Formula One Race Analysis Using Machine Learning

Abstract

Formula One (also known as Formula 1 or F1) is the highest class of international auto-racing for single-seater formula racing cars sanctioned by the Fédération International de automobile (FIA). The World Drivers’ Championship, which became the FIA Formula One World Championship in 1981, has been one of the premier forms of racing around the world since its inaugural season in 1950. This article looks at cost-effective alternatives for Formula 1 racing teams interested in data prediction software. In Formula 1 racing, research was undertaken on the current state of data gathering, data analysis or prediction, and data interpretation. It was discovered that a big portion of the league’s racing firms require a cheap, effective, and automated data interpretation solution. As the need for faster and more powerful software grows in Formula 1, so does the need for faster and more powerful software. Racing teams benefit from brand exposure, and the more they win, the more publicity they get. The paper’s purpose is to address the problem of data prediction. It starts with an overview of Formula 1’s current situation and the billion-dollar industry’s history. Racing organizations that want to save money might consider using Python into their data prediction to improve their chances of winning and climbing in the rankings.