Relative Age Effects in Basketball: Exploring the Selection into and Successful Transition Out of a National Talent Pathway

The Road to the Hoop: Relative Age Effects and Game-Related Performance in Youth Basketball

Relative Age Effects (RAEs) have been widely reported trends in basketball participation, but research on the relationship between RAEs and competitive performance has been contradictory. We aimed to determine the magnitude of RAEs in elite youth basketball players and to analyze RAEs on key performance indicators (KPIs). We recorded and analyzed the incidence of early birthdates and the KPIs of 2487 youth basketball players (aged 16-19 years). We evaluated RAEs by means of the incidence of early birthdates using (i) Chi-square (χ2) goodness-of-fit tests to compare player differences in birthdate quartiles and (ii) Poisson regression analysis to evaluate birthdates as a continuous variable. We conducted Kruskal-Wallis tests separately for each age group to assess possible relationships between birthdate quartile differences and KPIs. We observed consistent moderate RAEs across all ages. The Poisson regression analysis showed that athletes born near the beginning of the year were 4.6-8.4 times more likely to have been included on the squad than athletes born towards the end of the year. We observed no significant differences between KPIs for differently aged athletes. However, 16-year-old athletes with first quartile birthdates showed higher KPIs than those with fourth quartile birthdates of the same calendar year. The potential bases for RAEs are complex and include the characteristic demands of sports competition at various competition levels and athletes' ages, individual factors and social factors. We discuss these and other potential bases. Basketball coaches and managers should keep RAEs in mind when selecting youth players to avoid a selection bias towards players born at the beginning of the year which may close out training opportunities and cause drop outs for talented but slightly younger players.

Relative age effect and its impact on athletic performance among Chinese elite youth male basketball players

This study aimed to explore the presence and magnitude of relative age effects (RAEs) among elite male Chinese youth basketball players. A total of 728 adolescent players and 60 teams in the 2023 Chinese Student (Youth) Games were included. Player efficiency rating (PER) was calculated to evaluate individual performance, and the relative age team achievement (RATA) score was used to assess team-related RAEs. Partial correlation analysis was conducted to explore the relationships between relative age and performance parameters, with height and weight as control variables. The results indicate a skewed distribution of birth dates in the U-16 group. In contrast, the U-18 group exhibited a more balanced distribution. In the U-16 competitions, relative age had significant positive correlations with points, assists and PER. However, in the U-18 competitions, a significant positive correlation was only observed for assists. At the team level, in both U-16 and U-18 competitions, there was no significant correlation between the relative age and team performance indicators such as average point differential, winning percentage, and team efficiency. Given that RAEs in youth basketball may lead to inequitable talent selection and developmental opportunities, this phenomenon warrants attention, and measures should be implemented to mitigate potential selection bias and talent loss.

Talent Identification: Time to Move Forward on Estimation of Potentials? Proposed Explanations and Promising Methods

The scientific literature on talent identification is extensive, with significant advancements made over the past 30 years. However, as with any field, the translation of research into practice and its impact on the field have been slower than anticipated. Indeed, recent findings highlight a pervasive relative age effect, the effects of maturation being often overlooked, disparate populations between young and senior performers, and a necessity to embrace a holistic approach. However, simple elements can be implemented to avoid some of these known biases. This review synthesizes recent advancements, critically examines key elements to consider in talent identification, and proposes promising avenues for enhancement. These include (1) understanding and illustrating early performance influences, (2) implementing individualized performance trajectory models, (3) applying corrective adjustments based on relative, biological, and training age, and (4) improving estimation of potentials through a holistic approach that integrates "life pathways". In light of these necessary improvements, it seems opportune to propose a semantic shift to generate a change in both conceptual and operational paradigms. The proposed terminology of "estimation of potential" is based on a semantic and mathematical definition, which operationalizes its conceptualization. This study suggests that understanding the trajectories of transitions from youth to senior categories in each sport, coupled with a holistic approach centered on individual performance progressions across the three ages, would be a possible path toward estimating potential.

