list-randomizer
A list randomizer produces a random ordering of a list β equivalent to a fair shuffle. The use cases overlap with a shuffler, but "randomize" tends to be the term used for one-off draws (pick 3 winners, randomise team assignments) while "shuffle" is more often the term for music, decks, or repeated reorderings. The ZTools List Randomizer tool wraps Fisher-Yates with a "draw N" UI β paste the list, choose how many winners, get the result. Optional crypto-grade RNG for high-stakes draws.
Use casesβ
Pick raffle winnersβ
Paste 500 entrants, ask for 3 winners, copy the result. Fairness audit trail via the seed (if reproducibility is required) or crypto-RNG (if not).
Randomise team assignmentsβ
Twelve people, three teams of four. Randomize, partition into chunks of four β fairer than ad-hoc captain picks.
Quiz question orderingβ
Different students get questions in different orders. A randomised order per session reduces copying.
A/B testing β randomly assign treatmentβ
1,000 user IDs, half to A and half to B. Randomise then take the first 500 for A. Simple unbiased split.
How it worksβ
- Paste list β One item per line. Tool counts entries.
- Pick draw count β Either output the full randomised list, or "draw N" to take the first N items as winners.
- Pick RNG β Standard or cryptographic. For raffles with prizes, prefer crypto.
- Run and copy β Output is the randomised list (or top N). Re-run for a new draw.
Examplesβ
Input: [Alice, Bob, Carol, Dave, Eve]; draw 2
Output: One run: [Carol, Eve]. Another: [Alice, Dave]. Each 2-element subset equally likely.
Input: Randomise full list of 100
Output: Output: 100 items, fully shuffled. Use as random ordering for a survey.
Input: A/B split of 1000 users
Output: Randomise, take first 500 β group A; remaining 500 β group B. Each user equally likely to be in either group.
Frequently asked questionsβ
Is "randomize" the same as "shuffle"?
Mathematically yes β both produce a uniformly random permutation. We use the names interchangeably; the tool with "randomize" in the name surfaces a "draw N" UI by default.
How fair is the draw?
Fisher-Yates is unbiased. The RNG matters β Math.random is fine for casual draws; crypto.getRandomValues is better when fairness might be challenged.
Can I exclude duplicates?
Run a deduplicate first β random draws on a list with duplicates can pick the same name twice (different positions).
How is "draw N" different from "pick one"?
"Draw N" returns N distinct items (sampling without replacement). "Pick one" repeated N times can return the same item. Use the right tool for your scenario.
Privacy?
All processing in the browser. Names / IDs / sensitive data never leave the device.
Tipsβ
- For raffles, screenshot the seed + the input list + the output. Reproducible audit trail without exposing names elsewhere.
- When drawing more than ~30% of the list, shuffle the whole list and take the first N β same complexity, simpler audit.
- Avoid drawing names visibly during a live event; pre-randomise in private then reveal β looks fairer to participants.
Try it nowβ
The full list-randomizer runs in your browser at https://ztools.zaions.com/list-randomizer β no signup, no upload, no data leaves your device.
Last updated: 2026-05-06 Β· Author: Ahsan Mahmood Β· Edit this page on GitHub