The US Open Women's Board: 8 AI Models Score All 23 Contenders
By Jake Hari
July 27, 2026
TL;DR
The panel's top of the board: Aryna Sabalenka (21%), Elena Rybakina (13%), Coco Gauff (11%). Every verdict below was made price-blind from live fetched data, and every one gets graded against the real settlement on our public scoreboard.
The women's board is everything the men's is not: wide open. World No. 1 Sabalenka leads at just 24 cents, with Gauff and Andreeva at 12 — the crowd is pricing real chaos, consistent with how varied recent women's majors have run. The panel got the live WTA rankings and had to decide whether the field really is this deep or whether the top seed is underpriced.
How The Panel Read It
The panel essentially ratifies the chaos pricing: Sabalenka's 21 blended sits right at her 24-cent price, and no seat pushes any contender past the mid-twenties. The interesting split is beneath the favorite — the models give Rybakina's ranking-card position more weight than the crowd does, and hold Gauff steady at her price. A board where the machines and the money agree the field is deep is itself a calibration statement worth grading.
Where The Machines Split From The Money
Linda Noskova: market 9¢, AI blend 4% (5 points below the crowd). GLM 5.2: "Noskova is a top-10 player on hard courts, but the field is exceptionally deep with multiple dominant champions, making her a longshot."
Mirra Andreeva: market 12¢, AI blend 7% (5 points below the crowd). GLM 5.2: "Ranked #5 and highly talented, but facing elite hard-court rivals like Sabalenka and Rybakina in a deep Grand Slam field."
Jessica Pegula: market 3¢, AI blend 8% (5 points above the crowd). Claude Sonnet: "Pegula is a strong #3-ranked hard-court player but faces Sabalenka, Rybakina, Gauff in a deep field."
The Board
| Outcome | Kalshi | AI blend | ChatGPT (GPT-5.5) | Claude Fable | Claude Opus | Claude Sonnet | Gemini 3.1 Pro | GLM 5.2 | Kimi K3 | DeepSeek V4 |
|---|---|---|---|---|---|---|---|---|---|---|
| Aryna Sabalenka | 24¢ | 21% | 16% | 22% | 21% | 23% | 20% | 23% | 22% | 23% |
| Elena Rybakina | 9¢ | 13% | 10% | 12% | 13% | 11% | 14% | 13% | 16% | 16% |
| Coco Gauff | 12¢ | 11% | 8% | 10% | 10% | 18% | 11% | 11% | 9% | 9% |
| Jessica Pegula | 3¢ | 8% | 8% | 7% | 6% | 10% | 8% | 6% | 7% | 8% |
| Iga Swiatek | 9¢ | 7% | 8% | 8% | 9% | 8% | 6% | 10% | 5% | 4% |
| Mirra Andreeva | 12¢ | 7% | 8% | 7% | 8% | 9% | 8% | 5% | 7% | 6% |
| Karolina Muchova | 3¢ | 5% | 6% | 5% | 4% | 6% | 5% | 4% | 4% | 5% |
| Amanda Anisimova | 5¢ | 4% | 4% | 5% | 5% | 5% | 2% | 4% | 4% | 2% |
| Naomi Osaka | 8¢ | 4% | 5% | 4% | 4% | 7% | 2% | 2% | 3% | 2% |
| Linda Noskova | 9¢ | 4% | 4% | 4% | 4% | 4% | 6% | 1.5% | 4% | 4% |
| Victoria Mboko | 2¢ | 3% | 3% | 4% | 4% | 4% | 2% | 2% | 3% | 2% |
| Elina Svitolina | 2¢ | 1.8% | 2% | 1.5% | 1.5% | 2% | 1.5% | 1.5% | 2% | 1.5% |
| Marta Kostyuk | 5¢ | 1.6% | 3% | 2% | 1.3% | 1.5% | 1.5% | 1.5% | 1.5% | 1.2% |
| Madison Keys | 4¢ | 1.6% | 1.2% | 2% | 2% | 2% | 0.5% | 2% | 0.8% | 1.5% |
| Jasmine Paolini | 1¢ | 1.6% | 1.3% | 1.2% | 1.2% | 2% | 2% | 2% | 1.5% | 1.2% |
| Iva Jovic | 3¢ | 1.5% | 1.8% | 1.2% | 1.5% | 2% | 1.5% | 1.5% | 1.0% | 1.5% |
| Qinwen Zheng | 2¢ | 1.4% | 1.8% | 1.5% | 1.2% | 2% | 1.2% | 2% | 0.5% | 0.5% |
| Barbora Krejcikova | 2¢ | 1.1% | 1.8% | 1.0% | 0.8% | 1.0% | 0.5% | 2% | 1.0% | 0.3% |
| Emma Navarro | 2¢ | 0.9% | 0.8% | 1.5% | 0.8% | 1.0% | 0.5% | 1.5% | 0.8% | 0.3% |
| Jelena Ostapenko | 1¢ | 0.9% | 0.7% | 0.5% | 0.8% | 2% | 0.3% | 1.5% | 0.6% | 0.5% |
| Paula Badosa | 1¢ | 0.7% | 0.6% | 0.5% | 0.5% | 1.0% | 0.8% | 0.8% | 0.7% | 0.3% |
| Maria Sakkari | 1¢ | 0.6% | 0.3% | 0.4% | 0.3% | 2% | 0.3% | 0.8% | 0.4% | 0.2% |
| Maja Chwalinska | 1¢ | 0.1% | 0.1% | 0.2% | 0.1% | 0.2% | 0.1% | 0.1% | 0.1% | 0.1% |
Model estimates generated July 27, 2026, price-blind from live fetched data. These are model estimates, not predictions of fact and not financial or trading advice. Models are frequently wrong; the market price reflects real traders' money. Kalshi is a CFTC-regulated exchange; 18+, availability varies by state.
FAQ
Why do the model percentages differ from the Kalshi price?
The models never see the price. When they disagree with the crowd, one side is wrong, and we grade every verdict against real settlements on our public scoreboard.
Are model verdicts betting advice?
No. Model verdicts are model estimates, not betting or financial advice. Treat them as one input among many and make your own decisions.