https://github.com/vishaalpkumar/fifa-ratings-predictor

A market value predictor for a custom football player
https://github.com/vishaalpkumar/fifa-ratings-predictor

Last synced: 19 days ago
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A market value predictor for a custom football player

• Host: GitHub
• URL: https://github.com/vishaalpkumar/fifa-ratings-predictor
• Owner: VishaalPKumar
• Created: 2022-08-08T23:10:27.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2022-08-08T23:13:06.000Z (over 2 years ago)
• Last Synced: 2024-11-05T10:48:36.168Z (2 months ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 9.22 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# FIFA-Ratings-Predictor

CIS545 Final Project - FIFA Dataset Analysis

By Vishaal, Jeffrey, and Vikram

**Project Idea**

FIFA is titled as the best-selling sports video game franchise in the world. Football and players are obsessed with the game. Every year, fans are eager to know what the ratings of their favorite players are for the next iteration of FIFA. Oftentimes Electronic Arts (EA), the creators of FIFA, are questioned for their rating decisions and there is a lot of debate in the football community about the validity of these player ratings. We thought it would be interesting to analyze the player ratings, and team statistics in order to see some trends in the way EA rates football players. It would be interesting to visualize the similarities and differences among leagues, clubs, and national teams. We could answer some of football’s most debated questions:

Does your transfer value depend on the league you play in?

Which domestic league is the most competitive (player rating wise)

And so much more!

Here's the coolest part of this project, using this data analysis, we we can create a market value predictor - Depending on the different attributes/traits of the custom player, this predictor would estimate the market value of a player, as well as their salary. We've merged out player statistical data with WAGE and TRANSFER VALUE data that will allow us to perform supervised machine learning.

**Useful Links Related to this Project**

Dataset Source: https://sofifa.com and https://www.kaggle.com/bryanb/fifa-player-stats-database?select=FIFA17_official_data.csv

How Fifa Ratings are Calculated: https://www.earlygame.com/fifa/fifa-ratings-explained-overall-rating/

We've written a Medium article detailing our journey to demystifying the FIFA algorithm [here](https://medium.com/@vishaalkumar_21306/e391bce93ec9)!