Benchmarking Formula 1 results using a normal model
Fuente:
arXiv
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866916060430598144 |
|---|---|
| author | Fry, John Fanzon, Silvio Austin, Mark Brighton, Tom |
| author_facet | Fry, John Fanzon, Silvio Austin, Mark Brighton, Tom |
| contents | There is enduring interest in disentangling the effects of skill and luck in sport. A key issue in Formula 1 is distinguishing between car-level and driver-level effects. Four elite teams currently dominate Formula 1 and have won every major race for the last four years. In this paper we use univariate and bivariate normal models to quantify reasonable performance expectations at both driver and team levels, distinguishing between elite and non-elite teams. We illustrate our approach with an application to the last fully completed 2025 season. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_15192 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Benchmarking Formula 1 results using a normal model Fry, John Fanzon, Silvio Austin, Mark Brighton, Tom Applications There is enduring interest in disentangling the effects of skill and luck in sport. A key issue in Formula 1 is distinguishing between car-level and driver-level effects. Four elite teams currently dominate Formula 1 and have won every major race for the last four years. In this paper we use univariate and bivariate normal models to quantify reasonable performance expectations at both driver and team levels, distinguishing between elite and non-elite teams. We illustrate our approach with an application to the last fully completed 2025 season. |
| title | Benchmarking Formula 1 results using a normal model |
| topic | Applications |
| url | https://arxiv.org/abs/2603.15192 |