Random Name Picker

Pick random names with an animated spinning wheel or simple draw. Weighted selection, batch mode, and localStorage persistence — fully private.

7 names loaded

How to Use This Random Picker

1
Enter Your Names
Type or paste names (one per line). Add weights with a comma: "Alice, 3" gives Alice 3× probability. Click Save to persist in your browser.
2
Pick Your Mode
Use Spinning Wheel for a fun visual draw, or Simple Draw for instant random selection. Both use fair random algorithms.
3
Spin or Draw
Click Spin the Wheel or Simple Draw. The winner is displayed with a banner. Enable Remove After Draw for no-repeat picks.
4
Batch Draw (Optional)
Set batch count > 1 to select multiple winners at once. All drawn names are shown as chips below the wheel.

Frequently Asked Questions

How does the random name picker ensure fairness?
The simple draw mode uses the Fisher-Yates shuffle algorithm — a mathematically proven, O(n) algorithm that generates uniformly random permutations. Each permutation has equal probability. The spinning wheel uses Math.random() with a pre-calculated target angle based on random selection. Both methods are cryptographically fair for non-security purposes. For cryptographic randomness needs, a dedicated CSPRNG would be required.
How do I assign weights to specific names?
Add a comma and number after any name: "Alice, 3" gives Alice three entries in the draw pool, making her 3× more likely to be selected than a name with weight 1. Default weight is 1. For example, if Bob has weight 2 and Charlie has weight 1, Bob has a 2/3 chance and Charlie a 1/3 chance. This is perfect for raffles, giveaways, or when some entries deserve higher probability.
Can I pick multiple names at once?
Yes — set the Batch number to any value greater than 1. The tool will pick that many unique winners simultaneously. Enable Remove After Draw to remove winners from the pool so they cannot be selected again. With Remove After Draw off, the same name could be selected multiple times (drawing with replacement). The batch draw is sequential — each winner is removed before the next is drawn when Remove After Draw is enabled.
Is my data safe and private?
Yes, completely. All processing happens in your browser using JavaScript. Your name lists never leave your device — there are no servers, no accounts, no tracking, and no data collection. The optional Save feature uses localStorage (your browser's built-in storage), which stores data only on your device and is never transmitted anywhere. Unlike other name picker websites that may send your data to their servers, this tool is fully client-side and private by design.
What is the Fisher-Yates shuffle algorithm?
The Fisher-Yates shuffle (also known as the Knuth shuffle) is a mathematically proven algorithm for generating random permutations. Published by Ronald Fisher and Frank Yates in 1938 and later popularized by Donald Knuth, it works by iterating through an array from the last element to the first, swapping each element with a randomly chosen element that comes before it (including itself). The algorithm runs in O(n) time, uses O(1) extra space, and guarantees every permutation has exactly equal probability (1/n!). It is widely considered the gold standard for random shuffling.

Why Use a Random Name Picker?

Random name pickers are versatile tools used in classrooms (randomly calling on students), workplaces (selecting meeting facilitators or Secret Santa assignments), event planning (door prize drawings and raffles), team sports (picking starting lineups), and research (randomizing participant assignment). A good random picker removes human bias — when a teacher thinks they're calling on students "randomly," unconscious patterns inevitably emerge. True algorithmic randomness ensures every participant gets genuinely equal treatment.

This tool uses the Fisher-Yates shuffle algorithm for simple draws and a weighted random selection for the spinning wheel. The spinning wheel adds visual drama and anticipation — the deceleration animation builds suspense, making it perfect for live events, classroom activities, and team gatherings. For quick selections from large lists, the simple draw mode provides instant results without waiting for the animation.

Weighted Random Selection Explained

In a weighted random selection, each entry has an associated weight that determines its probability of being chosen. The probability for entry i with weight wᵢ is wᵢ / Σw (the entry's weight divided by the sum of all weights). This allows you to create "loaded" selections while maintaining randomness. Common use cases include raffles where some entries are more valuable (higher weight = more tickets), randomized task assignment based on skill level, and giveaways where participants can earn extra entries.

Weighted selection is implemented by expanding each entry into multiple copies in the draw pool (an entry with weight 3 appears 3 times), then applying the standard Fisher-Yates shuffle. For large weights (hundreds or thousands), a more efficient alias method or cumulative distribution function approach would be used, but for the typical use case of weights 1-10, the expansion method is perfectly adequate and conceptually simple.

Privacy Comparison: This Tool vs Other Name Pickers