Random Number Generator

Generate random integers instantly in your browser, with optional unique values and one-click copy.

This generator runs entirely in your browser — nothing is sent to a server, and it uses your device's cryptographic randomness when available.

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About the Random Number Generator

A random number generator produces integers picked at random from a range you define, such as 1 to 100 or 1 to 49. Set the minimum and maximum, choose how many numbers you want, decide whether duplicates are allowed, and the tool returns a fresh, unbiased draw. People reach for it to settle decisions fairly, pick lottery and raffle numbers, assign teams or seating, choose a contest winner, roll virtual dice, or pull a sample for a survey. Because it makes the choice for you, it removes the temptation to favour a number you secretly prefer, which is exactly what makes a draw feel and stay fair.

The single most important setting is unique versus repeatable. When unique numbers are switched on, each value can appear only once in the result, the way real lottery balls are drawn without being put back. That is what you want for picking distinct winners, assigning unrepeated jersey numbers, or any lotto-style draw. Repeatable mode lets the same value come up more than once, which matches independent events like rolling a die several times or simulating coin-style trials. Choosing the wrong mode is the most common mistake: unique mode also requires your range to be at least as large as the count you ask for.

Under the hood this tool uses a pseudo-random number generator (PRNG), the same approach behind most software randomness. A PRNG runs a mathematical algorithm from a starting value called a seed and produces a sequence that passes statistical tests for randomness but is, strictly speaking, deterministic. That differs from a true random number generator, which measures physical noise such as thermal or atmospheric noise. For lotteries, games, sampling, and everyday fair choices a good PRNG is more than enough; only cryptographic uses (keys, tokens) demand a cryptographically secure generator (CSPRNG) drawing on system entropy.

Accuracy and privacy notes: results are spread uniformly across your range, so every integer is equally likely and the tool avoids modulo bias, the subtle skew that naive implementations introduce when squeezing values into a range. A casual PRNG is not built to be unpredictable to an attacker, so do not use these numbers as passwords or security keys. The generation runs entirely in your browser, meaning your ranges and results are never uploaded or stored on a server. Refresh or click again any time for a brand-new independent draw.

Frequently asked questions

What is the difference between unique and repeatable numbers?

Unique mode draws each number only once, like lottery balls that are not replaced, so no value repeats in your result. Repeatable mode lets the same number appear more than once, which suits independent events such as rolling a die multiple times. For unique mode your range must be at least as large as the quantity you request.

Are these numbers truly random?

They are pseudo-random: produced by a well-tested algorithm that distributes values uniformly and passes standard randomness checks, but it is not a physical (true) random source. For lotteries, games, raffles, and sampling this is statistically sound and more than sufficient.

Can I use this to pick lottery numbers?

Yes. Set the range to match your game, for example 1 to 49, choose how many numbers to draw, and turn on unique numbers so none repeat. Each combination is equally likely, though no generator can improve your odds of winning.

Should I use this generator for passwords or security keys?

No. This is a general-purpose pseudo-random generator, not a cryptographically secure one (CSPRNG), so its output can be predictable to a determined attacker. Use a dedicated password manager or a security-grade random source for keys and tokens.

Why do I sometimes get the same number twice?

That happens when repeatable mode is on, where each draw is independent and duplicates are allowed by design. If you need every value to be distinct, switch on unique numbers and make sure your range is wide enough for the count you want.

From our blog

How to Split People Into Fair Teams in Seconds (Without the Schoolyard Draft)

By the Super Simple Digital Tools Team · Updated June 2026

The classic way to pick teams, two captains taking turns choosing names, is slow, public, and quietly cruel to whoever gets picked last. A team randomizer fixes the social problem by making the split impersonal: a computer deals the names, so there is no popularity contest and no one to blame. The trade-off is that randomness optimizes for fairness of process, not for evenly matched sides, so the trick is knowing when raw randomness is exactly what you want and when to add a light touch of structure on top.

Start by deciding what you are constraining. If you have a fixed number of stations, courts, or breakout rooms, set the number of teams and let the tool figure out how many people land in each. If instead the activity demands specific group sizes, say pairs for an interview exercise or fours for a card game, set the team size and let the number of groups fall out of your headcount. Getting this choice right first saves you from regenerating repeatedly because the groups came out the wrong shape.

When the roster will not divide cleanly, the tool spreads the leftovers so teams never differ by more than one member. Twenty-three people into four groups becomes three teams of six and one of five. This even-as-possible distribution matters more than it sounds: a single oversized group can mean one extra voice in a discussion or one extra player on a field, and keeping the gap to one person keeps things feeling fair without manual fiddling.

The fairness of the draw itself comes from the Fisher-Yates shuffle, which guarantees every ordering is equally probable and runs in a single fast pass through the list. That mathematical neutrality is the whole point: because nobody, including you, can predict or steer the outcome, the result is defensible. If a parent, student, or colleague questions a split, you can honestly say the assignment was pure chance with no thumb on the scale, which is far easier than defending hand-picked groups.

Random does not mean perfectly matched, though. For a casual icebreaker that is fine, but for a competitive game one team may happen to collect all the strongest players. The fix is simple and keeps most of the fairness: generate the teams, then run a short trade window where each team swaps one player, or sort players into rough skill bands first and randomize within each band before dealing them out. You get the impartiality of a random draw and the balance of a thoughtful one.

  • Paste names straight from a spreadsheet column or attendance list, one per line, instead of typing them, to avoid typos and missed names.
  • Regenerate a few times if the first split clusters friends or all the strong players together, the shuffle is independent each run, so a new draw costs nothing.
  • For repeat sessions, deliberately re-randomize each time so students or staff work with different people instead of the same clique every week.
  • Need skill balance? Split your list into tiers (strong, average, new), randomize each tier on its own, then assign one name from each tier to every team.

Read the full guide →

Tool by the Super Simple Digital Tools Team. Reviewed by our editorial team. Free to use, no signup required.

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