KabaddiPy: A package to enable access to Professional Kabaddi Data
Bhaskar Lalwani, Aniruddha Mukherjee

TL;DR
KabaddiPy is an open-source Python package that provides easy access to comprehensive Kabaddi match data, enabling analysis, modeling, and strategic insights for researchers, coaches, and players.
Contribution
It is the first open-source module to systematically collect, organize, and categorize Kabaddi data from multiple sources, facilitating research and strategic analysis.
Findings
Enables continuous monitoring of Kabaddi data streams
Supports building predictive models and strategic gameplay analysis
Fosters reproducible research in Kabaddi analytics
Abstract
Kabaddi, a contact team sport of Indian origin, has seen a dramatic rise in global popularity, highlighted by the upcoming Kabaddi World Cup in 2025 with over sixteen international teams participating, alongside flourishing national leagues such as the Indian Pro Kabaddi League (230 million viewers) and the British Kabaddi League. We present the first open-source Python module to make Kabaddi statistical data easily accessible from multiple scattered sources across the internet. The module was developed by systematically web-scraping and collecting team-wise, player-wise and match-by-match data. The data has been cleaned, organized, and categorized into team overviews and player metrics, each filterable by season. The players are classified as raiders and defenders, with their best strategies for attacking, counter-attacking, and defending against different teams highlighted. Our module…
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Taxonomy
TopicsICT in Developing Communities
