How to compare physical fitness when different tests are performed : A cross-sectional study on conversion formulas of common test items for young children

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Schuck, Tizian ; Siener, Maximilian:
How to compare physical fitness when different tests are performed : A cross-sectional study on conversion formulas of common test items for young children.
In: International Journal of Sports Science & Coaching. (2026) . - S. 1-8.
ISSN 2048-397X
DOI: https://doi.org/10.1177/17479541251407995

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Abstract

Background: Physical fitness tests are crucial for evaluating athletic development and health in children. However, methodological variations in standardized test batteries (e.g., different strength test durations) hinder comparisons between studies. Despite the widespread use, conversion formulas remain largely unexplored. This study aimed to develop conversion formulas between commonly used physical fitness tests in children, focusing on strength, speed, and flexibility.
Methods: A sample of 878 primary schoolchildren (age: 8.3 ± 0.6 years; 49.5% boys) performed ten physical fitness tests, comprising two tests for each of five different abilities: sprint speed (10 m/20 m), flexibility (standing-&-reach/sit-&-reach), throwing ability (with ball/shuttlecock), core strength (30 s/40 s Sit-ups), and upper limb strength (30 s/40 s Push-ups). Regression analyses (curve estimation) with multiple function types were employed to develop conversion formulas between corresponding test variations.
Results: Significant gender differences were found in certain tests ( p < 0.001, 0.3 ≤ d ≤ 1.1), resulting in the development of separate calculation formulas for males and females. Linear and quadratic models explained up to 99% of the variance for sprint, Push-up, and Sit-up tests. Quadratic models explained up to 84% of the variance for flexibility tests, whereas linear models explained up to 96% for throwing tests. Adding a constant term improved variance explanation only for flexibility tests.
Discussion: The results indicate that simple extrapolations of sprint and strength values are unsuitable for converting test results. The proposed conversion formulas offer a more nuanced approach, potentially enabling comparisons between different test methods.