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      Longitudinal Relationships Between Maturation, Technical Efficiency, and Performance in Age-Group Swimmers: Improving Swimmer Evaluation

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          Abstract

          Purpose: The study aimed to (1) accurately examine longitudinal relationships between maturity status and both technical skill indices and performance in Australian male (N = 64) age-group Front-crawl swimmers (10–15 y) and (2) determine whether individual differences in maturation influenced relationships between technical skill level and swimming performance. Methods: A repeated-measures design was used to assess maturity status and performance on 200-m Front-crawl trial across 2 competition seasons (2018–2020). Assessments were made on 3 to 5 occasions (median = 3) separated by approximately 4 months. Average horizontal velocity and stroke frequency were used to calculate technical skill indices, specifically stroke index, and arm propelling efficiency. Relationships between variables were assessed using linear mixed models, identifying fixed, and random effect estimates. Results: Curvilinear trends best described significant longitudinal relationships between maturity status with horizontal velocity ( F = 10.33 [1, 233.77]; P = .002) and stroke index ( F = 5.55 [1, 217.9]; P = .02) during 200-m Front-crawl trials. Maturity status was not significantly related to arm propelling efficiency ( P = .08). However, arm propelling efficiency was an independent predictor of Front-crawl velocity ( F = 55.89 [1, 210.45]; P < .001). Conclusions: Maturity status predicted assessment of swimmer technical skill (stroke index) and swimming performance. However, technical skill accessed via arm propelling efficiency was independent of maturation and was predictive of performance. Maturity status influences performance evaluation based on technical skill and velocity. Findings highlight the need to account for maturation and technical skill in age-group swimmers to better inform swimmer evaluation.

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          Most cited references33

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          An assessment of maturity from anthropometric measurements.

          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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            The relationship between peak height velocity and physical performance in youth soccer players.

            Longitudinal changes in height, weight and physical performance were studied in 33 Flemish male youth soccer players from the Ghent Youth Soccer Project. The players' ages at the start of the study ranged from 10.4 to 13.7 years, with a mean age of 12.2 +/- 0.7 years. Longitudinal changes were studied over a 5 year period. Peak height velocity and peak weight velocity were determined using non-smoothed polynomials. The estimations of peak height velocity, peak weight velocity and age at peak height velocity were 9.7 +/- 1.5 cm x year-1, 8.4 +/- 3.0 kg x year-1 and 13.8 +/- 0.8 years, respectively. Peak weight velocity occurred, on average, at the same age as peak height velocity. Balance, speed of limb movement, trunk strength, upper-body muscular endurance, explosive strength, running speed and agility, cardiorespiratory endurance and anaerobic capacity showed peak development at peak height velocity. A plateau in the velocity curves was observed after peak height velocity for upper-body muscular endurance, explosive strength and running speed. Flexibility exhibited peak development during the tear after peak height velocity. Trainers and coaches should be aware of the individual characteristics of the adolescent growth spurt and the training load should also be individualized at this time.
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              Enhancing a Somatic Maturity Prediction Model.

              Assessing biological maturity in studies of children is challenging. Sex-specific regression equations developed using anthropometric measures are widely used to predict somatic maturity. However, prediction accuracy was not established in external samples. Thus, we aimed to evaluate the fit of these equations, assess for overfitting (adjusting as necessary), and calibrate using external samples.
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                Author and article information

                Journal
                International Journal of Sports Physiology and Performance
                Human Kinetics
                1555-0265
                1555-0273
                August 1 2021
                August 1 2021
                : 16
                : 8
                : 1082-1088
                Article
                10.1123/ijspp.2020-0377
                4c398b92-2571-48ba-83f1-71490c1a74d0
                © 2021
                History

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