yes Arizona,yes Miami,yes Los Angeles A,yes Chicago WS
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 20:38 UTC | View → |
| Kalshi | — | — | — | 22:07 UTC | View → |
| Kalshi | — | — | — | 20:37 UTC | View → |
| Kalshi | — | — | — | 21:32 UTC | View → |
| Kalshi | — | — | — | 21:11 UTC | View → |
| Kalshi | — | — | — | 05:40 UTC | View → |
| Kalshi | — | — | — | 05:57 UTC | View → |
| Kalshi | — | — | — | 13:36 UTC | View → |
| Kalshi | — | — | — | 10:10 UTC | View → |
| Kalshi | — | — | — | 05:53 UTC | View → |
| Kalshi | — | — | — | 05:53 UTC | View → |
| Kalshi | — | — | — | 10:57 UTC | View → |
| Kalshi | — | — | — | 07:32 UTC | View → |
| Kalshi | — | — | — | 21:24 UTC | View → |
| Kalshi | — | — | — | 07:32 UTC | View → |
| Kalshi | — | — | — | 19:02 UTC | View → |
| Kalshi | — | — | — | 00:09 UTC | View → |
| Kalshi | — | — | — | 21:11 UTC | View → |
| Kalshi | — | — | — | 11:59 UTC | View → |
| Kalshi | — | — | — | 15:57 UTC | View → |
| Kalshi | — | — | — | 21:32 UTC | View → |
| Kalshi | — | — | — | 17:28 UTC | View → |
| Kalshi | — | — | — | 09:03 UTC | View → |
| Kalshi | — | — | — | 10:10 UTC | View → |
| Kalshi | — | — | — | 15:41 UTC | View → |
| Kalshi | — | — | — | 19:38 UTC | View → |
| Kalshi | — | — | — | 22:32 UTC | View → |
| Kalshi | — | — | — | 21:32 UTC | View → |
| Kalshi | — | — | — | 10:10 UTC | View → |
| Kalshi | — | — | — | 10:11 UTC | View → |
| Kalshi | — | — | — | 17:28 UTC | View → |
| Kalshi | — | — | — | 07:32 UTC | View → |
| Kalshi | — | — | — | 08:25 UTC | View → |
| Kalshi | — | — | — | 05:40 UTC | View → |
| Kalshi | — | — | — | 06:51 UTC | View → |
| Kalshi | — | — | — | 21:22 UTC | View → |
| Kalshi | — | — | — | 13:33 UTC | View → |
| Kalshi | — | — | — | 22:14 UTC | View → |
| Kalshi | — | — | — | 14:07 UTC | View → |
| Kalshi | — | — | — | 20:06 UTC | View → |
| Kalshi | — | — | — | 14:52 UTC | View → |
| Kalshi | — | — | — | 21:28 UTC | View → |
| Kalshi | — | — | — | 06:18 UTC | View → |
| Kalshi | — | — | — | 05:15 UTC | View → |
| Kalshi | — | — | — | 19:11 UTC | View → |
| Kalshi | — | — | — | 15:35 UTC | View → |
| Kalshi | — | — | — | 14:09 UTC | View → |
| Kalshi | — | — | — | 05:55 UTC | View → |
| Kalshi | — | — | — | 13:09 UTC | View → |
| Kalshi | — | — | — | 21:22 UTC | View → |
| Kalshi | — | — | — | 21:28 UTC | View → |
| Kalshi | — | — | — | 19:17 UTC | View → |
| Kalshi | — | — | — | 06:18 UTC | View → |
| Kalshi | — | — | — | 14:24 UTC | View → |
| Kalshi | — | — | — | 19:50 UTC | View → |
| Kalshi | — | — | — | 00:07 UTC | View → |
| Kalshi | — | — | — | 00:07 UTC | View → |
| Kalshi | — | — | — | 00:07 UTC | View → |
| Kalshi | — | — | — | 20:06 UTC | View → |
| Kalshi | — | — | — | 05:02 UTC | View → |
| Kalshi | — | — | — | 05:12 UTC | View → |
| Kalshi | — | — | — | 21:13 UTC | View → |
| Kalshi | — | — | — | 21:27 UTC | View → |
| Kalshi | — | — | — | 14:52 UTC | View → |
| Kalshi | — | — | — | 21:23 UTC | View → |
| Kalshi | — | — | — | 16:18 UTC | View → |
| Kalshi | — | — | — | 21:23 UTC | View → |
| Kalshi | — | — | — | 21:23 UTC | View → |
| Kalshi | — | — | — | 16:31 UTC | View → |
| Kalshi | — | — | — | 20:06 UTC | View → |
| Kalshi | — | — | — | 12:53 UTC | View → |
| Kalshi | — | — | — | 20:06 UTC | View → |
| Kalshi | — | — | — | 13:09 UTC | View → |
| Kalshi | — | — | — | 08:42 UTC | View → |
| Kalshi | — | — | — | 20:06 UTC | View → |
| Kalshi | — | — | — | 22:19 UTC | View → |
| Kalshi | — | — | — | 11:42 UTC | View → |
What do these odds mean?
Cross-platform data for yes Arizona,yes Miami,yes Los Angeles A,yes Chicago WS 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.