GitHub repository: vineethsaivs/Highest-Paid-Athletes-Analysis-With-Python
Primary language: Jupyter Notebook
Created: 2022-01-21T07:30:19Z
Description: Football clubs spend a huge amount of money every year to buy professional football players during the transfer window. Predicting how much players' value in the transfer market is one of the difficult tasks for managers of the club. Transfer market.com determines the players’ value using football experts. As crowdsourcing is needed, it is updated infrequently because of the participation of many users and humans are prone to errors. Data scientists around the world are attracted to this topic since then to create datasets and estimate using data-driven methods. The data-driven method seems to be an alternative approach for crowd driven websites for estimating players’ market value. I have constructed a dataset using 4250 players from 150 teams playing in European competitions and a period of five seasons. I have estimated players’ market value using regression analysis.