Conflict theory holds that law and the mechanisms of its enforcement are used by dominant groups in society to minimize threats to their interests posed by those whom they label as dangerous, especially minorities and the poor. Racial profiling has become an issue of significance in the past several years. Using data collected by the Richmond, Virginia Police Department, this article explores whether police traffic stop, search, and arrest practices differ according to racial or socioeconomic factors among neighborhoods, by means of a micro-level analysis of police practices using census tract data from a single city. Three principal findings emanate from this research. First, the total number of stops by Richmond police was determined solely by the crime rate of the neighborhood. Second, the percentage of stops that resulted in a search was determined by the percentage of the Black population. Third, when examining the percentage of stops that ended in arrest/summons, the analyses suggest that both the percentage of the Black population and the area crime rate served to decrease the percentage of police stops that ended in an arrest/summons. Implications for conflict theory and police decision-making are addressed. In conclusion, it is suggested that the collection of multiple levels of data are necessary for a more complete understanding of how police officers make decisions on the street. Tables provide information on a description of variables, stop rate regressed against predictor variables, search regressed against predictor variables, and arrest regressed against predictor variables. An appendix provides a list of variables captured. A source list of references is included.