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A pick-a-number wheel is a fair selector only when three things are settled before the spin: which rows count as chances, which values are eligible, and when the winner is chosen relative to the animation. The graphics rarely cause trouble. The trouble comes from decisions that were left implicit. If you searched for how to make a random number wheel with a specific range, the range rules in the second section matter more than the wheel’s appearance. The four gotchas below each come with a concrete example and the behavior you should state to users.
What “fair” has to mean for a number wheel
In the simplest model, every eligible entry has the same chance of winning. That is a statement about entries, not about numeric values. Suppose your list is 7, 7, 8 and the wheel selects one record uniformly. The value 7 wins two times in three, and 8 wins one time in three. Nothing is broken in that case; the model simply counts rows.
Before you write any code, decide which of three units the wheel selects:
- A list record. Each row, including repeats, is one chance. Use this when a repeated value represents an extra ticket.
- A unique displayed number. Each distinct value gets one chance. Deduplicate after parsing, not before.
- A weighted outcome. A value carries an explicit number of chances. The weight must be visible to participants.
State the unit on the screen, not only in code comments. A participant who sees “7” twice on the wheel should be able to tell whether that means two chances.
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Gotcha 1: Duplicate numbers may be tickets, typos, or weights
A repeated value in a pasted list usually has one of three origins, and each calls for different handling:
- Intentional tickets. A raffle where one name appears three times because that person bought three entries.
- Accidental repeats. A spreadsheet column copied with overlapping rows, so a value appears twice without anyone intending it.
- Explicit weights. A notation such as
7:3. NameWheel’s guide uses this form as its weighting example, to give one entry more chances.
The same visible list can produce different probabilities depending on which origin applies. The accidental-repeat case is the most dangerous because nobody notices it. Run a duplicate count before the spin and display the result, for example: “7 appears twice, so it has 2 chances; 8 has 1.” Duplicates are harmless only when your data definition says they are.
Gotcha 2: A range is a set of rules, not two endpoints
A range input needs five decisions: whether the endpoints are included, what the interval means, how exclusions apply, how malformed input is handled, and what happens when nothing is eligible. Picker Wheel’s documented interface exposes a minimum, a maximum, an interval, and a list of excluded numbers, which is a useful reference for the questions a builder has to answer.
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Generate values as the minimum plus whole multiples of the interval, keeping only values no greater than the maximum. With a range of 1 to 10 and an interval of 4, the values are 1, 5 and 9. The maximum of 10 is never reached, so it never appears. Many users will expect 10 to be included. Show the generated set on screen so that they can see this before spinning.
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What the interval means
Take a range of 0 to 100 with an interval of 25. The generated set is 0, 25, 50, 75 and 100: five slices. If the interface silently produces a different set, users have no way to check the wheel against what they asked for. Display the count of generated values next to the range so that the arithmetic is visible.
Exclusions apply to the generated set
Apply exclusions after generation, not to the raw numeric span. Excluding 25 from the range above leaves 0, 50, 75 and 100. Also decide what happens when an excluded value was never generated. A typo such as excluding 26 when 25 was intended is easy to miss if the interface ignores it. Flag excluded values that are not in the generated set.
Parsing and numeric edge cases
Values that look equal to a person may not be equal to a parser:
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1-10,5,,7orabcshould be rejected with a line-specific message. Silently dropping them or coercing them to zero changes the user’s list without telling anyone. - JavaScript numbers represent integers exactly only up to
Number.MAX_SAFE_INTEGER(9007199254740991). Above that, distinct integers can collapse to the same value, so two different entries can become one.
Empty and oversized sets
An empty eligible set must block the spin and say why. For example, a range of 1 to 5 with every value excluded leaves nothing to draw. Size limits also need explicit handling. Picker Wheel’s documentation (Version 103, dated “Oct 05” with no year shown on the page) lists up to 10,000 portions on desktop and tablet and 1,000 on mobile. Those are that product’s limits, not limits for every browser wheel. Your wheel should set its own maximum, test it on the devices you support, and refuse oversized input instead of rendering a partial wheel.
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Gotcha 3: The animation has to land on a result you already chose
The motion should be the last step, not the decision. The common bug is to let the wheel spin, then read whichever slice the pointer stopped on. That makes the outcome depend on easing curves, rounding and timing, and nothing in that process can be checked against the eligible set.
Pick the winner first
- Build the final eligible list after parsing, deduplication, weights and exclusions. Store each slice as a record with a stable ID, not just its displayed text.
