Paper Key : IRJ************799
Author: Suneet Adithya Menon,Krishna Ranjan M ,Aman Kumar
Date Published: 12 Nov 2024
Abstract
Where the actual effectiveness of the driver is a mixture of individual skill and the advantages provided by the car's constructor, this mutual interplay complicates deeper questions about performance within the discipline. It remains challenging to identify the best driver, the most successful constructor, or how significantly each contributes to winning races. This study addresses these questions using data from the hybrid phase of Formula One, spanning 1950 through 2021. We outline a novel approach using linear regression combined with Monte Carlo simulations to analyze finishing positions at individual races. The linear regression model captures the key factors affecting performance, while the Monte Carlo method adds robustness by simulating race scenarios to account for uncertainties. Our findings suggest that Hamilton and Verstappen are standout competitors, with top teams like Mercedes, Ferrari, and Red Bull consistently outperforming others. Results show that approximately 88% of the variance in race outcomes can be attributed to constructor contributions, offering a versatile framework for evaluating sports performance.Keywords: Linear regression; Monte Carlo; racing; sports performance