From partner synchrony to corner support: interpersonal co-regulation and performance recovery in DanceSport and boxing.

Sport psychology has often treated performance regulation as predominantly intrapersonal, yet competitive recovery can also be shaped by relational information. This Conceptual Analysis introduces the Relational Co-Regulation and Performance Recovery (RCPR) Model, a perturbation-centered framework for explaining how partner- and coach-generated inputs may alter recovery after within-competition disruption. Crucially, relational regulatory input is defined independently of success: an observable signal is a regulatory attempt because of its timing, content, and plausible task function, not because recovery follows. A co-regulatory transaction occurs when that input enters a temporally linked interaction loop of detection, appraisal, response, and possible updating; its outcome may be beneficial, null, or dysregulatory. The model also separates psychological state restoration, functional task restoration, and subsequent performance recovery rather than treating them as a single outcome. DanceSport and boxing are used as maximum-contrast theoretical exemplars rather than empirically established sport categories. DanceSport foregrounds predominantly continuous, reciprocal, embodied partner regulation during joint action, whereas boxing foregrounds predominantly intermittent and relatively asymmetrical coach-athlete regulation between rounds. Ecological dynamics, joint action, interpersonal emotion regulation, social support, communal coping, and coach-athlete relationship perspectives are integrated while their distinct explanatory roles are retained. Six core falsifiable propositions address incremental validity, regulatory architecture, matching and uptake, dyadic transmission and co-dysregulation, non-linear dosage constraints, and relational-training specificity. The model generates a research agenda based on perturbation-centered time series, representative simulations, quasi-experimental designs, and converging within-person evidence.