FINAL: ATL 3 — SD 8. Our Monte Carlo simulation projected ATL 6.4 - SD 5.2 (ATL at 56.9% win probability). The run line is -1.5 and the total is 9.0. Model projects 11.6 total runs.
ATL
6.4
Projected Score
VS
O/U 9.0
SD
5.2
Projected Score
Win Probability
ATLSD
-1.5
Run Line (ATL)
9.0
Total Line
10,000
Simulations
SD W5ATL
Calibrated accuracy at this confidence: 56.0% (2,971 games)
Projected Runs Range 10th – 90th percentile
SD
357
ATL
468
Projected
ATL 6.4 — SD 5.2
Actual
ATL 3 — SD 8
Pick Results
SD @ ATL F5 OVER 5.5f5WIN+1.10u
Starting Pitcher Matchup
Walker Buehler R
SD
usagewhiffbar labels show usage · mph
FC23%90 mph19% whiff
FF21%94 mph10% whiff
SI17%94 mph7% whiff
Reynaldo López R
ATL
usagewhiffbar labels show usage · mph
FF55%94 mph14% whiff
SL30%84 mph30% whiff
CU12%74 mph21% whiff
Weather Impact
Truist Park
91°F10 mph wind
HR: 1.022 Total: 1.009
thin air, 7mph in
Bullpen Comparison
SD
3.15ERA
3.66FIP
8.41K/9
3.44BB/9
1.23WHIP
ATL
2.18ERA
2.83FIP
9.74K/9
2.51BB/9
1.00WHIP
Betting Edges
RUN_LINE AWAY +1.5
-41.2% EV
-161
TOTAL UNDER 9.0
-26.3% EV
-115
TOTAL OVER 9.0
+18.2% EV
-105
F5 OVER 5.5
+17.6% EV
+110
F5_ML AWAY
-13.2% EV
+116
RUN_LINE HOME -1.5
+8.2% EV
+132
First 5 Innings & NRFI
SD F5
2.9 runs
34.9% win
ATL F5
3.9 runs
54.5% win
F5 Total
6.8
NRFI
43.8%
YRFI
56.2%
Avg 1st Inn Runs
1.40
HR Spotlight
Avg HRs
2.9
Over 0.5 HR
93%
Over 1.5 HR
77%
No HR
7%
Matt Olson ATL30.0%
ISO: 0.283 | Barrel: 14.3% | vs Walker Buehler | Platoon: 1.12x
Luis Campusano SD29.9%
ISO: 0.090 | Barrel: 9.0% | vs Reynaldo López
Michael Harris II ATL29.5%
ISO: 0.227 | Barrel: 9.1% | vs Walker Buehler | Platoon: 1.12x
Pitcher Strikeout Projections
Walker Buehler
0.0 K projected
SD | K/9: 0.0
Reynaldo López
0.0 K projected
ATL | K/9: 0.0
Injury Report
SD8 injured
Nick Pivetta SP60-DAY-IL
Miguel Andujar DH10-DAY-IL
Joe Musgrove SP60-DAY-IL
David Morgan RP15-DAY-IL
Samad Taylor LF10-DAY-IL
Jason Adam RP15-DAY-IL
+2 more
ATL8 injured
Spencer Schwellenbach SP60-DAY-IL
Ronald Acuna Jr. RF10-DAY-IL
Martin Perez SP15-DAY-IL
AJ Smith-Shawver SP60-DAY-IL
Sean Murphy C60-DAY-IL
Spencer Strider SP60-DAY-IL
+2 more
AI Intelligence Analysis
LEAN +1
Model 60.6% OVER 9.0 (11.59 total, +18.2% edge) with hot weather (91F) + 7mph into wind (but park neutral 1.0x) = modest support. SP: Reynaldo Lopez (C+, 3.78 ERA, 8.0 K/9, 0.285 stuff) vs Walker Buehler (B-, TBD ERA, 7.8 K/9, 0.271 stuff) — both similar grades but Lopez established 3.78 ERA > Buehler reliability. Weather 91F + low humidity (48%) + slight headwind offset suggests true total closer to 10.5-11.0 vs 9.0. F5 OVER 5.5 at +17.6% edge (56% prob) suggests first 5 innings hot. ATL bullpen elite (2.18 ERA, 9.74 K/9 — best in slate), SD bullpen strong (3.15 ERA) — may suppress back-end runs. 18% edge solid, not extreme.
Key Factors
- SP comparison: Lopez (3.78 ERA, C+ grade, 0.285 stuff score) vs Buehler (TBD ERA, B- grade, 0.271 stuff — essentially tied despite different grades). Lopez proven, Buehler coming off injury (typical for late July returns)
- Weather supports totals: 91F hot + low humidity (48%) = +0.4 runs added; 7mph into wind slightly suppresses but net positive
- ATL bullpen ELITE (2.18 ERA, 9.74 K/9) — best in entire slate. Late-game suppression likely, limiting total potential
- F5 OVER 5.5 edge +17.6% (56% prob) = first-inning hot expected; full game cools with elite ATL relief
- Park-adjusted total with Truist's 1.0x multiplier likely 10.5-11.0 vs market 9.0
Risk Factors
- ATL bullpen so elite (2.18 ERA, K/9 9.74) that late-game may cool rapidly — full-game OVER 9.0 faces headwind from back-end suppression
- Buehler returning from injury (history of elbow issues) — may not have full stuff
- historically mixed offers no support; model 60.6% win prob on OVER is near 60-65% weak historical support
Edge Analysis
Moneyline
ATL 56.9%
+8.2 pts
Run Line
-1.5
+8.2 pts
Total
9.0
+18.2 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 →