Across the last 20 Lotto draws, the Slicing method most often suggests: 32 (7), 31 (6), 33 (4), 5 (3), 21 (3), 35 (3). Data includes draw #214 of 27.06.2026.
The draw’s numbers are sorted in ascending order and cut into two parts: the first k numbers and the rest. Each part’s sum is divided by its count; the resulting averages (both neighboring integers when fractional) are recorded as candidates. The table shows which numbers collect the most such hits.
Slice averages are arithmetic over past draws, not a forecast: every number stays equally likely in the next draw. As a selection system the method works — it compresses each draw into a few characteristic numbers; mark the table leaders and build combinations with the generator.
Slicing Method Calculation Example
Source data:
Draw: 2, 3, 5, 8, 9, 10, 14, 18
Numbers sorted in ascending order
Slicing parameter: 2
First calculation:
Take first 2 numbers: 2 + 3 = 5
Divide by count: 5 ÷ 2 = 2.5
Since 2.5 is not integer, we record numbers 2 and 3
Second calculation:
Take remaining 6 numbers: 5 + 8 + 9 + 10 + 14 + 18 = 64
Divide by count: 64 ÷ 6 = 10.67
Record numbers 10 and 11
Result:
For this draw we get numbers: 2, 3, 10, 11
Each number is assigned frequency 1
Where to next
Draw Sums
The typical sum of a Lotto draw — the raw material Slicing cuts.
OpenSummary Table
Method voting: which numbers several approaches recommend at once.
OpenHot Numbers
The most frequent Lotto numbers — a ready hint with zero setup.
OpenBall Weight
A composite index of frequency and recency — another selection method.
OpenCombination Generator
Turn the marked numbers into combinations in one click.
OpenLotto Slicing Method FAQ
What is the Slicing method in the lottery?
A community-devised selection method: every Lotto draw is "sliced" into two parts, and the averages of their sums become candidate numbers. The name comes from kitchen slicing — the data is cut into pieces. Compare it with other methods on the summary table.
How are the method’s numbers calculated?
The draw’s numbers are sorted; the first k go into the upper slice, the rest into the lower one. Each slice’s sum is divided by its count: an integer result yields one candidate, a fractional one yields two (rounded down and up). A step-by-step example with real numbers is worked out below on the page. The related quantity is the whole draw’s sum.
What does the slice parameter control?
How many numbers go into the first slice (k): at k = 1 the upper slice is the single lowest number of the draw, everything else goes into the second. Changing k changes the averages and the resulting table — compare several values. The draw’s extreme numbers themselves live on the min and max page.
How does Slicing differ from moving averages?
Moving averages smooth a metric over a window of many draws, while Slicing averages the numbers inside a single draw, slice by slice. The shared idea is compressing data to a characteristic level, but the quantities and conclusions differ.
Does the method help you win?
No: every number is equally likely in the next draw, and past slice averages do not change that. The method is useful as a selection system — a way to get a short list of numbers from data rather than guessing. The real odds of every prize tier are openly calculated on the winning odds page.