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Data has become an integral part of team and opposition analysis in the modern game. Creating a repeatable and automated process can quickly identify trends and insight, saving valuable time for the busy analyst. Teams and federations use StatsBomb IQ to support their team and opposition analysis, exploiting edges found in the platform to secure victory over their opponents every matchday. Let’s demonstrate how this can be done by looking into the England vs Denmark semi-final at Euro 2020.

England

First, let’s look at a selection of attacking and build-up metrics and compare England’s performances to the eight Euro 2020 quarter-finalists:

• xG (7^th of 8)
• xG/shot (1^st of 8)
• Shots (8^th of 8)
• Counter Attacking Shots (8^th of 8)
• High Press Shots (8^th of 8)
• Box Cross % (8^th of 8)
• Pace To Goal (7^th of 8)
• Directness (7^th of 8)

We know England have been a safety-first team in this tournament, rarely letting the handbrake off and often withholding a body or six from participating in the attacking phase, so it’s little surprise to see their attacking metrics compare poorly to their rivals. The big caveat is, of course, that they’ve been superb defensively, but we’ll come onto that later. The first thing to note is England’s shooting habits. You get the feeling that Gareth Southgate’s perfect match would be a 1-0 victory where the shot count matches the scoreline. The Three Lions have averaged just 7.6 shots per game so far in Euro 2020, the fewest of the eight quarter-finalists, but there’s been little-to-no wastage which reflects in their 0.13 xG per shot. They may not create much, but they tend to be quality chances when they do. 18/38 of their shots have come from within 12 yards of goal, with an impressive number of them coming in central areas right between the posts.

England’s build-up play has been under the microscope for most of the tournament. Those who haven’t enjoyed it may label it stagnant and sterile; others who see the bigger, risk-averse picture may describe it as comfortable. Their Pace To Goal – the speed of build-up in m/s for possessions that end in shots – of 1.95m/s was the second-slowest of the eight quarter-finalists, with England refusing to commit bodies in the attacking transition and instead looking to combination play in the advanced wide areas to plot their way to goal.

Their precise approach to build-up can be seen in their final third entries. England have passed into the attacking third 127 times in open play this tournament. Of those 127, 84 are what you would call short ground passes; the type of which England fans can probably clearly envisage should they close their eyes: the short, risk-averse pass to a nearby teammate on the wing with the opposition crowding out the centre of the pitch. You would classify few of these passes as penetrative, with England preferring to do their damage from within the final third.

StatsBomb data contains pass height information, with High passes defined as played above shoulder height and Low passes defined as above ankle height but below shoulder height. Of England’s High and Low passes into the final third – 43 of the total 127 – there’s still little direct penetration on show, with many receptions on the wing and very few going beyond the 18-yard line. We know England take a risk-averse approach in everything they do, emphasising completing the next action in the chain towards goal, rather than spontaneous, high-risk play.

Raheem Sterling (23) and Luke Shaw (18) have been the most common recipients of passes into the final third, a left-sided lop-sided trend that continues into their box entries. England have passed their way into the opposition box 37 times in Euro 2020, 20 of which have been into the left-hand channel. Just ten came from the right flank.

  Defensive Approach:

• xG Conceded (2^nd of 8)
• xG/shot Conceded (2^nd of 8)
• Shots Conceded (4^th of 8)
• Counter Attacking Shots Conceded (1^st of 8)
• High Press Shots Conceded (3^rd of 8)
• Clear Shots Conceded (1^st of 8)
• PPDA (6^th of 8)
• Defensive Distance (3^rd of 8)
• Aggression (3^rd of 8)
• Pressures In Opposing Half % (3^rd of 8)

Defensively, England have been exemplary, keeping five clean sheets in five games. They’ve defended their penalty box superbly, conceding just a couple of attempts from between the posts at close range and blocking a large percentage of shots faced.

England generally look to defend higher up the pitch and have been effective in preventing the ball from reaching their danger zone too often, bombing out most opposition possessions in the middle third.

Germany caused England the most issues, creating the only two clear-cut chances England have conceded at the tournament, through Timo Werner (the shot left of the six-yard box) and Thomas Müller (the high-value shot on the edge of the box). Both chances came from England mistakes and rapid, direct transitions through the middle – something Denmark will be aware of and look to exploit.

  Set Plays:

• Shots per Corner (3^rd of 8)
• Shots per Indirect FK (4^th of 8)
• Shots per Corner Conceded (4^th of 8)
• Shots per Indirect FK Conceded (3^rd of 8)

As in the 2018 World Cup, England’s set plays have been solid, scoring twice and conceding nothing from set-piece situations so far. Defensively they’ve been very stingy, winning first contacts on all but one of the corners played into the central zone.

Denmark:

• xG (3^rd of 8)
• xG/shot (5^th of 8)
• Shots (3^rd of 8)
• Counter Attacking Shots (2^nd of 8)
• High Press Shots (1^st of 8)
• Box Cross % (3^rd of 8)
• Pace To Goal (2^nd of 8)
• Directness (1^st of 8)

Denmark’s tournament got off to a tricky start, but they find themselves in the semi-finals and attracting plaudits for their approach, playing with energy and aggression both in and out of possession. They lost their opening two fixtures to Finland and Belgium, but the signs were always there that they could be a threat at Euro 2020: they won the shot count 42-7 across the two games and were unfortunate not to come away with at least one win.

As if they were wearing their boots on the wrong feet, but either way, they found their scoring touch before it was too late, scoring ten goals from their next 43 shots to sweep aside Russia, Wales, and the Czech Republic to reach the semi-finals. Contrary to England, Denmark have looked to attack quickly and directly. Their Pace To Goal of 2.8m/s and Directness rating of 0.90 – a ratio of the distance towards goal at the start of the possession, divided by the total distance travelled in the build-up - reflect the verticality with which Denmark play, as does the number of opportunities they create on the counter, with 2.4 counter-attacking shots per game.

There are two key players to Denmark’s possession: Pierre-Emile Højbjerg and Joakim Mæhle. Højbjerg has taken on the chief playmaker role in the centre of the Denmark midfield, receiving the ball from the centre backs and distributing it wide to the advanced wing backs or into one of the front three of De rød-hvide’s 3-4-3. Højbjerg leads the Danish team for ball progressions to the final third (45) and has also made the 2^nd-most passes within the final third (82).

Joakim Mæhle’s performances down the left have received huge credit, offering width to Denmark’s attacks. In our recent article on our Similar Player Search tool, he appeared in our search for lateral defenders with a similar output to Trent Alexander-Arnold, and his performances showed up well according to our possession value model, On-Ball Value.

EXTREME SAMPLE SIZE WARNING The #Euro2020 group stage On-Ball Value scores are in, and.... ... that's as much help as we're going to give you. You can come to your own conclusions. Just remember the sample size. Please. (Pictured: Top 10 & Bottom 10 by OBV per 90) pic.twitter.com/eGUU0VnuU1

— StatsBomb (@StatsBomb) June 24, 2021

He’s been a critical outlet for the Danes, with 29 final third receptions, second only to Martin Braithwaite in the Denmark squad.

Defensive Approach:

• xG Conceded (3^rd of 8)
• xG/shot Conceded (5^th of 8)
• Shots Conceded (3^rd of 8)
• Counter Attacking Shots Conceded (6^th of 8)
• High Press Shots Conceded (4^th of 8)
• Clear Shots Conceded (6^th of 8)
• PPDA (2^nd of 8)
• Defensive Distance (2^nd of 8)
• Aggression (7^th of 8)
• Pressures In Opposing Half % (4^th of 8)

Defensively, Denmark have proven difficult to break down. They’ve conceded five goals, but three of those were in their opening two defeats and since then they’ve outscored the opposition 10-1. Their 3-4-3 provides a lot of central cover: the wide forwards Damsgaard and Braitwaite tuck in to take up a narrow position out of possession to help Delaney and Højbjerg in the middle and as a result, Denmark are able to defend in a higher block with an emphasis on crowding the central channels.

Their higher defensive line coupled with their lower Aggression % (the percentage of opposition ball receipts that are pressured, tackled, or fouled within 2 seconds) of 18% highlights that they prefer to retain their shape. Denmark position themselves higher up the pitch and then funnel the opposition into areas where they know they can apply heavier pressure, squeezing their opponents against the touchline and forcing the play backwards or regaining possession through a turnover.

What To Expect
With Denmark lining up in a 3-4-3, it remains to be seen whether Gareth Southgate will mirror that shape, as he did to great effect versus Germany, or stick with the same XI and 4-3-3 that breezed past Ukraine in the quarters. Denmark also have food for thought having taken a front-foot approach to their matches so far - will they play a more conservative game in a high stakes match, in what could also be classed as an “away” fixture at Wembley?

That’s just an overview of the various insights that can be drawn out of StatsBomb IQ. Teams and federations continue to source match-winning insight out of our analytics platform and data to give them an edge on matchday. For a full demo of the platform, contact us today.

Data has become an integral part of team and opposition analysis in the modern game. Creating a repeatable and automated process can quickly identify trends and insight, saving valuable time for the busy analyst. Teams and federations use StatsBomb IQ to support their team and opposition analysis, exploiting edges found in the platform to secure victory over their opponents every matchday. Let’s demonstrate how this can be done by looking ahead to the Spain vs Switzerland quarter-final at Euro 2020.

