| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Colt Keith: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Colt Keith: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Dillon Dingler: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Dillon Dingler: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Fernando Tatis Jr.: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Fernando Tatis Jr.: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Freddy Fermin: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Gleyber Torres: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Gleyber Torres: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Jackson Merrill: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Jackson Merrill: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Jake Cronenworth: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Jake Cronenworth: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Javier Báez: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Javier Báez: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Kerry Carpenter: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Kerry Carpenter: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Manny Machado: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Manny Machado: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Miguel Andujar: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Miguel Andujar: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Nick Castellanos: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Nick Castellanos: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Parker Meadows: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Parker Meadows: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Ramón Laureano: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Ramón Laureano: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Riley Greene: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Riley Greene: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Spencer Torkelson: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Spencer Torkelson: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Xander Bogaerts: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Xander Bogaerts: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Gavin Sheets: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Gavin Sheets: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Kevin McGonigle: 1+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| Kevin McGonigle: 2+ | 0% | 0¢ | 0¢ | — | $0 | Trade → |
This market lets traders take positions on the number of home runs hit in the Detroit vs San Diego game; it matters because home-run outcomes are a major driver of scoring and can move markets quickly as pregame information changes.
Detroit and San Diego bring different park profiles, lineups, and pitching staffs that historically influence how often the ball leaves the park. Recent MLB-wide trends and team roster construction also affect home-run frequency, but single-game outcomes remain highly sensitive to matchup- and weather-specific details.
Market prices reflect the crowd’s aggregated view of these factors and update as new information arrives; use them as a real-time signal rather than a fixed forecast and watch for shifts when starting lineups, weather, or pitching plans change.
Starting pitchers set the baseline: pitchers who allow more fly balls or have higher home-run-per-flyball rates increase expected home runs, while power pitchers and those who induce grounders lower it; markets update as starters are confirmed or changed.
Park factors matter: some parks historically suppress home runs and others are more favorable to power hitting; consider fence distances, typical wind patterns, and how each park has performed on similar days when weighing outcomes.
Key movers include late scratches or lineup changes for power hitters, unexpected starter swaps, injury reports, and weather-forecast revisions—each can materially change expected home-run totals and prompt market adjustment.
A shift to windy, warm, or dry conditions that blow out can increase the chance of home runs, while cold, damp, or onshore wind conditions typically reduce carry; live markets react quickly to observed game-time conditions.
Head-to-head history can offer context, especially about specific pitcher-hitter matchups and park outcomes, but it’s often limited by small sample sizes and roster turnover, so weigh it alongside current pitcher metrics, lineups, and game conditions.