What is K-means clustering?

K-means is a machine learning algorithm that automatically groups objects into K clusters by similarity of characteristics. For lottery numbers, three characteristics are used: draw frequency, depth, and average interval.

What do the cluster names mean?

Names are assigned automatically based on average characteristics: "hot stable" — high frequency, low depth; "cold stable" — low frequency, high depth; "warming up" — low overall frequency but low depth (recent appearance).

How many clusters should I choose?

4 clusters is recommended for standard lotteries. For lotteries with many numbers (e.g., 6 out of 49), you can try 5–6 clusters for finer grouping.

Does cluster analysis guarantee a win?

No, cluster analysis is a statistical analysis tool, not a prediction tool. It helps structure information about numbers, but each lottery draw is an independent random event.

Eurojackpot Lottery

Cluster Analysis — Grouping Numbers by Behavior

K-means clustering: combining numbers with similar draw patterns

Cluster analysis groups Eurojackpot lottery numbers by a combination of characteristics: draw frequency, depth (recency of last draw), and average interval. Instead of analyzing individual metrics, you see the complete picture: "hot stable", "cold", "warming up", and other groups.

Analysis based on 20 draws from 01/06/2026, 07:45 PM to 03/13/2026, 07:45 PM

How to Use Cluster Analysis for Eurojackpot

Step-by-step guide to clustering lottery numbers for Eurojackpot lottery

Choose the field and number of clusters

For multi-drum lotteries, select the desired field. The number of clusters (3–6) determines grouping detail — start with 4.

Study the cluster cards

Each cluster has a name describing the numbers' behavior: "hot stable", "cold stable", "warming up". Pay attention to the average frequency and depth.

Analyze the scatter plot

The "Frequency vs Depth" chart shows how numbers are distributed among clusters. Numbers in the top-left are frequent and recent; bottom-right are rare and long absent.

Use the generator

Mark numbers from clusters of interest and generate combinations. For example, choose "hot stable" for an aggressive strategy or "warming up" to bet on the trend.

About Cluster Analysis

K-means method and its application

K-means is one of the most popular unsupervised machine learning algorithms. It groups objects (numbers) into K clusters by minimizing the distance to the cluster center.

Frequency

How many times the number has been drawn

Depth

How many draws ago was the last appearance

Interval

Average gap between appearances

Comprehensive approach

Cluster analysis evaluates a number not by a single indicator, but by a combination of characteristics. A number with high frequency but great depth is not the same as a number with high frequency and low depth.

Cluster Analysis Tips

Practical recommendations for effective use of the method

Start with 4 clusters — this is the optimal number for most lotteries. Increase only if you need more detailed grouping.

Pay attention to the "warming up" cluster — these are numbers that have recently started appearing more frequently after a long quiet period.

Combine numbers from different clusters to create a balanced combination.

Clustering results depend on the number of draws. Use the period filter to compare results across different time intervals.

Frequently Asked Questions about Eurojackpot

Answers to common questions about lottery cluster analysis for Eurojackpot