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

Introduction

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

Methods

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

Results

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

Discussion

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

Selection-Dependent Differences in Youth Elite Basketball Players' Relative Age, Maturation-Related Characteristics, and Motor Performance

Purpose: The aim of the present study was to investigate the influence of players' relative age, maturation-related characteristics, and motor performance tests on two different stages of talent selection (regional and national level) in youth elite basketball. Methods: Relative age, maturation-related variables (height, weight, maturity offset, maturity timing) and motor performance (Countermovement jump, Standing long jump, Modified agility T-test, Linear sprint 20 m) of N = 68 male youth basketball players (Mage = 14.39 ± 0.28 years) were assessed during the initial selection tournament for the German U15 national team. Pre-selection biases regarding relative age and maturity timing on the regional level were investigated utilizing one-sample t-tests. Differences in relative age, maturation-related characteristics and motor performance between players selected (n = 27) and non-selected (n = 41) for the youth national team were examined via independent samples' t-tests and logistic regression analyses. Results: Strong pre-selection biases toward early-born and early-maturing players were confirmed on the regional level. Significant advantages in height and weight and higher values in maturity offset and maturity timing were found for selected players. Among the motor variables, only Countermovement jump performance was significantly better in selected players. When controlling for relative age and biological maturation regression models including motor performance variables did not significantly discriminate players' selection status. Conclusion: Coaches working in national, but also preceding selection stages (regional and club level) should raise their awareness to relative age and biological maturation when evaluating players' potential and current (motor) performance.

Basketball talent identification: a systematic review and meta-analysis of the anthropometric, physiological and physical performance factors

Background

The purpose of this study was to do a systematic review and meta-analysis about the anthropometric, physiological, and physical performance that discriminate the physical talent in basketball.

Methods

The search was conducted using the most relevant databases as Web of Science, PubMed, SPORTDiscus and Scopus, according to the PRISMA (2020) guideline. Keywords such as "basketball", "talented identification", "anthropometric", "physiology" and "physical performance" were used for the search, in English and following the "PICOS" question model. Eighteen articles' overall methodological quality was assessed using the Critical Review Forms.

Results

The study found in basketball, height, body mass, Yo-Yo test, T-test, 20 m sprint, and jump performance had statistical significance between elite and non-elite groups, including different positions and levels.

Conclusions

The reviewed literature highlighted a complicated relationship between anthropometric, physiological, and physical performance. Based on the results of the study, it's possible that height, body mass, agility, speed, endurance capacity, and lower lamb power could affect the early development of basketball.

Relative age effects and the youth-to-senior transition in Italian soccer: the underdog hypothesis versus knock-on effects of relative age

Relative Age Effects (RAEs) appear largely throughout youth soccer. However, little is known about how RAEs at youth levels can impact transition at senior levels. Accordingly, this study aimed to: (a) provide further test of RAEs by exploring the birth quarter (BQ) distribution of 2,030 Italian players born from 1975 to 2001 who have played in any of the Youth National Italian Soccer Teams; and (b) investigate how RAEs influence future career outcomes, by exploring the BQ distribution of players who completed the transition from youth squads to the Senior National Team (n = 182).  Chi-square statistics revealed significantly skewed BQ distributions for all Youth squads (P values <0.0001), and for the cohort of players who completed the transition (P = 0.003). In contrast, results from the Odds Ratios highlighted how BQ4s were more likely to transition from youth-to-senior compared to BQ1s. Results showed BQ1s remained overrepresented at senior level due to a residual bias effect. Whereas BQ4s who were able to overcome selection processes at youth levels recorded the highest likelihood of competing at senior levels. Involving players' career trajectories in RAEs studies is needed to understand how RAEs impacts career outcomes of early selected players.

Biological maturation, contextual factors, and future career in basketball: A possible interrelationship?

This study aimed to analyse the relationship between the maturational state and contextual factors with future basketball career success in Under-16 (U16) Portuguese youth preparing for the U16 European Basketball Championships. Eighty-five Under-15 (U15) and U16 male basketball players (height: 189.7 ± 6.53 cm; body mass: 81.1 ± 9.96 kg; the age of peak height velocity: 13.3 ± 0.7 y) were selected by the Portuguese national coaching staff to participate in a national team training camp in 2016, 2017, and 2018 years. A binary logistic regression was employed to identify the influence of maturation, born quartile, demographic, geographic and economic characteristics, and sport career (i.e., drop out during first season and chance of playing professionally). Early maturing players were typically classified as inside players. Training experience and predicted adult height, and type of first club were able to predict players who dropped out during their first season at senior level (both p < 0.01). No variables were able to predict who played in a professional league during their first season at senior level. Practitioners should use these data to consider how national level basketball players are identified and developed, but also keep in mind of their specific contextual factors.

What Variables Allow the Differentiation between More and Less Successful Adolescent Volleyball Players?