SPAIN

Spain qualified from Group E in 2^nd place – failing to beat Sweden or Poland in their opening games of the tournament before a 5-0 thumping of Slovakia in the deciding match secured their advance to the knockouts. The 0-0 and 1-1 draws versus Sweden and Poland quickly reiterated the stylistic approach we’ve come to expect from La Roja; possession-based, territorially-dominant football. There were flaws in both performances, sure, but Spain did enough to suggest they’d win both games more often than not. They failed to score from chances worth 1.92 xG versus Sweden and netted a score draw against Poland despite ‘winning’ the shot count 12-5 and creating 2.25 xG to Poland’s 0.58. Slovakia were then on the receiving end of Spain’s frustrations in the 5-0 thrashing, before a chaotic first knockout round versus Croatia exposed defensive frailties identified by observers earlier on in the tournament. For all the control Spain had exerted over their opponents in the group stage, they struggled for it when it mattered most against Croatia. In the final ten minutes of the match, Croatia’s tenacity and determination saw them overturn the 3-1 lead Spain were holding onto, forcing two late goals to take the tie into extra time. La Roja’s strengths and weaknesses were on display in their first four games of the tournament. Here’s what we might expect to see versus Switzerland. Build-Up & Attacking Phase Spain have so far had the shortest average goalkeeper pass length at the tournament at just 26.3m, with Unai Simón showing a preference for distributing the ball to the right-hand side of the defence. Unsurprisingly, they’ve averaged the highest possession in the tournament, with 73% of the ball in their four fixtures. Their attempts to pass their way into the goal has seen them come out with the slowest Pace To Goal – the average speed of build-up, in m/s, for possessions that end in shots – of all the teams that qualified for the knockout stage. Their controlled build-up means they’ve entered the final third more often than any team at the tournament at 85.7 entries per 90. Seeing as they’re spending so much time there, let’s dig into what they’re doing with the ball in the attacking third. In open play, they’ve played 670 passes originating in the final third (not including the penalty area). They played 127 (20%) back out of the final third, so 80% of the passes stayed within that area of the pitch. What’s surprising is that 105 passes (15%) attempted to enter the box. On average, Spain play six passes in the final third before they attempt a pass into the box. Of these 105 attempts, only 41 succeeded. Of the tournament quarter-finalists, Denmark and Italy have more penalty box pass entries, and they manage it in fewer passes. Spain’s possession play results in a large amount of the territory, but it does mean they struggle to penetrate at times, with them almost always playing against a set defence. With the set defences in mind, it’s perhaps unsurprising to say that Spain’s most effective route into the box has been through crossing, but it’s certainly surprising given their overall approach. 36% of Spain’s successful penalty box entries have come from a cross, the highest percentage from teams that qualified from the group stage. It’s important to know what Switzerland might be facing in this regard. Examining the start locations of Spain’s crosses indicates a couple of trends. From the left, their crosses tend to originate from wider and deeper positions. From the right, they’ve been far more successful at penetrating the “cutback zone” – the byline inside the penalty area. Looking at key players now, Pedri has arguably been Spain’s best player in Euro 2020, one of only three Spanish players to play every minute at the Euros so far despite this being his first tournament at the age of 18. His positive approach to the game has seen him move the ball into the attacking third more than any of his teammates, second only to Toni Kroos across the entire tournament. He’s also played the most passes within the final third, showing an ability to find space and show for the ball in attacking areas, whilst also looking for the forward pass when on the ball in there. 29% of his final third passes have been played forwards. Of course, to focus on Pedri would be to ignore the many threats Spain have in possession, and it’s worth noting that it’s Jordi Alba who’s played the most passes into the penalty area of their squad. He could come back into the XI more fresh after starting on the bench versus Croatia. Defensive Approach Spain’s game is all about territory, which means as soon as they turn the ball over, they’re going to look to counterpress the new possession to force a turnover, prevent the counter, or keep the play away from their half. As if opposition possession is the matador, Spain’s Aggression % (the proportion of opponent pass receipts that are pressured, tackled, or fouled within 2 seconds) is the highest of the 16 knockout teams at 25%. Their Defensive Distance – the average distance from a team’s own goal from which it makes a defensive action – of 51.6m is also the highest in the knockout stages. Expect Spain to pin Switzerland back should the Swiss not find a path out of the press. Speaking of which, one of Spain’s major weaknesses – as it is for many high-pressing teams – is what happens when the opposition breaks their press. The best chances Spain have conceded in the tournament so far have come when their opponents have waited for their opportunity and then attacked at pace with the Spanish defence pulled out of position. It’s definitely a positive that Spain have conceded the joint-fewest Shots in the tournament, but a tournament-high xG/per shot conceded of 0.18 demonstrates that it is possible to create clear-cut opportunities against them. The average distance from goal of the shots conceded is 14.4m - a tournament-low compared to their quarter-final rivals.  

SWITZERLAND

Qualifying from their group as one of the best 3^rd-place finishers meant Switzerland had to beat World Cup holders and pre-tournament favourites France on penalties in the first knockout round to reach this stage. In truth, their group stage performances were better than the 3^rd-place qualifier tag would suggest. They were comfortably beaten by a good-looking Italy, but comfortably beat an ugly Turkey and outclassed an organised Wales. The latter held them to a draw when Switzerland looked the likely winners. Both performances suggested there was enough about this Switzerland side to cause issues for whomever they drew in the first knockout round, which France certainly found out to their cost. Build Up & Attacking Phase Switzerland tend to mix it up more than their opposition in this match when playing from the back. Their average goalkeeper pass length of 32m is lower than most of their quarter-final rivals, but Yann Sommer’s goal kicks map displays a flexible approach to their play out from the back. Twenty-five of his goal kicks have been Ground passes to a nearby teammate, whereas 18 have been played off the ground to achieve more distance, logged as a Low (above ankle but below shoulder height) or High Pass by StatsBomb’s pass height information. It's likely Switzerland will play longer from the back versus Spain to play over the press and force the game up the pitch. Switzerland look to move the ball through the thirds at a much higher tempo than their quarter-final opponents. Rossocrociati have the fastest Pace To Goal of the quarter-final teams, moving the ball towards goal at 2.8m/s on average in possessions that ended in a shot. Their matches have also been high pace in a different sense. Games involving Switzerland have seen the largest shot volumes in the tournament, amassing 31.5 shots per game on average with their opponents. Switzerland are a volume team rather than one that values a high-quality chance – their average Shot Distance of 17.3m is the 2^nd-furthest of the quarter-finalists, and their 0.08 xG/shot is the worst rate of that group. The wing-backs tend to be the best outlets for getting the ball into the final third: of Switzerland’s 116 passes into the attacking third in the tournament, 78 of them were received on the flanks. That’s not to say their play is entirely funnelled out to the wings: Xherdan Shaqiri and Breel Embolo are both impressive technicians in central areas. But, Kevin Mbabu and particularly Steven Zuber have impressed as attacking outlets in the wing-back roles – Zuber has four assists from open play already, leading the tournament for goals created. They'll have to do it without their most capable progressor of the ball. Granit Xhaka's suspension means Switzerland will be without the player who's been trusted to play the most passes in the squad, has completed the most long balls, and has played the ball into the final third more than anyone else in the Swiss team. The pass network versus France emphasises Xhaka as the most frequent and valuable passer in the team. Defensive Approach Switzerland have so far adapted their defensive approach for each opponent, though they do appear to show a preference for defending in the middle and defensive third. They pressed from the front against Italy, but the plan backfired and that, alongside other factors, may have put Vladimir Petković off trying a similar approach versus Spain. Against Turkey and then France, they were much happier to sit off the opposition initially and then press more aggressively in the middle third. What To Expect We’ve identified several trends we expect to persist on Saturday’s quarter-final, as well as potential weaknesses on both sides. Will Spain keep Switzerland penned into their half? Will Switzerland be able to transition effectively and create dangerous chances as other teams have? Will Spain have to resort to crosses to gain entry to the box again?  

That’s just an overview of the various insights that can be drawn out of StatsBomb IQ. Teams and federations continue to source match-winning insight out of our analytics platform and data to give them an edge on matchday. For a full demo of the platform, contact us today.

Data has become an integral part of team and opposition analysis in the modern game: a repeatable and automated part of the process that can quickly identify longer-term trends and save valuable time for the busy analyst. Teams and federations use StatsBomb IQ to support their team and opposition analysis, exploiting edges found in the platform to secure victory over their opponents every matchday. Looking ahead to England vs Germany in the Euro 2020 round of 16, let’s demonstrate how this can be done.

GERMANY

Germany come into this game having survived the Group of Death, qualifying after a late Leon Goretzka equaliser in the deciding group game versus Hungary saved them from an early exit. As a collective, there have been question marks over Germany's performances in the group stage, but matches against strong nations in France and Portugal should provide us some clues as to how they might setup against England. The first thing to note is that Germany conceded the first goal in all three of their group stage games - in fact, each of those goals was scored within the opening 20 minutes of the game. As a result, their data is skewed slightly favourably with Die Mannschaft playing a more attacking mentality to chase the games than they're likely to operate with from the start against England. Sure enough, Germany controlled the shot counts in all three games (10-4, 13-7, and 18-9 respectively) as well as the territory, completing 272 final third entries to their opponents 80.  

