List Shuffler: Random Order Your Items
Randomly shuffle a list of items — for random ordering, lottery selection, and fair assignments.
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List Shuffler: Random Order Your Items Part of our complete guide to this topic — see the full series. The Fisher-Yates shuffle algorithm was first described by Ronald Fisher and Frank Yates in their 1938 statistical tables book and later popularized by Donald Knuth. The W3C Web Cryptography API specifies , the cryptographically secure random source used by this tool. Shuffling a list sounds trivial. Copy into a spreadsheet, use RAND(), sort, done. But the naïve approach introduces subtle biases — and for anything with stakes (a class lottery, a competition draw, a fair team assignment), bias has consequences. Understanding the correct algorithm takes two minutes and applies everywhere from classroom tools to casino-grade random permutations. --- Why Not Just Sort by Random? The most…
Frequently Asked Questions
How do I randomize a list?
Paste your items (one per line) into a list shuffler and click shuffle. Under the hood, the tool applies the Fisher-Yates algorithm using crypto.getRandomValues() as the entropy source, producing an unbiased permutation where every ordering is equally likely.
How do I shuffle an array online?
Use any list shuffler tool that accepts newline-separated input. For programmatic use: apply the Fisher-Yates (Knuth) shuffle. Iterate from the last element to the first, swapping each element with a random element at an equal or earlier position. Never use sort(() => Math.random() - 0.5) — it produces biased results.
What is the Fisher-Yates shuffle algorithm?
The Fisher-Yates shuffle (also called the Knuth shuffle) is an O(n) algorithm that produces an unbiased permutation. It works by iterating from the end of the array, swapping each element with a randomly chosen element from the unshuffled portion. All n! permutations are equally probable when using a true uniform random source.
Is browser random fair for shuffling?
Yes, when using crypto.getRandomValues(). This API taps the OS entropy pool (hardware randomness on modern systems) and produces uniformly distributed values. Math.random()-based shuffles are also practically fair for non-security applications — the statistical bias from the PRNG is negligible for list lengths under a few thousand.
How do I randomly assign people to teams?
List all participants, shuffle the list, then split sequentially into team-sized groups. If teams must be equal-sized and the total doesn't divide evenly, remove excess names from the shuffled list or allow one team to be larger. The shuffle ensures no bias in team composition.
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