Coaching diversity in Bulgarian youth football: A factorial, cluster, and SWOT analysis of methodologies and development strategies

Authors

DOI:

https://doi.org/10.26418/tajor.v3i3.96271

Keywords:

Youth Football, Coaching in Football, Bulgarian Football, SWOT.

Abstract

Background. Contemporary youth football development requires evidence-based coaching methodologies that align with both theoretical models and practical demands. However, discrepancies between elite and grassroots coaching approaches remain underexplored. This study aimed to identify prevailing pedagogical profiles among Bulgarian youth football coaches and to analyze the systemic factors shaping coaching practice. Methods. A mixed-methods design was employed, combining exploratory factor analysis (EFA), cluster analysis, and SWOT (strengths"“weaknesses"“opportunities"“threats) diagnostics. Data were collected from a national sample of 392 UEFA-licensed coaches working at different age and club levels. Results. Three pedagogical profiles emerged: game-based (28.1% variance, α = 0.85), technical/traditional (21.4%, α = 0.77), and tactical/structured (15.8%, α = 0.79). While elite academies favored tactical frameworks, grassroots coaches predominantly used isolated drills (λ = 0.82), revealing a clear gap between coaching theory and field application. SWOT findings indicated strong coach dedication and player motivation (95 mentions), but also systemic weaknesses such as methodological inconsistency (52 mentions) and infrastructural deficits. Opportunities included the integration of digital tools and sports science, whereas threats focused on talent emigration and limited funding. Conclusions. There is a need for greater coherence between pedagogical models and everyday coaching practices, particularly at the grassroots level. Contributions: This study introduces the first data-driven typology of Bulgarian youth coaches and offers actionable insights for modernizing coach education systems through frameworks such as Teaching Games for Understanding (TGFU) and the Constraints-Led Approach (CLA).

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Published

2025-09-04