yes Deni Avdija: 20+,yes Donovan Clingan: 10+,yes Toumani Camara: 15+
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 09:44 UTC | View → |
| Kalshi | — | — | — | 11:30 UTC | View → |
| Kalshi | — | — | — | 21:11 UTC | View → |
| Kalshi | — | — | — | 20:35 UTC | View → |
| Kalshi | — | — | — | 21:22 UTC | View → |
| Kalshi | — | — | — | 14:44 UTC | View → |
| Kalshi | — | — | — | 18:21 UTC | View → |
| Kalshi | — | — | — | 09:44 UTC | View → |
| Kalshi | — | — | — | 07:23 UTC | View → |
| Kalshi | — | — | — | 00:58 UTC | View → |
| Kalshi | — | — | — | 19:59 UTC | View → |
| Kalshi | — | — | — | 21:43 UTC | View → |
| Kalshi | — | — | — | 16:54 UTC | View → |
| Kalshi | — | — | — | 23:31 UTC | View → |
| Kalshi | — | — | — | 06:13 UTC | View → |
| Kalshi | — | — | — | 06:13 UTC | View → |
| Kalshi | — | — | — | 10:58 UTC | View → |
| Kalshi | — | — | — | 11:39 UTC | View → |
| Kalshi | — | — | — | 23:12 UTC | View → |
| Kalshi | — | — | — | 20:44 UTC | View → |
| Kalshi | — | — | — | 20:44 UTC | View → |
| Kalshi | — | — | — | 23:42 UTC | View → |
| Kalshi | — | — | — | 21:20 UTC | View → |
| Kalshi | — | — | — | 14:44 UTC | View → |
| Kalshi | — | — | — | 01:05 UTC | View → |
| Kalshi | — | — | — | 18:16 UTC | View → |
| Kalshi | — | — | — | 23:12 UTC | View → |
| Kalshi | — | — | — | 06:05 UTC | View → |
| Kalshi | — | — | — | 15:50 UTC | View → |
| Kalshi | — | — | — | 21:25 UTC | View → |
| Kalshi | — | — | — | 00:37 UTC | View → |
| Kalshi | — | — | — | 06:43 UTC | View → |
| Kalshi | — | — | — | 16:05 UTC | View → |
| Kalshi | — | — | — | 09:28 UTC | View → |
| Kalshi | — | — | — | 15:50 UTC | View → |
| Kalshi | — | — | — | 23:13 UTC | View → |
| Kalshi | — | — | — | 19:56 UTC | View → |
| Kalshi | — | — | — | 19:57 UTC | View → |
| Kalshi | — | — | — | 15:50 UTC | View → |
| Kalshi | — | — | — | 15:50 UTC | View → |
| Kalshi | — | — | — | 06:41 UTC | View → |
| Kalshi | — | — | — | 19:13 UTC | View → |
| Kalshi | — | — | — | 17:20 UTC | View → |
| Kalshi | — | — | — | 00:43 UTC | View → |
| Kalshi | — | — | — | 05:34 UTC | View → |
| Kalshi | — | — | — | 06:43 UTC | View → |
| Kalshi | — | — | — | 15:50 UTC | View → |
| Kalshi | — | — | — | 21:54 UTC | View → |
| Kalshi | — | — | — | 00:59 UTC | View → |
| Kalshi | — | — | — | 12:24 UTC | View → |
| Kalshi | — | — | — | 14:02 UTC | View → |
| Kalshi | — | — | — | 00:45 UTC | View → |
| Kalshi | — | — | — | 06:24 UTC | View → |
| Kalshi | — | — | — | 00:58 UTC | View → |
| Kalshi | — | — | — | 09:28 UTC | View → |
| Kalshi | — | — | — | 15:50 UTC | View → |
| Kalshi | — | — | — | 07:19 UTC | View → |
| Kalshi | — | — | — | 09:28 UTC | View → |
| Kalshi | — | — | — | 12:16 UTC | View → |
| Kalshi | — | — | — | 01:06 UTC | View → |
| Kalshi | — | — | — | 19:58 UTC | View → |
| Kalshi | — | — | — | 19:36 UTC | View → |
| Kalshi | — | — | — | 12:24 UTC | View → |
| Kalshi | — | — | — | 20:03 UTC | View → |
| Kalshi | — | — | — | 15:50 UTC | View → |
| Kalshi | — | — | — | 16:01 UTC | View → |
| Kalshi | — | — | — | 15:50 UTC | View → |
| Kalshi | — | — | — | 12:24 UTC | View → |
| Kalshi | — | — | — | 21:16 UTC | View → |
| Kalshi | — | — | — | 15:50 UTC | View → |
What do these odds mean?
Cross-platform data for yes Deni Avdija: 20+,yes Donovan Clingan: 10+,yes Toumani Camara: 15+ 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.