- Choose an index from 0 to n − 1 using the random method described below. Store the winning record ID before the animation starts.
- With n equal slices, slice i spans i × 360 / n to (i + 1) × 360 / n degrees, measured clockwise from the pointer in the unrotated wheel. Its centre is (i + 0.5) × 360 / n.
- Set the final rotation so the winning slice’s centre sits under the pointer. If the pointer is at the top and the wheel turns clockwise, the final rotation is 360 × k + (360 − centre), where k is a number of full turns added for effect.
- Animate to that rotation, then display the label belonging to the stored record ID, not a label read back from the pointer’s position.
If you add a random offset inside the winning slice so the stop looks natural, keep it away from the slice’s edges so the pointer never sits on a boundary. The offset changes where the wheel stops, not who wins.
Choosing an index without modulo bias
MDN’s reference page for Crypto.getRandomValues(), last updated in 2025, describes the method as returning cryptographically strong random values. It notes that implementations use a pseudo-random generator seeded with a value that has enough entropy, rather than a truly random source, for performance reasons. The method has been available across browsers since July 2015. That establishes the randomness source. It does not establish that your conversion from random bits to a slice index is unbiased.
The common mistake is byte % n. A byte has 256 possible values, so for n = 6 the remainders 0 to 3 each occur 43 times, while 4 and 5 occur 42 times. That is arithmetic about the mapping, not a measurement of any wheel, but the skew is built into the method. The standard fix is rejection sampling:
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function randomIndex(n) {
const range = 2 ** 32;
const limit = range - (range % n);
const buf = new Uint32Array(1);
let x;
do {
crypto.getRandomValues(buf);
x = buf[0];
} while (x >= limit);
return x % n;
}The loop discards values at or above the largest multiple of n below 232, so every remainder appears the same number of times among the accepted values. The function works for any n from 1 up to 232.
What visibility does and does not prove
NameWheel.org’s founder, Abd Shanti, has written that a visible wheel is better because everyone can watch the selection happen. That is a claim about observability. Viewers can confirm that the pointer stopped where the announced label says it did, which catches a display that disagrees with the result. It does not show that the list was built correctly, that the random method was used, or that the input stayed unchanged after people saw it. Those depend on the process around the wheel, covered in the checklist below.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Gotcha 4: Repeat modes change the probability model
Normal mode and elimination mode produce different probability models from the same list. Name the active mode on the wheel itself.
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|---|---|---|
| What happens to the winner | Stays in the pool | Is removed from the pool before the next draw |
| Chances in the next draw | Unchanged from the previous draw | Each remaining record’s chance rises, because the pool is smaller (with four equal records, 1/4 first, then 1/3 each for the remaining three) |
| Can the same entry win again | Yes | No |
| Final draw | Same chances as the first draw | The last remaining record wins with certainty |
| What the result history means | A series of independent draws | The order of an assignment, not independent draws |
Vendor guides for NameWheel and Picker Wheel both document elimination behavior, and Picker Wheel also describes a normal mode. The table reflects the uniform-record model; the same logic applies to weighted records with weights in place of equal chances.
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Remove the winning record, not every copy of its value
In elimination mode, the list 7, 7, 8 raises a question. If the first draw lands on one of the two 7 records and your code removes by value, both 7 entries disappear at once. Removing the record leaves one 7 in the pool for the next draw. Pick one behavior deliberately, state it on screen (“each ticket is removed once” or “each value is removed once”), and store the record ID so the history shows which ticket won.
Before a public draw
- Show the eligible set, its size, and the unit of selection before the spin begins.
- Lock the list once the spin starts. Any edit should require a reset, so the displayed set and the drawn set cannot diverge.
- Name the active mode on the wheel and keep the result log consistent with it.
- Describe the method in plain terms: a browser’s cryptographically strong random values, converted to a slice index without modulo bias. Do not call the wheel “provably fair.” No independent fairness audit or number-wheel-specific standard is currently available to cite, so describe the method rather than the outcome.
A number wheel earns trust when each choice is visible before the spin: the unit, the range rules, the mode, and the method. The animation then shows an outcome that was already defined.
Frequently Asked Questions
Is a number wheel better than dice or a text random-number generator?
It depends on what the audience needs to see and what the draw requires. Vendor guides compare them on five points: whether the audience can watch the selection, whether custom and weighted sets are supported, whether no-repeat draws are available, whether results can be recorded, and whether the device can show the full set legibly. Dice suit standard ranges and tactile play. These comparisons are written by vendors, not produced by independent usability research.
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