Game. Set. Data. An open-source laboratory dedicated to unveiling the hidden patterns of professional tennis through interactive data stories.
| Story | Live Link | Key Metric / Insight |
|---|---|---|
| The Race to Greatness | View Story | Insight: Nadal was a prodigy; Federer was a relatively late starter compared to his Big 3 peers. |
| Slam Power Rankings | View Story | Insight: GSDI reveals Bjorn Borg as the 'Don Bradman of tennis,' with dominance levels rivaling Nadal on clay. |
| Grand Slam Nail-Biters | View Story | Insight: Ranks the 2019 Wimbledon Final as the most exciting match ever; benchmarks the Alcaraz-Sinner RG clash as a modern epic. |
| Geography of Talent | View Story | Insight: Maps the 50-year talent shift from traditional strongholds to a globalized landscape. |
| Rivalry Networks | View Story | Insight: Player "gravity" and connections forged through historical matches and finals. |
| Indian Tennis Journey | View Story | Insight: Highlights the 70s-80s peak and the modern 'Singles Gap' despite worldwide doubles success. |
| The Road to a Slam | View Story | Insight: 90% win before age 27. Most legends make a definitive mark within 1-3 years on tour. |
| Brutal Tennis | View Story | Insight: 1/2500 high-schoolers turn pro. 50% quit within 2 yrs. 90% never win a trophy. |
- Interactive Storytelling: Narrative-driven data explorations built with D3.js and ECharts.
- Advanced Export Engine: Record HD videos of animations for social media with branded watermarks.
- Deep Analytics: Introducing custom metrics like the GSDI (Dominance Index) and NBI (Drama Index).
- Mobile First: All visualizations are optimized for mobile consumption with custom UI patterns.
- SEO & Social Ready: Full Open Graph and Twitter Card integration for rich previews.
- Frontend: D3.js v7, ECharts, Vanilla JS, CSS3 (Custom Design System).
- Data Engineering: Python (located in the sister repo tml-data).
- UI Architecture: Modular component injection for headers, footers, and sharing tools.
This repository is optimized for AI discovery.
- Knowledge Guide: See
readmeLLM.mdfor technical patterns. - AI Skill: See
.github/skills/for agentic capabilities. - Technical Summary: See
llms.txt.
We love new ideas! Whether it's a new visualization technique or a data question you want answered:
- Browse Open Issues.
- Suggest a new "Data Story" via the Issue tracker.
- Check the TODO.md for the project roadmap.
If you use this project for research or articles, please cite it:
@software{Kumar_Tennis_Analytics_Data_2024,
author = {Kumar, Saurabh},
title = {{Tennis Analytics: Data, Analysis and Visualization}},
url = {https://github.com/sorukumar/tennis-analytics},
version = {1.0.0},
year = {2024}
}Created with ❤️ for the tennis community by Saurabh Kumar