mplsoccer is a Python library for drawing soccer/football pitches in Matplotlib and loading StatsBomb open-data.

Use the package manager pip to install mplsoccer.

pip install mplsoccer

Here are the docs for mplsoccer.

Plot a StatsBomb pitch

from mplsoccer.pitch import Pitch
pitch = Pitch(pitch_color='grass', line_color='white', stripe=True)
fig, ax = pitch.draw()

mplsoccer shares some of the tools I built for the OptaPro Analytics Forum. At the time there weren’t any open-sourced python tools. Now alternatives exist, such as matplotsoccer.

By using mplsoccer, I hope that you can spend more time building insightful graphics rather than having to learn to draw pitches from scratch.

mplsoccer:

1. draws 7 different pitch types by changing a single argument, which is useful as there isn’t a standardised data format
2. extends matplotlib to plot heatmaps, (comet) lines, footballs and rotated markers
3. flips the data coordinates when in a vertical orientation so you don’t need to remember to flip them
4. creates tidy dataframes for StatsBomb data, which is useful as most of the alternatives produce nested dataframes

MIT

Contributions are welcome. It would be great to add the following functionality to mplsoccer:

• pass maps
• pass sonars
• Voronoi diagrams

Examples to help others are also welcome for a gallery.

Please get in touch at [email protected] or @numberstorm on Twitter.

mplsoccer was inspired by other people's work:

• Peter McKeever inspired the API design
• ggsoccer - a library for plotting pitches in R
• lastrow - often tweets animations from matches and the accompanying code
• fcrstats - tutorials for using football data
• fcpython - Python tutorials for using football data
• Karun Singh - tweets some interesting football analytics and visuals
• StatsBomb - great visual design and free open-data
• John Burn-Murdoch's tweet got me interested in football analytics