Abstract
This study utilizes a unique shared-course environment to compare the average speeds of the world’s two fastest auto racing formats, Formula One (F1) and IndyCar. These two racing circuits are distinct in terms of their places of origin, where in the world they typically source drivers and hold races, and the locations of their respective fan bases. Though F1 and IndyCar, cars share several common physical characteristics, their engines, chassis, tires, steering, and aerodynamics are distinct. While these two formats are commonly recognized as the two fastest forms of full-course auto-racing, the relative average speed capabilities of the two formats (e.g., over a neutral course) are unclear, as they have historically held official events on different sets of courses. In 2019, however, at the Circuit of the Americas in Austin, TX, F1 and IndyCar both held races over the same course, allowing for a natural experimental comparison in which year (state of technology), course, and even general weather conditions were common across the two races. By modeling qualifying times conditional on driver, race format, and other car characteristics, we statistically compare the relative average speeds of the two formats over the same course. In a set of fixed and mixed effects linear and polynomial regression models, we find that F1 was significantly and substantially faster than IndyCar. Average speed difference between the two formats was approximately 16.5 miles per hour over the course. These results inform not only race speed supremacy but returns to technological investment in the private sector.
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