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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2507.10966 |
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| _version_ | 1866918092589760512 |
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| author | Weissbock, Joshua Mills, Shirley |
| author_facet | Weissbock, Joshua Mills, Shirley |
| contents | Formula One race weekends are structured around multiple sessions: practices, qualifying, and the Grand Prix itself, each contributing to final race performance. This study analyzes nearly two decades of races, encompassing 7,800 driver-weekend observations, to quantify the predictive value of each session on race outcomes. Expanding on prior research with a larger dataset and a longitudinal perspective, statistical analyses using contingency coefficients and Ordinal Logistic Regression update prior knowledge that qualifying performance is the strongest determinant of final race position, surpassing race start positions and practice results as indicators. Unlike grid positioning at the start of the race, which is susceptible to penalties and external disruptions, qualifying results provide an unbiased measure of driver and car capability. These findings reinforce the strategic emphasis already placed on qualifying, offering an empirical validation of its dominant role in determining race outcomes across varied seasons and eras. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_10966 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Evaluating the Predictive Power of Qualifying Performance in Formula One Grand Prix Weissbock, Joshua Mills, Shirley Applications Formula One race weekends are structured around multiple sessions: practices, qualifying, and the Grand Prix itself, each contributing to final race performance. This study analyzes nearly two decades of races, encompassing 7,800 driver-weekend observations, to quantify the predictive value of each session on race outcomes. Expanding on prior research with a larger dataset and a longitudinal perspective, statistical analyses using contingency coefficients and Ordinal Logistic Regression update prior knowledge that qualifying performance is the strongest determinant of final race position, surpassing race start positions and practice results as indicators. Unlike grid positioning at the start of the race, which is susceptible to penalties and external disruptions, qualifying results provide an unbiased measure of driver and car capability. These findings reinforce the strategic emphasis already placed on qualifying, offering an empirical validation of its dominant role in determining race outcomes across varied seasons and eras. |
| title | Evaluating the Predictive Power of Qualifying Performance in Formula One Grand Prix |
| topic | Applications |
| url | https://arxiv.org/abs/2507.10966 |