MLB Baseball

ATL vs SF Prediction

June 28, 2026

10,000 Monte Carlo simulations

ATL vs SF prediction for June 28, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects SF 2.7 - ATL 3.3. ATL is favored with a 57.0% win probability. The run line is 1.5 and the total is 7.5. Model projects 6.0 total runs.

SF
2.7
Projected Score
VS O/U 7.5
ATL
3.3
Projected Score
Win Probability
43.0%
57.0%
SFATL
+1.5
Run Line (SF)
7.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 55.8% (2,559 games)

Projected Runs Range 10th – 90th percentile

ATL
135
SF
135
FINALSF 3 — ATL 2
Projected
SF 2.7 — ATL 3.3
Actual
SF 3 — ATL 2

Starting Pitcher Matchup

Chris Sale L
ATL
SL41%79 mph38% whiff
FF40%96 mph20% whiff
CH12%88 mph29% whiff
Robbie Ray L
SF
FF41%93 mph17% whiff
SL27%86 mph32% whiff
CH16%86 mph27% whiff

Weather Impact

Oracle Park
73°F12 mph wind
HR: 0.964 Total: 0.977
11mph in

Bullpen Comparison

ATL
2.18ERA
2.83FIP
9.74K/9
2.51BB/9
1.00WHIP
SF
4.06ERA
4.43FIP
8.10K/9
4.84BB/9
1.41WHIP

Betting Edges

RUN_LINE HOME +1.5
-39.5% EV
-118
TOTAL OVER 7.5
-23.7% EV
-104
RUN_LINE AWAY -1.5
-14.4% EV
-102
TOTAL UNDER 7.5
+13.0% EV
-118
ML AWAY
-9.3% EV
-179
F5_ML HOME
-6.6% EV
+142

First 5 Innings & NRFI

ATL F5
2.0 runs
50.1% win
SF F5
1.4 runs
31.5% win
F5 Total
3.3
NRFI
60.8%
YRFI
39.2%
Avg 1st Inn Runs
0.81

HR Spotlight

Avg HRs
1.8
Over 0.5 HR
84%
Over 1.5 HR
55%
No HR
16%
Matt Olson ATL30.0%
ISO: 0.285 | Barrel: 16.3% | vs Robbie Ray | Park: 0.88x
Drake Baldwin ATL30.0%
ISO: 0.316 | Barrel: 13.8% | vs Robbie Ray | Park: 0.88x
Ozzie Albies ATL30.0%
ISO: 0.183 | Barrel: 8.0% | vs Robbie Ray | Park: 0.88x Platoon: 1.12x

Pitcher Strikeout Projections

Chris Sale
0.0 K projected
ATL | K/9: 0.0
Robbie Ray
0.0 K projected
SF | K/9: 0.0

Injury Report

ATL8 injured
Robert Suarez RP15-DAY-IL
AJ Smith-Shawver SP60-DAY-IL
Danny Young RP60-DAY-IL
Kyle Farmer DH10-DAY-IL
Spencer Strider SP60-DAY-IL
Ronald Acuna Jr. RF10-DAY-IL
+2 more
SF8 injured
Daniel Susac C10-DAY-IL
Keaton Winn RP15-DAY-IL
Jason Foley RP60-DAY-IL
Harrison Bader CF10-DAY-IL
Joel Peguero RP60-DAY-IL
Rowan Wick RP60-DAY-IL
+2 more

AI Intelligence Analysis

LEAN +1YELLOW ZONE50.1% WR (n=256)
Chris Sale (B grade, 28.3% K rate, elite strikeout) vs Robbie Ray (C+ grade, 22.2% K rate) creates massive ATL away pitcher advantage, but market respects Sale at -178 (away team at 64.1% implied). Model sees only 58.1% away win prob — market OVERVALUING Sale at -178. However, UNDER 7.5 is the outlier value: model projects 5.99 total runs vs market 7.5, creating +13.0% edge at 61.1% win prob.

Key Factors

  • Sale elite: 28.3% K rate, B grade (top tier), 10.6 K/9 vs Ray 22.2% K rate, C+ grade, 8.0 K/9 — 6.1pt K-rate gap, significant
  • Oracle Park (SF) -12% park factor + 12.2 mph wind IN (-10.7 tail) = major run suppression. Model 5.99 total is realistic.
  • NRFI 60.8% model prob (no runs first inning) — game likely starts 0-0, supports under
  • Both bullpens middling (SF 4.06 ERA vs ATL 2.18 ERA advantage ATL) but Sale's K-rate dominates
  • Temperature 72.6F cool + wind in = classic low-scoring conditions

Risk Factors

  • Totals DISABLED market; use extreme caution. UNDER has 47.6% historical WR (DISABLED).
  • Sale's dominance might produce under 7.5 anyway; but market 7.5 total is respectable given conditions. 13.0% edge suspicious.
  • Oracle marine layer unpredictable; wind can shift
Sharp MoneyAgainst ModelATL -178 away favorite implies 64.1% but model sees 58.1% — market overestimating Sale advantage. However, Sale vs Ray mismatch (28.3% vs 22.2% K-rate) IS real; UNDER capture this better than directionality.

Edge Analysis

Moneyline
ATL 57.0%
-39.5 pts
Run Line
+1.5
-39.5 pts
Total
7.5
+13.0 pts
How this prediction was generated: This page shows output from the Olympus Bets MLB Baseball Monte Carlo engine. Each game is simulated 10,000 times using real-time team data, injury reports, and current odds. Probabilities are calibrated using Bayesian methods and sized via the Kelly Criterion. Probabilities are calibrated using Bayesian methods and sized via the Kelly Criterion. Full methodology →

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