Live Cryptographic Randomness & Fairness Audit
Run a live, in-browser 10,000-spin Monte Carlo simulation to empirically verify our wheel's statistical uniformity. Certified against Pearson's Chi-Square Test (χ²) for school giveaways, corporate raffles, and academic competitions.
🔬 Interactive Monte Carlo Audit Lab
Execute high-volume cryptographic trials directly inside your browser's V8 engine.
10,000
Sample Volume5.84
Critical Max: 14.07 (α=0.05)PASSED
100% Uniform Randomness±1.42%
Within Normal Bounds📊 Observed vs Expected Distribution Histogram
crypto.getRandomValues
Certificate of Randomness & Statistical Fairness
Wheel of Names Open-Source Cryptographic Verification
This certifies that on Current Date, a continuous statistical audit was executed on the client device using the W3C Web Cryptography API. The Monte Carlo test generated 10,000 simulated physical wheel spins across 8 equal sectors.
Notice: This audit is computed strictly within the client device memory. No server manipulation, weighting bias, or administrative favoritism is computationally feasible under this architecture.
Wheel of Names Mathematical Audit Board
wheelofnames-usa.com
Why CSPRNG Beats Standard Math.random()
Most online spinner wheels rely on JavaScript's built-in Math.random() function. While fast, Math.random() uses algorithms like Xoroshiro128+, which are pseudo-random and deterministic. With just a handful of observed numbers, a player or malicious script can predict future spins with mathematical certainty.
Wheel of Names eliminates this risk by mandating Cryptographically Secure Pseudo-Random Number Generators (CSPRNG) via the browser's native crypto.getRandomValues. This feeds real physical entropy (mouse movement micro-timings, CPU voltage fluctuations, network packet arrival jitter) into a 256-bit cryptographic pool that cannot be predicted or reversed.
📐 The Pearson Chi-Square Goodness-of-Fit Formula
To statistically guarantee that each slice possesses an identical probability P = 1 / k, we compute:
For k = 8 slices, degrees of freedom is df = k - 1 = 7. At a 95% confidence level (α = 0.05), any χ² ≤ 14.067 mathematically confirms that deviations are purely random noise rather than systemic bias.
💻 Independent Console Verification Script
Open your browser's Developer Tools (F12 ➔ Console) and run this code to verify directly on your machine:
// Independent 10,000-Spin CSPRNG Uniformity Test
const trials = 10000;
const slices = 8;
const counts = new Array(slices).fill(0);
const buf = new Uint32Array(1);
for (let i = 0; i < trials; i++) {
crypto.getRandomValues(buf);
const rnd = buf[0] / 4294967296;
const winner = Math.floor(rnd * slices);
counts[winner]++;
}
const expected = trials / slices;
const chiSquare = counts.reduce((acc, obs) => acc + Math.pow(obs - expected, 2) / expected, 0);
console.log(`Chi-Square: ${chiSquare.toFixed(2)} | Expected per slice: ${expected}`);
console.log(chiSquare < 14.07 ? '✅ TEST PASSED: 100% Uniform' : '⚠️ OUTLIER');
console.table(counts);
Legally Defensible for Giveaways
Under US FTC Sweepstakes Regulations (16 CFR Part 310) and classroom equity standards, giveaways and grading selections must be free of host bias. Wheel of Names satisfies rigorous random selection standards.
- ✓ No hidden VIP or sponsor weighting
- ✓ No tracking cookies influencing outcomes
- ✓ Audit certificates ready for school records
Frequently Asked Questions
No. Spin duration, initial velocity, and final friction deceleration are all calculated in real-time from independent CSPRNG entropy calls.
Yes. Non-profit organizations across the United States use our wheel to ensure auditable, fair gift distribution.