BUILD UP

Germany look to play short from the goalkeeper, with an average goalkeeper pass length of 29.9m the 4^th-shortest of the teams qualified from the group stage. Neuer has distributed evenly between the two sides of defence, playing 19 defensive third passes to Antonio Rudiger and 17 to Matthias Ginter, with the two wide centre backs charged with carrying the ball up the pitch before distributing to Mats Hummels at the centre of the back three, or Toni Kroos. Should the centre backs be unavailable for a short, ground pass, Neuer has found joy playing Low (not to be confused with Löw) or High passes to Robin Gosens on the left flank, but Neuer has so far struggled making these same passes to the right flank. Though influenced by the game state, particularly against Hungary where they were attacking a low block for long periods of the second half, their proclivity for moving the ball side-to-side in the build up shows up in their Directness rating – the total distance from goal at the start of a shot-ending possession, divided by the total distance travelled during the move. Their Directness ratio of 0.74 is a tournament-low for teams remaining in the knockout stages. We can expect Germany to control possession and look to create chances through longer periods of build-up play. Their 3-4-2-1 shape lends itself to attacking with width. Gosens and Joshua Kimmich from the wingback positions have so far been two of their more impressive performers at the tournament. Germany’s Successful Box Cross % - the percentage of successful passes into the box that are crosses – of 32% is the highest in the tournament, influenced by facing deeper blocks but also by the presence of quality wide players in Gosens and Kimmich, plus the likes of Gnabry and Sane pulling into the wider positions. Undoubtedly the key player in build up for Germany is midfielder Toni Kroos. The Real Madrid midfielder had the most touches in the team versus France and Portugal, and the third-most against Hungary. Kroos is central to Germany’s build up play, getting on the ball early in the build-up phase and looking to move the ball into the front three or out wide to the wingbacks who’ve advanced ahead of the ball in the wide areas. Kroos has not only completed the most passes in the German team, he’s also completed 57 long balls at the tournament (Neuer second with 27) and completed them at an 89% clip – his unerring accuracy a constant issue for the opposition block being shifted around by the range of Kroos' passing. The issue for England is that Kroos is also completely comfortable playing under pressure too. Just 9% of Kroos’ passes have been played under pressure so far, but he’s completed 93% of them. Not only is he able to retain the ball under pressure, he also rarely goes backwards, drawing the press and then bypassing it to keep Germany moving towards goal. In the final third, it’s Gosens (5) and Kimmich (4) who’ve laid on the most shots from open play for Germany so far, again highlighting the need for England to defend the wide areas well if they are to succeed.

DEFENDING & OUT OF POSSESSION

Germany have so far defended in a higher block. Their PPDA of 7.30 is the 2^nd-lowest of the knockout teams, and their Defensive Distance (average distance from a teams own goal from which it makes defensive actions) of 48.12m is 4^th highest of the same group. Their Aggression % (the proportion of opponent pass receipts that are pressured, tackled, or fouled within 2 seconds) of 23% is above the tournament average, and they made the 3^rd-most Counterpressures in the opposing half in the group stage, suggesting that England may well have to play out of the press in the early stages of build-up on Tuesday night.

SET PLAYS

Germany have been effective from set plays in the tournament so far, creating 11 set plays shots (joint-2^nd most). They’ve tended to go short when playing corners from the left, but from the right is where they’ve had the most danger, creating two shots (red squares) at the far post when the delivery has beaten the near post markers.    

ENGLAND

England made it out of Group D with some grinding performances, with their three matches containing a grand total of two goals for either team. Their strategy has been clear and so far effective: give absolutely nothing away and let that be the platform to carry them deeper into the tournament. The Three Lions’ enclosure has been placed firmly around their goal. The handbrake has been well and truly on, but it has returned three clean sheets in three games – so far, so good. It’s notable that in the two games they took the lead, versus Croatia and Czech Republic, England moreorless stopped attacking once they were ahead. Versus Croatia, they took the lead in the 57^th minute, creating just three shots afterwards and the last of which in the 74^th minute. And it was even more extreme vs Czech Republic, taking the lead in the 12^th minute and holding it for the remainder of the game – creating just two more shots in the 78 minutes afterwards and not a single one in the second half.

DEFENDING & OUT OF POSSESSION

Given their approach, it makes sense to examine their defensive approach first. Their defensive success is two-fold. The first is limiting the quality of shots against them. England conceded 26 shots in the group stage – a number bettered by six teams. But their xG per shot conceded of 6% was the lowest in the group stage, preventing the opposition from getting a clear sight of goal and resulting in just three shots on target total in the group stage fixtures. A big factor in this has been the positioning of the defensive unit. England had a defensive body in the way of every one of the 26 shots conceded in the group stage matches – not conceding a single chance where the shooter had a clear sight of just the goalkeeper between ball and goal. The amount of bodies defending the goal has also paid off in the territory they’ve conceded. England’s group stage opponents reached the final third on 96 occasions, but found it extremely difficult to penetrate the penalty area – England didn’t allow a single pass to be completed inside their penalty area during the group stage. This signals two things: one that England defended the space around their goal well, intercepting the passes that were played at close range, but also that forcing the opposition to deliver the ball from a further distance allows for more reaction time by defenders and goalkeeper. Germany will be facing an organised defensive unit on Tuesday evening.

BUILD UP

That risk aversion – defending leads and refusing to over-commit – has also led to England leaving little footprint as to their build up and attacking play. Their 23 shots was the lowest total of the 16 qualified teams in the group stages. Three High Press Shots created shows that England are ready and capable of pressing high when the situation allows, but no shots created on the counter-attack is another reflection of England’s reluctance to leave their shape and commit bodies forward. Instead, their chance creation has come from open play and from set plays. A look at England’s most dangerous sequences created so far – based on the expected goal value of the chance at the end of it – shows up some clear trends. The first is that they’ve tended to come from longer periods of build up. Excluding the corner in slide 4 – John Stones’ post-hitting header versus Scotland – all of England’s biggest chances have been created by phases of play that’ve lasted longer than 30 seconds, with three of them lasting over 60 seconds in duration. Much has been written about the pace of England’s build-up play, though the chances created versus Croatia (Sterling’s goal) and Czech Republic (Sterling’s shot against the post) hint at a capability to play quickly and incisively at the end of a sequence. Contrary to their opponents in this game, England have not opted to attempt many crosses so far, preferring to work the ball around the final third instead. England have attempted 12 crosses into the box (16^th of 16 group stage qualifiers) compared to Germany’s 40 (1^st). Despite this, England’s most common entry into the box has been down the left flank, with Raheem Sterling’s runs behind the defensive line proving a regular outlet for England’s attacking play. Another key topic has been the use of Harry Kane and his struggles in the tournament. Six shots and 0.92 xG has returned zero goals so far, and his isolation in the build up is evidenced in the data. Kane achieved just 27 Touches in the box in the group stage, a total that was 21^st highest at that stage of the tournament. For context, Scotland’s Lyndon Dykes managed 35 in the same time span. Outside the box England have struggled to get the Premier League’s top goalscorer involved too, receiving just 23 passes in the final third in three games, few of them in areas you feel he could do the most damage. Given the trends we’ve just identified, it promises to be a curious match up between the two sides. Will Germany’s proclivity for creating chances from wide persist against an England side well set up to defend their penalty box? Will England’s risk-averse approach in possession be able to withstand a Germany press, or will they be forced to look to create chances in transition to avoid being pinned into their own half under German pressure? Or is the match destined to go all the way to penalties as it did 25 years ago in Euro 96?

That’s just an overview of the various insights that can be drawn out of StatsBomb IQ. Teams and federations continue to draw match-winning insight out of our data and analytics platform to give them an edge on matchday. For a full demo of the platform and how it can help you, contact us today.

Right now, dozens of clubs around the world will be using StatsBomb IQ to aid their player recruitment planning and shortlisting ahead of the summer transfer window. IQ is designed by analysts, for analysts, with the goal of making data-driven insights easily accessible and digestible. Most importantly, it saves valuable time and resources for the time-poor analyst and is flexible and customisable to each user's specific needs.

StatsBomb Director of Football James Yorke provided the commentary for this walkthrough video of how IQ can be used for data scouting and shortlist creation. If you'd like to consume the walkthrough in written form and see further example profiles of players, read on.

Data can be used at all stages of the recruitment process, from the initial shortlisting all the way down to the final granular player assessments. Last week, we looked at how data can be used to create shortlists of forwards and centre backs that might be good stylistic fits for clubs looking for a particular profile of player. In this article, it's the turn of one of the more role-diverse positions on the pitch: full backs. Let's focus on a player who's become synonymous with the position in recent seasons, Trent Alexander-Arnold.

Alexander-Arnold's performances at full back for Liverpool have seen him become a key player in their recent domestic and European successes. We're all familiar with the ultra-attacking approach he takes to the position - asked to supply all the width on Liverpool's right flank and be a creative outlet both in build-up and in chance creation. Combined with Andy Robertson, Liverpool were one of the most frequent and dangerous crossing teams in the Premier League last season.

Having a player that can perform an attacking role to such a high standard is something clubs around the world will prioritise in today's modern game. So let's show you how StatsBomb IQ can be used to support this process in identifying and shortlisting players of this profile.

