yes Jason Day,yes Patrick Reed,yes Chris Gotterup,yes Gary Woodland,yes Scottie Scheffler
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 17:19 UTC | View → |
| Kalshi | — | — | — | 10:41 UTC | View → |
| Kalshi | — | — | — | 12:12 UTC | View → |
| Kalshi | — | — | — | 20:11 UTC | View → |
| Kalshi | — | — | — | 06:59 UTC | View → |
| Kalshi | — | — | — | 13:42 UTC | View → |
| Kalshi | — | — | — | 16:19 UTC | View → |
| Kalshi | — | — | — | 04:42 UTC | View → |
| Kalshi | — | — | — | 09:08 UTC | View → |
| Kalshi | — | — | — | 08:14 UTC | View → |
| Kalshi | — | — | — | 15:07 UTC | View → |
| Kalshi | — | — | — | 17:39 UTC | View → |
| Kalshi | — | — | — | 10:19 UTC | View → |
| Kalshi | — | — | — | 17:39 UTC | View → |
| Kalshi | — | — | — | 11:09 UTC | View → |
| Kalshi | — | — | — | 14:10 UTC | View → |
| Kalshi | — | — | — | 18:38 UTC | View → |
| Kalshi | — | — | — | 22:15 UTC | View → |
| Kalshi | — | — | — | 11:09 UTC | View → |
| Kalshi | — | — | — | 08:53 UTC | View → |
| Kalshi | — | — | — | 11:33 UTC | View → |
| Kalshi | — | — | — | 21:40 UTC | View → |
| Kalshi | — | — | — | 11:09 UTC | View → |
| Kalshi | — | — | — | 07:42 UTC | View → |
| Kalshi | — | — | — | 10:17 UTC | View → |
| Kalshi | — | — | — | 11:09 UTC | View → |
| Kalshi | — | — | — | 18:02 UTC | View → |
| Kalshi | — | — | — | 19:52 UTC | View → |
| Kalshi | — | — | — | 13:07 UTC | View → |
| Kalshi | — | — | — | 14:41 UTC | View → |
| Kalshi | — | — | — | 21:53 UTC | View → |
| Kalshi | — | — | — | 15:58 UTC | View → |
What do these odds mean?
Cross-platform data for yes Jason Day,yes Patrick Reed,yes Chris Gotterup,yes Gary Woodland,yes Scottie Scheffler 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
Your edge calculator
Enter your own probability estimate to see expected value and recommended position size using the Kelly Criterion.