MLB Baseball

LAA vs LAD Prediction

June 6, 2026

10,000 Monte Carlo simulations

LAA vs LAD prediction for June 6, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects LAD 5.4 - LAA 4.2. LAD is favored with a 61.8% win probability. The run line is -1.5 and the total is 8.5. Model projects 9.6 total runs.

LAD
5.4
Projected Score
VS O/U 8.5
LAA
4.2
Projected Score
Win Probability
61.8%
38.2%
LADLAA
-1.5
Run Line (LAD)
8.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 63.3% (2,183 games)

Projected Runs Range 10th – 90th percentile

LAA
246
LAD
357
FINALLAD 9 — LAA 2
Projected
LAD 5.4 — LAA 4.2
Actual
LAD 9 — LAA 2

Starting Pitcher Matchup

Jack Kochanowicz R
LAA
SI38%96 mph15% whiff
CH24%90 mph35% whiff
FF21%96 mph16% whiff
Yoshinobu Yamamoto R
LAD
FS28%91 mph36% whiff
FF26%96 mph23% whiff
FC14%91 mph23% whiff

Weather Impact

Dodger Stadium
68°F7 mph wind
HR: 0.995 Total: 0.995
7mph in

Bullpen Comparison

LAA
4.54ERA
4.86FIP
8.94K/9
5.33BB/9
1.46WHIP
LAD
3.00ERA
3.23FIP
9.69K/9
3.57BB/9
1.11WHIP

Betting Edges

ML AWAY
+36.3% EV
+290
F5_ML AWAY
+31.8% EV
+260
RUN_LINE AWAY +1.5
-29.2% EV
+138
RUN_LINE HOME -1.5
-19.8% EV
-167
F5_ML HOME
-18.2% EV
-345
ML HOME
-16.7% EV
-357

First 5 Innings & NRFI

LAA F5
2.2 runs
34.6% win
LAD F5
3.0 runs
50.9% win
F5 Total
5.2
NRFI
57.0%
YRFI
43.0%
Avg 1st Inn Runs
0.92

HR Spotlight

Avg HRs
2.1
Over 0.5 HR
87%
Over 1.5 HR
62%
No HR
13%

Pitcher Strikeout Projections

Jack Kochanowicz
0.0 K projected
LAA | K/9: 0.0
Yoshinobu Yamamoto
0.0 K projected
LAD | K/9: 0.0

Injury Report

LAA8 injured
Jorge Soler DHDAY-TO-DAY
Vaughn Grissom 2BDAY-TO-DAY
Nolan Schanuel 1B10-DAY-IL
Travis d'Arnaud C60-DAY-IL
Sam Bachman RPDAY-TO-DAY
Ben Joyce RP60-DAY-IL
+2 more
LAD8 injured
Blake Snell SP60-DAY-IL
Evan Phillips RP60-DAY-IL
Bobby Miller SP60-DAY-IL
Gavin Stone SP60-DAY-IL
Brusdar Graterol RP60-DAY-IL
Brock Stewart RP15-DAY-IL
+2 more

AI Intelligence Analysis

NEUTRAL -2YELLOW ZONE52.6% WR (n=38)
LAD -357 ML (78.1% market implied) vs model 65.1% LAD home win prob. Model says LAD edge is only -16.7% (market MORE bullish than model, rare). This is a STRONG AVOID. Yoshinobu Yamamoto (LAD, 3.09 ERA, ace-tier) vs Jack Kochanowicz (LAA, 5.65 ERA, weak back-end starter) is extreme pitcher mismatch favoring LAD. Market has ALREADY priced this to death (-357 is extremely sharp line, indicating professional consensus). Model doesn't see additional edge — just disagrees on coverage. Market is correct. Recommend STRONG SKIP.

Key Factors

  • PITCHER MISMATCH HEAVILY FAVORS LAD: Yamamoto 3.09 ERA (ace) vs Kochanowicz 5.65 ERA (back-end). This is A- vs C+ comparison. LAD has pitcher advantage, exactly the mismatch market has priced.
  • Market LINE is -357: Extremely sharp number indicating professional money consensus. -357 is rarely offered in sports betting — indicates sharp groups have all agreed LAD is best bet and market is enforcing hard closing line.
  • Model confidence 65% < Market confidence 78%. This is upside-down. When market is MORE bullish than model, it usually means model is missing something or market has executed strategy already.

Risk Factors

  • STRONG AVOID: Model disagrees with market on direction, and market is more confident. This is exact opposite of when you want to fade market.
  • High-confidence favorite at extreme odds: LAD -357 has already attracted 99% of available sharp money. Any remaining edge is residual and hard to extract at those odds.
  • Zone shows home ML only 52.6% WR (Yellow). LAD is home favorite and market has -16.7% edge vs model — zone suggests even home favorites at this confidence level underperform.
Sharp MoneyAgainst ModelMarket is MORE bullish LAD (78.1%) than model (65.1%) — massive gap indicates sharp consensus has aggressively backed LAD. Model is LESS confident than market, rare situation.
SHARP OPPOSITIONMODEL MARKET CONFLICTRED ZONE

Edge Analysis

Moneyline
LAD 61.8%
-19.8 pts
Run Line
-1.5
-19.8 pts
Total
8.5
+1.3 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. Probabilities are calibrated using Bayesian methods and sized via the Kelly Criterion. Full methodology →

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