Valencia in Transition

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Using STATS Playing Styles and Advanced Metrics to Show How Marcelino’s Valencia are Employing an Effective Counter Attack to Return to Spanish Relevance

Marcelino couldn’t contain his excitement and pulled up short with a hamstring problem after Simone Zaza scored a late winner against Real Sociedad in late September. The injury was of little concern to his club for at least a triad of reasons.

  1. Marcelino, 52, is Valencia’s manager, and no part of a professional football match has hinged on the performance of his legs since 1994.
  2. It was overshadowed by the fact that it gave Valencia yet another result to sway detractors amassed over the past two seasons back in their favour.
  3. This was hardly an exceptional occurrence. Marcelino, as a manager, once injured himself taking a seat for a presser.

It’s unsurprising to see Marcelino competing for the celebratory spotlight with his players in his first season with the club, though he’s said he recognises the need to tone down his touchline merriment. Given the past two campaigns, it’s of greater note that Valencia have had so many such opportunities through their first eight matches with the excitable man in their coach’s box.

Using STATS advanced metrics, we can show his players might need to reciprocate and go crazy for their new manager once in a while, even if he’s being particularly unpredictable when determining whether he’ll include each of them in his starting XI. Eight different lineups in as many fixtures might seem as erratic as the manager’s touchline fervor, but there appears to be something of a method behind it. We’ll get back to that in great detail on team and individual levels.

First, a bit on why Valencia’s strong start matters.

It wasn’t as long ago as it may seem that clubs outside of Madrid and Barcelona won the Spanish top flight. The last were Valencia in 2003-04 and ’01-02, and before that Deportivo La Coruña in 1999-2000. Modest success hasn’t eluded Valencia since. European football had been an expected part of the gig at Mestalla until recently. But there’s no arguing the past two campaigns in which supporters have endured successive 12th-place finishes – their first in the bottom half since 1987-88.

Los Che now find themselves second in the table as one of three unbeatens in what’s arguably Europe’s top league. The other two – Barcelona and Atlético Madrid – have reached at least the quarterfinals of the Champions League for the past four years.

So how do Valencia find themselves back up in the early-season mix for direct Champions League qualification? It’s not for a lack of competition. Quite the opposite, in fact, and it could be argued Valencia’s early-season fixtures have been as demanding as any Spanish club. Four of their eight league matches have come against clubs playing European football. That injury-inducing match came away to Sociedad a week before the same 3-2 scoreline played out in less-exciting fashion at home against Athletic Bilbao, Sociedad’s Europa League contemporary. But those victories bury the lede of quality draws in Marcelino’s second and third matches with the club.

Valencia left the Bernabau with a 2-2 result against the reigning European and Spanish champions after holding a lead into the 83rd minute, then followed the first international break with a scoreless home draw with Atlético.

Most recently was Los Che’s chaotic 6-3 win Sunday at Real Betis, who remain in the top half of the table.

So what’s changed from a season ago? A bit of everything. The manager, of course. Players. Players’ efficiency. Method – and that’s where we’ll begin by calling upon STATS Playing Styles before going more granular with advanced individual metrics.

Last season, Valencia went through four different managerial periods and three different bosses – Pako Ayestarán until Sept. 20, club ambassador and longtime centre back Voro González for the next eight days, Cesare Prandelli from Sept. 28-Dec. 30, and the ever-present stopgap Voro again until the end of the season. In terms of style, that unsurprisingly amounted to very little differentiating from La Liga averages:

Valencia’s 2016-17 playing styles measured against La Liga averages (0%).

They played more of a fast-tempo game than much of the league, but they didn’t sustain threat when doing so and were rather blasé in all other areas. What followed was a minus-9 goal difference for their worst mark since ’07-08 (-14) when Los Che finished 10th.

Through eight matches this term, there’s still not some overhaul of telling possession-based attacking styles that typically signify a dominant club – they rank 16th in possession at 45.3 percent, which is lower than last season (48.3 percent). It’s unsurprisingly a drastic departure from other top teams in the table. Barcelona are first (61.2 percent) and Real Madrid are second (60.6). But there is order to how Valencia score goals. It’s frequently about transition:

Valencia’s 2017-18 playing styles through eight La Liga matches measured against league averages (0%).

That plus-55 percent counter attacking style against the league average leads La Liga – yes, ahead of even counter masters Real Madrid (+37 in second). Among the top-five European leagues, only Benevento in Italy are countering at a higher percentage against their league average. Anyone familiar with the Italian table then jumps to a logical question: Why are Valencia succeeding and Benevento the clear-cut worst side in Serie A with eight losses and a minus-17 goal difference?

The answer is probably that counters ending with a striker tripping over the ball don’t mean much. The Serie A newcomers have had 59 possessions with a counter attacking value of at least 50 percent, and it’s amounted to two goals. And they spend far more time defending, as is evident by their overall style, so they’re not exactly creating chances in other tactically sound ways:

Benevento’s 2017-18 playing styles through eight Serie A matches measured against league averages (0%).

Valencia, meanwhile, are effective in their counter – more effective even than Real Madrid. Among Los Blancos 48 possessions on which their counter attacking style is of a value of at least 50 percent, they’ve scored once. Valencia have 53 such possessions and four goals after scoring eight goals off the counter all of last season.

All of this must originate somewhere, and that’s where counter attack regains come in. Last season, Valencia were 13th in La Liga in regains to begin a counter attack (154). That trailed leaders Real Madrid by 70, so nearly two per match. Their counter attack distance covered (8,705 metres) – made up of the total of counter attack distance carried and counter attack distance passed – ranked 14th. This season, they’re first in regains (53) and distance (3,171 metres) – more than a third of the way to reaching last season’s marks.