1) Create And Edit A Radar Template

The first thing to do when using IQ to identify players is to select the metrics that best reflect the role you're recruiting for. In this case, we're going to adjust the current full back radar to add key metrics that are closely associated with Alexander-Arnold's style of play.

We're looking to highlight the most synonymous parts of Alexander-Arnold's game - chance creation, competence in possession, width in attack, and ability to defend in a high line, so it makes sense to add:

• Average Defensive Action Distance: The average distance from the goal line that the player successfully makes a defensive action
• Carry Length: Average Carry Length
• Being Pressured Change in Pass%: How does passing % change when under pressure? This is calculated as Pressured Pass % minus Pass %
• Successful Crosses: Completed Crosses
• Open Play xG Assisted: xG Assisted from open play
• Open Play Key Passes: Passes that create shots for teammates, from open play only

We can see a radar that more closely resembles what we'd associate with Alexander-Arnold's style of play. He's performed to a very high standard in the chance creation metrics we selected (96th percentile for Open Play xG Assisted, for example), with stylistic indicators such as Carry Length and Average Defensive Action Distance providing further illustration of his player profile. When we're happy that the radar we've created reflects and demonstrates the profile of player we're looking for, we can save the template for future and repeated use.

But how can we use this information to find potential competition or players of a similar profile?

2) Use StatsBomb's Similar Player Search Tool

The first thing to do in Similar Player Search is to set the filters for potential replacements. StatsBomb cover 80+ competitions worldwide, but Liverpool tend to focus on recruiting from the very top of the market. For the purposes of this exercise, we’re going to set the following filters to search within:

• Season: 2020/21
• Minutes Played: >=1200
• Competition: Big 5 European
• Age: U-25

The returned list throws up some interesting names, some more realistic than others. It's no surprise to see Inter Milan's Achraf Hakimi flagged as a very similar profile of full back to Trent Alexander-Arnold - Hakimi put up 0.48 goals + assists per 90 from right wingback for I Nerazzurri in their Serie A title-winning season and in this campaign has boosted his reputation further as one of the world's best right-sided defenders. Priot to any qualitative scouting, the presence of Joakim Mæhle is a curious one as Atalanta profile as one of the most similar teams to Liverpool in StatsBomb's Similar Team Search tool, suggesting Mæhle might find the transition to Liverpool's playing style easier than most if Liverpool were hypothetically looking to add competition for the right back position and if Mæhle were hypothetically deemed to have the required quality to fulfil that role.

The list returned is 73 players long which can be exported for further filtering, analysis and scouting.

3) Use IQ Scout

The second thing we can do to find players and create scouting shortlists is to use IQ Scout. IQ Scout is the recently upgraded scouting and recruitment tool within the StatsBomb IQ platform. We can use IQ Scout to find more players that may not have been flagged in our Similar Player Search, using filters to bring the list of players down to a manageable and relevant number. The first thing to do in IQ Scout is to select the radar template we’ve just created so we can filter our shortlist based on those metrics. Setting a benchmark of:

• >= 3.75 Deep Progressions per 90 minutes
• >= 0.50 Open Play Key Passes per 90 minutes
• >= 0.50 Successful Crosses per 90 minutes
• >= 62% Tackled / Dribbled Past %

… returns a shortlist of 11 players (after excluding Alexander-Arnold) that we can be confident are worthy of further investigation and filtering.

Loosening or altering the filters brings up a different set of names, as does adding more leagues to the search, allowing you to widen or reduce the pool of players before you export the shortlist which includes their performance data across every metric in the StatsBomb IQ Scout database.

Of course, IQ is flexible to each user's demands and scouting criteria, so let's take a quick look at an alternative profile of full back to demonstrate this.

Benjamin Pavard has just come off the back of another title-winning season at Bayern Munich and heads into the Euros with France looking to double up on their 2018 World Cup win. Pavard has provided a stable solidity to Bayern's back four, counterbalancing the rampaging and aggressive Alphonso Davies on the opposite flank. Pavard's key duties in the Bayern backline have been to protect the Bavarian's from becoming exposed on the counter, allowing their more attacking talents to flourish, and provide a safe outlet in possession to recycle the ball to more adventurous teammates.

Assuming safety - both defensively and in-possession - is the most important attribute we want to search for in this exercise, we can create a new player template that is designed to highlight and emphasise this. We'll remove Pressures, Deep Progressions, xGBuildup, and Successful Dribbles from the original full back template. In their place we'll add:

• pAdj Pressures: Possession adjusted pressures
• Pressured Pass %: Proportion of pressured passes that were completed
• Dribbled Past: How often a player fails a challenge and is dribbled past
• Blocks/Shot: Blocks made per shot faced

The new radar clearly highlights Pavard's defensively excellent performances for Bayern, regularly winning the ball back and protecting the Bayern goal and rarely giving the ball away. This provides a template and benchmark we can use to find players that perform defensive or "safe" actions to a similarly high level. Using this template in the Similar Play Search with the following filters:

• Age: U-24
• Minutes Played: min. 1200
• Season: 2020/21
• Competition: Big 5 European Leagues + Austrian Bundesliga, Belgian Pro League A, German Bundesliga 2., Netherlands Eredivisie, Portuguese Liga NOS, and Swiss Super League.

... returns a list of 100 players, with the five most similar players seen below:

Heading into IQ Scout and applying the same preliminary filters as before with the addition of:

• >= 50% Aerial Win %
• <= 1.20 Dribbled Past per 90 minutes
• >= 1.0 pAdj Interceptions per 90 minutes
• >= 1.5 pAdj Tackles per 90 minutes
• >= 65% Pressured Pass %
• >= 67% Tackle / Dribbled Past %

... returns a list of 12 players, ones we can be confident will be a reasonably close fit to the safety-first full back profile we're looking for and worthy of further analysis and scouting. We can also create a wider or more specific shortlist of players by adjusting or changing the filters.

That’s just a glimpse of how StatsBomb IQ can be used for player recruitment and shortlist creation, prior to the deeper analysis we can perform within IQ once we’ve identified our targets. If you’re a football club or organisation and would like a full demo of how StatsBomb IQ and Data can help you achieve your objectives, get in touch with us today.

Right now, dozens of clubs around the world will be using StatsBomb IQ to aid their player recruitment planning and shortlisting ahead of the summer transfer window. IQ is designed by analysts, for analysts, with the goal of making data-driven insights easily accessible and digestible. Most importantly, it saves valuable time and resources for the time-poor analyst and is flexible and customisable to each user's specific needs.

Data can be used at all stages of the recruitment process, from the initial shortlisting, down to more granular player assessments, to support qualitative live and video scouting and background personality checks. Yesterday, we showed how data can be used in the early stages of the recruitment process to create a shortlist of forwards that might be worth further scouting. Today we're going to do the same with centre backs, starting with Burnley's James Tarkowski.

It's well known that Burnley have a particular - and effective - approach to defending when out of possession. If their opposition has possession deep in their own half, particularly from goal kicks, Burnley will play a high line and look to force their opponents to play the ball long, where they know their centre backs will more often than not win their duels near the halfway line. This is shown in their Defensive Distance: the average distance from their own goal that a team makes a defensive action.

However, should the opposition break the initial press and start to progress into the middle third and beyond, Burnley look to drop in and decrease the space between the lines, keeping a compact shape and defending any balls that come into the box. Their prioritising of their shape over engaging the opposition is reflected in their Aggression % - the percentage of opposition pass receipts that are pressured, tackled, or fouled within two seconds - of 16%, the lowest in the league.

For Tarkowski, this means that his main responsibilities as a Burnley centre back can be condensed into: being strong in aerial duels, being strong in ground duels, and defending his penalty box well, with little-to-no expectation on him to be an effective player in possession. Given Tarkowski's importance to Burnley, and the fact he's been linked with moves away in previous windows, it'd be sensible for Burnley to be planning and searching for potential successors already. Let's use StatsBomb IQ to help us do this.

1) Create And Edit A Radar Template

The first thing to do is adjust the standard Centre Back radar template to include metrics that best reflect Tarkowski's player profile and give us the best chance of finding a player that could replace him.

As mentioned, we're not expecting Tarkowski or his replacement to be highly effective in possession, so we'll remove Passing %, Pressured Long Balls, Unpressured Long Balls and xGBuildup from the standard radar template. In their place, we'll add:

• Average Defensive Action Distance: The average distance from the goal line that the player successfully makes a defensive action
• Clearances: Number of clearances made by a player
• Blocks/Shot: Blocks made per shot faced

We can see that Tarkowski is an excellent performer in aerial duels (in the 99th percentile for Aerial Wins and 91st percentile for Aerial Win %), ground duels (72nd percentile for Tackle / Dribbled Past %*), and defending his box (88th percentile for Blocks / Shot and 83rd percentile for Clearances). *Tackle / Dribbled Past %: Percentage of time a player makes a tackle when going into a duel vs getting dribbled past.

When we're happy that the radar reflects the profile of player we'll be searching for, we can save the template for repeated future use. But how can we use this information to find a potential replacement?

