Developing New Metrics: Blocking Crosses

One of the perennial problems using data to analyse football is the discrepancy that exists between those with the ability to manipulate data and those who understand what is taking place on a football pitch. Where data scientists will be able to build models or scrutinise the numbers, they may not know how to structure their models or implement their findings on the training ground. Equally, where football coaches will be able to break down the game into phases of play or recognise rehearsed patterns, they may not have the ability to make the data coherent in a way that helps them in their jobs.

At Analytics FC, we have attempted to overcome this problem by building a model which begins to interpret the raw data. Using our unique TransferLab algorithm—a Markov Chain model—we are able to take events that happen on the football pitch and ascribe them a numerical value which indicates how much an action improved that possession’s probability of ending in a goal (and just as importantly, how much it reduced the other team’s chance of scoring on the next possession).

For example, a player receives the ball in central midfield. At this point, the team might have a 1.5% chance of scoring at this point in the possession and also a 1% chance of conceding on the next possession. That situation isn’t very valuable. But if the player executes a dangerous through-ball into the final third, the team is now in a much better position and might have a 6% chance of scoring and only a 0.5% chance of conceding. The pass would be worth the difference in their team’s situation before and after it. 

The algorithm calculates every action and can therefore determine the overall impact a player has through all their actions and the impact is presented to clubs in terms of “Goal Difference Added” per 90.

The beauty of this approach is that it allows you to farm the data to find the sorts of actions that are creating value for teams and model your game-style to reflect that. If a certain pass into the box is proving a good source of value for a team, then the coach might want to think about ways to encourage those sorts of actions within the game. Suddenly, data and coaching are much more closely aligned.

In this series, we are going to explore some of these actions that add value to a team’s game:

Blocking Crosses

Keen watchers of Match of the Day will have heard one particular criticism levelled at full backs on countless occasions over the years: ‘He has to get out and stop the cross.’ 

The goal scorer might have been unmarked in the box. No matter. Seemingly no full back is ever exempt from this criticism. If they could have stopped the ball before it reached the target—so the logic seems to go—then any other defensive issues become moot.

Of course, it doesn’t really make other defensive players exempt from criticism but it is the job of a full back to defend the wide areas. Stopping the ball coming into the box is perhaps one of the most important parts of that job. 

Clubs take this aspect of the game very seriously. This article details how the England national teams aim to defend crosses with key parts of the defensive strategy being to funnel the ball wide and then have the players closest press intently to keep it out there and stop any crosses coming in. To do this, you need players who have the acceleration to get out quickly to the danger and the 1v1 defending nous to not be beaten too easily, allowing their opponent to cross without pressure. 

In modern football, it has become more and more important for full backs of elite teams to have the attributes to be able to acts almost as wingers in the attacking phase. As a result, attacking full backs have continued to increase in value with Trent Alexander Arnold and Alphonso Davies both ranking in Transfermarkt’s top 25 highest value players.

However, even those full backs who are elite going forwards need to be able to contribute defensively and there are other teams who perhaps don’t value full backs as highly for their attacking contributions and are most concerned about what they can bring to their team defensively. It would be beneficial for recruitment teams of those clubs to be able to identify those players who can defend the wide areas first and foremost. 

Finding the Best Cross Blockers using TransferLab

Thanks to TransferLab’s algorithm, it is now possible to find players who add the most value to their team’s goal difference through their ability to block crosses. In TransferLab, we now have access to a new metric: ‘Blocked Crosses (quality)’. 

Sorting by this metric and filtering for players who have a minimum of 720 minutes in TransferLab’s top three tiers of competition, here are the top performers for the 20/21 season: 

Aston Villa’s Matty Cash is the highest rated performer. Those who knew him in the early stages of his career might be surprised by this given that he originally broke through at Nottingham Forest as a winger.

Since being shifted to right back, though, he has flourished with Aston Villa paying a reported £14m for his services. He has been one of the best all-round full backs in the Premier League this season and would surely have made an England squad by now if it weren’t for the fact that his country have an embarrassment of riches in that position. 

TransferLab ranks him in the 85th percentile for Premier League full backs when it comes to 1v1 defending, which is something I’ve already noted as being important in blocking crosses. On top of this, he possesses excellent pace as well. This helps him with getting out to a winger if he is tucked in defending but also if he is beaten by a dribble he is often able to catch up and make a recovery challenge. 

