The Background
If you are reading this, hopefully you’ve already read and perhaps downloaded and used the Player Comparison Visualiser tool! If not, please have a look!
In the Player Comparison Visualiser, you can export the results of a Player Search in Football Manager 2022, import them into the Excel, and then use two drop-down menus (left and right) on the interface, to visually compare the performance metrics of any two players in the results.
The tool was a result of some number-crunching I’d been doing with Excel for a previous post and wonderful blogger A FM Old Timer getting in touch with me to collaborate on building something special.
Together we created the Visualiser tool and I wrote about it here.
The next step for us was to write about the possible applications of the tool. When it could be useful and how it can help you better judge your players, or even those out there in the transfer market.
So A FM Old Timer took the keys to the blog and wrote a brilliantly insightful post about his experiences managing Southampton in FM22, and how he puts the Player Comparison Visualiser to good use.
Without further ado, here he is!
Thanks
FM Stag
The Visualiser in Action – by A FM Old Timer
One of the clear uses for this Player Comparison Visualiser is being able to compare your players relative to that of others across leagues (that you have fully loaded). Below, I’ll run through some of my own players in my Southampton FC save and look at how they’re performing across various metrics in relation to players who are natural at the same position. Sadly the Player Search screen doesn’t yet enable us to identify minutes played by position in FM22 – but here’s hoping for the future.
To make my analysis a little more confined along realistic bounds, I put a cap on central defenders and strikers of no more than 27 years of age simply because I would not be permitted to buy a player who was older than this, based upon my board’s expectations of player recruitment. For the record, I wouldn’t typically sign a midfielder above this age either, but some of my midfielders have already aged above this limit and I wanted to analyse their performance, so this has been capped at 30. I also put a lower limit of £20,000 p/w in wages to remove many multiples of players who would not be of likely the prerequisite standard to play for my side. All player searches were run using a filter that sets a minimum bound of 1,000 minutes played.
Central defenders
Pascal Struijk and Alex Morgan (a newgen) have been two of my starting central defenders this season, with Neuhén Pérez the other. Naturally, the eye is drawn towards the respective right-hand side of both boxes on the visualiser. The pink line indicates just how superior these players are when defending across the vast majority of the in-game and Stag’s defensive metrics.
When I showed the above graphic to Stag, what jumped out to him straight away was Struijk’s poor tackle completions, 68%, putting him in the bottom 4% of all natural central defenders. Had I noticed this in game? No. Is it a concern? Very possibly – but then his tackle numbers are also very, very low – the lowest amongst his peers. Given our average possession across the Premier League season was 53%, using possession adjusted stats wouldn’t make much difference to the overall number of tackles. This is certainly something to consider, whether this needs to be addressed in the transfer market or not.
The above graphic also highlights the importance of attacking set pieces and carefully selecting the placement of tall players to attack the ball. Both Morgan and Struijk are league-leading in their goal metrics – Morgan is scoring a goal every five games – no mean feat for a centre back.
Their passing statistics are at first glance also encouraging as ball playing defenders but mixed in deeper study. 98% pass completion is excellent, putting both comfortably inside the top decile group. Morgan is also league-leading in clearances – Stag’s thinking was that given ball playing defenders have ‘take more risks’ hard coded for passing, this might result in more long passes, which are then clocked as a clearance. It does show just how much we are turning over the ball from the back though, which might help to explain why we’re only averaging 53% possession, along with trying to engage in quick counter-attacks.
What I would like to see (at the risk of this becoming a wish list) is to have the possession metric for the time that the player has been on the field of play, to get a far better idea if it varies depending upon which centre back plays (or indeed any other player playing on other positions).
Strikers
Above, I identified through the use of this visualisation tool that Struijk’s tackling metrics might be a cause for concern and one that might require addressing in the transfer market. When looking at my striker options, I’m going to take a different approach.
Here, my intention is to assess which of my three strikers are best suited to the roles I use in my 4312 system I’ve written about previously on my website.
Lorenzo Lucca, Sebastiano Esposito and Martín Satriano are the main players entrusted to fulfil the Advanced Forward and Deep-Lying Forward roles. All players have played both duties, with Satriano the most flexible of the three, switching across the two roles regularly.
What I want to know is which player is most effective in the specific roles that I wish them to play. This might help extract marginal gains, especially within knockout football, where single moments can make big differences, which any good striker should be able to achieve.
Straight off the bat, you can see what a phenomenal year Sebastiano Esposito has had – he’s a creator and goal scorer all in one – a clear Deep-Lying Forward who is able to link up play. This is the role he’s predominantly played in, so it’s good to know that this looks on the face of it to have been the right call for him. His creativity is at the highest level in terms of key passes, chances created and assists per 90. Little surprise then that he is in the 99th percentile for Stag’s Creative Efficiency metric.
Under the eye test, Martín Satriano has had a very good year, deputising for both Lucca and Esposito as part of heavy rotation and stepping in on a more semi-permanent basis when Lucca sustained injuries (neither particularly serious – pulled calf muscle followed by a twisted knee). This might make sense as to why his creative numbers by key passes and chances created per 90 are a little down on Esposito’s as a result of the fact that he’s played in the Advanced Forward position more often than not. This could also explain why he’s been pretty lethal in the number of shots and goals per 90 as well as his non-penalty xG/90. He is clearly a worthy deputy for either Esposito or Lucca.
