yes Oneil Cruz: 1+,yes Pete Crow-Armstrong: 1+
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 11:22 UTC | View → |
| Kalshi | — | — | — | 11:22 UTC | View → |
| Kalshi | — | — | — | 10:36 UTC | View → |
| Kalshi | — | — | — | 19:28 UTC | View → |
| Kalshi | — | — | — | 11:22 UTC | View → |
| Kalshi | — | — | — | 13:48 UTC | View → |
| Kalshi | — | — | — | 13:46 UTC | View → |
| Kalshi | — | — | — | 11:22 UTC | View → |
| Kalshi | — | — | — | 16:21 UTC | View → |
| Kalshi | — | — | — | 08:34 UTC | View → |
| Kalshi | — | — | — | 11:22 UTC | View → |
| Kalshi | — | — | — | 08:40 UTC | View → |
| Kalshi | — | — | — | 08:42 UTC | View → |
| Kalshi | — | — | — | 11:22 UTC | View → |
| Kalshi | — | — | — | 11:22 UTC | View → |
| Kalshi | — | — | — | 10:46 UTC | View → |
| Kalshi | — | — | — | 17:54 UTC | View → |
| Kalshi | — | — | — | 11:22 UTC | View → |
| Kalshi | — | — | — | 14:01 UTC | View → |
| Kalshi | — | — | — | 11:12 UTC | View → |
| Kalshi | — | — | — | 14:13 UTC | View → |
| Kalshi | — | — | — | 19:28 UTC | View → |
| Kalshi | — | — | — | 07:25 UTC | View → |
| Kalshi | — | — | — | 08:40 UTC | View → |
| Kalshi | — | — | — | 11:41 UTC | View → |
| Kalshi | — | — | — | 10:52 UTC | View → |
| Kalshi | — | — | — | 11:22 UTC | View → |
| Kalshi | — | — | — | 15:07 UTC | View → |
| Kalshi | — | — | — | 14:13 UTC | View → |
| Kalshi | — | — | — | 14:13 UTC | View → |
| Kalshi | — | — | — | 09:51 UTC | View → |
| Kalshi | — | — | — | 16:18 UTC | View → |
| Kalshi | — | — | — | 10:35 UTC | View → |
| Kalshi | — | — | — | 12:24 UTC | View → |
| Kalshi | — | — | — | 14:58 UTC | View → |
| Kalshi | — | — | — | 15:15 UTC | View → |
| Kalshi | — | — | — | 10:25 UTC | View → |
| Kalshi | — | — | — | 14:37 UTC | View → |
| Kalshi | — | — | — | 14:06 UTC | View → |
| Kalshi | — | — | — | 10:56 UTC | View → |
| Kalshi | — | — | — | 10:25 UTC | View → |
| Kalshi | — | — | — | 14:45 UTC | View → |
| Kalshi | — | — | — | 14:37 UTC | View → |
| Kalshi | — | — | — | 11:18 UTC | View → |
| Kalshi | — | — | — | 10:35 UTC | View → |
| Kalshi | — | — | — | 14:44 UTC | View → |
| Kalshi | — | — | — | 14:37 UTC | View → |
| Kalshi | — | — | — | 10:25 UTC | View → |
| Kalshi | — | — | — | 18:14 UTC | View → |
| Kalshi | — | — | — | 13:32 UTC | View → |
| Kalshi | — | — | — | 14:38 UTC | View → |
| Kalshi | — | — | — | 10:34 UTC | View → |
| Kalshi | — | — | — | 10:34 UTC | View → |
| Kalshi | — | — | — | 11:26 UTC | View → |
| Kalshi | — | — | — | 13:57 UTC | View → |
| Kalshi | — | — | — | 10:17 UTC | View → |
| Kalshi | — | — | — | 14:34 UTC | View → |
| Kalshi | — | — | — | 14:38 UTC | View → |
| Kalshi | — | — | — | 14:44 UTC | View → |
| Kalshi | — | — | — | 19:05 UTC | View → |
| Kalshi | — | — | — | 17:46 UTC | View → |
| Kalshi | — | — | — | 14:37 UTC | View → |
| Kalshi | — | — | — | 10:25 UTC | View → |
| Kalshi | — | — | — | 11:50 UTC | View → |
| Kalshi | — | — | — | 14:37 UTC | View → |
| Kalshi | — | — | — | 14:46 UTC | View → |
| Kalshi | — | — | — | 14:33 UTC | View → |
| Kalshi | — | — | — | 14:45 UTC | View → |
| Kalshi | — | — | — | 15:15 UTC | View → |
| Kalshi | — | — | — | 15:15 UTC | View → |
| Kalshi | — | — | — | 12:03 UTC | View → |
| Kalshi | — | — | — | 16:44 UTC | View → |
| Kalshi | — | — | — | 10:25 UTC | View → |
| Kalshi | — | — | — | 11:18 UTC | View → |
| Kalshi | — | — | — | 14:37 UTC | View → |
| Kalshi | — | — | — | 17:30 UTC | View → |
| Kalshi | — | — | — | 10:25 UTC | View → |
| Kalshi | — | — | — | 09:54 UTC | View → |
| Kalshi | — | — | — | 14:37 UTC | View → |
| Kalshi | — | — | — | 10:25 UTC | View → |
| Kalshi | — | — | — | 10:25 UTC | View → |
| Kalshi | — | — | — | 10:25 UTC | View → |
What do these odds mean?
Cross-platform data for yes Oneil Cruz: 1+,yes Pete Crow-Armstrong: 1+ 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.