2) Use StatsBomb's Similar Player Search Tool

The first thing to do in Similar Player Search is to set the filters for potential replacements. StatsBomb cover 80+ competitions worldwide, but Burnley tend to focus on a specific and limited number of markets when recruiting new players, mostly domestically. For the purposes of this exercise, we’re going to look at players from:

• Season: 2020/21
• Minutes Played: >=1200
• Competition: Big 5 European + English Championship
• Age: U-29

The top five most similar players make for interesting reading. Stoke's Harry Souttar has been praised for his performances in his first full season at Championship level and, at 22 years old, represents a centre back that could be of longer-term interest to a team that defends like Burnley. If Burnley were happy to look abroad, then not far below the top five players returned is Felix Uduokhai of Augsburg in the Bundesliga. Uduokhai not only has a similar profile to Tarkowski, but Augsburg also show up as a team that defends in a somewhat similar style to Burnley when comparing Burnley's defensive style to Big 5 + Championship teams in StatsBomb's Similar Team Search. At 23 years old, he could be another worth further investigation.

The list returned is 99 players long which can be exported for more detailed filtering, scouting and analysis.

3) Use IQ Scout

The second thing we can do to find players and create scouting shortlists is to use IQ Scout. IQ Scout is the recently upgraded scouting and recruitment tool within the StatsBomb IQ platform. We can use IQ Scout to find more players that may not have been flagged in our Similar Player Search, using filters to bring the list of players down to a manageable and relevant number. The first thing to do in IQ Scout is to select the radar template we’ve just created so we can filter our shortlist based on those metrics. Setting a benchmark of:

• >=70% Aerial Win %
• >= 3.0 Aerial Wins per 90 minutes
• <= 28.2 Average Defensive Distance (to find players used to defending in deeper areas)
• >= 0.05 Blocks/Shot
• >= 70% Tack/Dribbled Past %

… returns a shortlist of 12 players that we can be confident are worthy of further investigation and filtering.

Loosening or altering the filters brings up a different set of names, as does adding more leagues to the search, allowing you to widen or reduce the pool of players before you export the shortlist which includes their performance data across every metric in the StatsBomb IQ Scout database.

Of course, IQ is flexible to each user's demands and scouting criteria, so let's take a quick look at an alternative profile of centre back to demonstrate this.

Magdalena Ericsson has just come off the back of a title-winning and Champions League silver medal winning season with Chelsea. Ericsson's very capable on the ball, playing a crucial role in the early stages of build-up for Chelsea as well as possessing ability to progress the play herself through incisive passing or ball carrying.

Assuming on-ball ability is the most important attribute we want to search for in this exercise, we can create a new player template that is designed to highlight and emphasise this. We'll remove Fouls, Pressures, Pressured Long Balls, Unpressured Long Balls, pAdj Tackles and pAdj Interceptions. In their place we'll add:

• pAdj Tackles & Interceptions: Number of tackles and interceptions adjusted proportionally to the possession volume of a team
• Open Play Passes: Number of attempted passes in open play
• Being Pressured Change in Pass%: How does passing % change when under pressure? This is calculated as Pressured Pass % minus Pass %
• Deep Progressions: Passes and dribbles/carries into the opposition final third
• Carries: A player controls the ball at their feet while moving or standing still
• Carry %: Percentage of a player's Carries that were successful
• Carry Length: Average Carry length.

The new radar clearly highlights Ericsson's profile in possession: one that is heavily involved in the build-up (72 Passes In Open Play per 90) and moving the play forwards (7.9 Deep Progressions per 90). Using this template in the Similar Play Search with the following filters:

• Age: U-26
• Minutes Played: min. 900
• Season: 2020/21
• Competition: Big 5 European Leagues

... returns a list of 100 players, with the five most similar players seen below:

Heading into IQ Scout and applying the same preliminary filters as before with the addition of:

• >= 75% Tackled / Dribbled Past %
• >= 60% Aerial Win %
• >= 45 Open Play Passes per 90 minutes
• >= 2.8 Deep Progressions per 90 minutes

... returns a list of 10 players, ones we can be confident will be a reasonably close fit to the ball-playing centre back profile we're looking for and worthy of further analysis and scouting, with the opportunity to add, remove or adjust additional filters to create a wider or more specific shortlist of players. That’s just a glimpse of how StatsBomb IQ can be used for player recruitment and shortlist creation, prior to the deeper analysis we can perform within IQ once we’ve identified our targets alongside live and video qualitative scouting and background personality and availability checks. Next week we’ll look at another position on the pitch to further demonstrate how StatsBomb IQ can be customised to fit the precise profile of player you're looking for.

If you’re a football club or organisation and would like a full demo of how StatsBomb IQ and Data can help you achieve your objectives, get in touch with us today.

Right now, dozens of clubs around the world will be using StatsBomb IQ to aid their player recruitment planning and shortlisting ahead of the summer transfer window. IQ is designed by analysts, for analysts, with the goal of making data-driven insights easily accessible and digestible. Most importantly, it saves valuable time and resources for the time-poor analyst and is flexible and customisable to each user's specific needs.

Data can be used at all stages of the recruitment process, from the initial shortlisting down to more granular player assessments, to support qualitative live and video scouting and background personality checks. Today we're going to show you some examples of how IQ can be used to bring data into the recruitment process in the early stages when creating a scouting shortlist. Let’s look at a couple of Premier League forwards with different player profiles and role requirements. Given the rumours swirling around White Hart Lane at the minute, it seems likely that Tottenham might currently be in the process of drawing up contingency plans should Harry Kane depart for pastures new.

It goes without saying that Kane is vitally important to Spurs, being one of the best forwards in the world. Kane was the only player in the Premier League to hit both 0.20 xG per 90 *and* 0.20 xG assisted per 90 in the 2020/21 season. We want to create a shortlist of players that could be worth further investigation as potential replacements for the England striker. Spurs might be thinking about doing this in a number of different ways, replacing him with multiple players or adapting their style of play to bring the best out of other players, for example, but for the purposes of this exercise, let’s assume they’re looking for a direct replacement.

1) Create And Edit A Radar Template

The first thing we want to do in IQ is create a radar template that best reflects Kane’s output as a forward. We know that Kane takes on what you might call a “complete” role up front for Tottenham; dropping deep to be involved in build-up, providing creative link-play in the final third, whilst also being the team’s main goal threat. To do this, we select the “Edit Radar Template” function in IQ, choosing the relevant positions we want the data to filter for.

Next, we select the relevant metrics with which we want to judge Kane’s performances against and that will be used in the search for his potential replacement.

As an indicator of his ball progression and build-up play, we'll add Deep Progressions (the number of times the player moves the ball into the final third through a pass or dribble) to the original Striker radar template. As measures of his final third link play, we'll add Open Play Passes Into The Box as well as Open Play Key Passes. His goal threat will be measured by his Expected Goals and Shots totals.

Once our metrics are selected, we choose the radar percentile boundaries based on the distribution of data in each metric by the relevant positions we've chosen, in this case strikers.

When we’re happy with the metrics we’ve selected and layout of our radar, we can save the template for future use, and view the player on our newly created radar.

The new radar provides an accurate overview of Kane’s performances in the 2020/21 season against the criteria we' looking to judge:

• Goal Threat: 89th percentile for Expected Goals, 95th percentile for Shots
• Involvement In Build-Up: 95th percentile for Deep Progressions
• Final 3rd Link Play: 89th percentile for Open Play Passes Into The Box, 83rd percentile for Open Play Key Passes, 91st percentile for xG Assisted

We now have a radar that reflects Kane’s outputs. But how can we use this to aid our search for potential replacements?

2) Use StatsBomb IQ’s Similar Player Search Tool

The first thing to do in Similar Player Search is to set the filters for potential replacements. StatsBomb cover 80+ competitions worldwide, but Spurs will obviously be looking towards the top of the market for a possible new striker. For the purposes of this exercise, we’re going to look at players from:

• the 2020/21 season
• with a minimum of 1500 minutes played
• in a Big 5 league + Austrian Bundesliga, Portuguese Liga NOS, and English Championship
• and no older than 24 years old

The top 5 most similar players make for interesting reading, with perhaps Salzburg’s Patson Daka the most eye-catching given the rumours that he’s likely to follow Erling Haaland as the next forward off the Salzburg production line. Slightly different in style to Kane, Daka is more involved on the end of chances - as reflected by his Shot Touch % of 5% (the percentage of his touches that are shots) - and less involved in the build-up play, reflected by his 2.0 deep progressions per 90 minutes (compared to Kane's 4.3). However, the Zambian plays in a transition-heavy team (worth noting if Spurs are looking to stick with that style) and has shown consistent quality on the European stage. He might be worth consideration.

If we were to place more weight on the build-up and link-play metrics, names such as Amine Gouiri, Rafael Leão and João Félix appear closer to the top of the search. Some more realistic than others, but again perhaps worth further scouting and analysis from the Spurs recruitment team. On the criteria selected, 64 names were produced. We can export the shortlist with each of their similarity scores and outputs in the selected metrics attached to a .csv file for a more detailed look, whittling the names down based on their performances and potential availability.

There's still more we can do in IQ to increase our initial shortlist size.

3) Use IQ Scout

IQ Scout is the recently upgraded scouting and recruitment tool within the StatsBomb IQ platform. We can use IQ Scout to find more players that may not have been flagged in our Similar Player Search, using filters to bring the list of players down to a manageable and relevant number. The first thing to do in IQ Scout is to select the radar template we’ve just created so we can filter our shortlist based on those metrics. Setting a benchmark of:

• 2.0 Shots per 90
• 0.30 xG per 90
• 0.08 xG Assisted per 90
• 1.0 Open Play Key Passes per 90

… returns a shortlist of 12 players that we can be confident are worthy of further investigation.

