JohnsonJDDJ/zilean

Python package that facilitates machine learning tasks on League of Legends matches.

37
/ 100
Emerging

This tool helps esports analysts and data enthusiasts dive deep into League of Legends match data. It takes raw match timeline information from the Riot Games API, which details game statistics at every minute, and transforms it into structured data. You can then use this data to predict match outcomes or analyze player performance at specific points in a game.

No commits in the last 6 months.

Use this if you want to analyze detailed, minute-by-minute League of Legends match data to uncover patterns, predict game results, or evaluate player strategies using machine learning.

Not ideal if you're looking for simple match win/loss records or basic player statistics without needing granular, time-series analysis.

esports-analytics league-of-legends game-strategy player-performance predictive-modeling
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 15 / 25

How are scores calculated?

Stars

15

Forks

5

Language

Python

License

MIT

Last pushed

Aug 12, 2022

Commits (30d)

0

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