yes Carlos Alcaraz,yes Atlanta,yes San Antonio,yes Charlotte,yes Golden State,yes Los Angeles C,yes Utah,yes Miami,yes Houston,yes Boston,yes Orlando,yes New York
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 06:05 UTC | View → |
| Kalshi | — | — | — | 08:37 UTC | View → |
| Kalshi | — | — | — | 18:24 UTC | View → |
| Kalshi | — | — | — | 05:56 UTC | View → |
| Kalshi | — | — | — | 13:49 UTC | View → |
| Kalshi | — | — | — | 06:22 UTC | View → |
| Kalshi | — | — | — | 12:15 UTC | View → |
| Kalshi | — | — | — | 05:51 UTC | View → |
| Kalshi | — | — | — | 04:29 UTC | View → |
| Kalshi | — | — | — | 13:11 UTC | View → |
| Kalshi | — | — | — | 14:37 UTC | View → |
| Kalshi | — | — | — | 12:55 UTC | View → |
| Kalshi | — | — | — | 14:29 UTC | View → |
| Kalshi | — | — | — | 06:15 UTC | View → |
| Kalshi | — | — | — | 22:31 UTC | View → |
| Kalshi | — | — | — | 14:37 UTC | View → |
| Kalshi | — | — | — | 06:07 UTC | View → |
| Kalshi | — | — | — | 13:17 UTC | View → |
| Kalshi | — | — | — | 12:17 UTC | View → |
| Kalshi | — | — | — | 05:40 UTC | View → |
| Kalshi | — | — | — | 12:17 UTC | View → |
| Kalshi | — | — | — | 13:53 UTC | View → |
| Kalshi | — | — | — | 09:44 UTC | View → |
| Kalshi | — | — | — | 10:52 UTC | View → |
| Kalshi | — | — | — | 10:20 UTC | View → |
| Kalshi | — | — | — | 13:58 UTC | View → |
| Kalshi | — | — | — | 13:46 UTC | View → |
| Kalshi | — | — | — | 14:00 UTC | View → |
| Kalshi | — | — | — | 14:00 UTC | View → |
| Kalshi | — | — | — | 11:31 UTC | View → |
| Kalshi | — | — | — | 11:58 UTC | View → |
| Kalshi | — | — | — | 08:56 UTC | View → |
| Kalshi | — | — | — | 12:53 UTC | View → |
| Kalshi | — | — | — | 13:44 UTC | View → |
| Kalshi | — | — | — | 13:51 UTC | View → |
| Kalshi | — | — | — | 12:21 UTC | View → |
| Kalshi | — | — | — | 05:47 UTC | View → |
| Kalshi | — | — | — | 14:00 UTC | View → |
| Kalshi | — | — | — | 13:19 UTC | View → |
| Kalshi | — | — | — | 13:17 UTC | View → |
| Kalshi | — | — | — | 15:07 UTC | View → |
| Kalshi | — | — | — | 08:56 UTC | View → |
| Kalshi | — | — | — | 14:01 UTC | View → |
| Kalshi | — | — | — | 08:29 UTC | View → |
| Kalshi | — | — | — | 07:38 UTC | View → |
| Kalshi | — | — | — | 09:44 UTC | View → |
| Kalshi | — | — | — | 12:27 UTC | View → |
| Kalshi | — | — | — | 05:20 UTC | View → |
| Kalshi | — | — | — | 11:42 UTC | View → |
| Kalshi | — | — | — | 14:03 UTC | View → |
| Kalshi | — | — | — | 13:57 UTC | View → |
| Kalshi | — | — | — | 11:57 UTC | View → |
| Kalshi | — | — | — | 13:04 UTC | View → |
| Kalshi | — | — | — | 15:07 UTC | View → |
| Kalshi | — | — | — | 10:20 UTC | View → |
| Kalshi | — | — | — | 09:57 UTC | View → |
| Kalshi | — | — | — | 14:23 UTC | View → |
| Kalshi | — | — | — | 09:43 UTC | View → |
| Kalshi | — | — | — | 12:28 UTC | View → |
| Kalshi | — | — | — | 07:10 UTC | View → |
| Kalshi | — | — | — | 15:07 UTC | View → |
| Kalshi | — | — | — | 14:04 UTC | View → |
| Kalshi | — | — | — | 10:57 UTC | View → |
| Kalshi | — | — | — | 08:30 UTC | View → |
| Kalshi | — | — | — | 12:07 UTC | View → |
| Kalshi | — | — | — | 13:59 UTC | View → |
| Kalshi | — | — | — | 12:42 UTC | View → |
| Kalshi | — | — | — | 13:58 UTC | View → |
| Kalshi | — | — | — | 09:44 UTC | View → |
| Kalshi | — | — | — | 12:21 UTC | View → |
| Kalshi | — | — | — | 15:07 UTC | View → |
| Kalshi | — | — | — | 08:28 UTC | View → |
| Kalshi | — | — | — | 14:04 UTC | View → |
What do these odds mean?
Cross-platform data for yes Carlos Alcaraz,yes Atlanta,yes San Antonio,yes Charlotte,yes Golden State,yes Los Angeles C,yes Utah,yes Miami,yes Houston,yes Boston,yes Orlando,yes New York 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.