yes Miami,yes Brandon Miller: 10+,yes Miles Bridges: 10+,yes Kon Knueppel: 2+,yes Miles Bridges: 2+,yes Ausar Thompson: 2+
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 19:48 UTC | View → |
| Kalshi | — | — | — | 23:11 UTC | View → |
| Kalshi | — | — | — | 06:08 UTC | View → |
| Kalshi | — | — | — | 09:28 UTC | View → |
| Kalshi | — | — | — | 09:21 UTC | View → |
| Kalshi | — | — | — | 19:54 UTC | View → |
| Kalshi | — | — | — | 14:42 UTC | View → |
| Kalshi | — | — | — | 09:28 UTC | View → |
| Kalshi | — | — | — | 19:58 UTC | View → |
| Kalshi | — | — | — | 23:11 UTC | View → |
| Kalshi | — | — | — | 06:09 UTC | View → |
| Kalshi | — | — | — | 06:08 UTC | View → |
| Kalshi | — | — | — | 18:07 UTC | View → |
| Kalshi | — | — | — | 09:22 UTC | View → |
| Kalshi | — | — | — | 13:03 UTC | View → |
| Kalshi | — | — | — | 09:28 UTC | View → |
| Kalshi | — | — | — | 07:48 UTC | View → |
| Kalshi | — | — | — | 20:24 UTC | View → |
| Kalshi | — | — | — | 06:32 UTC | View → |
| Kalshi | — | — | — | 23:20 UTC | View → |
| Kalshi | — | — | — | 06:32 UTC | View → |
| Kalshi | — | — | — | 07:07 UTC | View → |
| Kalshi | — | — | — | 14:02 UTC | View → |
| Kalshi | — | — | — | 06:47 UTC | View → |
| Kalshi | — | — | — | 14:02 UTC | View → |
| Kalshi | — | — | — | 22:28 UTC | View → |
| Kalshi | — | — | — | 14:02 UTC | View → |
| Kalshi | — | — | — | 06:32 UTC | View → |
| Kalshi | — | — | — | 11:25 UTC | View → |
| Kalshi | — | — | — | 13:13 UTC | View → |
| Kalshi | — | — | — | 15:36 UTC | View → |
| Kalshi | — | — | — | 08:38 UTC | View → |
| Kalshi | — | — | — | 16:51 UTC | View → |
| Kalshi | — | — | — | 22:52 UTC | View → |
| Kalshi | — | — | — | 19:04 UTC | View → |
| Kalshi | — | — | — | 16:50 UTC | View → |
| Kalshi | — | — | — | 18:52 UTC | View → |
| Kalshi | — | — | — | 14:02 UTC | View → |
| Kalshi | — | — | — | 17:42 UTC | View → |
| Kalshi | — | — | — | 17:28 UTC | View → |
| Kalshi | — | — | — | 00:21 UTC | View → |
| Kalshi | — | — | — | 06:47 UTC | View → |
| Kalshi | — | — | — | 06:47 UTC | View → |
| Kalshi | — | — | — | 06:27 UTC | View → |
| Kalshi | — | — | — | 16:50 UTC | View → |
| Kalshi | — | — | — | 23:16 UTC | View → |
| Kalshi | — | — | — | 14:02 UTC | View → |
| Kalshi | — | — | — | 18:16 UTC | View → |
| Kalshi | — | — | — | 16:59 UTC | View → |
| Kalshi | — | — | — | 16:51 UTC | View → |
| Kalshi | — | — | — | 08:38 UTC | View → |
| Kalshi | — | — | — | 13:13 UTC | View → |
| Kalshi | — | — | — | 15:36 UTC | View → |
| Kalshi | — | — | — | 07:39 UTC | View → |
| Kalshi | — | — | — | 11:06 UTC | View → |
| Kalshi | — | — | — | 10:44 UTC | View → |
| Kalshi | — | — | — | 20:27 UTC | View → |
| Kalshi | — | — | — | 08:58 UTC | View → |
| Kalshi | — | — | — | 16:58 UTC | View → |
| Kalshi | — | — | — | 17:36 UTC | View → |
| Kalshi | — | — | — | 20:27 UTC | View → |
| Kalshi | — | — | — | 11:08 UTC | View → |
| Kalshi | — | — | — | 19:04 UTC | View → |
| Kalshi | — | — | — | 07:12 UTC | View → |
| Kalshi | — | — | — | 10:06 UTC | View → |
| Kalshi | — | — | — | 08:38 UTC | View → |
| Kalshi | — | — | — | 17:41 UTC | View → |
| Kalshi | — | — | — | 19:30 UTC | View → |
| Kalshi | — | — | — | 06:32 UTC | View → |
| Kalshi | — | — | — | 13:54 UTC | View → |
| Kalshi | — | — | — | 17:53 UTC | View → |
| Kalshi | — | — | — | 14:02 UTC | View → |
| Kalshi | — | — | — | 11:06 UTC | View → |
What do these odds mean?
Cross-platform data for yes Miami,yes Brandon Miller: 10+,yes Miles Bridges: 10+,yes Kon Knueppel: 2+,yes Miles Bridges: 2+,yes Ausar Thompson: 2+ 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.