Selector de ganadores

How multiple winners get picked

The random winner picker draws one or more names from your entrant list in a single pass, using crypto.getRandomValues() with rejection sampling to select each winner. When you ask for more than one winner, the tool draws without replacement by default: once someone is picked, they're removed from the pool before the next draw, so the same person can't take two prizes in one run unless you explicitly allow repeats. This is different from spinning a wheel repeatedly — all winners for a round are produced from one request, in order, which is convenient when you need to also rank second and third place.

Multiple winners and no-repeat draws, explained

"Number of winners" controls how many names come out of the pool per draw. "No-repeat" (on by default for most giveaway use cases) controls whether a person who already won in a previous round is excluded from later rounds too — useful for recurring weekly draws where you don't want last week's winner grabbing this week's prize as well. Turn no-repeat off if every draw should treat the full list as fresh, like a raffle where the same ticket-holder is allowed to win multiple distinct prizes.

Worked example: three prizes, one draw

Suppose 85 people entered a giveaway and you're awarding first, second, and third prizes. Set the winner count to 3, keep no-repeat on within the draw, and run it once. The tool draws winner one from all 85 entries, removes them, draws winner two from the remaining 84, removes them, then draws winner three from the remaining 83 — giving you an ordered list you can read out as first through third place. Every entrant had the same 1-in-85 chance of being drawn first, and the removal step only affects who's eligible for the next slot, not the fairness of any individual draw.

When to use this vs. other RandoKit tools

This tool is built for the "list of people, need N winners" shape of problem: giveaways, prize draws, selecting a review committee, assigning who gets the extra conference ticket. If you want the ceremony of watching a single name land visually, the wheel of names is more engaging for a live audience, though it's slower for picking several winners at once. If you need to split everyone into groups rather than pull a subset out, use the random team generator instead — that's a different problem (partitioning, not selecting). And for the mechanics behind repeated fair draws over time, the guide on picking names without repeating winners covers strategies for recurring giveaways in more depth.

Common mistakes

• Running the draw multiple times and only keeping the run whose winners you like — that undermines the fairness of the whole process.
• Forgetting to remove duplicate entries when someone submitted the same name twice by mistake, inflating their odds.
• Not deciding on no-repeat rules in advance for recurring giveaways, then facing complaints when a past winner is picked again.

Fairness note

In a single draw of N winners from a list, every entrant has the same probability of landing in any given position, and removing already-picked names before the next draw doesn't favor anyone — it just prevents duplicate selection. With 85 entries and 3 winners, each person's chance of winning at least one of the three slots is 3/85, about 3.5%, the same for everyone on the list. The draw relies on the browser's cryptographic random source rather than a simple pseudo-random generator, which matters if you want a defensible, hard-to-predict process; see how randomness works for the full explanation.

Privacy

The entrant list and winner history stay in your browser's local storage and are never sent to a server — the entire draw happens client-side. You can export the winner list as .txt or .csv for your records, or generate a shareable encoded URL, but no entrant data is uploaded anywhere in the process.