yes Philadelphia,yes Atlanta,yes Golden State,yes Utah,yes Miami,yes Houston,yes Boston,yes Orlando,yes New York
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 05:16 UTC | View → |
| Kalshi | — | — | — | 12:18 UTC | View → |
| Kalshi | — | — | — | 14:25 UTC | View → |
| Kalshi | — | — | — | 13:46 UTC | View → |
| Kalshi | — | — | — | 16:30 UTC | View → |
| Kalshi | — | — | — | 22:24 UTC | View → |
| Kalshi | — | — | — | 09:34 UTC | View → |
| Kalshi | — | — | — | 13:56 UTC | View → |
| Kalshi | — | — | — | 16:17 UTC | View → |
| Kalshi | — | — | — | 12:36 UTC | View → |
| Kalshi | — | — | — | 11:03 UTC | View → |
| Kalshi | — | — | — | 16:17 UTC | View → |
| Kalshi | — | — | — | 06:57 UTC | View → |
| Kalshi | — | — | — | 13:48 UTC | View → |
| Kalshi | — | — | — | 04:49 UTC | View → |
| Kalshi | — | — | — | 05:10 UTC | View → |
| Kalshi | — | — | — | 04:32 UTC | View → |
| Kalshi | — | — | — | 08:19 UTC | View → |
| Kalshi | — | — | — | 09:34 UTC | View → |
| Kalshi | — | — | — | 20:25 UTC | View → |
| Kalshi | — | — | — | 06:40 UTC | View → |
| Kalshi | — | — | — | 08:57 UTC | View → |
| Kalshi | — | — | — | 11:37 UTC | View → |
| Kalshi | — | — | — | 14:22 UTC | View → |
| Kalshi | — | — | — | 17:43 UTC | View → |
| Kalshi | — | — | — | 22:43 UTC | View → |
| Kalshi | — | — | — | 08:20 UTC | View → |
| Kalshi | — | — | — | 08:11 UTC | View → |
| Kalshi | — | — | — | 15:45 UTC | View → |
| Kalshi | — | — | — | 12:52 UTC | View → |
| Kalshi | — | — | — | 05:10 UTC | View → |
| Kalshi | — | — | — | 22:00 UTC | View → |
| Kalshi | — | — | — | 21:23 UTC | View → |
| Kalshi | — | — | — | 06:07 UTC | View → |
| Kalshi | — | — | — | 23:07 UTC | View → |
| Kalshi | — | — | — | 23:02 UTC | View → |
| Kalshi | — | — | — | 14:59 UTC | View → |
| Kalshi | — | — | — | 12:33 UTC | View → |
| Kalshi | — | — | — | 21:28 UTC | View → |
| Kalshi | — | — | — | 13:51 UTC | View → |
| Kalshi | — | — | — | 14:49 UTC | View → |
| Kalshi | — | — | — | 16:04 UTC | View → |
| Kalshi | — | — | — | 21:18 UTC | View → |
| Kalshi | — | — | — | 05:31 UTC | View → |
| Kalshi | — | — | — | 23:07 UTC | View → |
| Kalshi | — | — | — | 05:10 UTC | View → |
| Kalshi | — | — | — | 05:39 UTC | View → |
| Kalshi | — | — | — | 07:13 UTC | View → |
| Kalshi | — | — | — | 05:49 UTC | View → |
| Kalshi | — | — | — | 06:04 UTC | View → |
| Kalshi | — | — | — | 18:20 UTC | View → |
| Kalshi | — | — | — | 21:26 UTC | View → |
| Kalshi | — | — | — | 13:10 UTC | View → |
| Kalshi | — | — | — | 05:10 UTC | View → |
| Kalshi | — | — | — | 11:58 UTC | View → |
| Kalshi | — | — | — | 23:05 UTC | View → |
| Kalshi | — | — | — | 06:09 UTC | View → |
| Kalshi | — | — | — | 21:22 UTC | View → |
| Kalshi | — | — | — | 23:56 UTC | View → |
| Kalshi | — | — | — | 06:38 UTC | View → |
| Kalshi | — | — | — | 04:31 UTC | View → |
| Kalshi | — | — | — | 20:56 UTC | View → |
| Kalshi | — | — | — | 17:05 UTC | View → |
| Kalshi | — | — | — | 06:18 UTC | View → |
| Kalshi | — | — | — | 05:47 UTC | View → |
| Kalshi | — | — | — | 05:39 UTC | View → |
| Kalshi | — | — | — | 22:31 UTC | View → |
| Kalshi | — | — | — | 21:15 UTC | View → |
What do these odds mean?
Cross-platform data for yes Philadelphia,yes Atlanta,yes Golden State,yes Utah,yes Miami,yes Houston,yes Boston,yes Orlando,yes New York 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.