7 | 81.4 ± 14.9 | 0.588 | -0.05 | -0.25 | 0.15 | trivial |
| Sprint (s) | 3.36 ± 0.21 | 3.53 ± 0.18 | < 0.001 * | -0.87 | -1.08 | -0.66 | Large |
| Standing Long Jump (cm) | 258.3 ± 16.4 | 256.2 ± 18.0 | 0.226 | 0.12 | -0.08 | 0.32 | trivial |
| Vertical Jump (cm) | 324.3 ± 12.0 | 328.1 ± 12.3 | 0.002 * | -0.31 | -0.51 | -0.11 | Small |
| Sit-and-Reach (cm) | -16.4 ± 6.9 | -17.0 ± 6.3 | 0.364 | 0.09 | -0.11 | 0.29 | trivial |
| Sit-Ups (n) | 40.9 ± 9.4 | 40.7 ± 10.2 | 0.853 | 0.02 | -0.18 | 0.22 | trivial |
| Shuttle Run (s) | 58.4 ± 2.9 | 60.2 ± 3.1 | < 0.001 * | -0.60 | -0.80 | -0.40 | Moderate |
* denotes significant difference
Figures 1 and 2 show the comparison of the fitness of players in different positions in the U17 and U18 groups. The results of one-way ANOVA showed that all physical abilities were significantly different between positions (p < 0.05) except for sit-and-reach (p > 0.05). The post-hoc results showed that U17 and U18 centers were significantly slower than forwards and guards in terms of sprint and shuttle run speed (p < 0.05, d = 0.42 to 1.47), standing long jump was significantly lower than forwards and guards (p < 0.05, d = 0.55 to 0.76), sit-ups was significantly lower than forwards and guards (p < 0.05, d = 0.46 to 0.81) and vertical jump height was significantly higher than forwards and guards (p < 0.05, d = 0.44 to 1.46). U17 guards sprinted significantly faster than forwards (p < 0.05, d = 0.45), and U17 and U18 guards had significantly faster shuttle run speed than forwards (p < 0.05, d = 0.45 to 0.49).
Fig. 1.
Comparison of fitness by position for U17 players
Fig. 2.
Comparison of fitness by position for U18 players
Table 2 shows a comparison of the fitness of different ranked players in the U17 and U18 categories. The U17 top ranking players were significantly faster than the bottom ranking players in sprinting speed (p < 0.05, d=-0.29) and had a significantly higher vertical jump height (p < 0.05, d = 0.36) than the bottom ranking players. The U18 top ranking players had a significantly lower sit-and-reach than the bottom ranking players (p < 0.05, d=-0.42). There was no significant difference between the different rankings of other indicators (p > 0.05, d=-0.19 to 0.23).
Table 2.
Comparison of fitness in different ranking groups
| U17 | p | Cohen`s d | U18 | P | Cohen`s d | ||||
|---|---|---|---|---|---|---|---|---|---|
| Top | Bottom | Top | Bottom | ||||||
| Sprint (s) | 3.33 ± 0.18 | 3.39 ± 0.23 | 0.047 * | -0.29 | 3.51 ± 0.17 | 3.54 ± 0.19 | 0.208 | -0.18 | |
| Standing Long Jump (cm) | 260.2 ± 16.8 | 256.5 ± 15.9 | 0.115 | 0.23 | 257.5 ± 17.0 | 254.8 ± 19.0 | 0.305 | 0.15 | |
| Vertical Jump (cm) | 326.4 ± 12.1 | 322.2 ± 11.5 | 0.014 * | 0.36 | 328.0 ± 12.7 | 328.2 ± 12.0 | 0.938 | -0.01 | |
| Sit-and-Reach (cm) | -15.9 ± 6.6 | -16.8 ± 7.1 | 0.377 | 0.13 | -18.3 ± 6.0 | -15.7 ± 6.4 | 0.004 * | -0.42 | |
| Sit-Ups (n) | 40.3 ± 8.0 | 41.5 ± 10.6 | 0.386 | -0.13 | 40.7 ± 10.6 | 40.7 ± 9.8 | 0.992 | 0.00 | |
| Shuttle Run (s) | 58.1 ± 2.5 | 58.6 ± 3.1 | 0.185 | -0.19 | 59.9 ± 3.0 | 60.4 ± 3.2 | 0.219 | -0.18 | |
* denotes significant difference
Table 3 shows the correlation results between different fitness among players. It was shown that sprint was significantly negatively correlated with standing long jump and sit-ups (r=-0.17 to -0.45, p < 0.05) and positively correlated with shuttle run (r = 0.52, p < 0.05). Standing long jump was significantly positively correlate with vertical jump (r = 0.30, p < 0.05) and negatively correlated with sit-and-reach and shuttle run (r=-0.14 to -0.58, p < 0.05). Vertical jump was significantly correlate with sit-ups (r = 0.11, p < 0.05). Sit-and-reach was significantly positively correlate with shuttle run (r = 0.13, p < 0.05) and sit-ups was significantly negatively correlate with shuttle run (r=-0.28, p < 0.05).
