Influence of Maturation and Determinants of Repeated-Sprint Ability in Youth Basketball Players

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Abstract

Gonzalo-Skok, O, and Bishop, C. Influence of maturation and determinants of repeated-sprint ability in youth basketball players. J Strength Cond Res 38(2): 325–333, 2024—The main aims of the current study were (a) to determine the main predictors of general and specific repeated-sprint ability (RSA) tests, (b) to analyze the relationships between RSA tests and independent measures of physical performance, (c) to examine whether between-age differences exist, and (d) to assess whether maturation affects those mentioned above in young basketball players. Thirty-five young (U-14 to U-16), highly trained basketball players performed a linear sprint test (5, 10, and 25 m), an incremental running test, and 2 repeated-sprint tests (general [RSG]: 6 × 25 m; specific [RSS]: 6 × 5 + 5 m with a 45° change of direction and 20 seconds of passive recovery in both tests). Anthropometric variables were measured and used to calculate age at peak height velocity (APHV), which was used to determine maturation. The main determinants of RSA tests were aerobic performance and linear sprinting for RSS ( R ² = 0.84) and adding the percentage of body fat for RSG ( R ² = 0.94). Almost perfect relationships ( r = 0.93–0.99) were found between all RSA variables (i.e., the best [RSG _b and RSS _b] and mean time [RSG _m and RSS _m]). As age increased, performance in RSA was evident, as shown by improved best and mean scores. When APHV was controlled for, no significant differences were apparent in the comparison from U-14 and U-16 in 25 m, RSG _b, and RSG _m. By contrast, significant differences ( p < 0.05) were still evident with APHV controlled between U-14 and U-16 in 5 m, 10 m, RSS _b, and RSS _m. In conclusion, maturation positively affects linear sprinting and linear RSA performance, whereas specific (multidirectional) RSA seems to be related to other factors.

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Progressive statistics for studies in sports medicine and exercise science.

WILLIAM HOPKINS, STEPHEN W. MARSHALL, ALAN M. BATTERHAM … (2009)

Statistical guidelines and expert statements are now available to assist in the analysis and reporting of studies in some biomedical disciplines. We present here a more progressive resource for sample-based studies, meta-analyses, and case studies in sports medicine and exercise science. We offer forthright advice on the following controversial or novel issues: using precision of estimation for inferences about population effects in preference to null-hypothesis testing, which is inadequate for assessing clinical or practical importance; justifying sample size via acceptable precision or confidence for clinical decisions rather than via adequate power for statistical significance; showing SD rather than SEM, to better communicate the magnitude of differences in means and nonuniformity of error; avoiding purely nonparametric analyses, which cannot provide inferences about magnitude and are unnecessary; using regression statistics in validity studies, in preference to the impractical and biased limits of agreement; making greater use of qualitative methods to enrich sample-based quantitative projects; and seeking ethics approval for public access to the depersonalized raw data of a study, to address the need for more scrutiny of research and better meta-analyses. Advice on less contentious issues includes the following: using covariates in linear models to adjust for confounders, to account for individual differences, and to identify potential mechanisms of an effect; using log transformation to deal with nonuniformity of effects and error; identifying and deleting outliers; presenting descriptive, effect, and inferential statistics in appropriate formats; and contending with bias arising from problems with sampling, assignment, blinding, measurement error, and researchers' prejudices. This article should advance the field by stimulating debate, promoting innovative approaches, and serving as a useful checklist for authors, reviewers, and editors.

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Robert L Mirwald, Adam Baxter-Jones, Donald Bailey … (2002)

The range of variability between individuals of the same chronological age (CA) in somatic and biological maturity is large and especially accentuated around the adolescent growth spurt. Maturity assessment is an important consideration when dealing with adolescents, from both a research perspective and youth sports stratification. A noninvasive, practical method predicting years from peak height velocity (a maturity offset value) by using anthropometric variables is developed in one sample and cross-validated in two different samples. Gender specific multiple regression equations were calculated on a sample of 152 Canadian children aged 8-16 yr (79 boys; 73 girls) who were followed through adolescence from 1991 to 1997. The equations included three somatic dimensions (height, sitting height, and leg length), CA, and their interactions. The equations were cross-validated on a combined sample of Canadian (71 boys, 40 girls measured from 1964 through 1973) and Flemish children (50 boys, 48 girls measured from 1985 through 1999). The coefficient of determination (R2) for the boys' model was 0.92 and for the girls' model 0.91; the SEEs were 0.49 and 0.50, respectively. Mean difference between actual and predicted maturity offset for the verification samples was 0.24 (SD 0.65) yr in boys and 0.001 (SD 0.68) yr in girls. Although the cross-validation meets statistical standards for acceptance, caution is warranted with regard to implementation. It is recommended that maturity offset be considered as a categorical rather than a continuous assessment. Nevertheless, the equations presented are a reliable, noninvasive and a practical solution for the measure of biological maturity for matching adolescent athletes

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L Leger, D Mercier, Christopher Lambert … (1987)

A maximal multistage 20 m shuttle run test was designed to determine the maximal aerobic power of schoolchildren, healthy adults attending fitness class and athletes performing in sports with frequent stops and starts (e.g. basketball, fencing and so on). Subjects run back and forth on a 20 m course and must touch the 20 m line; at the same time a sound signal is emitted from a prerecorded tape. Frequency of the sound signals is increased 0.5 km h-1 each minute from a starting speed of 8.5 km h-1. When the subject can no longer follow the pace, the last stage number announced is used to predict maximal oxygen uptake (VO2max) (Y, ml kg-1 min-1) from the speed (X, km h-1) corresponding to that stage (speed = 8 + 0.5 stage no.) and age (A, year): Y = 31.025 + 3.238 X - 3.248A + 0.1536AX, r = 0.71 with 188 boys and girls aged 8-19 years. To obtain this regression, the test was performed individually. Right upon termination VO2 was measured with four 20 s samples and VO2max was estimated by retroextrapolating the O2 recovery curve at time zero of recovery. For adults, similar measurements indicated that the same equation could be used keeping age constant at 18 (r = 0.90, n = 77 men and women 18-50 years old). Test-retest reliability coefficients were 0.89 for children (139 boys and girls 6-16 years old) and 0.95 for adults (81 men and women, 20-45 years old).(ABSTRACT TRUNCATED AT 250 WORDS)