I’m analysing Lucca last in this section, in part because of his injuries which has hampered his form a little, and in part because of a player trait that he has – plays with his back to the goal. This should naturally lend itself to a large and strong forward that is good at linking up the play. Yet, when he slots into my preferred formation, I play him as an Advanced Forward. Am I missing a trick in having him in this role? Should I be switching around Esposito and Lucca? Clearly, looking at Esposito’s creativity metrics, you’d think it would be crazy to change things up, but things are always worth a second look.
Sure enough, Lucca shines just as brightly in chance creation – in fact, by chance creation and assists per 90, he’s the best talent out there that there is – as the song goes, nobody does it better. Perhaps a switch in positional role might be in order? Yet with Real Madrid, Barcelona and Manchester United all interested, why’d you have to be so good?
Central midfielders
With my analysis of central midfielders, I want to demonstrate the importance of having varied roles across a system. As I stated in the 4312 tactical write-up on my site, I prefer a runner, a passer and a defensively minded player as a combination. I somewhat combine the defensively minded and passing player with the role of a deep-lying playmaker on defend, but I have also opted for a Carrilero to support the right-hand side of the pitch, where Livramento or Walker-Peters bomb on to join the attack. I then have a Mezzala on attack on the left of the three as a runner into the half-space.
Monchu is my nominal creator-in-chief within the midfield – he’s the preferred deep-lying playmaker whose job it is to shield the back four and also be available to his teammates to receive and give a pass – think Rodri for Manchester City. As you can see, he makes a number of key passes, which have also led to many chances created and assists per 90. The trouble with this data is that he’s also one of my set piece takers. He takes direct and indirect free kicks, corners from the right-hand-side. Given our height in the centre-back position and with Lucca’s height, and Esposito and Satriano both pushing 6’2”, we have scored twenty-three goals so far over the last forty matches from corners and free-kicks combined – some 20.18% of all goals. As such, his metrics are hard to rely on to prove that he is a main creator in this side.
The same is also true of Ivan Ilić – he’s my go-to in the left-sided Mezzala slot, and this season he’s performing magnificently well in the role, scoring a season’s best 0.43 goals per 90, marginally outperforming his npxG by 0.09. Ignoring his terrifying comparative pass completion percentage, you’d think he was a creative genius. Yet he isn’t, at least not necessarily in open play – he takes the set-pieces from the left-hand side, thus throwing his metrics into the air too. Lies, damn lies, Boris Johnson lies…and statistics. So I’d love to show you what a great player Ilić is through his attacking contributions in open play, but I can’t. On the plus side, our approach to set-pieces is at least proving effective.
Instead, let’s take a look at Tomasso Pobega and Willot Swedberg. These players typically play in the Carrilero role, though Swedberg has had to deputise in the Mezzala role on occasion. From the outset, you can see that they’re very different players. Swedberg is far more aggressive in the attacking aspect of the game, creating lots of chances from open play, and even keen to finish moves too. Pobega, on the other hand, is far more reserved and isn’t even as good defensively, if we focus purely on his tackling metrics. The only thing going for Pobega is that he’s better at reading play, with his higher rate of interceptions per 90. This is perhaps no surprise given that he has four years of experience over Swedberg, and comes with a higher attribute for Aggression (though Swedberg’s attribute for Anticipation is actually higher).
The path not travelled
Ever wonder what may have happened in a save with a player you decided not to sign? Here I take a look at how the player comparison tool could be used to assess player performance on a player you’ve kept an eye on but for whatever reason didn’t pull the trigger on bringing him in.
Nico (left) had performed brilliantly for Leeds in the Championship, creating a league leading level of assists, chances and key passes. I had a need to have a backup plan for Nicolás Domínguez, who was attracting interest in his services. Domínguez was my rotational deep-lying midfielder, but was versatile enough to play across all three central midfield roles. I like to be prepared, when given enough warning, so that I am ready to acquire players if I’m ever in the position where I’ve just sold someone. This will either mean bringing a player back from a loan, promoting someone from the reserves/youth team (although this is rare), or bringing in a new player.
As it happens the interest in Domínguez never materialised until the January transfer window, by which time Nico had already signed a new deal with Leeds, perhaps to reward him for his creativity, but just as likely to remove the relegation release clause that made potentially signing him quite attractive. Regardless, he was no longer interested in a transfer. Leeds had attained promotion back to the Premier League. This did allow me to gain a better understanding as to how he, and indirectly Leeds, were fairing after making the step up, and whether or not I should maintain my interest in the Spaniard.
So how has he done? Not well is the answer – his assists have dropped off a cliff, so whilst he’s passing the ball around to his teammates well, his ability to create chances at this level has been found wanting. You can see too, to an extent, just how much extra defensive work he’s having to do in the Leeds midfield. He most likely enjoyed being part of a big team in the Championship, but has struggled as Leeds have in the Premier League – a potentially expensive mistake dodged. Instead, I signed Nicolò Rovella from Borussia Dortmund, who has an active contract clause for teams in the Champions League. I won’t show his metrics, as he’s not yet played the 1,000 minutes for us to qualify to come up in the player search.
All things considered, the Player Comparison Visualiser helped me draw these conclusions and subsequently make my decisions.
Thanks.
A FM Old Timer
Closing Comments
So there you have it! Thanks so much to A FM Old Timer for all his work. Not only on the Visualiser coding to begin with, but for writing this wonderful guest article on a number of the practical applications of the tool with a real save example.
If you don’t already follow A FM Old Timer and read his other excellent work, please do so here on Twitter.
Have you downloaded the Player Comparison Visualiser yet? In what ways have you found it useful?
Thanks for reading.
FM Stag