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

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.

How is the pick graded?

In public, the moment the game goes final — wins and losses alike, with the full record on the model accuracy page.

San Diego Padres vs San Francisco Giants: Final Score & Box Score — May 5, 2026

FINAL+5SD

21-14

105

14-22

Oracle Park · San Francisco, California

38,275 attended

Line movement

200 snapshots

SF spread

-1.5

open -1.5

Total

O/U 7.5

open O/U 7.5

SF no-vig %

54.2%

open 55.1% · -0.9

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.

Logged before first pitch · graded in public

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.

43.2%

ensemble · SD favored

Elo Static
44.4%
P(SF win)
33%
weight
Elo Pitching
45.1%
P(SF win)
32%
weight
Bullpen Park
45.0%
P(SF win)
34%
weight

Disagreement

0.31 pp

weighted σ across sub-models

Confidence

98% · 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.

+0.87

CLV pp

Open price

+113

Close price

+109

Open no-vig

44.9%

Close no-vig

45.8%

Market came to the model · Graded: hit

Logged before tip · graded in public

How we read this game

Which side does The One Analytics' model favor in SD at SF?: 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.
How is the pick graded?: In public, the moment the game goes final — wins and losses alike, with the full record on the model accuracy page.

Player projections

SF vs SD.

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.

129

projections · 77 high confidence

Strikeouts

Landen RouppSF
5.9± 1.8medium
Logan WebbSF
5.5± 1.5low
Michael KingSD
4.8± 2.9medium

Hits

Samad TaylorSD
1.4± 1.1low
Casey SchmittSF
1.4± 1.0high
Luis ArraezSF
1.3± 0.9high

Total bases

Bryce EldridgeSF
2.2± 2.3high
Casey SchmittSF
2.1± 2.3high
Luis ArraezSF
2.1± 1.8high

RBIs

Manny MachadoSD
0.7± 1.6high
Bryce EldridgeSF
0.7± 1.2high
Fernando Tatis Jr.SD
0.6± 0.9high

Earned runs

Griffin CanningSD
3.4± 3.2low
Adrian HouserSF
2.9± 2.7low
Randy VasquezSD
2.8± 2.1medium

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

.657

OPS

.719

▶

.728

.293

OBP

.319

▶

.309

3.89

Runs / G

4.50

▶

4.12

3.90

Team ERA

◀

4.19

4.46

1.30

WHIP

◀

1.31

1.39

8.4

K / 9

◀

8.5

8.1

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

SD 10 · SF 5 (by 5)

Model verdict

✓ Hit

Picked SD +6pp

Against the spread

No spread

Line score

Inning by inning

Team	1	2	3	4	5	6	7	8	9	R
SD	0	1	0	5	1	1	0	2	0	10
SF	2	2	0	0	0	0	1	0	0	5

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
J. MerrillCF	.235	5	2	3	2	0	0	2
M. Machado3B	.212	5	0	0	0	0	0	2
M. AndujarDH	.322	5	1	3	1	0	0	0
G. Sheets1B	.224	5	1	2	0	0	0	0
F. Tatis Jr.RF	.250	5	1	1	0	0	0	1
X. BogaertsSS	.270	4	1	2	2	1	1	0
N. CastellanosRF	.172	3	1	1	2	0	0	0
L. CampusanoC	.288	2	1	0	0	0	1	0
S. Song2B	.500	4	2	2	2	0	0	0
B. JohnsonRF	.208	1	0	0	0	0	0	0
Team		39	10	14	9	1	2	5

Player

.235

.212

.322

.224

.250

.270

.172

.288

.500

.208

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
W. BuehlerSP	5.1	7	4	4	0	5	82
J. EstradaRP	1.2	1	1	1	0	2	21
J. AdamRP	1.0	0	0	0	0	0	9
R. MarinaccioRP	1.0	0	0	0	0	1	9
Team	9.0	8	5	5	0	8	121

Player

5.1

1.2

1.0

1.0

Team

9.0

121

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. LeeRF	.271	4	1	1	1	0	0	0
C. SchmittDH	.306	4	1	1	2	1	0	1
R. Devers1B	.219	4	0	1	0	0	0	1
H. RamosLF	.262	4	0	0	0	0	0	2
B. EldridgeDH	.167	4	0	1	0	0	0	0
M. Chapman3B	.239	4	0	0	0	0	0	1
W. AdamesSS	.199	4	1	1	0	0	0	1
D. GilbertCF	.259	3	1	1	0	0	0	1
J. RodríguezC	.333	3	1	2	2	1	0	0
C. Koss2B	.077	1	0	0	0	0	0	1
Team		35	5	8	5	2	0	8

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. WebbSP	4.0	7	6	6	0	4	62
J. BrubakerRP	1.0	2	1	1	2	1	38
R. BoruckiRP	1.0	2	1	1	0	0	20
G. SantosRP	2.0	2	2	2	0	0	28
J. PegueroRP	1.0	1	0	0	0	0	8
Team	9.0	14	10	10	2	5	156

Team

3 sub-models, blended.

Closing-line value.

SF vs SD.

Team rate stats vs league

The morning-after recap.

Inning by inning

Tomorrow's slate is open.

Closing-line value.

Batters

Pitchers

Batters

Pitchers

SF vs SD.

3 sub-models, blended.