FIFA 22 Ultimate Team Recommender

Overview

This is project using Python to scrap FIFA player data from an open source website SoFIFA and apply automated non-interacitve scripts to process crawled data, then fit models to player statistics to setup a recommender (With UI) of players in FIFA22 given user inputs as constraints eg. budget, potential, attribute and etc.

Authors:

Chloe Zhang:

Jinghan Xu:

Minting Fu

Muke Wang

Shiyang Zhang

Tony Liang:

Usage of the project (Instructions)

1. Without using Docker

To replicate this project, clone this GitHub repository, install the dependencies listed below, and run the following command at the command line/terminal from the root directory of this project:

make all

To reset the repo to a clean state, with no intermediate or results files, run the following command at the command line/terminal from the root directory of this project:

make clean

2. Using Docker to run on Jupyter lab

1) Clone this GitHub repository and run the following code in the terminal

git clone https://github.com/FIFA22-UT-Recommender/fifa22-ultimate-team-recommender

2) Run this firstly in your terminal to pull latest docker image

docker pull tonyliang19/fifa22-ultimate-team-recommender

3) Run the following command to run the container based on the latest image

docker run -it --rm -v /$(pwd):/opt/notebooks/ -p 8888:8888 tonyliang19/fifa22-ultimate-team-recommender

4) After the command runs, copy the last link in your terminal similar to the following:

http://127.0.0.1:8888/lab?token=f4eef0c11762e60a7974f3ea3eb352a4913e70755433398b and open it on any browser like Google Chrome or Mozilla Firefox.

Then you should be able to run and explore the project interactively!

Dependencies

License

The underlying source code used to format and display the content of this project is licensed under the MIT License