Party & Randomizers Tools
Pickers, spinners and generators for when something has to be decided by chance.
Roll any number of dice with any number of sides, using cryptographic randomness — with the probability facts that surprise most players.
Coin FlipFlip a virtual coin with cryptographic randomness, single or in bulk — plus the research showing real coins are not quite fair.
Random Team GeneratorSplit a list of names into balanced random teams, with control over team count or team size and an option to keep the split fair.
Scavenger Hunt Clue BuilderPrintable clue cards that send every team a different way round the same stations, so no two teams are ever at the same place at the same time.
Charades, Pictionary & Taboo CardsDeal prompts for three party games, with a round timer and team scores. A shuffled deck rather than a random pick, so nothing repeats until all have come up.
Secret Role DealerDeal hidden roles for Werewolf, Spyfall and odd-one-out games on one phone, with the balance checked before the roles are handed out.
Numerology CalculatorLife path, expression, soul urge, personality and personal year numbers using the traditional Pythagorean method — presented as tradition, not prediction.
Zodiac Compatibility MatcherPick two signs and get the traditional element-and-modality reading, with the reasoning shown — presented as tradition rather than prediction.
Spin the WheelBuild a custom wheel and spin it to pick a name or an option at random, with equal odds regardless of how the segments look.
Magic 8-BallAsk a question and get one of the twenty classic answers, with the history of the toy and its actual answer distribution.
Bingo Card GeneratorGenerate printable bingo cards, each one different, with standard number ranges or your own custom words.
Secret Santa GeneratorRandomly assign Secret Santa pairings so nobody draws themselves, using a proper derangement rather than a shuffle with retries.
About these party & randomizers tools
Shuffling is much easier to get wrong than it looks. The obvious approach — give every item a random number and sort — does not produce a uniform shuffle, and the bias is not subtle for small lists. Worse, the once-common trick of sorting with a comparator that returns a random answer is not merely biased but undefined, because sorting algorithms assume the comparator is consistent, and feeding one that is not can produce badly skewed orders or, in some implementations, an outright crash. The correct method is Fisher-Yates: walk the list from the end, and swap each item with one chosen uniformly from those at or before it. It is three lines long, it is provably uniform, and it has been rediscovered and got wrong repeatedly for decades. The second thing worth knowing is how much shuffling a physical deck actually needs. Bayer and Diaconis showed in 1992 that seven riffle shuffles are required to bring a 52-card deck close to random, and that fewer leaves detectable structure — after three or four, substantial runs from the original order survive, which is exactly what card counters and magicians exploit. Casinos shuffle more than people assume for this reason. The third is that people are poor at judging randomness in the first place. Genuinely random sequences contain long runs, so a random draw that repeats a name reads as broken, and a shuffle that plays two tracks by the same artist in a row is usually working correctly — which is why several music services deliberately made theirs less random so that it would feel more so.