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

Kelly, Adam L.; Jiménez, Sol Beatriz; Calvo, Alberto Lorenzo; Rubia, Alfonso de la; Jackson, Daniel T.; Jeffreys, Mark; Ford, C R; Owen, Dave; Santos, Sara

doi:10.3390/sports9070101

Cited by 15 publications

(14 citation statements)

References 62 publications

(77 reference statements)

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“…For this reason, several investigations have recently emerged addressing the relative age effect (RAE), understood as the tendency to overrepresent players born in the first months of the year in the selection process [ 17 ]. The RAE has been contrasted on several occasions in high-level adolescent players in team sports [ 12 , 18 , 19 ] and seems to be more evident around the APHV [ 11 ], obtaining better results for those players born in the first months of the year. However, in sports such as volleyball, it seems that the relationship of RAE with performance and chances of selection remain unclear, possibly due to the specific characteristics of the sport [ 20 ].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2022

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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.

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Section: Introductionmentioning

confidence: 99%

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

et al. 2022

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“…As a factor affecting basketball-specific functional abilities and skills, the interindividual differences in biological maturation have not been regularly evaluated, especially in young female athletes. However, research findings indicate the relative age effect on the success of youth basketball teams [ 26 – 28 ]. Overrepresentation of athletes born in the first months of the year in all age groups has been shown [ 29 ].…”

Section: Introductionmentioning

confidence: 99%

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

Gryko

Adamczyk

Kopiczko

et al. 2022

BMC Sports Sci Med Rehabil

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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 VO2max). 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 VO2max tests), body height (10 m), body mass (10 m, 20 m, VJ, VO2max), 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.

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“…Our results correspond with the previous literature, increasing in vertical jump, only evident in the U-16 and the U-18 age group. This in fact highlights the importance of strength and power development at this maturational stages as game demands increase with age [ 84 ] and performance needs to be higher coinciding with the difficult transition from U-18 to senior in basketball [ 48 , 85 ]. For this reason, strength and conditioning programs should take advantage from this “sweet spot” to develop and prepare youth basketball players for future performance and in order to facilitate the senior transition and avoid injury risk [ 36 , 86 , 87 ].…”

Section: Discussionmentioning

confidence: 99%

“…Muscular power development post PHV might be attributed to hormonal changes, fiber type distribution and increase in muscle mass during adolescence [ 32 , 37 , 38 ]. Multiple interventions (in particular plyometric training) are a well-established method to improve speed in different stages from childhood to late maturity of an athlete [ 23 , 42 , 85 , 92 , 93 , 94 , 95 ]. According to the literature, in the early childhood, it seems to be primarily attributed to neural capacity, motor recruitment and coordination [ 33 , 42 , 96 ].…”

Section: Discussionmentioning

confidence: 99%

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

Sacot

Ros

Prats‐Puig

et al. 2022

IJERPH

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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.

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

Cited by 15 publications

References 62 publications

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

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

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

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

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