Professor: Stephen Lee
30 November 2016
Abdullah Alowairdhi
University Of Idaho, Moscow, ID
Projects II & III
Data Visualization D3.js
Data Science (the Future of the Internet)
Analysis of Soccer's Player Performance
Identifying the most important attributes of Soccer player's performance which determine their overall ratings by using series of supervised and unsupervised classifications and regression techniques
“Does the dataset tell us what are the set of skills/attributes that determines the overall rating of a soccer plyer performance? Therefore, we can decide to buy that player or not.”
“Soccer players with certain set of skills/attributes are more likely to have higher performance rating than other players”.
Players and Teams' attributes sourced from EA Sports' FIFA video game series, http://sofifa.com/ FIFA series and all FIFA assets property of EA Sports.
7 datasets - 183 attributes & 200,000 observations
2 dataset Selected :
Player dataset with 11,060 obs and 7 attrbs &
Player_Attributes dataset with 183,978 obs and 42 attrbs