Demonstrating a linkage between known footwear and a questioned impression left at the scene of a crime is a function of the observed agreement between class, subclass and wear features exhibited by the impressions being compared. If sufficient detail is present (beyond class and subclass characteristics), then the similarity, clarity, quantity and quality of what are termed randomly acquired characteristics (RACs) (such as nicks, tears, cuts, etc.) can form the basis of a source identification. When an examiner evaluates the possibility of a source identification, the weight attributed to the features being observed is based on the assumption that RAC acquisition is random. Thus, the final conclusion reported by the analyst regarding the possible source of a questioned impression is a function of how likely the observed RAC agreement (in terms of position, size, shape, geometry, etc.) would be expected by chance alone when comparing unrelated outsoles. Inherent in this approach is the presumption that RACs are indeed randomly distributed on outsoles (and the term random has even become part of the features label). However, there is limited evidence to support this assertion (despite the fact that it is based on sound reasoning --- RACs are assumed to be acquired based on numerous variables, such as the nature of the outsole material, the terrain traveled, the way the wearer walks, the type of usage, the degree of wear, the pressure of contact, etc.). In fact, most theoretical models regarding the chance association of features assume independence, and are therefore based on untested assumptions, and the remaining empirical studies have either been of limited sample size, or report conflicting results (claims of both dependence and uniformity in distribution). Thus, there remains a significant research deficit concerning the spatial distribution of RACs on outsoles, of which existing published work cannot clarity. In response to this fundamental need for study, the aim of this project is to perform a detailed assessment of RAC distributions as a function of outsole contact area and tread design, using the largest currently available database of 72,306 acquired features collected from 1,300 outsoles. Moreover, this evaluation will utilize generally accepted methods within the field of spatial statistics to compare RAC distributions to appropriately constructed Poisson point processes in order to clarify the nature of RAC distributions, and the degree to which their localization can be regarded as stochastic.