yes Pittsburgh,yes Arizona,yes Los Angeles A,yes Chicago WS
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 15:47 UTC | View → |
| Kalshi | — | — | — | 14:30 UTC | View → |
| Kalshi | — | — | — | 06:37 UTC | View → |
| Kalshi | — | — | — | 07:01 UTC | View → |
| Kalshi | — | — | — | 15:47 UTC | View → |
| Kalshi | — | — | — | 16:22 UTC | View → |
| Kalshi | — | — | — | 12:14 UTC | View → |
| Kalshi | — | — | — | 16:40 UTC | View → |
| Kalshi | — | — | — | 13:44 UTC | View → |
| Kalshi | — | — | — | 05:52 UTC | View → |
| Kalshi | — | — | — | 15:43 UTC | View → |
| Kalshi | — | — | — | 13:51 UTC | View → |
| Kalshi | — | — | — | 16:43 UTC | View → |
| Kalshi | — | — | — | 15:21 UTC | View → |
| Kalshi | — | — | — | 15:43 UTC | View → |
| Kalshi | — | — | — | 05:52 UTC | View → |
| Kalshi | — | — | — | 14:56 UTC | View → |
| Kalshi | — | — | — | 18:59 UTC | View → |
| Kalshi | — | — | — | 20:31 UTC | View → |
| Kalshi | — | — | — | 14:25 UTC | View → |
| Kalshi | — | — | — | 17:12 UTC | View → |
| Kalshi | — | — | — | 12:14 UTC | View → |
| Kalshi | — | — | — | 06:48 UTC | View → |
| Kalshi | — | — | — | 10:50 UTC | View → |
| Kalshi | — | — | — | 09:30 UTC | View → |
| Kalshi | — | — | — | 09:30 UTC | View → |
| Kalshi | — | — | — | 10:53 UTC | View → |
| Kalshi | — | — | — | 20:16 UTC | View → |
| Kalshi | — | — | — | 09:55 UTC | View → |
| Kalshi | — | — | — | 10:53 UTC | View → |
| Kalshi | — | — | — | 06:09 UTC | View → |
| Kalshi | — | — | — | 09:30 UTC | View → |
| Kalshi | — | — | — | 10:53 UTC | View → |
| Kalshi | — | — | — | 09:30 UTC | View → |
| Kalshi | — | — | — | 12:53 UTC | View → |
| Kalshi | — | — | — | 10:00 UTC | View → |
| Kalshi | — | — | — | 10:55 UTC | View → |
| Kalshi | — | — | — | 06:48 UTC | View → |
| Kalshi | — | — | — | 10:54 UTC | View → |
| Kalshi | — | — | — | 11:54 UTC | View → |
| Kalshi | — | — | — | 10:55 UTC | View → |
| Kalshi | — | — | — | 10:54 UTC | View → |
| Kalshi | — | — | — | 09:31 UTC | View → |
| Kalshi | — | — | — | 12:50 UTC | View → |
| Kalshi | — | — | — | 17:52 UTC | View → |
| Kalshi | — | — | — | 09:29 UTC | View → |
| Kalshi | — | — | — | 21:13 UTC | View → |
| Kalshi | — | — | — | 09:28 UTC | View → |
| Kalshi | — | — | — | 09:31 UTC | View → |
| Kalshi | — | — | — | 18:48 UTC | View → |
| Kalshi | — | — | — | 07:50 UTC | View → |
| Kalshi | — | — | — | 10:54 UTC | View → |
| Kalshi | — | — | — | 15:44 UTC | View → |
| Kalshi | — | — | — | 15:23 UTC | View → |
| Kalshi | — | — | — | 15:32 UTC | View → |
| Kalshi | — | — | — | 12:09 UTC | View → |
| Kalshi | — | — | — | 19:13 UTC | View → |
| Kalshi | — | — | — | 06:56 UTC | View → |
| Kalshi | — | — | — | 10:54 UTC | View → |
| Kalshi | — | — | — | 16:14 UTC | View → |
| Kalshi | — | — | — | 08:07 UTC | View → |
| Kalshi | — | — | — | 07:50 UTC | View → |
| Kalshi | — | — | — | 10:53 UTC | View → |
| Kalshi | — | — | — | 09:30 UTC | View → |
| Kalshi | — | — | — | 18:15 UTC | View → |
| Kalshi | — | — | — | 17:56 UTC | View → |
| Kalshi | — | — | — | 20:15 UTC | View → |
| Kalshi | — | — | — | 10:54 UTC | View → |
| Kalshi | — | — | — | 06:13 UTC | View → |
| Kalshi | — | — | — | 09:31 UTC | View → |
What do these odds mean?
Cross-platform data for yes Pittsburgh,yes Arizona,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.