Predicting winners in the Formula 1 car racing season

Faculty Sponsor

Saso Poposki


Arts and Sciences


Data Science, Statistics

Presentation Type

Oral Presentation

Symposium Date

Spring 4-29-2021


Sports and statistical analysis have gone hand in hand for as long as many of us can remember. Predicting the winner of any sports contest is always filled with a group of passionate and certain voices. The use of predictive modeling with statistics has been a very popular method for predicting outcomes in the world of sports. With increased access to computers and data in our world today, predictive modelling has become ever more accessible to sports fans. This research project aims to use predictive modeling to predict the winner in all 23 races of the Formula 1 world championship in the 2021 season. Formula 1 (or F1) is the highest level of international motor racing in the world, with 70 years of pedigree. The history of F1, combined with vast amounts of publicly available historical data, allows us to pursue this model. This model will focus on data relating to the drivers, team standings, qualifying teams, results, weather, and circuits.

Biographical Information about Author(s)

I am a Senior Data Science major at Valparaiso University. For as long as I can remember, I have always been passionate about motorsport; especially Formula 1 (or F1). The increasing use of data analytics in sports has inspired me to use all the things I have learned at Valpo to build a prediction model around F1. I hope to potentially use my data science experience to one day work for a motorsport team, potentially in F1.

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