Golden oldies with something to offer – data analysis

In the current economic climate, clubs are struggling on multiple fronts. Empty stadiums mean no tickets sales, resulting in cash-flow being at an all-time low. No longer can clubs look to the summer window armed with a treasure chest promised by the board  frugality has moved to the fore.  

For some clubs, the struggle of keeping afloat is compounded by the fear of relegation. Now the Premier League has committed to being completed, teams are desperately testing players to gain an understanding of who will be ready to lead the relegation survival charge. No money, empty stadiums, and incomplete line-ups will inevitably lead to one thing: cost-cutting. 

This data analysis isolates data fit to a specification which will readily assist teams in finding good players at low costs.

The Conditions

The data in this analysis has been cleansed to show the following:

1. Attacking players 
2. Over the age of 30
3. Playing in the best 10 leagues outside of Europe’s big-five. 
4. Have played +800 minutes of league football 
5. Have a market value of under £25,000,000

This criterion has been created in order to assist mid/low-level Premier League teams who will be certainly looking for a bargain to improve their squad next year. Despite there being low potential re-sell value, these players offer great initial value, which is perfect for the current situation. Even a club the size of Man United have proved with Odion Ighalo that there are aged players in less developed leagues that can still perform in the Premier League at little entry cost.

A holistic view

Using wyscout to scour the leagues, the following players were returned. The visual below is a Ternary triangle which measures the filtered players on three key metrics that accurately depict a player’s attacking ability. As you can see these are Expected Goals per 90 (xG90), Expected Assists per 90 (xA90), and Dribbling success. 

The markers of each player are measured on barycentric coordinates, which essentially means all metrics work in relationship with each other. This means that where a player is closer to one corner of the triangle  xG90 for example  they are not achieving a higher xG90 than players further away, instead, their playing-style is more focused/weighted around scoring goals.

Putting it succinctly, a player’s position in the triangle shows the balance of their playing style in comparison to the other metrics. The players in the centre of the triangle are not worse players, just more well-rounded in their game.

So let’s look at the results. As we can see some interesting names fill the triangle. Towards the xG end, players such as Rademel Falcao, aged 34, is still a goal-focused striker for Galatasary. The experienced Colombian achieves 0.76 xG90, showing little interest in creating for his teammates achieving an xA90 of just 0.06.

Jermain Defoe, now of Rangers, is another household name who fits the criteria. The ex-Tottenham man appears to be more balanced than some of his peers, achieving an xg90 of 0.66, an xA90 of 0.11, and making 4.42 dribbles per game.

A final observation of this graph looks at Yannick Bolasie, Sporting CP. True to form, the ex-Everton man still focuses his playing style around taking players on, attempting 5.86 dribbles per 90, and achieving an xG90 of 0.17 and an XA90 of 0.07. Valued at just £4,000,000 by Wyscout and still just 30 years old, there is potential for value with this player.

The more you look at the triangle the more interesting names you see appear. But to fully isolate the stand-out players we must drill into this data a little further, this has been done below. 

Dribbling

This section is for clubs who are looking to find a player who’s playing style is centred around 1 vs 1 duels and technical dribbling. These players are excellent in transition and also in the attacking phase when penetrating rigid defensive structures.