FIFA 2018 Player Data Set

This plot compares Player Ratings against there respective age groups. Paired in groups of 5 years.

Plot 1 Player Rating Vs Age Group

As you can see players have peak performance from the ages 25-35.This would be when both skills and experience are maximized.

After that you can see a plateau or slight decline which can imply that there physical skills may drop or stay the same but there experience is most likely what keeps them going from that age on.

This bring us to our next plot that shows use the age of a player and there possible potential. A new variable was created for this one and it is called growth gap. This take the players current overall and subtracts it by the potential variable.

This plot can be very crucial to determine what the potential of future players may have based on there age.

Plot 2 - Age Vs Potential

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As shows in the plot your highest potential age from this data would be around 16-20. With a major drop coming right after that. This is reasonable and why lots of soccer teams recruit people at a very young age hoping to have picked the right apple out of the bunch that may have huge upside potential.

For our next plot this is going to show us correlation between a player overall and what factors the most into that decision.

Plot 3 - Player skill correlated to Overall

Potential looks to have the highest correlation with overall.While dribbling come next. Which makes complete sense. Since potential is noticeable if you are familiar with sports. Seeing life in a player is very important to determine the type of player they will be. By having dribbling as the next highest this goes hand in hand.

Now that we have talked about players overall skills and potentials let move onto they pay they might be receiving or not receiving.

This plot will show the distribution of player wages against there preferred position.

Plot 4 - Wages Vs Preferred Position

The distribution of wages across preferred positions reveals clear structural differences in market valuation. Attacking roles such as strikers or wingers tend to have higher median wages compared to defensive players. But this isn’t true for everyone. There is extreme outlines in almost every position. This can happen since there is elite players that play that position that are deserved to high wages.

That segways us to my last and final plot that shows the wage Inequality by position.

Plot 5 - Wage Inequality by Position

The coefficient of variation analysis confirms that wage inequality varies meaningfully across positions. The biggest red flag here would be that right wingers are among the highest paid player along side some of the lowest paid. players. Which would align with my previous plot showing how attacking position players seem to have the highest median wage.