Cait Conley (D) leads at 64%. Moderate consensus — room for value on contrarian bets.
| # | Outcome | Probability | If Right | Volume |
|---|---|---|---|---|
| 1 | Cait Conley (D) | 64% | +57% | $18K |
| 2 | Mike Lawler (R) | 36% | +174% | $22K |
Real-money prediction market · Trade with confidence
This market will resolve according to the party of the candidate who wins the NY-17 congressional district seat in the U.S. House of Representatives in the 2026 midterm elections. The midterm election...
This prediction market tracks whether NY-17 House Election Winner will occur, with $40K in total trading volume reflecting significant trader interest. Prediction markets aggregate the collective intelligence of participants who stake real money on outcomes, making them one of the most reliable forecasting tools available for events driven by polling data, political developments, and historical voting patterns.
Traders lean toward Cait Conley (D) at 64%, suggesting a probable but not certain outcome. This moderate confidence level often reflects genuine uncertainty — markets at this range tend to see the most price movement as new information emerges.
Trading activity is exceptionally high, with $15K traded in the last 24 hours alone (37% of total volume). This surge often indicates breaking news, a key deadline approaching, or a significant shift in market sentiment.
This market is scheduled to resolve by 2026-11-04. As the resolution date approaches, expect increased trading activity and tighter probability estimates. Historical data shows that prediction market accuracy improves significantly in the final days before resolution.
As of Oct 01, 2026 at 13:05 UTC, the leading outcome is Cait Conley (D) at 64% probability, with $40K in total trading volume on Polymarket.
What Are Prediction Markets? · How to Trade · Odds Calculator · Compare Platforms