MLB Baseball

STL vs OAK Prediction

May 14, 2026

10,000 Monte Carlo simulations

STL vs OAK prediction for May 14, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects OAK 3.9 - STL 3.3. OAK is favored with a 58.3% win probability. The run line is -1.5 and the total is 9.5. Model projects 7.2 total runs.

OAK
3.9
Projected Score
VS O/U 9.5
STL
3.3
Projected Score
Win Probability
58.3%
41.7%
OAKSTL
-1.5
Run Line (OAK)
9.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 57.9% (2,063 games)

Projected Runs Range 10th – 90th percentile

STL
135
OAK
246
FINALOAK 4 — STL 5
Projected
OAK 3.9 — STL 3.3
Actual
OAK 4 — STL 5

Starting Pitcher Matchup

Michael McGreevy R
STL
FF25%91 mph10% whiff
CH20%86 mph33% whiff
SI16%90 mph9% whiff
Jacob Lopez L
OAK
FF34%90 mph12% whiff
SL29%77 mph23% whiff
FC20%86 mph22% whiff

Weather Impact

Oakland Coliseum
72°F6 mph wind
HR: 0.987 Total: 0.991
6mph in

Bullpen Comparison

STL
4.61ERA
4.42FIP
7.99K/9
4.58BB/9
1.40WHIP
OAK
4.12ERA
4.07FIP
8.97K/9
4.42BB/9
1.39WHIP

Betting Edges

RUN_LINE AWAY +1.5
-44.4% EV
-185
TOTAL OVER 9.5
-42.4% EV
-115
TOTAL UNDER 9.5
+35.0% EV
-105
F5 UNDER 5.5
+29.0% EV
-114
NRFI NRFI
+18.2% EV
+114
F5_ML AWAY
-12.9% EV
-108

First 5 Innings & NRFI

STL F5
1.7 runs
35.6% win
OAK F5
2.1 runs
45.8% win
F5 Total
3.9
NRFI
59.1%
YRFI
40.9%
Avg 1st Inn Runs
0.79

HR Spotlight

Avg HRs
2.3
Over 0.5 HR
90%
Over 1.5 HR
66%
No HR
10%
Jordan Walker STL30.0%
ISO: 0.323 | Barrel: 15.2% | vs Jacob Lopez | Park: 0.94x Platoon: 1.12x
Shea Langeliers OAK30.0%
ISO: 0.298 | Barrel: 16.9% | vs Michael McGreevy | Park: 0.94x
JJ Wetherholt STL25.8%
ISO: 0.123 | Barrel: 9.0% | vs Jacob Lopez | Park: 0.94x

Pitcher Strikeout Projections

Michael McGreevy
0.0 K projected
STL | K/9: 0.0
Jacob Lopez
0.0 K projected
OAK | K/9: 0.0

Injury Report

STL8 injured
Lars Nootbaar LF60-DAY-IL
Matt Pushard RP15-DAY-IL
Sem Robberse SPDAY-TO-DAY
Victor Santos RPDAY-TO-DAY
Ixan Henderson SPDAY-TO-DAY
Ramon Urias 3B10-DAY-IL
+2 more
OAK5 injured
Brooks Kriske RP15-DAY-IL
Max Muncy 3B10-DAY-IL
Denzel Clarke CF10-DAY-IL
Jacob Wilson SS10-DAY-IL
Gunnar Hoglund SP60-DAY-IL

AI Intelligence Analysis

NEUTRAL -1YELLOW ZONE50.4% WR (n=250)
Model projects OAK 58.3% despite STL having DOMINANT pitcher advantage (McGreevy 2.35 vs Lopez 6.60 ERA, 4.25 gap). Massive UNDER edge (35%, EXCEEDS 12% calibration cap) signals model overconfidence on underdogs. Game resolved STL 5-4 (away team won as expected, UNDER hit narrowly).

Key Factors

  • Pitcher mismatch MASSIVE: McGreevy (2.35 ERA, 20.5% K, B- grade) >>> Lopez (6.60 ERA, 17.0% K, C grade). 4.25 ERA gap should drive ~15-20% win prob swing to away.
  • Model projects OAK 58.3% despite pitcher disadvantage — RED FLAG indicating model undervalues pitcher quality at home or overvalues home field.
  • UNDER edge 35% EXCEEDS 12% calibration max for ML, 12% for totals — flagged HIGH_EDGE_WARNING. Edges >15% historically 38.1% WR per calibration data.
  • Park factor Oakland 1.0 (neutral) removes park excuse — edge entirely on pitcher + lineup, where away has advantage.
  • Weather mild (71.9F, -5.6 tail wind, 5 mph in) suppresses slightly but not driving edge; pitcher dominates.

Risk Factors

  • Model's 35% UNDER edge is among highest on slate and EXCEEDS calibration standards — should be capped at 12-15%, suggesting 3-4 unit overestimation.
  • Home team lean (OAK 58%) contradicts pitcher data — model potentially overweighting home field advantage or underweighting SP quality gap in this matchup.
  • Actual 9 runs close to market 9.5 (slight under win) but well above model 7.18, suggesting model SIGNIFICANTLY under-projected run potential.
Sharp MoneyAgainst ModelMarket slightly favored away STL at -120 (marginal lean against model's OAK home lean), suggesting sharps recognized pitcher advantage.
RESOLVED GAMEHIGH EDGE WARNINGPITCHER MISMATCH IGNOREDHOME LEAN UNJUSTIFIEDMODEL OVERCONFIDENTAWAY WIN VALIDATES CRITICISM

Edge Analysis

Moneyline
OAK 58.3%
-2.9 pts
Run Line
-1.5
-2.9 pts
Total
9.5
+35.0 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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