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MH3511 FIFA Analysis

This is a group project for MH3511 Data Analysis with Computer focusing on the analysis of FIFA players in 2023.

Abstract:

FIFA (International Federation of Association Football) has millions of fans worldwide and the quadrennial World Cup always has everyone excited, and fans all over the world stay up all night to watch their favourite football player play. In our FIFA dataset, there are a lot of exciting variables to see. Through our study and analysis, we aim to explore as much of the dataset as possible and produce insights into some of the burning questions that fans may have about their favourite sport and league. Our study addresses questions such as 'Does the jersey number of the players mean anything?' 'Does the prestige level of the player's team affect his value?' and so on. We will examine the relationships between variables and what meaningful insights they can provide using basic data analysis techniques.

Contributions:

  1. Ivan Lim Khai Ze (Ivan)
  2. Max Tan Han Xian (Max)
  3. Tio Guo Yong (GY)
  4. Yeoh Ming Wei (MW)

Statistical Analysis:

  1. Numerical Data Analysis

    1. One Sample T-test of Average BMI of Players (MW)
    2. Proportion Test of Overall Ratings of Players (MW)
    3. Paired T-test of LongShots vs Finishing (Ivan)
  2. Categorical Data Analysis

    1. Chi-Square Test of JerseyNumber vs BestPosition (Max)
  3. Mixed Data Analysis

    1. ANOVA Test of Crossing vs Best Position (GY)
    2. Two Sample T-test of IntPrestige vs Value (Ivan)
    3. Kruskal-Wallis Test of Overall vs Skill Moves (Ivan)
    4. Two Sample T-test of Preferred Foot vs Shot Power (Ivan)
  4. Correlation and OLS Regression (Max)

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MH3511 Data Analysis with Computer project.

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