yes Dallas,yes Detroit,yes New Orleans
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 08:25 UTC | View → |
| Kalshi | — | — | — | 09:06 UTC | View → |
| Kalshi | — | — | — | 04:28 UTC | View → |
| Kalshi | — | — | — | 07:32 UTC | View → |
| Kalshi | — | — | — | 08:34 UTC | View → |
| Kalshi | — | — | — | 08:26 UTC | View → |
| Kalshi | — | — | — | 07:51 UTC | View → |
| Kalshi | — | — | — | 07:53 UTC | View → |
| Kalshi | — | — | — | 10:43 UTC | View → |
| Kalshi | — | — | — | 09:06 UTC | View → |
| Kalshi | — | — | — | 09:36 UTC | View → |
| Kalshi | — | — | — | 16:09 UTC | View → |
| Kalshi | — | — | — | 07:25 UTC | View → |
| Kalshi | — | — | — | 08:00 UTC | View → |
| Kalshi | — | — | — | 09:07 UTC | View → |
| Kalshi | — | — | — | 07:51 UTC | View → |
| Kalshi | — | — | — | 06:26 UTC | View → |
| Kalshi | — | — | — | 09:06 UTC | View → |
| Kalshi | — | — | — | 09:05 UTC | View → |
| Kalshi | — | — | — | 08:35 UTC | View → |
| Kalshi | — | — | — | 09:07 UTC | View → |
| Kalshi | — | — | — | 16:08 UTC | View → |
| Kalshi | — | — | — | 09:06 UTC | View → |
| Kalshi | — | — | — | 09:06 UTC | View → |
| Kalshi | — | — | — | 08:53 UTC | View → |
| Kalshi | — | — | — | 09:06 UTC | View → |
| Kalshi | — | — | — | 23:47 UTC | View → |
| Kalshi | — | — | — | 07:24 UTC | View → |
| Kalshi | — | — | — | 15:59 UTC | View → |
| Kalshi | — | — | — | 10:55 UTC | View → |
| Kalshi | — | — | — | 01:04 UTC | View → |
| Kalshi | — | — | — | 08:46 UTC | View → |
| Kalshi | — | — | — | 07:28 UTC | View → |
| Kalshi | — | — | — | 23:43 UTC | View → |
| Kalshi | — | — | — | 14:51 UTC | View → |
| Kalshi | — | — | — | 22:43 UTC | View → |
| Kalshi | — | — | — | 13:43 UTC | View → |
| Kalshi | — | — | — | 01:02 UTC | View → |
| Kalshi | — | — | — | 19:20 UTC | View → |
| Kalshi | — | — | — | 21:26 UTC | View → |
| Kalshi | — | — | — | 09:11 UTC | View → |
| Kalshi | — | — | — | 07:27 UTC | View → |
| Kalshi | — | — | — | 13:53 UTC | View → |
| Kalshi | — | — | — | 04:31 UTC | View → |
| Kalshi | — | — | — | 09:24 UTC | View → |
| Kalshi | — | — | — | 07:22 UTC | View → |
| Kalshi | — | — | — | 07:24 UTC | View → |
| Kalshi | — | — | — | 07:27 UTC | View → |
| Kalshi | — | — | — | 19:27 UTC | View → |
| Kalshi | — | — | — | 01:04 UTC | View → |
| Kalshi | — | — | — | 14:16 UTC | View → |
| Kalshi | — | — | — | 21:04 UTC | View → |
| Kalshi | — | — | — | 04:40 UTC | View → |
| Kalshi | — | — | — | 14:51 UTC | View → |
What do these odds mean?
Cross-platform data for yes Dallas,yes Detroit,yes New Orleans is still being collected.
How to read cross-platform spreads
When two platforms price the same event meaningfully differently, it usually means one of three things: liquidity is thin on one side, fee structures are pushing a spread, or traders on one platform have information the other lacks. Spreads larger than 5 percentage points on events with over $50K in volume often resolve toward the higher-volume platform's price.
About this data
Beeks.ai aggregates prediction market data from Polymarket, Kalshi, and Manifold. Updates run every minute. Consensus probability is a volume-weighted average across all matched markets. Historical snapshots are stored for calibration analysis.
News & context
Your edge calculator
Enter your own probability estimate to see expected value and recommended position size using the Kelly Criterion.