From monitoring metrics to decision evidence: validating actionability in applied sport science

In high-performance sport, athlete monitoring and management systems now make physiological, biomechanical, and contextual data easier to collect and share than ever before. Yet it remains unclear whether this expansion has produced better decisions or improved athlete-relevant outcomes. Existing frameworks classify monitoring tools, establish standards for verifying and validating biometric technologies for a stated use, and, increasingly, link patterns of monitoring signals to candidate coaching actions. These advances are necessary, but they do not establish whether valid monitoring information influences decisions or improves the outcomes those decisions are intended to affect. In this Perspective, we argue that actionability should be treated as a claim about decision utility rather than as an inherent property of a metric or monitoring system. We distinguish two levels of evaluation: decision impact, whether monitoring information influences the decision that would otherwise have been made; and outcome evidence, whether the resulting decision improves or protects athlete-relevant outcomes. Practical value also depends on whether a pathway is implemented as intended and whether its benefits justify the burden of implementation. To support evaluation in applied settings, we outline feasible approaches ranging from descriptive audits and decision-impact studies to pragmatic outcome designs. Although our primary focus is high-performance sport, the same decision-evidence logic may extend to health, rehabilitation, and amateur sport. Ultimately, monitoring should be judged by the strength of evidence linking its use to decisions that serve the athlete's best interest.