Table 3.
Correlations between different fitness test indicators
| Sprint | Sprint | Standing Long Jump | Vertical Jump | Sit-and-Reach | Sit-Ups | Shuttle Run |
|---|---|---|---|---|---|---|
| 1 | ||||||
| Standing Long Jump | -0.45 * | 1 | ||||
| Vertical Jump | 0.05 | 0.30 * | 1 | |||
| Sit-and-Reach | 0.08 | -0.14 * | 0.05 | 1 | ||
| Sit-Ups | -0.17 * | 0.20 | 0.11 * | -0.13 | 1 | |
| Shuttle Run | 0.52 * | -0.58 * | -0.07 | 0.13 * | -0.28 * | 1 |
* denotes statistical significance
Discussion
This study investigated the physical fitness of a large sample of elite youth basketball players. The main finding was that physical fitness characteristics were largely comparable between U17 and U18 players. Apart from small-to-moderate differences in sprinting, shuttle running, and vertical jump performance, no substantial age-related differences were observed, indicating that key physical capacities may have largely stabilized by late adolescence. Besides, significant positional differences existed in most fitness indicators and U17 top-ranking teams showed superior speed and vertical jump compared to lower-ranking ones.
In different age groups, the present study showed that physical fitness profiles of U17 and U18 elite basketball players were largely comparable. Although U17 players demonstrated faster sprint and shuttle run performance, and U18 players exhibited slightly greater vertical jump height, the observed differences were small to moderate in magnitude and were not consistent across all fitness indicators. These findings contrast with results commonly reported in younger age groups, where older players generally outperform younger peers across most physical domains [22, 23]. This discrepancy likely reflects differences in biological development stage, as players in the U17–U18 age range are predominantly post-pubertal, and major gains in general physical fitness may have already occurred prior to this phase [12]. The faster sprint and shuttle run performance observed in U17 players may be partially explained by training emphasis and selection characteristics rather than continued biological development. In late adolescence, basketball training increasingly prioritizes body mass, strength, and physical contact [24], particularly for players progressing toward senior competition, which may negatively affect linear speed and repeated running ability if not carefully managed [25]. Conversely, the slightly superior vertical jump performance in U18 players may reflect continued neuromuscular adaptations and greater exposure to strength-oriented training, which has been shown to enhance jump-related performance in older adolescent basketball players [26]. Therefore, coaches and practitioners should be cautious when interpreting fitness test results based solely on age category in post-pubertal youth basketball and should place greater emphasis on individual and position-specific profiles rather than assuming linear age-related progression.
In different positions, we found that there was a significant difference in fitness for different positions except for sit-and-reach in both U17 and U18 groups, in line with previous studies [11, 19]. A basketball player’s position is largely determined by body type and on-court responsibilities, with inside players require more confrontation and rebounding contests and are therefore taller, while outside players requiring more running and are relatively lower in stature [15, 24]. A study of adolescent athletes of similar age groups at a German national selection tournament also revealed differences in technical execution, decision-making and final efficacy across different positions [27]. Time-motion analyses during the game further explain the differences in fitness by position, with centers doing less sprinting, jumping, and other high-intensity activities compared to guards and forwards [28, 29], especially in the late stage of the match [29]. Additionally, research suggests that inside players tend to mature earlier biologically [9], which may also contribute to the differences in physical conditioning across positions. However, our study did not measure this aspect, and further exploration is needed in the future. Taken together, it suggests training should be position-specific, with centers focusing on speed and explosiveness and guards and forwards enhancing high-intensity running and agility.
