yes Stephen Curry: 20+,yes Kawhi Leonard: 25+,yes Kevin Durant: 20+,yes Dillon Brooks: 10+,yes Over 204.5 points scored
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 17:57 UTC | View → |
| Kalshi | — | — | — | 17:57 UTC | View → |
| Kalshi | — | — | — | 19:02 UTC | View → |
| Kalshi | — | — | — | 17:00 UTC | View → |
| Kalshi | — | — | — | 01:41 UTC | View → |
| Kalshi | — | — | — | 01:42 UTC | View → |
| Kalshi | — | — | — | 19:27 UTC | View → |
| Kalshi | — | — | — | 01:44 UTC | View → |
| Kalshi | — | — | — | 02:06 UTC | View → |
| Kalshi | — | — | — | 21:49 UTC | View → |
| Kalshi | — | — | — | 16:59 UTC | View → |
| Kalshi | — | — | — | 17:00 UTC | View → |
| Kalshi | — | — | — | 02:03 UTC | View → |
| Kalshi | — | — | — | 20:19 UTC | View → |
| Kalshi | — | — | — | 20:19 UTC | View → |
| Kalshi | — | — | — | 01:20 UTC | View → |
| Kalshi | — | — | — | 01:01 UTC | View → |
| Kalshi | — | — | — | 19:27 UTC | View → |
| Kalshi | — | — | — | 02:39 UTC | View → |
| Kalshi | — | — | — | 02:07 UTC | View → |
| Kalshi | — | — | — | 01:45 UTC | View → |
| Kalshi | — | — | — | 01:11 UTC | View → |
| Kalshi | — | — | — | 01:19 UTC | View → |
| Kalshi | — | — | — | 02:02 UTC | View → |
| Kalshi | — | — | — | 02:02 UTC | View → |
| Kalshi | — | — | — | 17:59 UTC | View → |
| Kalshi | — | — | — | 01:19 UTC | View → |
| Kalshi | — | — | — | 02:03 UTC | View → |
| Kalshi | — | — | — | 22:45 UTC | View → |
| Kalshi | — | — | — | 02:25 UTC | View → |
| Kalshi | — | — | — | 01:18 UTC | View → |
| Kalshi | — | — | — | 18:45 UTC | View → |
| Kalshi | — | — | — | 02:06 UTC | View → |
| Kalshi | — | — | — | 04:36 UTC | View → |
| Kalshi | — | — | — | 01:57 UTC | View → |
| Kalshi | — | — | — | 02:05 UTC | View → |
| Kalshi | — | — | — | 02:00 UTC | View → |
| Kalshi | — | — | — | 02:36 UTC | View → |
| Kalshi | — | — | — | 01:20 UTC | View → |
| Kalshi | — | — | — | 02:16 UTC | View → |
| Kalshi | — | — | — | 21:33 UTC | View → |
| Kalshi | — | — | — | 16:57 UTC | View → |
| Kalshi | — | — | — | 12:22 UTC | View → |
| Kalshi | — | — | — | 01:45 UTC | View → |
| Kalshi | — | — | — | 00:39 UTC | View → |
| Kalshi | — | — | — | 01:19 UTC | View → |
| Kalshi | — | — | — | 02:16 UTC | View → |
| Kalshi | — | — | — | 01:20 UTC | View → |
| Kalshi | — | — | — | 01:30 UTC | View → |
| Kalshi | — | — | — | 01:18 UTC | View → |
| Kalshi | — | — | — | 02:05 UTC | View → |
| Kalshi | — | — | — | 02:04 UTC | View → |
| Kalshi | — | — | — | 01:04 UTC | View → |
| Kalshi | — | — | — | 00:43 UTC | View → |
| Kalshi | — | — | — | 02:23 UTC | View → |
| Kalshi | — | — | — | 10:21 UTC | View → |
| Kalshi | — | — | — | 01:58 UTC | View → |
| Kalshi | — | — | — | 02:06 UTC | View → |
| Kalshi | — | — | — | 02:32 UTC | View → |
| Kalshi | — | — | — | 00:55 UTC | View → |
| Kalshi | — | — | — | 17:30 UTC | View → |
| Kalshi | — | — | — | 22:24 UTC | View → |
| Kalshi | — | — | — | 17:23 UTC | View → |
| Kalshi | — | — | — | 01:23 UTC | View → |
