Interindividual variability in road runners: A secondary analysis as a basis for digital twin modeling in sport (Research, Society and Development, 2026)
Road running is a widely practiced sport characterized by a high diversity of participant profiles. Performance in this modality results from the interaction of biomechanical, physiological, and demographic factors that vary substantially among individuals, which limits the applicability of generalist models based on population averages. This study aimed to analyze interindividual variability among runners from a road race using secondary data as a basis to discuss the need for individualized digital twins in the sports context. This observational, quantitative, and retrospective study was conducted through the analysis of public, aggregated, and anonymized data from 7,096 runners who participated in the Redepharma Run 2025, held in the city of Campina Grande, Paraíba, Brazil. The analyzed variables included sex, age group, and race distance selection. The results demonstrated marked demographic and participatory heterogeneity among runners, with significant overlap between groups traditionally used for classification, such as sex and age, indicating that individuals with distinct characteristics may present similar participation patterns. These findings demonstrated that approaches based on average profiles are insufficient to adequately represent the complexity of human behavior in road running. It is concluded that the high interindividual variability observed poses relevant challenges to generic performance modeling and reinforces the need for personalized approaches, such as individualized digital twins, to improve understanding, monitoring, and application of this technology in sport.