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Showing posts from October, 2021

Classifying profitable soccer players

Overview In this project I set out to create a classification model in order to predict key characteristics where soccer players are expected to show significant market value growth in the short to mid-term future. I relied on data available on, a European soccer player market valuation database/website used by soccer clubs around the world.  Data Collection and Cleaning In order to collect the relevant data, I developed a scrapping program using Beautiful Soup on Python. After scraping all of the necessary data, I used python to remove any null values and standardized all data types. After collecting and cleaning the data through Python. I was finally ready to perform preliminary data exploration to find any key trends of themes in the dataset.  Exploratory Data Analysis Size = Change in market value, X = age, Y = Market Value From an initial review of the dataset, I found that there was most likely a strong relationship between the age of the player and expected mar