yes Carlos Alcaraz,yes Both Teams To Score,yes Philadelphia,yes Cade Cunningham: 15+,yes OG Anunoby: 15+
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 00:42 UTC | View → |
| Kalshi | — | — | — | 11:14 UTC | View → |
| Kalshi | — | — | — | 00:43 UTC | View → |
| Kalshi | — | — | — | 11:14 UTC | View → |
| Kalshi | — | — | — | 13:44 UTC | View → |
| Kalshi | — | — | — | 09:06 UTC | View → |
| Kalshi | — | — | — | 09:05 UTC | View → |
| Kalshi | — | — | — | 23:53 UTC | View → |
| Kalshi | — | — | — | 09:04 UTC | View → |
| Kalshi | — | — | — | 09:06 UTC | View → |
| Kalshi | — | — | — | 08:57 UTC | View → |
| Kalshi | — | — | — | 09:03 UTC | View → |
| Kalshi | — | — | — | 09:03 UTC | View → |
| Kalshi | — | — | — | 09:06 UTC | View → |
| Kalshi | — | — | — | 08:57 UTC | View → |
| Kalshi | — | — | — | 12:57 UTC | View → |
| Kalshi | — | — | — | 08:24 UTC | View → |
| Kalshi | — | — | — | 09:03 UTC | View → |
| Kalshi | — | — | — | 09:02 UTC | View → |
| Kalshi | — | — | — | 09:06 UTC | View → |
| Kalshi | — | — | — | 09:04 UTC | View → |
| Kalshi | — | — | — | 09:06 UTC | View → |
| Kalshi | — | — | — | 09:03 UTC | View → |
| Kalshi | — | — | — | 09:03 UTC | View → |
| Kalshi | — | — | — | 09:03 UTC | View → |
| Kalshi | — | — | — | 09:05 UTC | View → |
| Kalshi | — | — | — | 13:50 UTC | View → |
| Kalshi | — | — | — | 08:58 UTC | View → |
What do these odds mean?
Cross-platform data for yes Carlos Alcaraz,yes Both Teams To Score,yes Philadelphia,yes Cade Cunningham: 15+,yes OG Anunoby: 15+ 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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