Why More Data Breaks Decision-Making in Elite Sport

Elite sport has entered a paradoxical phase: as data precision increases, consensus collapses. High-quality monitoring systems (GPS, HRV, load, AI analytics) often converge internally yet produce stable, conflicting recommendations. This record introduces the Pre-Resolution Reality Layer (PRRL)—the domain where further precision no longer leads to convergence—and the Singularity Seed Cycle Law (SSCL) as its regime-boundary classifier. Rather than correcting models or resolving disagreement, SSCL identifies when divergence is structural. This provides a practical decision lens for coaches, sports scientists, and AI systems facing irreducible conflict under high precision. The record includes: A full conceptual framework (PDF) A one-page regime lens for rapid dissemination An executable Python demonstrator Canonical statement:SSCL operates at the Pre-Resolution Reality Layer, identifying when further precision no longer leads to convergence but signals an intrinsic regime boundary.