Randomness Audit
SpinWheeli's spin result is chosen using your browser's built-in cryptographically secure random number generator (crypto.getRandomValues) — the same class of randomness used for security tokens, not a weak "Math.random()" pattern. Run a simulation below to see the distribution for yourself.
Why this matters
A fair random picker should give every entry roughly the same share of wins over a large number of spins, with only small statistical noise. If one entry consistently wins far more or less than expected, something would be biased. Run the simulation a few times — the deviation should stay small and shrink as the spin count grows.
FAQ
Does this test the real wheel or a simulation?
It uses the exact same random-selection method SpinWheeli's wheel uses, run many times instantly instead of animating each spin.
Why isn't every entry exactly equal?
True randomness always has some natural variance — like flipping a fair coin 1,000 times won't give exactly 500/500. The more spins you run, the closer results get to perfectly even.
What about weighted wheels?
Weighted entries are designed to win more or less often on purpose — this audit is for equal-weight fairness testing.
Ways to use the Randomness Audit
- Verify that each entry wins about equally often before a live draw.
- Show students how random distributions behave.
- Build trust with a giveaway audience by publishing the results.
Tips for best results
- Run at least several thousand spins; small samples look uneven by chance.
- Expect small differences between entries; that is normal randomness.
Good to know
Why are the counts not identical?
True randomness produces small variation. Counts should be close, not equal.