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
Bangladesh won 3 of their last 10 games; San Marino won 0. Current form favours Bangladesh.
Combined avg of 1.11 goals per game. Expected total for this match: 2.6 (Over 2.5 probability: 49%).
Bangladesh hold a 127-point rating edge: roughly 19.1% extra win probability on ratings alone.
Only 1 historical meeting(s). Ratings carry the most weight in this prediction.
Bangladesh keep 25.4% clean sheets vs San Marino's 4.4%, a 21pp gap that could be decisive in a tight contest.
Bangladesh have a major tournament title to their name; San Marino do not. Proven pedigree at the highest level.
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.