Using statistics and data analysis to find the best attackers in the U-24 age pool in Europe's Top 5 Leagues.

In this data analysis thread, with data from @fbref / @StatsBomb, I'll be conducting statistical analyses to find the best attackers in this age pool.

Before we go, some starters on some of the terms I'll be using and how to interpret them.

This is the bell curve and it is a way of representing datasets. The center of this curve is the mean of the dataset and other data points are *standard deviations* away.

A standard deviation is a measure of spread - a way of representing to measure how far you are from the mean.

What's important here is that those standard deviations can tell how much the data is contained. As shown here, when you are +1/-1 SD away - that covers 68% of data.

The reason I'm telling all of this is you that what I'll be doing is converting data points of various metrics to this distribution. What you will see is something called z-scores.

Z-Scores between 0-1.00 = you are part of the average 34% of the data.

Z-Scores between 1.00-2.00 = you are in the 14% of the dataset.

Z-scores between 2.00-3.00 = you are in the 2% of the dataset.

See - it's simple! Use this chart for constant reference.

Now onto the matter of analyzing. When we have numbers floating around, sure we can rank them from largest to smallest based on their value.

However, to really figure out where those numbers are in the context of all attackers in Europe's Top 5 - we need something else.

This is where standardization comes in. I won't be going into details but it will convert our raw numbers into a scale between -3.00 to 3.00 and will do so considering the mean and standard deviation of our dataset.

In other terms, it provides us with numbers that now account for what the average U-24 attacker is and the various attackers out there.

But we want to go one step further - who is actually world-class/generational/the next big thing?

Here are standardized xA/90.

Any player with a number above 2.00 is basically in the top 2% among all these U-24 attackers making them the "next big thing".

Nkunku, Gnabry, Traore, and Sancho all justify their hype rightly. They are *statistically* the best in xA/90.

Here's passes to the final third per 90.

Again scores of 2.00+ = top 2% while scores of 3.00+ = top 0.5%.

Lopez, Lo Celso, Buendia, and Brandt all show themselves to be the top 1% among U-24 attackers in passing to final 3rd.

In passes to the penalty area, Sancho undoubtedly cements his status as generational. He's in the top 1% of attackers and that's something. Other important names include, Grealish, Guedes, Buendia, and Ounas.

In crossing play, Leon Bailey comes out as the best U-24 crossed but Ounas and Traore also show themselves the best in this metric.

Buendia and Havertz are world-press resistant players as they are in the top 1% and the gap is quite big. Yacine Adli makes his appearance along with Nadiem Amiri.

Finally, in passes that switch play - Torres marks his claim as the best player to do so. We also see long lost Renato Sanches at the top so maybe there's a player in there somewhere.

It looks like Buendia, Sancho, Nkunku, Gnabry, and Brandt can be statistically termed as the truly world-class U24 attackers.

However, don't always look at the outliers - that's where everyone looks. Scores between 1.5 and 2.0 mean that the attacker is in the top 5/6%

and you may find good talent for a cheap price or someone who isn't hyped up yet.

Regardless, I hope you liked this analysis on truly finding players that were world-class in their age pool through statistics.

Any likes/RTs/comments are appreciated - as always, stay strong and stay safe.

Dhanyavad.