Pick items with custom probabilities.
Weighted Random Picker
Generate weighted random picks from your options. Set probabilities for each item and draw fairly in your browser.
- No sign-up
- Runs in your browser
- Cryptographic randomness
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Not every option should have an equal chance. Enter one option and weight per line, and the picker turns those weights into a probability distribution. A weight of 10 is selected ten times as often as a weight of 1, on average.
The picker uses cumulative weights and a cryptographically secure random value. It is useful for loot tables, games, raffles with different ticket counts, A/B tests, and classroom activities.
How to use the weighted random picker
- 01
Add options and weights
Use one option and weight per line, for example Pizza, 3. Weights can be integers or decimals.
- 02
Choose the draw count
Pick one or more winners. Repeated winners are possible when you draw with replacement.
- 03
Generate and copy
Generate a weighted pick and copy the result or the full set.
Popular ways to use weighted random picks
Game loot tables
Make common rewards frequent and rare rewards genuinely rare.
Unequal raffles
Give participants different numbers of tickets or entries.
A/B tests and classroom
Randomly assign variants, questions, or activities with the proportions you want.
Frequently asked questions
How do weights become probabilities?
Each option receives its weight divided by the sum of all weights. For example, weights 1, 2, and 7 become probabilities 10%, 20%, and 70%.
Is the weighted picker truly random?
It uses a secure random value, walks the cumulative distribution, and selects the matching segment. On a large sample, frequencies approach the configured weights.
Can I draw without duplicates?
Yes. Enable No duplicates and each selected option is removed after the draw, with the remaining weights renormalized. For independent draws with replacement, the same option can appear again.
Do weights have to be integers?
No. You can use decimals as well. All weights must be finite and greater than zero, and the total must be greater than zero.
How can I check the distribution?
Run many draws and compare observed frequencies with the expected probabilities. Small samples vary; large samples should approach the weights.