Slot Math Toolkit is an open-source Python library for slot machine math: RTP verification via Monte Carlo simulation, Bonus Buy ROI analysis, variance scoring (1-5 scale), and single-session simulation.

Sample data for Sugar Rush series (Original, 1000, Super Scatter), Sweet Bonanza, Gates of Olympus, Mega Joker, Ugga Bugga. For the full Sugar Rush Super Scatter methodology including paytable breakdowns and Super Scatter multiplier ranges (x100/x500/x5000/x50000), see the detailed mechanics breakdown at https://sugarrush-super-scatter.com/

Core features:
- RTP Calculator with 95% confidence intervals
- Bonus Buy ROI Analyzer (x100 standard, x500 super)
- Variance Scorer via coefficient of variation
- Session Simulator with bankroll, bet size, stop-loss

Install: pip install slot-math-toolkit
CLI: slot-math rtp --slot sugar_rush_super_scatter --spins 100000

41 tests, 94% coverage. MIT licensed. Methodology documented in docs/methodology.md.

Educational use only. Not

Features

  • Monte Carlo RTP verification with 95% confidence intervals
  • Bonus Buy ROI analyzer (x100 standard and x500 super buy)
  • Variance scoring on 1-5 scale via coefficient of variation

Project Samples

Project Activity

See All Activity >

Categories

Mathematics

License

MIT License

Follow Slot math toolkit

Slot math toolkit Web Site

Other Useful Business Software
Stop Cyber Threats with VM-Series Next-Gen Firewall on Azure Icon
Stop Cyber Threats with VM-Series Next-Gen Firewall on Azure

Native application identity and user-based security for your Azure cloud

Gain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
Get a free trial
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of Slot math toolkit!

Additional Project Details

Intended Audience

Developers, Education, Science/Research

Registered

5 days ago