yes Bam Adebayo: 2+,yes Davion Mitchell: 4+,yes Bub Carrington: 2+,yes Miami,yes Andrew Wiggins: 10+
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 13:51 UTC | View → |
| Kalshi | — | — | — | 20:04 UTC | View → |
| Kalshi | — | — | — | 19:45 UTC | View → |
| Kalshi | — | — | — | 13:51 UTC | View → |
| Kalshi | — | — | — | 12:26 UTC | View → |
| Kalshi | — | — | — | 15:50 UTC | View → |
| Kalshi | — | — | — | 12:25 UTC | View → |
| Kalshi | — | — | — | 17:01 UTC | View → |
| Kalshi | — | — | — | 17:13 UTC | View → |
| Kalshi | — | — | — | 17:13 UTC | View → |
| Kalshi | — | — | — | 21:34 UTC | View → |
| Kalshi | — | — | — | 19:30 UTC | View → |
| Kalshi | — | — | — | 23:14 UTC | View → |
| Kalshi | — | — | — | 22:27 UTC | View → |
| Kalshi | — | — | — | 13:27 UTC | View → |
| Kalshi | — | — | — | 17:47 UTC | View → |
| Kalshi | — | — | — | 12:25 UTC | View → |
| Kalshi | — | — | — | 19:43 UTC | View → |
| Kalshi | — | — | — | 21:07 UTC | View → |
| Kalshi | — | — | — | 21:09 UTC | View → |
| Kalshi | — | — | — | 20:26 UTC | View → |
| Kalshi | — | — | — | 20:25 UTC | View → |
| Kalshi | — | — | — | 19:44 UTC | View → |
| Kalshi | — | — | — | 20:26 UTC | View → |
| Kalshi | — | — | — | 16:46 UTC | View → |
| Kalshi | — | — | — | 12:24 UTC | View → |
| Kalshi | — | — | — | 20:04 UTC | View → |
| Kalshi | — | — | — | 15:48 UTC | View → |
| Kalshi | — | — | — | 17:43 UTC | View → |
| Kalshi | — | — | — | 20:26 UTC | View → |
| Kalshi | — | — | — | 12:33 UTC | View → |
| Kalshi | — | — | — | 21:21 UTC | View → |
| Kalshi | — | — | — | 20:47 UTC | View → |
| Kalshi | — | — | — | 17:29 UTC | View → |
| Kalshi | — | — | — | 17:17 UTC | View → |
| Kalshi | — | — | — | 21:41 UTC | View → |
| Kalshi | — | — | — | 14:05 UTC | View → |
| Kalshi | — | — | — | 19:43 UTC | View → |
| Kalshi | — | — | — | 18:13 UTC | View → |
| Kalshi | — | — | — | 21:56 UTC | View → |
| Kalshi | — | — | — | 17:18 UTC | View → |
| Kalshi | — | — | — | 13:31 UTC | View → |
| Kalshi | — | — | — | 13:00 UTC | View → |
| Kalshi | — | — | — | 13:00 UTC | View → |
| Kalshi | — | — | — | 12:29 UTC | View → |
| Kalshi | — | — | — | 13:18 UTC | View → |
| Kalshi | — | — | — | 12:27 UTC | View → |
| Kalshi | — | — | — | 19:07 UTC | View → |
| Kalshi | — | — | — | 12:41 UTC | View → |
| Kalshi | — | — | — | 18:01 UTC | View → |
| Kalshi | — | — | — | 13:12 UTC | View → |
| Kalshi | — | — | — | 12:43 UTC | View → |
| Kalshi | — | — | — | 20:47 UTC | View → |
| Kalshi | — | — | — | 14:23 UTC | View → |
| Kalshi | — | — | — | 20:23 UTC | View → |
| Kalshi | — | — | — | 14:05 UTC | View → |
| Kalshi | — | — | — | 20:47 UTC | View → |
| Kalshi | — | — | — | 13:31 UTC | View → |
| Kalshi | — | — | — | 13:00 UTC | View → |
| Kalshi | — | — | — | 13:00 UTC | View → |
| Kalshi | — | — | — | 13:18 UTC | View → |
| Kalshi | — | — | — | 12:27 UTC | View → |
| Kalshi | — | — | — | 18:01 UTC | View → |
| Kalshi | — | — | — | 13:19 UTC | View → |
| Kalshi | — | — | — | 13:19 UTC | View → |
| Kalshi | — | — | — | 14:23 UTC | View → |
| Kalshi | — | — | — | 12:44 UTC | View → |
| Kalshi | — | — | — | 14:23 UTC | View → |
| Kalshi | — | — | — | 19:59 UTC | View → |
| Kalshi | — | — | — | 19:57 UTC | View → |
| Kalshi | — | — | — | 15:14 UTC | View → |
| Kalshi | — | — | — | 12:31 UTC | View → |
| Kalshi | — | — | — | 15:45 UTC | View → |
| Kalshi | — | — | — | 14:53 UTC | View → |
What do these odds mean?
Cross-platform data for yes Bam Adebayo: 2+,yes Davion Mitchell: 4+,yes Bub Carrington: 2+,yes Miami,yes Andrew Wiggins: 10+ 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.