yes Pittsburgh,yes Cincinnati,yes Toronto,yes New York M,yes Tampa Bay,yes Baltimore,yes Giancarlo Stanton: 1+
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 06:37 UTC | View → |
| Kalshi | — | — | — | 08:07 UTC | View → |
| Kalshi | — | — | — | 14:28 UTC | View → |
| Kalshi | — | — | — | 09:47 UTC | View → |
| Kalshi | — | — | — | 16:31 UTC | View → |
| Kalshi | — | — | — | 17:01 UTC | View → |
| Kalshi | — | — | — | 12:13 UTC | View → |
| Kalshi | — | — | — | 06:36 UTC | View → |
| Kalshi | — | — | — | 20:48 UTC | View → |
| Kalshi | — | — | — | 10:55 UTC | View → |
| Kalshi | — | — | — | 07:22 UTC | View → |
| Kalshi | — | — | — | 15:00 UTC | View → |
| Kalshi | — | — | — | 20:49 UTC | View → |
| Kalshi | — | — | — | 15:21 UTC | View → |
| Kalshi | — | — | — | 19:30 UTC | View → |
| Kalshi | — | — | — | 20:10 UTC | View → |
| Kalshi | — | — | — | 10:55 UTC | View → |
| Kalshi | — | — | — | 20:10 UTC | View → |
| Kalshi | — | — | — | 21:05 UTC | View → |
| Kalshi | — | — | — | 14:35 UTC | View → |
| Kalshi | — | — | — | 16:56 UTC | View → |
| Kalshi | — | — | — | 07:16 UTC | View → |
| Kalshi | — | — | — | 20:51 UTC | View → |
| Kalshi | — | — | — | 15:03 UTC | View → |
| Kalshi | — | — | — | 15:02 UTC | View → |
| Kalshi | — | — | — | 10:55 UTC | View → |
What do these odds mean?
Cross-platform data for yes Pittsburgh,yes Cincinnati,yes Toronto,yes New York M,yes Tampa Bay,yes Baltimore,yes Giancarlo Stanton: 1+ 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
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