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Predicting Formula 1 Races using Ordered Logistic Regression and Elo Ratings
Name: Luke Pritchard
Major: Statistical & Data Sciences
Minor: Global Media and Digital Studies
Advisor: Dr. Moses Luri, Dr. Jillian Morrison (second reader)
This paper investigates the Formula One World Championship in the context of predicting race results. Formula One is an incredibly popular sport that takes place on 5 continents around the globe that has over 2 billion dollars in revenue per year. Positions in each race can be a massive difference in terms of prize and sponsorship money/exposure. Previous research was done for Junior IS to see if the final championship results could be predicted to moderate success. This paper looks to predict individual races. To do so, ordinal logistic regression and the Elo method are used, combined, and compared. Originally used in chess and now used in many areas, such as the NBA or in video games, the Elo ranking system tries to approximate the skill of people through mathematics. Data is sourced from the FIA directly and contains current and historical race result data. This research seeks to find out if Elo ranking works well in this area, and if combining it with data from Qualifying sessions that take place before the race and previous races in a season can be useful. Specifically, the 2017-2021 era of high aero, turbo-hybrid cars are investigated.
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Posted in Comments Enabled, Independent Study, Symposium 2022 on April 26, 2022.
5 responses to “Predicting Formula 1 Races using Ordered Logistic Regression and Elo Ratings”
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Nice job Luke! Races are random, huh? Your dad might disagree!
Great job, Luke! I know about Elo from my days playing competitive Overwatch on PS4, but had no idea about its use elsewhere. Thank you for sharing and congratulations!
This is really cool research, Luke! I was unaware of the history of the Elo rating and its use across a broad range of competitions, including chess. Congratulations!
Luke, Good job! I learned a lot about races from your presentation! All the best after graduation!
Luke, what exciting work! Congratulations, and best wishes for what’s ahead!