EmilDanielsson / Player-Rating-Project

This project aims to rate football players using data and statistics recorded from the last match they participated in. Much of the code included in this project can be used for other purposes when working with the Wyscout data set. For example minutes_played.py, fitting_functions.py and KPI_functions.py.

Player_Rating_Project

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Instruction of how to run the files, and what needs to be downloaded beforehand, for the Player_Rating_Project. Project has been carried out at Uppsala university for the course "Advanced Course on Topics in Scientific Computing I", HT2021 period 1.

Python Packages Needed

• pandas
• numpy
• json
• matplotlib
• seaborn
• mplsoccer
• sklearn
• statsmodels
• tabulate

Downloads

Make sure to have Python3 downloaded, along with needed packages listed above.

Get the Wyscout data from: https://figshare.com/collections/Soccer_match_event_dataset/4415000/2

The following data sets from Wyscout are needed: "events.json", "matches.json", "players.json" and "teams.json".

Place the downloaded Wyscout data in a folder named: Wyscout, placed two levels above the Python code (see below).

Download the folder 'Json_files' from https://drive.google.com/drive/folders/1Yhta6-kl6Z9sn_Uy2JpMC9UiNObn6VFz?usp=sharing and place at one level above the Python code (see below). The files in this folder can also be generated if the Wyscout data is downloaded by running the following programmes in order:

1. create_events_df_eu.py

2. minutes_played.py

3. create_KPI_dataframe.py 

(4.) create_KPI_dataframe_EDIT.py (need some modifications, see comments)

This is though not recomended since it takes quite a lot of time to run create_KPI_dataframe.py.

Also download Excel-sheet Gameweek_38.xlsx from https://docs.google.com/spreadsheets/d/1bIpAxH0iWEot8tAlIQcvBB_uX-Au-qjX/edit?usp=sharing&ouid=117928085659621731785&rtpof=true&sd=true and place at one level above the Python code (see below).

Running Instructions

When the folders and files above are downloaded (or created) the following programs can be ran to see the resulting ratings from gameweek 38

1. GW_38_Ratings.py

2. the_match_ranking.py

The following programs can then be ran to evalute the ratings and the xG-model

1. GW_38_Ratings_evaluation.py

2. xG_model_evaluation.py

3. validation_vs_WhoScored.py

Project Organization

├── README.md                               <- The top-level README for running this project.
|
├── Wyscout                                 <- Wyscout data folder.
│   │
│   ├── players.json
│   │
│   ├── teams.json  
│   │
│   ├── events            
│   │   ├── events_England.json
│   │   ├── events_France.json
│   │   ├── events_Germany.json
│   │   ├── events_Italy.json
│   │   └── events_Spain.json
│   │
│   └── matches            
│       ├── matches_England.json
│       ├── matches_France.json
│       ├── matches_Germany.json
│       ├── matches_Italy.json
│       └── matches_Spain.json
│
└──Player_rating_Project                    <- Main folder for this project.
    |
    │── Gameweek_38.xlsx                    <- Excel with validation data from Whoscored to compare with.
    │
    │── Json_files                          <- Folder where created json-files are stored.
    │
    └── Python_Code                         <- Source code for this project.
        |
        |── create_events_df_eu.py
        |── create_KPI_dataframe_EDIT.py
        |── create_KPI_dataframe.py
        |── FCPython.py
        |── fitting_functions.py
        |── GW_38_Ratings_evaluation.py
        |── GW_38_Ratings.py
        |── KPI_functions.py
        |── minutes_played.py
        |── the_match_ranking.py
        |── validation_vs_WhoScored.py
        └── xG_model_evaluation.py

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By: Jakob Edberger Persson and Emil Danielsson, 2021