Our Prediction Accuracy
We believe in transparency. Here's how our pG predictions actually perform against real match results.
How We Measure Accuracy
Since we predict goals (not bet outcomes), we measure accuracy using Mean Absolute Error (MAE) — the average difference between our predicted goals and actual goals scored.
Understanding MAE
We calculate this error for every prediction, then average across all matches. Lower MAE = more accurate predictions.
Why MAE Instead of Win/Loss %?
We predict goals, not bet outcomes. A "correct" prediction where we said 1.8 pG and the team scored 2 is more meaningful than simply tracking whether a bet would have won. MAE measures the quality of our goal predictions directly.
Current Performance
Based on walk-forward validation across 15,000+ matches in Europe's top 5 leagues:
What These Numbers Mean
Home MAE of 0.71 means our home goal predictions are typically within 0.71 goals of the actual result.
If we predict 1.8 home goals, actual results average between 1.1 and 2.5
Away MAE of 0.64 means our away predictions are slightly more accurate than home predictions.
Away goals are generally lower and less variable, making them easier to predict
Putting These Numbers in Context
Better Than Naive Baselines
Simply predicting league averages (e.g., "every home team scores 1.5 goals") produces MAE around 1.0+. Our model significantly outperforms this baseline.
Validated on Unseen Data
These numbers come from walk-forward validation — predicting matches the model hadn't seen during training. No data leakage or overfitting.
Football Has Inherent Variance
Even a "perfect" model can't predict exact goals. A team with 2.0 xG might score 0-4 goals. Some error is unavoidable — football is chaotic.
MAE Reference Scale
Our current MAE of ~0.67-0.71 places us in the "Good" to "Excellent" range
Verify It Yourself
We don't ask you to trust us blindly. You can verify our accuracy:
Results Page
Our Results page shows predictions alongside actual outcomes. You can see exactly what we predicted vs. what happened for every match.
View ResultsOur Commitment
We publish all predictions before matches and never retroactively change them. What you see is what we predicted. This transparency is fundamental to how we operate.
Honest Limitations
Our model performs well on average, but every prediction system has limitations:
Individual Match Variance
MAE is an average. Individual predictions can be off by more. A match where we predicted 2.0 pG might end with 0 or 4 goals.
No Model is Perfect
We don't capture player injuries, tactical changes, or motivation factors. These can cause predictions to miss significantly on specific matches.
Performance Can Vary
Accuracy varies by league, team type, and time of season. Early season predictions (less data) may be less accurate than mid-season.
Key Takeaways
- We measure with MAE — average error between predicted and actual goals
- Current MAE: ~0.71 (home), ~0.64 (away) — predictions typically within 0.7 goals of actual
- Validated honestly — walk-forward testing on unseen data, no cheating
- Verifiable — check our Results page to see predictions vs. actuals
- Honest about limits — individual matches vary, no model is perfect