![mplsoccer logo](https://raw.githubusercontent.com/andrewRowlinson/mplsoccer/main/docs/source/logo.png)
**mplsoccer is a Python library for plotting soccer/football charts in Matplotlib
and loading StatsBomb open-data.**
---
## Installation
Use the package manager [pip](https://pip.pypa.io/en/stable/) to install mplsoccer.
```bash
pip install mplsoccer
```
Or install via [Anaconda](https://docs.anaconda.com/free/anaconda/install/index.html).
```bash
conda install -c conda-forge mplsoccer
```
---
## Docs
Read more in the [docs](https://mplsoccer.readthedocs.io/) and see some
examples in our [gallery](https://mplsoccer.readthedocs.io/en/latest/gallery/index.html).
---
## Quick start
Plot a StatsBomb pitch
```python
from mplsoccer import Pitch
import matplotlib.pyplot as plt
pitch = Pitch(pitch_color='grass', line_color='white', stripe=True)
fig, ax = pitch.draw()
plt.show()
```
![mplsoccer pitch](https://raw.githubusercontent.com/andrewRowlinson/mplsoccer/main/docs/quick_start.png)
Plot a Radar
```python
from mplsoccer import Radar
import matplotlib.pyplot as plt
radar = Radar(params=['Agility', 'Speed', 'Strength'], min_range=[0, 0, 0], max_range=[10, 10, 10])
fig, ax = radar.setup_axis()
rings_inner = radar.draw_circles(ax=ax, facecolor='#ffb2b2', edgecolor='#fc5f5f')
values = [5, 3, 10]
radar_poly, rings, vertices = radar.draw_radar(values, ax=ax,
kwargs_radar={'facecolor': '#00f2c1', 'alpha': 0.6},
kwargs_rings={'facecolor': '#d80499', 'alpha': 0.6})
range_labels = radar.draw_range_labels(ax=ax)
param_labels = radar.draw_param_labels(ax=ax)
plt.show()
```
![mplsoccer radar](https://raw.githubusercontent.com/andrewRowlinson/mplsoccer/main/docs/quick_start_radar.png)
---
## What is mplsoccer?
In mplsoccer, you can:
- plot football/soccer pitches on nine different pitch types
- plot radar charts
- plot Nightingale/pizza charts
- plot bumpy charts for showing changes over time
- plot arrows, heatmaps, hexbins, scatter, and (comet) lines
- load StatsBomb data as a tidy dataframe
- standardize pitch coordinates into a single format
I hope mplsoccer helps you make insightful graphics faster,
so you don't have to build charts from scratch.
---
## Want to help?
I would love the community to get involved in mplsoccer.
Take a look at our [open-issues](https://github.com/andrewRowlinson/mplsoccer/issues)
for inspiration.
Please get in touch at rowlinsonandy@gmail.com or
[@numberstorm](https://twitter.com/numberstorm) on Twitter to find out more.
---
## Recent changes
View the [changelog](https://github.com/andrewRowlinson/mplsoccer/blob/master/CHANGELOG.md)
for a full list of the recent changes to mplsoccer.
---
## Inspiration
mplsoccer was inspired by:
- [Peter McKeever](https://petermckeever.com/) heavily inspired the API design
- [ggsoccer](https://github.com/Torvaney/ggsoccer) influenced the design and Standardizer
- [lastrow's](https://twitter.com/lastrowview) legendary animations
- [fcrstats'](https://twitter.com/FC_rstats) tutorials for using football data
- [fcpython's](https://fcpython.com/) Python tutorials for using football data
- [Karun Singh's](https://twitter.com/karun1710) expected threat (xT) visualizations
- [StatsBomb's](https://statsbomb.com/) great visual design and free open-data
- John Burn-Murdoch's [tweet](https://twitter.com/jburnmurdoch/status/1057907312030085120) got me
interested in football analytics
---
## License
[MIT](https://choosealicense.com/licenses/mit)
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