Altering the filters slightly towards a more creative type of forward returns a list of 15 names, mostly new ones. We can change or loosen the filters as much as we want based on which we want to weight more heavily. Do we want a well-rounded forward who performs to at least an average level across a range of metrics? Or do we want one who is elite in a couple of highly important ones?

Once again, we can export the shortlists for further analysis and scouting, with the file containing the player's performances across every StatsBomb metric.

To demonstrate the flexibility of StatsBomb IQ to each user's needs, we can repeat the process for a forward with a slightly different profile to Harry Kane. Leeds’ Patrick Bamford is another prolific English goalscorer in the Premier League, but his role in the Leeds team is different to that of Kane’s. Bamford is relied upon to consistently find space in the box, be a finisher of the team’s chances rather than create them, and provide a high work rate out of possession in Marcelo Bielsa’s system.

We can create a radar template that best reflects Bamford’s outputs in the Leeds team and the type of player we’re searching for. The key metrics we'll be judging Bamford and his potential replacements against will be:

Find Space In The Box:

• Touches In Box

Finisher Of Chances:

• xG
• Shots
• Shot Touch %

Defensive Work Rate:

• Pressures
• Pressure Regains
• Counterpressures
• Possession-Adjusted Tackles & Interceptions

Again we can set the radar percentile boundaries based on the data filtered by each position, so we can see the 5th and 95th percentiles for counterpressures by strikers, for example, and then save our template for future use.

We can see that Bamford performs well in the metrics we’ve highlighted as being important to a player of his role and requirements: in the 96th percentile for Touches In The Box, the 88th percentile for Pressure Regains, and with a Shot Touch % of 5%. The Similar Player Search (using the same criteria as used for Kane but with the Eredivisie and Belgian Pro League added) returns some high-profile (and likely expensive) names. Danilo of FC Twente (on loan from Ajax) could be the most attainable of the top five, but not far further down the list you find Youssef En-Nesyri of Sevilla and Adam Armstrong of Blackburn, for example.

We can export the shortlist and then head into IQ Scout to widen our pool of players. Selecting the same competition, age, and minutes played filters and applying further filters on our metrics with a minimum of:

• 2.0 Pressure Regains per 90
• 13.5 Pressures per 90
• Shot Touch % of 3%
• 10 Touches In Box per 90
• 0.2 xG per 90

…returns a list of 16 names that we can be confident will be close to the style of player we’re searching for, again allowing the option to loosen or change the filters if we want to widen or reduce our shortlist, and also allowing us to export the list of players for further analysis and scouting, with the players' performance in each StatsBomb metric listed within the exported file.

That’s just a glimpse of how StatsBomb IQ can be used for player recruitment and shortlist creation, prior to the deeper analysis we can perform within IQ once we’ve identified our targets, alongside live and video qualitative scouting and background personality and availability checks. Later in the week we’ll look at different positions to further demonstrate how StatsBomb IQ can be customised to fit the precise profile of player you're looking for.

If you’re a football club or organisation and would like a full demo of how StatsBomb IQ and Data can help you achieve your objectives, get in touch with us today.

One of Brazil’s biggest football clubs, Clube Atlético Mineiro, have signed a partnership with StatsBomb, empowering their analytics department, led by Rodrigo Picchioni and Pedro Picchioni, with the most detailed football data available. This is the first time StatsBomb, one of the fastest growing sports data companies in the world has expanded its marketing-leading services into Brazil.

The partnership will see Clube Atlético Mineiro receive StatsBomb’s cutting edge data covering over 3,400 events per match, across dozens of leagues and competitions across the globe. Alongside the data, the club will have full access to StatsBomb IQ, the most advanced and customisable football analytics platform available.

Clube Atlético Mineiro join around 100 professional clubs and federations around the world in enhancing their ability to scout and recruit players, analyse upcoming opponents and evaluate team performance.

Plínio Signorini, CEO, Clube Atletico Mineiro said:

"Clube Atlético Mineiro has chosen the best data provider in the world to start its analytics department. One of the strategic principles of our club is, after all, to be a reference in Latin America both on and off the pitch. In order to achieve that, it is crucial to seek innovative and efficient partners such as StatsBomb."

StatsBomb’s Head of Tactical Innovation and Business Development, Pablo Peña Rodríguez said:

"It is great to be working with one of the biggest clubs in Brazil. Throughout our conversations, the analytics team at Atletico Mineiro have shown fantastic ambition and understanding of the role our data and IQ platform can play in their preparations. We’re delighted to be expanding into Brazil and are looking forward to more opportunities in the region."

Norwich City are back, promoted as Champions of the Championship for the second time in three seasons to return to the Premier League for the 2021/22 season. Talk of ‘trusting the process’ has been heard numerous times in recent weeks – The Canaries stuck with the same formula that had already earned them promotion in 2018/19; same manager, same principles, same players (mostly).

The dual pursuit of success and self-sufficiency instilled by Sporting Director Stuart Webber came at a sporting cost last season in their Premier League relegation, but having sent Daniel Farke “to war without a gun” in 2019/20 – the highest figure Norwich spent in the summer of 2019 was £750,000 - Farke certainly had the benefit of a full range of weapons in 2020/21. The squad had been refreshed with depth and quality but, more importantly, Norwich retained their best performers from the previous two seasons to lead the charge back to the top flight.

Of the eleven most-used players this season, four were in the eleven most-used in 18/19 (Emiliano Buendía, Tim Krul, Teemu Pukki, Max Aarons) and only three were summer signings: Oli Skipp, Ben Gibson and Jakob Lungi Sørensen. Grant Hanley, Todd Cantwell, Kenny McLean and Mario Vrančić were all less-prominent parts of the 18/19 group but were this time around well ingrained in Farke’s playing style and much more prominent members of the squad.

There’s little doubt that Norwich have been better this time than when they won the league two years ago. The 2020/21 iteration felt more complete as a side, almost entirely down to performing much better defensively than in 2018/19. They scored 18 fewer goals in this campaign, but they conceded 21 fewer across the 46 games as well, nearly half-a-goal-a-game drop-off on their last Championship season.

The improvement at the back can be put down to a few different factors, most of them more refined performances from individuals in executing the gameplan as the underlying numbers remained similar: in 2018/19 Norwich conceded 53 (non-penalty) goals from 47.2 expected goals, in 2020/21 it was 33 conceded from 45.7 expected goals.

But there was more balance to the side now. Kenny McLean and Oli Skipp anchored the midfield and kept the middle of the park on lock to allow the attacking talents to dovetail in advanced areas of the pitch without fear of being hit in transition. Skipp had a particularly stellar season on loan from Spurs, receiving immense credit for his positional sense and tidiness in the midfield and often covering for Max Aarons’ raids down the right wing by preventing the opposition from transitioning down that flank if possession was lost.

If the ball did reach dangerous areas, Grant Hanley and Ben Gibson were almost always there to clean up – Hanley made the most interceptions and the most clearances (both adjusted for possession) of all centre backs in the Championship - and Tim Krul also had a much better season in goal too. After conceding 52 goals from 49 post-shot expected goals in 2018/19, which takes into account the placement of the shot to judge the probability of the goalkeeper making a save, he fared far better in 2020/21 to save Norwich roughly seven goals, conceding 22 goals from 29.2 post-shot expected goals. His Shot Stopping % of 7% - the measure of goals saved above average, as a percentage of shots faced by the goalkeeper – ranked the highest of all Championship goalkeepers this season.

Norwich finished the season with the second-best defensive record and the second-best attacking record, combining for the best goal difference overall. Their attacking game and approach in possession drew the most attention and praise, in-part because of the ease on the eye and in-part because of the elite talent, especially so at Championship level, they had executing it.

The Canaries had more of the ball than any other side in the second tier this season but also moved it into the areas that matter more than anyone else: entering the final third more than any other team, completing the most passes within 20m of goal (Deep Completions), and completing the most passes within the opposition penalty area.

Their short passing and combination play resulted in some wonderful football being played at times, Cantwell and Buendía in particular regularly producing technical quality way above Championship level when tucking into central areas from the left and right flank respectively.

That technique and invention compounded with the intelligent movement of Teemu Pukki resulted in a regular supply line of through balls splitting the opponents' defence. Rarely did a game go by without Norwich getting in behind the opposition, completing 105 through balls for an average of 2.3 per game. For context, the teams with the third and fourth-most through balls in the Championship, Brentford and Bournemouth, completed 108 defence-splitting passes combined.

Of the players to complete the most through balls in the league, three were from Norwich, with Buendía and Vrančić making the top two and Cantwell rounding out the top five just below Harvey Elliott and Callum O’Hare.

Buendía's starting position on the right flank is on teamsheet only. In reality, it's Aarons who'll keep the width when Norwich are in the attacking phase with Buendía tucking into central areas - where he can cause more damage with a greater sight of goal. It's clearly observable when looking at his through balls, only two of which were played from an area wide of the penalty area, the rest coming from a more narrow starting position.

It's also notable how many of those threaded passes were played from deeper areas. These were not typically passes that broke the opposition's deep block, often they were quick and laser-like passes in transition where Buendía and particularly Pukki’s skillsets thrived. After winning the ball in their defensive third, if Norwich could get the ball to Buendía lurking intently in the space between the opposition midfield and defence then it would spell trouble for their opponents, with Pukki playing on the shoulder and poised to make a perfectly timed run in behind.

