Every prediction is saved before the match and compared with the result.
In short
Over 25 matches the model got the outcome (1, X or 2) right 56% of the time. Always picking a home win would be right about 44% of the time. Its percentages are 9% less wrong than those taken from league averages alone.
With fewer than 30 matches this is only a first look: the numbers can change a lot.
How the last round went
23 October – 25 October · outcome right 5 out of 9 (56%) · exact score right 1 time
The surprises
The best predictions
14 correct predictions out of 25. Last 12: 6 correct. More matches are needed before judging form.
Real results are needed to calculate a reliable score. No correction is applied.
Lab · look back
25 predictionsComparison on predictions actually saved before the result. No prediction is rebuilt after the fact.
Model quality
The model is 9% less wrong than the simple method. With 25 matches the figure is still shaky: it needs at least fifty matches, ideally a hundred.
When I say 60%, does it happen?
Each point is a band of predictions (the number next to it says how many matches). The closer the points are to the dashed line, the more reliable the percentages.
If "Stated" and "Actual" are close, the percentages are reliable.
Does the news help?
Over 14 matches: with the news the error is 0.39, with statistics alone 0.39. Too early to say. Outcome right: 7 of 14 with the news, 7 of 14 with statistics alone.
New model or old?
Over 25 matches, statistics only: error 0.39 for the current model, 0.41 for the first version. Too early to say.
Reliability by market
A 0–100 indicator built from calibration and Brier score. It is descriptive, not a guarantee of results. The model's picks use the history only when there are at least 10 observations per category.
Sample still too small: the system keeps collecting data without changing the model's probabilities.