CWS vs LAA prediction for May 4, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects LAA 3.6 - CWS 4.1. CWS is favored with a 54.1% win probability. The run line is -1.5 and the total is 7.5. Model projects 7.7 total runs.
LAA
3.6
Projected Score
VS
O/U 7.5
CWS
4.1
Projected Score
Win Probability
LAACWS
-1.5
Run Line (LAA)
7.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 53.6% (2,040 games)
Projected Runs Range 10th – 90th percentile
CWS
246
LAA
246
Projected
LAA 3.6 — CWS 4.1
Actual
LAA 0 — CWS 6
Starting Pitcher Matchup
Davis Martin R
CWS
FF26%94 mph19% whiff
FC17%90 mph25% whiff
CH16%89 mph9% whiff
José Soriano R
LAA
SI28%97 mph27% whiff
FF25%98 mph22% whiff
KC25%86 mph44% whiff
Weather Impact
Angel Stadium
64°F11 mph wind
HR: 0.956 Total: 0.973
11mph in
Bullpen Comparison
CWS
5.16ERA
4.91FIP
8.54K/9
5.72BB/9
1.57WHIP
LAA
5.10ERA
4.99FIP
8.58K/9
4.88BB/9
1.39WHIP
Betting Edges
RUN_LINE AWAY +1.5
-28.8% EV
-161
RUN_LINE HOME -1.5
-25.1% EV
+134
F5_ML AWAY
+24.1% EV
+148
F5_ML HOME
-23.6% EV
-189
ML HOME
-19.7% EV
-159
ML AWAY
+18.8% EV
+134
First 5 Innings & NRFI
CWS F5
2.1 runs
43.6% win
LAA F5
1.8 runs
36.8% win
F5 Total
3.9
NRFI
62.4%
YRFI
37.6%
Avg 1st Inn Runs
0.72
HR Spotlight
Avg HRs
2.0
Over 0.5 HR
87%
Over 1.5 HR
60%
No HR
13%
Munetaka Murakami CWS30.0%
ISO: 0.314 | Barrel: 18.5% | vs José Soriano | Park: 0.98x Platoon: 1.12x
Mike Trout LAA30.0%
ISO: 0.280 | Barrel: 16.8% | vs Davis Martin | Park: 0.98x
Jorge Soler LAA28.6%
ISO: 0.253 | Barrel: 13.2% | vs Davis Martin | Park: 0.98x
Pitcher Strikeout Projections
Davis Martin
0.0 K projected
CWS | K/9: 0.0
José Soriano
0.0 K projected
LAA | K/9: 0.0
Injury Report
CWSHealthy
LAA8 injured
Grayson Rodriguez SP15-DAY-IL
Alek Manoah SP15-DAY-IL
Logan O'Hoppe C10-DAY-IL
Yusei Kikuchi SP15-DAY-IL
Ryan Johnson SP15-DAY-IL
Walbert Urena SPDAY-TO-DAY
+2 more
Edge Analysis
Moneyline
CWS 54.1%
-25.1 pts
Run Line
-1.5
-25.1 pts
Total
7.5
+5.1 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. Full methodology →