MLB Baseball

ARI vs LAD Prediction

July 12, 2026

10,000 Monte Carlo simulations

FINAL: LAD 3 — ARI 5. Our Monte Carlo simulation projected LAD 5.1 - ARI 3.8 (LAD at 58.2% win probability). The run line is -1.5 and the total is 9.5. Model projects 9.0 total runs.

LAD
5.1
Projected Score
VS O/U 9.5
ARI
3.8
Projected Score
Win Probability
58.2%
41.8%
LADARI
-1.5
Run Line (LAD)
9.5
Total Line
10,000
Simulations
ARI W5LAD L5
Calibrated accuracy at this confidence: 56.9% (2,790 games)

Projected Runs Range 10th – 90th percentile

ARI
246
LAD
357
FINALLAD 3 — ARI 5
Projected
LAD 5.1 — ARI 3.8
Actual
LAD 3 — ARI 5

Pick Results

ARI @ LAD NRFInrfiLOSS-0.50u

Starting Pitcher Matchup

Mitch Bratt L
ARI
FF39%92 mph10% whiff
SV32%81 mph20% whiff
SL22%88 mph57% whiff
Emmet Sheehan R
LAD
FF43%94 mph25% whiff
SL31%87 mph39% whiff
CH16%86 mph22% whiff

Weather Impact

Dodger Stadium
82°F5 mph wind
HR: 1.016 Total: 1.006
thin air

Bullpen Comparison

ARI
3.28ERA
3.68FIP
8.28K/9
3.10BB/9
1.10WHIP
LAD
3.58ERA
3.45FIP
10.00K/9
3.64BB/9
1.19WHIP

Betting Edges

RUN_LINE AWAY +1.5
-43.9% EV
-118
TOTAL OVER 9.5
-20.5% EV
-108
TOTAL UNDER 9.5
+11.1% EV
-112
ML HOME
-10.9% EV
-227
ML AWAY
+9.9% EV
+188
F5_ML HOME
-5.4% EV
-208

First 5 Innings & NRFI

ARI F5
2.2 runs
31.8% win
LAD F5
3.2 runs
55.8% win
F5 Total
5.4
NRFI
50.4%
YRFI
49.6%
Avg 1st Inn Runs
1.10

HR Spotlight

Avg HRs
2.5
Over 0.5 HR
91%
Over 1.5 HR
70%
No HR
9%
Ketel Marte ARI30.0%
ISO: 0.162 | Barrel: 13.5% | vs Emmet Sheehan | Park: 0.92x Platoon: 1.12x
Shohei Ohtani LAD30.0%
ISO: 0.250 | Barrel: 23.4% | vs Mitch Bratt | Park: 0.92x
Corbin Carroll ARI25.4%
ISO: 0.264 | Barrel: 14.5% | vs Emmet Sheehan | Park: 0.92x Platoon: 1.12x

Pitcher Strikeout Projections

Mitch Bratt
0.0 K projected
ARI | K/9: 0.0
Emmet Sheehan
0.0 K projected
LAD | K/9: 0.0

Injury Report

ARI8 injured
Tommy Troy LFDAY-TO-DAY
Ryan Waldschmidt CFDAY-TO-DAY
Zac Gallen SPOUT
Corbin Burnes SP60-DAY-IL
Jordan Lawlar LF10-DAY-IL
Michael Soroka SP15-DAY-IL
+2 more
LAD8 injured
Edwin Diaz RP60-DAY-IL
Blake Snell SP60-DAY-IL
Enrique Hernandez 1B10-DAY-IL
Blake Treinen RP15-DAY-IL
Will Smith C10-DAY-IL
Tyler Glasnow SP60-DAY-IL
+2 more

AI Intelligence Analysis

NEUTRAL -1YELLOW ZONE53.9% WR (n=170)
Model projects 58.2% LAD home win, market implies 69.4% (LAD -227, favorite odds). That's -10.9% edge against home — model disfavors LAD despite heavy market preference. Emmet Sheehan (B, 26.1% K-rate) vs Mitch Bratt (C+, 23.1% K-rate, high 15.4% BB rate) shows home advantage to LAD. However, market's 69.4% is EXTREME; likely indicates public knowledge (lineup, injury, sharp consensus) not reflected in model.

Key Factors

  • Pitcher advantage to LAD: Sheehan (26.1% K-rate, 10.1 K/9) > Bratt (23.1% K-rate, 8-K/9 equivalent)
  • Market extreme: LAD -227 (69.4% implied) vs model 58.2% = -10.9% edge against favorite
  • Recent form: ARI swept LAD in recent series (per ESPN); model may not account for momentum
  • Park factor: LAD 0.92 slightly suppressive, but Ohtani's 30% HR prob suggests power value
  • Total edge: -20.5% on overs (market 9.5, model 41.2%) suggests market very bullish on low-scoring game

Risk Factors

  • DATA INTEGRITY: Model heavily disfavors LAD favorite (-10.9%) vs market consensus. Likely indicates model lag or public information not in sim.
  • ARI just beat LAD in sweep — public recency bias may be driving LAD favorites down (arbitrage opportunity?)
  • Market -227 is extreme favorite pricing; suggests sharp action already moved line
Sharp MoneyAgainst ModelLAD -227 is extreme favorite; market consensus heavily favors LAD. Sharp action likely already priced in, creating closing-line-value risk for contrarians.
DATA INTEGRITYMODEL MARKET CONFLICT

Edge Analysis

Moneyline
LAD 58.2%
+0.5 pts
Run Line
-1.5
+0.5 pts
Total
9.5
+11.1 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. Probabilities are calibrated using Bayesian methods and sized via the Kelly Criterion. Full methodology →

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