Conceptual framework proposes scheduled 36-hour multidimensional recovery periods across elite sports organizations, suggesting structured micro-recovery mitigates systemic fatigue in athletes and...
Recovery in elite professional sport is now widely understood as a multidimensional process spanning physiological, psychological, cognitive, and social domains, yet recovery models applied in professional clubs and sporting organisations have been slow to reflect this. Most remain reactive and athlete-centred, leaving the full complexity of competitive fatigue inadequately addressed and the equivalent recovery demands on coaching and performance staff entirely unrecognised. No structural framework currently places initiative-taking, calendar-embedded multidimensional recovery as a deliberate component of seasonal planning. Main body. We introduce micro-recovery dosing (MRD): proactively planned, pre-scheduled 36-hour multidimensional recovery periods embedded within the competitive season as a proposed starting point at five to eight instances per year, extending to all members of the high-performance organisation. Drawing on neuromuscular recovery kinetics, autonomic science, sleep architecture research, occupational recovery psychology, and complex systems theory, we construct a convergent theoretical rationale for the proposed parameters and distinguish MRD from related constructs. We present a role-differentiated implementation framework with supporting evidence and a discussion of emerging AI-driven monitoring tools. Conclusions. Taken together, the four-domain convergent rationale and the complex systems perspective provide a theoretically coherent basis for MRD’s proposed structure. We argue for a specific organisational transformation: the shift from recovery as an incidental gap between performance demands to an intentionally designed recovery architecture that encompasses athletes and staff alike. The article identifies the active ingredient problem as the central scientific challenge and sets out a structured empirical agenda.
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Shalom et al. (2026) studied this question.
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