There are more reasons transition works for one club and doesn’t for another. To measure the efficacy of the correlating defensive and midfield play, we’ve got to get beyond simple sums. We showed last week how Kevin De Bruyne has been one of Europe’s most dominant offensive players, despite having a comparatively limited direct involvement with goals and assists. We did this with STATS’ ball movement points. BMP is a metric that considers every involvement a player has in a possession to credit or discredit decisions with the ball and reward creativity. It’s what football minds could always see but never quantify. It goes beyond expected assists by looking at the full chain of passes and weighs the probability of that pass leading to a shot later in the play. Passing points generate expected shot points, so if a player generates one BMP, he’s generated passes to lead to – or defend – one shot.

Yeah, that’s ambitious. So how is this done? The process is measured and assigned objective value using machine learning and massive amounts of historical league data to express the level of threat or wastefulness that can be attributed to a player. It’s broken down into categories of offensive and defensive as well as positive and negative with net values telling the more conclusive story.

There’s dBMP+, which measures how many created chances a defender prevents – breaking up attacks in important situations. There’s dBMP-, which measures liabilities in possession – giving the ball away in dangerous areas. Combine that for net dBMP. While Benevento sit in the bottom half of Italy with a 0.13 dBMP rating, Valencia (0.27) lead Spain. So we’d previously established with playing styles that Benevento are spending a lot of time defending, and dBMP helps us show that they’re not making great decisions with the ball when doing so. Valencia might not be the most attack-minded club in Spain, but they’re at least effective in their own half. That might not matter quite as much for ball-dominant clubs such as Barcelona. It absolutely does for sides that have to pick their attacking moments judiciously.

So on the pitch, who specifically is to reward for executing the system Marcelino seems to be implementing?

We’ll start with the sexy goal-scoring numbers from a striker mired in that special brand of Italian sorrow this time last year for his happenings with club and country.

Zaza scored six goals in 20 matches in his time with Valencia last season and has passed that already this season with seven and three winners. With six goals in his last four matches, he seems a healthy distance from his Euro 2016 penalty miss for Italy and his disappointing spell with West Ham United. The numbers back that up with the 26-year-old ranking in the top five in Europe’s top-five leagues in finishing with an expected goal differential of plus-3.5 among a pretty elite group a season after posting a minus-1.9 xGD. Notice than in Spain, he jumped this past weekend ahead of even a guy named Messi:

As we noted before with ball movement points, midfield play has a lot to do with Valencia’s success, and that’s true on an individual level as well. Bringing in on-loan Geoffrey Kondogbia from Inter Milan as a central presence might have displaced 20-year-old Carlos Soler some after the latter became a mainstay in the middle last season, but it seems to be working out for Marcelino. Kondogbia, who’s attracting attention from top Premier League clubs, ranks second among all midfielders in Europe’s top-five leagues in dBMP, and he’s one of three to really distinguish himself from the pack:

Valencia don’t quite make the same use of the corresponding playmaker guiding a dangerous attack at the other end. Their top-ranked player in oBMP among the top-five leagues is Dani Parejo tied for 29th, but when filtering that down to only La Liga, it’s good enough for fifth among a star-studded top 10. It’s rather impressive when considering the opportunities and surrounding creatives much of the rest of this list has to work off of:

(Graphics by Stephan van Niekerk)

Bored yet? OK, let’s talk goals again. We can’t forget about Rodrigo, who scored five goals in 19 La Liga matches last season and was an objectively mediocre finisher with a -0.6 xGD. He was with Spain as they wrapped up qualifying last week for reasons that go beyond David Villa nearing 36 years old. Rodrigo has scored in five straight matches for the club and also got one in his start against Albania on Oct. 6. Although none for Valencia have been match-winners, he has compiled early-season efficiency (+1.6 xGD) to show he’s not exactly feasting on scraps.

Finally, goalkeeping. Neto, who spent the past few seasons behind Gianluigi Buffon at Juventus, has a +2.1 expected save differential, which is calculated by subtracting expected saves from saves to show how a keeper is performing against league averages. That mark ranks sixth in the division and, you guessed it, is better than his former mentor Gigi (+0.7). It’s not quite the level of Pau López (+6.2), Jan Oblak (+6.0) and Guaita (+5.3), but the Valencia keeper is still going above and beyond from time to time. It’s also important here to consider that Valencia aren’t leaning on him to continually bail them out in an unsustainable way.

So Valencia have a manager pushing for some consistency in style, and he has players making it happen at various levels that we’re now equipped to properly measure. That’s what it takes to earn 18 points in Spain through eight matches, three of which have been draws and another three being one-goal victories. But this is La Liga, home to the two most dominant clubs in the world in recent years. Recall Real Madrid’s Spanish-record unbeaten run of 40 in all competitions ending in January. Barcelona notched 39 in 2015-16. Is it right for a club that’s won domestic titles of its own to make much of this just yet?

Given the circumstances of the past two seasons, it somehow feels right for Marcelino to stick with those celebrations.

The Daring Process of Kevin De Bruyne

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How STATS Ball Movement Points Show Manchester City’s Midfielder Has Been the Most Dangerous Creator in Europe This Season

Kevin De Bruyne’s 67th-minute strike in a 1-0 win at Stamford Bridge wasn’t just an aesthetically impressive example of fast-tempo football – it was arguably the most important goal to be scored in England so far this season. It distanced Manchester City from title holders Chelsea entering the international break and gave the 26-year-old his first Premier League goal of the campaign against the club that sent him to Wolfsburg.

