Model Results
This statistical model produces MLB game predictions using player-level performance forecasts from the proprietary Miñoso Projection System, combined with game-specific projections for plate appearances (batters) and innings pitched (pitchers). First implemented for the 2024 MLB season, the model blends key elements of Joe Peta’s WAR-based approach from Trading Bases with enhancements drawn from leading public projection systems (e.g., ZiPS, Steamer, THE BAT). The result is a customized, data-driven framework for estimating win probabilities for each MLB matchup.
Minoso Model V2 (2024-Present)
2024
Selections:
654
Record:
354-300
Win %:
54.1%
P/L (U):
+22.87u
ROI:
2.74%
Avg Odds:
-112
Post Mortem
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Positives
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Avoidance of team bias (all 30 teams selected at least 6 games)
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Avoidance of HFA bias (49.69% of selections were Home teams)
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20u+ return
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ROI holding at close to 3.00% despite 654 samples
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Negatives/Items to Address
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Off-season testing showed too low an edge threshold was used (2025 will raise)
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Final month performance fall off (-14.43u in September 2024)
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Model did not deal well with constant lineup shifts (2025 will end in August)
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Minoso Model V1 (2023)
2023
Selections:
856
Record:
408-448
Win %:
P/L (U):
47.7%
+8.57u
ROI:
1.00%
Avg Odds:
+112
Post Mortem
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Positives
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Avoidance of team bias (all 30 teams selected at least 7 games)
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The model consistently identified mispriced teams—such as ARI, STL, CIN, and DET—while effectively avoiding market-driven sentiment trends. It generated +10.56 units selecting LAA and +8.09 units fading them.
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Negatives/Items to Address
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Off-season testing showed the edge threshold used was too low, raised for 2024
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Plate appearance & pitching rotation projections alone were not enough to capture impact of player absences on lineups (Proprietary WAR esque valuation metrics used for 2024)
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Model underweighted LIVE Baseruns and consistently miss-valued teams that deviated far from pre-season projections (optimal weighting tested and implemented for 2024)
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