Sweden vs Japan prediction for June 25, 2026: Our Monte Carlo simulation ran 5,000 game iterations and projects Japan 1.72 - Sweden 1.15. Japan is favored with a 49.7% win probability. Expected total goals: 2.9..
Japan
1.72
Projected Goals
VS
2.9 total
Sweden
1.15
Projected Goals
Match Outcome Probabilities
JapanDrawSweden
Calibrated accuracy at this confidence: 62.1% (1,107 games)
Projected Goals Range 10th – 90th percentile
Sweden
0.41.11.9
Japan
0.91.72.5
Projected
Japan 1.72 — Sweden 1.15
Actual
Japan 1 — Sweden 1
Expected Goals (xG)
Japan1.72
Sweden1.15
20.4Shots16.5
7.5On Target5.8
6.3Corners5.8
Goal Probabilities
Over 0.5
97.1%
Over 1.5
84.6%
Over 2.5
47.9%
Over 3.5
47.4%
Under 2.5
52.1%
BTTS
62.1%
Most Likely Scores
1-1
12.3%
2-1
9.7%
1-0
9.0%
2-0
8.5%
0-0
6.7%
Match Context
WCHigh
Japan
1.96
Draw
3.52
Sweden
4.37
AI Intelligence Analysis
NEUTRALYELLOW ZONE42.6% WR (n=49)
Home ML is YELLOW zone (42.6% WR) with high draw probability (25.65%) and no clear edge; model (49.72%) and market (51.0%) are essentially aligned, making this a coin flip with draw risk.
Key Factors
- Home ML zone is YELLOW: 42.6% WR (49 bets, z=-1.0). Better than RED but still below 50%. Home ML is systemically disadvantaged.
- Model-market alignment: Model 49.72% vs Market 51.0% (gap only -1.28%). Both sides price Japan as coin flip.
- xG gap favors Japan: Japan 1.72 vs Sweden 1.15 = 0.57 xG advantage (modest, supports slight home favoritism)
- Very high draw probability: 25.65% (model) vs 28.4% (market implied). Market expects more draws than model. Either way, ~26%+ of outcomes are DRAWS, eating into win probability.
Risk Factors
- Draw outcome (26%+ probability) counts as loss for home ML
- Japan's xG advantage (0.57) is moderate, not dominant. Sweden is competitive.
- World Cup is emotionally charged; away team can pull off upset with proper motivation and tactical setup
YELLOW ZONEHIGH DRAW RISKNO EDGEHOME ML MARGINAL
Edge Analysis
Moneyline
Japan 49.7%
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Total
2.9
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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 →