That finish, as pretty as it was, isn’t the main reason we should praise De Bruyne’s efforts for the Premier League leaders.

Even in that six-match goalless stretch to start the season, you weren’t going to hear many supporters complaining about De Bruyne’s form the way one might if Sergio Aguero went through such a drought. Nor will you in the week following his inclusion in the Ballon d’Or 30-man list, from which fellow City creative David Silva is somehow once again conspicuously absent.

De Bruyne has been directly involved in four of Manchester City’s 22 Premier League goals. His goal – which featured the Messi-esque combination of build up and finishing inclusions from a pretty one-touch layoff to Gabriel Jesus before getting it right back on the run for a two-touch 20-yard left-footer to the upper corner – and three assists works out to an 18 percent involvement from the goal-and-assist perspective. It’s not a particularly high rate, and on a personal level, it’d be his lowest in three seasons with City.

But that’s precisely why KDB’s start to the 2017-18 season can act as one of the most relevant contemporary examples of why there need to be better metrics in football. Now settled into a deeper central position after the tinkering Pep Guardiola went through with his creatives in his first season in charge, De Bruyne is still generating all sorts of threat. He’s always been the type of creative midfielder who gains praise for his passing ability and his field awareness. He makes work difficult for defensive players with his precision, and his ball movement is rarely lacking ambition. It’s now measurable with ball movement points, which reward the process in a way traditional binary metrics such as successful passes fall short.

And, through seven matches, BMP shows the Belgian has evolved into the most dangerous playmaker in Europe with his globally overlooked club teammate not far behind.

First, a quick rundown on BMP, which we’ve used a few times before when discussing transfers and how key players are contributing to the top-five European leagues. BMP is a metric that considers every involvement a player has in a possession to credit or discredit decisions with the ball and reward creativity. It’s what football minds could always see but never quantify. It goes beyond expected assists by looking at the full chain of passes and weighs the probability of that pass leading to a shot later in the play. Passing points generate expected shot points, so if a player generates one BMP, he’s generated passes to lead to – or defend – one shot.

Yeah, that’s ambitious. So how is this done? The process is measured and assigned objective value using machine learning and massive amounts of historical league data to express the level of threat or wastefulness that can be attributed to a player. It’s broken down into categories of offensive and defensive as well as positive and negative (oBMP+, oBMP-, dBMP+ dBMP-) with net values telling the more conclusive story.

Got it? Good. Back to KDB.

First, the basics. In 2015-16, his seven goals and nine assists among Man City’s 71 goals amounted to 22.5 percent involvement. Last season, his six goals and 18 assists out of 80 Man City league tallies amounted to a 30 percent involvement. At that level, this season’s inclusion looks like a regression.

It’s not. While Guardiola experimented last season, De Bruyne’s 7.62 oBMP still managed to place second in England behind Mesut Özil (9.00). The season before, Manuel Pellegrini’s last, his 4.14 oBMP ranked 16th in England, and that came behind teammates Yaya Toure (4.82 in eighth), Silva (4.60, 10th) and Fernandinho (4.32, 13th). Özil (10.95) led then as well. For the sake of comparison, La Liga’s leaders last season were Lionel Messi (7.52) and Toni Kroos (5.97).

Onto the current term. It’s of course very early in the season and this is a tight pack, but now consider this season’s oBMP rankings across Europe’s top-five divisions in league play. Of the top 20, 11 are midfielders, and plenty don’t have the goals or assists to display their true value:

(Graphics by Stephan van Niekerk)

De Bruyne is leading, but he’s also the only player to separate himself from the next best player by any considerable sum. Project that 2.29 mark out over a 38-game season, and he’s looking at a 12.44 oBMP that cruises past his own marks from the past two seasons and even Özil’s. And right behind him is his teammate, who again hasn’t been given any love by the Ballon d’Or brass despite consistently creating on elite levels among the world class.

It follows that these players must have a pretty impressive oBMP+, meaning they are ambitious and effective with ball circulation in the attack – they find the channels and play a mean through ball, or they consistently deliver that low, bending cross that makes centre backs trip themselves. It also follows that they may have a considerable oBMP- because of the number of chances they have to craft opportunity, but they’ve got to limit that to exist as a leading creative player. For example, Alexis Sanchez ranked fourth in oBMP+ last season (10.66) but first in oBMP- (-5.01), so his wastefulness drops his net oBMP (5.65), which was not only a considerable margin behind teammate Özil but also Arsenal midfielder Granit Xhaka (5.92).

Now keep in mind BMP does not take into account finishing, which STATS quantifies by calculating expected goal differential (subtracting expected goals from actual goals). That’s where players such as Radamel Falcao (plus-5.8), Paulo Dybala (+4.7), Ciro Immobile (+3.5), again Messi (+3.4) and Mathew Leckie (+3.1) have distinguished themselves this season.

Maybe you can see where this is going. We’re going to write more in the coming weeks and take this a step further by quantifying the value of overall offensive contribution. But when you focus solely on the process of getting the ball to those finishing players in positions to succeed, right now there’s been no better creative than De Bruyne.

Styles of Their Own: How Deep Data Differentiates the Best of Europe’s Best

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Assessing the Leaders of La Liga, Bundesliga, Serie A, Premier League and Ligue 1 with STATS Playing Styles, Expected Goals and Saves, and Ball Movement Points

The tables will tell you the five leaders of Europe’s top leagues all have goal differences between plus-17 and 19 through six or seven matches, but the brand of dominance with which they’ve arrived there varies. With Champions League fixtures occupying midweek, let’s look into the tendencies of Barcelona, Manchester City, Paris Saint-Germain, Borussia Dortmund and Napoli in league play using STATS’ advanced metrics.

