yes Milwaukee,yes Detroit,yes Houston,yes New York,yes LaMelo Ball: 15+
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 07:54 UTC | View → |
| Kalshi | — | — | — | 08:51 UTC | View → |
| Kalshi | — | — | — | 21:49 UTC | View → |
| Kalshi | — | — | — | 07:55 UTC | View → |
| Kalshi | — | — | — | 13:13 UTC | View → |
| Kalshi | — | — | — | 12:51 UTC | View → |
| Kalshi | — | — | — | 00:16 UTC | View → |
| Kalshi | — | — | — | 16:48 UTC | View → |
| Kalshi | — | — | — | 18:50 UTC | View → |
| Kalshi | — | — | — | 23:00 UTC | View → |
| Kalshi | — | — | — | 00:08 UTC | View → |
| Kalshi | — | — | — | 00:35 UTC | View → |
| Kalshi | — | — | — | 23:40 UTC | View → |
| Kalshi | — | — | — | 18:50 UTC | View → |
| Kalshi | — | — | — | 00:07 UTC | View → |
| Kalshi | — | — | — | 23:39 UTC | View → |
| Kalshi | — | — | — | 12:51 UTC | View → |
| Kalshi | — | — | — | 10:59 UTC | View → |
| Kalshi | — | — | — | 08:51 UTC | View → |
| Kalshi | — | — | — | 10:58 UTC | View → |
| Kalshi | — | — | — | 08:51 UTC | View → |
| Kalshi | — | — | — | 07:20 UTC | View → |
| Kalshi | — | — | — | 13:06 UTC | View → |
| Kalshi | — | — | — | 01:02 UTC | View → |
| Kalshi | — | — | — | 20:49 UTC | View → |
| Kalshi | — | — | — | 01:03 UTC | View → |
| Kalshi | — | — | — | 08:42 UTC | View → |
| Kalshi | — | — | — | 07:59 UTC | View → |
| Kalshi | — | — | — | 08:41 UTC | View → |
| Kalshi | — | — | — | 18:54 UTC | View → |
| Kalshi | — | — | — | 09:43 UTC | View → |
| Kalshi | — | — | — | 07:06 UTC | View → |
| Kalshi | — | — | — | 09:43 UTC | View → |
| Kalshi | — | — | — | 22:50 UTC | View → |
| Kalshi | — | — | — | 00:42 UTC | View → |
| Kalshi | — | — | — | 13:35 UTC | View → |
| Kalshi | — | — | — | 15:12 UTC | View → |
| Kalshi | — | — | — | 15:07 UTC | View → |
| Kalshi | — | — | — | 07:16 UTC | View → |
| Kalshi | — | — | — | 14:44 UTC | View → |
| Kalshi | — | — | — | 08:42 UTC | View → |
| Kalshi | — | — | — | 22:50 UTC | View → |
| Kalshi | — | — | — | 13:01 UTC | View → |
| Kalshi | — | — | — | 12:53 UTC | View → |
| Kalshi | — | — | — | 22:46 UTC | View → |
| Kalshi | — | — | — | 07:13 UTC | View → |
| Kalshi | — | — | — | 21:03 UTC | View → |
| Kalshi | — | — | — | 07:15 UTC | View → |
| Kalshi | — | — | — | 09:45 UTC | View → |
| Kalshi | — | — | — | 08:41 UTC | View → |
| Kalshi | — | — | — | 09:53 UTC | View → |
| Kalshi | — | — | — | 16:41 UTC | View → |
| Kalshi | — | — | — | 17:40 UTC | View → |
| Kalshi | — | — | — | 08:12 UTC | View → |
| Kalshi | — | — | — | 18:22 UTC | View → |
| Kalshi | — | — | — | 09:20 UTC | View → |
| Kalshi | — | — | — | 07:53 UTC | View → |
| Kalshi | — | — | — | 18:46 UTC | View → |
| Kalshi | — | — | — | 07:15 UTC | View → |
| Kalshi | — | — | — | 13:45 UTC | View → |
| Kalshi | — | — | — | 08:06 UTC | View → |
| Kalshi | — | — | — | 01:04 UTC | View → |
| Kalshi | — | — | — | 08:39 UTC | View → |
| Kalshi | — | — | — | 00:42 UTC | View → |
| Kalshi | — | — | — | 17:14 UTC | View → |
| Kalshi | — | — | — | 20:49 UTC | View → |
| Kalshi | — | — | — | 08:45 UTC | View → |
| Kalshi | — | — | — | 23:17 UTC | View → |
| Kalshi | — | — | — | 18:27 UTC | View → |
| Kalshi | — | — | — | 09:43 UTC | View → |
| Kalshi | — | — | — | 17:48 UTC | View → |
| Kalshi | — | — | — | 19:20 UTC | View → |
What do these odds mean?
Cross-platform data for yes Milwaukee,yes Detroit,yes Houston,yes New York,yes LaMelo Ball: 15+ 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.