Baseball Player Ranker

Compare historical baseball players across any era using the Lahman database. Rank players by configurable weighted stats with era-adjusted z-scores.

Features

• Batter and Pitcher rankings with separate stat sets
• Era-adjusted z-scores so players from different eras are compared fairly
• Configurable stat weights - choose which stats matter and how much
• Position filtering for batters (C, 1B, 2B, 3B, SS, LF, CF, RF, OF, DH)
• Year range selection from 1871 to 2025
• Minimum qualification thresholds (plate appearances / innings pitched)

Quick Start

1. Install dependencies:

   pip install -r requirements.txt

2. Build the database (uses the CSV files already in the repo):

   python scripts/build_db.py

3. Run the app:

   streamlit run app.py

How It Works

For each stat in each season, a z-score is computed: z = (player_value - league_mean) / league_std_dev. This normalizes stats across eras so a .300 BA in the dead-ball era is valued differently than in the steroid era.

When aggregating across seasons, z-scores are weighted by plate appearances (batters) or innings pitched (pitchers). The final composite score is a weighted average of selected z-scores based on user-configured weights.

Data Source

Lahman Baseball Database - complete batting, pitching, and fielding statistics from 1871 to 2025.

Deployment

Deploy for free on Streamlit Community Cloud:

1. Push this repo to GitHub
2. Connect the repo in Streamlit Cloud
3. Set entry point to app.py
4. The build script runs automatically if configured as a setup command

Tech Stack

• Python with Streamlit for the web UI
• SQLite for the database (built from Lahman CSVs)
• pandas for data manipulation and z-score computation