Generate cryptographically secure random numbers with multiple distributions. Perfect for gaming, research, simulations, and development.
Use the number generator above for custom random numbers
Supports multiple distributions and formats
Enter the minimum and maximum values for your random number. The range can be anything from 1-10 for simple decisions to 1-1,000,000 for lottery-style draws.
Select from three distribution types: uniform (equal chance for every number), normal (bell curve centered on the midpoint), or exponential (favoring lower values). Uniform is the default and works for most use cases.
Click generate to produce your random number or batch of numbers. You can generate a single number or multiple numbers at once, with results appearing instantly along with statistical analysis.
Switch to dice rolling mode for tabletop gaming, lottery number generator for pick-your-numbers games, or explore the statistical analysis view to examine the distribution of your generated results.
Uses the Web Crypto API for true cryptographic randomness, not pseudo-random algorithms. This means results are unpredictable and suitable for applications where fairness and security matter.
Generate numbers with uniform, normal (Gaussian), or exponential distributions. Each type serves different purposes, from fair raffles to realistic simulations and statistical modeling.
Built-in dice roller supports standard RPG dice notation (d4, d6, d8, d10, d12, d20, d100). Roll multiple dice at once and see individual results plus the total.
Generate lottery-style number sets with no duplicates. Configure the number count and range to match any lottery format, from Powerball to EuroMillions.
View the distribution of your generated numbers with mean, median, standard deviation, and a visual histogram. Useful for verifying randomness and understanding distribution patterns.
Tabletop gamers and dungeon masters use the dice roller for D&D, Pathfinder, and other RPG systems. Rolling multiple dice with custom sides and getting instant totals speeds up gameplay. The cryptographic randomness ensures no player can question the fairness of digital dice rolls compared to physical ones.
Developers and data scientists use random number generators for testing, simulations, and sampling. The distribution options are particularly valuable: uniform distribution for Monte Carlo simulations, normal distribution for modeling natural phenomena, and exponential distribution for simulating time between events. The statistical analysis confirms the generated numbers follow the expected distribution.
Teachers, event organizers, and content creators use random number generators for raffles, classroom activities, contest winners, and decision-making. When you need to pick a winner from 500 entries or randomly assign students to groups, the tool provides transparent, cryptographically fair results that everyone can trust.
Yes. The tool uses the Web Crypto API (crypto.getRandomValues), which provides cryptographically secure random numbers generated from your operating system entropy source. This is the same randomness used in security applications like encryption key generation.
Uniform distribution gives every number in the range an equal chance of being selected, like rolling a fair die. Normal (Gaussian) distribution clusters results around the center of the range in a bell curve shape, making extreme values rare. Most natural phenomena follow a normal distribution.
Yes. The lottery number generator mode ensures no duplicates in each set of numbers. For general random number generation, each draw is independent, so duplicates can occur naturally. If you need a unique set, the lottery mode is the right choice.
The dice roller supports all standard RPG dice: d4, d6, d8, d10, d12, d20, and d100 (percentile). You can roll multiple dice of any type simultaneously and see each individual result along with the sum total.
The tool supports ranges from negative to positive values in the billions. For most practical purposes, any range you need is supported. Extremely large ranges (trillions+) may lose precision due to floating-point limitations in JavaScript, but standard use cases are fully covered.