# Accuracy of anthropometric-based predictive equations for tracking fat mass over a competitive season in elite female soccer players: a validation study

## TL;DR

This study compares the accuracy of two anthropometric equations for tracking body fat in elite female soccer players over a season, finding that both are valid alternatives to lab methods.

## Contribution

The study evaluates the longitudinal validity of anthropometric equations for fat mass tracking in elite female athletes during a competitive season.

## Key findings

- Evans’s equation showed no bias compared to DXA with R² values of 0.69 and 0.70.
- Both equations accurately tracked fat mass changes over time with R² values between 0.68 and 0.83.
- Evans’s equation outperformed Warner’s at the group level despite overestimating in low-fat and underestimating in high-fat individuals.

## Abstract

Body fat is a key body composition parameter monitored in soccer. Identifying reliable alternatives to laboratory techniques for assessing body fat during the competitive period is essential. This study aimed to evaluate the cross-sectional and longitudinal validity of anthropometric prediction equations in elite female soccer players.

Eighteen female soccer players (age: 26.6 [3.8] years; height: 168 [6.3] cm; body mass: 64.1 [7.4] kg; body mass index: 22.7 [1.9] kg/m²) from an Italian Serie A team were assessed at four time points during a competitive season. Fat mass was estimated using anthropometric equations by Evans and Warner and compared to dual-energy X-ray absorptiometry (DXA), which served as the reference method.

Cross-sectional agreement analysis revealed a bias of -4.5% with Warner’s equation, while Evans’s equation showed no bias compared to DXA, with coefficient of determination (R²) values of 0.69 and 0.70, respectively. Both methods showed a negative association (Evans: r = -0.53, Warner: r = -0.63) when the difference between the values and the mean with DXA were correlated. Longitudinal agreement analysis showed no significant differences in fat mass changes between the anthropometric equations and DXA, with R² values ranging from 0.68 to 0.83. The 95% limits of agreement between the methods for individual changes in fat mass ranged from − 3.3 to 3.2%. Furthermore, no significant changes (p > 0.05) in fat mass were observed over the season with any method.

At the group level, Evans’s equation provides valid estimates of fat mass, whereas it may overestimate values in players with low body fat and underestimate them in those with high fat mass. The Warner equation showed the same trend as Evans at the individual level, also resulting in poor accuracy at the group level. Despite this, both anthropometric equations are valid alternatives to DXA for monitoring fat mass changes during the season, with Evans’s equation showing superior overall performance.

The online version contains supplementary material available at 10.1186/s13102-025-01115-4.