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Loot drop probability calculator

The chance of getting a rare drop over many tries — the maths behind grinding for a mount, a shiny, or a knife skin. From the per-attempt drop rate and the number of attempts, it works out the probability of at least one (or several) drops, and how many runs you need for a 50%, 90% and 99% chance.

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The Loot drop probability calculator turns Drop rate per attempt (%), Number of attempts, Desired drops (at least) into Chance of ≥ desired drops, Expected drops, Attempts for 50% chance (1 drop), Attempts for 90% chance, Attempts for 99% chance, instantly and for free. For instance, with Drop rate per attempt (%) = 1, Number of attempts = 100 and Desired drops (at least) = 1 it returns Chance of ≥ desired drops = 63.4%, Expected drops = 1 and Attempts for 50% chance (1 drop) = 69.

How to use it

  1. Enter your values: Drop rate per attempt (%), Number of attempts, Desired drops (at least).
  2. Read the result instantly: Chance of ≥ desired drops, Expected drops, Attempts for 50% chance (1 drop), Attempts for 90% chance, Attempts for 99% chance.

Frequently asked questions

What does the Loot drop probability calculator actually compute?

It takes Drop rate per attempt (%), Number of attempts and Desired drops (at least) and derives Chance of ≥ desired drops, Expected drops, Attempts for 50% chance (1 drop), Attempts for 90% chance and Attempts for 99% chance from them. The calculation is live as you type, so the result updates on every change.

What information do I need to provide?

3 values: Drop rate per attempt (%), Number of attempts and Desired drops (at least). Nothing else is required — no account, no file upload.

Can you show a worked example?

With Drop rate per attempt (%) = 1, Number of attempts = 100 and Desired drops (at least) = 1, the calculator returns Chance of ≥ desired drops = 63.4%, Expected drops = 1 and Attempts for 50% chance (1 drop) = 69. Those figures come from running this exact tool, so you can reproduce them by entering the same values.

What happens if I enter larger values?

It moves a lot. Using Drop rate per attempt (%) = 1.1, Number of attempts = 200 and Desired drops (at least) = 2 instead, Chance of ≥ desired drops goes from 63.4% to 64.7% — which is why it is worth testing a few scenarios rather than trusting a single figure.

What does it give for smaller values?

Scaled down to Drop rate per attempt (%) = 0.9, Number of attempts = 50 and Desired drops (at least) = 1, Chance of ≥ desired drops comes out at 36.37%. The relationship is worth checking at both ends before you rely on a single result.

When would I actually use this?

Summarising a dataset before drawing conclusions from it, checking whether a difference between two groups is real, and putting an interval around an estimate.

What is the most common mistake?

Reading a p-value as the probability that the hypothesis is wrong. It is the probability of seeing data at least this extreme if the null were true — a different statement, and a much weaker one.

What is the difference between the Loot drop probability calculator and the Binomial Probability Calculator?

This one returns Chance of ≥ desired drops and Expected drops; the Binomial Probability Calculator returns Result. That is the whole difference — open the one whose figure you need.

Is there a tool for the next step?

Dice Roll Probability Calculator is the closest one after this: Exact odds that a roll of nd s (+ modifier) meets a target — built by convolution, not simulated.

What else is worth having open alongside it?

Odds to probability converter and Probability calculator — they come up in the same task often enough to be worth a second tab.

Further reading

All guides →
ExplainerA 1 % Drop Rate Does Not Mean One Hundred RunsAt 1 %, a hundred attempts give you 63.4 % — not certainty. Ninety per cent takes 230 attempts and ninety-nine takes 459, and more than a third of players are still empty-handed at a hundred.ExplainerProbability Basics, With ExamplesProbability measures how likely something is, from 0 to 1. Here's the basic idea, how to combine events with AND and OR, and the complement.ExplainerWhat Is a Z-Score? Standard Deviations Above the MeanA z-score is z = (x − μ) / σ — how many standard deviations a value sits from the mean. Learn how to compute it, read the standard normal curve, and turn it into a percentile.ExplainerMean, Median and Mode: What's the Difference?Mean, median and mode all describe the 'middle' of your data — but answer different questions. Here's what each means, with examples and when to use which.ExplainerGeometric vs Arithmetic Mean: Which to UseThe arithmetic mean adds and divides; the geometric mean multiplies and takes a root. Learn which fits growth rates, ratios, and averages.How-toHow to Calculate Standard Deviation (Step by Step)Standard deviation measures how spread out your data is. Here's the formula, a worked example, and the difference between population and sample.