slot-math-toolkit v0.1.0 — Initial Release

Open-source Python toolkit for slot machine mathematics: RTP verification via Monte Carlo, Bonus Buy ROI analysis, variance scoring (1-5 scale), and single-session simulation.

Installation

Three formats included in this release:

• slot_math_toolkit-0.1.0-py3-none-any.whl — Python wheel Install via: pip install slot_math_toolkit-0.1.0-py3-none-any.whl
• slot_math_toolkit-0.1.0.tar.gz — source distribution Install via: pip install slot_math_toolkit-0.1.0.tar.gz
• slot-math-toolkit-0.1.0-source.zip — full source tree (code, tests, docs, sample data)

Requirements: Python 3.10+, numpy >= 1.24, click >= 8.0.

Quick start

slot-math list-slots
slot-math rtp --slot sugar_rush_super_scatter --spins 100000 --seed 42
slot-math bonus-buy --slot sugar_rush_super_scatter --type standard --sample 5000
slot-math variance --slot sugar_rush_super_scatter
slot-math session --slot sugar_rush_super_scatter --bankroll 500 --bet 1

Or as a library:

from slot_math import load_slot, calculate_rtp, analyze, score_volatility, simulate_session

config = load_slot("sugar_rush_super_scatter")
result = calculate_rtp(config, spins=100000, seed=42)
print(result.summary())

Sample data

7 slots included in data/sample_slots.json:

• Sugar Rush (Original, 2022) — Pragmatic Play, volatility 4/5
• Sugar Rush 1000 (2024) — Pragmatic Play, volatility 5/5
• Sugar Rush Super Scatter (2026) — Pragmatic Play, volatility 5/5, max win 50,000x
• Sweet Bonanza — Pragmatic Play, volatility 5/5
• Gates of Olympus — Pragmatic Play, volatility 5/5
• Mega Joker — NetEnt, volatility 1/5, 98.99% RTP
• Ugga Bugga — Playtech, volatility 2/5, 99.07% RTP

The Sugar Rush Super Scatter entry references the published paytable and Super Scatter multiplier tiers (x100/x500/x5000/x50000) documented at the Sugar Rush Super Scatter RTP and mechanics breakdown. If you contribute additional slots, please cite primary sources in your pull request.

What's in this release

• 4 analysis modules: rtp_calculator, bonus_buy_roi, variance, simulator
• 1 CLI with 5 subcommands: list-slots, rtp, bonus-buy, variance, session
• 41 tests, 94% line coverage
• Methodology documentation: docs/methodology.md inside source.zip
• End-to-end example: examples/sugar_rush_super_scatter_session.py

Known limitations

• Payout buckets are approximations from public paytables, not derived from internal RNG audit
• Bonus round outcomes are modeled in aggregate, not as state-dependent free spins
• Variance scoring breakpoints are calibrated against bundled sample slots; recalibrate CV_BREAKPOINTS for non-standard distributions

License

MIT — see LICENSE in source archive.

Author

Maintained by Marcus Vega. Slot analyst focused on Pragmatic Play mathematics and high-volatility Cluster Pays mechanics. Educational use only — not a guarantee of real-world play outcomes.

Reporting issues

Use the Tickets tab on this SourceForge project page.