Predicting Standings in F1 Sports Driver's Championship using Lasso Penalised Regression

Abstract

F1 has always consisted of intense battles of newly developed technologies between teams. Each year, all 10 teams in F1 develop new strategies and cutting-edge technologies to stay ahead of their competitors. The strategies that they develop are a product of thousands of simulations consisting of millions of variables including weather, temperature, pressure, drivers, machinery, etc. that affect the chances of winning. The aim of this research is to understand such variables & data and propose a model to predict the winning team, as close as possible to genuine results.