Enter or load your numbers in the analyzer. The latest draw report describes the actual draw, not your selection.
Explore all statistics — guided topics
These pages describe the history of this game. They do not predict future numbers. Use the selection tool on a page to compare your own numbers.
Numbers and gaps
Start with frequency and gaps: how often each number appeared in the selected historical sample.
Draw structure
Compare sum, parity, endings and range. On a page with a selection comparison, open it to check your numbers.
Relationships and random model
Explore pairs, triples and partners, then the random model. Historical relationships do not improve future odds.
Draws and tools
Read the latest draw report for the actual drawn numbers. Use the analyzer and matching draws for your own selection.
Replay the past, one draw at a time
Before each assessed draw, nine fixed rules select the same number of main numbers using only earlier results. We then count the overlap with the real result. These are explicit selection rules based on analyses, not a claim that every statistic predicts numbers.
The target draw and all later draws are excluded from every calculation. No future selection or recommended numbers are generated. Additional pools are assessed separately below where available.
Actual history: 100 · 21.08.2026 14:00 — 09.10.2026 22:00. Assessed steps: 75 (exploration 45, later assessment 30).
What matched the latest assessed draw?
09.10.2026 22:00 · #111456
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13
15
20
21
23
Calculations used earlier draws only: #108684 — #111330, 27.09.2026 14:00 — 09.10.2026 14:00.
Rule
Earlier selection; ✓ marks overlap
Hits
Most frequent
1
✓
2
✓
3
✓
4
✓
5
✓
8
9
✓
11
14
16
20
✓
22
7 / 12
Least frequent
1
✓
6
7
✓
10
12
13
✓
15
✓
18
19
21
✓
23
✓
24
6 / 12
Longest gaps
2
✓
6
10
12
13
✓
14
16
19
20
✓
22
23
✓
24
4 / 12
Repeats
1
✓
3
✓
4
✓
5
✓
7
✓
8
9
✓
11
15
✓
17
18
21
✓
8 / 12
Partners
1
✓
2
✓
3
✓
5
✓
8
9
✓
11
14
16
17
20
✓
22
6 / 12
Binary rhythm (2 bits)
3
✓
4
✓
5
✓
9
✓
14
15
✓
17
18
19
20
✓
21
✓
22
7 / 12Earlier pattern examples: 2–10; selections with no example: 0.
Binary rhythm (3 bits)
2
✓
3
✓
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✓
5
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9
✓
14
15
✓
17
18
19
21
✓
22
7 / 12Earlier pattern examples: 0–8; selections with no example: 1.
Binary rhythm (4 bits)
3
✓
4
✓
5
✓
6
9
✓
11
12
15
✓
17
18
19
22
5 / 12Earlier pattern examples: 0–5; selections with no example: 4.
Binary rhythm (5 bits)
2
✓
3
✓
4
✓
5
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6
9
✓
11
15
✓
17
18
19
22
6 / 12Earlier pattern examples: 0–5; selections with no example: 6.
More overlaps in one draw describe that draw. They do not establish a dependable method.
Which rules matched more often in this history?
The first 60% of assessed steps form exploration. Its leaders are marked below; the ranking uses only the later 40% assessment period. All rules use the same draws and selection size.
Random-model expectation: 12 × 12 / 24 = 6.000 hits per draw; 30 assessment draws → 180.00 total expected hits.
Rank / rule
Exploration mean
Assessment mean
Difference from model
Assessment total
Whole-period mean
1. Repeats
6.022
6.167
0.167
185
6.080
1. Binary rhythm (2 bits)
5.644
6.167
0.167
185
5.853
1. Binary rhythm (3 bits)
5.889
6.167
0.167
185
6.000
4. Most frequent
5.778
6.133
0.133
184
5.920
5. Least frequentExploration leader (ties possible)
6.267
6.067
0.067
182
6.187
6. Binary rhythm (5 bits)
5.956
5.967
-0.033
179
5.960
7. Partners
5.733
5.933
-0.067
178
5.813
7. Binary rhythm (4 bits)
5.911
5.933
-0.067
178
5.920
9. Longest gaps
5.978
5.833
-0.167
175
5.920
A positive difference is an observation, not statistical proof of an advantage. Comparing nine rules and changing settings after seeing their results increases the risk of finding an accidental leader. Both periods remain retrospective; they are not a preregistered validation.
Accumulated overlap in the later assessment period — Most frequent
Solid line: actual accumulated hits. Dashed line: uniform-model expectation for the same number of draws and selections. The line is not a confidence interval.
X: assessed draws; Y: accumulated hits.
