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In League Two this season, something strange happened… Two of the automatically promoted teams and two sides that reached the playoffs were StatsBomb customers.

Flamengo and Palmeiras are the last two winners of the Copa Libertadores, and one of them will again get their hands on the trophy when they meet in the final of the 2021 edition in Montevideo on Saturday. It is the second consecutive all-Brazilian final and one that features representatives from each of its two primary cities: Rio de Janeiro and São Paulo. Both teams are on course to finish in the top three domestically this season — although only Flamengo still have a chance of overhauling champions elect Atlético Mineiro — and while Flamengo have been the better team in terms of both results and the underlying numbers over the course of the campaign, the difference isn’t so great as to think the result of the final is a foregone conclusion. Flamengo are a much more possession-orientated team, building up short from the back and into midfield and dominating the ball in their matches. They hold a 60% share of possession on average — four percentage points clear of the next team. Palmeiras hover much closer to the 50% mark and are more direct in their approach, with one of the longest average pass lengths in the league. This difference in approach is evident if we look at the zones from which the two teams create most danger. With the help of On-Ball Value (OBV), our new model that values every on-ball action in terms of its positive or negative impact on a team’s likelihood of scoring / not conceding, we can visualise the areas of the pitch from which they generate most value in comparison to the league average. Flamengo are a lot more active through the centre of the pitch and particularly in the interior channels of the attacking midfield line, from where they create the majority of their chances. From the left, the value is added by Giorgian de Arrascaeta’s incisive passing and Michael’s aggressive carries; from the right, primarily by the passing of striker Gabriel Barbosa. Barbosa, scorer of the two late goals that gave Flamengo their dramatic win over River Plate in the 2019 final, plays as the lone striker in Renato Gaucho’s habitual 4-2-3-1 formation and is the club’s top scorer in the Libertadores, but he is far from their only goal threat. Flamengo have the best top-line and underlying attacking numbers in Brazil, in addition to averaging 2.75 goals per match in the Libertadores, and Bruno Henrique and Michael have also reached double figures in league play. In terms of advancing the ball into attacking areas, it is the contribution of ex-Atlético Madrid and Chelsea left-back Filipe Luís that stands out. He is much more active in infield areas than the average Serie A full-back — on the other side of the pitch either Mauricio Isla or the promising Matheuzinho generally play much higher and wider — and leads both his team and the league in deep progressions (passes or carries into the final third), distance advanced towards goal in the attacking half and once all actions directly related to shots have been stripped out, OBV. At 36, he’s still going strong. Ball progression is more evenly split between the two sides of the pitch at Palmeiras, with a mix of carries and passes from Dudu on the left — second to Filipe Luis in the league in terms of distance advanced towards goal in the attacking half — allied to the regular forward movements of right-back Marcos Rocha (or his deputy Gabriel Menino). Further back, Luan is among the Serie A central defenders who add most value with their passing according to OBV. The right is, though, undoubtedly their most productive side in terms of chance creation, with the dark red colouration inside the area there on the OBV chart above primarily representing the excursions of Rocha, forward Rony and attacking-midfield drifter Gustavo Scarpa. Scarpa has been Palmeiras’ most profile shooter and chance creator in the league this season, with three non-penalty goals and 11 assists to his credit and the league’s highest OBV contribution per 90 amongst all players with at least 900 minutes of playing time. But he has seen comparatively few minutes in the Libertadores and is most likely to start the final from the bench. With Luiz Adriano expected to miss out through injury, coach Abel Ferreira is likely to start Rony as the main striker in a formation that could vary between a 4-3-2-1 and 3-4-2-1 depending on the positioning of Felipe Melo, still going at 38. In the league, Rony has spent more time out wide than he did last season, with a consequent effect on his shot volume and goal output, but he is the team’s top scorer in the Libertadores, with six goals to his credit — 0.78 per 90. At the other end of the pitch, there is an even starker difference in approach between the two sides. Flamengo not only defend further away from their own goal than any other Serie A side, but they are also one of the league’s most aggressive teams in closing down opponents, particularly so directly after losing possession. Palmeiras, meanwhile, defend marginally deeper than the league average, and are clearly less active defensively in the opposition half. Interestingly, though, both appear equally proficient in converting opposition turnovers into efforts on goal, figuring amongst the Serie A teams who most often shoot and score within 20 seconds of regaining possession. Flamengo and Palmeiras have already met twice in the league this season, with Flamengo emerging victorious on both occasions. They won 1-0 with a dominant performance on the opening day of the season and then 3-1 away from home a couple of months back in what was actually a closer match in terms of chance quantity and quality. Flamengo are again the most probable victors on Saturday, but Palmeiras have already seen off two other Brazilian teams to make it this far, and the reigning champions certainly shouldn’t be discounted. The stage is set for an entertaining final.


