yes Cincinnati,yes Toronto,yes Boston,yes Los Angeles D,yes Atlanta,yes Charlotte
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 15:29 UTC | View → |
| Kalshi | — | — | — | 18:00 UTC | View → |
| Kalshi | — | — | — | 21:56 UTC | View → |
| Kalshi | — | — | — | 20:46 UTC | View → |
| Kalshi | — | — | — | 11:41 UTC | View → |
| Kalshi | — | — | — | 15:59 UTC | View → |
| Kalshi | — | — | — | 18:10 UTC | View → |
| Kalshi | — | — | — | 18:00 UTC | View → |
| Kalshi | — | — | — | 18:00 UTC | View → |
| Kalshi | — | — | — | 12:37 UTC | View → |
| Kalshi | — | — | — | 22:33 UTC | View → |
| Kalshi | — | — | — | 08:52 UTC | View → |
| Kalshi | — | — | — | 13:07 UTC | View → |
| Kalshi | — | — | — | 12:37 UTC | View → |
| Kalshi | — | — | — | 13:10 UTC | View → |
| Kalshi | — | — | — | 16:11 UTC | View → |
| Kalshi | — | — | — | 22:05 UTC | View → |
| Kalshi | — | — | — | 13:12 UTC | View → |
| Kalshi | — | — | — | 21:10 UTC | View → |
| Kalshi | — | — | — | 11:41 UTC | View → |
| Kalshi | — | — | — | 23:07 UTC | View → |
| Kalshi | — | — | — | 19:03 UTC | View → |
| Kalshi | — | — | — | 15:06 UTC | View → |
| Kalshi | — | — | — | 15:18 UTC | View → |
| Kalshi | — | — | — | 18:10 UTC | View → |
| Kalshi | — | — | — | 17:48 UTC | View → |
| Kalshi | — | — | — | 16:19 UTC | View → |
| Kalshi | — | — | — | 21:05 UTC | View → |
| Kalshi | — | — | — | 19:39 UTC | View → |
| Kalshi | — | — | — | 23:26 UTC | View → |
| Kalshi | — | — | — | 17:02 UTC | View → |
| Kalshi | — | — | — | 18:38 UTC | View → |
| Kalshi | — | — | — | 10:15 UTC | View → |
| Kalshi | — | — | — | 12:51 UTC | View → |
| Kalshi | — | — | — | 11:09 UTC | View → |
| Kalshi | — | — | — | 22:46 UTC | View → |
| Kalshi | — | — | — | 22:22 UTC | View → |
| Kalshi | — | — | — | 10:13 UTC | View → |
| Kalshi | — | — | — | 13:52 UTC | View → |
| Kalshi | — | — | — | 21:33 UTC | View → |
| Kalshi | — | — | — | 23:30 UTC | View → |
| Kalshi | — | — | — | 10:14 UTC | View → |
| Kalshi | — | — | — | 13:18 UTC | View → |
| Kalshi | — | — | — | 22:34 UTC | View → |
| Kalshi | — | — | — | 13:15 UTC | View → |
| Kalshi | — | — | — | 07:48 UTC | View → |
| Kalshi | — | — | — | 20:54 UTC | View → |
| Kalshi | — | — | — | 12:50 UTC | View → |
| Kalshi | — | — | — | 20:54 UTC | View → |
| Kalshi | — | — | — | 19:33 UTC | View → |
| Kalshi | — | — | — | 12:50 UTC | View → |
| Kalshi | — | — | — | 15:18 UTC | View → |
| Kalshi | — | — | — | 19:54 UTC | View → |
| Kalshi | — | — | — | 22:09 UTC | View → |
| Kalshi | — | — | — | 13:16 UTC | View → |
| Kalshi | — | — | — | 15:08 UTC | View → |
| Kalshi | — | — | — | 18:39 UTC | View → |
| Kalshi | — | — | — | 21:52 UTC | View → |
| Kalshi | — | — | — | 16:54 UTC | View → |
| Kalshi | — | — | — | 21:13 UTC | View → |
| Kalshi | — | — | — | 16:37 UTC | View → |
| Kalshi | — | — | — | 10:25 UTC | View → |
| Kalshi | — | — | — | 10:15 UTC | View → |
| Kalshi | — | — | — | 19:07 UTC | View → |
| Kalshi | — | — | — | 08:28 UTC | View → |
| Kalshi | — | — | — | 11:09 UTC | View → |
| Kalshi | — | — | — | 10:18 UTC | View → |
| Kalshi | — | — | — | 12:06 UTC | View → |
| Kalshi | — | — | — | 20:11 UTC | View → |
| Kalshi | — | — | — | 14:49 UTC | View → |
| Kalshi | — | — | — | 11:09 UTC | View → |
| Kalshi | — | — | — | 20:28 UTC | View → |
| Kalshi | — | — | — | 12:05 UTC | View → |
| Kalshi | — | — | — | 13:18 UTC | View → |
What do these odds mean?
Cross-platform data for yes Cincinnati,yes Toronto,yes Boston,yes Los Angeles D,yes Atlanta,yes Charlotte 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.