yes Detroit,yes Cincinnati,no Over 9.5 runs scored
| Platform | Yes | No | Volume | Last seen | Link |
|---|---|---|---|---|---|
| Kalshi | — | — | — | 16:06 UTC | View → |
| Kalshi | — | — | — | 18:34 UTC | View → |
| Kalshi | — | — | — | 23:07 UTC | View → |
| Kalshi | — | — | — | 20:43 UTC | View → |
| Kalshi | — | — | — | 16:31 UTC | View → |
| Kalshi | — | — | — | 20:49 UTC | View → |
| Kalshi | — | — | — | 20:35 UTC | View → |
| Kalshi | — | — | — | 07:16 UTC | View → |
| Kalshi | — | — | — | 19:40 UTC | View → |
| Kalshi | — | — | — | 20:50 UTC | View → |
| Kalshi | — | — | — | 21:51 UTC | View → |
| Kalshi | — | — | — | 14:54 UTC | View → |
| Kalshi | — | — | — | 07:05 UTC | View → |
| Kalshi | — | — | — | 06:42 UTC | View → |
| Kalshi | — | — | — | 19:45 UTC | View → |
| Kalshi | — | — | — | 23:52 UTC | View → |
| Kalshi | — | — | — | 19:19 UTC | View → |
| Kalshi | — | — | — | 18:01 UTC | View → |
| Kalshi | — | — | — | 07:13 UTC | View → |
| Kalshi | — | — | — | 07:13 UTC | View → |
| Kalshi | — | — | — | 05:12 UTC | View → |
| Kalshi | — | — | — | 05:12 UTC | View → |
| Kalshi | — | — | — | 20:43 UTC | View → |
| Kalshi | — | — | — | 21:24 UTC | View → |
| Kalshi | — | — | — | 19:32 UTC | View → |
| Kalshi | — | — | — | 21:12 UTC | View → |
| Kalshi | — | — | — | 22:42 UTC | View → |
| Kalshi | — | — | — | 17:10 UTC | View → |
| Kalshi | — | — | — | 05:38 UTC | View → |
| Kalshi | — | — | — | 20:49 UTC | View → |
| Kalshi | — | — | — | 23:04 UTC | View → |
| Kalshi | — | — | — | 20:49 UTC | View → |
| Kalshi | — | — | — | 22:16 UTC | View → |
| Kalshi | — | — | — | 22:12 UTC | View → |
| Kalshi | — | — | — | 23:36 UTC | View → |
| Kalshi | — | — | — | 05:42 UTC | View → |
| Kalshi | — | — | — | 08:39 UTC | View → |
| Kalshi | — | — | — | 16:57 UTC | View → |
| Kalshi | — | — | — | 23:46 UTC | View → |
| Kalshi | — | — | — | 17:10 UTC | View → |
| Kalshi | — | — | — | 21:48 UTC | View → |
| Kalshi | — | — | — | 16:21 UTC | View → |
| Kalshi | — | — | — | 19:26 UTC | View → |
| Kalshi | — | — | — | 21:30 UTC | View → |
| Kalshi | — | — | — | 08:41 UTC | View → |
| Kalshi | — | — | — | 22:00 UTC | View → |
| Kalshi | — | — | — | 22:41 UTC | View → |
| Kalshi | — | — | — | 22:37 UTC | View → |
| Kalshi | — | — | — | 22:06 UTC | View → |
| Kalshi | — | — | — | 12:18 UTC | View → |
| Kalshi | — | — | — | 00:15 UTC | View → |
| Kalshi | — | — | — | 21:48 UTC | View → |
| Kalshi | — | — | — | 23:31 UTC | View → |
| Kalshi | — | — | — | 23:02 UTC | View → |
| Kalshi | — | — | — | 23:23 UTC | View → |
| Kalshi | — | — | — | 18:27 UTC | View → |
| Kalshi | — | — | — | 10:35 UTC | View → |
| Kalshi | — | — | — | 16:16 UTC | View → |
| Kalshi | — | — | — | 18:47 UTC | View → |
| Kalshi | — | — | — | 17:07 UTC | View → |
| Kalshi | — | — | — | 22:08 UTC | View → |
| Kalshi | — | — | — | 16:09 UTC | View → |
| Kalshi | — | — | — | 21:12 UTC | View → |
| Kalshi | — | — | — | 16:23 UTC | View → |
| Kalshi | — | — | — | 17:10 UTC | View → |
| Kalshi | — | — | — | 05:42 UTC | View → |
| Kalshi | — | — | — | 19:19 UTC | View → |
| Kalshi | — | — | — | 21:04 UTC | View → |
| Kalshi | — | — | — | 10:35 UTC | View → |
| Kalshi | — | — | — | 21:13 UTC | View → |
| Kalshi | — | — | — | 22:37 UTC | View → |
| Kalshi | — | — | — | 19:32 UTC | View → |
| Kalshi | — | — | — | 16:16 UTC | View → |
What do these odds mean?
Cross-platform data for yes Detroit,yes Cincinnati,no Over 9.5 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.