GUI for creating football visualizations
This guide provides step-by-step instructions for installing Python, Anaconda, and Jupyter Notebook on both macOS and Windows.
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Open a terminal.
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Check if Python is already installed:
python --version
If Python is not installed, install it using Homebrew: /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
brew install python
Download the latest Python installer from the official website: Python Downloads. Run the installer and make sure to check the box that says "Add Python to PATH" during installation. Click "Install Now" and wait for the installation to complete. Verify the installation by opening a command prompt and typing:
python --version
macOS and Windows
Download the Anaconda installer from the official website: Anaconda Downloads. Run the installer and follow the on-screen instructions. During installation, make sure to check the box that says "Add Anaconda to my PATH environment variable." Click "Install" and wait for the installation to complete. Verify the installation by opening a new terminal or command prompt and typing:
conda --version
##Jupyter Notebook Installation macOS and Windows
Open a terminal or command prompt. Install Jupyter Notebook using conda:
conda install -c conda-forge jupyterlab
Start Jupyter Notebook by typing:
jupyter notebook
Your default web browser should open with the Jupyter Notebook interface. Create a new notebook or open an existing one to start working.
This tool allows you to visualize soccer event data in an interactive GUI. It produces visualizations like touchmaps, passmaps, etc. for selected players.
The tool requires the following to run:
Python 3.x Jupyter Notebook Packages: tkinter, pandas, matplotlib, mplsoccer, soccerdata, socceraction See the instructions above on setting up Python and the required packages.
The tool expects seasonal data files to be placed in a csv folder. The files should follow this naming convention: merged_2324_LaLiga.csv merged_2324_LaLiga_spadl.csv
The merged_season_leaguename.csv file contains the event data. The merged_season_leaguename_spadl.csv file is optional and only needed for visualizing carries.
To get a player's Understat ID, go to their profile page on www.understat.com. The ID will be in the URL: https://understat.com/player/99
The ID in this case is 99.
Once the data is set up, run the Jupyter Notebook and interact with the GUI to generate visualizations.
The following visualizations are supported: Touchmap, Passmap, Defensive Actions, Take-ons, Half-space and zone14 passes, Receptions, Carries, Shots. Select the player, season, and visualization types, then click "Create Vizzes" to generate the images.
- Run the Zude05 Notebook file from JupterNotebook
- Click on the Load csv button.
- Select the Team
- Select the Player
- Insert the understat ID of the player if you want to visualize shots with xG.
- Pick the Colors
- Setup Figure and Pitch Configuration
- Select your first colormap for the receptions and the second one for xG and xT (carries).
- Choose your visualizations from the checkboxes.
- Click on Create Vizzes.
- You will find the vizzes in the Output folder. Make this directory where the Notebook is located, if it's not there already.