Keep-highest dice pool calculator

Calculate probability kept sum reaches query and exact kept-sum distribution with your own figures.

Your numbers

Use the units shown. Results update as you change valid inputs.

Use probability kept sum reaches query and exact kept-sum distribution to compare changes to your inputs. The method and limits below explain the scope.

Examples

Examples

Try the starting example

Fair dice rolled
3
Sides per die
6
Highest dice kept
2
At-least kept-sum query
10
Probability kept sum reaches query
0.356481
Exact kept-sum distribution
2: 0.00462962962963; 3: 0.0138888888889; 4: 0.0324074074074; 5: 0.0555555555556; 6: 0.087962962963; 7: 0.125; 8: 0.157407407407; 9: 0.166666666667; 10: 0.157407407407; 11: 0.125; 12: 0.0740740740741
Expected kept sum
8.458333
Kept-sum variance
4.905671

Try another scenario

Fair dice rolled
3
Sides per die
6
Highest dice kept
1
At-least kept-sum query
10
Probability kept sum reaches query
0
Exact kept-sum distribution
1: 0.00462962962963; 2: 0.0324074074074; 3: 0.087962962963; 4: 0.171296296296; 5: 0.282407407407; 6: 0.421296296296
Expected kept sum
4.958333
Kept-sum variance
1.308449
Calculation method

Calculation method

Probability kept sum reaches query

Sum exact histogram-weighted outcomes with retained sum≥query.

Exact kept-sum distribution

Enumerate face-count histograms, weighting each by n!/product(face-count factorials); retain the highest specified count.

Expected kept sum

First moment of the exact integer-count distribution.

Kept-sum variance

Second central moment from exact integer weighted sums.

Symbols and units
a
Fair dice rolled
b
Sides per die
c
Highest dice kept
d
At-least kept-sum query

Use the units shown. A list keeps the order in which you enter its values. The symbol ^ means “raised to the power of”.

Assumptions & limits

Assumptions & limits

  • Independent fair dice with highest-face retention. Count-histogram enumeration is bounded to 100,000 histograms and reports an input error above that bound; keep-zero is a deterministic zero sum.
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Further reading

OpenStax: finite probability and sampling without replacement; rules are explicit in each worksheet ↗

Background reading; this does not imply endorsement or independent review of SumFizz.

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