Publicação
Optimizing race strategy: a machine learning model for predicting formula 1 pit stop timing
| datacite.subject.fos | Ciências Sociais::Economia e Gestão | pt_PT |
| dc.contributor.advisor | Batikas, Michail | |
| dc.contributor.author | Hettmann, Valentin Fedor | |
| dc.date.accessioned | 2024-11-13T14:24:55Z | |
| dc.date.available | 2024-11-13T14:24:55Z | |
| dc.date.issued | 2024-01-11 | |
| dc.date.submitted | 2024-01-11 | |
| dc.description.abstract | This thesis explores Formula 1 pit stop strategies through advanced analytics, with a focus on driver clustering in relation to performance, tactical, and behavioural aspects. Our approach led to the identification of four distinct driver categories, providing a framework to investigate various pit stop strategies. By integrating these driver profiles into predictive models, the study delves into the impact of driver characteristics on team strategy and pit stop efficiency. We introduce a novel dimension by developing a binary prediction model for pit stop timing, thoroughly evaluated within a simulation environment. This research contributes to a more refined understanding of strategic elements in Formula 1, demonstrating the role of tailored analytic methods in optimizing racing tactics and decision-making processes. | pt_PT |
| dc.identifier.tid | 203605616 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10362/175111 | |
| dc.language.iso | eng | pt_PT |
| dc.relation | UID/ECO/00124/2013 | pt_PT |
| dc.subject | Machine learning | pt_PT |
| dc.subject | Predictive modeling | pt_PT |
| dc.subject | Strategy | pt_PT |
| dc.subject | Pit stop | pt_PT |
| dc.subject | Motorsport | pt_PT |
| dc.subject | Formula 1 | pt_PT |
| dc.title | Optimizing race strategy: a machine learning model for predicting formula 1 pit stop timing | pt_PT |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | masterThesis | pt_PT |
| thesis.degree.name | A Work Project, presented as part of the requirements for the Award of a Master’s degree in Business Analytics from the Nova School of Business and Economics. | pt_PT |
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