PIT vs HOU prediction for June 4, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects HOU 5.3 - PIT 5.3. HOU is favored with a 52.7% win probability. The run line is 1.5 and the total is 8.5. Model projects 10.7 total runs.
HOU
5.3
Projected Score
VS
O/U 8.5
PIT
5.3
Projected Score
Win Probability
HOUPIT
+1.5
Run Line (HOU)
8.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 55.5% (1,970 games)
Projected Runs Range 10th – 90th percentile
PIT
357
HOU
357
Projected
HOU 5.3 — PIT 5.3
Actual
HOU 1 — PIT 5
Starting Pitcher Matchup
Jared Jones R
PIT
FF36%99 mph26% whiff
SL26%89 mph22% whiff
CH20%93 mph50% whiff
Kai-Wei Teng R
HOU
ST36%85 mph33% whiff
FF26%94 mph15% whiff
SI18%94 mph15% whiff
Weather Impact
Minute Maid Park
78°F5 mph windRoof: retractable
HR: 1.046 Total: 1.024
neutral
Bullpen Comparison
PIT
4.20ERA
4.14FIP
9.42K/9
4.44BB/9
1.34WHIP
HOU
4.75ERA
4.64FIP
8.32K/9
5.15BB/9
1.40WHIP
Betting Edges
RUN_LINE HOME +1.5
-32.3% EV
-185
TOTAL UNDER 8.5
-27.0% EV
-118
TOTAL OVER 8.5
+18.7% EV
-104
F5_ML AWAY
-15.2% EV
-120
RUN_LINE AWAY -1.5
-8.2% EV
+152
ML AWAY
-7.3% EV
-106
First 5 Innings & NRFI
PIT F5
2.7 runs
38.8% win
HOU F5
3.1 runs
48.4% win
F5 Total
5.8
NRFI
45.4%
YRFI
54.6%
Avg 1st Inn Runs
1.25
HR Spotlight
Avg HRs
2.7
Over 0.5 HR
93%
Over 1.5 HR
74%
No HR
7%
Yordan Alvarez HOU30.0%
ISO: 0.310 | Barrel: 19.2% | vs Jared Jones | Park: 0.99x Platoon: 1.12x
Christian Walker HOU30.0%
ISO: 0.254 | Barrel: 14.4% | vs Jared Jones | Park: 0.99x
Brandon Lowe PIT21.6%
ISO: 0.323 | Barrel: 15.6% | vs Kai-Wei Teng | Park: 0.99x Platoon: 1.12x
Pitcher Strikeout Projections
Jared Jones
0.0 K projected
PIT | K/9: 0.0
Kai-Wei Teng
0.0 K projected
HOU | K/9: 0.0
Injury Report
PIT7 injured
Chris Devenski RP15-DAY-IL
Konnor Griffin SS10-DAY-IL
Joey Bart C10-DAY-IL
Anthony Solometo SPDAY-TO-DAY
Oddanier Mosqueda RPDAY-TO-DAY
Mike Clevinger RPDAY-TO-DAY
+1 more
HOU8 injured
Yainer Diaz C10-DAY-IL
Brandon Walter SP60-DAY-IL
Bennett Sousa RP15-DAY-IL
Lance McCullers Jr. SP15-DAY-IL
Cristian Javier SP60-DAY-IL
Jose Altuve 2B10-DAY-IL
+2 more
AI Intelligence Analysis
NEUTRAL -2YELLOW ZONE50.1% WR (n=303)
DATA INTEGRITY FAILURE: Jared Jones listed with 11.21 ERA (career catastrophic) but B+ grade (0.667) and 28.6% K rate (elite). Profile is internally inconsistent. Model projects HOU 52.7% despite massive Teng (2.78 ERA) vs Jones (11.21 ERA) pitcher gap — model should project 65%+ if Jones is actually pitching. Cannot reliably analyze until Jones's status is confirmed as healthy/accurate.
Key Factors
- CRITICAL: Jared Jones 11.21 ERA is catastrophically high. If accurate, HOU should be 70%+ favorite, not 52.7%. If inaccurate (data error or returning from injury), model cannot assess properly.
- Pitcher gap if real: Teng 2.78 ERA vs Jones 11.21 ERA = 8.43 ERA gap (largest on slate). This should be HOU domination.
- Over edge conflict: Model 18.7% over edge on 8.5 total conflicts with elite home pitcher (Teng 2.78 ERA) that should drive unders.
- Inconsistent profile: Jones B+ grade (0.667) + 28.6% K rate suggests he's actually a quality pitcher, but 11.21 ERA suggests disaster. Internal conflict.
- Market skepticism: -109 HOU is tight, suggesting market doesn't trust the pitcher quality gap (likely knowing Jones status uncertainty)
Risk Factors
- Data integrity: Cannot assess game without clarity on Jones. Is he injured? Returning? Just had a bad stretch? Current data is unusable.
- High edge trap: 18.7% over edge is large and triggers overconfidence pattern (high edge + high prob = worst WR).
- Model failure: If Jones actually has 11.21 ERA and is healthy, model projecting only 52.7% HOU is severe underfitting. If Jones data is wrong, model is garbage. Either way, unreliable.
DATA INTEGRITYHIGH EDGE WARNINGCALIBRATION FAILURE
Edge Analysis
Moneyline
HOU 52.7%
-32.3 pts
Run Line
+1.5
-32.3 pts
Total
8.5
+18.7 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 →