Major League Baseball predictions for Tuesday, September 1, 2026
Model win probabilities and confidence tiers for every Major League Baseball game on Tuesday, September 1, 2026, published before first pitch, tip or kick and graded automatically afterwards. Research and analytics only, not betting advice.
Major League Baseball matchups and model calls
- lossSeattle Mariners at Boston Red SoxModel call: Boston Red Sox (70% confidence, Strong) · Final 9-6
- winDetroit Tigers at Minnesota TwinsModel call: Minnesota Twins (70% confidence, Strong) · Final 2-15
- winSan Francisco Giants at Pittsburgh PiratesModel call: Pittsburgh Pirates (70% confidence, Strong) · Final 12-13
- winToronto Blue Jays at Cleveland GuardiansModel call: Cleveland Guardians (70% confidence, Strong) · Final 1-6
- PendingAthletics at Texas RangersModel call: Texas Rangers (70% confidence, Strong) · 12:05 AM UTC
- winNew York Mets at Tampa Bay RaysNo published call, model passed on this game · Final 2-6
- PassSt. Louis Cardinals at Los Angeles DodgersNo published call, model passed on this game · 2:10 AM UTC
- PassNew York Yankees at Los Angeles AngelsNo published call, model passed on this game · 1:38 AM UTC
- PassBaltimore Orioles at Colorado RockiesNo published call, model passed on this game · 12:40 AM UTC
- winSan Diego Padres at Cincinnati RedsNo published call, model passed on this game · Final 3-4
- winAtlanta Braves at Washington NationalsNo published call, model passed on this game · Final 5-9
- PassChicago White Sox at Houston AstrosNo published call, model passed on this game · 12:10 AM UTC
- lossMiami Marlins at Kansas City RoyalsNo published call, model passed on this game · Final 6-3
- PassMilwaukee Brewers at Chicago CubsNo published call, model passed on this game · 11:40 PM UTC
- PassPhiladelphia Phillies at Arizona DiamondbacksNo published call, model passed on this game · 1:40 AM UTC
How these Major League Baseball projections are built
Each matchup runs through an ensemble of opponent-adjusted efficiency, recent form, availability of key players, rest and travel, and sport-specific factors. The blended output is calibrated against past results before a confidence tier is assigned, and games below the league publish floor are recorded as a pass instead of a call.
What calibration meansReading the confidence tiers
Lean is a slight model preference, Moderate a clear one, and Strong is reserved for calls clearing both the confidence and edge floors for Major League Baseball. Every tier is graded separately in the public ledger, so you can check whether Strong calls actually outperform Lean calls over a real sample.
Confidence tiers explained