← PredictionsNew York Mets at Tampa Bay Rays
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

New York Mets39%
Tampa Bay Rays61%
Tampa Bay Rays 61%, 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

3.4 – 4.1expected runs
0–7New York Mets, 80% range
1–8Tampa Bay Rays, 80% range
7.4total runs
Most likely finals 1–2, 3–4, 2–3 (each under 4%, which is the point: no single score is likely). From 6,000 simulated games.

Starting pitchers

Justin HagenmanNew York Mets
Innings5.1 3.3–7.0
Strikeouts4.5 2–7
Walks1.9 0–4
Hits allowed4.6 2–7
Home runs0.6 0–2
Runs allowed2.1 0–5
Pitches83 60–107
2+ strikeouts94%
3+ strikeouts83%
4+ strikeouts66%
5+ strikeouts46%
6+ strikeouts28%
7+ strikeouts16%
Griffin JaxTampa Bay Rays
Innings5.3 3.7–7.0
Strikeouts6.0 3–9
Walks1.5 0–3
Hits allowed4.3 2–7
Home runs0.7 0–2
Runs allowed1.8 0–4
Pitches83 60–107
3+ strikeouts94%
4+ strikeouts85%
5+ strikeouts72%
6+ strikeouts56%
7+ strikeouts38%
8+ 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

0.94×park
0.94×run environment
the park favours pitchers (0.94x runs). Park factors are measured from 25,110 games by comparing each club at home with the same club on the road, so a good offence does not inflate its own park. Player rates are park-neutralised before this is applied, or the park would count twice.
What this does not know
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