Journal of African Development

This study aimed to develop an integrated anthropometric and motor fitness profile of youth roller sports skaters using multivariate statistical techniques. The primary objective was to identify latent physical traits and classify skaters into distinct morpho-functional clusters aligned with sport-specific demands. Fifteen male roller sports skaters aged 11 to 14 years (M = 12.7 ± 1.1) were assessed for 12 anthropometric traits, including height, weight, limb lengths, girths, bone breadths and skinfolds, alongside six motor fitness variables: agility (shuttle run), speed (30m sprint), power (standing broad jump), flexibility (sit and reach), core endurance (sit-ups), and balance (stork stand test). Descriptive statistics, Pearson correlations, Principal Component Analysis (PCA), and hierarchical cluster analysis were applied using IBM SPSS (v26.0). Descriptive statistics indicated normal developmental variability in anthropometric and motor fitness traits among participants. Pearson’s r indicated strong correlations among body composition measures (e.g., weight, girths, bone breadths) but weaker associations with performance traits like balance and agility. PCA extracted four components accounting for 85.2% of the total variance. The first component reflected musculoskeletal mass, while the second was characterized by agility and speed-related traits. Cluster analysis yielded three athlete profiles differing in body size, limb proportions and fitness capabilities. Multivariate profiling revealed meaningful somatic patterns and performance groupings among youth roller skaters. These findings underscore the value of combining morphological and motor fitness assessments to support targeted talent identification and personalized training interventions. The approach offers a sport-specific model for physical profiling in early adolescence.