This work introduces a novel theoretical framework for representing turbulent statistics through partitions of the state space. Part 1 focuses on the development of the theory and methodology behind this approach. The method provides a systematic way to partition the state space, offering a more structured and refined representation of turbulence. The resulting framework is a powerful tool for analyzing turbulent flows and could pave the way for improved statistical modeling techniques.