yes Miami wins by over 1.5 runs,yes Kawhi Leonard: 1+,yes Deni Avdija: 6+,yes John Collins: 10+,yes Donovan Clingan: 10+,yes Toumani Camara: 10+,yes Brook Lopez: 4+,yes Los Angeles C wins by over 4.5 points,yes Over 213.5 points scored
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 06:27 UTC | View → |
| Kalshi | — | — | — | 09:08 UTC | View → |
| Kalshi | — | — | — | 17:15 UTC | View → |
| Kalshi | — | — | — | 20:47 UTC | View → |
| Kalshi | — | — | — | 21:06 UTC | View → |
| Kalshi | — | — | — | 22:31 UTC | View → |
| Kalshi | — | — | — | 09:05 UTC | View → |
| Kalshi | — | — | — | 06:23 UTC | View → |
| Kalshi | — | — | — | 14:09 UTC | View → |
| Kalshi | — | — | — | 05:07 UTC | View → |
| Kalshi | — | — | — | 14:09 UTC | View → |
| Kalshi | — | — | — | 22:28 UTC | View → |
| Kalshi | — | — | — | 06:49 UTC | View → |
| Kalshi | — | — | — | 21:27 UTC | View → |
| Kalshi | — | — | — | 18:51 UTC | View → |
| Kalshi | — | — | — | 05:04 UTC | View → |
| Kalshi | — | — | — | 05:05 UTC | View → |
| Kalshi | — | — | — | 09:11 UTC | View → |
| Kalshi | — | — | — | 05:04 UTC | View → |
| Kalshi | — | — | — | 05:10 UTC | View → |
What do these odds mean?
Cross-platform data for yes Miami wins by over 1.5 runs,yes Kawhi Leonard: 1+,yes Deni Avdija: 6+,yes John Collins: 10+,yes Donovan Clingan: 10+,yes Toumani Camara: 10+,yes Brook Lopez: 4+,yes Los Angeles C wins by over 4.5 points,yes Over 213.5 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.
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