2025-11-02

DAT301 Midterm: FC26 Players Data

by Owen Chugg

The Data

The Data set is the FC26 data from the game FC26 recieved from kaggle

The data set was created by finding the statstics of soccer players from the game

The data consists of the players name, height, weight, league, position, and overall value out of 100

Brief Overview

We will explore player data through a series of visualizations to better understand trends and relationships within the dataset.

  • 3D Graph — Displays the relationship between the top 5 player leagues, ratings, and positions.
  • Overlapping Histogram — Compares distributions of player height and weight.
  • Heat Map — Highlights the top and bottom 5 player values relative to age.
  • Pie Chart — Shows the top 10 nations represented by players.

Player League, Rating, and Position

Using Plotly, I crated a 3D graph showing the top 5 ranked positions for the top 5 leagues in the dataset. The graph shows the average player rating along with the positions and league associated with the rating

Player Height vs Player Weight

In this graph I used ggplot and found the the standard distribution of the weight and height of the players to creating an overlapping bar graph of the standardized values to find the number of players that coincide with the weight and height of the standard scores.

Calculating the z-scores code

In order to calculate the z-scores I used the formula to the standardized values. For example, when I was finding height i found the z-score by subtracting the height from the mean and then dividing by the standard deviation.

height_z = (height_cm - mean(height_cm, na.rm = TRUE)) / sd(height_cm, na.rm = TRUE) weight_z = (weight_kg - mean(weight_kg, na.rm = TRUE)) / sd(weight_kg, na.rm = TRUE)

value vs age

I used plotly to create a heat map of the top and bottom 5 wages by age in the game. The wages are calculated off of the real wages of soccer players in real life so it is interesting to see how much players are valued in major sports like soccer.

Players by Nation

In this graph, I wanted to see the percentageof which players come from which nation. It is interesting that most of the players come from Europe and South America but that makes sense since soccer is a big part of their culture.