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Welcome back, Norwich City. Back-to-back Championship titles sandwiched a Premier League relegation in 2019/20 – the Canaries will be looking to improve on their previous showing in the top tier this time around. You’ll recognise a few faces from their last outing in the top flight: Daniel Farke remains in charge and with a new four-year deal in his desk drawer to continue getting his tactical fingerprints all over this team; and much of the spine from the Premier League relegation season remains, with the likes of Tim Krul, Max Aarons, Todd Cantwell and Teemu Pukki all demonstrating a capability to play at this level the last time they were here. There’s no question that Norwich were deserving Championship champions after a hugely impressive season which saw them graduate with 97 points. They were the best team in the league both aesthetically and by the numbers; their expected goal difference of +30.2 was superior to anyone else in the division. This was largely powered by a free-flowing attack that created a continuous stream of chances from all areas of play. They took more shots than anybody else, created the most xG from open play, and were as comfortable forcing turnovers from the front as they were counterattacking at speed or playing through their opponents with dovetailing possession play. Luton Town manager Nathan Jones dubbed them the “Manchester City of the Championship”, an easy comparison to make that’s not without merit: Norwich also generally favoured a short-passing approach in possession with the freedom to rotate positionally and committing plenty of bodies to the attack. They possessed the slowest Pace to Goal in the league at 2.2 m/s, completed their passes at a higher rate than anyone else, and reached the final third more often than their rivals. A strength of Norwich’s attacking play last season was their ability to play through even the most stubborn defensive lines. Norwich led the league for completed throughballs with 105, at a rate of 2.3 per game. To put those numbers into context, Brentford and Bournemouth – the teams with the third and fourth-most completed throughballs — completed 108 defence-splitting passes combined. That ability to carve through defences meant that Norwich were often able to create a lot of space in the penalty area to get their shots away–they took by far the most open play footed shots in the box last season and, because the defence had often already been bypassed, on average there were very few defenders placed deeper than the Norwich attacker taking the shot. Out of possession they were organised, engaging the opposition higher up the pitch if the situation merited it but more often dropping in to defend from their own half. Norwich had the 17th-highest Defensive Distance in the Championship last season at 43.8 metres, the average distance from a team’s own goal from which it makes defensive actions. It’s a nod to Daniel Farke’s coaching ability that their high press, when they did engage in it, was highly effective, both in turning the ball over and in creating opportunities for them in attack. They made the 2nd-most shots following a high press, and forced the more counterpressure regains than anyone else in the league last season; counterpressure regains being regains that occurred within 5 seconds of a player counterpressing an opponent. That Norwich conceded the fewest counterattacking shots in the league was as much down to the midfield pair of Oliver Skipp and Kenny McLean performing caretaking duties in front of the defence as it was the effective counterpress. Norwich weren’t shy of committing bodies forward, often attacking with six players if not more with the full-backs bombing on, so when the opposition did attempt to break from their own third, they found Skipp and McLean – with their names like a 70s buddy cop duo – taking no nonsense and pulling over any opposition attempts to break and enter. Personnel & Transfers Daniel Farke changed little about his team’s approach the last time they came up, drawing praise from football purists but ultimately falling short, relegated in 20th place and with a -49 goal difference. Change is anticipated this time around, with Farke reportedly looking to play with the handbrake on more often and prioritise Norwich’s defensive shape over their attacking fluidity. Knowing what we do about the ex-Dortmund II coach and the club’s overarching philosophy, this far from equates to a complete overhaul of the playing style, just tweaks and adjustments here and there to make the team as a whole more defensively robust. It’s expected that we could see Norwich drop the #10 and line up in a 4-3-3 with a bigger focus on transitions, as opposed to the 4-2-3-1 witnessed in every Farke season to date. This is likely to mean that… ok, ok, ok. I’ve gone on long enough. Time to talk about the elephant in the room. Emiliano Buendía. Last season Buendía put in one of the most impressive individual seasons ever seen in England’s second tier, often playing football that looked more suited to the Champions League than the Championship. As well as consistently dazzling and delighting the Norwich support with displays of ball mastery, the Argentinian showed why he’s developed a reputation as a feisty customer, biting at the ankles of his opponents and generally being an absolute nuisance out of possession. He completed the ‘double double’ – recording 15 goals and 14 assists – but also moved the ball to the final third more than any other player in the league (adjusted to a per 90 minutes rate) and recorded the most possession-adjusted pressures per 90 as well. There’s little this player doesn’t do. No surprise then that Aston Villa were keen to offer Norwich a fee that was the highest the Canaries have ever received for a player. It goes without saying that Buendía will be very difficult to replace. Which brings us to the squad additions. So far there’s been three key moves, the first being what looks to be Buendía’s replacement: Milot Rashica. Rashica doesn’t represent a direct like-for-like exchange and his signing backs up the theory that Norwich will emphasise attacking transitions this season. Signed from relegated Bundesliga club Werder Bremen, Rashica’s attacking versatility could make him an important player for Norwich this season. He’s predominantly a wide attacker, but has also spent time leading the line and in deeper central positions across his 3.5 Bundesliga seasons. Last season he put up reasonable shot (2.4 per 90) and dribble (2.5 per 90) volumes on a relegated side, and a defensive work rate is also visible in the data, particularly in previous seasons. The second and third key moves are that of Billy Gilmour, signed on a season-long loan from Chelsea, and Pierre Lees Melou, who arrives from OGC Nice in Ligue 1. Gilmour’s burgeoning reputation makes his signing regarded as a bit of a coup. It’s highly likely Farke’s existing relationship with Thomas Tuchel – Farke was Dortmund II manager while Tuchel was there as first team manager — played a key role in securing his signature, but Gilmour should be well suited to Norwich’s play as well, his technical ability should help to speed up those transitions through the midfield. Though the club still retains an interest in taking Championship Team of The Year entrant Oliver Skipp on loan from Tottenham again, the signing of Melou does add defensive reinforcement to the midfield. Curiously, Melou only moved into the professional game at the age of 22, jumping from France’s 5th tier to join Dijon in Ligue 2 in 2015, the equivalent of graduating from the National League to the Championship in one step. He switched to Nice after one Ligue 1 season with Dijon and has been a regular in the French top tier ever since, making 151 appearances over five seasons. Besides the years of experience in a top European league, there’s lots to like about Melou’s profile. Given he’ll be at the centre of Premier League midfield battles, an ability to play under pressure is essential, and it appears as though he should be capable of doing that: Melou’s Pressured Pass Completion % of 85% was the same clip as his regular, unpressured pass completion %. Norwich will also be looking for a defensive contribution from their new midfielder, and this is where it seems the Frenchman will excel. Melou was one of the most active defenders in Ligue 1 last season; compared to all central midfielders in the league, he ranked 12th for possession-adjusted tackles and interceptions. All in all, if he can translate these performances to the Premier League, this looks like it could be a very clever bit of business at the reported £3.5m fee. Projection The bad news is the sale of Buendía, but the good news is that there’s a strong sense that Norwich come into this Premier League season better prepared to make a good fist of avoiding relegation than the last time they were here, even without Buendía. Farke and co. will be under no illusions that this will likely be another season of struggle, but it feels as though everyone at the club is richer for the experience of the 2019/20 season, and arrive ready to fight smarter in this campaign. The points spreads are backing them to beat their points tally from last time with the line set at 36.25, a total that makes them 2nd favourites to go down but one that also puts them within range of their relegation rivals and well capable of survival. It’s a challenge no doubt, but Farke’s men ride again.  


