PHI vs SD prediction for May 25, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects SD 3.2 - PHI 3.8. PHI is favored with a 55.9% win probability. The run line is 1.5 and the total is 7.5. Model projects 7.0 total runs.
SD
3.2
Projected Score
VS
O/U 7.5
PHI
3.8
Projected Score
Win Probability
SDPHI
+1.5
Run Line (SD)
7.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 54.0% (2,610 games)
Projected Runs Range 10th – 90th percentile
PHI
246
SD
135
Projected
SD 3.2 — PHI 3.8
Actual
SD 0 — PHI 3
Starting Pitcher Matchup
Jesús Luzardo L
PHI
ST36%86 mph47% whiff
FF26%97 mph13% whiff
CH22%86 mph40% whiff
Griffin Canning R
SD
CH33%90 mph33% whiff
FF24%95 mph26% whiff
SL22%88 mph43% whiff
Weather Impact
PETCO Park
70°F11 mph wind
HR: 0.980 Total: 0.987
7mph in
Bullpen Comparison
PHI
4.48ERA
3.35FIP
10.21K/9
3.24BB/9
1.37WHIP
SD
3.26ERA
3.48FIP
8.35K/9
3.50BB/9
1.22WHIP
Betting Edges
RUN_LINE HOME +1.5
-43.0% EV
-161
TOTAL OVER 7.5
-18.5% EV
-104
TOTAL UNDER 7.5
+8.1% EV
-118
RUN_LINE AWAY -1.5
-7.7% EV
+132
ML HOME
-6.8% EV
+110
F5 UNDER 4.5
+6.4% EV
-141
First 5 Innings & NRFI
PHI F5
2.1 runs
46.4% win
SD F5
1.7 runs
34.8% win
F5 Total
3.9
NRFI
63.8%
YRFI
36.2%
Avg 1st Inn Runs
0.70
HR Spotlight
Avg HRs
1.5
Over 0.5 HR
78%
Over 1.5 HR
44%
No HR
22%
Kyle Schwarber PHI29.0%
ISO: 0.387 | Barrel: 20.0% | vs Griffin Canning | Park: 0.90x Platoon: 1.12x
Bryce Harper PHI26.1%
ISO: 0.300 | Barrel: 14.5% | vs Griffin Canning | Park: 0.90x Platoon: 1.12x
Bryson Stott PHI17.1%
ISO: 0.168 | Barrel: 8.3% | vs Griffin Canning | Park: 0.90x Platoon: 1.12x
Pitcher Strikeout Projections
Jesús Luzardo
0.0 K projected
PHI | K/9: 0.0
Griffin Canning
0.0 K projected
SD | K/9: 0.0
Injury Report
PHI8 injured
Kyle Backhus RP15-DAY-IL
Zach Pop RP15-DAY-IL
Keaton Anthony 1BDAY-TO-DAY
Johan Rojas CFSUSPENSION
Rene Pinto CDAY-TO-DAY
Daniel Robert RPDAY-TO-DAY
+2 more
SD8 injured
Matt Waldron SP15-DAY-IL
German Marquez SP15-DAY-IL
Luis Campusano C10-DAY-IL
Jhony Brito RP60-DAY-IL
Yu Darvish SPOUT
Blake Hunt CDAY-TO-DAY
+2 more
AI Intelligence Analysis
LEAN
Model projects 7.02 total runs (UNDER 7.5, +8.1% edge, 58.4% model prob). Pitcher matchup slightly favors PHI (Luzardo B, 0.607 grade vs Canning B-, 0.456 grade), but both are solid arms (both ~10.7-10.8 K/9). Edge comes from weather: Petco Park (0.9 park factor, -10% run suppression) + wind 11.2 mph IN (additional suppression) + temp 69.6F (slightly cool). Model projects 7.02 runs; market at 7.5 = modest undervalue of run environment (0.48 run gap). UNDER bet requires discipline (totals disabled, grade F), but weather + park factor stack supports play.
Key Factors
- Park factor + weather stack: Petco (0.9 multiplier) + wind 11.2 mph IN (0.987 multiplier per system) + temp 69.6F (slightly cool, minor suppression) = cumulative ~0.89 run multiplier vs neutral baseline. Model 7.02 baseline vs market 7.5 = 0.48 run undervalue.
- Pitcher profile: Luzardo (B, 0.607 grade, 10.8 K/9) is solid premium arm; Canning (B-, 0.456 grade, 10.7 K/9) is comparable. Both have excellent K-rates; likely low-run environment per league trends. No dramatic SP-driven scoring advantage either direction.
- NRFI probability 61.0% (model) — elevated first-inning scoring resistance supports under lean.
- Historical: Both teams play in/near Petco and Oracle (marine layer parks). Expect lower-scoring matches in NL West coastal matchups.
Risk Factors
- TOTALS DISABLED (grade F, 44.9% WR). Extreme caution on ALL total edges, even 8.1%. This is hard filter; consider skipping due to calibration risk alone.
- Edge 8.1% is modest; combined with disabled totals status, risk/reward is poor. Market may be accurately pricing Petco run environment despite park factor.
- Underdog PHI value play (+129 away) may be more interesting (55.6% model prob) than chasing total edge.
WEATHER IMPACTPARK FACTORTOTALS VALUE
Edge Analysis
Moneyline
PHI 55.9%
-43.0 pts
Run Line
+1.5
-43.0 pts
Total
7.5
+8.1 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 →