🧪 Is Thunderball really random?
We run all 3,029 Thunderball draws since 12.05.2010 through 11 statistical tests. The question: do the draws behave the way pure chance predicts, or are there patterns, “hot” numbers, seasonal effects?
No anomaly: 1 of 11 tests fall below the 5% threshold – pure chance would produce 0.55. After correcting for multiple testing (Holm), no finding remains.
| Test | Finding | p-value | p (Holm) |
|---|---|---|---|
| Uniform numbers Is every number drawn equally often? χ² = 26.1 with 38 df; largest deviation: 14 (z = -1.87). | normal | 0.928 | 1.000 |
| Uniform Thunderball Are all Thunderball drawn equally often? 3,029 draws; χ² = 16.3 with 13 df; largest deviation: 3 (z = 2.30). | normal | 0.231 | 1.000 |
| Seasonal numbers Do some numbers come up more often in certain months? number × month, χ² = 406.9 with 456 df; most extreme cell: 30 in November (z = 3.49). | normal | 0.952 | 1.000 |
| Draw day Do the numbers depend on the day of the draw? number × weekday, χ² = 160.9 with 152 df; most extreme cell: 11 on Saturday (z = 3.17). | normal | 0.294 | 1.000 |
| Stability over time Have the frequencies shifted over the years? 4 periods, χ² = 142.3 with 152 df; largest deviation: 11 in period 3 (z = 2.60). | normal | 0.703 | 1.000 |
| Sum of numbers Do the sums follow the exact distribution? mean sum 100.20 (theoretical 100.00); χ² = 39.4 with 32 df. | normal | 0.173 | 1.000 |
| Even/odd Is the mix of even and odd numbers right? χ² = 11.5 with 5 df. | slightly unusual, not significant after correction | 0.042 | 0.460 |
| Consecutive numbers Do pairs like 12–13 appear as often as expected? 44.0% of draws contain consecutive numbers (theoretical 43.6%). | normal | 0.664 | 1.000 |
| Repeats from previous draw Does a draw depend on the previous one? on average 0.64 numbers of the previous draw come up again (theoretical 0.64). | normal | 0.880 | 1.000 |
| Number pairs Do certain pairs come up together too often? most frequent pair 16 + 26: 60 times (expected 40.9); spread of all pairs compared with 100 random series. | normal | 0.277 | 1.000 |
| Gaps between hits Are a number's absences as long as pure chance predicts? gap distribution compared with 100 simulated random series. | normal | 0.574 | 1.000 |
The latest draw
Draw of 17.10.2026 (9 18 23 27 28) – rarest feature: 2 number(s) repeated from the previous draw; this happens about once every 9 draws.
Almost every draw has some “rare” feature if you look at enough features. That is no sign of manipulation.
Strategies on trial: do frequent or overdue numbers predict anything?
For every draw since 12.05.2010, the test picks numbers using only the earlier draws (last N draws) and counts how many come up in the next draw. The benchmark is what a random selection of the same size hits on average.
Popular strategies
| Strategy | Selection | Hits per draw | expected | ratio | p-value | p (Holm) | |
|---|---|---|---|---|---|---|---|
| … | |||||||
Test your own mix
N1/N2: frequency within the last N draws. N3/N4: current gap (draws since last hit, over the whole history). Overlaps count once.
Distribution of hits per draw
observed expected (chance)
Cumulative excess / shortfall vs. chance
Important: every combination has the same chance in every draw. No strategy can improve the number of hits; test enough variants and you will still find some with p < 5% – that is chance (see above, multiple testing).
How to read the table
The p-value is the probability of a result at least this extreme under pure chance. Below 5%, a single test is usually called “significant”. Because 11 tests run at once, about 0.55 such hits are expected by chance alone; the Holm correction accounts for that. Only a result still below 5% after correction would be a serious hint.
Method
Based on the official draws of the current 5/39 format (since 12.05.2010). Frequency tests: chi-square corrected for drawing without replacement. Pairs and gaps: compared with 100 simulated random series of the same length (Monte Carlo, two-sided). Everything is recalculated after every draw.
Rules & FAQ
Is Thunderball rigged?
The data show no sign of it. 1 of 11 tests fall below 5% (0.55 expected by pure chance), 0 after correcting for multiple testing. The draws behave like those of a fair drawing machine.
Can these tests predict winning numbers?
No. Precisely because the draws pass the tests, there is no exploitable pattern: every combination has the same chance in every draw.
Why is a test sometimes “unusual”?
At the 5% level, one test in twenty fires by pure chance on average. That is why we also show the Holm-corrected p-value, which accounts for the number of tests.