Sport Analytics Tools is a project dedicated to publishing information (code, tutorials, media) to help data scientists and sports enthusiasts work with sports data effectively.

• I believe that open-source solutions are superior to proprietary technologies.
• I believe that if you've solved a problem or possess valuable knowledge, you should share it.

The goal of this project is to assist people interested in sports data science in tackling data analysis tasks.

• I've developed nba_data, a repository of NBA data that can be accessed in seconds instead of hours via the NBA API.
• I am the author of the nba-on-court library, which simplifies working with NBA data.
• I am a contributor to well-known sports libraries such as nba_api, hoopR, and worldfootballR.

Through this project, I aim to create a comprehensive knowledge base of tools and resources to enhance the workflow with sports data.

Tool for mapping player IDs between NBA Stats API and Basketball Reference.

• Automated ID mapping between different basketball data sources
• Multiple matching algorithms for high accuracy
• Handles special cases and non-English names
• Easy-to-use Python interface

• Python 3.8+
• Core dependencies: beautifulsoup4, numpy, pandas, requests, nba_api, python-Levenshtein

Learn more about NBA Player ID Mapping Tool →

A lightweight Python module for quickly retrieving football match event data from WhoScored.com using a provided match_id. Supports direct export to multiple formats:

• raw
• event
• spadl
• atomic-spadl

• Fast, direct event retrieval by match_id (no schedule/tournament setup needed)
• Outputs in multiple formats for downstream analysis
• In-memory conversion to SPADL/atomic-SPADL (no disk I/O)
• Works for matches outside major European leagues and one-off games

• Quick analysis of individual matches (especially outside Big Five leagues)
• Immediate access to event data in SPADL/atomic-SPADL formats

• Manual entry of match_id required
• Not intended for bulk downloads or production systems

Learn more about whoscored_light →

# Clone the repository
git clone https://github.com/shufinskiy/sport_analytics_tools.git
cd sport_analytics_tools

Contributions are welcome! Please feel free to submit pull requests, particularly for:

• Adding new tools for sports analytics
• Improving existing functionality
• Adding documentation and tutorials
• Bug fixes and optimizations

Apache License 2.0