TennisEdge's AI model finds no betting value in A. Eala vs M. Sawangkaew (Birmingham on 2026-06-05) — the market is efficient, with A. Eala favoured at 1.40.
Independent estimates of who wins, each from a different method. The blend is what the bot prices against the market.
| Method | A. Eala | M. Sawangkaew |
|---|---|---|
| Elo ratings-based, surface-weighted |
36.4% | 63.6% |
| Machine learning 29-feature gradient-boosted model |
14.2% | 85.8% |
| Blend what the bot actually prices off |
25.3% | 74.7% |
| Market implied de-vigged from the opening odds |
66.3% | 33.7% |
We publish how well these score against the closing market, including where they lose: how accurate are tennis predictions?
| Player | Surface | Elo | Record | Matches |
|---|---|---|---|---|
| A. Eala | hard | 1905 | 174–90 | 264 |
| M. Sawangkaew | hard | 1718 | 145–79 | 224 |
Our own ratings, computed from match results since 2018. Players with fewer than 5 rated matches are omitted rather than shown at a provisional starting value. Last updated Aug. 3, 2026.
Level at 1–1 over 2 meetings. Full record.
| Date | Event | Surface | Winner | Score |
|---|---|---|---|---|
| June 5, 2026 | Birmingham | grass | A. Eala | 2 - 0 |
| Nov. 22, 2024 | ITF W100 Takasaki Women | hard | M. Sawangkaew | 2 - 1 |
| W | J. Pegula | 1 - 2 | Aug. 3, 2026 |
| W | N. Osaka | 0 - 2 | Aug. 1, 2026 |
| W | E. Svitolina | 2 - 0 | July 31, 2026 |
| W | L. Fernandez | 0 - 2 | July 29, 2026 |
| W | Q. Zheng | 2 - 1 | July 28, 2026 |
| L | R. Sramkova | 0 - 2 | Aug. 1, 2026 |
| L | T. Preston | 2 - 1 | July 31, 2026 |
| W | E. Jones | 0 - 2 | July 30, 2026 |
| W | N. Hibino | 1 - 2 | July 29, 2026 |
| W | E. S. Liang | 0 - 2 | July 28, 2026 |
All June 5, 2026 results & picks →
Math-only prediction: no LLM calls used