yes Chicago C,yes Milwaukee,yes Atlanta,yes San Antonio,yes Golden State,yes Miami,yes Houston,yes Boston,yes Denver,yes Orlando,yes Philadelphia,yes New York
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 18:59 UTC | View → |
| Kalshi | — | — | — | 07:44 UTC | View → |
| Kalshi | — | — | — | 16:49 UTC | View → |
| Kalshi | — | — | — | 07:17 UTC | View → |
| Kalshi | — | — | — | 18:22 UTC | View → |
| Kalshi | — | — | — | 19:53 UTC | View → |
| Kalshi | — | — | — | 16:26 UTC | View → |
| Kalshi | — | — | — | 18:14 UTC | View → |
| Kalshi | — | — | — | 13:38 UTC | View → |
| Kalshi | — | — | — | 12:30 UTC | View → |
| Kalshi | — | — | — | 18:27 UTC | View → |
| Kalshi | — | — | — | 21:01 UTC | View → |
| Kalshi | — | — | — | 19:09 UTC | View → |
| Kalshi | — | — | — | 18:48 UTC | View → |
| Kalshi | — | — | — | 16:41 UTC | View → |
| Kalshi | — | — | — | 10:08 UTC | View → |
| Kalshi | — | — | — | 19:52 UTC | View → |
| Kalshi | — | — | — | 13:39 UTC | View → |
| Kalshi | — | — | — | 17:10 UTC | View → |
| Kalshi | — | — | — | 19:30 UTC | View → |
| Kalshi | — | — | — | 18:28 UTC | View → |
| Kalshi | — | — | — | 18:27 UTC | View → |
| Kalshi | — | — | — | 20:03 UTC | View → |
| Kalshi | — | — | — | 18:36 UTC | View → |
| Kalshi | — | — | — | 19:56 UTC | View → |
| Kalshi | — | — | — | 14:59 UTC | View → |
| Kalshi | — | — | — | 20:03 UTC | View → |
| Kalshi | — | — | — | 16:37 UTC | View → |
| Kalshi | — | — | — | 12:52 UTC | View → |
| Kalshi | — | — | — | 15:25 UTC | View → |
| Kalshi | — | — | — | 13:12 UTC | View → |
| Kalshi | — | — | — | 16:42 UTC | View → |
| Kalshi | — | — | — | 10:34 UTC | View → |
| Kalshi | — | — | — | 12:29 UTC | View → |
| Kalshi | — | — | — | 16:59 UTC | View → |
| Kalshi | — | — | — | 13:09 UTC | View → |
| Kalshi | — | — | — | 17:13 UTC | View → |
| Kalshi | — | — | — | 12:44 UTC | View → |
| Kalshi | — | — | — | 19:01 UTC | View → |
| Kalshi | — | — | — | 14:52 UTC | View → |
| Kalshi | — | — | — | 14:58 UTC | View → |
| Kalshi | — | — | — | 12:54 UTC | View → |
| Kalshi | — | — | — | 19:01 UTC | View → |
| Kalshi | — | — | — | 15:53 UTC | View → |
| Kalshi | — | — | — | 11:37 UTC | View → |
| Kalshi | — | — | — | 17:28 UTC | View → |
| Kalshi | — | — | — | 15:53 UTC | View → |
| Kalshi | — | — | — | 09:28 UTC | View → |
| Kalshi | — | — | — | 18:38 UTC | View → |
| Kalshi | — | — | — | 18:05 UTC | View → |
| Kalshi | — | — | — | 16:37 UTC | View → |
| Kalshi | — | — | — | 19:13 UTC | View → |
| Kalshi | — | — | — | 18:56 UTC | View → |
| Kalshi | — | — | — | 18:16 UTC | View → |
| Kalshi | — | — | — | 13:12 UTC | View → |
| Kalshi | — | — | — | 12:52 UTC | View → |
| Kalshi | — | — | — | 20:22 UTC | View → |
| Kalshi | — | — | — | 13:17 UTC | View → |
| Kalshi | — | — | — | 19:48 UTC | View → |
| Kalshi | — | — | — | 18:56 UTC | View → |
| Kalshi | — | — | — | 19:13 UTC | View → |
| Kalshi | — | — | — | 12:50 UTC | View → |
| Kalshi | — | — | — | 13:28 UTC | View → |
| Kalshi | — | — | — | 19:13 UTC | View → |
| Kalshi | — | — | — | 16:30 UTC | View → |
| Kalshi | — | — | — | 19:13 UTC | View → |
| Kalshi | — | — | — | 19:13 UTC | View → |
| Kalshi | — | — | — | 13:00 UTC | View → |
| Kalshi | — | — | — | 13:33 UTC | View → |
| Kalshi | — | — | — | 13:41 UTC | View → |
| Kalshi | — | — | — | 11:51 UTC | View → |
| Kalshi | — | — | — | 14:52 UTC | View → |
| Kalshi | — | — | — | 11:48 UTC | View → |
| Kalshi | — | — | — | 14:58 UTC | View → |
| Kalshi | — | — | — | 12:45 UTC | View → |
| Kalshi | — | — | — | 19:35 UTC | View → |
| Kalshi | — | — | — | 19:53 UTC | View → |
| Kalshi | — | — | — | 20:14 UTC | View → |
What do these odds mean?
Cross-platform data for yes Chicago C,yes Milwaukee,yes Atlanta,yes San Antonio,yes Golden State,yes Miami,yes Houston,yes Boston,yes Denver,yes Orlando,yes Philadelphia,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.