Benchmarking Formula One auto racing circuits: a two stage DEA approach

Abstract

Formula One (F1) World Championship has become one of the most successful sport tournaments over the last decade. Races take place in modern-day closed racing circuits, whose design plays a key role in racing results. This paper proposes a framework for the design efficiency assessment of the more representative racing circuits that hosted Grands Prix during the recent F1 seasons. The proposed approach considers two basic circuit features (namely, circuit length and number of turns) and combines car performance and race safety data. The methodology used is based on data envelopment analysis (DEA). The number of inefficient circuits is small, five in the case of variable returns to scale and nine (out of 21) when constant returns to scale are assumed. Potential improvements in terms of speed, fuel consumption and safety targets are computed. For each inefficient circuit its reference set is identified. Also, a second-stage DEA fractional regression analysis is carried out to study the influence of the circuit type (race or street circuit), the track orientation (clockwise or anticlockwise) and the number of red-flagged races due to rainfall on the circuits’ efficiency. The results indicate that all three variables are significant. The implications of the results for track designers and F1 organizers are also discussed.