Croatia vs Panama prediction for June 23, 2026: Our Monte Carlo simulation ran 5,000 game iterations and projects Panama 1.07 - Croatia 1.98. Croatia is favored with a 58.4% win probability. Expected total goals: 3.1..
Panama
1.07
Projected Goals
VS
3.1 total
Croatia
1.98
Projected Goals
Match Outcome Probabilities
PanamaDrawCroatia
Calibrated accuracy at this confidence: 82.0% (1,103 games)
Projected Goals Range 10th – 90th percentile
Croatia
1.22.02.8
Panama
0.31.11.8
Projected
Panama 1.07 — Croatia 1.98
Actual
Panama 0 — Croatia 1
Expected Goals (xG)
Panama1.07
Croatia1.98
19.3Shots17.4
7.0On Target6.2
6.2Corners6.0
Goal Probabilities
Over 0.5
97.3%
Over 1.5
84.0%
Over 2.5
56.3%
Over 3.5
43.5%
Under 2.5
43.7%
BTTS
61.3%
Most Likely Scores
1-1
11.0%
1-2
10.1%
0-2
9.4%
0-1
8.7%
1-3
6.7%
Match Context
WCHigh
Panama
7.50
Draw
4.60
Croatia
1.49
AI Intelligence Analysis
NEUTRAL -1RED ZONE36.1% WR (n=50)
Away ML RED zone (36% WR); market more bullish on Croatia (67%) than model (58%); draw risk 22%; no edge.
Key Factors
- Away ML RED zone: 36.1% win rate (worst soccer ML category, z=-1.98)
- xG differential: Croatia +0.91 (1.98 vs 1.07) — meaningful advantage, but priced by market
- Market advantage: 67% implied vs 58% model = -8.67% gap AGAINST us
- Draw probability: 22% — substantial, reduces away win chance materially
- Stakes: High — both teams need points in World Cup group stage
Risk Factors
- Away ML BLOCKED — RED zone with z=-1.98 is the worst soccer ML performance
- 22% draw probability + 58% model away win = only true 58% outright win chance
- Market is MORE bullish than model — we're paying too much for Croatia
AWAY ML TRAPDRAW RISKRED ZONEHIGH EDGE WARNINGMODEL MARKET CONFLICT
Edge Analysis
Moneyline
Croatia 58.4%
--
Total
3.1
--
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 →