List Randomizer
List randomization shuffles items into random order using the Fisher-Yates algorithm. This algorithm guarantees uniform distribution (each permutation equally likely) and runs in O(n) time. Process: iterate through list, swap each element with a random element from remaining items. Common uses: randomizing quiz questions, shuffling playlists, generating random teams, prize drawings, A/B test assignment. To randomize text: paste list (one item per line), click shuffle, get randomized output. Results are cryptographically unpredictable using Math.random(). For high-security applications requiring true randomness (lotteries, cryptography), use crypto.getRandomValues() instead.
Randomize and shuffle lists of items. Enter names, tasks, or options and shuffle them randomly. Pick random items (1, 3, or 5). Supports newline, comma, or custom separators. Remove duplicates and empty lines. Perfect for team selection, random drawing, task ordering, and decision making.
Enter Items
0 items detected
Examples
Options
Use Cases
- Random team selection or assignment
- Shuffle presentation order
- Pick random winners from a list
- Randomize task priorities
- Create random reading or watching order
How to Use
- Enter your value in the input field
- Click the Calculate/Convert button
- Copy the result to your clipboard
Frequently Asked Questions
- How does list randomization work and is it truly random?
- List randomizers use pseudorandom algorithms (like Fisher-Yates shuffle) to rearrange items unpredictably. Modern implementations use cryptographically secure random number generators (CSRNG) for unpredictability. While not "truly random" (which requires physical entropy sources), they are sufficiently random for practical purposes like team selection, prize drawings, and task ordering. Each item has an equal probability of appearing in any position.
- What can I use a list randomizer for?
- Common uses: randomly assign teams or partners for group work, shuffle presentation orders or speaking turns, randomly select winners for giveaways or raffles, randomize survey or test question order to reduce bias, shuffle playlist or task lists for variety, randomly distribute tasks among team members, pick random samples from lists, or make unbiased decisions between multiple options. Any scenario requiring random selection or ordering benefits.
- How do I ensure my randomization is fair?
- Use a reputable randomizer tool with cryptographically secure algorithms. Remove duplicates before randomizing to ensure equal probability. For high-stakes selections (legal drawings, research studies), document the process: save inputs, timestamps, and results. Run multiple randomizations to verify results differ. For contests, consider using verifiable randomness sources or third-party witnesses. Most list randomizers provide truly unbiased results without human intervention.
- Can I pick multiple random items from a list?
- Yes, most list randomizers offer "pick N random items" functionality. This is useful for selecting winners (pick 3 from 100 entries), choosing samples (pick 20 from 200 customers for feedback), or creating random groups. You can pick with replacement (same item can be selected multiple times) or without replacement (each item selected only once). For team division, pick sequentially: first N for team 1, next N for team 2, etc.
- What input formats do list randomizers accept?
- Most randomizers accept multiple formats: newline-separated (one item per line), comma-separated (item1, item2, item3), space-separated, or custom delimiters (semicolon, tab, pipe). Many tools auto-detect format. For best results, use one format consistently. Advanced features may include: trimming whitespace, removing duplicates, filtering empty entries, and case-insensitive duplicate detection. Paste from spreadsheets (Excel, Google Sheets) works with most tools.
- How do I divide a list into random teams or groups?
- First, shuffle the entire list randomly. Then divide sequentially: if you have 20 people and need 4 teams of 5, take items 1-5 for team 1, 6-10 for team 2, etc. Some randomizers have built-in team division features. For uneven teams, decide whether extra members go to first teams or last teams. This method ensures random assignment while maintaining desired team sizes.
- Can I save and reuse my randomized results?
- Most list randomizers allow copying results to clipboard or downloading as text/CSV files. For documentation, screenshot results with timestamps. If you need to reproduce results, some tools provide seed values — using the same seed with the same input produces identical randomization. For accountability in contests or research, save original inputs, randomization timestamp, and final order. Cloud-based tools may offer save/share links.
- What is the Fisher-Yates shuffle algorithm?
- Fisher-Yates (also called Knuth shuffle) is the standard algorithm for unbiased list randomization. It works backwards through the list, swapping each element with a random element before it. Time complexity is O(n), and it guarantees each permutation has equal probability (1/n!). Modern list randomizers use this algorithm or similar unbiased methods. It avoids the bias of naive approaches like "sort by random number" which do not produce uniform distributions.