Lucky Dip
Based on Entropy / RNG
How it Works
Here's the mathematician's truth: in a fair lottery, every number has exactly the same probability of being drawn. Sometimes the best strategy is no strategy. The Lucky Dip embraces this reality, using cryptographic randomness to generate picks that are guaranteed to be unbiased—introducing necessary entropy to your selection.
The Uniform Distribution
Every number from 1 to N has an equal 1/N probability of being selected.
Entropy/RNG (Random Number Generation) uses cryptographic methods to ensure genuinely unbiased picks.
Why "true" random matters:
- Human-picked numbers cluster around birthdays (1-31) - Pattern-seeking leads to predictable choices - Even computer algorithms can have subtle biases
Our Implementation:
1. Use `crypto.getRandomValues()` for cryptographic randomness 2. Apply Fisher-Yates shuffle for uniform distribution 3. Guarantee no algorithmic bias in selection
The philosophical angle:
If the lottery is truly fair, no strategy has an edge. Random selection ensures you're not inadvertently biasing yourself *against* certain combinations (like picking only your "lucky" numbers and missing the jackpot combination).
Fun fact:
More jackpots are won by machine-generated Quick Picks than by player-chosen numbers—largely because Quick Picks represent more tickets overall.
Advantages
- Mathematically pure approach
- No human bias in selection
- Every combination equally possible
- No analysis paralysis
Considerations
- No strategic edge over other players
- Can feel unsatisfying for strategy enthusiasts
- Doesn't leverage historical data
- Purely luck-dependent
Visualization: Scatter Plot
Interactive chart visualization coming soon
Use this Strategy in The Lab
Configure weights and generate predictions with Lucky Dip