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
Lebanon keep 29.3% clean sheets vs Yemen's 21.2%, a 8pp gap that could be decisive in a tight contest.
13.6% of Lebanon's games end goalless, well above the global average, suggesting a low-scoring match.
Lebanon's longest unbeaten run is 16 games vs Yemen's 8. Lebanon have shown greater resilience historically.
Combined avg of 2.23 goals per game. Expected total for this match: 2.6 (Over 2.5 probability: 47%).
Yemen are gaining momentum recently (+74 pts). Lebanon have moved -7 pts in the same window.
Lebanon hold a 5-point rating edge: roughly 0.7% extra win probability on ratings alone.
AI Match-Up Evaluation
Sign in to unlock the AI-generated match-up evaluation, predicted winner and editorial verdict.
Head-to-Head Record
5 meeting(s) · 2002-2026
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.