yes Kyle Kuzma: 10+,yes Myles Turner: 10+,yes De'Aaron Fox: 10+,yes Alperen Sengun: 15+,yes Cameron Johnson: 10+,yes Paolo Banchero: 20+
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 14:41 UTC | View → |
| Kalshi | — | — | — | 23:14 UTC | View → |
| Kalshi | — | — | — | 14:39 UTC | View → |
| Kalshi | — | — | — | 21:58 UTC | View → |
| Kalshi | — | — | — | 21:34 UTC | View → |
| Kalshi | — | — | — | 23:22 UTC | View → |
| Kalshi | — | — | — | 14:38 UTC | View → |
| Kalshi | — | — | — | 18:54 UTC | View → |
| Kalshi | — | — | — | 18:01 UTC | View → |
| Kalshi | — | — | — | 13:55 UTC | View → |
| Kalshi | — | — | — | 14:44 UTC | View → |
| Kalshi | — | — | — | 17:05 UTC | View → |
| Kalshi | — | — | — | 14:27 UTC | View → |
| Kalshi | — | — | — | 23:29 UTC | View → |
| Kalshi | — | — | — | 14:38 UTC | View → |
| Kalshi | — | — | — | 00:55 UTC | View → |
| Kalshi | — | — | — | 16:30 UTC | View → |
| Kalshi | — | — | — | 14:27 UTC | View → |
| Kalshi | — | — | — | 21:58 UTC | View → |
| Kalshi | — | — | — | 18:03 UTC | View → |
| Kalshi | — | — | — | 14:38 UTC | View → |
| Kalshi | — | — | — | 23:14 UTC | View → |
| Kalshi | — | — | — | 20:24 UTC | View → |
| Kalshi | — | — | — | 14:42 UTC | View → |
| Kalshi | — | — | — | 14:41 UTC | View → |
| Kalshi | — | — | — | 14:37 UTC | View → |
| Kalshi | — | — | — | 19:36 UTC | View → |
| Kalshi | — | — | — | 23:15 UTC | View → |
| Kalshi | — | — | — | 16:30 UTC | View → |
| Kalshi | — | — | — | 23:12 UTC | View → |
| Kalshi | — | — | — | 01:12 UTC | View → |
| Kalshi | — | — | — | 13:55 UTC | View → |
| Kalshi | — | — | — | 18:07 UTC | View → |
| Kalshi | — | — | — | 18:36 UTC | View → |
| Kalshi | — | — | — | 18:45 UTC | View → |
| Kalshi | — | — | — | 19:31 UTC | View → |
| Kalshi | — | — | — | 00:01 UTC | View → |
| Kalshi | — | — | — | 14:53 UTC | View → |
| Kalshi | — | — | — | 16:10 UTC | View → |
| Kalshi | — | — | — | 20:29 UTC | View → |
| Kalshi | — | — | — | 00:28 UTC | View → |
| Kalshi | — | — | — | 21:16 UTC | View → |
| Kalshi | — | — | — | 23:02 UTC | View → |
| Kalshi | — | — | — | 16:50 UTC | View → |
| Kalshi | — | — | — | 20:27 UTC | View → |
| Kalshi | — | — | — | 16:09 UTC | View → |
| Kalshi | — | — | — | 15:31 UTC | View → |
| Kalshi | — | — | — | 15:29 UTC | View → |
| Kalshi | — | — | — | 20:27 UTC | View → |
| Kalshi | — | — | — | 23:02 UTC | View → |
| Kalshi | — | — | — | 15:52 UTC | View → |
| Kalshi | — | — | — | 14:53 UTC | View → |
| Kalshi | — | — | — | 23:11 UTC | View → |
| Kalshi | — | — | — | 21:33 UTC | View → |
| Kalshi | — | — | — | 23:47 UTC | View → |
| Kalshi | — | — | — | 23:44 UTC | View → |
| Kalshi | — | — | — | 19:49 UTC | View → |
| Kalshi | — | — | — | 14:52 UTC | View → |
| Kalshi | — | — | — | 00:01 UTC | View → |
| Kalshi | — | — | — | 23:50 UTC | View → |
| Kalshi | — | — | — | 16:11 UTC | View → |
| Kalshi | — | — | — | 14:53 UTC | View → |
| Kalshi | — | — | — | 14:53 UTC | View → |
| Kalshi | — | — | — | 00:29 UTC | View → |
| Kalshi | — | — | — | 20:54 UTC | View → |
| Kalshi | — | — | — | 16:10 UTC | View → |
| Kalshi | — | — | — | 23:59 UTC | View → |
| Kalshi | — | — | — | 17:38 UTC | View → |
| Kalshi | — | — | — | 23:49 UTC | View → |
| Kalshi | — | — | — | 17:36 UTC | View → |
| Kalshi | — | — | — | 14:53 UTC | View → |
| Kalshi | — | — | — | 14:53 UTC | View → |
| Kalshi | — | — | — | 21:59 UTC | View → |
What do these odds mean?
Cross-platform data for yes Kyle Kuzma: 10+,yes Myles Turner: 10+,yes De'Aaron Fox: 10+,yes Alperen Sengun: 15+,yes Cameron Johnson: 10+,yes Paolo Banchero: 20+ 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.