Daily Lotto: 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.

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 18.12.2025 to 14.10.2026.

Matches per prediction

ObservedExpected
0 Matches131 / 135.2
1 Matches131 / 125.2
2 Matches34 / 35.8
3 Matches4 / 3.7
4 Matches0 / 0.1
5 Matches0 / 0.0

Average: 0.703 matches per prediction – chance gives 0.694.

Deviation from the expectation of chance: chi² = 0.46, p = 0.793. The model hits exactly as often as numbers picked at random.

Model line for the next draw

317202123

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

Latest predictions

DatePredictionMatches
14.10.2026 212162130 1
12.10.2026 25101721 0
11.10.2026 4691025 1
10.10.2026 612192435 0
09.10.2026 214212333 0
08.10.2026 26233136 0
07.10.2026 67232733 0
06.10.2026 513232532 0
04.10.2026 714152126 0
03.10.2026 25121623 0
02.10.2026 57162324 1
01.10.2026 1519252736 1
30.09.2026 314192531 1
29.09.2026 1220303136 0
27.09.2026 1024252933 1
26.09.2026 514172636 0
23.09.2026 1021252628 1
22.09.2026 1314212426 1
21.09.2026 915162336 1
20.09.2026 211142527 1
18.09.2026 1023263135 0
17.09.2026 314152426 1
14.09.2026 512202430 0
13.09.2026 25122431 1
12.09.2026 612233132 0
10.09.2026 514162135 1
09.09.2026 714162324 1
08.09.2026 914203132 0
07.09.2026 1292526 1
06.09.2026 325293134 0
05.09.2026 23122326 1

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 5 from 36, 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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