# kickscore
[](https://github.com/lucasmaystre/kickscore/actions/workflows/build.yml)
[](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).
## 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
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