We’ve talked about playing styles and expected goals and saves plenty. Ball movement points less so. BMP is a nifty metric that rewards creativity, going beyond expected assists by looking at the full chain of passes and weighing the probability of that pass leading to a shot. It measures the process and assigns objective value using machine learning and massive amounts of historical league data to calculate the level of threat a player creates.

Unsurprisingly, a few of those players suit up at Camp Nou, though Europe’s most dangerous creatives so far this season operate elsewhere. Read on for the details.

La Liga – Barcelona

Barcelona’s 2017-18 playing styles through six La Liga matches measured against league averages (0%).

A matter of weeks ago, the departure of Neymar and a 5-1 aggregate loss to Real Madrid in the Spanish Super Cup sent the Catalans – or at least their supporters – into something of a panic. Take into account they didn’t land Philippe Coutinho and their summer splash Ousmane Dembele will be shelved for at least three months, and on the surface it seems it should be Barca and not Real Madrid seven points back in La Liga. Instead, the Blaugrana rolled Juventus in the Champions League and have a plus-18 La Liga goal difference.

Yes, Messi has nine league goals in six matches. Yes, he’s outscored 14 of the 20 La Liga clubs. Yes, his 22 shots on goal are nearly half of the team’s 45, and his total either matches or betters the team total of seven La Liga clubs. But Barcelona didn’t need him to net in a 3-0 win at Girona over the weekend. The success might have something to do with a relatively healthy Andres Iniesta and impressive play out of fellow midfielder Ivan Rakitic, who leads La Liga in offensive ball movement points (oBMP) with a 1.10 rating. Messi ranks second (1.05) ahead of Real Madrid’s Toni Kroos (0.98).

Make no mistake that this isn’t the Barcelona midfield of 2009, but they are operating with impressive tempo to complement their typical sustained possession. It’s only six matches, but they’re so far playing faster this year than they did with Neymar. Their fast tempo playing style is up from 154 percent above league average last season to +212 so far this term. In typical Barca fashion, they played directly less than any La Liga club last season (-40 percent). That’s barely changed (-34). Anyone they replace Neymar with won’t match his on-pitch value, but it’s becoming clearer that he wasn’t Barcelona’s engine. We’ll see if that changes with more demanding matches on the horizon, which is the case for all five clubs discussed here.

Premier League – Manchester City

Manchester City’s 2017-18 playing styles through six Premier League matches measured against league averages (0%).

No surprise here. Pep Guardiola assures us that this hasn’t already turned into a two-team race with his Manchester rivals, but that might just be coach speak. It may have been between those two all along, as we wrote before the season started. That argument was based largely on expected goals and saves, and a lot of that is playing out as the numbers implied it might. Take note of Ederson, who’s made more saves than expected. His plus-1.5 expected save differential – calculated by subtracting expected saves from actual saves – ranks just ahead of Gianluigi Buffon.

Assess City’s playing styles through six matches, and you’ll see plenty of evidence of the kind of big-money dominance they’re going to be capable of in Guardiola’s second season. Their offensiveness has increased from 45 percent above league average to +81, while maintenance – possession in one’s own half – has slightly decreased (+42 percent to +39). Attacking possession styles of build up (+69 to +102), sustained threat (+48 to +77) and fast tempo (+64 to +172) have all jumped along with crossing (+18 to +50). It’s a dangerous team that’s made up of dangerous individuals.

The same case can be made using ball movement points, but the most noteworthy players in that category aren’t Man City newcomers. Kevin De Bruyne might not be scoring, but his oBMP (2.03) is considerably higher than any player in the top-five European leagues with teammate and fellow playmaker David Silva (1.53) ranking second. The only other duo anywhere near that level isn’t the previously mentioned Barca duo, though one of the players famously moved from Catalonia this summer.

Ligue 1 – Paris Saint-Germain

Paris Saint-Germain’s 2017-18 playing styles through seven Ligue 1 matches measured against league averages (0%).

Since he’s already come up in the sections above covering two teams he doesn’t play for, let’s get to Neymar. Heads would soon roll if any other club were listed here after the summer PSG had. Any Neymar-Edinson Cavani penalty rift – perceived or otherwise – isn’t impacting their dominance. But the oBMP duo teased above wasn’t them. It’s Thiago Motta (fifth: 1.35) and Neymar (seventh: 1.27) among the leaders of Europe’s top-five leagues. Kylian Mbappe is settling in and staying out of the goal-scoring diva antics, but let’s focus on playing style because Paris have, essentially overnight, started challenging Barcelona as Europe’s most ball-dominant attacking club.

Their build up (+86 percent in 2016-17 up to +165), sustained threat (+48 to +111) and fast tempo (+115 to +238) have all spiked this season, while their direct play (-46 to -62) has fallen off even more. The same goes for maintenance, which has fallen from +89 of the average to +59. That all points toward that front three and the accompanying midfield having the ball in attacking circumstances. They’re making dangerous decisions when they do: Motta, Neymar, Adrien Rabiot (1.15) and Marco Verratti (1.05) make up four of Ligue 1’s top six in oBMP.

This version of PSG dropped points for the first time over the weekend with a goalless draw at Montpellier. Neymar, of course, didn’t play. Assuming he’s quickly back and healthy for the months to come, it’s hard to imagine any scenario other than this dominant of a Paris side taking back the title from depleted holders Monaco.

Onto another potential changing of the guard.

Bundesliga – Borussia Dortmund

Borussia Dortmund’s 2017-18 playing styles through six Bundesliga matches measured against league averages (0%).

