MORALE CHECK Elo Tracker

Track Elo ratings for your local gaming club using automated web scraping from Best Coast Pairings (BCP).

Features

• Automated Event Scraping: Extract match results from BCP events with a single command
• Team Filtering: Track only matches between your team members at larger tournaments
• Faction Tracking: Capture which army/faction each player used in each match
• Automatic Event Management: Sequential event numbering and metadata tracking
• Clean Name Handling: Automatic name normalization and cleaning
• Polite Scraping: Built-in delays and realistic browser fingerprinting
• Elo Calculations: Standard Elo rating system (K-factor 32, default 1500)
• Glicko-2 Calculations: Alternative rating system tracking rating confidence (RD) and volatility
• Pretty Rankings: Generate Discord-ready markdown tables

Installation

1. Clone the repository

   git clone https://github.com/boada/mc_elo.git
   cd mc_elo

2. Install dependencies

   pip install -r requirements.txt
   playwright install chromium

Usage

Scrape an Event

# MORALE CHECK team filter (default)
python bcp_all_rounds.py <event_id> <num_rounds>

# Different team name
python bcp_all_rounds.py <event_id> <num_rounds> "OTHER TEAM"

# No team filter (all matches)
python bcp_all_rounds.py <event_id> <num_rounds> none

Example:

python bcp_all_rounds.py kxuw1i2Xdykm 3

The scraper will:

• Automatically assign the next event number
• Fetch team roster and factions from BCP
• Extract all rounds with match results
• Filter for MORALE CHECK team-only matches (default)
• Save to data/events/event_XXX.csv

Update Elo Rankings

python update_elo.py

This combines all event CSVs and recalculates current Elo ratings from scratch. Note: Deletes existing ratings.json to prevent ghost players from filtered events.

Update Glicko-2 Rankings

python glicko_updater.py

Uses the Glicko-2 system, which additionally tracks:

• Rating Deviation (RD): Confidence in the rating — lower means more certain
• Volatility: How consistent a player's performance is

Output is saved to glicko_ratings.json.

View Rankings

python show_rankings.py

Generates a markdown-formatted table with:

• Player rankings by Elo rating
• Win-loss records (W-L or W-D-L if draws exist)
• Dynamic column widths for clean display
• Ready to paste into Discord or other platforms

Project Structure

mc_elo/
├── bcp_all_rounds.py      # Main web scraper
├── event_manager.py       # Event metadata tracking
├── elo_updater.py         # Elo calculation engine
├── glicko_updater.py      # Glicko-2 calculation engine
├── update_elo.py          # Combine events and update ratings
├── show_rankings.py       # Display formatted rankings
├── name_cleaner.py        # Name normalization utilities
├── requirements.txt       # Python dependencies
├── data/
│   ├── events/           # Individual event CSVs
│   │   ├── event_001.csv
│   │   └── event_002.csv
│   ├── events.json       # Event metadata registry
│   └── all_events.csv    # Combined match history
└── ratings.json          # Current Elo ratings
└── glicko_ratings.json   # Current Glicko-2 ratings (with RD and volatility)

Data Format

Event CSV Columns

• event_num: Sequential event number
• event_id: BCP event ID
• round: Round number
• player1: First player name (cleaned)
• player2: Second player name (cleaned)
• result: Match result (1 = player1 win, 0 = player1 loss, 0.5 = draw)
• player1_faction: Army/faction player1 used (if team filter enabled)
• player2_faction: Army/faction player2 used (if team filter enabled)

How It Works

1. Team Roster Extraction: Scrapes the main placings page to get team roster and faction data
2. Match Scraping: Iterates through each round using the ?round=N parameter
3. Name Cleaning: Normalizes names (Title Case, removes parentheticals)
4. Team Filtering: Only includes matches where both players are on the team
5. Elo Calculation: Standard Elo formula with K=32, starting rating=1500
6. Glicko-2 Calculation: Processes matches in batch per rating period; tracks RD (confidence) and volatility alongside rating

Best Practices

• Polite Scraping: The scraper includes 2-5 second delays between requests
• Team Filtering: Use team names to avoid polluting rankings with external matches
• Sequential Events: Events are numbered automatically to maintain chronological order
• Backup Data: The data/ directory contains all match history

Future Enhancements

• Faction-specific Elo ratings
• Matchup win rate analysis
• Player statistics and trends
• Web dashboard/UI
• Head-to-head records

Requirements

• Python 3.8+
• Playwright (for web scraping)
• Access to BCP event pages

License

MIT

Credits

Built for the MORALE CHECK gaming club.