Lotto Plus 1: AI prediction and backtest – what are "statistical" lines worth?

Two honest experiments on the real draws: we compare random Quick Pick lines with "hot" lines built from the most frequent numbers, and we let a learning algorithm (k nearest neighbours) predict each draw, always using only the data known before the draw. Both methods are compared with the exact expectation of pure chance.

Backtest: Quick Pick lines vs hot lines (12 months)

For each of the 105 draws from 15.10.2025 to 14.10.2026, each group plays 10 lines: random Quick Pick versus lines built from the 15 most drawn numbers over the previous 100 draws. The Bonus ball are random in both groups so that only the main numbers are compared. 1,050 lines per group in total.

MatchesQuick PickHotExpected by chance
0512525483.1
1398394424.2
2125121126.2
3151015.7
4000.8
5000.0
6000.0

Wins by tier

TierMatchesQuick PickHotExpected by chance
16 Matches000.00
25 Matches + Bonus ball000.00
35 Matches000.01
44 Matches + Bonus ball000.03
54 Matches000.77
63 Matches + Bonus ball311.02
72 Matches + Bonus ball121610.98
83 Matches12914.64

Result: the difference between the two groups is not statistically significant (chi² = 1.25, p = 0.741). It stays within what pure chance produces for a sample of this size.

AI prediction (k nearest neighbours)

For each draw, the model looks for the 7 past moments whose preceding 3 draws most resembled the current ones and plays the numbers most often drawn next. It is reapplied after every draw and never sees the future. 300 draws evaluated from 29.11.2023 to 14.10.2026.

Matches per prediction

ObservedExpected
0 Matches136 / 138.0
1 Matches123 / 121.2
2 Matches36 / 36.1
3 Matches5 / 4.5
4 Matches0 / 0.2
5 Matches0 / 0.0
6 Matches0 / 0.0

Average: 0.700 matches per prediction – chance gives 0.692.

Deviation from the expectation of chance: chi² = 0.06, p = 0.971. The model hits exactly as often as numbers picked at random.

Model line for the next draw

101421233852

For entertainment only: this line has exactly the same chance as any other.

Latest predictions

DatePredictionMatches
14.10.2026 21213324648 1
07.10.2026 567114452 0
03.10.2026 81327293145 0
30.09.2026 6721263135 1
26.09.2026 71226273546 0
23.09.2026 101822314046 0
19.09.2026 202127293440 1
16.09.2026 72126353752 0
12.09.2026 22728444647 0
09.09.2026 81532374849 0
05.09.2026 111422333746 0
26.08.2026 61722293050 0
22.08.2026 111726484951 1
19.08.2026 3620212246 1
15.08.2026 61316222746 1
12.08.2026 152327444648 1
08.08.2026 4931444850 0
05.08.2026 3812323346 0
29.07.2026 212228303540 0
25.07.2026 41820354650 1
22.07.2026 3626293145 0
18.07.2026 12734404347 0
15.07.2026 469122027 1
04.07.2026 91116283245 0
01.07.2026 151618192629 1
27.06.2026 82127474849 1
24.06.2026 61518224446 1
20.06.2026 81011152740 0
17.06.2026 31622294246 0
13.06.2026 162126274448 0
10.06.2026 81629313446 0
03.06.2026 3531323546 0
30.05.2026 11222353848 0

How it works

A nearest-neighbour model looks for points in time whose last draws resembled the current ones and picks the numbers that followed most often. It is reapplied draw by draw without looking into the future; a backtest additionally compares Quick Picks with lines made of frequent numbers.

Example

For 6 from 52, 0.7 matches per line are expected on average; the model lands exactly there.

Limitations

No model can predict random draws. The page shows this transparently with a chi-squared test.

Frequently asked questions about this tool

Can AI predict lottery numbers?
No. With independent, uniformly distributed draws there is no pattern a model could learn.
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