How to Use the Gacha Pull Distribution Simulator
This simulator uses the Monte Carlo method to run many independent simulations with your pull probability, then shows how many pulls it took to get the first success in each run. Compare the theoretical expected value (1 ÷ p) against the actual distribution to understand gacha probability in practice.
How to Read the Distribution
The tallest bar in the histogram shows the most common pull count range. When the average and median differ greatly, it means the distribution has a long right tail — most players succeed quickly, but a few may need far more pulls than average.
How to Use It
Run the simulation before spending to understand the realistic range of pulls needed. Low probability rates create longer tails, meaning unlucky runs can cost far more than the average. Running more simulations gives a more stable distribution view.
Frequently Asked Questions
The simulator uses random numbers, so each run differs slightly. More simulations produce results closer to the theoretical value.
Average is the mean pulls; median is the midpoint where half the simulations finished within that many pulls.
The default of 1000 is sufficient. For a more detailed distribution, enter up to 5000.