Soccer

Austin FC vs Houston Dynamo Prediction

July 26, 2026

5,000 Monte Carlo simulations

Austin FC vs Houston Dynamo prediction for July 26, 2026: Our Monte Carlo simulation ran 5,000 game iterations and projects Houston Dynamo 1.84 - Austin FC 1.17. Houston Dynamo is favored with a 53.3% win probability. Expected total goals: 3.0..

Houston Dynamo
1.84
Projected Goals
VS 3.0 total
Austin FC
1.17
Projected Goals
Match Outcome Probabilities
53.3%
23%
23.5%
Houston DynamoDrawAustin FC
Calibrated accuracy at this confidence: 60.1% (1,163 games)

Projected Goals Range 10th – 90th percentile

Austin FC
0.41.21.9
Houston Dynamo
1.11.82.6

Expected Goals (xG)

Houston Dynamo1.84
Austin FC1.17
19.9Shots16.0
7.3On Target5.7
6.1Corners5.6

Goal Probabilities

Over 0.5
97.0%
Over 1.5
78.5%
Over 2.5
55.5%
Over 3.5
42.8%
Under 2.5
44.5%
BTTS
61.5%

Most Likely Scores

1-1
11.6%
2-1
9.9%
2-0
8.5%
1-0
8.4%
1-2
6.3%

Match Context

MLSMedium
Houston Dynamo
1.70
Draw
4.13
Austin FC
4.83

AI Intelligence Analysis

NEUTRAL -1
Home ML historically mixed with 23% draw risk undermines edge; market's -175 line reflects sharp response to July 25 3-0 HDN result, likely properly priced.

Key Factors

  • xG gap: +0.67 (HDN 1.84 vs AUS 1.17) — modest advantage not reflecting market overconfidence
  • Model prob 53.3% vs market 65.2% — model 11.9% lower, suggesting market correctly re-rated after 3-0 win
  • Home ML profitability historical support at a supportive track record — weak across sample
  • Draw probability: 23.16% from model — significant outcome that kills ML value despite home preference

Risk Factors

  • Recent result bias: 3-0 HDN win on 7/25 may have overweighted market odds; regression to mean possible
  • Draw acts as LOSS outcome for any moneyline bet — 23% probability is material
Sharp MoneyAgainst ModelMarket has pushed HDN from more modest favorite to -175 following 3-0 win; sharp action evidently with home team.

Edge Analysis

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Edge Analysis
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How this prediction was generated: This page shows output from the Olympus Bets Soccer Monte Carlo engine. Each game is simulated 5,000 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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