Mega Millions: 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 21.10.2025 to 20.10.2026, each group plays 10 lines: random Quick Pick versus lines built from the 15 most drawn numbers over the previous 100 draws. The Mega 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
0721690716.6
1284316293.7
2444337.9
3111.8
4000.0
5000.0

Wins by tier

TierMatchesQuick PickHotExpected by chance
15 matches + Mega Ball000.00
25 matches000.00
34 matches + Mega Ball000.00
44 matches000.03
53 matches + Mega Ball000.08
63 matches111.73
72 matches + Mega Ball131.58
81 match + Mega Ball51812.24
90 match + Mega Ball253229.86

Result: the difference between the two groups is not statistically significant (chi² = 2.40, p = 0.494). 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 08.12.2023 to 20.10.2026.

Matches per prediction

ObservedExpected
0 Matches205 / 204.7
1 Matches86 / 83.9
2 Matches8 / 10.8
3 Matches1 / 0.5
4 Matches0 / 0.0
5 Matches0 / 0.0

Average: 0.350 matches per prediction – chance gives 0.357.

Deviation from the expectation of chance: chi² = 0.54, p = 0.764. The model hits exactly as often as numbers picked at random.

Model line for the next draw

915192553

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

Latest predictions

DatePredictionMatches
20.10.2026 1617505155 0
16.10.2026 1120313555 1
13.10.2026 410135057 0
09.10.2026 1232355155 0
06.10.2026 126274663 1
02.10.2026 3452931 0
29.09.2026 3440495568 0
25.09.2026 1821223845 0
22.09.2026 218202759 0
18.09.2026 26313549 0
15.09.2026 224505366 0
11.09.2026 1012173043 1
08.09.2026 2237546166 1
04.09.2026 1011182451 0
01.09.2026 3741596170 1
28.08.2026 720303638 0
25.08.2026 1922444567 0
21.08.2026 1519323663 0
18.08.2026 1237465766 0
14.08.2026 46102163 0
11.08.2026 312414352 0
07.08.2026 1519303852 0
04.08.2026 24334963 0
31.07.2026 1835394855 1
28.07.2026 1049556566 1
24.07.2026 1319626567 0
21.07.2026 736495255 0
17.07.2026 711395967 0
14.07.2026 26283347 1
10.07.2026 1315222549 0
07.07.2026 1020446266 0
03.07.2026 1718244351 0
30.06.2026 1342626667 1
26.06.2026 1336575866 1
23.06.2026 316194658 0
19.06.2026 2427364344 0
16.06.2026 1840435255 0
12.06.2026 1134404251 1
09.06.2026 2439454758 0
05.06.2026 3437384364 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 70, 0.4 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.
▲