Want to read about another team? The rest of our Premier League season previews can be found here If you’re a club, media or gambling entity and want to know more about what StatsBomb can do for you, please contact us at Sales@StatsBomb.com We also provide education in this area, so if this taste of football analytics sparked interest, check out our Introduction to Football Analytics course Follow us on Twitter in English and Spanish and also on LinkedIn

Read more about how StatsBomb data supports the internal processes and workflows at clubs and organisations around the world.

One of the major benefits of using StatsBomb data is the ease at which it can fit into existing systems and infrastructures within data and analysis departments.

Our two main products are the raw event data and our analytics platform, StatsBomb IQ. The event data allows for research, analysis, and modelling on a large-scale basis, whilst IQ packages the data into a quickly digestible and visual format. One of the most valuable features of the product is the IQ API.

The IQ API makes it easier to work with StatsBomb metrics in an automated fashion. All the data that can be viewed in IQ – either in the Team/Player stats tables or in IQ Scout – can be pulled directly into the user’s software without the need to download a CSV and import it first. Crucially, it saves analysts time and forms a part of an efficient workflow: everything that IQ was designed to be.

Not only does this make the process much faster and automated, but it also allows the user to customise and filter the metrics as much as desired, without having to do it from within StatsBomb IQ. You can even create new metrics of your own by working with the ones we offer, should you want to.

