Player Similarity and Interpolation Model using Clustering:

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Player Similarity Model: A model that is used to find players, similar to the given player based on various stats and features using clustering and cosine similarity. Player Interpolation Model: A model capable of combining existing stats and features of two different players and finding players similar to the combined profile.

Similarity

Interpolation

Environment:

• Coded in Python 3.8
• This was trained in a cloud runtime (Colab).

Code folder structure:

• data - has the master and supporting databases.
• model.ipynb - has the models.

Instructions to run code:

• Run pip install matplotlib numpy pandas sklearn soccerplots to install the required dependencies.
• Open model.ipynb to get an interactive iterface of the model.

Team Members

• Sreyas
• Sricharan
• Sathish Prasad
• Sriram