Physical Performance Profiles of Highly Trained U14–U19 Youth Soccer Players: Age-Category Differences and Associations with Maturity Offset

This study aimed to examine age- and maturity-related differences in anthropometric characteristics, body composition, functional movement, and field-based physical performance among U14–U19 male youth soccer players. Seventy academy players completed anthropometric and body composition assessments, the Functional Movement Screen, a 30-m linear sprint, the Illinois Agility Test with and without the ball to assess change-of-direction speed (CODs), a standing long jump, and the Yo-Yo Intermittent Recovery Test Level 1. Biological maturation was estimated using the Mirwald equation. Age-category differences were examined using one-way ANOVA or Welch’s ANOVA, as appropriate. Associations between variables were assessed using Pearson’s correlation coefficient, while multivariable linear regression models were used to examine the independent associations of chronological age and maturity offset with physical performance outcomes. Significant age-category differences were observed in estimated age at peak height velocity (F(4, 65) = 5.12, η2 = 0.240), maturity offset (F(4, 65) = 45.12, η2 = 0.735), body height (F(4, 32.15) = 5.01, η2 = 0.319), body weight (F(4, 65) = 15.47, η2 = 0.488), skeletal muscle mass (F(4, 65) = 16.36, η2 = 0.502), 30-m sprint time (F(4, 65) = 27.97, η2 = 0.633), CODs without a ball (F(4, 65) = 16.52, η2 = 0.504), standing long jump (F(4, 65) = 11.39, η2 = 0.412), and endurance test performance (F(4, 30.21) = 16.47, η2 = 0.408; all p < 0.01). The U14 players generally demonstrated less favorable performance than the older age categories. Interestingly, no significant age-category differences were observed in body fat percentage, Functional Movement Screen total score, or CODs with the ball. In the regression analyses, maturity offset was significantly associated only with standing long jump performance (β = 0.496, p = 0.012), but the association did not remain significant after Holm correction. The reported age-category values may provide preliminary benchmarks for evaluating youth academy soccer players, but they should be interpreted alongside maturity status and individual developmental characteristics. Future studies could complement field-based testing with biomechanical and treadmill-based laboratory assessments to provide a more comprehensive evaluation of age- and maturity-related performance.

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Journal
Sports
Published
2026-09-14
DOI
https://doi.org/10.3390/sports14090402
Primary Topic
Sports Performance and Training
Type
article
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article

Physical Performance Profiles of Highly Trained U14–U19 Youth Soccer Players: Age-Category Differences and Associations with Maturity Offset

Krisztián Havanecz, Ferenc Ihász
Sports
Sports Performance and Training
article

Physical Performance Profiles of Highly Trained U14–U19 Youth Soccer Players: Age-Category Differences and Associations with Maturity Offset

Krisztián Havanecz, Ferenc Ihász
article en

Abstract

This study aimed to examine age- and maturity-related differences in anthropometric characteristics, body composition, functional movement, and field-based physical performance among U14–U19 male youth soccer players. Seventy academy players completed anthropometric and body composition assessments, the Functional Movement Screen, a 30-m linear sprint, the Illinois Agility Test with and without the ball to assess change-of-direction speed (CODs), a standing long jump, and the Yo-Yo Intermittent Recovery Test Level 1. Biological maturation was estimated using the Mirwald equation. Age-category differences were examined using one-way ANOVA or Welch’s ANOVA, as appropriate. Associations between variables were assessed using Pearson’s correlation coefficient, while multivariable linear regression models were used to examine the independent associations of chronological age and maturity offset with physical performance outcomes. Significant age-category differences were observed in estimated age at peak height velocity (F(4, 65) = 5.12, η2 = 0.240), maturity offset (F(4, 65) = 45.12, η2 = 0.735), body height (F(4, 32.15) = 5.01, η2 = 0.319), body weight (F(4, 65) = 15.47, η2 = 0.488), skeletal muscle mass (F(4, 65) = 16.36, η2 = 0.502), 30-m sprint time (F(4, 65) = 27.97, η2 = 0.633), CODs without a ball (F(4, 65) = 16.52, η2 = 0.504), standing long jump (F(4, 65) = 11.39, η2 = 0.412), and endurance test performance (F(4, 30.21) = 16.47, η2 = 0.408; all p < 0.01). The U14 players generally demonstrated less favorable performance than the older age categories. Interestingly, no significant age-category differences were observed in body fat percentage, Functional Movement Screen total score, or CODs with the ball. In the regression analyses, maturity offset was significantly associated only with standing long jump performance (β = 0.496, p = 0.012), but the association did not remain significant after Holm correction. The reported age-category values may provide preliminary benchmarks for evaluating youth academy soccer players, but they should be interpreted alongside maturity status and individual developmental characteristics. Future studies could complement field-based testing with biomechanical and treadmill-based laboratory assessments to provide a more comprehensive evaluation of age- and maturity-related performance.

SportsVol. 14(9)
Hungarian School Sport Federation (HU), Széchenyi István University (HU)
Openalex Percentile: Top 9%
Sports Performance and Training
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