MLB Baseball

ARI vs LAD Prediction

March 28, 2026

10,000 Monte Carlo simulations

FINAL: LAD 3 — ARI 2. Our Monte Carlo simulation projected LAD 5.9 - ARI 3.7 (LAD at 69.4% win probability). The run line is -1.5 and the total is 8.5. Model projects 9.6 total runs.

LAD
5.9
Projected Score
VS O/U 8.5
ARI
3.7
Projected Score
Win Probability
69.4%
30.6%
LADARI
-1.5
Run Line (LAD)
8.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 90.0% (2,040 games)

Projected Runs Range 10th – 90th percentile

ARI
246
LAD
468
FINALLAD 3 — ARI 2
Projected
LAD 5.9 — ARI 3.7
Actual
LAD 3 — ARI 2

Pick Results

ARI @ LAD NRFInrfiLOSS-1.00u

Starting Pitcher Matchup

Eduardo Rodriguez L
ARI
FF47%92 mph19% whiff
CH20%86 mph28% whiff
FC16%89 mph19% whiff
Tyler Glasnow R
LAD
FF34%96 mph18% whiff
CU23%82 mph41% whiff
SL22%90 mph41% whiff

Weather Impact

Dodger Stadium
72°F6 mph wind
HR: 0.997 Total: 0.996
6mph in

Bullpen Comparison

ARI
4.97ERA
4.45FIP
8.60K/9
4.46BB/9
1.59WHIP
LAD
3.22ERA
3.45FIP
10.84K/9
3.76BB/9
1.24WHIP

Betting Edges

RUN_LINE AWAY +1.5
-48.4% EV
-106
TOTAL UNDER 8.5
-19.0% EV
-105
F5 UNDER 4.5
+15.6% EV
-102
NRFI NRFI
+13.4% EV
-104
TOTAL OVER 8.5
+11.6% EV
-115
F5_ML AWAY
-9.4% EV
+186

First 5 Innings & NRFI

ARI F5
1.5 runs
25.4% win
LAD F5
2.6 runs
57.6% win
F5 Total
4.1
NRFI
60.1%
YRFI
39.9%
Avg 1st Inn Runs
0.77

HR Spotlight

Avg HRs
0.0
Over 0.5 HR
0%
Over 1.5 HR
0%
No HR
0%
Shohei Ohtani LAD19.8%
ISO: 0.275 | Barrel: 15.0% | vs Eduardo Rodriguez | Park: 0.92x
Corbin Carroll ARI16.7%
ISO: 0.301 | Barrel: 12.4% | vs Tyler Glasnow | Park: 0.92x Platoon: 1.12x
Will Smith LAD14.2%
ISO: 0.194 | Barrel: 9.2% | vs Eduardo Rodriguez | Park: 0.92x Platoon: 1.12x

Pitcher Strikeout Projections

Eduardo Rodriguez
0.0 K projected
ARI | K/9: 0.0
Tyler Glasnow
0.0 K projected
LAD | K/9: 0.0

Injury Report

ARI8 injured
Blake Walston SP60-DAY-IL
Cristian Mena RP60-DAY-IL
Merrill Kelly SP15-DAY-IL
Lourdes Gurriel Jr. LF10-DAY-IL
Tyler Locklear 1B10-DAY-IL
Adrian Del Castillo C10-DAY-IL
+2 more
LAD8 injured
Brock Stewart RP15-DAY-IL
Jake Cousins RP15-DAY-IL
Evan Phillips RP60-DAY-IL
Blake Snell SP15-DAY-IL
Brusdar Graterol RP15-DAY-IL
Bobby Miller SP60-DAY-IL
+2 more

AI Intelligence Analysis

LEAN +1GREEN ZONE60.1% WR (n=81)
LAD at -238 is correctly priced with Tyler Glasnow (B overall, 10.6 K/9, 29.9% K rate) vs Eduardo Rodriguez (B- overall, C stuff, 8.3 K/9) in a showdown where LAD's lineup power (Ohtani 19.8% HR prob) backs Glasnow and ARI is decimated by injuries (Burnes, Kelly, Walston, multiple relievers) — model gives 69.7% at exactly the market price (-1% edge) confirming this is correctly priced.

Key Factors

  • SP mismatch: Glasnow (B overall, B stuff, 29.9% K rate, 10.6 K/9) vs Rodriguez (B-, C stuff, 20.6% K rate, 8.3 K/9) — quality edge to LAD
  • Model: LAD 69.7% win prob vs market implied 70.4% = -1.0% edge — market perfectly priced; no line value
  • ARI rotation injuries: Burnes (60-day IL elbow), Kelly (15-day IL ribs), Walston (60-day IL), multiple relievers out — severely depleted
  • LAD run line -1.5 at 50.8% model prob — rare quality cover probability for heavy favorite; may be preferred market
  • Home ML GREEN zone (61.9% WR, 539 sample) structurally supports, but model confirms the -238 is fairly priced

Risk Factors

  • ARI injury list is massive — market likely already discounting ARI quality; no informational edge exists here
  • Model total 9.6 vs market 8.5 = 1.1 OVER edge, but LAD park factor 0.92 with 6.4 mph wind blowing in (total_mult 0.996) — Dodger Stadium is not a bandbox; avoid OVER
  • LAD missing Snell, Stone, Miller from rotation (all on IL) — Glasnow carrying disproportionate workload; bullpen could be thin
PITCHER MISMATCHGREEN ZONEDIRECTION CONFIRMED

Edge Analysis

Moneyline
LAD 69.4%
-4.5 pts
Run Line
-1.5
-4.5 pts
Total
8.5
+11.6 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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