Which side does The One Analytics' model favor in SF at SEA?

The model favors SF, based on a weighted edge across matchup factors. The pick is logged before the game and graded in public.

When is the pick logged, and can it change?

Every model pick is timestamped before the game starts and is never edited after the fact.

San Francisco Giants vs Seattle Mariners: Final Score & Box Score — Jul 19, 2026

FINAL+3SEA

42-57

SEA

50-50

T-Mobile Park · Seattle, Washington

36,204 attended

Line movement

200 snapshots

SEA spread

-1.5

open PK · -1.5

Total

O/U 7.5

open O/U 7.0 · +0.5

SEA no-vig %

61.5%

open 59.3% · +2.2

Stepped lines reflect captured market snapshots from odds_snapshots. Spread sign convention: negative = SEA favored. Live mode caps the in-game branch to the last 60 minutes.

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.

57.6%

ensemble · SEA favored

Elo Static
57.4%
P(SEA win)
33%
weight
Elo Pitching
56.9%
P(SEA win)
33%
weight
Bullpen Park
58.2%
P(SEA win)
34%
weight

Disagreement

0.54 pp

weighted σ across sub-models

Confidence

96% · high

maps from disagreement

Substrate count

3 / 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.

The receipts

Closing-line value.

-4.35

CLV pp · steam

Open price

+135

Close price

+163

Open no-vig

40.7%

Close no-vig

36.4%

Market faded the model hard · Graded: miss

How we read this game

Which side does The One Analytics' model favor in SF at SEA?: The model favors SF, based on a weighted edge across matchup factors. The pick is logged before the game and graded in public.
When is the pick logged, and can it change?: Every model pick is timestamped before the game starts and is never edited after the fact.

Line shopping · 1 book

Where to bet this game.

Same model, different prices. The same moneyline can vary 25¢ across books — taking the worst price wipes out a real edge instantly. Star marks the best-paying book per side.

+20.7pp

best edge · SEA · DraftKings

no live price

SEA

★ best

+155DraftKings

edge +20.7pp · implied 36.8%

Book	SF	SEA	Best edge
DraftKings	-205	+155★	+20.7

Edges shown are model probability minus no-vig implied probability for that side at that book. Stars mark the highest-paying cell per side. Lines refresh every 60 seconds.

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.

123

projections · 95 high confidence

Strikeouts

Logan GilbertSEA
6.7± 2.0high
Bryan WooSEA
6.1± 1.9high
Bryce MillerSEA
5.9± 4.4low

Hits

Cole YoungSEA
1.5± 1.1high
Jung Hoo LeeSF
1.2± 0.9high
Josh NaylorSEA
1.1± 0.9high

Total bases

Jung Hoo LeeSF
2.4± 2.8high
Cole YoungSEA
2.2± 1.5high
Osleivis BasabeSF
2.2± 3.6low

RBIs

Osleivis BasabeSF
1.2± 2.2low
Cal RaleighSEA
0.8± 1.0high
Jung Hoo LeeSF
0.8± 1.4high

Earned runs

Carson WhisenhuntSF
3.5± 2.6low
Bryan WooSEA
3.2± 2.4high
Landen RouppSF
2.7± 1.9high

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

Matchup · 2026

Team rate stats vs league

MLB Stats API

league avg

SEA

.724

OPS

◀

.720

.689

.310

OBP

.318

.310

4.20

Runs / G

◀

4.50

4.02

4.36

Team ERA

4.18

▶

3.75

1.35

WHIP

1.30

▶

1.19

7.8

K / 9

8.5

▶

8.7

Postgame · final

The morning-after recap.

Line score, top performers, model verdict against Vegas, and how the closing line shaped up vs the actual outcome.

Final

SEA wins

SF 3 · SEA 6 (by 3)

Model verdict

✓ Hit

Picked SEA +7pp

Against the spread

No spread

Line score

Inning by inning

Team	1	2	3	4	5	6	7	8	9	R
SF	2	0	0	0	1	0	0	0	0	3
SEA	0	0	0	2	1	1	2	0	6

What's next

Tomorrow's slate is open.

See every model edge for tonight's remaining games and tomorrow's slate side-by-side, or jump straight to DraftKings & FanDuel for the full board.

MLB edges →Full slate →

Tomorrow's board↗Tomorrow's board↗

21+ · we may earn a referral fee · your odds unchanged.

Data via ESPN · MLB Stats API · Baseball Savant

batting box score. Tap a column header to sort by that stat; tap again to reverse, a third time to clear. The team leader in each stat is highlighted. Players who did not play are listed at the bottom.
Player
L. Arraez2B	.326	4	0	1	1	0	0	2
B. EldridgeDH	.275	3	1	1	1	1	1	2
C. SchmittLF	.278	4	1	1	0	0	0	0
R. Devers1B	.243	4	0	0	0	0	0	3
H. RamosLF	.277	4	0	1	1	0	0	2
J. LeeRF	.303	4	0	1	0	0	0	0
W. AdamesSS	.228	3	1	0	0	0	1	2
G. McCrayCF	.000	2	0	0	0	0	0	2
D. CavanaughC	.243	3	0	0	0	0	0	3
Team		31	3	5	3	1	2	16

Player

.326

.275

.278

.243

.277

.303

.228

.000

.243

Team

pitching box score. Tap a column header to sort by that stat; tap again to reverse, a third time to clear. The team leader in each stat is highlighted. Players who did not play are listed at the bottom.
Player
R. RaySP	4.0	8	3	1	2	6	86
S. HentgesRP	1.0	0	0	0	0	0	5
A. HouserSP	3.0	4	3	3	1	1	50
Team	8.0	12	6	4	3	7	141

Player

R. RaySP

4.0

S. HentgesRP

1.0

A. HouserSP

3.0

Team

8.0

141

batting box score. Tap a column header to sort by that stat; tap again to reverse, a third time to clear. The team leader in each stat is highlighted. Players who did not play are listed at the bottom.
Player
J.P. CrawfordSS	.215	3	0	1	0	0	2	0
J. RodriguezCF	.256	4	1	1	0	0	1	1
C. Young2B	.259	4	2	3	2	1	0	1
R. ArozarenaLF	.281	4	1	1	0	0	0	1
C. RaleighC	.163	4	0	0	0	0	0	1
J. Naylor1B	.253	4	1	2	1	0	0	0
M. GarverC	.184	4	0	1	0	0	0	1
We. Wilson3B	.200	2	0	1	1	0	0	1
C. EmersonSS	.195	4	0	1	0	0	0	1
L. RaleyRF	.230	2	1	1	1	1	0	0
V. RoblesRF	.210	0	0	0	0	0	0	0
Team		35	6	12	5	2	3	7

pitching box score. Tap a column header to sort by that stat; tap again to reverse, a third time to clear. The team leader in each stat is highlighted. Players who did not play are listed at the bottom.
Player
L. GilbertSP	6.0	4	3	3	1	10	95
E. BazardoRP	1.0	1	0	0	0	3	16
G. SpeierRP	1.0	0	0	0	1	1	16
A. MunozRP	1.0	0	0	0	0	2	9
Team	9.0	5	3	3	2	16	136

Team

SEA

—

3 sub-models, blended.

Closing-line value.

Where to bet this game.

SEA vs SF.

Team rate stats vs league

The morning-after recap.

Inning by inning

Tomorrow's slate is open.

Where to bet this game.

Closing-line value.

Batters

Pitchers

Batters

Pitchers

SEA vs SF.

3 sub-models, blended.