MLB Baseball

PHI vs STL Prediction

August 11, 2026

10,000 Monte Carlo simulations

FINAL: STL 2 — PHI 0. Our Monte Carlo simulation projected STL 3.9 - PHI 4.2 (PHI at 51.4% win probability). The run line is 1.5 and the total is 7.5. Model projects 8.0 total runs.

STL
3.9
Projected Score
VS O/U 7.5
PHI
4.2
Projected Score
Win Probability
48.6%
51.4%
STLPHI
+1.5
Run Line (STL)
7.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 51.2% (3,251 games)

Projected Runs Range 10th – 90th percentile

PHI
246
STL
246
FINALSTL 2 — PHI 0
Projected
STL 3.9 — PHI 4.2
Actual
STL 2 — PHI 0

Pick Results

PHI @ STL NRFInrfiWIN+0.42u

Starting Pitcher Matchup

Cristopher Sánchez L
PHI
SI43% · 95
CH38% · 87
SL19% · 86
usagewhiffbar labels show usage · mph
SI43%95 mph10% whiff
CH38%87 mph43% whiff
SL19%86 mph43% whiff
Andre Pallante R
STL
FF32% · 95
SL30% · 88
SI18% · 95
usagewhiffbar labels show usage · mph
FF32%95 mph12% whiff
SL30%88 mph30% whiff
SI18%95 mph10% whiff

Weather Impact

Busch Stadium
98°F11 mph wind
HR: 1.098 Total: 1.052
thin air, 8mph out

Bullpen Comparison

PHI
4.39ERA
3.82FIP
10.38K/9
3.55BB/9
1.35WHIP
STL
4.34ERA
4.37FIP
7.96K/9
4.21BB/9
1.36WHIP

Betting Edges

RUN_LINE AWAY -1.5
-11.9% EV
+106
F5_ML AWAY
-10.7% EV
-164
ML AWAY
-7.0% EV
-154
TOTAL OVER 7.5
-6.1% EV
-120
ML HOME
+5.6% EV
+142
TOTAL UNDER 7.5
-3.6% EV
-102

First 5 Innings & NRFI

PHI F5
2.2 runs
43.9% win
STL F5
2.0 runs
38.4% win
F5 Total
4.2
NRFI
56.8%
YRFI
43.2%
Avg 1st Inn Runs
0.86

HR Spotlight

Avg HRs
2.4
Over 0.5 HR
90%
Over 1.5 HR
68%
No HR
10%
Kyle Schwarber PHI30.0%
ISO: 0.290 | Barrel: 16.6% | vs Andre Pallante | Park: 0.98x Platoon: 1.12x
Bryce Harper PHI25.2%
ISO: 0.319 | Barrel: 14.0% | vs Andre Pallante | Park: 0.98x Platoon: 1.12x
Jordan Walker STL23.5%
ISO: 0.244 | Barrel: 11.8% | vs Cristopher Sánchez | Park: 0.98x Platoon: 1.12x

Pitcher Strikeout Projections

Cristopher Sánchez
0.0 K projected
PHI | K/9: 0.0
Andre Pallante
0.0 K projected
STL | K/9: 0.0

Injury Report

PHI6 injured
Caleb Kilian RP15-DAY-IL
Brad Keller RP60-DAY-IL
Tanner Banks RP60-DAY-IL
Rafael Marchan C10-DAY-IL
Johan Rojas CF60-DAY-IL
Adolis Garcia RF60-DAY-IL
STL2 injured
Ramon Urias 3B60-DAY-IL
Max Rajcic RP60-DAY-IL

AI Intelligence Analysis

NEUTRAL -1
DATA INTEGRITY FLAG: model favors STL home (56.4% win prob) despite PHI's Sánchez (2.86 ERA elite) clearly outpitching STL's Pallante (3.92 ERA) — home field alone doesn't explain a swing this large, especially with extreme hot/windy conditions that should favor scoring, not STL specifically.

Key Factors

  • PITCHER MISMATCH AGAINST STL: Pallante (3.92 ERA, 17.4% K-rate, B- stuff) vs Sánchez (2.86 ERA, 27.7% K-rate, B+ elite stuff). Sánchez has a 1.06 ERA advantage for PHI, yet model still favors STL — model's lean must be attributed to home field/park, not pitching, and that attribution looks too large to trust blindly.
  • Extreme weather: 97.5F (hottest conventional-park game on slate) + 10.6mph wind out = should meaningfully elevate scoring, yet market total (7.5) sits below model (8.01) by only 0.51 — doesn't fully reconcile with the heat.
  • PHI's Sánchez, despite elite ERA, shows modest strikeout upside in game (5.5 K/9 mean) — hittable in aggregate, which may explain some model behavior but not the full STL favorite lean.

Risk Factors

  • Model attribution concern: STL favored despite worse starting pitcher; without a specific, verifiable driver (bullpen gap, lineup wOBA edge) this violates the pitcher attribution sanity check.
  • historical support profitability is weak (a supportive track record) for this home ML profile.
  • Both model and market agree directionally (STL favored) but disagree on magnitude — the disagreement itself is the risk, not a clear opportunity.
Sharp MoneyAgainst ModelMarket has STL even more heavily favored (60.6% implied) than the model (56.4%) — sharp money leaning even harder on STL than our own model does.

Edge Analysis

Moneyline
PHI 51.4%
+1.8 pts
Run Line
+1.5
+1.8 pts
Total
7.5
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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 →
Permanent record: this game page is retired 90 days after the event. The full graded MLB 2026 record — every pick, win rate, units and ROI — lives on the MLB 2026 season report card.

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