UFC 333: Volkanovski vs Evloev
| UFC 333: Volkanovski vs Evloev | ||
| Statistical Win Probabilities | October 24, 2026 | ||
| Bout | Predicted Winner | Probability |
|---|---|---|
| Alexander Volkanovski vs. Movsar Evloev | Movsar Evloev | 70.6% |
| Petr Yan vs. Merab Dvalishvili | Merab Dvalishvili | 51.8% |
| Lone’er Kavanagh vs. Ramazan Temirov | Ramazan Temirov | 52.1% |
| Alexander Volkov vs. Rizvan Kuniev | Rizvan Kuniev | 51.5% |
| Dominick Reyes vs. Azamat Murzakanov | Dominick Reyes | 53.3% |
| Abus Magomedov vs. Cam Rowston | Cam Rowston | 66.0% |
| Nikita Krylov vs. Abdul Rakhman Yakhyaev | Abdul Rakhman Yakhyaev | 85.9% |
| Grant Dawson vs. Nurullo Aliev | Nurullo Aliev | 68.6% |
| Daniel Santos vs. Bolaji Oki | Bolaji Oki | 58.5% |
| Iasmin Lucindo vs. Nicolle Caliari | Iasmin Lucindo | 68.7% |
| Simplified Model (Limited Data) | ||
| Aaron Pico vs. Losene Keita | Losene Keita | 53.7% |
| Abubakar Vagaev vs. Jacob Malkoun | Jacob Malkoun | 54.7% |
| Colby Thicknesse vs. Asaf Chopurov | Asaf Chopurov | 54.8% |
| Noah Gugnon vs. Kody Steele | Noah Gugnon | 60.9% |
| Probabilities are statistical estimates, not guarantees. | ||
Note
These winning probabilities are computed using historical data and classical statistical learning models. For some bouts, detailed career data was available for both fighters. For others, such as matches involving newer athletes, only limited data could be used (marked above as “limited data”). Not all estimates carry the same statistical confidence level, and limited-data calculations are softer. Combat sports are inherently unpredictable; unexpected factors like sudden injuries or late-notice card changes cannot be captured by mathematical models. Therefore, these figures should be treated strictly as data-driven statistical estimates, not guarantees of any outcome.
Arti Statistics LLC is not a gambling platform. We do not accept wagers, offer real-money gaming, or provide betting advice. The predictive analytics displayed above are provided entirely for free educational and informational purposes to help fans better understand the fight game through data science. If you have any questions or comments about our models, please reach out to our team.