Effect of maturity timing on the physical performance of male Polish basketball players aged 13 to 15 years

Gryko, Karol

doi:10.1038/s41598-021-01401-4

Cited by 11 publications

(11 citation statements)

References 63 publications

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“…Maturity timing was a relevant predictor of the 20 m linear speed and SVJ tests. Considering the results of another study conducted by Gryko et al [42], the authors indicate that body height, body mass and chronological age are essential predictors for linear speed and endurance performance which is partly consistent with the ndings of our research. Results also showed that functional movement screening (FMS) is one of the most important predictors of physical tness and sport-speci c skills tests.…”

Section: Discussionsupporting

confidence: 92%

Can be possible to predict motor and technical performance using multidimensional approach among adolescent male basketball players?

Mikołajec,

Arede,

Gryko

2024

Preprint

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The aims of the present study were (i) identify and compare the basic anthropometric characteristics, motor performance, game-related skills and functional capacity of under-15 (U-15) and under-16 (U-16) male basketball players, (ii) examine the influence of maturity offset on all performance parameters, (iii) predict test outcome in linear speed, agility, jumping, aerobic endurance and sport-specific skills. Two hundred thirty-four athletes volunteered participated in the study and completed a test battery including morphological variables (body height, body mass, standing reach), fitness (agility, jumping performance, aerobic endurance), technical skills (jump shot, free throws, dribbling) and functional movement screen. The U-16 group outperformed U-15 in terms of body height and mass, but also SVJmax and VJmax. Moreover, when data was adjusted considering chronological age, the group with more advanced maturity offset within U-15 group had achieved greater values in body mass, body height, arm reach and VJmax variable. Data analysis adjusted for age, body height and body mass with the reference to years after PHV showed that PHV2 group among U-15 basketball players had better jumping performance, and 20 m linear speed compared to PHV1 group. Maturity status was a relevant predictor of 20 m linear speed and SVJ tests. Other results indicate that chronical age (20 m speed, VO2max), body height (5, 10, 20 m speed, agility), body mass (agility), functional abilities (20 m speed, SVJ, VJ, VO2max) were significant predictors of physical performance. On the other hand, only body height (free throws) and FMS (jump shot, dribbling) manifested an impact on the level of sport-specific skills. The obtained results indicate that FMS test applied to young basketball players is not only right tool for injury prediction but also its outcome can influence technical performance. Therefore, we can conclude that composite score of < 14 out of 20 may result in low level of sport-specific capacity. It is significant evidence of practical application of FMS tests.

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Section: Discussionsupporting

confidence: 92%

Can be possible to predict motor and technical performance using multidimensional approach among adolescent male basketball players?

Mikołajec,

Arede,

Gryko

2024

Preprint

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“…1 . This is a modified Lane Agility Drill [ 46 ] test, with the length and width changed to 6 × 6 m to ensure that the proportions between defensive shuffle and sprint were identical. The position of the photocell at the change of direction line was 1 m from the line.…”

Section: Methodsmentioning

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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“…Frontiers in Physiology frontiersin.org 2023; Pezoa-Fuentes et al, 2023), sports (Müller et al, 2017;Gryko, 2021) and especially in young soccer players (Asadi et al, 2018;Müller et al, 2018;Peña-González et al, 2022;Ginés et al, 2023). These evidences found in this study may be important for coaches, technicians, physicians, physiotherapists, and directors of youth soccer academies, as the analysis of BC and PF should be analyzed by MS and not by CA.…”

Section: Figurementioning

confidence: 56%

Reference values for body composition and physical fitness of young Brazilian elite soccer players

Portella,

Vidal-Espinoza,

Sulla-Torres

et al. 2023

Front. Physiol.

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Objective: a) to verify whether body composition and physical fitness should be analyzed by chronological age and/or maturity stage in young Brazilian soccer players and b) to propose reference values for the evaluation of body composition and physical fitness by maturity stage in elite soccer players.Methods: A descriptive-correlational study was carried out in 206 young Brazilian soccer players (11–16 years old). The sample selection was non-probabilistic by convenience. Weight and standing height were evaluated. Body composition (BC) was assessed by dual X-ray absorptiometry (DXA). BC indicators [(percent fat (%F), Fat-free mass (FFM), Fat mass (FM) and Bone mass (BM)] were extracted. For physical fitness (PF), we applied the Flexibility (cm) sit and reach tests, explosive strength tests [Counter Movement Jump CMJ (cm) and horizontal jump HJ (cm)], speed [Speed 10, 20, 30 and 40 m (seconds)] and Yo-Yo endurance level I test. Percentiles were constructed for BC and PF using the LMS method [L (Lambda; skewness), M (Mu; median) and S (Sigma; coefficient of variation)].Results: The explanatory power between chronological age (CA) with BC was: FM (R2 = 0.03%), FFM (R2 = 0.66%) and BM (R2 = 0.62%), while between maturity status (MS) with BC were: FM (R2 = 0.04%), FFM (R2 = 0.71%) and BM (R2 = 0.66). The explanatory power between the CA with the physical fitness tests ranged from: (R2 = 0.22–0.62%). While between MS with physical fitness the values ranged from: (R2 = 0.23–0.64%). Percentiles per MS (P3, P5, P10, P15, P25, P50, P75, P85, P90, P95 and P97) were proposed for both BC and PF.Conclusion: The results of the study have shown that the evaluation of BC and PF of young soccer players should be performed by controlling for MS rather than for CA. The inclusion of a non-invasive method to control MS by means of percentiles during puberty may contribute to the development of retention and exclusion of young soccer players, thus, they may have a better chance of achieving sporting success.

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Effect of maturity timing on the physical performance of male Polish basketball players aged 13 to 15 years

Cited by 11 publications

References 63 publications

Can be possible to predict motor and technical performance using multidimensional approach among adolescent male basketball players?

Can be possible to predict motor and technical performance using multidimensional approach among adolescent male basketball players?

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

Reference values for body composition and physical fitness of young Brazilian elite soccer players

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