yes San Diego,yes Milwaukee,yes San Antonio,yes Miami,yes Boston,yes Orlando,yes Philadelphia
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 16:35 UTC | View → |
| Kalshi | — | — | — | 22:53 UTC | View → |
| Kalshi | — | — | — | 16:35 UTC | View → |
| Kalshi | — | — | — | 14:55 UTC | View → |
| Kalshi | — | — | — | 05:31 UTC | View → |
| Kalshi | — | — | — | 05:24 UTC | View → |
| Kalshi | — | — | — | 05:25 UTC | View → |
| Kalshi | — | — | — | 10:32 UTC | View → |
| Kalshi | — | — | — | 05:24 UTC | View → |
| Kalshi | — | — | — | 14:30 UTC | View → |
| Kalshi | — | — | — | 15:44 UTC | View → |
| Kalshi | — | — | — | 16:35 UTC | View → |
| Kalshi | — | — | — | 15:40 UTC | View → |
| Kalshi | — | — | — | 10:32 UTC | View → |
| Kalshi | — | — | — | 14:30 UTC | View → |
| Kalshi | — | — | — | 22:33 UTC | View → |
| Kalshi | — | — | — | 09:30 UTC | View → |
| Kalshi | — | — | — | 05:24 UTC | View → |
| Kalshi | — | — | — | 05:31 UTC | View → |
| Kalshi | — | — | — | 08:04 UTC | View → |
| Kalshi | — | — | — | 01:04 UTC | View → |
| Kalshi | — | — | — | 16:27 UTC | View → |
| Kalshi | — | — | — | 18:49 UTC | View → |
| Kalshi | — | — | — | 21:40 UTC | View → |
| Kalshi | — | — | — | 16:51 UTC | View → |
| Kalshi | — | — | — | 08:12 UTC | View → |
| Kalshi | — | — | — | 19:44 UTC | View → |
| Kalshi | — | — | — | 13:16 UTC | View → |
| Kalshi | — | — | — | 12:15 UTC | View → |
| Kalshi | — | — | — | 17:08 UTC | View → |
| Kalshi | — | — | — | 21:36 UTC | View → |
| Kalshi | — | — | — | 19:25 UTC | View → |
| Kalshi | — | — | — | 19:25 UTC | View → |
What do these odds mean?
Cross-platform data for yes San Diego,yes Milwaukee,yes San Antonio,yes Miami,yes Boston,yes Orlando,yes Philadelphia 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.