MLB Baseball

SD vs SF Prediction

May 6, 2026

10,000 Monte Carlo simulations

SD vs SF prediction for May 6, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects SF 2.4 - SD 2.3. SF is favored with a 51.6% win probability. The run line is 1.5 and the total is 8.5. Model projects 4.7 total runs.

SF
2.4
Projected Score
VS O/U 8.5
SD
2.3
Projected Score
Win Probability
51.6%
48.4%
SFSD
+1.5
Run Line (SF)
8.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 53.6% (2,040 games)

Projected Runs Range 10th – 90th percentile

SD
024
SF
024
FINALSF 1 — SD 5
Projected
SF 2.4 — SD 2.3
Actual
SF 1 — SD 5

Starting Pitcher Matchup

Bradgley Rodriguez R
SD
CH42%89 mph44% whiff
SI26%97 mph12% whiff
FF20%98 mph17% whiff
Adrian Houser R
SF
SI44%95 mph6% whiff
CH21%86 mph36% whiff
SL15%88 mph16% whiff

Weather Impact

Oracle Park
65°F3 mph wind
HR: 0.994 Total: 0.996
neutral

Bullpen Comparison

SD
4.28ERA
3.86FIP
8.03K/9
3.53BB/9
1.32WHIP
SF
3.23ERA
3.95FIP
8.47K/9
4.62BB/9
1.32WHIP

Betting Edges

TOTAL OVER 8.5
-59.8% EV
-105
TOTAL UNDER 8.5
+48.4% EV
-115
F5 UNDER 4.5
+44.0% EV
-114
RUN_LINE HOME +1.5
-43.5% EV
-189
NRFI NRFI
+23.5% EV
-118
RUN_LINE AWAY -1.5
-23.5% EV
+155

First 5 Innings & NRFI

SD F5
1.1 runs
32.5% win
SF F5
1.2 runs
37.1% win
F5 Total
2.3
NRFI
72.0%
YRFI
28.0%
Avg 1st Inn Runs
0.48

HR Spotlight

Avg HRs
1.1
Over 0.5 HR
66%
Over 1.5 HR
29%
No HR
34%
Gavin Sheets SD23.8%
ISO: 0.236 | Barrel: 10.7% | vs Adrian Houser | Park: 0.88x Platoon: 1.12x
Casey Schmitt SF18.6%
ISO: 0.298 | Barrel: 14.5% | vs Bradgley Rodriguez | Park: 0.88x
Ramón Laureano SD17.5%
ISO: 0.094 | Barrel: 9.4% | vs Adrian Houser | Park: 0.88x

Pitcher Strikeout Projections

Bradgley Rodriguez
0.0 K projected
SD | K/9: 0.0
Adrian Houser
0.0 K projected
SF | K/9: 0.0

Injury Report

SD8 injured
Jake Cronenworth 2B7-DAY IL
Will Wagner 3B10-DAY-IL
German Marquez SP15-DAY-IL
Bryan Hoeing RP60-DAY-IL
Nick Pivetta SP15-DAY-IL
Joe Musgrove SP15-DAY-IL
+2 more
SF8 injured
Harrison Bader CF10-DAY-IL
Logan Webb SPDAY-TO-DAY
Erik Miller RP15-DAY-IL
Jared Oliva CF60-DAY-IL
Daniel Susac C10-DAY-IL
Jason Foley RP60-DAY-IL
+2 more

AI Intelligence Analysis

LEAN +1YELLOW ZONE50.7% WR (n=236)
Massive pitching mismatch: Rodriguez (away, 1.75 ERA, 20% K, B grade) vs Houser (home, 7.69 ERA, 12% K, C grade) = 5.94 ERA gap in SD's favor. Market sets 8.5 total but model projects 4.69 (3.81 run gap, 48.4% edge on UNDER). This game is fundamentally low-scoring due to elite away SP, cold weather (64.6°F), and Oracle Park's marine layer (-12% run factor = 0.88x multiplier). UNDER 8.5 is the core edge.

Key Factors

  • Elite SP mismatch: Rodriguez 1.75 ERA / 20% K (B grade, elite stuff) vs Houser 7.69 ERA / 12% K (C grade, poor stuff) = 5.94 ERA gap.
  • Park/weather suppression: Oracle Park 0.88x multiplier (marine layer, 2.9 mph in-wind) reduces runs by ~1.5 total vs average ballpark.
  • Cold temperature: 64.6°F suppresses HR distance by 0.3-0.5 runs vs 75°F baseline.
  • Historical SP-driven unders: When ace (sub-2.5 ERA) starts vs poor arm (>7.0 ERA), UNDER edges average 35-45% in cold parks.

Risk Factors

  • Edge >45% = EXTREME. Triggers overconfidence alert. Model could be wrong by 10-15 points due to hidden variables (batter adjustments, bullpen fatigue, lineup changes).
  • TOTAL market DISABLED (grade D). Suggests systematic market inefficiency, not edge opportunity. Recent performance: 49.3% WR on totals.
  • Market set at 8.5 suggests public expects more runs. Possible hidden factor: SD lineup vs Houser historically struggles (need platoon data to check).
EXTREME EDGE WARNING (48.4% under edge, triggers overconfidence review)DISABLED MARKET (TOTAL grade D, 49.3% WR, but F5 GREEN at 57.4%)ELITE SP MISMATCH (5.94 ERA gap, Rodriguez 1.75 vs Houser 7.69)PARK FACTOR STRONG (Oracle 0.88x multiplier, marine layer)WEATHER IMPACT (cold 64°F, in-wind suppression)F5 PREFERENCE (44% edge, F5 totals GREEN zone)

Edge Analysis

Moneyline
SF 51.6%
-43.5 pts
Run Line
+1.5
-43.5 pts
Total
8.5
+48.4 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. Full methodology →

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