Spin the wheel to pick a random name — great for teachers & giveaways
Our Random Name Picker Wheel is a fun and fair way to select random names from a list. The visual spinning wheel with deceleration animation makes the selection exciting and transparent.
| Method | Meaning | Use when |
|---|---|---|
| Without replacement | A name drawn cannot be drawn again | Multiple distinct winners, team allocation, seating |
| With replacement | A name can be drawn repeatedly | Independent trials, simulations, picking a turn each round |
| Weighted | Some entries have more chances | Referral bonuses, ticket counts — and it must be disclosed |
| Stratified | Draw separately within groups | Guaranteeing at least one winner per region or category |
The right algorithm is the Fisher–Yates shuffle: walk from the last element backwards, and at each position swap with a randomly chosen element at or before it. Every one of the n! orderings is then equally likely. The common mistake is array.sort(() => Math.random() - 0.5), which is not a uniform shuffle — comparison sorts assume a consistent comparator, and a random one produces a measurably biased distribution that varies by browser. If a draw’s fairness matters, the shuffle implementation matters.
Taking a random integer and reducing it with % n is biased unless n divides the generator’s range exactly. If a generator produces 0–255 and you need 0–9, the values 0–5 can be produced 26 ways and 6–9 only 25 ways — a 4 % advantage to the first six entries. With ten entries nobody notices; with a large entry list and a small range it is a real skew. The correct fix is rejection sampling: discard values that fall in the incomplete final block and draw again.
| Situation | Better than random |
|---|---|
| Picking who speaks next in a meeting | Round-robin from a fixed list — random repeatedly skips someone |
| Allocating an unpleasant task | A rota, so the burden is visibly even over time |
| Splitting into balanced teams | Snake draft, then randomise within skill tiers |
| Choosing among equally good options | Random genuinely is best — it ends the debate |
| Tie-break in a competition | A pre-declared objective criterion, with random only as the last resort |
Publish the numbered entry list before drawing, announce the method in advance, use a cryptographically secure generator or a publicly verifiable seed, record the draw, and publish the winning entry number so any entrant can check the list.
No. Comparison sorts assume a consistent comparator, so a random one produces a biased and browser-dependent distribution. Use the Fisher-Yates shuffle, which makes every ordering equally likely.
Reducing a random integer with the modulo operator skews the result unless the number of entries divides the generator’s range exactly, giving the lowest-numbered entries a slight advantage. Rejection sampling — discarding values in the incomplete final block — removes it.
If it draws with replacement, repeats are expected: drawing ten times from ten names produces at least one repeat more than 99 % of the time. Choose the without-replacement mode if each name should be picked at most once.
Only for genuinely equivalent choices where the goal is to end the debate impartially. For recurring or unpleasant tasks a rota is fairer, because random selection produces streaks that feel — and over a short run genuinely are — uneven.
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