Current practices based on estimated volume and basic queuing theory to calculate delay resulting from non-recurrent congestion do not account for the day-to-day fluctuations in traffic. In an attempt to address this issue, probe GPS data are used to develop impact zone boundaries and calculate Vehicle Hours of Delay (VHD) for incidents stored in the Traffic Response and Incident Management Assisting the River City (TRIMARC) incident log in Louisville, KY. Multiple linear regression along with stepwise selection is used to generate models for the maximum queue length, the average queue length, and VHD to explore the factors that explain the impact boundary and VHD. Models predicting queue length do not explain significant amounts of variance but can be useful in queue spillback studies. Models predicting VHD are as effective as the data collected; models using cheaper-to-collect data sources explain less variance; models collecting more detailed data explained more variance. Models for VHD can be useful in incident management after action reviews and predicting road user costs.