In this paper we develop a method and relevant feature constructs for the measurement of accident risk exposure from a large sample of real-world GPS data that includes accident and accident-free drivers. For trip frequency and accumulated driven distance features, an evaluation of their discriminatory power is given based on computational results. In our conclusion, we briefly discuss suitable classification approaches and limitations arising from external validity considerations.