yes De'Aaron Fox: 2+,yes Alperen Sengun: 2+,yes Amen Thompson: 2+,yes Atlanta,yes San Antonio,yes Golden State,yes Miami,yes Houston,yes Boston,yes Oklahoma City,yes Orlando,yes Philadelphia,yes Phoenix,yes New York,yes De'Aaron Fox: 10+,yes Toumani Camara: 10+,yes Jabari Smith Jr.: 10+,yes Scottie Barnes: 10+,yes Kevin Durant: 2+
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 00:10 UTC | View → |
| Kalshi | — | — | — | 10:33 UTC | View → |
| Kalshi | — | — | — | 08:03 UTC | View → |
| Kalshi | — | — | — | 08:13 UTC | View → |
| Kalshi | — | — | — | 08:14 UTC | View → |
| Kalshi | — | — | — | 08:15 UTC | View → |
| Kalshi | — | — | — | 10:16 UTC | View → |
| Kalshi | — | — | — | 08:05 UTC | View → |
| Kalshi | — | — | — | 22:22 UTC | View → |
| Kalshi | — | — | — | 19:30 UTC | View → |
| Kalshi | — | — | — | 08:02 UTC | View → |
| Kalshi | — | — | — | 09:25 UTC | View → |
| Kalshi | — | — | — | 07:57 UTC | View → |
| Kalshi | — | — | — | 07:59 UTC | View → |
| Kalshi | — | — | — | 08:04 UTC | View → |
| Kalshi | — | — | — | 08:16 UTC | View → |
| Kalshi | — | — | — | 08:15 UTC | View → |
| Kalshi | — | — | — | 07:56 UTC | View → |
| Kalshi | — | — | — | 10:32 UTC | View → |
| Kalshi | — | — | — | 10:32 UTC | View → |
| Kalshi | — | — | — | 13:58 UTC | View → |
| Kalshi | — | — | — | 16:46 UTC | View → |
| Kalshi | — | — | — | 20:19 UTC | View → |
| Kalshi | — | — | — | 16:23 UTC | View → |
| Kalshi | — | — | — | 10:33 UTC | View → |
| Kalshi | — | — | — | 21:03 UTC | View → |
| Kalshi | — | — | — | 10:33 UTC | View → |
| Kalshi | — | — | — | 07:58 UTC | View → |
| Kalshi | — | — | — | 07:56 UTC | View → |
| Kalshi | — | — | — | 22:23 UTC | View → |
| Kalshi | — | — | — | 07:58 UTC | View → |
| Kalshi | — | — | — | 07:56 UTC | View → |
| Kalshi | — | — | — | 08:05 UTC | View → |
| Kalshi | — | — | — | 07:55 UTC | View → |
| Kalshi | — | — | — | 08:04 UTC | View → |
| Kalshi | — | — | — | 09:29 UTC | View → |
| Kalshi | — | — | — | 18:47 UTC | View → |
| Kalshi | — | — | — | 09:28 UTC | View → |
| Kalshi | — | — | — | 19:30 UTC | View → |
| Kalshi | — | — | — | 08:03 UTC | View → |
| Kalshi | — | — | — | 10:32 UTC | View → |
| Kalshi | — | — | — | 17:24 UTC | View → |
| Kalshi | — | — | — | 10:32 UTC | View → |
| Kalshi | — | — | — | 07:59 UTC | View → |
| Kalshi | — | — | — | 10:04 UTC | View → |
| Kalshi | — | — | — | 09:53 UTC | View → |
| Kalshi | — | — | — | 08:12 UTC | View → |
| Kalshi | — | — | — | 23:42 UTC | View → |
| Kalshi | — | — | — | 08:01 UTC | View → |
| Kalshi | — | — | — | 08:00 UTC | View → |
| Kalshi | — | — | — | 08:01 UTC | View → |
| Kalshi | — | — | — | 07:55 UTC | View → |
| Kalshi | — | — | — | 20:18 UTC | View → |
| Kalshi | — | — | — | 10:04 UTC | View → |
| Kalshi | — | — | — | 09:28 UTC | View → |