| Kalshi | — | — | — | 01:50 UTC | View → |
| Kalshi | — | — | — | 10:17 UTC | View → |
| Kalshi | — | — | — | 10:17 UTC | View → |
| Kalshi | — | — | — | 08:35 UTC | View → |
| Kalshi | — | — | — | 10:17 UTC | View → |
| Kalshi | — | — | — | 02:25 UTC | View → |
| Kalshi | — | — | — | 22:56 UTC | View → |
| Kalshi | — | — | — | 01:25 UTC | View → |
| Kalshi | — | — | — | 01:26 UTC | View → |
| Kalshi | — | — | — | 01:38 UTC | View → |
| Kalshi | — | — | — | 23:40 UTC | View → |
| Kalshi | — | — | — | 00:41 UTC | View → |
| Kalshi | — | — | — | 23:40 UTC | View → |
| Kalshi | — | — | — | 02:25 UTC | View → |
| Kalshi | — | — | — | 01:56 UTC | View → |
| Kalshi | — | — | — | 02:23 UTC | View → |
| Kalshi | — | — | — | 01:58 UTC | View → |
| Kalshi | — | — | — | 01:00 UTC | View → |
| Kalshi | — | — | — | 22:16 UTC | View → |
| Kalshi | — | — | — | 01:12 UTC | View → |
| Kalshi | — | — | — | 23:40 UTC | View → |
| Kalshi | — | — | — | 20:51 UTC | View → |
| Kalshi | — | — | — | 01:42 UTC | View → |
| Kalshi | — | — | — | 02:40 UTC | View → |
| Kalshi | — | — | — | 01:57 UTC | View → |
| Kalshi | — | — | — | 02:23 UTC | View → |
| Kalshi | — | — | — | 02:02 UTC | View → |
| Kalshi | — | — | — | 00:56 UTC | View → |
| Kalshi | — | — | — | 22:13 UTC | View → |
| Kalshi | — | — | — | 02:12 UTC | View → |
| Kalshi | — | — | — | 00:42 UTC | View → |
| Kalshi | — | — | — | 23:45 UTC | View → |
| Kalshi | — | — | — | 20:13 UTC | View → |
| Kalshi | — | — | — | 01:59 UTC | View → |
| Kalshi | — | — | — | 01:49 UTC | View → |
| Kalshi | — | — | — | 01:27 UTC | View → |
| Kalshi | — | — | — | 02:26 UTC | View → |
| Kalshi | — | — | — | 02:22 UTC | View → |
| Kalshi | — | — | — | 17:29 UTC | View → |
| Kalshi | — | — | — | 17:31 UTC | View → |
| Kalshi | — | — | — | 00:56 UTC | View → |
| Kalshi | — | — | — | 22:42 UTC | View → |
| Kalshi | — | — | — | 01:33 UTC | View → |
| Kalshi | — | — | — | 00:42 UTC | View → |
| Kalshi | — | — | — | 00:07 UTC | View → |
| Kalshi | — | — | — | 00:44 UTC | View → |
| Kalshi | — | — | — | 22:48 UTC | View → |
| Kalshi | — | — | — | 18:57 UTC | View → |
| Kalshi | — | — | — | 02:06 UTC | View → |
| Kalshi | — | — | — | 02:03 UTC | View → |
| Kalshi | — | — | — | 18:18 UTC | View → |
| Kalshi | — | — | — | 01:25 UTC | View → |
| Kalshi | — | — | — | 01:57 UTC | View → |
| Kalshi | — | — | — | 20:52 UTC | View → |
| Kalshi | — | — | — | 02:03 UTC | View → |
| Kalshi | — | — | — | 01:55 UTC | View → |
| Kalshi | — | — | — | 00:57 UTC | View → |
| Kalshi | — | — | — | 20:49 UTC | View → |
| Kalshi | — | — | — | 20:48 UTC | View → |
| Kalshi | — | — | — | 01:50 UTC | View → |
| Kalshi | — | — | — | 01:48 UTC | View → |
| Kalshi | — | — | — | 02:11 UTC | View → |
| Kalshi | — | — | — | 02:11 UTC | View → |
What do these odds mean?
Cross-platform data for yes Stephen Curry: 20+,yes Kawhi Leonard: 25+,yes Kevin Durant: 20+,yes Dillon Brooks: 10+,yes Over 204.5 points scored 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.