A 97-Cent Rookie Race: 8 AI Models Check The WNBA ROY Board
By Jake Hari
July 27, 2026
TL;DR
The panel's top of the board: Lauren Betts (29%), Olivia Miles (18%), Ta'Niya Latson (13%). 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 crowd calls this race over: Olivia Miles at 97 cents. This board is also an honesty test for our protocol — no clean rookie-stat ledger was available to fetch, so the models were told exactly that and instructed not to invent numbers. Where the panel landed Betts-first against the crowd's near-certainty on Miles, it did so on draft-pedigree reasoning alone, and the disclosure below tells you exactly how much weight to put on it.
How The Panel Read It
Read the gap honestly: the crowd's 97 cents on Miles almost certainly encodes the actual season — a live rookie campaign the models could not see, because no clean rookie-stat ledger was available to fetch and the protocol forbids inventing one. The panel's Betts-first read is draft-pedigree reasoning, disclosed as such. We publish it anyway because the scoreboard grades honesty: if the crowd's information beats the panel's priors here, that gets recorded, and it is exactly the kind of data-gap lesson that improves the next card.
Where The Machines Split From The Money
Olivia Miles: market 97¢, AI blend 18% (79 points below the crowd). ChatGPT (GPT-5.5): "With no rookie-stat ledger, Miles gets a meaningful prior from elite prospect status, but ROTY is a large field and performance evidence is missing."
Gabriela Jaquez: market 49¢, AI blend 3% (46 points below the crowd). Claude Sonnet: "Jaquez is a fringe/bench rookie, not a top ROY contender in a competitive field." [Editor's note: per current reporting Jaquez has started the majority of her games; this premise reflects the missing rookie ledger, not her actual season. The verdict stands as published and will be graded as such.]
Flau'jae Johnson: market 3¢, AI blend 12% (9 points above the crowd). Gemini 3.1 Pro: "As a high-profile 2026 lottery pick with excellent scoring ability, Johnson is a solid contender in a competitive rookie class." [Editor's note: Johnson was the No. 8 pick; the 2026 lottery covered picks 1-5. The verdict stands as published and will be graded as such.]
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 |
|---|---|---|---|---|---|---|---|---|---|---|
| Lauren Betts | 1¢ | 29% | 16% | 35% | 35% | 55% | 15% | 30% | 20% | 25% |
| Olivia Miles | 97¢ | 18% | 12% | 14% | 24% | 25% | 12% | 15% | 25% | 20% |
| Ta'Niya Latson | 7¢ | 13% | 12% | 12% | 25% | 20% | 5% | 12% | 9% | 10% |
| Flau'jae Johnson | 3¢ | 12% | 8% | 20% | 12% | 4% | 25% | 18% | 5% | 5% |
| Azzi Fudd | 3¢ | 12% | 7% | 15% | 10% | 5% | 6% | 15% | 20% | 18% |
| Cotie McMahon | 1¢ | 7% | 6% | 4% | 5% | 2% | 5% | 18% | 2% | 15% |
| Kiki Rice | 7¢ | 7% | 7% | 5% | 5% | 5% | 12% | 9% | 5% | 8% |
| Georgia Amoore | 1¢ | 7% | 8% | 7% | 10% | 10% | 0.5% | 12% | 4% | 3% |
| Madina Okot | 1¢ | 6% | 1.2% | 3% | 8% | 3% | 0.5% | 2% | 4% | 25% |
| Raven Johnson | 1¢ | 5% | 1.5% | 3% | 4% | 3% | 2% | 18% | 1.0% | 5% |
| Gianna Kneepkens | 7¢ | 4% | 2% | 5% | 8% | 8% | 1.2% | 4% | 3% | 4% |
| Awa Fam | 2¢ | 4% | 2% | 4% | 4% | 3% | 1.5% | 2% | 12% | 1.0% |
| Janiah Barker | 2¢ | 4% | 2% | 2% | 2% | 3% | 2% | 4% | 1.5% | 12% |
| Gabriela Jaquez | 49¢ | 3% | 2% | 2% | 3% | 1.0% | 2% | 5% | 2% | 5% |
| Isobel Borlase | — | 3% | 1.5% | 2% | 3% | 3% | 1.0% | 5% | 2% | 5% |
| Nell Angloma | 11¢ | 1.9% | 2% | 2% | 2% | 3% | 0.1% | 2% | 3% | 0.5% |
| Pauline Astier | 5¢ | 1.6% | 1.5% | 3% | 2% | 2% | 0.5% | 3% | 0.6% | 0.5% |
| Jovana Nogic | 1¢ | 1.6% | 1.5% | 2% | 2% | 3% | 0.5% | 3% | 0.5% | 0.5% |
| Angela Dugalic | — | 1.5% | 1.5% | 2% | 2% | 3% | 0.1% | 3% | 0.5% | 0.1% |
| Tie/Co-Winners | 5¢ | 0.8% | 1.2% | 0.5% | 1.0% | 1.0% | 0.5% | 1.0% | 0.8% | 0.5% |
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.