Variables Distribution is one of Boardssey's most-used design tools, a way to model how a value (cost, attack, healing, points, etc.) is distributed across the cards or components in your game, and tune that distribution until it feels right.
If you've ever stared at a spreadsheet of cards wondering "are there too many 5-cost cards and not enough 1-cost?", this tool is built for that exact question.
What this page helps you do
Enter the values for one variable across your component set.
Visualize the distribution with a histogram or curve.
Adjust until the distribution matches your design intent.
Open the tool
Set up your data
Two ways to get values in:
Type or paste them directly into the data column.
Upload a CSV with one column per variable (cost, attack, etc.).
Each row represents one card / component. Each column is one variable (cost, attack, health, etc.). You can model multiple variables side by side.
See the distribution
For each variable, the tool shows:
A histogram, how many components fall in each bucket.
A curve, the smoothed distribution shape.
Statistics: mean, median, range, standard deviation.
Look for:
Cluster around your target average: most cards should be near the expected average; outliers should be intentional.
A reasonable spread: too narrow means the game feels samey; too wide means inconsistent.
Gaps: a hole in the middle of the range usually means a missing-cards-feel-bad design issue.
Tune
Adjust values directly in the data column and watch the distribution update live. Common moves:
Move outliers in: if you have one card at cost 12 and the next is at cost 7, that gap is suspicious. Raise some 7s or lower the 12.
Fill gaps: bucket counts at zero suggest values that should exist for player choice variety.
Match a target curve: many designers aim for a bell curve, a rising curve, or a specific shape. Tune until the histogram matches.
Multi-variable analysis
When you load multiple variables (cost, attack, defense, etc.), the tool can:
Show them side by side: compare how each is distributed.
Cross-tabulate: show "average attack at each cost level" or "attack/cost ratio" to spot inflation.
Highlight outliers: cards that are extreme on one variable but not on others (often the most or least balanced).
Tips & common questions
Why does this matter for board games? Distribution shapes player experience. A deck where 80% of cards cost 3 and 20% cost 7 plays very differently from one with a smooth 1–10 distribution. The first feels predictable; the second feels chaotic. Match distribution to the experience you want.
Can I export back to a CSV? Yes, export your modified data and pull it into your spreadsheet or production tool.
What about non-numeric variables (card type, color)? Use the count tools, the histogram works on categorical data too, showing frequency of each type.
Is there an automatic "fix it" button? No, by design. The tool surfaces problems; the design decisions stay yours.