DSO

Probability

Dice Sum Odds Calculator

Count exact ways to roll a target sum with identical fair dice, calculate probability and odds, display the full sum distribution, and extend the entered payoff assumptions across planned rolls.

Ways to reach exact target-
Total equally likely outcomes-
Exact target-sum probability-
Exact probability as percentage-
Expected successful rolls-
Expected net result across planned rolls-
Probability minus entered comparison-

Decision view

Exact dice-sum probability distribution

Exact dice-sum probability distributionEvery attainable sum is shown, with the entered target highlighted and the comparison probability marked.
Exact scenario comparisonExact target sum changes while all other entered assumptions remain constant.
Exact target sumWays to reach exact targetTotal equally likely outcomesExact target-sum probabilityExact probability as percentageExpected successful rollsExpected net result across planned rollsProbability minus entered comparison

How to use Dice Sum Odds Calculator

  1. Enter the number of identical dice, sides per die, and exact target sum.
  2. Enter planned independent rolls and the payoff assumptions.
  3. Add a comparison probability if useful.
  4. Read the full probability histogram instead of judging the target in isolation.

Calculator guide

Understanding Dice Sum Odds Calculator

Exact dice-sum probability comes from counting equally likely ordered outcomes, not from assuming every possible total is equally likely. The complete distribution shows why center sums occur more often than edge sums and supports a transparent expected-payoff calculation.

Sums are unequal Middle totals have more combinations.
Count first Probability follows from favorable ways over all ways.
Histogram explains Every attainable total is displayed.
Payoff is separate Probability alone does not determine value.

Calculation method

How the calculation works

Count exact sum combinations for identical fair dice, divide by the complete equally likely outcome space, and extend the probability to odds, expected hits, and entered payoff arithmetic. Count ordered outcomes that equal the target, divide by sⁿ total outcomes, convert to odds, and multiply success and failure counts by their entered net payoff and stake.

Detailed calculation process

Count exact dice-sum outcomes before extending to payoff

The default rolls two fair six-sided dice, targets a total of 8, plans 100 independent rolls, risks $5 on failure, and receives a $20 net win on success.

General formula: Ω = sⁿF(tn,s) = Σ(-1)^k C(n,k)C(t-sk-1,n-1)p = F/ΩO_against = (1-p)/pE[X] = NpEV = N[pW-(1-p)S] The bounded-composition count F gives ordered ways for n identical-sided dice to sum to t. Dividing by the complete outcome space gives exact probability. Expected value uses the entered net win on success and stake loss on failure.

What each symbol means

n, s, t Number of dice, sides per die, and exact target sum.
Ω, F Total equally likely ordered outcomes and favorable ordered outcomes (ways).
p, O_against Exact success probability and unfavorable-to-favorable odds ratio.
N, E[X] Planned independent rolls and expected number of target outcomes.
W, S, EV Net win per success ($), stake lost per failure ($), and expected net result ($).

Worked substitution with the default inputs

1. Count the outcome space Ω = 6²Ω = 36 ordered outcomes Each die has six possibilities and the ordered pair creates 36 equally likely outcomes.
2. Count ways to make eight F = {(2,6),(3,5),(4,4),(5,3),(6,2)}F = 5 ways Order matters for distinct faces, so (2,6) and (6,2) are separate outcomes.
3. Calculate probability and odds p = 5/36 = 0.1388889 = 13.8889%O_against = (31/36)/(5/36) = 31/5 = 6.2 The odds ratio means 6.2 unfavorable outcomes per favorable outcome in the exact theoretical space.
4. Extend to planned rolls E[X] = 100(5/36)E[X] = 13.8889 successes An expected count is a long-run average and does not require any one 100-roll sample to contain a fractional result.
5. Reconcile the entered payoff EV = 13.8889($20)-(100-13.8889)($5)EV = $277.78-$430.56 = -$152.78 Success winnings and failure stakes are kept separate before netting.

For two fair six-sided dice, sum 8 has 5 of 36 ordered outcomes, or 13.8889%; the entered payoff assumptions produce an expected net result of -$152.78 over 100 rolls.

Exact distribution

See every attainable dice sum and its probability

A probability histogram displays the complete combinatorial distribution, highlights the entered target, and marks the comparison probability.

Edge sums Few ordered outcomes reach the minimum and maximum.
Central peak More combinations accumulate near the middle.
Target bar The selected sum is highlighted.
Comparison line The entered percentage remains a visible benchmark.

Worked situations

Practical examples

  • Two six-sided dice have 36 ordered outcomes.
  • Five ordered pairs sum to 8.
  • At the entered payoff, expected failure losses exceed expected success winnings.

Better inputs

Useful tips

  • Confirm whether the game pays net profit or total return.
  • Use the full distribution when comparing several target sums.
  • Do not treat expected value as a guarantee over a short sequence.

Before relying on the result

Limitations and common mistakes

  • The calculation assumes fair, independent dice with identical side counts.
  • Real game rules can change payout, stake loss, pushes, bonuses, limits, and eligible outcomes.
  • Expected value does not describe bankroll volatility, loss streaks, or responsible-play limits.

Reference

Key terms

Ordered outcome
A face result for each die where die positions are distinguishable.
Favorable ways
Ordered outcomes whose faces sum to the target.
Odds against
Unfavorable probability divided by favorable probability.
Expected value
Probability-weighted average net result over repeated trials.

Important note

Calculated directly from the entered values using the displayed formula and rounding settings.

Frequently asked questions

Why are dice sums not equally likely?

Different totals can be formed by different numbers of ordered face combinations.

Why is the expected success count fractional?

It is a probability-weighted average across repeated samples, not a predicted literal count.

What happens when the target is impossible?

Favorable ways and probability become zero, so odds against are not meaningfully finite.

Does a negative expected value predict my exact loss?

No. It describes the long-run average under the entered assumptions.