yes Miami,yes Brandon Miller: 4+,yes Atlanta wins by over 7.5 points
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 05:57 UTC | View → |
| Kalshi | — | — | — | 16:39 UTC | View → |
| Kalshi | — | — | — | 16:39 UTC | View → |
| Kalshi | — | — | — | 11:43 UTC | View → |
| Kalshi | — | — | — | 08:30 UTC | View → |
| Kalshi | — | — | — | 11:44 UTC | View → |
| Kalshi | — | — | — | 15:06 UTC | View → |
| Kalshi | — | — | — | 06:13 UTC | View → |
| Kalshi | — | — | — | 08:29 UTC | View → |
| Kalshi | — | — | — | 04:48 UTC | View → |
| Kalshi | — | — | — | 04:48 UTC | View → |
| Kalshi | — | — | — | 05:24 UTC | View → |
| Kalshi | — | — | — | 05:24 UTC | View → |
| Kalshi | — | — | — | 08:11 UTC | View → |
| Kalshi | — | — | — | 13:50 UTC | View → |
| Kalshi | — | — | — | 05:24 UTC | View → |
| Kalshi | — | — | — | 17:22 UTC | View → |
| Kalshi | — | — | — | 08:29 UTC | View → |
| Kalshi | — | — | — | 05:57 UTC | View → |
| Kalshi | — | — | — | 04:48 UTC | View → |
| Kalshi | — | — | — | 14:52 UTC | View → |
| Kalshi | — | — | — | 08:30 UTC | View → |
| Kalshi | — | — | — | 20:38 UTC | View → |
| Kalshi | — | — | — | 16:45 UTC | View → |
| Kalshi | — | — | — | 06:37 UTC | View → |
| Kalshi | — | — | — | 04:40 UTC | View → |
| Kalshi | — | — | — | 23:06 UTC | View → |
| Kalshi | — | — | — | 19:47 UTC | View → |
What do these odds mean?
Cross-platform data for yes Miami,yes Brandon Miller: 4+,yes Atlanta wins by over 7.5 points 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.
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