Essential dynamics is the application of principal component analysis to a dynamic trajectory derived from a simulation protocol in order to extract biologically relevant information contained in the high dimensional data. In this work, we apply the methodology of essential dynamics to protein trajectories derived from geometrical simulations, which are based on the perturbation of geometrical constraints inherent in a protein. Specifically, we show that the geometrical simulation model is highly efficient for the determination of native state dynamics. Furthermore, by the application of subspace analysis to the essential subspaces of multiple sets of proteins that were simulated under multiple modeling paradigms, we show that the geometrical modeling paradigm is internally consistent and provides results that are qualitatively and quantitatively similar to results obtained from the more commonly employed methods of elastic network models and molecular dynamics. The geometrical paradigm is therefore established as a viable alternative or co-model for the investigation of native state protein dynamics with application to both small, single domain proteins as well as large, multi domain systems.