EuroNumbers Prediction Stats
This page looks at the separate “EuroNumbers engine” from the book.
For each draw, the model produces a set of 6 candidate EuroNumbers.
The real game then draws 2 EuroNumbers out of 12.
We count how many of the 2 landed inside the 6 predicted numbers
(hits = 0, 1, or 2).
To see if the model does better than random, we compare the historical hit frequencies with the theoretical baseline where the 6 numbers were chosen uniformly at random.
Summary vs random play
Based on 3 resolved predictions.
| Hits | Model (empirical) | Random baseline |
|---|---|---|
| 0 hits | 0.000 | 0.227 |
| 1 hit | 0.667 | 0.545 |
| 2 hits | 0.333 | 0.227 |
Probability of getting at least one EuroNumber correct:
Model: 1.000,
Random: 0.773
(lift ≈ 1.29 vs random)
Average number of EuroNumbers hit per prediction:
Model: 1.333,
Random: 1.000
When we only look at perfect EuroNumbers (2/2 inside the 6), the empirical probability is 0.333 compared to 0.227 for random play (lift ≈ 1.47).
Prediction log
Below you can see the full EuroNumbers prediction history used in the stats above.
| # | Draw index | Prediction Date | Predicted set (6 nums) | Actual EuroNumbers | Hits |
|---|---|---|---|---|---|
| 1 | 908 | 2025-12-06 | 11 10 7 1 2 12 | 6 10 | 1 |
| 2 | 909 | 2025-12-09 | 11 7 1 2 12 9 | 2 9 | 2 |
| 3 | 910 | 2025-12-12 | 11 7 1 12 8 3 | 2 11 | 1 |
All of this is descriptive, not a promise. The point is to see whether the EuroNumbers model leans even a little away from pure randomness, and to keep track of that story over time.