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

The model favors KC, 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 Kansas City Royals: Final Score & Box Score — Jul 21, 2026

FINAL+1KC

42-59

42-60

Kauffman Stadium · Kansas City, Missouri

25,175 attended

Line movement

200 snapshots

KC spread

+1.5

open PK · +1.5

Total

O/U 9.5

open O/U 9.0 · +0.5

KC no-vig %

49.8%

open 49.6% · +0.2

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

56.4%

ensemble · KC favored

Elo Static
56.0%
P(KC win)
33%
weight
Elo Pitching
55.6%
P(KC win)
33%
weight
Bullpen Park
56.6%
P(KC win)
34%
weight

Disagreement

0.41 pp

weighted σ across sub-models

Confidence

97% · 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.

+0.22

CLV pp

Open price

-108

Close price

-109

Open no-vig

49.6%

Close no-vig

49.8%

Line barely moved · Graded: hit

How we read this game

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

no live price

Book	SF	KC	Best edge
DraftKings	+108	-141	+1.4

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

KC 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.

122

projections · 88 high confidence

Strikeouts

Noah CameronKC
5.1± 3.3high
Landen RouppSF
5.1± 2.0high
Logan WebbSF
5.0± 2.0high

Hits

Jung Hoo LeeSF
1.2± 0.9high
Rafael DeversSF
1.0± 1.3high
Salvador PerezKC
0.9± 0.8high

Total bases

Jung Hoo LeeSF
2.4± 2.8high
Osleivis BasabeSF
2.2± 3.6low
Salvador PerezKC
1.8± 1.6high

RBIs

Osleivis BasabeSF
1.2± 2.2low
Luke MaileKC
1.0± 1.6low
Jung Hoo LeeSF
0.8± 1.4high

Earned runs

Carson WhisenhuntSF
3.5± 2.6low
Noah CameronKC
3.0± 2.7high
Seth LugoKC
2.9± 2.3high

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

.724

OPS

◀

.720

.711

.310

OBP

.318

.313

4.20

Runs / G

◀

4.50

4.13

4.36

Team ERA

◀

4.18

4.87

1.35

WHIP

◀

1.30

1.43

7.8

K / 9

◀

8.5

7.6

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

KC wins

SF 2 · KC 3 (by 1)

Model verdict

✓ Hit

Picked KC +6pp

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	2	0	0	0	0	2
KC	0	0	1	0	0	2	0	0	3

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
H. RamosLF	.273	3	0	0	1	0	0	0
B. EldridgeDH	.271	4	0	1	0	0	0	2
C. SchmittLF	.273	3	0	0	0	0	1	1
R. Devers1B	.241	4	0	0	0	0	0	0
W. AdamesSS	.225	4	0	0	0	0	0	3
J. LeeRF	.303	3	0	1	0	0	1	1
J. RodríguezC	.244	3	1	1	0	0	0	1
D. GilbertCF	.228	4	1	1	1	0	0	2
C. Koss2B	.143	2	0	1	0	0	1	0
G. McCrayCF	.000	0	0	0	0	0	0	0
Team		30	2	5	2	0	3	10

Player

.273

.271

.273

.241

.225

.303

.244

.228

.143

.000

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
T. MahleSP	5.0	5	3	3	1	4	91
S. HentgesRP	0.1	1	0	0	0	1	14
K. WinnRP	0.2	1	0	0	0	0	9
D. SmithRP	1.0	1	0	0	1	2	13
C. KilianRP	1.0	0	0	0	0	0	11
Team	8.0	8	3	3	2	7	138

Player

5.0

0.1

0.2

1.0

1.0

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
C. JensenC	.242	4	1	1	1	1	0	0
L. ThomasCF	.240	4	0	0	0	0	0	2
J. CaglianoneRF	.258	2	0	0	0	0	0	1
S. PerezDH	.211	3	1	0	0	0	0	2
V. Pasquantino1B	.226	3	0	2	1	0	1	1
S. MarteRF	.270	3	0	1	0	0	0	0
M. Massey2B	.266	4	0	1	0	0	0	1
N. Loftin3B	.244	4	0	2	1	0	0	0
T. TolbertSS	.328	3	0	0	0	0	0	0
I. CollinsLF	.247	1	1	1	0	0	1	0
Team		31	3	8	3	1	2	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. AvilaSP	6.1	5	2	2	1	7	87
M. StrahmRP	0.2	0	0	0	0	1	11
J. SchreiberRP	1.0	0	0	0	1	0	20
A. LangeRP	1.0	0	0	0	1	2	15
Team	9.0	5	2	2	3	10	133

Team

—

3 sub-models, blended.

Closing-line value.

Where to bet this game.

KC 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

KC vs SF.

3 sub-models, blended.