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
Zimbabwe won 4 of their last 10 games; Botswana won 1. Current form favours Zimbabwe.
Zimbabwe hold the historical edge: 11W-5D-6L across 22 meetings.
Zimbabwe have a major tournament title to their name; Botswana do not. Proven pedigree at the highest level.
18.4% of Botswana's games end goalless, well above the global average, suggesting a low-scoring match.
Combined avg of 2.12 goals per game. Expected total for this match: 2.1 (Over 2.5 probability: 36%).
Botswana have won 19% of games entering as underdogs (49W from 254). A strong record against the odds.
AI Match-Up Evaluation
Sign in to unlock the AI-generated match-up evaluation, predicted winner and editorial verdict.
Head-to-Head Record
22 meeting(s) · 2012-2026
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.