https://github.com/somdeep/Statball

Statball - Football soccer stats analyser from top 5 european leagues with data obtained by web scraping from Fbref and Statsbomb
https://github.com/somdeep/Statball

csharp data-science data-scraping data-viz dotnet dotnet-core fbref football football-analytics football-data scouting-data scraping soccer soccer-analytics soccer-data statsbomb tableau visualizations

Last synced: about 1 month ago
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Statball - Football soccer stats analyser from top 5 european leagues with data obtained by web scraping from Fbref and Statsbomb

• Host: GitHub
• URL: https://github.com/somdeep/Statball
• Owner: somdeep
• License: mit
• Created: 2021-05-31T05:36:25.000Z (over 3 years ago)
• Default Branch: master
• Last Pushed: 2023-04-08T19:25:23.000Z (over 1 year ago)
• Last Synced: 2024-07-07T22:35:36.390Z (2 months ago)
• Topics: csharp, data-science, data-scraping, data-viz, dotnet, dotnet-core, fbref, football, football-analytics, football-data, scouting-data, scraping, soccer, soccer-analytics, soccer-data, statsbomb, tableau, visualizations
• Language: C#
• Homepage:
• Size: 3.93 MB
• Stars: 18
• Watchers: 2
• Forks: 2
• Open Issues: 6
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• awesome-football - **somdeep/Statball**

README

        
# Statball [![build passing](https://img.shields.io/badge/build-passing-brightgreen.svg?style=flat)]() [![dotnet core](https://img.shields.io/badge/dotnet-6.0-blue.svg?style=flat)](https://learn.microsoft.com/en-us/dotnet/core/install/windows?tabs=net60)

Statball - Football (soccer) stats analyser from top 5 european leagues with data obtained from Fbref and Statsbomb.

Fbref : https://fbref.com/en/comps/Big5/Big-5-European-Leagues-Stats

Statsbomb : https://statsbomb.com/

Visualizations created using Tableau Public : https://public.tableau.com/

1. Built-In Data Scraper/ API to pull or scrape data from fbref and Statsbomb - using C# / webapp / web scraping

2. Preferred position filtering

3. Combined statscore value

4. Multi resource file processing - for combined statscore value as well

5. Clustering based talent identification

6. Performance/Role analysis

7. Similarity analysis for position/player using Cosine/other similarity  - vector/array based

8. Player scouting based on customisable player profiles and statscore based scouting.

## **Visualization and Scouting Samples**

**Visualization 1** : Heavily Involved Creators, and Messi in a league of his own (20/21, minimum 20 90s).

![europecreatorsandteams](https://user-images.githubusercontent.com/14120777/126045267-0c9dd978-b226-4f52-b316-73e26296a03f.png)

**Sample 1** : Top 30 AM profile players from top 5 leagues (20/21, stats p90, minimum 20 90s).

![image](https://user-images.githubusercontent.com/14120777/126031154-3a13b672-dcb2-4dbf-9be7-5dae79295205.png)

## **Prerequisite Installations**

**Download and install .NET Core from here** : https://docs.microsoft.com/en-us/dotnet/core/install/windows?tabs=net50

**How to Run** : Download the project and run the **dotnet run** command as below : 

```

dotnet run

dotnet run -h|--help

```

Follow steps here if needed : https://docs.microsoft.com/en-us/dotnet/core/tools/dotnet-run