Gaps vs. model Mini Lotto

Do gap lengths look like a geometric distribution?

What would you like to check?

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.

Game: Mini Lotto
Number pool: 42
Selected range: 50 most recent
Draws in the sample: 50
From: 2026-08-12T20:00:00Z
To: 2026-09-30T20:00:00Z
Latest draw in the sample: 2026-09-30T20:00:00Z
Calculated at: 2026-10-01T22:06:29+02:00
Source: Service draw archive
Freshness: Checking…

Draw range

Changing the range in this analysis will be available once the script is enabled — for now you're seeing the range 50.

Gaps between hits and the model

A gap is the number of draws without a given number. The model assumes a constant probability of a hit in every draw, independent of previous results. Only completed gaps are included in the histogram.

Draws in range (N)

Completed gaps (M)

250

Histogram discrepancy (D)

8,271

Distribution of gap lengths

Observed and expected numbers of completed gaps in length buckets.
gap length	observed (O)	expected (E)	contribution
0	26,000	29,762	0,476
1	37,000	26,219	4,433
2	21,000	23,098	0,190
3	14,000	20,348	1,980
4–5	33,000	33,717	0,015
6–8	41,000	36,963	0,441
9–12	33,000	31,774	0,047
13–20	31,000	30,664	0,004
21+	14,000	17,456	0,684

How we calculate this

The probability of hitting one number in a draw is p = 0,11905 (we pick 5 of 42). For a bucket from a to b the model gives (1−p)^a − (1−p)^b+1, and for the 21+ bucket the value (1−p)²¹. The expected E is M times that probability, a row’s contribution is (O − E)² / E, and D is the sum of contributions from buckets with E greater than zero. D is not a significance test: gaps come from many numbers at once and are related to one another, so a high value describes a divergence, it proves no cause. Data computed on 2026-10-01T22:06:29+02:00.

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.

Open the full selection analyzer →

History player — move through past draws

Choose a year, use the slider or start automatic playback. This is a presentation of recorded results, not a forecast.

Year

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.

Number of simulated draws

What do these numbers show?

The histogram covers 250 completed gaps from 50 draws.
The expected values come from a geometric model with a hit probability of 0,11905 per draw.
The D measure sums up the divergence of the histogram from the model. It does not point to a cause and is not a significance test — gaps from many numbers are related to one another.

These are historical data. Each draw is independent of previous draws, so these numbers do not tell us what will be drawn next.

How do I use this page?

Check how many draws (N) and how many completed gaps (M) the table covers.
Compare the observed column with the expected column in the same row.
The contribution shows which bucket departs most from the model.
Read the D measure as a description of the whole histogram's divergence, not as a forecast.

What this page does not do: it does not predict future results and does not improve your chance of winning.

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.

Related analyses

Gap distribution

How long have the gaps between draws of each number typically been, and do they match the model?

Fit to the random model

Do the results deviate from the uniform and independent model?

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