Match-Up Lab
Pre-match analysis powered by rating models, historical head-to-head records, and contextual signals.
Pick a Match-Up
Choose any two teams and the rating model will compute win, draw, and loss probabilities along with expected goals.
Rating-Based Prediction
WFS predictor · expected score + venue adjustment · drawn from full historical performance
Key Factors
Rating-model adjustments and contextual signals that could influence the outcome
Only 1 historical meeting(s). Ratings carry the most weight in this prediction.
Jordan keep 37.4% clean sheets vs Switzerland's 24.6%, a 13pp gap that could be decisive in a tight contest.
Both teams are evenly matched in recent form: Switzerland 4/10, Jordan 5/10. A closely contested match is expected.
Jordan have a major tournament title to their name; Switzerland do not. Proven pedigree at the highest level.
12.7% of Jordan's games end goalless, well above the global average, suggesting a low-scoring match.
Combined avg of 2.79 goals per game. Expected total for this match: 2.6 (Over 2.5 probability: 47%).
AI Match-Up Evaluation
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Head-to-Head Record
1 meeting(s) · 2026-2026
Comparative Profile
Era-aware metrics use only games from the last 10 years.
Rating Trajectory (Last 2 Years)
Both teams' rating lines overlaid · convergence / divergence analysis
Rolling Win Rate (20-Game Window)
Rolling win rate comparison · which team is in better current form?
Scenario Modeller
Adjust venue and rating parameters to see how the prediction changes in real time.
Adjust parameters above to see real-time probability changes
Recent Meetings
If they play 100 times
Scoreline distribution from the WFS predictor. Each cell shows how often that score would occur out of 100 simulated games: amber for home wins, slate for draws, violet for away wins.