BAL vs HOU prediction for July 17, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects HOU 6.3 - BAL 4.8. HOU is favored with a 58.6% win probability. The run line is 1.5 and the total is 8.5. Model projects 11.2 total runs.
HOU
6.3
Projected Score
VS
O/U 8.5
BAL
4.8
Projected Score
Win Probability
HOUBAL
+1.5
Run Line (HOU)
8.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 57.8% (2,790 games)
Projected Runs Range 10th – 90th percentile
BAL
357
HOU
468
Starting Pitcher Matchup
Dean Kremer R
BAL
FS35%83 mph45% whiff
FF23%93 mph12% whiff
SI16%92 mph15% whiff
Peter Lambert R
HOU
FF31%94 mph17% whiff
CH22%87 mph35% whiff
SL16%86 mph26% whiff
Weather Impact
Minute Maid Park
85°F9 mph windRoof: retractable
HR: 1.036 Total: 1.018
thin air
Bullpen Comparison
BAL
4.34ERA
4.01FIP
8.76K/9
3.44BB/9
1.30WHIP
HOU
4.13ERA
4.29FIP
8.50K/9
4.68BB/9
1.32WHIP
Betting Edges
TOTAL UNDER 8.5
-30.8% EV
+100
RUN_LINE AWAY -1.5
-29.2% EV
+140
F5_ML AWAY
-20.7% EV
-106
TOTAL OVER 8.5
+19.1% EV
-122
RUN_LINE HOME +1.5
-14.5% EV
-169
ML AWAY
-13.0% EV
-104
First 5 Innings & NRFI
BAL F5
2.7 runs
33.8% win
HOU F5
3.7 runs
54.6% win
F5 Total
6.4
NRFI
48.3%
YRFI
51.7%
Avg 1st Inn Runs
1.21
HR Spotlight
Avg HRs
2.8
Over 0.5 HR
93%
Over 1.5 HR
75%
No HR
7%
Pitcher Strikeout Projections
Dean Kremer
0.0 K projected
BAL | K/9: 0.0
Peter Lambert
0.0 K projected
HOU | K/9: 0.0
Injury Report
BAL8 injured
Blaze Alexander 3B10-DAY-IL
Keegan Akin RP60-DAY-IL
Ryan Helsley RP15-DAY-IL
Felix Bautista RP60-DAY-IL
Colin Selby RP60-DAY-IL
Chris Bassitt SP15-DAY-IL
+2 more
HOU8 injured
Mike Burrows SP15-DAY-IL
Brice Matthews CFDAY-TO-DAY
Ronel Blanco SP60-DAY-IL
Bennett Sousa RP60-DAY-IL
Hayden Wesneski SP60-DAY-IL
Kai-Wei Teng RP15-DAY-IL
+2 more
AI Intelligence Analysis
Edge Analysis
Moneyline
HOU 58.6%
-14.5 pts
Run Line
+1.5
-14.5 pts
Total
8.5
+19.1 pts
More Projections Today
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 →