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Predicting-the-Market-Value-of-Footballers

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About this project

- In this study, the prediction of the market value of the football players whose specific features were entered was performed.
  • It turns out that “ball control” is more important than other features, according to my feature selection.

-To take this project further, more attention could be paid to the feature engineering parts, for example, as I mentioned in the article, one-hot encoding could be used to infer teams or mathematical operations could be done to increase the correlation between some features, like averaging two columns. And as a further future project, we could publish this model as a website, with a simple interface that would allow users, such as coaches, to know in advance how much market value their players will have in a completely online environment.

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