Since nearly the beginning of the wide spread adoption of the automobile, motorized traffic data collection has occurred so that decision makers have information to plan the transportation system. Widespread motorized traffic data collection has allowed for estimating traffic volumes using developed extrapolation methods whereby short-term counts in sample locations can be expanded to longer periods. As states and local planning agencies make investments in bicycle infrastructure and count programs develop, similar extrapolation methods will be needed. The only available guidance on extrapolating bicycle counts comes from the National Bicycle and Pedestrian Documentation Project (NBPDP), yet no validation of these factors have been done to assess their usability in specific area. Using bicycle traffic count data from the Central Lane Metropolitan Planning Organization Count Program in Oregon, this research demonstrates that using study area data to generate time-of-day factors produces results with less error compared to application of the NBPDP time-of-day factors. Factors are generated in two separate way in order to reduce error from estimating daily bicycle volumes. Factors groups are developed using bicycle facility type where counts are collected. This research also seeks to add to the literature concerning bicycle travel patterns by using study area data to establish a university travel pattern exemplified by a flat hourly distribution from morning to evening.