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

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.

Milwaukee Brewers vs San Francisco Giants: Final Score & Box Score — Jul 28, 2026

FINAL+6MIL

MIL

67-40

45-62

Oracle Park · San Francisco, California

38,021 attended

Line movement

200 snapshots

SF spread

+1.5

open PK · +1.5

Total

O/U 7.5

open O/U 7.5

SF no-vig %

43.6%

open 43.6%

Stepped lines reflect captured market snapshots from odds_snapshots. Spread sign convention: negative = SF 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.

41.3%

ensemble · MIL favored

Elo Static
46.0%
P(SF win)
33%
weight
Elo Pitching
44.1%
P(SF win)
33%
weight
Bullpen Park
44.2%
P(SF win)
34%
weight

Disagreement

0.87 pp

weighted σ across sub-models

Confidence

94% · 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.

-0.96

CLV pp

Open price

+119

Close price

+124

Open no-vig

43.6%

Close no-vig

42.7%

Market faded the model · Graded: miss

How we read this game

Which side does The One Analytics' model favor in MIL at SF?: 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.

+11.3pp

best edge · SF · DraftKings

MIL

no live price

★ best

+193DraftKings

edge +11.3pp · implied 32.1%

Book	MIL	SF	Best edge
DraftKings	-261	+193★	+11.3

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

SF vs MIL.

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.

127

projections · 96 high confidence

Strikeouts

Jacob MisiorowskiMIL
9.4± 2.7high
Logan HendersonMIL
6.2± 2.8low
Dustin MayMIL
5.3± 2.9high

Hits

Jackson ChourioMIL
1.2± 0.9high
Jung Hoo LeeSF
1.2± 0.9high
Brice TurangMIL
1.1± 0.9high

Total bases

Osleivis BasabeSF
2.5± 3.4low
Jung Hoo LeeSF
2.3± 2.8high
Jake BauersMIL
2.0± 1.7high

RBIs

Osleivis BasabeSF
1.3± 2.0low
Luis LaraMIL
0.8± 1.5medium
Brice TurangMIL
0.7± 0.9high

Earned runs

Carson WhisenhuntSF
3.5± 2.6low
Landen RouppSF
2.7± 1.9high
Robert GasserMIL
2.5± 3.1low

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

Matchup · 2026

Team rate stats vs league

MLB Stats API

MIL

league avg

.735

OPS

◀

.720

.723

.337

OBP

◀

.318

.309

4.97

Runs / G

◀

4.50

4.20

3.47

Team ERA

◀

4.18

4.37

1.16

WHIP

◀

1.30

1.36

9.8

K / 9

◀

8.5

7.8

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

MIL wins

MIL 8 · SF 2 (by 6)

Model verdict

✓ Hit

Picked MIL +4pp

Against the spread

No spread

Line score

Inning by inning

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

Final play

“End of the 9th inning”

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
B. Turang2B	.269	5	0	3	2	0	0	1
J. ChourioLF	.279	5	0	2	2	0	0	0
W. ContrerasC	.273	5	1	2	0	0	0	0
C. YelichDH	.239	4	1	1	0	0	1	1
A. Vaughn1B	.309	4	1	1	0	0	0	0
L. LaraRF	.289	4	1	1	3	0	1	1
G. MitchellCF	.270	3	1	1	0	0	1	0
C. PrattSS	.283	4	2	1	1	0	1	0
D. Hamilton3B	.239	2	1	1	0	0	1	0
Team		36	8	13	8	0	5	3

Player

.269

.279

.273

.239

.309

.289

.270

.283

.239

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
L. HendersonSP	5.2	2	0	0	2	7	93
A. AshbyRP	0.1	0	0	0	0	0	9
C. YohoRP	1.0	1	0	0	0	0	22
G. AndersonRP	1.0	2	2	2	0	2	18
A. UribeRP	1.0	2	0	0	0	0	15
Team	9.0	7	2	2	2	9	157

Player

5.2

0.1

1.0

1.0

1.0

Team

9.0

157

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	.325	4	1	1	0	0	0	0
B. EldridgeDH	.256	4	1	1	2	1	0	2
H. RamosLF	.257	4	0	1	0	0	0	0
R. Devers1B	.246	4	0	1	0	0	0	1
J. LeeRF	.301	4	0	1	0	0	0	2
W. AdamesSS	.227	4	0	1	0	0	0	1
G. McCrayCF	.182	3	0	1	0	0	1	1
D. CavanaughC	.244	3	0	0	0	0	1	0
C. Koss2B	.115	3	0	0	0	0	0	2
Team		33	2	7	2	1	2	9

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. RouppSP	3.2	4	4	4	3	1	84
J. BrubakerRP	3.0	5	3	3	0	1	57
J. FoleyRP	1.1	4	1	1	1	0	33
K. WinnRP	1.0	0	0	0	1	1	17
Team	9.0	13	8	8	5	3	191

Team

MIL

3 sub-models, blended.

Closing-line value.

Where to bet this game.

SF vs MIL.

Team rate stats vs league

The morning-after recap.

Inning by inning

Tomorrow's slate is open.

Where to bet this game.

Batters

Pitchers

Batters

Pitchers

Closing-line value.

SF vs MIL.

3 sub-models, blended.