https://github.com/lucasmaystre/kickscore

Pairwise comparisons with flexible time-dynamics.
https://github.com/lucasmaystre/kickscore

elo-rating machine-learning ranking

Last synced: 4 months ago
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Pairwise comparisons with flexible time-dynamics.

• Host: GitHub
• URL: https://github.com/lucasmaystre/kickscore
• Owner: lucasmaystre
• License: mit
• Created: 2019-05-12T10:07:31.000Z (about 7 years ago)
• Default Branch: master
• Last Pushed: 2025-09-05T08:29:16.000Z (10 months ago)
• Last Synced: 2025-10-21T19:55:41.504Z (8 months ago)
• Topics: elo-rating, machine-learning, ranking
• Language: Python
• Size: 579 KB
• Stars: 60
• Watchers: 7
• Forks: 15
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# kickscore

[![Build package](https://github.com/lucasmaystre/kickscore/actions/workflows/build.yml/badge.svg)](https://github.com/lucasmaystre/kickscore/actions/workflows/build.yml)

[![Code coverage](https://codecov.io/gh/lucasmaystre/kickscore/branch/master/graph/badge.svg)](https://codecov.io/gh/lucasmaystre/kickscore)

`kickscore` is the dynamic skill rating system powering [Kickoff.ai](https://kickoff.ai/).

In short, `kickscore` can be used to understand & visualize the skill of players (or teams) competing in pairwise matches, and to predict outcomes of future matches. It extends the [Elo rating system](https://en.wikipedia.org/wiki/Elo_rating_system) and [TrueSkill](https://en.wikipedia.org/wiki/TrueSkill).

![evolution of NBA teams\' skill over history](https://lum-public.s3-eu-west-1.amazonaws.com/kickscore-nba-history.svg)

## Getting started

To install the latest release directly from PyPI, simply type:

    pip install kickscore

To get started, you might want to explore one of these notebooks:

- [Basic example illustrating the API](examples/kickscore-basics.ipynb) ([interactive version](https://colab.research.google.com/github/lucasmaystre/kickscore/blob/master/examples/kickscore-basics.ipynb))

- [Visualizing the history of the NBA](examples/nba-history.ipynb) ([interactive version](https://colab.research.google.com/github/lucasmaystre/kickscore/blob/master/examples/nba-history.ipynb))

## References

- Lucas Maystre, Victor Kristof, Matthias Grossglauser, [Pairwise Comparisons with Flexible Time-Dynamics](https://arxiv.org/abs/1903.07746), KDD 2019