A total of 131 male basketball players (age: 14.5 ± 0.7 years; height: 180.6 ± 9.7 cm) participated in comprehensive physical testing under the supervision of the French Basketball Federation's technical staff.

The testing battery included measurements of stature, maximal aerobic speed (MAS), sprint performance, basketball-specific agility (Butterfly test), and vertical jump height: •

Stature: measured in centimeters in a standard standing position.

Future performance levels were retrospectively stratified into three categories based on players’ achievements in adulthood: •

Category 1 (Elite): participation in top-level competition (NBA or European professional leagues).

This study was approved by the scientific committee of the Institut de Recherche Médicale et d’Épidémiologie du Sport. Data collection complied with the General Data Protection Regulation (GDPR) and adhered to the principles of the Declaration of Helsinki. All data were anonymized prior to analysis.

Figure 1A presents the first factorial plane of the PCA, which accounts for 69.7% of the total variance. The first principal axis (44.0%) contrasts 10-meter sprint and Butterfly test performance (negative loading) with vertical jump height and MAS (positive loading), while stature does not contribute significantly. The second axis (25.6%) contrasts stature and jump height (positive loading) with MAS (negative loading); 10 m sprint is not strongly represented on this axis.

Figure 1B shows the four clusters obtained through HCPC. •

Cluster 1 (“Hybrid”): high MAS and jump height, but lower sprint and agility (Butterfly) performance.

A Chi-square goodness-of-fit test comparing the distribution of birth quarters to a uniform distribution revealed a significant relative age effect across the entire sample (p = 0.0005, χ² = 31.9). The observed effect size was moderate [Cramér's V = 0.35, 95% CI (0.21, 0.46)]. A post hoc power analysis indicated a high observed power (87%) to detect the effect, suggesting that the test was sufficiently powered despite the modest sample size (N = 87).

Q1 was markedly overrepresented (resid = + 5.51), while Q3 (resid = −2.66) and Q4 (resid = −2.17) were underrepresented, indicating a clear skew in birth date distribution favoring early-born players.

The results confirm the presence of a RAE in youth basketball, consistent with previous research (36–39). Players born in Q1 and Q2—especially within the “Explosive” and “Hybrid” clusters—displayed superior physical performance in sprint, agility, jump height, and aerobic capacity. This advantage likely stems from more advanced maturation levels, reinforcing the well-documented maturation-selection hypothesis (29, 36, 40–43). Such results illustrate how being born earlier in the selection year can yield immediate benefits in competition and talent selection processes.

Interestingly, these physical advantages did not translate into a clear pathway toward elite performance. This phenomenon, sometimes termed the “underdog effect” (44), has been noted in sports like rugby union (45), cricket (46), and football (47). Several plausible mechanisms could drive this effect, including psychological factors, identity construction in the face of adversity, and enhanced learning or resilience among late-born athletes (46, 48). Additionally, it is possible that coaches subconsciously give preferential treatment to those with early physical advantages, thus overlooking potentially talented but physically less mature players (49). These findings collectively underscore the necessity of refining selection criteria to account for not just chronological age but also relative, biological, and training ages (50). In doing so, basketball federations and coaches can ensure a more equitable talent development system that looks beyond immediate physical attributes, ultimately fostering a deeper pool of potential elite athletes.

Moreover, recognizing the interplay between relative age and the dynamic trajectories of player development enriches current talent identification practices. Taking RAE into account helps mitigate biases that might prematurely exclude later-born athletes from advanced training opportunities. Moving forward, this more nuanced perspective opens new avenues for research that investigate how RAE-driven imbalances manifest in different stages of a basketball career—from regional and national development programs to professional and international competitions.

The identification of four distinct athletic profiles—“Explosive,” “Hybrid,” “Elevated,” and “Resilient”—offers further insight into the limitations of relying solely on early physical performance to predict long-term success (Figure 3).

For instance, although the “Explosive” cluster showed strong speed and agility at a young age, its members predominantly remained at the amateur or developmental level by age 18. These observations align with a recent review on basketball talent identification (27) indicating that while top youth performers display superior anthropometric, physiological, and physical characteristics (51), such early advantages do not necessarily predict senior success (52). Indeed, across multiple Olympic sports, junior performance explains only a minor fraction (2.2%) of the reliable variance in senior performance (52). Thus, progression rates and annual improvements—rather than absolute performance at a young age—may serve as more reliable talent predictors (50, 53, 54).

Interestingly, the “Hybrid” profile—characterized by higher MAS and jump height—showed stronger representation within the amateur category. This observation contrasts with existing literature, which typically associates higher aerobic capacity (VO₂ max) with enhanced recovery and sustained high-intensity efforts, favoring progression in basketball (27). Similarly, superior aerobic fitness has been reported in the most promising young basketball players (55). This discrepancy could be explained by several factors such as insufficient technical-tactical development despite favorable physical attributes. Consequently, while endurance and repeated-effort capacity remain important, they should be interpreted within a broader developmental context, rather than as standalone predictors of success.

Meanwhile, the “Elevated” cluster—characterized by taller stature and robust vertical jump performance—showed a relatively stronger pathway to the developmental category. Height remains a well-known asset in basketball (42, 56, 57), often forming the basis of early selection (27, 58). Research on professional leagues, such as the NBA, corroborates that height and body composition hold pivotal roles in offensive and defensive skills, including shooting, passing, rebounding, and shot-blocking (1, 2, 6). However, our results also emphasize that height alone is insufficient: the combination of height and lower-limb power (e.g., strong vertical jump) appears key in identifying players with greater developmental potential. This finding aligns with various studies demonstrating that higher jumping ability and lower-body power—often measured via the Squat Jump (SJ) or Countermovement Jump (CMJ)—are essential for basketball success (27, 59).

Collectively, these observations reflect the multifaceted nature of talent identification in basketball. While certain physical attributes (e.g., speed, agility) may confer early advantages and selection benefits, they do not reliably guarantee sustained success (52). This highlights the need for holistic evaluation frameworks—encompassing not only physical performance but also psychological, technical, and tactical factors (50). Coaches and talent scouts should adopt broader, more flexible selection criteria, accounting for individual developmental pathways and future growth potential, rather than focusing solely on immediate measures of performance. Importantly, variables such as mental resilience, learning ability, and willingness to adapt should be integrated into monitoring and evaluation programs, acknowledging that players mature and evolve at different rates.

Moreover, placing an emphasis on relative, biological, and training ages can help capture each player's developmental status more accurately (50). Given that physical and psychological attributes can shift dramatically between early adolescence and adulthood, continuous longitudinal tracking is vital for making informed decisions regarding training regimens, positional roles, and competitive opportunities. By refining these frameworks, youth basketball programs can balance current performance assessments with the recognition that some late maturers—often overlooked in conventional selection models—may ultimately become top-tier players.

Key limitation of this study lies in the relatively small number of players who reached the elite category (n = 9), which limits the statistical power and generalizability of the findings. While effect sizes were included to aid interpretation, larger and more diverse samples are needed to confirm the observed patterns and enhance external validity.

Additionally, the exclusive focus on physical parameters provides only a partial view of basketball potential. Other key domains—such as technical skills, tactical understanding, and psychological traits—were not assessed, yet play a critical role in long-term success.

Further longitudinal research is warranted to track how early advantages or disadvantages evolve across adolescence and into adulthood. Moreover, future work should consider recalibrating performance metrics by incorporating relative age, biological maturity, and training experience, all of which could improve the precision and fairness of youth talent assessments.