AI Verdict
Home Win — 39% probability ★★☆☆☆
- Predicted score: 1-1
- Outlook stable
Confidence: Uncertain · Updated: Thu, Jun 25, 2026 03:00 AM
AI Prediction
Predicted outcome: Home Win (39% probability)
- Home Win: 39%
- Draw: 32%
- Away Win: 29%
Most likely scores: 1-1 (13%), 1-0 (13%), 0-0 (13%)
Predicted scoreline: 1-1
Model Confidence
Confidence Rating: Uncertain (20%)
Very close race — model is uncertain about the ranking
This measures how certain the AI is about the ranking of outcomes (Home Win > Draw > Away Win), not the probability of any single outcome.
Match Pulse
➡️ Outlook stable (LOW CONFIDENCE)
No significant events detected
Prediction Timeline
How the AI's prediction evolved during the match — from kickoff to final whistle.
Prediction Stability: Stable
Prediction remained stable
Probability swing: 0%
Turning Point: N/A' — Model maintained confidence throughout the match
Model maintained confidence throughout the match
In-Match Probability Shifts
- — H: 39% / D: 32% / A: 29% [Kickoff]
- 46' — H: 51% / D: 28% / A: 21% [Goal]
- 57' — H: 63% / D: 24% / A: 13% [Goal]
- 76' — H: 53% / D: 19% / A: 28% [Goal]
Explainable AI Review
After the match, the AI explains why its prediction succeeded or failed.
Predicted: [object Object]
Actual: [object Object]
Prediction Correct? ✅ Yes
What Went Wrong — And Why
The model's prediction held — it expected a home win (39% confidence) but the match ended 2-1. Primary factor: Pre-match injuries affected team performance.
Key Deviations
Where the match numbers diverged from model expectations.
Error Analysis
Primary Reason: Pre-match injuries affected team performance
Error Categories: Injury Impact
Model Performance
How the AI model has performed historically, so you can calibrate your trust in its predictions.
- This match: ✅ Correct — Predicted [object Object], Actual [object Object]
- Track record: The model is evaluated continuously. Visit the Tracking page for Brier scores, calibration curves, and accuracy by league.
- How predictions are made: Our ensemble combines Gradient Boosting + Random Forest with Poisson-based score distributions, trained on historical match data, ELO ratings, and recent form.
Advanced Details
Frequently Asked Questions
- Why is this match so hard to predict?
- With probabilities of Home 39%, Draw 32%, Away 29%, the model considers all outcomes to be closely balanced — this is a genuinely unpredictable matchup.
- How confident is the model in this ranking (Uncertain, 20%)?
- Model Confidence measures how certain the AI is about the order of outcomes, not any single probability. This is a toss-up — the model struggles to separate the outcomes confidently.
- Why was this prediction correct?
- The match unfolded largely as the model expected — key metrics like xG and possession aligned with predictions, and no unexpected events (red cards, injuries) disrupted the forecast.
- How does the AI prediction model work?
- Our ensemble combines Gradient Boosting and Random Forest models trained on historical match data, ELO team ratings, recent form, and statistical metrics. Score distributions use Poisson-based simulations for the most likely scorelines.