Buendía’s influence on this Norwich team and the Championship itself was so great that there have been discussions in recent weeks as to whether this has been the greatest individual season ever witnessed in England’s second tier. The quality shown in the final third has been closer to that seen in the Champions League than the Championship, with the Argentine finishing the season on 14 non-penalty goals and 14 assists, backed up by accruing the most xG assisted in the league (13.2) from the most key passes (120).

His influence in the final third bears out in how often Norwich were able to get him on the ball in those areas, with Buendía completing 760 final third passes across the season (19.4 per 90 minutes) and 82 open-play passes into the penalty area (2.1 per 90 minutes). Both were league best numbers, as was the fact that just 8% of his passes in the final third went backwards, a league-best figure amongst Championship attacking midfielders and wingers and a number that illustrates his ability to keep the attack moving towards goal.

That he’s one of the league’s most active defenders is just the cherry on top. The truth is, Buendía very likely would’ve won the Player Of The Season award for his attacking play alone, but his contribution on the defensive end only adds to the mesmeric nature of his performances.

His determination and work rate has landed him disciplinary trouble at times, picking up 2nd yellows for a red card on two occasions this season, but his discipline out-of-possession has been a key part of Norwich’s success, providing support to Oli Skipp and Max Aarons in defending the right flank. Adjusted for possession, given Norwich had more of the ball than any other side this season, Buendía recorded the most pressures of any player in the Championship in 2020/21. Of course, none of this would’ve been possible without another exemplary season leading the line from Teemu Pukki, playing the role of 20+ goal striker yet again. Pukki’s role in the team remained the same as it always has – lead the press and provide a nuisance when the team's out of possession, make devilish runs and finish lethally when the team's in possession. Following on from earlier, 1-in-5 of Pukki’s shots came after a through ball. One of the most archetypal forwards in the league, both in role and in attributes, Pukki was behind only Adam Armstrong for the percentage of total touches that are a shot, with 5% of his touches being a shot on goal. The Fin eventually finished third in the goalscoring charts, both with & without penalties, but his expected numbers were ahead of Ivan Toney and Armstrong – Pukki finished with 27.3 expected goals + expected goals assisted, the most in the Championship this season. Deserved champions, the common consensus is that Norwich are much better prepared than last time to attempt Premier League survival next season. A period of uncertainty around whether they can keep their best stars in yet another transfer window will surely ensue, but one thing we can be certain of – the process will remain the same.

Perhaps we’ve misunderstood all along. For all the years that French football has had the "farmers league" tag directed at it, supposedly for the lack of quality in the league, is it possible that the accusers have the whole time been referring to the fertile soil that churns out huge quantities of players talented enough to play on the continent each season?

It’s true of Ligue 1, and it’s certainly true of Ligue 2. Of all the second tiers of the ‘Big 5’ European leagues, Ligue 2 stands out as one of the most prolific and consistent breeding grounds for players that go on to play at the top of the game. In the last couple of years alone we’ve seen Alexis Claude-Maurice (OGC Nice), Pape Gueye (Marseille), Silas Wamangituka (VfB Stuttgart), and Maxence Lacroix (VfL Wolfsburg) graduate from France’s second division to play towards the top end of some of the best leagues in the world. Tino Kadewere, another example, made the summer move from Le Havre to Lyon with great success, completing a seamless transition from the top half of Ligue 2 to a title challenge in Ligue 1.

And so, the next batch. Already confirmed as the next graduate out of Ligue 2 is Kouadio Koné. After a breakthrough season in 2019/20, the 19 year old Toulouse midfielder has dialled it up in 2020/21, enough to convince Borussia Mönchengladbach to part with a rumoured €9million in January to secure his services for the 2021/22 season, leaving him at Toulouse to finish the Ligue 2 campaign. Koné profiles like a classic box-to-box, do-it-all midfielder, contributing plenty on the defensive end, impressive in transition both in carrying the ball and playing forward passes to his attackers, and not shy of testing the goalkeeper from range.

Very active off the ball, Koné has shown a tenacious streak both in his propensity for closing down the player in possession, or making a tackle to win the ball back, or generally firefighting across the midfield.

Koné picks up far fewer Interceptions relatively speaking, with 0.9 interceptions per 90 ranking 50th of 57 Ligue 2 central midfielders to play at least 1200 minutes this season, which is perhaps unsurprising for a player so eager to engage the opposition rather than hold his position. On the flip side, that tenacity has seen him rack up the fifth-most tackles per 90 minutes amongst Ligue 2 central midfielders, as well as the sixth-most pressures.

That’s to ignore the fun stuff though.

Clearly the French U19 international’s standout attribute is his ability to get the ball -> carry the ball. That penchant for engaging the opponent isn’t limited to his defensive work, he’s keen to take them on when on the ball as well: Koné attempts (4.0) and completes (2.9) more dribbles than his Ligue 2 centre midfield contemporaries, and completes them at a rate (73%) only Leverton Pierre (76%) of Dunkerque can beat for players who attempt at least 2.0 dribbles per 90. His ball-carrying ability is also reflected in his Carry numbers, the volume of which is around league average, but his average carry length of 6 metres is second only to Rominigue Kouamé of Troyes with 6.2 metres, displaying his ability to carry the ball over longer distances from the centre of the park.

It’s the areas of the pitch that Koné is dribbling in that make him an interesting player. Clearly a useful asset to have when transitioning from defence to attack, he utilises this skill both in the defensive half and in the attacking third and drifting left or right, with 1.8 completed dribbles per 90 in the middle third and 1.0 in the attacking third. Not just utilising this asset in moving Toulouse up the pitch, but also as a means to create space in the attacking phase as well.

When it comes to progressing the play through passing, Koné has also shown ability here, just behind teammate Branco van den Boomen for moving the ball to the final third (5.2 Deep Progressions per 90) , a figure that puts him 10th overall in Ligue 2 central midfielders. Indeed, he profiles similarly to van den Boomen across most passing metrics, showing similar importance and sharing responsibility in possession with his more senior midfield partner. It’s easy to see why he’s trusted with the ball when he’s able to protect it so well, completing 81% of his passes under pressure.

There isn’t too much of a goal threat from Koné yet, but that’s not to say he hasn’t contributed there, averaging 1.8 shots per 90 – with most of them from 18 yards out or further - amounting to 0.10 xG per 90, a figure which has translated into two goals this season.

Remembering that he's only 19, it becomes easy to see why Mönchengladbach decided to take him on as a project player, clearly possessing the ability to compete at a higher level. If Koné can mimic the success that compatriot Maxence Lacroix has managed in his first season of Bundesliga football at Wolfsburg, then Gladbach fans are surely going to be pleased.

One player who hasn’t sealed a move in advance but has hardly been going under the radar is Mohamed Bayo. The Clermont Foot forward has been spearheading the third-placed side’s promotion push and leads the scoring with 17 goals - 15 when you exclude penalties. Bayo clearly has a superior goal threat to his striking peers in Ligue 2 with 3.4 shots per 90 the highest rate in the league, and many of them come from high-probability positions - an xG per shot of 16% is the eighth-best rate amongst Ligue 2 forwards.

TL;DR: LOTS of GOOD shots.

Bayo’s path to the Clermont first team is an interesting one. A graduate of their academy, he spent the 2019-20 season in the Championnat National on loan at USL Dunkerque, top scoring for his temporary side with 12 goals to lead them to promotion to Ligue 2. It was only the sale of Clermont top scorer Adrian Grbic to Ligue 1 Lorient in the summer of 2020 that gave Bayo the opportunity to enter the XI and lead the Clermont forward line. He hasn’t looked back.

Clearly a capable penalty box forward, scoring all of his 15 non-penalty goals from inside the box, the 22 year old’s contribution to Clermont’s attack extends further than his goal scoring exploits. Defensively his output could be a little higher, registering 10.8 pressures per 90 – slightly below average for Ligue 2 forwards, but his contribution to the attacking phase cannot be questioned. As well as carrying the ball reasonably well, with an average carry length of 4.6 metres and carrying the ball into the box 1.4 times per 90, behind only Paris FC's Gaëtan Laura, and as well as being plenty capable taking on defenders, completing 1.9 dribbles per 90 (only three Ligue 2 forwards complete more), it’s his contribution to creating chances for his team mates that stands out. He sets up 1 open play shot per game on average, and assists 0.17 expected goals per 90, which, when you do the math, means that the average chance he sets up has an expected conversion rate of 17%. Given the average shot is converted at ~10-11%, Bayo’s clearly chooses his moments to pass wisely when he’s not pulling the trigger himself, setting up quality goalscoring opportunities. That creativity plus the expected goals output of his own shots mean that Bayo's expected goals contribution amounts to the highest of all Ligue 2 forwards this season.

Clermont could well be playing Ligue 1 football themselves next season if they can seal promotion, currently two points with a game in hand behind Kouadio Koné's Toulouse, but otherwise it seems highly likely there’ll be interest from the top tier of French football, let alone elsewhere on the continent, for a forward that’s clearly stood out in the second tier this season. Kouadio Koné will certainly be in the big leagues. We'll wait and see if Mohamed Bayo joins him too.