| Kalshi | — | — | — | 16:23 UTC | View → |
| Kalshi | — | — | — | 08:02 UTC | View → |
| Kalshi | — | — | — | 07:56 UTC | View → |
| Kalshi | — | — | — | 23:42 UTC | View → |
| Kalshi | — | — | — | 09:21 UTC | View → |
| Kalshi | — | — | — | 21:37 UTC | View → |
| Kalshi | — | — | — | 08:16 UTC | View → |
| Kalshi | — | — | — | 11:25 UTC | View → |
| Kalshi | — | — | — | 09:02 UTC | View → |
| Kalshi | — | — | — | 11:25 UTC | View → |
| Kalshi | — | — | — | 11:56 UTC | View → |
| Kalshi | — | — | — | 09:00 UTC | View → |
| Kalshi | — | — | — | 14:33 UTC | View → |
| Kalshi | — | — | — | 22:17 UTC | View → |
| Kalshi | — | — | — | 11:57 UTC | View → |
| Kalshi | — | — | — | 08:48 UTC | View → |
| Kalshi | — | — | — | 14:38 UTC | View → |
| Kalshi | — | — | — | 00:09 UTC | View → |
| Kalshi | — | — | — | 09:18 UTC | View → |
| Kalshi | — | — | — | 09:18 UTC | View → |
| Kalshi | — | — | — | 12:00 UTC | View → |
| Kalshi | — | — | — | 23:28 UTC | View → |
| Kalshi | — | — | — | 18:03 UTC | View → |
| Kalshi | — | — | — | 11:57 UTC | View → |
| Kalshi | — | — | — | 12:00 UTC | View → |
| Kalshi | — | — | — | 12:17 UTC | View → |
| Kalshi | — | — | — | 12:16 UTC | View → |
| Kalshi | — | — | — | 14:25 UTC | View → |
| Kalshi | — | — | — | 09:18 UTC | View → |
| Kalshi | — | — | — | 10:42 UTC | View → |
| Kalshi | — | — | — | 11:56 UTC | View → |
| Kalshi | — | — | — | 01:12 UTC | View → |
| Kalshi | — | — | — | 18:05 UTC | View → |
| Kalshi | — | — | — | 12:26 UTC | View → |
| Kalshi | — | — | — | 12:26 UTC | View → |
| Kalshi | — | — | — | 12:26 UTC | View → |
| Kalshi | — | — | — | 21:28 UTC | View → |
| Kalshi | — | — | — | 14:32 UTC | View → |
| Kalshi | — | — | — | 18:04 UTC | View → |
| Kalshi | — | — | — | 09:02 UTC | View → |
| Kalshi | — | — | — | 13:13 UTC | View → |
| Kalshi | — | — | — | 23:13 UTC | View → |
| Kalshi | — | — | — | 22:17 UTC | View → |
| Kalshi | — | — | — | 12:00 UTC | View → |
| Kalshi | — | — | — | 13:17 UTC | View → |
| Kalshi | — | — | — | 17:50 UTC | View → |
| Kalshi | — | — | — | 23:13 UTC | View → |
| Kalshi | — | — | — | 14:18 UTC | View → |
| Kalshi | — | — | — | 21:16 UTC | View → |
| Kalshi | — | — | — | 15:24 UTC | View → |
| Kalshi | — | — | — | 09:11 UTC | View → |
| Kalshi | — | — | — | 11:25 UTC | View → |
| Kalshi | — | — | — | 14:36 UTC | View → |
| Kalshi | — | — | — | 14:25 UTC | View → |
What do these odds mean?
Cross-platform data for yes De'Aaron Fox: 2+,yes Alperen Sengun: 2+,yes Amen Thompson: 2+,yes Atlanta,yes San Antonio,yes Golden State,yes Miami,yes Houston,yes Boston,yes Oklahoma City,yes Orlando,yes Philadelphia,yes Phoenix,yes New York,yes De'Aaron Fox: 10+,yes Toumani Camara: 10+,yes Jabari Smith Jr.: 10+,yes Scottie Barnes: 10+,yes Kevin Durant: 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.