There are a total of three APIs as part of the overall IQ API:

Player Match – provides stats for all players in a given match. This match-by-match data makes it easy to perform post-match analysis with the most detailed and contextual event data available. We know some customers prefer to create their own bespoke match reports rather than use the ones provided in IQ: this API allows them to do that

Player Season – services per 90 aggregated data for all players in a league season. These are the same stats that are available in our league-player, squad, and IQ Scout pages

Team Season – supplies aggregated per game data for all teams in a league season. Containing the same metrics as those found in the Team Stats page in IQ, plus some new ones, these metrics allow the analysis of a team’s performance in their relevant competition

StatsBomb Director of Football James Yorke said: “The IQ API is a quality-of-life addition that makes our customer’s lives significantly easier, and allows for the interaction between the end-user and the IQ platform to be automated. This means the customer’s analysis and reports can be updated at the click of a button, pulling StatsBomb data directly into their software and platforms to allow quick and easy analysis of their team or players performance.”

Users can access the API through the StatsBomb Data Hub, where documentation detailing the names and definitions of the metrics provided can also be found.

If you’re a football club or organisation and would like to speak with us about how StatsBomb data and services can enhance your operation, get in touch today.

The StatsBomb Team

The eagerly anticipated, StatsBomb Live data set is about to launch. Engineered by the same experts, with the same commitment to accuracy and quality, StatsBomb Live brings the best of StatsBomb, but now in a real-time format. Save the date for August 12th, where you can expect a first look at the exciting features that make up this game-changing new product. The online event will cover:

  • Exclusive insight as to how StatsBomb Live was designed and created, keeping customer feedback central to decision making processes
  • Meet the team who brought the StatsBomb Live product to life and hear about how they have tackled the challenge of balancing speed with quality in a real-time environment
  • Sneak peaks as to how StatsBomb Live clients will be able to access, analyse and visualise this exciting new data set

This completely unique product offering is perfect for those who need to analyse the highest quality football data, in real-time. Be sure to tune in to see how StatsBomb Live can work for digital media, broadcasting, betting and gaming and professional football. Join StatsBomb’s co-founder and COO, Charlotte Randall and many other key members of the StatsBomb Live team on August 12th to find out more. Everyone is welcome, all you need to do to register for this free online event is sign up here. We can’t wait to see you! And to book in for your free StatsBomb Live demo, please contact: sales@statsbomb.com

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 (7th of 8)
  • xG/shot (1st of 8)
  • Shots (8th of 8)
  • Counter Attacking Shots (8th of 8)
  • High Press Shots (8th of 8)
  • Box Cross % (8th of 8)
  • Pace To Goal (7th of 8)
  • Directness (7th 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 (2nd of 8)
  • xG/shot Conceded (2nd of 8)
  • Shots Conceded (4th of 8)
  • Counter Attacking Shots Conceded (1st of 8)
  • High Press Shots Conceded (3rd of 8)
  • Clear Shots Conceded (1st of 8)
  • PPDA (6th of 8)
  • Defensive Distance (3rd of 8)
  • Aggression (3rd of 8)
  • Pressures In Opposing Half % (3rd 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 (3rd of 8)
  • Shots per Indirect FK (4th of 8)
  • Shots per Corner Conceded (4th of 8)
  • Shots per Indirect FK Conceded (3rd 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 (3rd of 8)
  • xG/shot (5th of 8)
  • Shots (3rd of 8)
  • Counter Attacking Shots (2nd of 8)
  • High Press Shots (1st of 8)
  • Box Cross % (3rd of 8)
  • Pace To Goal (2nd of 8)
  • Directness (1st 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 2nd-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.

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 (3rd of 8)
  • xG/shot Conceded (5th of 8)
  • Shots Conceded (3rd of 8)
  • Counter Attacking Shots Conceded (6th of 8)
  • High Press Shots Conceded (4th of 8)
  • Clear Shots Conceded (6th of 8)
  • PPDA (2nd of 8)
  • Defensive Distance (2nd of 8)
  • Aggression (7th of 8)
  • Pressures In Opposing Half % (4th 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 2nd 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 3rd-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 3rd-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 2nd-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 4th-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 2nd-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 4th 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 3rd-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-2nd 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 57th minute, creating just three shots afterwards and the last of which in the 74th minute. And it was even more extreme vs Czech Republic, taking the lead in the 12th 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 (16th of 16 group stage qualifiers) compared to Germany’s 40 (1st). 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 21st 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 Pedro Picchioni and Rodrigo 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.”