yes Orlando,yes New York,yes LaMelo Ball: 15+,yes Over 208.5 points scored,yes Over 207.5 points scored
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 16:19 UTC | View → |
| Kalshi | — | — | — | 22:12 UTC | View → |
| Kalshi | — | — | — | 04:50 UTC | View → |
| Kalshi | — | — | — | 13:07 UTC | View → |
| Kalshi | — | — | — | 10:57 UTC | View → |
| Kalshi | — | — | — | 05:12 UTC | View → |
| Kalshi | — | — | — | 17:15 UTC | View → |
| Kalshi | — | — | — | 14:29 UTC | View → |
| Kalshi | — | — | — | 06:52 UTC | View → |
| Kalshi | — | — | — | 04:33 UTC | View → |
| Kalshi | — | — | — | 22:36 UTC | View → |
| Kalshi | — | — | — | 04:50 UTC | View → |
| Kalshi | — | — | — | 06:32 UTC | View → |
| Kalshi | — | — | — | 15:00 UTC | View → |
| Kalshi | — | — | — | 12:05 UTC | View → |
| Kalshi | — | — | — | 23:21 UTC | View → |
| Kalshi | — | — | — | 08:42 UTC | View → |
| Kalshi | — | — | — | 04:41 UTC | View → |
| Kalshi | — | — | — | 00:31 UTC | View → |
| Kalshi | — | — | — | 06:02 UTC | View → |
| Kalshi | — | — | — | 05:55 UTC | View → |
| Kalshi | — | — | — | 05:15 UTC | View → |
| Kalshi | — | — | — | 20:09 UTC | View → |
| Kalshi | — | — | — | 05:15 UTC | View → |
| Kalshi | — | — | — | 06:32 UTC | View → |
| Kalshi | — | — | — | 16:17 UTC | View → |
What do these odds mean?
Cross-platform data for yes Orlando,yes New York,yes LaMelo Ball: 15+,yes Over 208.5 points scored,yes Over 207.5 points scored 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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