Park factor
95 total idx
T-Mobile Park run environment
Park factor boosts run scoring, so contact quality matters more tonight here.
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San Francisco Giants at Seattle Mariners
SF
SF
31-43
PregameSun, 4:10 PM EDT
SEA
SEA
39-37
Verdict
Pass · no edge tonight.
The model doesn't see daylight against the posted line on this game. We don't surface negative-EV picks; check the drill-down for sub-model context.
Why this matchup
1 signal · model + marketT-Mobile Park · Seattle, Washington
Drill down
Sub-model tables · ensemble breakdown · last meeting · book shop · player props
Drill down
Sub-model tables · ensemble breakdown · last meeting · book shop · player props
Pregame · scouting report
The matchup, end-to-end.
Probable starters, projected lineups, head-to-head this season, our model edge against the market — every angle on one surface.
Away starter
TBD
Probable starter not yet announced. ESPN typically posts the card 12–24 hours before first pitch.
Home starter
TBD
Probable starter not yet announced. ESPN typically posts the card 12–24 hours before first pitch.
Vegas line
Lines post once a sportsbook releases them.
Model edge
Our model rates this game once both starters are confirmed.
Head to head
SeriesSF wins series 2-0
TypePreseason Series
Model ensemble · how the prediction is built
3 sub-models, blended.
Each sub-model uses a different rating substrate. Bayesian model averaging weights them by rolling Brier score so the ensemble inherits each model's strengths. Disagreement flags games where the sub-models don't see eye-to-eye — lower confidence, wider band.
47.7%
ensemble · SF favored
Elo Static
fallback · inputs missing
50.0%
P(SEA win)
33%
weight
Elo Pitching
fallback · inputs missing
50.0%
P(SEA win)
32%
weight
Bullpen Park
fallback · inputs missing
50.0%
P(SEA win)
34%
weight
Disagreement
0.00 pp
weighted σ across sub-models
Confidence
100% · high
maps from disagreement
Substrate count
0 / 3 active
ones with full inputs tonight
Weights recalibrated nightly on a 90-day rolling window with strict point-in-time correctness — no model gets credit for a game it hasn't seen. Headline % is Platt-scaled per league; sub-model rows show raw BMA inputs.
Player projections
SEA vs SF.
Per-player stat projections built from a recency-weighted blend of the last ten games, season average, and matchup context. Confidence reflects sample size and stability — the top of each list is who to watch.
130
projections · 73 high confidence
Strikeouts
- Logan GilbertSEA6.1± 2.7medium
- Bryce MillerSEA6.0± 3.0low
- Bryan WooSEA5.8± 4.0low
Hits
- Luis ArraezSF1.4± 0.8high
- Bryce EldridgeSF1.3± 0.8high
- Jung Hoo LeeSF1.3± 1.3high
Total bases
- Bryce EldridgeSF2.4± 2.1high
- Luis ArraezSF2.2± 1.6high
- Dominic CanzoneSEA2.0± 2.4high
RBIs
- Bryce EldridgeSF0.8± 1.1high
- Matt ChapmanSF0.8± 1.1high
- Colt EmersonSEA0.6± 0.8high
Earned runs
- Bryan WooSEA3.1± 3.9low
- George KirbySEA2.9± 1.6medium
- Adrian HouserSF2.9± 2.7low
Projections recompute every 30 minutes · prop lines plug in once sportsbook ingest lands
Matchup · 2026
Team rate stats vs league
MLB Stats API
SF
league avg
SEA
.730
OPS
◀
.718
.710
.309
OBP
.319
▶.316
4.19
Runs / G
4.50
4.21
4.49
Team ERA
4.18
▶3.62
1.40
WHIP
1.31
▶1.18
8.1
K / 9
8.5
▶8.7
Data via ESPN · MLB Stats API · Baseball Savant