Inspect the latest 20 chronological steps
Target draw
Earlier training IDs
Earlier selection
Hits
09.10.2026 22:00 · #111456
#108684 — #111330
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7 / 12
09.10.2026 14:00 · #111330
#108544 — #111190
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20
22
7 / 12
08.10.2026 22:00 · #111190
#108416 — #111062
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11
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7 / 12
08.10.2026 14:00 · #111062
#106734 — #110922
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6 / 12
07.10.2026 22:00 · #110922
#106730 — #110799
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22
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4 / 12
07.10.2026 14:00 · #110799
#106728 — #110656
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8
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7 / 12
06.10.2026 22:00 · #110656
#106723 — #110527
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4 / 12
06.10.2026 14:00 · #110527
#106721 — #110408
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7 / 12
05.10.2026 22:00 · #110408
#106718 — #110405
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✓
5 / 12
05.10.2026 14:00 · #110405
#106716 — #110403
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9
11
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24
✓
7 / 12
04.10.2026 22:00 · #110403
#106710 — #110400
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8 / 12
04.10.2026 14:00 · #110400
#106708 — #110398
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7 / 12
03.10.2026 22:00 · #110398
#106705 — #110286
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7 / 12
03.10.2026 14:00 · #110286
#106703 — #110145
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7 / 12
02.10.2026 22:00 · #110145
#106700 — #110019
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6 / 12
02.10.2026 14:00 · #110019
#106698 — #109879
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8 / 12
01.10.2026 22:00 · #109879
#106693 — #109751
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6 / 12
01.10.2026 14:00 · #109751
#106691 — #109610
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23
✓
6 / 12
30.09.2026 22:00 · #109610
#106687 — #109485
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7 / 12
30.09.2026 14:00 · #109485
#106685 — #109339
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7 / 12
Which draw properties matched the earlier history?
For each step, we build an empirical range from the earlier window only: sorted positions floor(0.1 × (N−1)) and ceil(0.9 × (N−1)), inclusive. We check whether the later actual property lies inside it. Discrete values and ties can make coverage exceed 80%. These are descriptive ranges, not confidence intervals or number selections.
Property
Earlier median, latest step
Earlier range
Actual latest value
Inside, later assessment
Sum
148
120–169 (N=25)
123 · inside
24/30 · 80.0%
Range
21
20–23 (N=25)
22 · inside
28/30 · 93.3%
Even numbers
6
5–8 (N=25)
3 · outside
26/30 · 86.7%
High numbers
6
4–8 (N=25)
5 · inside
27/30 · 90.0%
Repeats from the preceding draw
6
5–8 (N=24)
8 · inside
23/30 · 76.7%
Band 1–10
5
3–7 (N=25)
7 · inside
28/30 · 93.3%
Band 11–20
5
4–6 (N=25)
3 · outside
24/30 · 80.0%
Band 21–24
2
1–3 (N=25)
2 · inside
30/30 · 100.0%
Properties have different units and are not ranked together by number hits. Bands are 1–10, 11–20, etc.; the final band ends at the pool limit. Repeat examples require a predecessor within the earlier window, so their sample is one draw shorter.
Does the historical leader remain the same?
The later assessment is divided into consecutive, non-overlapping periods. All tied leaders are shown; the final incomplete period remains visible. Periods below 15 draws are marked as small.
Changes in the set of leaders: 1/1 period boundaries.
Period
N
Leaders, including ties
Leader total
25.09.2026 14:00 — 07.10.2026 14:00
25
Binary rhythm (3 bits)
156
07.10.2026 22:00 — 09.10.2026 22:00
5 · small sample
Repeats
35
Changing a period size after seeing the outcome is retrospective fitting. This view does not establish a dependable rule.
Your selection in the same history
Enter your main numbers in the form above or open this view from My number report.
Save this historical assessment
JSON stores settings and calculated results; CSV contains the ranking. The HTML snapshot can be opened without internet and contains the visible assessment, not a new offline calculation. Exports include your entered numbers: share them only deliberately.
Sum of co-occurrence shares with numbers from the last earlier draw. Each partner count is divided by the anchor number’s frequency; self-pairs are excluded.
For each number, take its final two earlier presence bits, find that pattern in the earlier window, and measure how often a 1 followed it. Add two model-weighted pseudo-observations. A pattern without previous examples receives the model baseline.
Uses the final 3 earlier bits and known historical successors, with the same two model-weighted pseudo-observations as the two-bit rule. No earlier examples means the model baseline.
Uses the final 4 earlier bits and known historical successors, with the same two model-weighted pseudo-observations as the two-bit rule. No earlier examples means the model baseline.
Uses the final 5 earlier bits and known historical successors, with the same two model-weighted pseudo-observations as the two-bit rule. No earlier examples means the model baseline.
Sums, parity, ranges and decades describe a whole draw. They cannot fairly be ranked by number overlap without inventing additional selection rules. This page therefore compares only the nine rules defined above. Each independent draw retains the same odds.
Interactive tools
Explore the same data actively. The tools describe history and the random model; they do not predict the next result.
My selection — check its properties against history
This describes the entered selection and its position in the historical sample. It does not increase its chance.
Choose a year, use the slider or start automatic playback. This is a presentation of recorded results, not a forecast.
Open the module to load the available years.
Random-model simulator — see ordinary random variation
Generate independent draws with the rules of this game and compare observed counts with the common expected value. Every run is different.
How to read statistical measures
Random model ?
The random model assumes every number has the same chance of being drawn each time. We compare results against this model to see whether the history departs from it — not to predict the next draw.
Expected value ?
The expected value is the average result we'd see if the numbers were fully random, repeated a great many times. Real history almost always differs from it a little — that alone is nothing unusual.
Deviation ?
Deviation shows how far a value is from what the random model expects, measured in units of typical spread. A value close to zero matches the model; the further from zero, the bigger the difference — but with many numbers compared at once, a few larger deviations are ordinary spread, not a signal.
Percentile ?
The percentile shows what share of results (from the model or from history) fall below the value being checked. Percentile 80 means about 80% of results fall below it and 20% above — it describes a place in the distribution, not a forecast.
Typicality ?
Typicality describes how close a value sits to the centre of the model's or history's distribution — typical values happen often, extreme ones rarely. It's a descriptive comparison and says nothing about what the next draw will bring.