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6 Jupyter notebooks that teach you to build a Polymarket bot with a 69.8% backtest win rate.
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What to do next:
- Unzip the file — you'll see 6 notebooks (01-06)
- Open
01_scraping_espn.ipynbin Jupyter or VS Code - Run each cell top-to-bottom — the code works end-to-end
- Stuck? Paste any cell into ChatGPT or Claude and ask for help
Backtest results from this system
Time-split validation on 2025-26 season. ESPN WP as market proxy. Held to settlement, net of fees. Full validation →
All 6 modules included
Scraping ESPN
Build an async scraper that fetches 60,000+ games across 7 sports
Elo Ratings
Implement Elo from scratch — home advantage, K-factor tuning, 907+ teams
Win Probability Models
Train LR+Spline and XGBoost+Isotonic — why simpler models make more money
Backtesting
Time-split validation, adverse selection traps, execution cost modeling
Live Bot
Polymarket API, ESPN polling, edge detection, order execution, shadow mode
Deployment
FastAPI server, HTTPS, Discord alerts, cron scheduling, 24/7 monitoring
New to Python? Never used a Jupyter notebook? +
You don't need to be a programmer. A Jupyter notebook is like a document where you can run code one step at a time — click a cell, press Shift+Enter, see the result. No terminal commands, no complex setup.
How to get started in 3 minutes:
- Install Python from python.org (click the big download button)
- Open your terminal and type:
pip install notebook pandas numpy - Navigate to the course folder and type:
jupyter notebook - Your browser opens. Click
01_scraping_espn.ipynb. Start running cells.
Stuck on anything? Copy any cell into ChatGPT or Claude and ask "explain this line by line" or "help me fix this error." The notebooks are designed to work with AI assistants — think of it as having a tutor sitting next to you.
Alternative: Use Google Colab (free, runs in your browser, no install needed). Just upload the .ipynb file.
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