Add options, assign weights, and pick — results appear with the probability you define. Higher weight = more likely. Perfect for probability demos, loot tables, and unequal random decisions.
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A weighted random generator assigns each option a relative probability proportional to its weight. If you have three options with weights 1, 2, and 3, their probabilities are 1/6 ≈ 16.7%, 2/6 ≈ 33.3%, and 3/6 = 50%. The implementation uses a cumulative weight array — a random number from 0 to the total weight is drawn, then mapped to the option whose range it falls in. This is the standard weighted random algorithm used in game engines, A/B testing frameworks, and recommendation systems.
Use cases
Game designers use weighted tables to define item drop rates — a common sword might have weight 50 while a legendary weapon has weight 1. Probability teachers use it to demonstrate non-uniform distributions. HR teams use it for weighted candidate selection simulations. Icebreaker facilitators assign weights to activities based on group interest. Any situation where not all outcomes should be equally likely — but should still be random — is a weighted random problem.
Tips for setting weights
Weights are relative, not absolute percentages — only the ratios between them matter. Weight 10 vs. weight 5 is the same as weight 2 vs. weight 1 (one is twice as likely as the other). Use small integers for simplicity: weight 3 for "likely," weight 2 for "possible," weight 1 for "rare." The probability bars next to each option update in real time as you adjust weights, so you can see exactly what percentage each option represents before you pick.
Frequently asked questions
What is a weighted random generator?
A weighted random generator picks options with probabilities proportional to their assigned weights. An option with weight 3 is three times more likely to be chosen than an option with weight 1. This lets you simulate non-uniform probability distributions — where not all outcomes are equally likely — while still producing random results each time.
How do weights work?
The total weight is calculated by summing all individual weights. Each option's probability equals its weight divided by the total. For example, three options with weights 1, 2, and 3 have a total weight of 6, giving probabilities of 1/6 ≈ 16.7%, 2/6 ≈ 33.3%, and 3/6 = 50%. The probability bars next to each option update in real time as you adjust weights so you can see the exact breakdown before picking.
What can I use this for?
Common uses include game design (defining loot tables and item drop rates), probability demonstrations in classrooms, unequal raffle draws where premium ticket holders have higher weight, A/B test simulation, and icebreaker activities where popular options have higher weights. Any situation where not all outcomes should be equally likely — but should still be random — is a weighted random problem.
Can I name the options?
Yes. You can enter any label for each option — a name, an item, an outcome, or any text. Each option also gets a weight from 1 to 99. The generator supports up to 10 options at once. You can add or remove options at any time, and the probability bars update instantly to reflect your current weights.
Who uses this tool
Game designers
Define loot tables and item drop rates — set weights to make rare items truly rare without writing code.
Teachers
Demonstrate non-uniform probability distributions hands-on — adjust weights and observe how results cluster toward higher-weighted options.
Event organizers
Run unequal raffles — give premium ticket holders a higher weight for fair but weighted prize draws.
Developers
Prototype and test weighted random algorithms before implementing them in code — verify behavior visually before writing a line.