yes James Harden: 1+,yes Darius Garland: 1+,yes Tyrese Maxey: 1+,yes Miami
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 08:52 UTC | View → |
| Kalshi | — | — | — | 12:57 UTC | View → |
| Kalshi | — | — | — | 18:32 UTC | View → |
| Kalshi | — | — | — | 09:55 UTC | View → |
| Kalshi | — | — | — | 12:44 UTC | View → |
| Kalshi | — | — | — | 09:09 UTC | View → |
| Kalshi | — | — | — | 17:28 UTC | View → |
| Kalshi | — | — | — | 18:31 UTC | View → |
| Kalshi | — | — | — | 08:08 UTC | View → |
| Kalshi | — | — | — | 17:26 UTC | View → |
| Kalshi | — | — | — | 12:11 UTC | View → |
| Kalshi | — | — | — | 22:23 UTC | View → |
| Kalshi | — | — | — | 09:55 UTC | View → |
| Kalshi | — | — | — | 23:02 UTC | View → |
| Kalshi | — | — | — | 13:18 UTC | View → |
| Kalshi | — | — | — | 15:11 UTC | View → |
| Kalshi | — | — | — | 22:40 UTC | View → |
| Kalshi | — | — | — | 13:22 UTC | View → |
| Kalshi | — | — | — | 08:52 UTC | View → |
| Kalshi | — | — | — | 21:02 UTC | View → |
| Kalshi | — | — | — | 14:16 UTC | View → |
| Kalshi | — | — | — | 12:46 UTC | View → |
| Kalshi | — | — | — | 09:55 UTC | View → |
| Kalshi | — | — | — | 14:17 UTC | View → |
| Kalshi | — | — | — | 23:12 UTC | View → |
| Kalshi | — | — | — | 17:27 UTC | View → |
| Kalshi | — | — | — | 10:34 UTC | View → |
| Kalshi | — | — | — | 08:56 UTC | View → |
| Kalshi | — | — | — | 14:02 UTC | View → |
| Kalshi | — | — | — | 19:17 UTC | View → |
| Kalshi | — | — | — | 10:34 UTC | View → |
| Kalshi | — | — | — | 16:27 UTC | View → |
| Kalshi | — | — | — | 12:46 UTC | View → |
| Kalshi | — | — | — | 10:35 UTC | View → |
| Kalshi | — | — | — | 10:13 UTC | View → |
| Kalshi | — | — | — | 14:02 UTC | View → |
| Kalshi | — | — | — | 17:55 UTC | View → |
| Kalshi | — | — | — | 10:34 UTC | View → |
| Kalshi | — | — | — | 10:34 UTC | View → |
| Kalshi | — | — | — | 09:03 UTC | View → |
| Kalshi | — | — | — | 11:36 UTC | View → |
| Kalshi | — | — | — | 11:36 UTC | View → |
| Kalshi | — | — | — | 13:36 UTC | View → |
| Kalshi | — | — | — | 15:31 UTC | View → |
| Kalshi | — | — | — | 15:31 UTC | View → |
| Kalshi | — | — | — | 18:09 UTC | View → |
| Kalshi | — | — | — | 10:13 UTC | View → |
| Kalshi | — | — | — | 10:13 UTC | View → |
| Kalshi | — | — | — | 15:32 UTC | View → |
| Kalshi | — | — | — | 15:33 UTC | View → |
| Kalshi | — | — | — | 10:18 UTC | View → |
| Kalshi | — | — | — | 23:40 UTC | View → |
| Kalshi | — | — | — | 12:51 UTC | View → |
| Kalshi | — | — | — | 09:07 UTC | View → |
| Kalshi | — | — | — | 10:42 UTC | View → |
| Kalshi | — | — | — | 11:34 UTC | View → |
| Kalshi | — | — | — | 17:58 UTC | View → |
| Kalshi | — | — | — | 16:28 UTC | View → |
| Kalshi | — | — | — | 17:35 UTC | View → |
| Kalshi | — | — | — | 12:38 UTC | View → |
| Kalshi | — | — | — | 00:08 UTC | View → |
| Kalshi | — | — | — | 10:34 UTC | View → |
| Kalshi | — | — | — | 17:33 UTC | View → |
| Kalshi | — | — | — | 12:50 UTC | View → |
| Kalshi | — | — | — | 12:38 UTC | View → |
| Kalshi | — | — | — | 09:01 UTC | View → |
| Kalshi | — | — | — | 19:05 UTC | View → |
| Kalshi | — | — | — | 19:13 UTC | View → |
| Kalshi | — | — | — | 10:34 UTC | View → |
| Kalshi | — | — | — | 08:56 UTC | View → |
| Kalshi | — | — | — | 10:34 UTC | View → |
| Kalshi | — | — | — | 10:12 UTC | View → |
| Kalshi | — | — | — | 21:46 UTC | View → |
| Kalshi | — | — | — | 17:29 UTC | View → |
| Kalshi | — | — | — | 12:47 UTC | View → |
| Kalshi | — | — | — | 10:34 UTC | View → |
| Kalshi | — | — | — | 19:08 UTC | View → |
| Kalshi | — | — | — | 15:31 UTC | View → |
What do these odds mean?
Cross-platform data for yes James Harden: 1+,yes Darius Garland: 1+,yes Tyrese Maxey: 1+,yes Miami 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.