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Simulation-based tool to analyze Confidence Pick Em pools

Project description

confpickem - Yahoo NFL Confidence Pick'em Analyzer

A Python package for analyzing and optimizing picks for Yahoo NFL Confidence Pick'em pools. This package provides tools for:

  • Scraping Yahoo Pick'em league data
  • Analyzing pick distributions and trends
  • Simulating outcomes and optimizing picks
  • Evaluating different picking strategies

Installation

You can install the package using pip:

pip install confpickem

Quick Start

from confpickem import YahooPickEm, ConfidencePickEmSimulator, run_simulation

# Initialize scraper with your league info
yahoo = YahooPickEm(
    week=1,
    league_id=YOUR_LEAGUE_ID,
    cookies_file='cookies.txt'
)

# Run simulation with actual picks
simulator, stats = run_simulation(yahoo)

# Print expected points and win percentages
print("\nExpected Points by Player:")
print(stats['expected_points'])
print("\nWin Percentages:")
print(stats['win_pct'])

Features

Yahoo Data Scraping

  • Scrape pick distributions and crowd confidence levels
  • Track actual picks and results from your league
  • Cache responses to avoid excessive requests

Simulation and Analysis

  • Monte Carlo simulation of game outcomes
  • Player skill modeling and analysis
  • Pick optimization algorithms
  • Risk/reward analysis

Strategy Optimization

  • Evaluate different picking strategies
  • Optimize confidence point assignments
  • Analyze pick correlations and game importance

Dependencies

  • Python ≥ 3.8
  • requests
  • pandas
  • numpy
  • beautifulsoup4
  • scipy

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

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