MLB Baseball

LAA vs TEX Prediction

July 9, 2026

10,000 Monte Carlo simulations

FINAL: TEX 7 — LAA 6. Our Monte Carlo simulation projected TEX 4.6 - LAA 4.0 (TEX at 55.0% win probability). The run line is -1.5 and the total is 7.5. Model projects 8.5 total runs.

TEX
4.6
Projected Score
VS O/U 7.5
LAA
4.0
Projected Score
Win Probability
55.0%
45.0%
TEXLAA
-1.5
Run Line (TEX)
7.5
Total Line
10,000
Simulations
LAATEX W4
Calibrated accuracy at this confidence: 57.2% (2,789 games)

Projected Runs Range 10th – 90th percentile

LAA
246
TEX
357
FINALTEX 7 — LAA 6
Projected
TEX 4.6 — LAA 4.0
Actual
TEX 7 — LAA 6

Pick Results

LAA @ TEX YRFInrfiWIN+0.60u

Starting Pitcher Matchup

Reid Detmers L
LAA
FF44%94 mph18% whiff
SL33%86 mph33% whiff
CH11%84 mph28% whiff
Nathan Eovaldi R
TEX
FS36%88 mph32% whiff
CU22%76 mph38% whiff
FC21%91 mph27% whiff

Weather Impact

Globe Life Field
97°F14 mph windRoof: retractable
HR: 1.033 Total: 1.015
thin air

Bullpen Comparison

LAA
4.26ERA
4.74FIP
9.10K/9
5.18BB/9
1.42WHIP
TEX
3.60ERA
4.14FIP
7.63K/9
3.27BB/9
1.23WHIP

Betting Edges

RUN_LINE AWAY +1.5
-42.8% EV
-200
F5 OVER 3.5
+11.8% EV
-128
TOTAL UNDER 7.5
-11.8% EV
-118
RUN_LINE HOME -1.5
+11.1% EV
+164
F5_ML AWAY
-8.9% EV
+100
NRFI YRFI
+5.1% EV
+120

First 5 Innings & NRFI

LAA F5
2.2 runs
38.4% win
TEX F5
2.6 runs
47.1% win
F5 Total
4.9
NRFI
49.0%
YRFI
51.0%
Avg 1st Inn Runs
1.10

HR Spotlight

Avg HRs
2.9
Over 0.5 HR
94%
Over 1.5 HR
76%
No HR
6%
Mike Trout LAA30.0%
ISO: 0.241 | Barrel: 15.8% | vs Nathan Eovaldi | Park: 1.02x
Zach Neto LAA30.0%
ISO: 0.200 | Barrel: 14.0% | vs Nathan Eovaldi | Park: 1.02x
Jorge Soler LAA30.0%
ISO: 0.207 | Barrel: 12.7% | vs Nathan Eovaldi | Park: 1.02x

Pitcher Strikeout Projections

Reid Detmers
0.0 K projected
LAA | K/9: 0.0
Nathan Eovaldi
0.0 K projected
TEX | K/9: 0.0

Injury Report

LAA8 injured
Ben Joyce RP60-DAY-IL
Adam Frazier 2B10-DAY-IL
Travis d'Arnaud C60-DAY-IL
Yusei Kikuchi SP60-DAY-IL
Grayson Rodriguez SP15-DAY-IL
Jack Kochanowicz SP60-DAY-IL
+2 more
TEX8 injured
Cody Bradford SP60-DAY-IL
Danny Jansen C10-DAY-IL
Jakob Junis RP15-DAY-IL
Jalen Beeks RP15-DAY-IL
Corey Seager SS10-DAY-IL
Jordan Montgomery SP60-DAY-IL
+2 more

AI Intelligence Analysis

LEAN +1YELLOW ZONE50.1% WR (n=318)
Full-game ML edges are minimal (TEX -3.3%, LAA -4.4%, both negative), but F5 OVER 3.5 shows +11.8% edge (62.8% prob) due to early-game scoring potential in extreme heat (97.4°F highest on slate). Despite 13.9 mph wind IN at retractable Globe Life Field, early innings typically see lighter winds and elevated scoring before conditions suppress. RUN_LINE HOME +11.1% edge (42.1% prob) also playable but less intuitive. Prefer F5 OVER 3.5 for clearest edge with intuitive logic: heat boosts F5 scoring before wind suppression.

Key Factors

  • Nathan Eovaldi (TEX home): B grade, 8.6 K/9, excellent (0.602 overall), modern splitter/curveball mix—strong pitcher
  • Reid Detmers (LAA away): B grade, 8.0 K/9, 4.46 ERA, well-rounded arsenal—comparable quality
  • Pitcher matchup nearly even; no clear SP advantage to either side
  • Temperature 97.4°F (EXTREME, highest on slate) boosts early-game scoring potential; F5 OVER 3.5 +11.8% edge (62.8% prob) captures heat effect before conditions suppress
  • RUN_LINE HOME +11.1% edge also exists but less intuitive; prefer F5 OVER for clarity

Risk Factors

  • Full-game ML edges are negative (both TEX and LAA)—market correctly priced on directional calls
  • 13.9 mph wind IN suppresses scoring mid-to-late; if game extended, full total may not expand as F5 suggests
  • YELLOW zone total at 50.1% WR—zone profitability not strong; edge magnitude (11.8% on F5) is moderate
WEATHER IMPACTF5 ADVANTAGEEXTREME HEAT

Edge Analysis

Moneyline
TEX 55.0%
+11.1 pts
Run Line
-1.5
+11.1 pts
Total
7.5
+2.5 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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