MLB game · live box score, model edge, odds · The One Analytics

SEA

38-36

PregameWed, 6:40 PM EDT

PIT

37-37

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 + market

Park factor

98 total idx

PNC Park run environment

Park factor boosts run scoring, so contact quality matters more tonight here.

PNC Park · Pittsburgh, Pennsylvania

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

Braxton Ashcraft

SP · #35

5-3

W-L

3.30

ERA

1.10

WHIP

84.2

Last 3 starts

vsMIA-5.0 IP2 ER4 K

@ATLL(5-3)5.0 IP6 ER5 K

vsMINW(5-2)6.0 IP2 ER11 K

Vegas line

Lines post once a sportsbook releases them.

Model edge

Our model rates this game once both starters are confirmed.

Head to head

SeriesSeries starts 6/23

TypeRegular Season 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.

48.1%

ensemble · SEA favored

Elo Static
fallback · inputs missing
50.0%
P(PIT win)
33%
weight
Elo Pitching
fallback · inputs missing
50.0%
P(PIT win)
32%
weight
Bullpen Park
fallback · inputs missing
50.0%
P(PIT 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

PIT vs SEA.

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.

125

projections · 80 high confidence

Strikeouts

Paul SkenesPIT
7.2± 2.8medium
Braxton AshcraftPIT
6.4± 2.9low
Logan GilbertSEA
6.1± 2.7medium

Hits

Bryan ReynoldsPIT
1.2± 1.1high
Cole YoungSEA
1.2± 0.9high
Jake MangumPIT
1.1± 0.9high

Total bases

Bryan ReynoldsPIT
2.5± 3.2high
Dominic CanzoneSEA
2.1± 2.7high
J.P. CrawfordSEA
2.0± 2.9high

RBIs

Brandon LowePIT
0.7± 0.8high
Bryan ReynoldsPIT
0.6± 1.0high
Esmerlyn ValdezPIT
0.6± 1.6low

Earned runs

Mitch KellerPIT
3.6± 2.5medium
Bryan WooSEA
3.1± 3.9low
Jared JonesPIT
3.0± 3.3low

Projections recompute every 30 minutes · prop lines plug in once sportsbook ingest lands

Matchup · 2026

Team rate stats vs league

MLB Stats API

SEA

league avg

PIT

.712

OPS

.717

▶

.739

.317

OBP

.319

▶

.335

4.24

Runs / G

4.50

▶

4.96

3.65

Team ERA

◀

4.17

4.25

1.19

WHIP

◀

1.31

8.7

K / 9

8.5

▶

9.2

Data via ESPN · MLB Stats API · Baseball Savant

Seattle Mariners at Pittsburgh Pirates

The matchup, end-to-end.

3 sub-models, blended.

PIT vs SEA.

Team rate stats vs league

3 sub-models, blended.