The aim of this paper was to analyze traffic crash data by using a simplified method in determining significant factors that increase the risk of a motorcyclist being fatally injured once involved in a motorcycle crash in Ohio. The concept of overrepresentation, which is similar to relative risk, was used in identifying significant variables associated with the elevated risk of a motorcycle crash resulting into a fatality. The overrepresentation factor (ORF) was calculated for each variable of interest. The ORF offers a simple but powerful procedure of determining whether a certain factor significantly occurs more or less frequently in one subset than in its complementary subset. The procedure involved determining the magnitude of the overrepresentation by computing the ORF values and determining whether or not the overrepresentation is statistically significant by computing the confidence intervals over ORF values at a 5% alpha level. The results show that being age 65 and over, riding while speeding, riding while under the influence of alcohol or drugs, riding without a helmet, riding at nighttime, being male, and being the operator were statistically significant motorcyclist-related characteristics that elevated the risk of being fatally injured. The significant roadway characteristics included crashes occurring on major roads, on horizontal curves (bends), on graded road segments, and on open roadway segments (non-intersections). Environment conditions such as dark with light or dark with no light and when the weather condition was cloudy had significant effects of increasing the chances of motorcyclists’ fatal injuries once they get involved in traffic crashes. Moreover, crashes occurring on Saturdays pose significantly higher risks of fatalities when compared with other days of the week. In terms of crash type characteristics, a motorcyclist had elevated risks of being fatally injured when involved in single-vehicle crashes especially running off-the-road, crossing the median/centerline, and hitting a curb. Head-on and angle collisions in multivehicle crashes were significant causes of fatal injuries. The overrepresentation method was able to correctly identify similar fatal risk factors that were identified in previous studies that used more advanced and rigorous methods.