Cash Five: 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 lab (neural networks) ›

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 10.11.2025 to 24.10.2026.

Matches per prediction

ObservedExpected
0 Matches120 / 131.7
1 Matches138 / 126.6
2 Matches39 / 37.5
3 Matches3 / 4.0
4 Matches0 / 0.1
5 Matches0 / 0.0

Average: 0.750 matches per prediction – chance gives 0.714.

Deviation from the expectation of chance: chi² = 2.06, p = 0.357. The model hits exactly as often as numbers picked at random.

Model line for the next draw

59131432

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

Latest predictions

DatePredictionMatches
24.10.2026 710112134 0
23.10.2026 514173034 1
22.10.2026 25122930 0
21.10.2026 315273034 1
20.10.2026 2324263234 0
19.10.2026 510121323 1
17.10.2026 1113152431 0
16.10.2026 511132225 0
15.10.2026 57102027 0
14.10.2026 2591326 0
12.10.2026 910112934 1
10.10.2026 610131735 0
07.10.2026 124272830 0
06.10.2026 613192022 1
05.10.2026 811121430 1
03.10.2026 811182830 0
02.10.2026 315242830 1
01.10.2026 611282933 1
30.09.2026 27111723 1
29.09.2026 311182234 1
26.09.2026 316202324 1
25.09.2026 216202335 0
24.09.2026 110152029 0
23.09.2026 25152122 1
22.09.2026 915162735 1
21.09.2026 611152028 1
18.09.2026 116172035 0
16.09.2026 15131623 0
15.09.2026 3461734 1
14.09.2026 511192134 0
12.09.2026 69152124 0
11.09.2026 1620212830 1
10.09.2026 34122134 0
09.09.2026 23182027 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 5 from 35, 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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