Let's say I have regiments of varying sizes, 500, 1000, 4000 troops.

I want to distribute 1000 troops worth of losses to them so that in aggregate they lose 1000 troops. I want to do it as a performant 1-shot calculation and not a sim.

What's the best way to do this?

  • \$\begingroup\$ Are all your troops equal? If you have melee soldiers, archers and dragons, it would make not much sense that your 50 dragons are all dead when your melee soldiers are untouched. \$\endgroup\$
    – Zibelas
    Nov 22, 2022 at 10:24
  • \$\begingroup\$ @Zibelas all troops are equal, the game is not primarily centered around combat and it's not very detailed. \$\endgroup\$
    – Harry
    Nov 22, 2022 at 12:46

1 Answer 1


I would take one regiment, work out the losses for that randomly. I think this is a binomial distribution, but calculating a random binomial variable doesn't have a "one shot" closed form, You can get close enough by finding the expected mean and standard deviation and using the erf() function to find a random variable on the normal distribution (This might be less accurate with kill rates close to 0 or 1). Take that number off both the size of that regiment and the total damage left to allocate.

For a binomial distribution, the mean is \$np\$ where \$n\$ is the number of units and \$p\$ is the probability of being killed, the standard deviation is \$\sqrt{np(p-1)}\$. If you can generate a random Gaussian variable r with a mean of 0 and standard deviation of 1, mean+r*sdev should give you what you want.

Now recalculate the remaining proportion of losses, and do the next regiment in the same way. Repeat for all regiments except the last one.

For the last regiment, just take the remaining damage.

It might be a little counter-intuitive, but if your distributions are close to correct and you catch edge cases (such as checking that remaining kill rate always stays between 0 and 1 inclusive), the order that you do this in doesn't mathematically matter - there won't be any bias (although I would go from smallest to largest to best avoid the edge cases).

For your example, you want to take 1000/5500 (proportion 0.1818...), so the mean is 90.909..., the standard deviation is approximately 8.62439. Say you determine that the first regiment takes 85 damage (slightly below average). You now have 915 damage to distribute between the other two regiments, 915/5000 = 0.183. Say the second regiment takes 187 damage (slightly above average). The remaining regiment takes the remaining 728 damage.

Having done all of that, it would be much easier and still reasonably quick to do a simulation (just take damage one at a time and recalculate proportions as you go) unless the regiments get really large.

For bias towards small or large regiments, just tweak the probabilities, but I'm not going to go into that since I see you removed that part of the question.

  • \$\begingroup\$ Great answer thanks, really helpful already. \$\endgroup\$
    – Harry
    Nov 22, 2022 at 14:30
  • \$\begingroup\$ Just added some more distribution stuff, including how to get the mean and standard deviation. More later. It's also a good idea to wait about a day before accepting an answer in case someone posts a better one. \$\endgroup\$
    – MadMan
    Nov 22, 2022 at 17:30
  • \$\begingroup\$ I would use something like this right: stackoverflow.com/questions/25582882/…? \$\endgroup\$
    – Harry
    Nov 22, 2022 at 19:19
  • \$\begingroup\$ @Harry something like that - there seem to be many ways of generating a Gaussian distribution. I'm not familiar with what tools are available in Javascript. \$\endgroup\$
    – MadMan
    Nov 22, 2022 at 22:28
  • 1
    \$\begingroup\$ yeah it's implemented in my game, happy with the result thanks! \$\endgroup\$
    – Harry
    Nov 23, 2022 at 3:20

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