Note: this is an unofficial fan-made tool. It is designed for reasoning about probability scenarios, not for asserting official event odds or guarantees.

1. Problem

Loot-box style systems are hard to think about because intuition is terrible at compounding probabilities. People remember anecdotes, not distributions. I wanted a tool that made the odds, pity logic, and expected values visible enough to support an informed decision.

2. Approach

The simulator models a base drop rate, a configurable number of pulls, and an optional pity rule, then turns those assumptions into cumulative probability curves and summary statistics.

  • Show the chance of at least one drop, exactly one drop, and zero drops.
  • Show expected drops over a configurable range of container counts.
  • Make pity logic explicit so it can be reasoned about instead of assumed.

3. Evidence

Ship drop simulator main view
The main view turns a vague discussion about luck into a visible curve with concrete summary numbers.
Ship drop simulator with pity enabled
Pity settings change the shape of the curve in ways that are much easier to understand once plotted explicitly.

4. Outcome

The tool reframes a monetization mechanic as a probability problem. That is useful both for players thinking clearly about expected outcomes and for anyone designing consumer-facing systems that rely on repeated draws.

5. Tech stack

  • Client-side JavaScript probability model
  • Plotly for interactive charts
  • Responsive UI with scenario controls for drop rate, pull count, and pity threshold

6. Useful links

7. Related reading

8. Call to action

Open the interactive simulator if you want to inspect the curves yourself, or get in touch if you need a similar decision-support tool for another probability-heavy system.