yes Toronto,yes Dallas,yes San Antonio,yes Detroit,yes Houston,yes Philadelphia,yes Oklahoma City,yes Portland,yes Los Angeles L
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 08:41 UTC | View → |
| Kalshi | — | — | — | 07:26 UTC | View → |
| Kalshi | — | — | — | 07:51 UTC | View → |
| Kalshi | — | — | — | 07:25 UTC | View → |
| Kalshi | — | — | — | 11:14 UTC | View → |
| Kalshi | — | — | — | 08:14 UTC | View → |
| Kalshi | — | — | — | 08:41 UTC | View → |
| Kalshi | — | — | — | 08:41 UTC | View → |
| Kalshi | — | — | — | 08:13 UTC | View → |
| Kalshi | — | — | — | 08:13 UTC | View → |
| Kalshi | — | — | — | 08:15 UTC | View → |
| Kalshi | — | — | — | 07:25 UTC | View → |
| Kalshi | — | — | — | 07:44 UTC | View → |
| Kalshi | — | — | — | 07:25 UTC | View → |
| Kalshi | — | — | — | 08:14 UTC | View → |
| Kalshi | — | — | — | 08:50 UTC | View → |
| Kalshi | — | — | — | 08:26 UTC | View → |
| Kalshi | — | — | — | 08:29 UTC | View → |
| Kalshi | — | — | — | 10:53 UTC | View → |
| Kalshi | — | — | — | 08:13 UTC | View → |
| Kalshi | — | — | — | 08:54 UTC | View → |
| Kalshi | — | — | — | 08:56 UTC | View → |
| Kalshi | — | — | — | 11:47 UTC | View → |
| Kalshi | — | — | — | 07:27 UTC | View → |
| Kalshi | — | — | — | 11:49 UTC | View → |
| Kalshi | — | — | — | 07:44 UTC | View → |
| Kalshi | — | — | — | 08:13 UTC | View → |
| Kalshi | — | — | — | 08:15 UTC | View → |
| Kalshi | — | — | — | 12:31 UTC | View → |
| Kalshi | — | — | — | 08:49 UTC | View → |
| Kalshi | — | — | — | 08:54 UTC | View → |
| Kalshi | — | — | — | 08:29 UTC | View → |
| Kalshi | — | — | — | 08:37 UTC | View → |
| Kalshi | — | — | — | 08:46 UTC | View → |
| Kalshi | — | — | — | 08:49 UTC | View → |
| Kalshi | — | — | — | 08:42 UTC | View → |
| Kalshi | — | — | — | 08:38 UTC | View → |
| Kalshi | — | — | — | 20:33 UTC | View → |
| Kalshi | — | — | — | 20:53 UTC | View → |
| Kalshi | — | — | — | 12:22 UTC | View → |
| Kalshi | — | — | — | 07:59 UTC | View → |
| Kalshi | — | — | — | 10:20 UTC | View → |
| Kalshi | — | — | — | 10:35 UTC | View → |
| Kalshi | — | — | — | 07:32 UTC | View → |
| Kalshi | — | — | — | 11:48 UTC | View → |
| Kalshi | — | — | — | 09:55 UTC | View → |
| Kalshi | — | — | — | 08:42 UTC | View → |
| Kalshi | — | — | — | 23:13 UTC | View → |
| Kalshi | — | — | — | 07:59 UTC | View → |
| Kalshi | — | — | — | 09:55 UTC | View → |
| Kalshi | — | — | — | 09:55 UTC | View → |
| Kalshi | — | — | — | 07:25 UTC | View → |
| Kalshi | — | — | — | 08:54 UTC | View → |
| Kalshi | — | — | — | 10:35 UTC | View → |
| Kalshi | — | — | — | 20:53 UTC | View → |
| Kalshi | — | — | — | 21:15 UTC | View → |
| Kalshi | — | — | — | 08:52 UTC | View → |
| Kalshi | — | — | — | 08:54 UTC | View → |
| Kalshi | — | — | — | 11:49 UTC | View → |
| Kalshi | — | — | — | 08:46 UTC | View → |
| Kalshi | — | — | — | 08:48 UTC | View → |
| Kalshi | — | — | — | 08:52 UTC | View → |
| Kalshi | — | — | — | 10:34 UTC | View → |
| Kalshi | — | — | — | 20:25 UTC | View → |
| Kalshi | — | — | — | 08:29 UTC | View → |
| Kalshi | — | — | — | 07:59 UTC | View → |
| Kalshi | — | — | — | 20:40 UTC | View → |
| Kalshi | — | — | — | 08:38 UTC | View → |
| Kalshi | — | — | — | 08:56 UTC | View → |
| Kalshi | — | — | — | 08:51 UTC | View → |
| Kalshi | — | — | — | 07:45 UTC | View → |
| Kalshi | — | — | — | 20:24 UTC | View → |
| Kalshi | — | — | — | 08:52 UTC | View → |
| Kalshi | — | — | — | 08:51 UTC | View → |
| Kalshi | — | — | — | 21:15 UTC | View → |
| Kalshi | — | — | — | 08:51 UTC | View → |
| Kalshi | — | — | — | 08:42 UTC | View → |
| Kalshi | — | — | — | 20:36 UTC | View → |
What do these odds mean?
Cross-platform data for yes Toronto,yes Dallas,yes San Antonio,yes Detroit,yes Houston,yes Philadelphia,yes Oklahoma City,yes Portland,yes Los Angeles L 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.