ATL vs SF prediction for June 26, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects SF 2.9 - ATL 4.2. ATL is favored with a 61.9% win probability. The run line is 1.5 and the total is 7.5. Model projects 7.1 total runs.
SF
2.9
Projected Score
VS
O/U 7.5
ATL
4.2
Projected Score
Win Probability
SFATL
+1.5
Run Line (SF)
7.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 62.2% (2,443 games)
Projected Runs Range 10th – 90th percentile
ATL
246
SF
135
Starting Pitcher Matchup
Reynaldo López R
ATL
FF54%94 mph12% whiff
SL32%83 mph28% whiff
CU10%74 mph23% whiff
R TBD
SF
Weather Impact
Oracle Park
60°F11 mph wind
HR: 0.958 Total: 0.975
10mph 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
-49.3% EV
-167
TOTAL OVER 7.5
-21.9% EV
-122
ML HOME
-18.6% EV
+104
TOTAL UNDER 7.5
+14.2% EV
+100
ML AWAY
+9.4% EV
-122
RUN_LINE AWAY -1.5
+4.7% EV
+138
First 5 Innings & NRFI
ATL F5
2.2 runs
48.9% win
SF F5
1.5 runs
31.1% win
F5 Total
3.7
NRFI
64.0%
YRFI
36.0%
Avg 1st Inn Runs
0.68
HR Spotlight
Avg HRs
1.4
Over 0.5 HR
75%
Over 1.5 HR
40%
No HR
25%
Pitcher Strikeout Projections
Reynaldo López
0.0 K projected
ATL | K/9: 0.0
0.0 K projected
SF | K/9: 0.0
Injury Report
ATL8 injured
AJ Smith-Shawver SP60-DAY-IL
Danny Young RP60-DAY-IL
Robert Suarez RPDAY-TO-DAY
Kyle Farmer DH10-DAY-IL
Spencer Strider SP60-DAY-IL
Ronald Acuna Jr. RF10-DAY-IL
+2 more
SF8 injured
Daniel Susac CDAY-TO-DAY
Luis Arraez 2BDAY-TO-DAY
Keaton Winn RP15-DAY-IL
Heliot Ramos LF10-DAY-IL
Jason Foley RP60-DAY-IL
Harrison Bader CF10-DAY-IL
+2 more
AI Intelligence Analysis
Edge Analysis
Moneyline
ATL 61.9%
-49.3 pts
Run Line
+1.5
-49.3 pts
Total
7.5
+14.2 pts
More Projections Today
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 →