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10eLotto Extra Autocorrelation Analysis

10eLotto Extra: do draws have "memory"? Are results correlated between draws?

Autocorrelation shows whether the results of draw N are related to draw N-1, N-2, and beyond. If significant autocorrelation is detected, it's a valuable signal for forecasting. If not, it confirms the randomness of the "10eLotto Extra" lottery.

Analysis based on 20 draws from 04/22/2026, 10:00 PM to 05/25/2026, 10:00 PM

Max lag:

Draw sums autocorrelation

Correlogram with 95% confidence intervals

Observations

Significant lags

±0.4383

95% confidence interval

No autocorrelation detected

All ACF values are within the 95% confidence interval. The sequence is statistically random.

ACF(1) for All Numbers

Autocorrelation at lag 1 — quick overview of each number's "memory"

Ball	ACF(1)	Status
1	-0.2000	Normal
2	0.0500	Normal
3	-0.0553	Normal
4	-0.1167	Normal
5	-0.1167	Normal
6	0.0500	Normal
7	0.1833	Normal
8	0.2069	Normal
9	-0.1167	Normal
10	-0.1265	Normal
11	0.0500	Normal
12	-0.0553	Normal
13	-0.1167	Normal
14	-0.1167	Normal
15	-0.1405	Normal
16	-0.2833	Normal
17	-0.1167	Normal
18	0.0000	Normal
19	-0.1167	Normal
20	-0.1265	Normal
21	-0.0167	Normal
22	-0.2119	Normal
23	-0.1167	Normal
24	-0.1167	Normal
25	-0.0553	Normal
26	-0.2000	Normal
27	-0.0553	Normal
28	-0.0553	Normal
29	0.4389	Significant
30	0.0500	Normal
31	-0.2000	Normal
32	0.0000	Normal
33	-0.2687	Normal
34	-0.1265	Normal
35	-0.1265	Normal
36	0.0500	Normal
37	-0.2625	Normal
38	-0.0553	Normal
39	-0.1167	Normal
40	-0.2625	Normal
41	-0.1167	Normal
42	0.1125	Normal
43	-0.0553	Normal
44	-0.0553	Normal
45	-0.1853	Normal
46	0.2069	Normal
47	0.1125	Normal
48	0.0500	Normal
49	-0.2000	Normal
50	-0.1853	Normal
51	-0.1375	Normal
52	-0.1265	Normal
53	-0.0833	Normal
54	-0.1167	Normal
55	-0.3500	Normal
56	-0.0833	Normal
57	0.4389	Significant
58	0.0000	Normal
59	0.0500	Normal
60	0.0976	Normal
61	-0.1167	Normal
62	-0.1265	Normal
63	-0.1853	Normal
64	-0.1853	Normal
65	0.4389	Significant
66	-0.1853	Normal
67	0.3167	Normal
68	-0.2625	Normal
69	-0.6773	Significant
70	-0.0553	Normal
71	-0.0833	Normal
72	0.0500	Normal
73	0.1833	Normal
74	0.4500	Significant
75	-0.2833	Normal
76	-0.0167	Normal
77	-0.1265	Normal
78	0.0500	Normal
79	-0.1167	Normal
80	0.0500	Normal
81	-0.2833	Normal
82	-0.0553	Normal
83	0.0000	Normal
84	-0.1405	Normal
85	0.2643	Normal
86	-0.1853	Normal
87	-0.0833	Normal
88	0.1125	Normal
89	-0.1853	Normal
90	-0.2625	Normal

About Autocorrelation

Mathematical foundations

The autocorrelation function (ACF) measures the linear dependence between values of a time series separated by k steps (lag). In the context of a lottery: is the result of draw N related to the result of draw N-k?

ACF Formula

ACF(k) = Σ(xₜ - x̄)(xₜ₊ₖ - x̄) / [n · Var(x)]

ACF values range from -1 to +1. If |ACF| exceeds the confidence interval ±1.96/√n, the correlation is statistically significant.