yes Los Angeles A,yes New York Y,yes Seattle,yes Texas
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 12:19 UTC | View → |
| Kalshi | — | — | — | 23:48 UTC | View → |
| Kalshi | — | — | — | 04:29 UTC | View → |
| Kalshi | — | — | — | 16:58 UTC | View → |
| Kalshi | — | — | — | 12:19 UTC | View → |
| Kalshi | — | — | — | 22:21 UTC | View → |
| Kalshi | — | — | — | 09:01 UTC | View → |
| Kalshi | — | — | — | 20:57 UTC | View → |
| Kalshi | — | — | — | 23:22 UTC | View → |
| Kalshi | — | — | — | 22:05 UTC | View → |
| Kalshi | — | — | — | 23:42 UTC | View → |
| Kalshi | — | — | — | 16:58 UTC | View → |
| Kalshi | — | — | — | 21:56 UTC | View → |
| Kalshi | — | — | — | 23:47 UTC | View → |
| Kalshi | — | — | — | 16:33 UTC | View → |
| Kalshi | — | — | — | 12:19 UTC | View → |
| Kalshi | — | — | — | 08:25 UTC | View → |
| Kalshi | — | — | — | 22:02 UTC | View → |
| Kalshi | — | — | — | 23:10 UTC | View → |
| Kalshi | — | — | — | 23:39 UTC | View → |
| Kalshi | — | — | — | 00:44 UTC | View → |
| Kalshi | — | — | — | 22:05 UTC | View → |
| Kalshi | — | — | — | 09:01 UTC | View → |
| Kalshi | — | — | — | 23:17 UTC | View → |
| Kalshi | — | — | — | 16:33 UTC | View → |
| Kalshi | — | — | — | 07:45 UTC | View → |
| Kalshi | — | — | — | 22:21 UTC | View → |
| Kalshi | — | — | — | 09:13 UTC | View → |
| Kalshi | — | — | — | 23:28 UTC | View → |
| Kalshi | — | — | — | 16:58 UTC | View → |
| Kalshi | — | — | — | 23:47 UTC | View → |
| Kalshi | — | — | — | 12:20 UTC | View → |
| Kalshi | — | — | — | 12:19 UTC | View → |
| Kalshi | — | — | — | 08:44 UTC | View → |
| Kalshi | — | — | — | 23:17 UTC | View → |
| Kalshi | — | — | — | 12:20 UTC | View → |
| Kalshi | — | — | — | 13:54 UTC | View → |
| Kalshi | — | — | — | 07:45 UTC | View → |
| Kalshi | — | — | — | 07:56 UTC | View → |
| Kalshi | — | — | — | 17:48 UTC | View → |
| Kalshi | — | — | — | 23:24 UTC | View → |
| Kalshi | — | — | — | 08:58 UTC | View → |
| Kalshi | — | — | — | 07:56 UTC | View → |
| Kalshi | — | — | — | 11:58 UTC | View → |
| Kalshi | — | — | — | 00:42 UTC | View → |
| Kalshi | — | — | — | 23:15 UTC | View → |
| Kalshi | — | — | — | 21:46 UTC | View → |
| Kalshi | — | — | — | 04:37 UTC | View → |
| Kalshi | — | — | — | 08:55 UTC | View → |
| Kalshi | — | — | — | 23:48 UTC | View → |
| Kalshi | — | — | — | 23:11 UTC | View → |
| Kalshi | — | — | — | 21:46 UTC | View → |
| Kalshi | — | — | — | 22:01 UTC | View → |
| Kalshi | — | — | — | 17:46 UTC | View → |
| Kalshi | — | — | — | 23:52 UTC | View → |
| Kalshi | — | — | — | 20:17 UTC | View → |
| Kalshi | — | — | — | 23:11 UTC | View → |
| Kalshi | — | — | — | 12:54 UTC | View → |
| Kalshi | — | — | — | 23:41 UTC | View → |
| Kalshi | — | — | — | 08:53 UTC | View → |
| Kalshi | — | — | — | 23:44 UTC | View → |
| Kalshi | — | — | — | 16:08 UTC | View → |
| Kalshi | — | — | — | 23:47 UTC | View → |
| Kalshi | — | — | — | 23:57 UTC | View → |
| Kalshi | — | — | — | 23:24 UTC | View → |
| Kalshi | — | — | — | 23:37 UTC | View → |
| Kalshi | — | — | — | 21:06 UTC | View → |
| Kalshi | — | — | — | 23:48 UTC | View → |
| Kalshi | — | — | — | 23:28 UTC | View → |
| Kalshi | — | — | — | 05:43 UTC | View → |
| Kalshi | — | — | — | 23:13 UTC | View → |
| Kalshi | — | — | — | 07:55 UTC | View → |
| Kalshi | — | — | — | 23:29 UTC | View → |
| Kalshi | — | — | — | 09:18 UTC | View → |
| Kalshi | — | — | — | 16:15 UTC | View → |
| Kalshi | — | — | — | 23:29 UTC | View → |
What do these odds mean?
Cross-platform data for yes Los Angeles A,yes New York Y,yes Seattle,yes Texas 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.