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This paper uses time diary data to demonstrate how the spatial distribution of Americans’ routine activities changes over the course of a day. These patterns are then used to create different street robbery outcome variables for different times of the day at the census block level in Philadelphia, PA USA. A series of count regression models and equality of coefficient tests are then used to explore the effects of different facilities on street robbery outcomes across different time blocks in order to determine whether these facilities have different effects on street robbery patterns across different periods of the day. The implications of the results for crime and place theory and predictive crime modeling are then discussed.