It’d be easy here to argue that Bayern Munich are leaving the door open for Dortmund to capture their first title since 2011-12, but that might be taking due credit away from the challengers. Of the five clubs discussed here, Roman Burki has provided the most valuable goalkeeping, ranking 12th among the top-five European league keepers in expected save differential at +2.8 between Inter Milan’s Samir Handanovic (+2.8) and Manchester United’s David De Gea (+2.5).

Surprisingly, Sokratis Papastathopoulos’ 1.29 oBMP is the highest any defender in the top-five leagues and leads Bundesliga players of all positions. They’ve also had some efficient finishing. Pierre-Emerick Aubameyang’s +2.1 expected goal differential is third in the Bundesliga, while Maximilian Philipp’s +1.8 is fifth. It’s of course a slippery slope to lean on such individual efficiencies, but these cases aren’t anomalies. PEA posted a Bundesliga-best +6.1 xGD last season, while Philipp’s nine goals with Freiburg came in a relatively impressive +2.6 above his expected mark of 6.4.

In terms of playing style, Dortmund have gone away from the high press some (down from +26 percent last season to +7), while increasing significantly in build up (+58 to +125) and fast tempo (+67 to +174). Their counter attacking has also increased from +19 to +41, which puts their playing styles web almost eerily in line with this week’s Champions League opponents Real Madrid.

Give Dortmund credit for their start, but another dark-horse club has gathered even more hype across Europe.

Serie A – Napoli

Napoli’s 2017-18 playing styles through six Serie A matches measured against league averages (0%).

We’ve saved the most intriguing – and possibly most exciting relative to their league – for last. Napoli may be the outliers on this list because they haven’t won a title since a guy named Maradona was around 1989-90 and Juventus have won the Serie A every season dating to 2011-12. And unlike other clubs on this list, they haven’t compromised their style or spent untold millions to jump in front of Juve on goal difference through six matches. That comes as a relief to plenty of the football world that sees manager Maurizio Sarri as one of the key names in pushing the modern game forward. As was pointed out in a recent ESPN FC piece, Fabio Capello boasted Sarri as an innovator on the level of 1970s Ajax, 1980s AC Milan and 2000s Barcelona. Pep Guardiola had a hand in the last of those and called Napoli one of the three best clubs in Europe back in August when Man City drew them in the Champions League group stage.

Napoli are highlighted by a rather un-Italian attack that’s scored more league goals than any club in Europe’s top-five leagues, including that explosive PSG side that’s played an additional match. How, specifically, are they doing it with a player payroll that ranks fifth in Serie A? Pace and press are key parts. In fact, Napoli might play as fast as any club on the planet. They don’t sustain threat like other clubs on this list (+13 percent of Serie A average last season and +10 this season), but their fast tempo (+265 up from +231) and high press (+78 up from +44) are increasing from already head-turning numbers last season.

On an individual level, Sarri is well aware of Lorenzo Insigne’s value, and that’s supported by a 1.19 oBMP that trails only Juve’s Miralem Pjanic in Serie A. What’s scary – or enthralling – is Napoli have only recently found the No. 9 to head this monster up. Dries Mertens has six goals with a +2.3 xGD, and that’s not a matter of the Belgian finding a streak of luck to start the campaign. He scored 28 goals in 35 matches last season with Serie A’s second best xGD of +6.9. It has, with little doubt, something to do with the system.

Long Live the High Press: The Subtle Adaptation of Premier League Newcomers Huddersfield Town

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Assessing the Terriers’ First Three Premier League Matches in Comparison with Their 2016-17 Championship Season Using STATS Playing Styles, Ball Movement Points and High Press Regains

Before anyone gets too excited here, let’s acknowledge two things.

1. Huddersfield Town are still 35 match weeks away from being 2015-16 Leicester City, which is to say let’s not waste any more time with a serious comparison.

2. Huddersfield Town are still 35 match weeks away from being 2016-17 Hull City, who won two of their first three matches before managing 28 points in the next 35 games on their way to deserved relegation with a Premier League-worst minus-43 goal difference.

But lumping the Terriers in with Hull might be more irresponsible than any comparison with those fantastic Foxes. The unsexy truth is Huddersfield likely fall somewhere between, which hardly warrants this level of attention. What does deserve acknowledgement is the tactical competence of a relatively unknown club that spent the past 10 seasons split between second- and third-tier football.

The Terriers represent a community trapped in a triangle of Manchester, Leeds and Sheffield in northern England and play at the aptly inconspicuous grounds of 24,500-seat John Smith’s Stadium. They arrived last month seeming to have an idea of how they’d like to play in the top flight, which we’ll show below. More so, they already seem comfortable implementing it, despite it being in some ways a significant departure from a more possession-based Championship system of last season that earned them their first top-flight campaign in 45 years. In short, the influence of another German manager in the Premier League on Huddersfield boss David Wagner is already showing, which we’ll get back to.

First, the cautionary tale of Hull. Take a deep look back at their start last year, and you’ll see the Tigers got those initial six points with plenty of direct play and possession in their own half (maintenance). They didn’t counter, their high press was lowly and their possession-based styles in attack (build up, sustained threat, fast tempo) were essentially nonexistent:

Hull City’s 2016-17 playing styles through three matches measured against league averages (0%).

That held true over the course of the season with maintenance and direct play as the only two areas they operated above league averages. It’s hard to say that amounts to a system of note, and it caught up to them. Their 80 goals against were the most in the Premier League since Fulham conceded 85 in 2013-14, and it can’t even be attributed to bad luck. Their expected goals against was 83.3, so they actually conceded fewer goals than what would be expected under league average circumstances.

