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Powerball number predictor using quantum-inspired algorithm with momentum, mean reversion, and statistical filters

Project description

powerball-quantum

Powerball number predictor using quantum-inspired algorithm with momentum, mean reversion, and statistical filters.

Installation

Python (pip):

pip install powerball-quantum

Node.js (npm):

npm install powerball-quantum

Python Usage

CLI

# Get 5 recommended picks
powerball-quantum predict

# Get 10 picks with analysis
powerball-quantum predict -c 10 -a

# Quick single pick
powerball-quantum quick

# Update data from NY Lottery API
powerball-quantum update

Python API

from powerball_quantum import predict, quick_pick, update_data

# Get 5 picks
picks = predict(count=5)
for pick in picks:
    print(pick)
# Output: 21 - 26 - 34 - 57 - 61  🔴 1

# Quick single pick
my_pick = quick_pick()
print(my_pick.white_balls, my_pick.powerball)
# [5, 7, 28, 38, 66], 23

# Update data
update_data()

Node.js Usage

CLI

npx powerball-quantum predict
npx powerball-quantum quick
npx powerball-quantum update

JavaScript API

const { predict, quickPick } = require('powerball-quantum');

const picks = await predict({ count: 5 });
const myPick = await quickPick();

Algorithm

QUANTUM combines Wall Street quant-inspired signals:

Signal Description
Momentum Exponential decay weighting - recent numbers score higher
Z-Score Mean reversion - overdue numbers get boosted
Recent Trend Last 15 draws with stronger emphasis
Pair Synergy Numbers that frequently appear together

7-Stage Filter

  1. No duplicate with historical combinations
  2. Sum range: 130-220
  3. Odd/Even ratio: 2:3 or 3:2
  4. High/Low balance: 2:3 or 3:2
  5. Decade balance: At least 3 different decades
  6. Ending diversity: At least 4 different last digits
  7. No triple consecutive numbers

Data Source

Historical data from NY Open Data Powerball API.

Disclaimer

For educational and entertainment purposes only. Lottery numbers are randomly drawn. No algorithm can predict or guarantee winning numbers. Gamble responsibly.

License

MIT

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