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Soccer-Players-Clustering

This Project is created as part of Introduction to Machine Learning course included in Data Science Studies at Warsaw University of Technology. We are using the dataset from Kaggle: • https://www.kaggle.com/datasets/spicemix/soccer-detailed-players-match-data?resource=download&select=players_away_matches.csv.

Our project goal is to find the best possible clustering model for analysing player performance data in football matches in order to provide insight to teams, coaches, analysts, scouting agencies and betting companies

Project team:

Anna Ostrowska

Mateusz Iwaniuk

Validators team:

Paweł Florek

Mateusz Deptuch

1st part of the project - Exploratory Data Analysis

Can be found in the folder "EDA".

2nd part of the project - feature engineering

Can be found in the folder "feature_validation".

3rd part of the project - final

Includes the final model selected by us for the realisation of the business plan. Can be found in the "final" folder.

Final reports

Reports are written in Polish.

They can be found in "raport" and "raport_walidacyjny" file.

We have also report about our validator work for the other team.

Presentation

The final presentation in Polish can be found in the "Ocena występów piłkarzy" file.

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Our project goal is to find the best possible clustering model for analysing player performance data in football matches in order to provide insight to teams, coaches, analysts, scouting agencies and betting companies.

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