Kinanthropometric and physical fitness variables have been habitually used for the detection of sports talent in adolescent populations. Considering these variables, players who obtained better scores than their peers in kinanthropometric and physical fitness variables have been traditionally selected for promotion in their teams, without taking into account the possible effect of the maturation process. The aim of the present study was to analyse the differences between adolescent volleyball players in terms of success assessment and the age category, as well as to identify variables that may predict success in volleyball. A total of 101 volleyball players in the U14 age category (28 boys and 73 girls; age = 13.28 ± 0.49 years) and 99 players in the U16 age category (20 boys and 79 girls; age = 15.24 ± 0.59 years) participated in the study. Significant differences were observed in biological maturation in male groups (p < 0.001-0.041), kinanthropometric variables related to bone structure and muscle mass in male groups (p < 0.001-0.048), in variables related to adipose tissue in the U16 female group (p = 0.012-0.032) and in physical fitness tests related to muscle strength and power (p < 0.001-0.049), indicating that more successful (MS) players showed a more advanced biological maturation process, higher values of kinanthropometric variables related to bone structure and muscle mass, and lower values in variables related to adipose tissue, as well as higher levels of physical fitness. The difference in biological maturation and its relationship with structural and muscular anthropometric variables in boys, and physical fitness tests related to muscle strength and power in both boys and girls, are of great importance in the selection process of sports talent in volleyball. These findings should be considered by clubs and coaches, who could be discarding players who could improve their sports performance in later stages when their maturational development is equalised.

Relative age effect reversal on the junior-to-senior transition in world-class athletics

The relative age effect (RAE) is a selection bias resulting from the interaction between the selected dates and birthdates. Nevertheless, the impact of birthdate on the junior-to-senior transition in international track and field is unclear. This study aimed to quantify the RAE's magnitude and test if birthdate affects the junior-to-senior transition rate. The birthdate and performances of 5,766 sprinters (female: 51.0%) and 5,863 jumpers (female: 45.9%) were collected. Elite athletes (operationally defined as the World's all-time Top 200, 100 and 50 athletes) were identified according to Under 18 and Senior categories. Skewed quartile distributions were observed in the Under 18 (effect size ranged = 0.15-0.10) but not in the Senior category. RAE magnitude increased according to performance level (i.e., from Top 200 to Top 50) and was higher in males than females. Relatively younger athletes showed significantly higher transition rates with a higher chance of maintaining top level in the senior category (odds ratio (OR) ~ 1.64). The probability of maintaining success was lower for sprinters than jumpers (OR ~ 0.70), influenced by decade of birth and continental place but similar for male and female athletes. Data corroborate that relatively younger athletes are disadvantaged in the junior category but advantaged when transitioning to the senior category.

Special Issue "Talent Identification and Development in Youth Sports"

We are delighted to share our Special Issue on Talent Identification and Development in Youth Sports [...].

Multidisciplinary Neuromuscular and Endurance Interventions on Youth Basketball Players: A Systematic Review with Meta-Analysis and Meta-Regression

The main aims of this systematic review with meta-analysis and meta-regression were to describe the effect of multidisciplinary neuromuscular and endurance interventions, including plyometric training, mixed strength and conditioning, HIIT basketball programs and repeated sprint training on youth basketball players considering age, competitive level, gender and the type of the intervention performed to explore a predictive model through a meta-regression analysis. A structured search was conducted following PRISMA guidelines and PICOS model in Medline (PubMed), Web of Science (WOS) and Cochrane databases. Groups of experiments were created according to neuromuscular power (vertical; NPV and horizontal; NPH) and endurance (E). Meta-analysis and sub-groups analysis were performed using a random effect model and pooled standardized mean differences (SMD). A random effects meta-regression was performed regressing SMD for the different sub-groups against percentage change for NPV and NPH. There was a significant positive overall effect of the multidisciplinary interventions on NPV, NPH and E. Sub-groups analysis indicate differences in the effects of the interventions on NPV and NPH considering age, gender, competitive level and the type of the intervention used. Considering the current data available, the meta-regression analysis suggests a good predictability of U-16 and plyometric training on jump performance. Besides, male and elite level youth basketball players had a good predictability on multidirectional speed and agility performance.

