yes Real Madrid,yes Philadelphia,yes Roma
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 05:52 UTC | View → |
| Kalshi | — | — | — | 08:38 UTC | View → |
| Kalshi | — | — | — | 09:27 UTC | View → |
| Kalshi | — | — | — | 06:05 UTC | View → |
| Kalshi | — | — | — | 14:46 UTC | View → |
| Kalshi | — | — | — | 13:57 UTC | View → |
| Kalshi | — | — | — | 05:46 UTC | View → |
| Kalshi | — | — | — | 13:07 UTC | View → |
| Kalshi | — | — | — | 08:38 UTC | View → |
| Kalshi | — | — | — | 13:28 UTC | View → |
| Kalshi | — | — | — | 06:49 UTC | View → |
| Kalshi | — | — | — | 08:19 UTC | View → |
| Kalshi | — | — | — | 02:15 UTC | View → |
| Kalshi | — | — | — | 06:13 UTC | View → |
| Kalshi | — | — | — | 16:15 UTC | View → |
| Kalshi | — | — | — | 08:15 UTC | View → |
| Kalshi | — | — | — | 08:38 UTC | View → |
| Kalshi | — | — | — | 10:46 UTC | View → |
| Kalshi | — | — | — | 05:57 UTC | View → |
| Kalshi | — | — | — | 08:15 UTC | View → |
| Kalshi | — | — | — | 11:46 UTC | View → |
| Kalshi | — | — | — | 05:27 UTC | View → |
| Kalshi | — | — | — | 08:15 UTC | View → |
| Kalshi | — | — | — | 06:18 UTC | View → |
| Kalshi | — | — | — | 05:58 UTC | View → |
| Kalshi | — | — | — | 04:56 UTC | View → |
| Kalshi | — | — | — | 06:05 UTC | View → |
| Kalshi | — | — | — | 09:01 UTC | View → |
| Kalshi | — | — | — | 06:17 UTC | View → |
| Kalshi | — | — | — | 11:46 UTC | View → |
| Kalshi | — | — | — | 12:31 UTC | View → |
| Kalshi | — | — | — | 05:57 UTC | View → |
| Kalshi | — | — | — | 14:27 UTC | View → |
| Kalshi | — | — | — | 13:11 UTC | View → |
| Kalshi | — | — | — | 04:56 UTC | View → |
| Kalshi | — | — | — | 14:39 UTC | View → |
| Kalshi | — | — | — | 15:38 UTC | View → |
| Kalshi | — | — | — | 04:56 UTC | View → |
| Kalshi | — | — | — | 06:47 UTC | View → |
| Kalshi | — | — | — | 12:38 UTC | View → |
| Kalshi | — | — | — | 11:46 UTC | View → |
| Kalshi | — | — | — | 12:54 UTC | View → |
| Kalshi | — | — | — | 06:17 UTC | View → |
| Kalshi | — | — | — | 02:12 UTC | View → |
| Kalshi | — | — | — | 12:36 UTC | View → |
| Kalshi | — | — | — | 06:00 UTC | View → |
| Kalshi | — | — | — | 15:31 UTC | View → |
| Kalshi | — | — | — | 15:11 UTC | View → |
| Kalshi | — | — | — | 16:02 UTC | View → |
| Kalshi | — | — | — | 11:51 UTC | View → |
| Kalshi | — | — | — | 11:51 UTC | View → |
| Kalshi | — | — | — | 10:13 UTC | View → |
| Kalshi | — | — | — | 14:22 UTC | View → |
| Kalshi | — | — | — | 16:03 UTC | View → |
| Kalshi | — | — | — | 16:18 UTC | View → |
| Kalshi | — | — | — | 14:48 UTC | View → |
| Kalshi | — | — | — | 08:47 UTC | View → |
| Kalshi | — | — | — | 05:34 UTC | View → |
| Kalshi | — | — | — | 07:53 UTC | View → |
| Kalshi | — | — | — | 11:51 UTC | View → |
| Kalshi | — | — | — | 16:02 UTC | View → |
| Kalshi | — | — | — | 08:11 UTC | View → |
| Kalshi | — | — | — | 08:11 UTC | View → |
| Kalshi | — | — | — | 15:06 UTC | View → |
| Kalshi | — | — | — | 07:21 UTC | View → |
| Kalshi | — | — | — | 13:54 UTC | View → |
| Kalshi | — | — | — | 07:51 UTC | View → |
| Kalshi | — | — | — | 12:32 UTC | View → |
| Kalshi | — | — | — | 14:48 UTC | View → |
| Kalshi | — | — | — | 11:22 UTC | View → |
| Kalshi | — | — | — | 12:14 UTC | View → |
| Kalshi | — | — | — | 04:54 UTC | View → |
| Kalshi | — | — | — | 05:38 UTC | View → |
| Kalshi | — | — | — | 06:39 UTC | View → |
| Kalshi | — | — | — | 05:29 UTC | View → |
| Kalshi | — | — | — | 10:13 UTC | View → |
| Kalshi | — | — | — | 05:39 UTC | View → |
| Kalshi | — | — | — | 14:46 UTC | View → |
| Kalshi | — | — | — | 05:15 UTC | View → |
| Kalshi | — | — | — | 11:54 UTC | View → |
| Kalshi | — | — | — | 15:32 UTC | View → |
| Kalshi | — | — | — | 06:39 UTC | View → |
| Kalshi | — | — | — | 08:58 UTC | View → |
| Kalshi | — | — | — | 07:28 UTC | View → |
What do these odds mean?
Cross-platform data for yes Real Madrid,yes Philadelphia,yes Roma 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.