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Our final look at the major European leagues sees the German Bundesliga come under the spotlight. Talk of a Bavarian behemoth, a alliterative forward winning with Wolves, hard-pressing Hütter, and sorry Schalke 04. On the back of a Bundesliga, DFB-Pokal, and UEFA Champions League treble, Bayern Munich continue to meet their lofty standards. On course for yet another 80+ points haul, the juggernaut continues to plough a furrow through the Bundesliga, but there are some curious trends in their performance levels this season. Bayern aren’t swatting teams aside with the ease and comfort that we’ve come to expect of them - their xG difference of 0.64 per game is their lowest since 2016/17. Their 15-game expected goals trendline since the start of the 2018/19 season illustrates the fact that they haven’t quite been at their imperious best so far this campaign. The 26 goals they've conceded already is only six shy of the 32 they gave up in the entirety of 2019/20. There was even a six-game spell between FC Köln on October 31^st and Union Berlin on December 12^th inclusive that Bayern didn’t “beat” their opponents on expected goals – in each of those six matches the opposition created the more dangerous opportunities. But FCB didn’t lose a single one, claiming three wins and three draws from their “wobble”. Since then, they’ve flexed their muscle and performances have improved in line with a commanding haul of 21 points from the next eight, a run that has seen them pull clear at the top. RB Leipzig are looking to go one better than last years third-place finish and their metrics look sufficiently strong to support them, but it's below them where chaos starts to ensue: just three points separate Wolfsburg in third and Borussia Mönchengladbach in seventh. Wolfsburg, who had to win the Bundesliga relegation/promotion play-off match two seasons in a row between 2016-2018 just to stay in the league, are currently on course for their highest finish for six seasons and Champions League qualification. Big Wout Weghorst - to give him his full name - is having his best goalscoring season in the green of Die Wölfe. He's behind only Robert Lewandowski for non-penalty goals with 11. At the other end of the pitch, goalkeeper Koen Casteels is on course to concede fewer goals than expectation for the fourth season running, with the best Shot Stopping % in the Bundesliga this season (Save % - xSave%). Another team gunning for a rare Champions League qualification is Eintracht Frankfurt, who haven’t qualified for the premier European competition since they lost the 1960 final to Real Madrid (when it was known as the European Cup). Right now, they're in position to break that duck. You know what you’re going to get with an Adi Hütter side. The ex-RB Salzburg and Young Boys coach has again instilled an aggressive press into his team, one that’s proven effective as Frankfurt currently sit fourth in the table, having lost just two of their 19 games. No other side in the league engages the opposition as regularly as Frankfurt: their Aggression % - the portion of opponent’s ball receipts that are tackled, fouled, or pressured within two seconds - is the highest in the Bundesliga at 24%. Andre Silva, like Weghorst, is having his best Bundesliga season yet, but it’s supplier-in-chief Daichi Kamada who’s providing the chances for the Portuguese forward. Kamada, who top-scored himself for Frankfurt in 2019/20, is behind only Thomas Müller and Marco Reus for xG assisted from open play. Meanwhile, the irony will not be lost on long-term followers of football analytics discourse for the way that Lucien Favre lost his job at Borussia Dortmund, on the back of some pretty large underperformance on their expected goals. Favre's teams were notorious for outscoring the performance metric, but this season it came unstuck and Dortmund currently languish in sixth place despite having the strongest expected goal difference this campaign. At 37.5 xG, which happens to be the same as Bayern’s, their chance creation in attack has been the best in the Bundesliga, but where Bayern have scored 51 non-penalty goals from their 37.5 xG, Dortmund have finished bang on expectation, scoring 37 times. They haven’t been able to match this in defence, conceding 25 non-penalty goals from 19.6 xG. Despite a strong start, going 5-0-1 in their first six games, the five games that followed cost Favre his position as Dortmund won just once. His last match was a heavy home defeat to VfB Stuttgart - there was no ambiguity over who deserved the result on that day. Speaking of VfB Stuttgart, they’re making an impressive mark on the league following promotion back to the Bundesliga in 2019/20. Previously assistant to Julian Nagelsmann at Hoffenheim, Pellegrino Matarazzo was appointed to his first senior management role in December 2019 and led Stuttgart to 2^nd place in the Bundesliga 2. Right now, Stuttgart have the fourth-best xG Difference but are behind expectation in both defence and attack, to have a goal difference of +6 from an expected goal difference of +9.5. At the bottom, Schalke 04’s sorry season has persisted despite two managerial changes already. David Wagner was politely asked to leave just two games into the 2020/21 campaign after back to back defeats continued an 18-match winless run, and the appointment of Germany under-18’s coach Manuel Baum did not have the desired effect. He was relieved of his duties after just 10 games. Now it’s Christian Gross who looks to dig something out of the Miners in his 33^rd year of management. Nine points adrift and bottom of nearly every performance metric you can think of, it’ll be some turnaround if Gross can steer them to safety.

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We continue our tour through the major European leagues with a look at the season to date in La Liga, the most goal and shot shy of the big five leagues but one that nevertheless features some intriguing storylines, including a runaway leader, tactical adjustments and some standout individuals.

Atlético Madrid, Runaway Leaders

In the last 16 seasons, Atlético Madrid are the only side other than Barcelona and Real Madrid to have won La Liga, and they may just be on course to do so again. Diego Simeone’s side are 10 points clear at the top, and also have a game in hand over those two sides. Fifty points from 19 matches has them on course to equal the league’s highest-ever points total of 100 if they are able to maintain that rhythm. The likelihood is that they won’t. No side have overperformed their metrics to a greater extent than Atlético so far this season. They are running ahead of expectation at both ends of the pitch, but particularly so in attack, where they are around 13 goals ahead of their xG. It is almost the exact opposite to what happened to them last season, when all their forwards were underperforming their xG at this stage of the campaign. This time around, everyone is overperforming: Luis Suárez, Marcos Llorente, João Félix, Ángel Correa, even Yannick Carrasco. That is likely to even out a bit from hereon out, but Atlético can still count upon a goalkeeper who has consistently shown his value by overperforming his metrics. On both an outright and shot-volume-adjusted basis, Jan Oblak has been the league’s best shot stopper this season. Even if Atlético’s points accumulation rate does slow somewhat during the second half of the campaign, they probably have enough of a cushion to absorb that and still end up lifting the trophy. Barcelona seem to be finding their feet after a shaky start, at least in terms of results, under Ronald Koeman, and do have the best underlying numbers in the league... ...but they would have to maintain an extremely strong pace to chase Atlético down from here. Real Madrid likewise have better metrics than the current leaders, but have struggled for consistency. The league looks to be Atlético’s to lose.

Pressing Matters

One of the most obvious changes upon Koeman’s arrival to the Barcelona bench was that they immediately began to contest possession less frequently, particularly high up the pitch. Whether by PPDA (Passes per Defensive Action) or Aggression (the percentage of opposition ball receipts that are contested within two seconds), they were one of most passive teams in the league through the first few months of the season. In fact, by the former measure, Barcelona were more passive than they’d been at any previous stage in our dataset, which extends back to 2004, in those first 10 or 11 matches under Koeman. But since then, there does seem to have been a shift towards a slightly more proactive setup, more in line with what we saw at times under Ernesto Valverde. Some of that could simply be due to the natural ebb and flow of the season. Barcelona had midweek Champions League engagements through much of the opening three months of the campaign, perhaps necessitating a less energy intensive approach. We’ll have to wait for a larger sample to see if this apparent shift holds through the remainder of the campaign. At the opposite end of the scale sit a Celta Vigo side who have become notably more proactive without the ball this season, and particularly so since Eduardo Coudet replaced Óscar García as head coach in November. They have pushed their defensive line up and are logging a higher Aggression percentage than any other side in the league.

Relentlessly Positive Ontiveros

Huesca have been in the bottom three since the seventh matchday, but things are so tight down there, with just four points spanning the bottom six, that they still have a decent chance of scrambling clear of the relegation zone. If they are to do so than Javi Ontiveros is likely to have a big role to play. Whether from the start or the bench, he is an intensely positive player who seems not to understand the idea of a backwards step. Whether on the pass or the carry, he is a relentless ball progressor... ...and while his shooting locations bring to mind Spurs-era Andros Townsend... ...he is such an entertaining watch that you can almost forgive him. Not only does he produce far more shots per 90 after carries of 10 metres or more (1.47) than any other player in the league, but he also leads it in nutmegs per 90 (ahead of Alberto Perea and Bryan Gil) and ranks in the top three for successful dribbles. Ontiveros is the guy to inject a bit of fun into your viewing of La Liga.

Additional tidbits

• Nabil Fekir of Real Betis has taken more shots than any other player in the big five leagues this season without scoring: 53. He’s also only converted one of his three penalties.
• One of the many advantages of the StatsBomb dataset is that we record the foot with which each pass is played. That allows us to see that for the second season in a row, Tomás Pina of Alavés is the most two-footed player in La Liga. Last season, he played an exact 50-50 split of passes with each foot. This time he’s slightly favoured the left in a 51-49 split. Pedro Bigas has consistently been one of the league's most two-footed players through his time with Las Palmas and now Eibar, and he is again there at Pina’s side.

Join us at StatsBomb Evolve on March 17th 2021 to discover how we are revolutionising the football data industry (once again), including the launch of our new data product, StatsBomb 360.