The relative age effect in the Gaelic Athletic Association (GAA): A mixed methods approach

In the Gaelic Athletic Association (GAA), Talent Academies (TAs) and senior teams cater for high performing players, however only two previous studies have quantified the relative age effect (RAE; i.e., a selection bias favouring those born near the beginning of the cut-off date) in these cohorts. Additionally, no studies to date have explored stakeholder understanding of the RAE using qualitative methods. This study aimed to: (a) quantify the RAE in TAs and senior teams, and (b) investigate stakeholder perspectives of the talent development environment, providing practical insight into the RAE. A mixed methods sequential explanatory study design was employed. Phase one involved a retrospective analysis of longitudinal data for the frequency and distribution of births using TA (n=12,445) and senior (n=8,752) players. Phase two comprised two focus groups of key stakeholders [coaches (n=4) and Talent Development Leaders (n=4)] at TA and senior level. Analysis revealed a significant difference between TA birth quarter (BQ) distributions compared with expected distributions across all age groups (P<0.001; BQ1=30.4% vs. BQ4=17.6%), while at senior level, there were no significant differences between observed and expected BQ distributions (χ² (df=3) =3.812, P=0.282). In phase two, inductive analysis revealed three higher order themes: (a) understanding of the RAE, (b) selection criteria, and (c) player characteristics. The GAA are encouraged to reflect on the practice of chronological age band grouping, investigate possible solutions to limit the effects of the RAE, and offer support programmes to educate key stakeholders on the potential impact of the RAE on talent development.

Does predicted age at peak height velocity explain physical performance in U13-15 basketball female players?

Background

The aims of the study were (1) to identify the physical fitness and basic anthropometric characteristics of Polish female basketball players aged 13–15 years, (2) to show the effect of maturity timing on the performance in motor tests and basic body composition parameters, (3) to identify the index that contributes most to the prediction of performance in the tests of speed, jumping ability, agility, and endurance.

Methods

The sample included 904 female Polish players (U13–15). In part 1, maturity timing category distribution were examined within across age-groups. Maturity timing was followed by grouping with respect to years before or after the observed peak high velocity (PHV): PHV0 (− 0.50 to 0.49), PHV1 (0.50 to 1.49), PHV2 (1.50 to 2.49) and PHV3 (2.50 to 3.49). In part 2, the relationship between the anthropometric variables, physical fitness performance was assessed based on maturity timing categories (ANCOVA analysis). In part 3, backward stepwise multiple regression analyse quantified the relationship between maturity timing (group of PHV) and physical performance.

Results

ANCOVA results (age, body height, and body mass as covariates) showed in the U13 female basketball players significantly higher sprinting (20 m), jumping ability and endurance tests results of the PHV1 group. Better results was observed in U14 female players in PHV1 compared to PHV2 and PHV3 in 20 m and jumping tests but opposite trend was observed for 5 m sprint and endurance test (distance covered and VO2_max). U15 basketball players from the PHV3 group were characterized by better results of jumping abilities, endurance, 10 m and 20 m sprint and agility (total, S₄) tests. Maturity timing (10 m), chronological age (5 m, 20 m, agility, SVJ, VJ, and VO_2max tests), body height (10 m), body mass (10 m, 20 m, VJ, VO_2max), and the interaction between body mass and height (SVJ) were significant (adjusted R² = 0.02–0.10; p < 0.001) predictors of motor skills.

Conclusion

Trainng content of female basketball players aged 13–15 years old should be adjusted to biological requirements especially in jumping, endurance and 20 m sprint test. The time from peak height velocity (PHV) was a significant predictor only in the 10 m sprint test.

The Effect of Age, Biological Maturation and Birth Quartile in the Kinanthropometric and Physical Fitness Differences between Male and Female Adolescent Volleyball Players

BACKGROUND

Differences in kinanthropometric and physical fitness performance between boys and girls usually start during adolescence, as a result of the changes in the hormonal environment that occur with the advance of age and biological maturation; Methods: A total of 96 1st Regional Division players adolescent volleyball players, 48 males, (age = 14.17 ± 1.00 years-old) and 48 females (age = 14.41 ± 1.21 years-old) underwent a kinanthropometric assessment, were asked to perform different physical fitness test and to complete a questionnaire. Chronological age, maturity offset, age at peak height velocity (APHV), and birth quartile were calculated; Results: Statistical differences were observed between male and female players in the APHV (p < 0.001). Male players showed higher values in the bone and muscle-related variables (p < 0.001-0.040), as well as in the strength and power production-related physical tests (p < 0.001-0.012), while the female showed higher values in the fat-related variables (p = 0.003-0.013), and performed better in the flexibility tests. Age, maturity offset, and birth quartile showed to have statistical influence in the differences found between sex groups; Conclusions: There is a clear influence of age and biological maturation on the differences found between sexes in adolescent volleyball players that could be taken into account regarding grouping in early stages.