This article is about a piece of code about checking which FIFA footballers you should invest in FIFA 2016. Even if you’re more into doing sports outside than spending time while playing sport video games, it might be worth checking.

It’s more than evident that having a stronger team gives you by default dominance on a pitch. But how to do that having limited funds in a video game? The answer might be shocking, but let’s predict who’s going to be worth more in upcoming seasons…

Why?

What is the reason? It’s simple! For money… and satisfaction, obviously 🙂

But let me describe in few words what exactly we want to achieve. The purpose is to sign contracts with rising football stars and give the ability to other FCs to buy our players (buy low, sell high). Another option is just to let him play with us and gain experience scoring goals (buy low, profit). Simple economics, right?

I have to admit this software was developed with my friend Tom as a project done some time ago. There was one constraint – use Entity Framework, read more about it in further reading.

How?

Data is king!

At a time when the solution was developed, I didn’t make a note from which exactly URL data was taken (for sure, it was kaggle.com – data scientists know this site). I regret it to this day. The most probably it was this URL: the set of FIFA complete player dataset – the content seems to be the same, but while the project was built, the list of players and players attributes were separated (let me know if you know the source).

The obtained dataset of footballers and the assumption of using Entity Framework have to be combined. Entity Framework works as a mapper between Database data and Objects. For project purposes, data was loaded into SQL Server 2017 (of course, there were shorter ways of dealing with those data 🙂 ). At this stage, we have two tables in the database: “Player” and “Player_attributes”. Screenshot:

The missing part is an algorithm and GUI (the simplest GUI is more than enough).

Algorithm

The question that is bothering you may be:
“What parameters should be considered in order to estimate player’s possibilities?”.
Well, chosen were: position, preferred foot and highest attribute (the best skill on a field: eg. attack, defense, crossing, heading accuracy, short passing, volleys, dribbling, etc.). It’s not very complex but gives an idea of overall abilities when comparing to average representant having identified skills.

In a nutshell, the idea behind this project is:
– Select a player name from the available list (loaded in GUI),
– Application will confirm the finding by showing a message with player’s name and assigned ID,
– Found ID will be used to concatenate players attributes from the other database table,
– Tab “Player’s data” contains selected player’s FIFA classification per season,
– Tab “Estimation” contains estimation of profile representative (based on held position, preferred foot, max attribute)

Results&Conclusions

Let’s check Lewandowski, Messi and Ronaldo if they’re worth buying while playing FIFA 2016.

Lewandowski:

Messi:

Ronaldo:

All of checked players have at the time of checking higher ratings than compared with. It shouldn’t shock you, as when FIFA 16 was the current one, all of the mentioned footballers were top stars! There is no point in comparing the best players to average in specialized positions.

To prove this method is worth consideration, let’s check Kylian Mbappe. In 2016 he was entering top leagues and world’s football at the age of 17.

Mbappe:

As you can see on the summary in the right-bottom corner, in FIFA 16 this player achieves a rating of an average player on specified position, just while entering real football. It seems that comparable scores have more experienced players, so taking a bit of risk, this contract may earn some money! Feel free to test.

At last, the point was to find whether it’s worth investing in a particular footballer!

Application

Download: https://scouting-footballers-est.sourceforge.io

A few technical details regarding “Scouting footballers estimation”:

Authors	Tom Spencer & Marek Pierścieniak (coolautomations.com)
Language	C# (.NET Framework 4.7.2)
Integrated Development Enviornment	Visual Studio Community 2019 (16.7.7)
Libraries	Entity Framework 6 (EF6) v 6.0.0 by Microsoft (nuget)
Requirements to run	.NET Framework installed