yes Arizona,yes Over 8.5 runs scored,no Over 8.5 runs scored
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 22:56 UTC | View → |
| Kalshi | — | — | — | 18:22 UTC | View → |
| Kalshi | — | — | — | 19:32 UTC | View → |
| Kalshi | — | — | — | 16:04 UTC | View → |
| Kalshi | — | — | — | 16:23 UTC | View → |
| Kalshi | — | — | — | 21:05 UTC | View → |
| Kalshi | — | — | — | 19:18 UTC | View → |
| Kalshi | — | — | — | 04:28 UTC | View → |
| Kalshi | — | — | — | 12:00 UTC | View → |
| Kalshi | — | — | — | 06:42 UTC | View → |
| Kalshi | — | — | — | 16:21 UTC | View → |
| Kalshi | — | — | — | 01:05 UTC | View → |
| Kalshi | — | — | — | 20:33 UTC | View → |
| Kalshi | — | — | — | 16:40 UTC | View → |
| Kalshi | — | — | — | 05:46 UTC | View → |
| Kalshi | — | — | — | 00:58 UTC | View → |
| Kalshi | — | — | — | 16:35 UTC | View → |
| Kalshi | — | — | — | 06:45 UTC | View → |
| Kalshi | — | — | — | 00:18 UTC | View → |
| Kalshi | — | — | — | 14:22 UTC | View → |
| Kalshi | — | — | — | 05:30 UTC | View → |
| Kalshi | — | — | — | 19:42 UTC | View → |
| Kalshi | — | — | — | 07:41 UTC | View → |
| Kalshi | — | — | — | 16:39 UTC | View → |
| Kalshi | — | — | — | 06:52 UTC | View → |
| Kalshi | — | — | — | 05:32 UTC | View → |
| Kalshi | — | — | — | 00:37 UTC | View → |
| Kalshi | — | — | — | 19:19 UTC | View → |
| Kalshi | — | — | — | 18:35 UTC | View → |
| Kalshi | — | — | — | 08:41 UTC | View → |
| Kalshi | — | — | — | 06:31 UTC | View → |
| Kalshi | — | — | — | 16:10 UTC | View → |
| Kalshi | — | — | — | 00:59 UTC | View → |
| Kalshi | — | — | — | 00:56 UTC | View → |
| Kalshi | — | — | — | 18:36 UTC | View → |
| Kalshi | — | — | — | 01:04 UTC | View → |
| Kalshi | — | — | — | 00:14 UTC | View → |
| Kalshi | — | — | — | 21:19 UTC | View → |
| Kalshi | — | — | — | 01:03 UTC | View → |
| Kalshi | — | — | — | 12:58 UTC | View → |
| Kalshi | — | — | — | 20:45 UTC | View → |
| Kalshi | — | — | — | 20:41 UTC | View → |
| Kalshi | — | — | — | 07:11 UTC | View → |
| Kalshi | — | — | — | 04:36 UTC | View → |
| Kalshi | — | — | — | 08:48 UTC | View → |
| Kalshi | — | — | — | 17:04 UTC | View → |
| Kalshi | — | — | — | 07:22 UTC | View → |
| Kalshi | — | — | — | 11:36 UTC | View → |
| Kalshi | — | — | — | 22:02 UTC | View → |
| Kalshi | — | — | — | 21:07 UTC | View → |
| Kalshi | — | — | — | 18:18 UTC | View → |
| Kalshi | — | — | — | 20:45 UTC | View → |
| Kalshi | — | — | — | 06:58 UTC | View → |
| Kalshi | — | — | — | 08:58 UTC | View → |
| Kalshi | — | — | — | 20:48 UTC | View → |
| Kalshi | — | — | — | 17:02 UTC | View → |
| Kalshi | — | — | — | 13:02 UTC | View → |
| Kalshi | — | — | — | 17:58 UTC | View → |
| Kalshi | — | — | — | 21:37 UTC | View → |
| Kalshi | — | — | — | 02:20 UTC | View → |
| Kalshi | — | — | — | 21:51 UTC | View → |
| Kalshi | — | — | — | 19:45 UTC | View → |
| Kalshi | — | — | — | 02:20 UTC | View → |
| Kalshi | — | — | — | 09:44 UTC | View → |
| Kalshi | — | — | — | 10:21 UTC | View → |
| Kalshi | — | — | — | 22:07 UTC | View → |
| Kalshi | — | — | — | 00:10 UTC | View → |
| Kalshi | — | — | — | 14:21 UTC | View → |
| Kalshi | — | — | — | 20:54 UTC | View → |
| Kalshi | — | — | — | 16:58 UTC | View → |
| Kalshi | — | — | — | 16:59 UTC | View → |
| Kalshi | — | — | — | 22:06 UTC | View → |
| Kalshi | — | — | — | 09:46 UTC | View → |
| Kalshi | — | — | — | 01:01 UTC | View → |
| Kalshi | — | — | — | 18:47 UTC | View → |
| Kalshi | — | — | — | 00:41 UTC | View → |
| Kalshi | — | — | — | 22:21 UTC | View → |
| Kalshi | — | — | — | 20:34 UTC | View → |
| Kalshi | — | — | — | 18:21 UTC | View → |
What do these odds mean?
Cross-platform data for yes Arizona,yes Over 8.5 runs scored,no Over 8.5 runs 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
Your edge calculator
Enter your own probability estimate to see expected value and recommended position size using the Kelly Criterion.