yes Arizona,yes Miami,yes New York M,yes New York Y,yes Baltimore,yes Los Angeles D
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 18:17 UTC | View → |
| Kalshi | — | — | — | 20:11 UTC | View → |
| Kalshi | — | — | — | 13:22 UTC | View → |
| Kalshi | — | — | — | 21:12 UTC | View → |
| Kalshi | — | — | — | 13:47 UTC | View → |
| Kalshi | — | — | — | 20:15 UTC | View → |
| Kalshi | — | — | — | 10:49 UTC | View → |
| Kalshi | — | — | — | 22:29 UTC | View → |
| Kalshi | — | — | — | 20:21 UTC | View → |
| Kalshi | — | — | — | 16:30 UTC | View → |
| Kalshi | — | — | — | 05:48 UTC | View → |
| Kalshi | — | — | — | 11:41 UTC | View → |
| Kalshi | — | — | — | 22:45 UTC | View → |
| Kalshi | — | — | — | 11:41 UTC | View → |
| Kalshi | — | — | — | 17:10 UTC | View → |
| Kalshi | — | — | — | 08:04 UTC | View → |
| Kalshi | — | — | — | 05:48 UTC | View → |
| Kalshi | — | — | — | 16:30 UTC | View → |
| Kalshi | — | — | — | 20:10 UTC | View → |
| Kalshi | — | — | — | 19:30 UTC | View → |
| Kalshi | — | — | — | 20:21 UTC | View → |
| Kalshi | — | — | — | 10:57 UTC | View → |
| Kalshi | — | — | — | 20:48 UTC | View → |
| Kalshi | — | — | — | 11:52 UTC | View → |
| Kalshi | — | — | — | 05:38 UTC | View → |
| Kalshi | — | — | — | 16:23 UTC | View → |
| Kalshi | — | — | — | 11:52 UTC | View → |
| Kalshi | — | — | — | 21:09 UTC | View → |
| Kalshi | — | — | — | 21:09 UTC | View → |
| Kalshi | — | — | — | 16:42 UTC | View → |
| Kalshi | — | — | — | 05:38 UTC | View → |
| Kalshi | — | — | — | 21:31 UTC | View → |
| Kalshi | — | — | — | 23:21 UTC | View → |
| Kalshi | — | — | — | 00:18 UTC | View → |
| Kalshi | — | — | — | 21:27 UTC | View → |
| Kalshi | — | — | — | 16:42 UTC | View → |
| Kalshi | — | — | — | 15:36 UTC | View → |
| Kalshi | — | — | — | 20:26 UTC | View → |
| Kalshi | — | — | — | 11:43 UTC | View → |
| Kalshi | — | — | — | 10:44 UTC | View → |
| Kalshi | — | — | — | 15:14 UTC | View → |
| Kalshi | — | — | — | 21:07 UTC | View → |
| Kalshi | — | — | — | 06:12 UTC | View → |
What do these odds mean?
Cross-platform data for yes Arizona,yes Miami,yes New York M,yes New York Y,yes Baltimore,yes Los Angeles D 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.