This is the code base I created to both collect football data, and then use this data to train a neural network to predict the outcomes of football matches based on the fifa ratings of a team's starting 11.
See the blog post for more information on the methodology.
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.
You'll need:
To install the dependencies,
pip install -r requirements.txt`
The crawlers are all written using Scrapy. For proper usage it would be beneficial to first know how to use Scrapy.
For a quick start, just go to ./fifa_ratings_predictor/crawler and
use
scrapy crawl <spider name> -o <output file>
It goes without saying that if you do use these crawlers, please don't bombard the sites with a stupid amount of requests - scrape responsibly.
I have deliberately left all of the data off of the repo because a) it's not really my data and b) it's not good practice to have data on a repo.
To install everything except the crawler you can run
pip install .
from the top level directory.
You can then import the methods, for example the simulator,
from fifa_ratings_predictor.simulation import SeasonSimulator
- Python 3.6 - The programming language
- Scrapy - Scraping framework
- TensorFlow - Neural network framework
Get in contact on Twitter if you have any issues.
This project is licensed under the MPL-2.0 License - see the LICENSE file for details