Prediction Accuracy
Performance of the model over the last 14 days of completed matches in our dataset. Every number below is computed from settled fixtures, not selected retrospectively.
1X2 hit rate
57.1%
BTTS hit rate
71.4%
Over/under 2.5
77.6%
Brier score
0.574
Sample size
49
How to read these numbers
The 1X2 hit rate counts how often the highest-probability outcome was the outcome that occurred. Realistic figures for football sit between 45% and 55%; anything advertised far above that range across a large sample should be treated with caution.
BTTS and over/under are two-way markets, so a coin flip scores 50%. A model needs to beat that meaningfully and consistently to be adding value.
The Brier score measures calibration rather than raw hits: it compares each probability issued against what actually happened, and lower is better. It is the fairest single number for judging a probabilistic model, because it penalises confident mistakes more than cautious ones.
Sample size is shown deliberately. A hit rate over a small number of matches carries large error bars, and short-term swings in either direction are expected even from a well-calibrated model.