Introduction

In this document I analyze player statistics from FIFA 19.

Required Packages

The following packages are necesary to view the FIFA 19 information.

Package Explanation
tidyverse For all things tidy
readr To reading the csv file
DT To display some data using Data tables
knitr For introducing R and HTML together
rmdformats For ready-to-use R Markdown

My Data - Part 1:

The file contains 89 attributes for each player, including ratings for specific soccer skills such as: Passing and Goal Kick Accuracy.

Filtering FIFA19 Data

We can use the following data table to compare stats for players over the age of 30:

Ratings by Nation

The following table shows the average overall rating for players, by country, arranged by the country with the most number of players.

Net Value of a Player

A player’s Value is the maximum worth of a contract that can be offered to that player (in the game). A player’s Wage is the current amount of their contract. A player’s NetValue is the number of times above Wage that a player is worth. This figure is a multiple and is similar to MLB’s WAR (wins above replacement) which measures a pitcher’s value to a team. This multiple can be used in a smiliar fashion. To see the first meaningful values you’ll want to go to page 2 of the data below.

Goal Kicking Stats

The best opportunity to score a goal comes from a goal kick opportunity. Players are rated on 5 categories of goal kick performance: Diving, Handling, Kicking, Positioning, and Reflexes. An average of these categories comprises Goal Kick Score (GK_Score). The data has been arranged in descending order by GK Score.

Skill Average

My Data - Part 2:

Overall Rating vs. Shot Power

Shot Power is the force with which a player is able to kick a ball. I am interested to know whether a higher Shot Power means a player receives a higher Overall Rating. Based on the chart below, not necessarily. However, once a player reaches Shot Power higher than 50, the Overall Rating begins to increase.

Facetted Data

In the following graphic, players are broken down by position. The positions that begin with ‘L’ stand for left side of the field, ‘R’ for right side, and ‘C’ for center fielders. The second and third letters refer to Forwards, Midfielders, Backs, and Wingers. There are also ‘Defenders’, noted with a ‘D’, and ‘Strikers’ are labeled ‘ST’.

This graph shows that center fielders on either sides of the field are the most accurate in terms of free kicks. GK, or goal kicker, has the lowest free kick accuracy of all the positions (hence why they play in goal).

Ratings

The following graphic represents players from the top 8 soccer nations and their assigned Overall rating by FIFA 19. England, France, and Germany have the most number of players with upside potential, that is, players with higher Potential ratings than Overall ratings. By contrast, Argentina, Brazil, and Spain have players with Overall ratings that are closer in range to their Potential rating. This implies that these players are more accurately rated with regard to expectations.

Penalties Hurt your Team

This graphic shows the number of penalties, by nation, by each player in terms of their overall rating. England was less likely to have highly-rated players commit a penalty than the other nations. Italian players demonstrated the widest spread of rated players to commit a penalty, while Germany, France, and Spain were the nations with highly-rated players most likely to commit a penalty.

Speed Kills

Speed is a critical element in soccer, especially for Forwards. This chart shows the nations with the fastest players.