yes Milwaukee,yes Cleveland,yes Boston,yes Oklahoma City,yes Orlando,yes New York
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 13:51 UTC | View → |
| Kalshi | — | — | — | 12:04 UTC | View → |
| Kalshi | — | — | — | 09:34 UTC | View → |
| Kalshi | — | — | — | 16:01 UTC | View → |
| Kalshi | — | — | — | 21:43 UTC | View → |
| Kalshi | — | — | — | 08:35 UTC | View → |
| Kalshi | — | — | — | 15:15 UTC | View → |
| Kalshi | — | — | — | 04:30 UTC | View → |
| Kalshi | — | — | — | 09:34 UTC | View → |
| Kalshi | — | — | — | 07:31 UTC | View → |
| Kalshi | — | — | — | 21:43 UTC | View → |
| Kalshi | — | — | — | 10:12 UTC | View → |
| Kalshi | — | — | — | 12:35 UTC | View → |
| Kalshi | — | — | — | 17:32 UTC | View → |
| Kalshi | — | — | — | 20:25 UTC | View → |
| Kalshi | — | — | — | 11:41 UTC | View → |
| Kalshi | — | — | — | 04:30 UTC | View → |
| Kalshi | — | — | — | 11:53 UTC | View → |
| Kalshi | — | — | — | 17:48 UTC | View → |
| Kalshi | — | — | — | 04:23 UTC | View → |
| Kalshi | — | — | — | 10:11 UTC | View → |
| Kalshi | — | — | — | 16:14 UTC | View → |
| Kalshi | — | — | — | 16:14 UTC | View → |
| Kalshi | — | — | — | 04:46 UTC | View → |
| Kalshi | — | — | — | 07:31 UTC | View → |
| Kalshi | — | — | — | 10:10 UTC | View → |
| Kalshi | — | — | — | 13:55 UTC | View → |
| Kalshi | — | — | — | 07:20 UTC | View → |
| Kalshi | — | — | — | 13:00 UTC | View → |
| Kalshi | — | — | — | 10:06 UTC | View → |
| Kalshi | — | — | — | 11:42 UTC | View → |
| Kalshi | — | — | — | 10:59 UTC | View → |
| Kalshi | — | — | — | 21:49 UTC | View → |
| Kalshi | — | — | — | 09:17 UTC | View → |
| Kalshi | — | — | — | 14:23 UTC | View → |
| Kalshi | — | — | — | 21:46 UTC | View → |
| Kalshi | — | — | — | 13:14 UTC | View → |
| Kalshi | — | — | — | 18:46 UTC | View → |
| Kalshi | — | — | — | 07:43 UTC | View → |
| Kalshi | — | — | — | 08:39 UTC | View → |
| Kalshi | — | — | — | 09:24 UTC | View → |
| Kalshi | — | — | — | 19:15 UTC | View → |
| Kalshi | — | — | — | 08:42 UTC | View → |
| Kalshi | — | — | — | 13:39 UTC | View → |
| Kalshi | — | — | — | 05:57 UTC | View → |
| Kalshi | — | — | — | 08:39 UTC | View → |
| Kalshi | — | — | — | 19:45 UTC | View → |
| Kalshi | — | — | — | 10:06 UTC | View → |
| Kalshi | — | — | — | 04:38 UTC | View → |
| Kalshi | — | — | — | 10:21 UTC | View → |
| Kalshi | — | — | — | 16:51 UTC | View → |
| Kalshi | — | — | — | 18:03 UTC | View → |
| Kalshi | — | — | — | 09:24 UTC | View → |
| Kalshi | — | — | — | 08:17 UTC | View → |
| Kalshi | — | — | — | 14:19 UTC | View → |
| Kalshi | — | — | — | 14:16 UTC | View → |
| Kalshi | — | — | — | 12:18 UTC | View → |
| Kalshi | — | — | — | 10:06 UTC | View → |
| Kalshi | — | — | — | 09:24 UTC | View → |
| Kalshi | — | — | — | 07:53 UTC | View → |
| Kalshi | — | — | — | 20:05 UTC | View → |
| Kalshi | — | — | — | 15:01 UTC | View → |
| Kalshi | — | — | — | 11:56 UTC | View → |
| Kalshi | — | — | — | 10:59 UTC | View → |
| Kalshi | — | — | — | 12:18 UTC | View → |
| Kalshi | — | — | — | 12:49 UTC | View → |
| Kalshi | — | — | — | 09:41 UTC | View → |
| Kalshi | — | — | — | 14:56 UTC | View → |
| Kalshi | — | — | — | 13:14 UTC | View → |
| Kalshi | — | — | — | 14:32 UTC | View → |
| Kalshi | — | — | — | 07:25 UTC | View → |
| Kalshi | — | — | — | 12:01 UTC | View → |
| Kalshi | — | — | — | 08:57 UTC | View → |
| Kalshi | — | — | — | 15:18 UTC | View → |
| Kalshi | — | — | — | 12:04 UTC | View → |
| Kalshi | — | — | — | 23:15 UTC | View → |
| Kalshi | — | — | — | 08:23 UTC | View → |
| Kalshi | — | — | — | 12:21 UTC | View → |
| Kalshi | — | — | — | 00:07 UTC | View → |
| Kalshi | — | — | — | 21:58 UTC | View → |
| Kalshi | — | — | — | 08:57 UTC | View → |
| Kalshi | — | — | — | 21:35 UTC | View → |
| Kalshi | — | — | — | 05:08 UTC | View → |
| Kalshi | — | — | — | 10:23 UTC | View → |
| Kalshi | — | — | — | 19:46 UTC | View → |
| Kalshi | — | — | — | 19:55 UTC | View → |
What do these odds mean?
Cross-platform data for yes Milwaukee,yes Cleveland,yes Boston,yes Oklahoma City,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.