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This small project can import football results by using a webcrawler and analyse the data in flask.

License: MIT License

Python 71.49% Makefile 0.12% HTML 28.40%
webcrawler requests beautifulsoup csv pandas mathplotlib flask bootstrap python

flask_football's Introduction

Football

This small project can import football results by using a webcrawler and analyse the data in flask.

It was created to learn flask, web crawling, data processing and data visualization.

Features

  • flask generates an interactive GUI environment
  • extract the soccer results from the official DFB-website (https://www.dfb.de/index/)
  • format and save the data in CSV-files automatically
  • get season overviews
  • create dynamic data diagrams
  • calculate the attack/defence value of each club and try to predict the results (based on poisson)
  • compare the predicted and real results by using the coefficient of determination (R²)



First Steps:

Import results

  • open main.py and choose the url for a league

  • run:

GET_ALL(url)
  • results will be saved in a CSV-file automatically (folder: CSV)

Select a data source

  • open main.py and select the CSV-file you want to work with



GUI

start START_Gui.py (default IP: 127.0.0.1:5000)

choose a club in the dropdown menu:

drawing

now you can switch between the options and analyse the data:

drawing



Example calculation:


drawing

flask_football's People

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