MLB Baseball

TEX vs STL Prediction

June 3, 2026

10,000 Monte Carlo simulations

TEX vs STL prediction for June 3, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects STL 4.2 - TEX 5.1. TEX is favored with a 55.9% win probability. The run line is 1.5 and the total is 7.5. Model projects 9.4 total runs.

STL
4.2
Projected Score
VS O/U 7.5
TEX
5.1
Projected Score
Win Probability
44.1%
55.9%
STLTEX
+1.5
Run Line (STL)
7.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 53.1% (2,514 games)

Projected Runs Range 10th – 90th percentile

TEX
357
STL
246
FINALSTL 5 — TEX 3
Projected
STL 4.2 — TEX 5.1
Actual
STL 5 — TEX 3

Starting Pitcher Matchup

MacKenzie Gore L
TEX
FF43%95 mph19% whiff
CU22%82 mph29% whiff
CH11%87 mph30% whiff
Andre Pallante R
STL
FF30%95 mph14% whiff
SL29%88 mph32% whiff
SI19%95 mph10% whiff

Weather Impact

Busch Stadium
82°F6 mph wind
HR: 1.055 Total: 1.030
thin air

Bullpen Comparison

TEX
3.47ERA
4.14FIP
7.47K/9
3.57BB/9
1.23WHIP
STL
4.36ERA
4.35FIP
8.23K/9
4.51BB/9
1.39WHIP

Betting Edges

RUN_LINE HOME +1.5
-43.3% EV
-204
TOTAL UNDER 7.5
-19.6% EV
-106
ML HOME
-14.9% EV
-116
TOTAL OVER 7.5
+10.1% EV
-114
RUN_LINE AWAY -1.5
+8.5% EV
+168
ML AWAY
+7.4% EV
-102

First 5 Innings & NRFI

TEX F5
2.7 runs
44.0% win
STL F5
2.5 runs
41.3% win
F5 Total
5.3
NRFI
52.7%
YRFI
47.3%
Avg 1st Inn Runs
1.03

HR Spotlight

Avg HRs
2.4
Over 0.5 HR
90%
Over 1.5 HR
69%
No HR
10%
Jake Burger TEX30.0%
ISO: 0.185 | Barrel: 11.2% | vs Andre Pallante | Park: 0.98x
Jordan Walker STL30.0%
ISO: 0.318 | Barrel: 16.2% | vs MacKenzie Gore | Park: 0.98x Platoon: 1.12x
Joc Pederson TEX28.9%
ISO: 0.141 | Barrel: 6.9% | vs Andre Pallante | Park: 0.98x Platoon: 1.12x

Pitcher Strikeout Projections

MacKenzie Gore
0.0 K projected
TEX | K/9: 0.0
Andre Pallante
0.0 K projected
STL | K/9: 0.0

Injury Report

TEX8 injured
Corey Seager SS10-DAY-IL
Wyatt Langford LF10-DAY-IL
Chris Martin RP15-DAY-IL
Robert Garcia RP60-DAY-IL
Sam Haggerty LFBEREAVEMENT
Josh Smith 2B10-DAY-IL
+2 more
STL8 injured
Ramon Urias 3B10-DAY-IL
Nathan Church LF10-DAY-IL
Lars Nootbaar LF60-DAY-IL
Packy Naughton RPDAY-TO-DAY
Sem Robberse SPDAY-TO-DAY
Victor Santos RPDAY-TO-DAY
+2 more

AI Intelligence Analysis

LEAN +1YELLOW ZONE45.7% WR (n=9)
Model favors TEX away (54.2% win prob) with 7.4% edge at +110 odds (slight dog). MacKenzie Gore (0.468 B-, 8.0 K/9) vs Andre Pallante (0.443 B-, 8.0 K/9) is a pitcher toss-up (identical K rates, similar grades). The edge comes from TEX offense being slightly better wOBA vs STL in this matchup. Market prices STL at -116 (53.7% implied), model gives TEX 54.2% — only 0.5% swing, so edge is THIN but real. 7.4% edge is in the yellow zone but lower prob (~50-55%) is safer than high-prob edges. LEAN at 0.75 units.

Key Factors

  • SP matchup identical: Gore 0.468 B- (8.0 K/9) vs Pallante 0.443 B- (8.0 K/9) = essentially tied. Edge is NOT pitcher-driven.
  • TEX lineup slightly better wOBA vs STL given injuries (Seager 10-day IL back, Langford 10-day IL forearm limit middle order, but still have depth)
  • Market total 7.5 seems light given park (Busch Stadium park factor 1.0, temp 81.6F warm, 4.6 mph tail wind = 1.03 mult), model 9.38 is reasonable
  • 7.4% ML edge is modest but in yellow zone where sample size is small (9 bets, 45.7% WR) — less reliable

Risk Factors

  • Away underdog RED zone (44.8% WR) = structural disadvantage
  • 7.4% edge is moderate, not strong conviction territory
  • TEX road team dynamics, STL home field effect (~3-4 pts), partially offset model advantage
RED ZONEAWAY UNDERDOGYELLOW ZONEINJURY IMPACTTHIN EDGE

Edge Analysis

Moneyline
TEX 55.9%
-43.3 pts
Run Line
+1.5
-43.3 pts
Total
7.5
+10.1 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 →

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