Skip to content

QUICKSTART.md

Latest commit

 

History

History
256 lines (185 loc) · 6.21 KB

QUICKSTART.md

File metadata and controls

256 lines (185 loc) · 6.21 KB
Raw

Quick Start Guide

Get your Fantasy Football Trade Analyzer running in 5 minutes!

🚀 Fast Setup

Option 1: Using the Run Script (Recommended)

# Make the script executable (Linux/Mac)
chmod +x run_app.sh

# Run the app
./run_app.sh

Option 2: Manual Setup

# Install dependencies
pip install -r requirements.txt

# Run the app
streamlit run app.py

The app will open automatically in your browser at http://localhost:8501

📝 Step-by-Step First Use

1. Get Your Sleeper League ID

  1. Go to sleeper.app
  2. Open your league
  3. Look at the URL: https://sleeper.app/leagues/YOUR_LEAGUE_ID/team
  4. Copy the YOUR_LEAGUE_ID portion

2. Enter League ID

  1. In the sidebar, paste your League ID
  2. Click outside the input box
  3. Wait for league data to load (5-10 seconds)

3. Select Your Team

  1. Choose your team name from the dropdown
  2. View your roster with enhanced valuations

4. Explore Features

AI Trade Suggestions:

  • Automatically generated based on your team needs
  • Shows potential gains/losses
  • Considers positional balance

Manual Trade Analyzer:

  • Enter custom trades
  • Get instant fairness verdicts
  • See detailed value breakdowns

League Overview:

  • Power rankings
  • Compare against other teams
  • Identify trading partners

🎯 Demo Mode (No API Key Required)

The app works out-of-the-box with mock data:

  • 200+ players with realistic projections
  • All positions including IDP
  • Full feature set available

Demo limitations:

  • Synthetic data (not real NFL data)
  • No historical trends
  • Generic player details

🔑 Add Real Data (Optional)

For real NFL data, get a free SportsDataIO API key:

  1. Sign up at sportsdata.io
  2. Free tier: 1000 requests/month
  3. Open app.py
  4. Replace API_KEY = "YOUR_SPORTSDATAIO_KEY_HERE" with your key
  5. Restart the app

Benefits of real data:

  • Actual NFL projections
  • Historical performance (3 years)
  • Real player ages and injury status
  • Team performance metrics
  • Strength of schedule analysis

📊 Understanding the Analysis

Player Valuations

Each player gets an "Adjusted Value" based on:

60% - Current projections (2026 season)
20% - Historical average (past 3 years)
10% - Team performance impact
5%  - Strength of schedule
5%  - Age & injury adjustments

VORP (Value Over Replacement)

Shows how much better a player is than a "replacement level" player:

  • QB: Top 12
  • RB: Top 24
  • WR: Top 30
  • TE: Top 12
  • IDP varies by position

Higher VORP = more valuable player

Trade Fairness

Trades are evaluated as:

  • ✅ Fair: Within ±5% value
  • 🎉 Great for You: +10% or more
  • ⚠️ Unfavorable: -10% or less
  • ⚖️ Slightly Imbalanced: Between ±5-10%

🏆 Best Practices

Finding Good Trades

  1. Check AI Suggestions First

    • Pre-analyzed for mutual benefit
    • Based on roster construction
    • Considers positional needs

  2. Look for Complementary Needs

    • Your strength = their weakness
    • Their strength = your weakness
    • Win-win scenarios

  3. Don't Overpay

    • Aim for positive or neutral value
    • Consider injury risk and age
    • Think about playoffs

  4. Position Scarcity

    • RBs and TEs are often scarce
    • May need to "overpay" slightly
    • Balance is key

Using IDP Leagues

The analyzer fully supports IDP with:

  • Tackles, sacks, interceptions
  • Position-specific baselines
  • Defensive player projections

IDP Positions:

  • DL (Defensive Line): Prioritize sacks
  • LB (Linebackers): High tackle volume
  • DB (Defensive Backs): Interceptions + tackles

🔧 Troubleshooting

"Error fetching Sleeper users"

  • Double-check your League ID
  • Ensure the league is active
  • Try refreshing the page

"Using mock data" warning

  • This is normal without an API key
  • All features still work
  • Add API key for real data

Players not showing up

  • Some players may not match between databases
  • Fuzzy matching attempts to find closest match
  • Very new players may be missing

Slow loading

  • First load caches data (slower)
  • Subsequent loads are faster
  • API calls may take 10-30 seconds

💡 Pro Tips

  1. Compare Multiple Trades

    • Use manual analyzer for variations
    • Try 2-for-1, 1-for-2 scenarios
    • Consider package deals

  2. Think Long-Term

    • Age matters for ROS and beyond
    • Injury history compounds risk
    • Schedule gets easier/harder

  3. League Context Matters

    • Are you competing now or rebuilding?
    • Do you need a specific position?
    • Who else might trade with you?

  4. Use Charts

    • Position distribution shows balance
    • Power rankings show standing
    • Visual insights help decisions

  5. Re-analyze Weekly

    • Projections change
    • Injuries happen
    • New opportunities emerge

📚 Next Steps

Once comfortable with basics:

  1. Customize Scoring - Edit SCORING_WEIGHTS in app.py
  2. Adjust Baselines - Match your league size
  3. Add ML Predictions - Train models on historical data
  4. Export Analysis - Save trade history and results
  5. Multi-League - Analyze multiple leagues

🤝 Share Insights

Use the analysis to:

  • Propose trades to league mates
  • Justify your trade offers
  • Counter-offer with data
  • Build trade packages

❓ Common Questions

Q: Does this work for dynasty leagues? A: Yes! Age adjustments help with dynasty valuation. Future versions will add explicit keeper/dynasty modes.

Q: Can I use this for DFS? A: Not directly - this is designed for season-long leagues. But projections could inform DFS decisions.

Q: How accurate are the projections? A: With real API data, projections are from SportsDataIO (used by NFL teams). No projection is perfect, but these are industry-standard.

Q: Can I analyze trades that already happened? A: Yes! Use the manual analyzer to evaluate past trades and learn.

Q: Does it work for other platforms (ESPN, Yahoo)? A: Currently only Sleeper API is integrated. Manual entry works for any platform.

🎓 Learn More

  • Read README_STREAMLIT.md for detailed documentation
  • Check config_example.py for customization options
  • Review app.py code comments for technical details

Ready to dominate your league? Let's analyze some trades! 🏈