But the data-driven story of Huddersfield’s seven points coming out of the international break looks considerably different. On the surface, they’ve played what one could say amounts to an average or below-average schedule. That said, they’re one of two sides (Manchester United) that haven’t conceded. Of the 18 sides that haven’t conceded through three matches in the Premier League era, the average finishing position is 5.3. Only four of those sides have finished outside of the top eight. Manchester City ’07-08 and Portsmouth ’06-07 finished ninth, and Birmingham City ’03-04 finished 10th. But don’t consider Huddersfield in the clear just yet. Charlton Athletic didn’t concede through three matches in 1998-99 and were relegated after finishing 18th.

Wagner is approaching the small sample of success with appropriate caution.

“We are happy with our start (to the season) because of our results, the clean sheets and because of the performances we have put in,” Wagner, the Premier League Manger of the Month, told the club’s official website. “The players can see now that if they follow their ideas and their identity, even in the Premier League, they have a chance.”

What exactly that identity is has shifted some with the climb. Consider last year’s side, which finished fifth and won the playoff for the third promotion spot. Along with Reading and Fulham, they were one of the Championship’s dominant possession-based attacking sides, even if they worked in a high press (they did, and we’ll get to that):

Huddersfield Town’s overall 2016-17 playing styles measured against league averages (0%).

It’s known that Wagner makes fitness a priority, which seemed to translate to widespread tactical and situational success last season to compensate for a minus-2 goal differential. They scored one goal in their last five matches, yet somehow managed to win the playoff.

Now consider this season and the significant departure in possession-based attacking styles:

Huddersfield Town’s 2017-18 playing styles through three matches measured against league averages (0%).

That’s not something Wagner didn’t foresee entering the season.

“We changed sometimes in the last season the style of our game as well,” he said. “When we played Newcastle away, we played slightly different than in other games. So there will be some games in the Premier League as well where we have to maybe slightly change our style. But the idea and our identity will always be the same.”

Their high press style is 52 percent above league average through three matches, which ranks first, but they’re also effective in execution of regaining the ball while pressing. Huddersfield are tied for the league lead in high press regains with a familiar club:

2017-18 Premier League Playing Style Totals

TeamMABUSTFTDPPMDPPDCMCDCADCARHPR
Huddersfield
Town
39728821550130737740712.01316
Liverpool678479246104111826530881.81516
Bournemouth582364228138130596659466.9915
Chelsea60735428987111697153707.71315
Leicester City37317013821140505463615.61115
Tottenham
Hotspur
685663399204778010035949.91415
Everton5702311441121646047581018.31614
Manchester
City
594739462218511119322694.21213
Southampton57747730016391737437760.11313
Watford334198205561465665541029.91713
Arsenal62771035031273956426488.5911
Stoke City33929019185113646754968.11510
Swansea City556226131121135623760479.8810
Brighton and
Hove Albion
54223713869115606356449.699
Newcastle
United
30115916523127666243903.5148
West Bromwich
Albion
24014712433163586759725.9138
Crystal Palace375278166110144706736498.195
Manchester
United
58769741924193748936939.0165
West Ham
United
51320611271134464752412.165
Burnley42119014857151806657645.0104
MA=Maintenance Involvements; BU=Build Up Involvements; ST=Sustained Threat Involvements; FT=Fast Tempo Possessions; DPM=Direct Play Passes Made; DPD=Direct Play Passes Defended; CM=Crosses Made; CD=Crosses Defended; CAD=Counter Attack Distance (Metres); CAR=Counter Attack Regains; HRP=High Press Regains.

Liverpool, managed by Wagner’s mentor Jurgen Klopp and his well-known gegenpressing striving for immediate ball recovery, led that category last season with 199, or 5.2 per match. It’s interesting to at least note here that Hull’s 112 were next to last, and Leicester’s 161 in 2015-16 were five behind leading Manchester United. That might be oversimplifying things, but the only teams to finish in the top six the past two seasons without being above league average percentages in maintenance, build up, sustained threat and fast tempo are Leicester, Tottenham Hotspur and Southampton in 2015-16. Those clubs all operated above the league average high press percentage and ranked in the top seven in regains.

Huddersfield through three matches are just ahead of Liverpool’s per-match pace from last season, but that actually shouldn’t come as too much of a surprise. They led the Championship last season with 217 over 46 matches (4.7 per match).

So while there was a shift in style from the Championship, that’s not to say they didn’t employ a high press last year. They’re not attacking with the ball this season, but they are similarly disrupting. They’ve just had to go about it differently and will have to continue to do so because they’re realistically not going to be a possession-based attacking team anytime soon at this level. That probably means their forwards are doing a bit more work this campaign, but they might have brought in the right attacker to head that up.

They’ve succeeded thus far with much of the same team under the same manager. Ten of the 15 players Wagner has used in their three matches are holdovers from the Championship side, but some key players certainly joined the club over the summer.

There’s Steve Mounie for the obvious reason of scoring twice in his first three games with the club, but he’s also contributed four high press regains. That ranks tied for third in a small sample size, but Mounie was one of 12 players in Ligue 1 last season with double-digit goals and high press regains:

2016-17 Ligue 1

PlayerTeamGoalsHigh Press Regains
Edinson CavaniParis SG3510
Alexandre LacazetteLyon2810
Florian ThauvinMarseille1513
Steve MounieMontpellier1413
Nicolas de PrévilleLille1416
Benjamin MoukandjoLorient1310
Emiliano SalaNantes1215
Lucas MouraParis SG1214
Jimmy BriandGuingamp1218
Loïs DionyDijon1111
Ryad BoudebouzMontpellier1116
Valère GermainMonaco1010
Players with at least 10 goals and 10 high press regains.

