Weighted Random Picker

Weighted Random Picker

Randomly select items from a list with custom weights — give some items higher chances of being picked than others. Uses cryptographic randomness for fair, unbiased selections. Pick one or multiple items, with or without replacement, and track your pick history and statistics.

Cómo utilizar

Add items and assign weights to each — higher weights mean higher probability of being selected. The tool automatically calculates and displays each item’s probability percentage. Click Pick to randomly select an item. Choose how many items to pick at once, and toggle between with replacement (items can be picked again) and without replacement (each item picked only once per batch). Import items from CSV or paste a newline-separated list.

Características

• Custom Weights — Assign any numeric weight to each item. A weight of 10 makes an item twice as likely to be picked as one with weight 5. Probability percentages update automatically.
• Cryptographic Randomness — Uses crypto.getRandomValues() for truly fair, unbiased random selection. No pseudo-random shortcuts.
• Pick Multiple Items — Select 1 or more items at once. Toggle between with replacement (items can repeat) and without replacement (each item selected at most once per batch).
• Pick History — Full log of all picks in the current session with timestamps and pick numbers. Clear history when needed.
• Probability Visualization — Pie/donut chart showing weight distribution. After multiple picks, compare actual distribution against expected probabilities.
• CSV Import — Paste items as CSV (item,weight) or newline-separated text. Items without weights default to 1.
• Dynamic Item Management — Add, remove, and reorder items freely. Start with preset empty rows and add more as needed.

How Weighted Selection Works

Weighted random selection uses a cumulative distribution function: all weights are summed, a random number is generated between 0 and the total weight, then the algorithm walks through cumulative weights to find which item the random number falls into. An item with weight 30 out of a total weight of 100 has exactly a 30% chance of being selected on each pick. This is the same algorithm used in lotteries, game loot tables, and scientific sampling.