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

The model favors SD, 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 San Diego Padres: Final Score & Box Score — Jul 31, 2026

FINAL+7SD

47-63

56-54

Petco Park · San Diego, California

44,057 attended

Line movement

200 snapshots

SD spread

-1.5

open -1.5

Total

O/U 8.5

open O/U 8.5

SD no-vig %

58.3%

open 56.7% · +1.5

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

61.6%

ensemble · SD favored

Elo Static
59.1%
P(SD win)
33%
weight
Elo Pitching
63.6%
P(SD win)
33%
weight
Bullpen Park
59.9%
P(SD win)
34%
weight

Disagreement

1.95 pp

weighted σ across sub-models

Confidence

87% · 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.

+0.60

CLV pp

Open price

-146

Close price

-150

Open no-vig

56.7%

Close no-vig

57.3%

Market came to the model · Graded: hit

How we read this game

Which side does The One Analytics' model favor in SF at SD?: The model favors SD, 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.

+28.2pp

best edge · SF · DraftKings

★ best

+700DraftKings

edge +28.2pp · implied 11.7%

no live price

Book	SF	SD	Best edge
DraftKings	+700★	-1540	+28.2

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

SD 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.

127

projections · 96 high confidence

Strikeouts

Landen RouppSF
5.1± 2.0high
Logan WebbSF
5.0± 2.0high
Casey MizeSD
4.8± 2.8medium

Hits

Jung Hoo LeeSF
1.3± 0.8high
Jackson MerrillSD
1.2± 1.1high
Ty FranceSD
1.1± 1.0high

Total bases

Jung Hoo LeeSF
2.4± 2.7high
Osleivis BasabeSF
2.3± 3.2low
Jackson MerrillSD
1.9± 1.9high

RBIs

Osleivis BasabeSF
1.1± 2.0low
Manny MachadoSD
0.8± 1.4high
Jackson MerrillSD
0.7± 0.9high

Earned runs

Carson WhisenhuntSF
3.6± 2.3low
Walker BuehlerSD
3.0± 2.8high
Carson SeymourSF
2.7± 2.1low

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

.722

OPS

◀

.719

.694

.309

OBP

.318

.312

4.17

Runs / G

4.50

▶

4.23

4.38

Team ERA

4.18

▶

4.21

1.36

WHIP

1.30

▶

1.33

7.8

K / 9

8.5

▶

8.3

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

SD wins

SF 0 · SD 7 (by 7)

Model verdict

✓ Hit

Picked SD +9pp

Against the spread

No spread

Line score

Inning by inning

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

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	.328	3	0	1	0	0	0	1
H. RamosLF	.264	3	0	0	0	0	0	1
B. EldridgeDH	.250	3	0	0	0	0	0	2
R. Devers1B	.247	2	0	0	0	0	1	0
J. LeeRF	.300	3	0	0	0	0	0	0
W. AdamesSS	.225	3	0	0	0	0	0	0
G. McCrayCF	.150	3	0	0	0	0	0	1
D. CavanaughC	.245	3	0	0	0	0	0	1
C. Koss2B	.184	3	0	1	0	0	0	0
O. BasabeSS	.000	1	0	0	0	0	0	0
D. GilbertCF	.236	1	0	0	0	0	0	0
J. RodríguezC	.235	1	0	0	0	0	0	0
Team		29	0	2	0	0	1	6

Player

.328

.264

.250

.247

.300

.225

.150

.245

.184

.000

.236

.235

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
C. WhisenhuntSP	3.1	7	6	6	4	3	74
A. HouserSP	4.2	5	1	1	1	3	64
Team	8.0	12	7	7	5	6	138

Player

C. WhisenhuntSP

3.1

A. HouserSP

4.2

Team

8.0

138

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
F. Tatis Jr.RF	.286	3	2	1	0	0	2	0
L. RengifoLF	.381	3	3	1	0	0	2	1
M. Machado3B	.214	4	0	1	1	0	0	1
T. France1B	.287	2	0	2	3	0	1	0
J. MerrillCF	.234	4	1	0	0	0	0	1
L. CampusanoC	.306	4	0	3	1	0	0	0
X. BogaertsSS	.218	4	0	1	0	0	0	1
F. FerminC	.170	4	0	1	0	0	0	1
J. BowenRF	.167	4	1	2	1	1	0	1
Team		32	7	12	6	1	5	6

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
B. RodriguezRP	1.0	0	0	0	0	2	13
Y. MatsuiRP	3.0	1	0	0	0	2	49
G. MarquezSP	5.0	1	0	0	1	2	70
Team	9.0	2	0	0	1	6	132

Team

—

3 sub-models, blended.

Closing-line value.

Where to bet this game.

SD vs SF.

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.

SD vs SF.

3 sub-models, blended.