TL;DR
The panel's top of the board: Cam Schlittler (35%), Dylan Cease (28%), Sonny Gray (10%). Every verdict below was made price-blind from live fetched data, and every one gets graded against the real settlement on our scoreboard.
The crowd sees a two-horse race: Cam Schlittler at 52 cents, Dylan Cease at 45, and everyone else at 3 or less. The models got the real pitching leaderboards — ERA, strikeouts, wins, WHIP — and their job was to decide whether the market's near-total dismissal of the field is justified with two months left.
What The Models Were Given
Each model saw the live AL pitching leaderboards (ERA, strikeouts, wins, WHIP) fetched from MLB StatsAPI at generation time, with a coverage note that absence from the tables means not currently leading. Eight model seats were asked on every outcome; where a seat's verdict did not return, its table cell shows an em dash and the blend averages the seats that answered.
Where The Machines Split From The Money
Dylan Cease: market 45¢, AI blend 28% (17 points below the crowd). Gemini 3.1 Pro: "Despite leading in strikeouts and having a stellar ERA, Cease trails Schlittler in both ERA and wins, making him a strong secondary contender."
Cam Schlittler: market 52¢, AI blend 35% (17 points below the crowd). Claude Sonnet: "Leads ERA and near top in wins/Ks with two months left, but crowded field keeps this a strong-not-certain favorite."
Sonny Gray: market 2¢, AI blend 10% (8 points above the crowd). Claude Sonnet: "Gray leads AL wins with a strong ERA, but Cease and Schlittler have superior rate/strikeout numbers in a crowded field."
Drew Rasmussen: market 3¢, AI blend 1.4% (2 points below the crowd). DeepSeek V4: "He's far from the AL lead in ERA, wins, and strikeouts with two months left, making a Cy Young win highly unlikely."
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 |
|---|---|---|---|---|---|---|---|---|---|---|
| Cam Schlittler | 52¢ | 35% | 44% | 35% | 33% | 20% | 38% | 40% | 42% | 30% |
| Dylan Cease | 45¢ | 28% | 29% | 30% | 33% | 32% | 22% | 22% | 22% | 35% |
| Sonny Gray | 2¢ | 10% | 8% | 10% | 10% | 22% | 7% | 12% | 7% | 7% |
| Gavin Williams | 1¢ | 5% | 4% | 6% | 8% | 9% | 4% | 4% | 4% | 4% |
| Nathan Eovaldi | 1¢ | 4% | 2% | 5% | 4% | 6% | 2% | 6% | 2% | 2% |
| Tarik Skubal | 3¢ | 3% | 1.8% | 3% | 7% | 5% | 1.2% | 1.0% | 3% | 0.2% |
| Pablo Lopez | 3¢ | 3% | — | 0.5% | 1.5% | 1.0% | 0.5% | 0.5% | 0.4% | 15% |
| Joe Ryan | 1¢ | 3% | 2% | 2% | 5% | 2% | 2% | 3% | 1.5% | 2% |
| Parker Messick | 1¢ | 2% | 2% | 3% | 3% | 3% | 4% | 0.5% | 4% | 0.5% |
| Garrett Crochet | 1¢ | 1.8% | 0.4% | 2% | 5% | 4% | 0.5% | 0.5% | 2% | 0.1% |
| Shane McClanahan | 1¢ | 1.8% | 1.5% | 2% | 2% | 1.0% | 2% | 3% | 1.0% | 2% |
| Max Fried | 1¢ | 1.4% | 1.2% | 2% | 3% | 1.0% | 0.5% | 1.0% | 2% | 0.1% |
| Hunter Brown | 1¢ | 1.4% | 0.6% | 2% | 4% | 2% | 0.3% | 1.0% | 0.8% | 0.5% |
| Drew Rasmussen | 3¢ | 1.4% | 1.5% | 1.0% | 1.0% | 3% | 1.5% | 1.5% | 1.0% | 0.5% |
| Logan Gilbert | 2¢ | 1.4% | 0.6% | 2% | 2% | 2% | 0.5% | 2% | 0.5% | 1.2% |
| George Kirby | 1¢ | 1.1% | 0.4% | 1.0% | 2% | 2% | 1.0% | 1.5% | 0.8% | 0.5% |
| Tanner Bibee | 1¢ | 1.1% | 0.8% | 0.5% | 2% | 2% | 1.0% | 1.0% | 0.8% | 1.0% |
| Bryan Woo | 1¢ | 0.9% | 0.6% | 1.5% | 2% | 1.0% | 0.5% | 1.0% | 0.4% | 0.5% |
| Cole Ragans | 1¢ | 0.9% | 0.3% | 1.5% | 1.5% | 1.0% | 0.5% | 1.0% | 0.5% | 0.5% |
| Luis Castillo | 1¢ | 0.8% | 0.3% | 0.5% | 1.2% | 0.5% | 1.0% | 2% | 0.8% | 0.1% |
| Carlos Rodon | 1¢ | 0.8% | 0.4% | 1.0% | 0.8% | 2% | 0.5% | 1.0% | 0.5% | 0.1% |
| Jacob Degrom | 1¢ | 0.7% | 0.6% | 1.0% | 1.5% | 1.0% | 0.1% | 0.5% | 1.0% | 0.2% |
| Grayson Rodriguez | 1¢ | 0.7% | 0.3% | 0.5% | 1.2% | 1.0% | 1.5% | 0.5% | 0.2% | 0.1% |
| Kris Bubic | 1¢ | 0.7% | 0.6% | 0.5% | 2% | 1.0% | 0.1% | 0.4% | 0.2% | 0.5% |
| MacKenzie Gore | 1¢ | 0.6% | 0.3% | 0.3% | 0.5% | 2% | 0.1% | 1.0% | 0.4% | 0.5% |
| …plus 17 more names, all under 2% blended — every name was scored; the table shows the top of the field |
Model estimates generated July 26, 2026, price-blind. 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.
Related Verdicts
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 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.
What data did the models see?
Each model saw the live AL pitching leaderboards (ERA, strikeouts, wins, WHIP) fetched from MLB StatsAPI at generation time, with a coverage note that absence from the tables means not currently leading.
