yes Aaron Pico,yes Kelvin Gastelum,yes Christopher Padilla,yes Dominick Reyes,yes Tatiana Suarez
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 10:21 UTC | View → |
| Kalshi | — | — | — | 05:08 UTC | View → |
| Kalshi | — | — | — | 14:50 UTC | View → |
| Kalshi | — | — | — | 10:21 UTC | View → |
| Kalshi | — | — | — | 14:49 UTC | View → |
| Kalshi | — | — | — | 14:50 UTC | View → |
| Kalshi | — | — | — | 13:53 UTC | View → |
| Kalshi | — | — | — | 14:40 UTC | View → |
| Kalshi | — | — | — | 10:21 UTC | View → |
| Kalshi | — | — | — | 14:45 UTC | View → |
| Kalshi | — | — | — | 20:28 UTC | View → |
| Kalshi | — | — | — | 14:31 UTC | View → |
| Kalshi | — | — | — | 16:59 UTC | View → |
| Kalshi | — | — | — | 15:47 UTC | View → |
| Kalshi | — | — | — | 14:14 UTC | View → |
| Kalshi | — | — | — | 23:21 UTC | View → |
| Kalshi | — | — | — | 21:00 UTC | View → |
| Kalshi | — | — | — | 00:22 UTC | View → |
| Kalshi | — | — | — | 00:08 UTC | View → |
| Kalshi | — | — | — | 23:21 UTC | View → |
| Kalshi | — | — | — | 09:21 UTC | View → |
| Kalshi | — | — | — | 16:59 UTC | View → |
| Kalshi | — | — | — | 18:55 UTC | View → |
| Kalshi | — | — | — | 07:05 UTC | View → |
| Kalshi | — | — | — | 12:05 UTC | View → |
| Kalshi | — | — | — | 00:08 UTC | View → |
| Kalshi | — | — | — | 00:14 UTC | View → |
| Kalshi | — | — | — | 05:34 UTC | View → |
| Kalshi | — | — | — | 09:14 UTC | View → |
| Kalshi | — | — | — | 12:05 UTC | View → |
| Kalshi | — | — | — | 18:13 UTC | View → |
| Kalshi | — | — | — | 08:44 UTC | View → |
| Kalshi | — | — | — | 08:44 UTC | View → |
| Kalshi | — | — | — | 00:30 UTC | View → |
| Kalshi | — | — | — | 00:30 UTC | View → |
What do these odds mean?
Cross-platform data for yes Aaron Pico,yes Kelvin Gastelum,yes Christopher Padilla,yes Dominick Reyes,yes Tatiana Suarez 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.