Atlanta Braves vs San Francisco Giants: MLB Prediction, Pick & Odds — Jun 28, 2026

ATL

48-27

PregameSun, 4:05 PM EDT

31-45

Verdict

Pass · no edge tonight.

The model doesn't see daylight against the posted line on this game. We don't surface negative-EV picks; check the drill-down for sub-model context.

Why this matchup

1 signal · model + market

Park factor

94 total idx

Oracle Park run environment

Park factor boosts run scoring, so contact quality matters more tonight here.

Oracle Park · San Francisco, California

Drill down

Sub-model tables · ensemble breakdown · last meeting · book shop · player props

Pregame · scouting report

The matchup, end-to-end.

Probable starters, projected lineups, head-to-head this season, our model edge against the market — every angle on one surface.

Away starter

Grant Holmes

SP · #66

4-3

W-L

4.33

ERA

1.40

WHIP

68.2

Last 3 starts

vsSFL(4-3)2.0 IP3 ER2 K

@CHW-3.2 IP3 ER2 K

vsTORW(4-2)6.0 IP2 ER4 K

Home starter

Robbie Ray

SP · #38

5-6

W-L

4.07

ERA

1.33

WHIP

79.2

Last 3 starts

@ATLW(5-6)6.1 IP0 ER8 K

vsWSH-5.2 IP5 ER3 K

@CHCW(4-6)5.0 IP0 ER4 K

Vegas line

Lines post once a sportsbook releases them.

Model edge

Our model rates this game once both starters are confirmed.

Head to head

SeriesSF leads series 2-0

TypeRegular Season Series

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.

49.4%

ensemble · ATL favored

Elo Static
fallback · inputs missing
50.0%
P(SF win)
33%
weight
Elo Pitching
fallback · inputs missing
50.0%
P(SF win)
32%
weight
Bullpen Park
fallback · inputs missing
50.0%
P(SF win)
34%
weight

Disagreement

0.00 pp

weighted σ across sub-models

Confidence

100% · high

maps from disagreement

Substrate count

0 / 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.

Player projections

SF vs ATL.

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.

133

projections · 84 high confidence

Strikeouts

Chris SaleATL
7.4± 2.0low
Landen RouppSF
5.9± 1.8medium
Logan WebbSF
5.3± 1.8low

Hits

Casey SchmittSF
1.4± 1.0high
Jung Hoo LeeSF
1.4± 1.3high
Luis ArraezSF
1.4± 1.0high

Total bases

Bryce EldridgeSF
2.4± 2.1high
Drake BaldwinATL
2.1± 2.1high
Casey SchmittSF
2.1± 2.3high

RBIs

Bryce EldridgeSF
0.8± 1.1high
Drake BaldwinATL
0.7± 0.8high
Matt ChapmanSF
0.7± 1.1high

Earned runs

Adrian HouserSF
2.9± 2.7low
Landen RouppSF
2.8± 2.5medium
Trevor McDonaldSF
2.8± 2.6low

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

Matchup · 2026

Team rate stats vs league

MLB Stats API

ATL

league avg

.740

OPS

◀

.719

.731

.318

OBP

◀

.319

.310

4.97

Runs / G

◀

4.50

4.16

3.34

Team ERA

◀

4.19

4.49

1.19

WHIP

◀

1.31

1.40

8.7

K / 9

◀

8.5

8.1

Data via ESPN · MLB Stats API · Baseball Savant

Atlanta Braves at San Francisco Giants

The matchup, end-to-end.

3 sub-models, blended.

SF vs ATL.

Team rate stats vs league

3 sub-models, blended.