Note that in this example against Phil Foden—an elite dribbler—Cash got himself as close to his opponent as he could but positioned his body well enough that he could react as Foden shifted the ball out of his feet. The Villa full back’s use of tiny steps meant that he was never over committed and was able to deflect the cross behind. 

It’s also worth mentioning Benjamin Mendy, who also performs well on this metric, perhaps surprisingly. When he’s been fit, he’s been a huge threat going forwards but it’s safe to say that his defensive work can leave a lot to be desired with opponents often targeting the space left behind him when he goes forwards. 

In this example, we can perhaps see why performs well. His 1v1 defensive technique is not as refined as Cash’s as he doesn’t manage to get as tight to Zambo Anguissa and jockey him as the Villa man did with Foden. As such, his opponent burst away from him to the byline but he is able to demonstrate the athletic side of his defending, managing to catch up and deflect the cross which Aymeric Laporte then cleared away. 

Of course, good defensive technique is preferable but Mendy demonstrates that being a supreme athlete can cover a multitude of sins in certain situations. 

The Best Under 23 Players

As I have done throughout this series, I wanted to highlight the best under 23 players according to the blocked crosses metric as we know that many of the smartest recruitment teams prefer to try to sign players at that age so that they come into their prime whilst under contract. 

Using the same filters as above, but adding the age filter, here are the top performers: 

Obviously Matty Cash is top, as he was in the non-age filtered list.

It’s not surprising at all to see Manchester United’s Aaron Wan-Bissaka make this list, given that he’s known as one of the top 1v1 defenders in the Premier League. In fact, the criticism of him has often been that his attacking qualities aren’t at the elite level needed to be a full back for Manchester United, regardless of how good he is as a defender.  

Reece James of Chelsea is another to make this list. His ability going forwards—particularly in his outstanding crossing—is a lot better than both Wan-Bissaka and Cash. This has meant that he’s been given recognition at international level where the other two have not made the grade thus far. However, as TransferLab shows, he’s another genuine all-rounder at full back, contributing lots defensively as well as in attack: 

Comparing James’ profile to Cash’s, we can see that James is a top performer in almost every single metric with headers in open play being his only weak point (and even that being above average). He also has far more activity high up the pitch than Cash but that should be expected given the differences in team quality.

With this new TransferLab custom metric though, we’re able to see that he’s a standout player in a particular area of defending which is vital to the role of full back and which traditional metrics would perhaps have missed. 

Another player worth highlighting on this list is the youngest. 18-year-old Aaron Hickey moved to Bologna before the start of this season and has featured for 721 minutes in Serie A this season. 

His TransferLab profile in an all round fullback template compared to all full backs in Serie A shows that he still has plenty of development ahead of him. But given his age, he shows plenty of promise and this metric has highlighted an area that he excels in already. 

Similarly to the example of Matty Cash, observe how he positions his body in this clip, ready to react to any quick change of direction form his opponent, attempting to keep them out wide rather than driving to the centre. As he was able to get so close, the block was easily made when it was necessary. 

Scotland already have two top quality left backs in Andy Robertson and Kieran Tierney but they will be extremely hopeful that Hickey will be the next in line. 

More Filtering Options

As well as filtering for age, I have applied position specific filters, given that a recruitment team are likely to be looking specifically for a right back or left back, rather than just a miscellaneous full back. 

Here are the top performers with the same filters as the original search which TransferLab has listed as primarily playing as a right back:

Here are the left backs:

Again, it would be possible to also add the age filter, further filter minutes or go to specific leagues rather than the tiers I have been using to ensure a wide search for talent.

Perhaps this metric would be a good one to use with a filter for centre backs only in order to identify those who could defend the wide areas best in a back three formation, knowing that wingbacks will be caught high up the pitch on occasions. This custom metric is certainly able to identify players who have excelled in this area in the past better than the traditional defensive metrics have been able to.  

Developing New Metrics

In this series, we will be covering a number of novel metrics we have developed using TransferLab’s algorithm. However, we can create any number of new metrics to determine whether certain in-game actions accrue or reduce goal difference in games.

Using the algorithm, we can assign a “Goal Difference Added” per 90 value to any on-field action that moves the ball from one part of the pitch to another and then compare players using these values.

If you have any ideas about potential metrics, do get in touch with us and we’ll see what we can do to implement them.

Analytics FC provides software and data services to entities within football looking to realise the gains possible from analytical thinking. We provide cutting-edge software solutions such as TransferLab, which helps improve and simplify recruitment decisions. To find out more about TransferLab and our other data services, or to find out more about us, visit our website.

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