Associations between anthropometric outcomes and fat percentage with physical performance in professional soccer players: a cutoff points approach

Abstract With a plethora of anthropometric and body composition measurements, may be challenging for soccer technical staff determining the most suitable protocol for their players. Objectives Therefore, the aim of the study was to analyze the correlations of anthropometric measures and fat percentage obtained by different protocols with the physical performance of male professional soccer players. Additionally, the study aimed to propose cutoff points for anthropometric measures and fat percentage. Methods Fifty-two male soccer players (24.60 ± 4.98 years) from a state championship’s second division participated. The sum of skinfolds and fat percentage were obtained using four reference protocols (Pollock seven-skinfolds, Jackson and Pollock three-skinfolds, Jackson and Pollock three-skinfolds of the upper limbs, and Faulkner four-skinfolds). Physical performance was assessed by squat jump, counter movement jump, 30 cm drop jump, 20 m sprint, and YoYo intermittent recovery level 1 (YoYoIRL1) tests. Pearson, Spearman, and ROC curve analysis were used considering α <0.05 as significance level. Results Significant correlations occurred between the abdominal skinfold (r=−0.579), chest, abdominal, and front thigh skinfolds sum (rho=−0.518), and the Jackson and Pollock fat percentage protocol using these skinfolds (r=−0.534) with the YoYoIRL1 (all p<0.001). Cutoff points for these measurements were determined to be 20 mm (area under the curve (AUC)=0.800, sensitivity=92.7 %, specificity=63.6 %), 33 mm (AUC=0.783, sensitivity=68.3 %, specificity=81.8 %), and 13 % (AUC=0.787, sensitivity=95.1 %, specificity=54.5 %), respectively. Conclusions Therefore, the soccer technical staff can implement these measures, largely associated with physical performance, in players with characteristics similar to the evaluated group. The proposed cut-off points provide a practical alternative for integration into other monitoring strategies.