MLB Baseball

LAA vs HOU Prediction

March 29, 2026

10,000 Monte Carlo simulations

LAA vs HOU prediction for March 29, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects HOU 5.3 - LAA 6.7. LAA is favored with a 57.5% win probability. The run line is -1.5 and the total is 9.0. Model projects 12.0 total runs.

HOU
5.3
Projected Score
VS O/U 9.0
LAA
6.7
Projected Score
Win Probability
42.5%
57.5%
HOULAA
-1.5
Run Line (HOU)
9.0
Total Line
10,000
Simulations
LAAHOU W5
Calibrated accuracy at this confidence: 57.4% (2,040 games)

Projected Runs Range 10th – 90th percentile

LAA
579
HOU
357

Pick Results

Tatsuya Imai OVER 4.5 Ksk_propsLOSS-0.50u

Starting Pitcher Matchup

Jack Kochanowicz R
LAA
SI47%96 mph13% whiff
FF18%96 mph21% whiff
SL15%87 mph25% whiff
Tatsuya Imai R
HOU

Weather Impact

Minute Maid Park
77°F6 mph windRoof: retractable
HR: 1.019 Total: 1.010
neutral

Bullpen Comparison

LAA
4.41ERA
4.84FIP
10.25K/9
6.13BB/9
1.78WHIP
HOU
4.96ERA
5.22FIP
11.90K/9
3.77BB/9
1.32WHIP

Betting Edges

TOTAL UNDER 9.0
-38.6% EV
-115
TOTAL OVER 9.0
+33.3% EV
-105
F5_ML AWAY
+30.5% EV
+138
RUN_LINE HOME -1.5
-29.5% EV
+116
ML AWAY
+29.3% EV
+142
F5_ML HOME
-26.8% EV
-175

First 5 Innings & NRFI

LAA F5
3.0 runs
50.4% win
HOU F5
2.3 runs
34.9% win
F5 Total
5.3
NRFI
54.8%
YRFI
45.2%
Avg 1st Inn Runs
0.98

HR Spotlight

Avg HRs
0.0
Over 0.5 HR
0%
Over 1.5 HR
0%
No HR
0%
Yordan Alvarez HOU25.1%
ISO: 0.120 | Barrel: 15.0% | vs Jack Kochanowicz | Park: 0.99x Platoon: 1.12x
Mike Trout LAA19.3%
ISO: 0.221 | Barrel: 15.0% | vs Tatsuya Imai | Park: 0.99x
Zach Neto LAA19.2%
ISO: 0.204 | Barrel: 15.0% | vs Tatsuya Imai | Park: 0.99x

Pitcher Strikeout Projections

Jack Kochanowicz
0.0 K projected
LAA | K/9: 0.0
Tatsuya Imai
0.0 K projected
HOU | K/9: 0.0

Injury Report

LAA7 injured
Kirby Yates RP15-DAY-IL
Robert Stephenson RP60-DAY-IL
Anthony Rendon 3B60-DAY-IL
Vaughn Grissom 2B10-DAY-IL
Ben Joyce RP15-DAY-IL
Alek Manoah SP15-DAY-IL
+1 more
HOU8 injured
Enyel De Los Santos RP15-DAY-IL
Bennett Sousa RP15-DAY-IL
Josh Hader RP15-DAY-IL
Nate Pearson RP15-DAY-IL
Hayden Wesneski SP15-DAY-IL
Brandon Walter SP60-DAY-IL
+2 more

AI Intelligence Analysis

NEUTRAL -2RED ZONE38.6% WR (n=576)
This game is an analytical disaster: HOU's Tatsuya Imai has zero pitch data (MLB debut), LAA's Jack Kochanowicz is a C+ grade arm (0.322 score, C- stuff), the model shows a 29.3% LAA away edge and 33.3% over edge — both in extreme HIGH_EDGE_WARNING territory that historically resolves against the model at alarming rates.

Key Factors

  • Tatsuya Imai: ZERO pitch data, zero K-rate, zero ERA — complete DATA_INTEGRITY failure; MLB debut
  • Kochanowicz: C+ grade (0.322 overall, C- stuff, 5.8 K/9) — legitimately poor SP quality on road side
  • LAA ML away edge 29.3%: RED zone territory (historical 38.6% WR at ANY away ML) — extreme danger zone
  • Over 9.0 edge 33.3%: both massive edges exceed 9-10% max cap — model is almost certainly overconfident on both
  • Minute Maid Park: 77.2°F, neutral wind — retractable dome, HOU bullpen 4.96 ERA vs LAA 4.41 ERA (both below average)

Risk Factors

  • HOU missing Josh Hader (15-day IL, biceps), Ronel Blanco (15-day IL, elbow) — two of their best arms out; this is why model sees a gap
  • Extreme edge warning: when model shows 29%+ edge on ML, historical WR tracks near 38% not 53%+ — systematic failure pattern
  • ESPN confirms: HOU won 9-7 via Paredes 2-RBI double in 8th — validates model's over lean (16 total runs) but NOT the LAA side
Sharp MoneyAgainst ModelBooks price HOU -166 (home) while model gives LAA 57.5% — a massive model-market conflict suggesting market has significant insider info on Imai's preparation that model lacks.
TBD PITCHERHIGH EDGE WARNINGDATA INTEGRITYMODEL MARKET CONFLICTRED ZONE

Edge Analysis

Moneyline
LAA 57.5%
-29.5 pts
Run Line
-1.5
-29.5 pts
Total
9.0
+33.3 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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