← PredictionsSan Francisco Giants at Pittsburgh Pirates
Every number here is a probability, not a call. Over the last 14 days the next-pitch model was graded on 34,173 real pitches: the top pick was right 39% of the time, and stated probabilities landed within 1.4 points of how often things actually happened. It grades itself every night and corrects what it can.

Win probability

San Francisco Giants46%
Pittsburgh Pirates54%
Pittsburgh Pirates 54%, give or take 0.6 points of simulation noise · anchored to 115,696 real games in this exact situation, then adjusted for these two teams.

Projected score

4.1 – 4.1expected runs
1–8San Francisco Giants, 80% range
1–8Pittsburgh Pirates, 80% range
8.2total runs
Most likely finals 3–4, 2–3, 1–2 (each under 4%, which is the point: no single score is likely). From 6,000 simulated games.

Starting pitchers

Landen RouppSan Francisco Giants
Innings5.1 3.3–7.0
Strikeouts5.3 3–8
Walks2.6 1–5
Hits allowed4.7 2–8
Home runs0.6 0–2
Runs allowed2.3 0–5
Pitches86 63–110
2+ strikeouts97%
3+ strikeouts91%
4+ strikeouts78%
5+ strikeouts61%
6+ strikeouts44%
7+ strikeouts30%
Jared JonesPittsburgh Pirates
Innings4.8 3.3–6.3
Strikeouts5.1 2–8
Walks1.8 0–4
Hits allowed3.9 2–7
Home runs0.7 0–2
Runs allowed1.9 0–4
Pitches77 56–96
2+ strikeouts97%
3+ strikeouts90%
4+ strikeouts76%
5+ strikeouts58%
6+ strikeouts40%
7+ strikeouts25%
Each figure is the median of the simulated games with an 80% range beside it. Pitch counts are estimated from batters faced (fitted on 17,200 real outings; typical error 8 pitches). These assume the starter is not pulled early for a reason the model cannot see — an injury, a blowout, or a quick hook.

Park and weather

1.00×park
1.00×run environment
What this does not know
Full game page · state as of 20260902_014013