Group Members: Yuchen Wu, Xinmeng Zhang
Inspiration
We are aware that some soccer scouts use the dataset of the FIFA game to filter players in the real world, so analyzing the dataset of FIFA might help us understand soccer better.
What it does
This project makes various visualizations of the features of soccer players, such as age, wage, height, weight, and nationality, and offers an analysis of these visualizations. The project also includes the machine learning part that predicts the wage of players using the ratings.
How we built it
We built it with python on Google Colab and Github. We connect with each other on Discord
Challenges we ran into
Our project includes some new libraries such as plotly and wordcloud that are difficult to understand at first. We also spent a lot of time adjusting the machine learning part
Accomplishments that we're proud of
The wordmap and radar graph were pretty cool, and the machine learning part really offers some insight of real world soccer
What we learned
We learned the interesting statistics of soccer players such as income level and average height.
What's next for FIFA Players Rating and Wage Analysis
We want to look at the players for each age range such as under 20, 20-25, 25-30, over 30, etc.
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