Regarding the different ranked athletes, we found differences in speed and vertical jump in the U17 players and differences in sit-and-reach in the U18 players. Compared to players in lower ranked team rankings, players in higher ranked teams were better in sprint and vertical jump performance in U17 groups, which is in line with previous studies [4, 5]. Superior speed and vertical jump performance may provide athletes with a competitive edge in scenarios such as breaks and rebounds contests. Specifically, a recent study has shown that athletes with better vertical jump performance have more playing time and efficiency [30]. However, we did not find the above differences among U18 players, and the differences in the above qualities among U17s were not large (small effect sizes). The reason for this may lie in the fact that the above tests do not fully reflect an athlete’s speed and jumping ability on the field. For instance, the average sprint distance in basketball matches is 3.9 to 9.5 m [31], which is much lower than the 3/4 court. In addition, physical fitness is only one aspect of basketball performance, and skill performance has a large impact on basketball level [32]. More specifically, Lockie et al. [33] found that no significant correlation between playing time and NBA Combine test results.
One limitation of this study is that athletes were not tested for strength, which has been shown to have a significant impact on game performance [34]. However, since the athletes in this study were not adult athletes and the interval between testing and competition was not long, strength testing was not conducted. Besides, given that post-pubertal youth exhibit substantial individual variability in biological maturation, the lack of this data may obscure the true relationship between chronological age and physical fitness [18]—some athletes may be biologically more advanced or delayed relative to their peers of the same age, leading to unaccounted-for variations in physical fitness that could confound the comparisons between U17 and U18 groups or across ranking levels. Furthermore, some of the selected physical tests (e.g. 3/4 court sprint and shuttle run) may be not well aligned with the actual demands of basketball performance. Finally, although widely used, the field-based assessments may have limited ecological validity as they do not fully replicate basketball-specific movements. Future research could collect other strength indicators such as grip strength, combine biological maturation data and using more specific basketball fitness tests, such as 5/10m sprint test, to get deep insight.
Conclusion
In conclusion, this study demonstrates that elite youth basketball players exhibit distinct physical fitness profiles based on age group, playing position, and competitive ranking. Our findings reveal that physical fitness profiles of U17 and U18 elite basketball players were largely comparable, except that U18 basketball athletes had higher vertical jumps and slower sprints and shuttle run than the U17 basketball athletes. There were significant fitness differences between U17 and U18 athletes at different positions. And U17 athletes from higher ranked teams performed better in speed and vertical jump. Practitioners should conduct longitudinal monitoring of players across seasons and inclusion of technical-tactical performance indicators along with physical fitness.
Acknowledgements
We thank all participants for their contributions to this study.
Authors’ contributions
Data curation, X.A., Y.P. and H.C.; formal analysis, Y.P., H.C. and X.W.; funding acquisition, X.A. and H.C.; investigation, X.A. and H.C.; methodology, X.A., Y.P., P.C. and X.W.; project administration, X.A.; supervision, H.C; visualization, X.W.; writing—original draft, X.A., Y.P. and X.W.; writing—revision, H.C. and P.C. All authors have read and agreed to the published version of the manuscript.
Funding
This study was support by the funding of Research Project of Humanities and Social Sciences of the Education Commission of Chongqing Municipality (Project No: 24SKGH314) and Project of the Scientific and Technological Research Plan of the Chongqing Municipal Education Commission (Project No: KJQN20240160).
Data availability
Data can be requested from the Corresponding Author on reasonable request.
Declarations
Ethics approval and consent to participate
This study was approved by Ethics Committee of Chongqing University of Education (CQUE-LL20250301003). All participants or their guardians gave written informed consent prior to enrolment. The study adheres to the Declaration of Helsinki.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Conflict of interest
The authors declare no conflict of interest.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Xiang Ao and Yan Peng contribute equal and share the first author in this study.
Contributor Information
Hui Chen, Email: chenhui@cque.edu.cn.
Xiaobin Wei, Email: weixiaobin@mail.tsinghua.edu.cn.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Data can be requested from the Corresponding Author on reasonable request.