He did it for a club that seemed to succeed with a high press. Montpellier operated just three percent above the league average but ranked fifth in regains.

Looking further into individual performance and beyond playing style to quantify Huddersfield’s success, there’s Jonas Lössl with his three clean sheets in his first three with the Terriers, which have come with the keeper outperforming the league average of expected saves. Subtract the former Mainz 05 man’s expected saves from his saves, and his differential comes out at plus-2.3, meaning he’s saved them at least two goals the average keeper wouldn’t. As STATS has written before, goalkeeping was a huge part of Leicester’s dream run.

But there are also holdovers from last year who are properly adapting. STATS has brought ball movement points into analysis, which is broken down into categories of offensive and defensive as well as positive and negative (oBMP+, oBMP-, dBMP+ dBMP-). These metrics use machine learning to assign an objective value to every involvement a player has in a possession to credit or discredit decisions with the ball, measuring how dangerous a player is with ball circulation by relating it to the probability of a shot happening later in that play. Passing points generate expected shot points, so if a player generates one BMP, he’s generated passes to lead to one shot.

Aaron Mooy’s 0.67 oBMP+ ranks 15th in the Premier League ahead of players like Dele Alli, Wayne Rooney and Alex Oxlade-Chamberlain, despite the midfielder having to exist in a very different system. That doesn’t tell the whole story because he, like the rest of the team, is having to defend more than last season. Yet his 0.30 defensive contribution, calculated by adding dBMP+ and expected goals defended, is also interesting to consider. It ranks between noteworthy central presences such as N’Golo Kante (0.35), who we all remember from Leicester, and Nemanja Matic (0.29).

They also only have one player in the top 50 of dBMP-, which is impressive for a club that’s spending a decent amount of time in their own half. Again, these are small sample sizes, but it’s a start.

That’s all those seven points are thus far for the Terriers – a start. So are Huddersfield ’17-18 going to be Leicester ’15-16, Hull ’16-17 or Klopp’s Liverpool?

The answer is probably none of the above. They’ve simply evolved from their former selves, but that might have staying power.

Gylfi Sigurdsson, the Costly Set-Piece Specialist? Maybe Not for Everton

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Using STATS’ Advanced Metrics to Show the Move Presents the Midfielder with a Chance to Prove He Can Be a Playmaker at a Club with a More Possession-Based Style

It’s true that two of Gylfi Sigurdsson’s nine goals last season came on free kicks and three came from the penalty spot. It’s true that of his 13 assists, eight came on set pieces. It’s true that Fernando Llorente is 6-foot-4 and Wayne Rooney is 5-foot-9. It’s also true that Sigurdsson is probably too far into his prime to ever be Mesut Özil.

You’ve read all of this elsewhere in the days after his move to Everton.

But calling Everton’s £45 million signing of Sigurdsson money spent on a set-piece specialist is a bit shortsighted. Dead-ball goals, assists and teammate physique aren’t necessarily the most well-rounded ways to measure whether Sigurdsson will fit in the run of play at Goodison Park. The rest of Swansea’s starting XI didn’t move with him, so it’s necessary to also consider club playing styles he’s more likely to be a part of under Ronald Koeman rather than the Swansea managerial mashup he’d experienced since rejoining the club in 2014-15. It’s also necessary to consider his own distribution aptitude.

First, the highlights. They’re there to suggest Sigurdsson in his mid-20s became the player he rarely was with Tottenham, and they go beyond his Europa League dreamer from 50 yards on Aug. 24 against Hajduk Split. If you haven’t already, do yourself a favour and watch it:

Against Manchester United on April 30 as Swansea scrapped for a much-needed away point to fight relegation, Sigurdsson sets up for a 24-yard free kick in the 79th minute while trailing 1-0, sees a defender leave David De Gea’s line, and immediately placed the ball in the back of the net in the precise position of the departed defender. The Swans got that point because of it.

Against Sunderland on May 13 as Swansea tried to secure safety, there’s Sigurdsson’s long ninth-minute free kick dropped into the box just out of reach of the charging keeper on the head of Llorente to give the Swans an initial lead in a 2-0 final.

From the run of play, there’s his two-touch heal pass to Martin Olsson in the 69th minute to set up an equaliser against Burnley on March 4.

Those are contributions that are obviously identifiable as valuable to anyone with football sense, and it’s now quantifiable. STATS measures players’ team point contribution, which factors in objective value to such plays, much like expected goals. Sigurdsson contributed 5.4 points last season, which was right at his expected points (xP) of 5.5.

What might be more telling here is while Sigurdsson’s point contribution ranked 31st in the Premier League, it accounted for 13.2 percent of his team’s points in matches he played. That wasn’t far behind some pretty impressive names among players who appeared in at least half of a single club’s fixtures, and it was ahead of notable others. It’s also interesting to consider how many of Everton’s transfer window signings were similarly impactful for their clubs last season.

So it’s very possible Swansea would not be a Premier League club this season had he not been there.

But the key counterpoint to his performance in the run of play might be that ball movement metrics don’t speak as well for Sigurdsson as certain elite attacking midfielders. STATS’ data-science team is able to leave behind often-misleading binary metrics of passes completed and assign objective value to distribution based on pass risk and reward.

Similarly, they’ve brought ball movement points into analysis, which is broken down into categories of offensive and defensive as well as positive and negative (oBMP+, oBMP-, dBMP+ dBMP-). These metrics use machine learning to assign an objective value to every involvement a player has in a possession to credit or discredit decisions with the ball, measuring how dangerous a player is with ball circulation by relating it to the probability of a shot happening later in that play. Passing points generate expected shot points, so if a player generates one BMP, he’s generated passes to lead to one shot.

Looking only at his positive offensive involvements, Sigurdsson is impressive, ranking eighth last season among a truly elite bunch of Premier League creatives.

But bring in his negative involvements, and his 3.4 net oBMP levels out considerably to 33rd. Comparatively, he’s nowhere near the top four of Özil (9.0), Kevin De Bruyne (7.6), David Silva (7.6) and Eden Hazard (7.2).

The leaders in those categories, however, at least have an opportunity to play for clubs that attack. Not only do they attack, they attack with possession. This is where things get interesting in evaluating the opportunity before Sigurdsson under Koeman. On one hand, the attacking systems those elite players are a part of makes it impressive that they’re able to limit their oBMP-, meaning they make relatively few adverse decisions with the ball while attacking. On the other, there’s the argument that Sigurdsson’s Swansea surroundings didn’t give him the opportunity to do so.

Everton are not Manchester City or Arsenal, but they also aren’t a club struggling to avoid the drop each April and May. Swansea have been in that defensive role in the table, and it’s reflected in their playing style.

According to STATS Playing Styles, which measure a club’s time spent in specific styles compared to league averages, Swansea operated far less frequently in possession-based styles such as build up (minus-21 percent), fast tempo (-15) and sustained threat (-10).

Everton, meanwhile, were at least slightly above the league averages in all three categories while also counter attacking more frequently.

That might not be a significant enough change to turn Sigurdsson into Everton’s version of Özil. But before concluding Sigurdsson is little more than a dead-ball wiz, let’s first give him a chance to be the playmaking midfielder at a club that operates at or above possession-based norms in the Premier League.

That opportunity could come with the new-look Toffees. It’s less of a long shot than a 50-yard dreamer.

Premier League 2017-18: Manchester’s Rise and North London’s Fall

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How 2016-17 Expected Goal and Save Values Help Illustrate What’s to Come in the Premier League

Either Pep Guardiola has been taking note of some new metrics or his football sense is just that keen. Regardless, the argument can be made that Joe Hart had the last laugh.

For last season, that is.

The goalkeepers Guardiola enlisted over Hart didn’t only fail the eye test as Manchester City fell 15 points shy of the Premier League title in the manager’s first season. Claudio Bravo and Willy Caballero were a measurable problem for Guardiola, and the manager wasted little time rectifying that this transfer window by bringing in Ederson from Benfica.

STATS has refined some of the most advanced metrics in football, and using them gives insight into just how teams measure up against expectations. Expected goal value uses machine learning and historical tracking data to address how likely a goal is based on the location of a shot, the position of the defenders and manner of the attack. Possibly the best way to think of it in terms of how it measures a player’s worth is that it assesses the individual against the league average.

Man City allowed 39 actual goals. Their expected goals against came in at 36.9, and the plus-2.1 differential – meaning they allowed more goals than they should have – accounted for the fourth worst in the league ahead of only Crystal Palace, Watford and Liverpool. The contributions of Bravo and Caballero with expected save differential – calculated by subtracting expected saves from actual saves – was minus-5.7, meaning they did not save nearly six more shots than the average keeping tandem would have. That ranked ahead of only Crystal Palace’s keepers. With Hart featuring the year before Guardiola’s arrival, City were at a perfectly acceptable shade above the league average at +0.1.

That very last line of defense is, of course, not the only area where City spent this summer. The signings of Benjamin Mendy, Kyle Walker and Danilo figure to address any defensive shortcomings for a side that’s dealt with inconsistency and injury even after bringing in John Stones last year. Without even getting into the addition of Bernardo Silva and having Gabriel Jesus for an entire season, those signings may amount to the changes City need to bring Guardiola yet another trophy in yet another league.

If you’re not yet convinced, let’s now consider improvements they could see from within their established attack by surveying Guardiola’s most trusted finisher and his supporting cast.

Sergio Aguero’s -4.1 expected goal differential – calculated by subtracting an individual’s expected goals from converted goals – last season was the third worst in the division, but he was at +3.6 the previous season. He still scored 20 goals last season, and he did so while wasting chances. Of the seven 20-goal scorers from the past two seasons, he’s the only to post a negative xG differential. That’s a class he’s repeatedly been a part of, so it probably follows that he’s quite unlikely to waste as many chances going forward.

Now consider David Silva (-1.9), Raheem Sterling (-1.8) and Kevin De Bruyne (-1.6). Silva was right at that rate in 2015-16 while Sterling was slightly better (-1.0), but De Bruyne’s was +2.5.

If Aguero and De Bruyne get back up to a level we know they’re capable of and City put them in similar situations to score, the tandem could theoretically account for 11 more goals. Add that to the prospective goalkeeping improvement, and City have the possibility for a staggering overall goal differential increase.

But a similar argument can be applied to the attack of City’s closest rivals, who spent big this summer on efficiency they sorely need. If that works out, the managerial rivalry we saw between Guardiola and Jose Mourinho elsewhere could reach maximum velocity in England.

Manchester United’s potential for improved efficiency is enormous

After a 4-0 loss at Chelsea on Oct. 23, Manchester United found themselves five points back of the eventual Premier League champions.

From there, the Red Devils allowed 17 goals in 29 league matches, conceded more than a goal once and kept 14 clean sheets. On paper, that certainly looks like the defensive capacity to give a club every opportunity to make up those points to win the league.

Yet they drew 13 of those 29 matches, lost two and did not traditionally qualify for the Champions League because of it. Their five goalless finals in that time included Old Trafford disappointments with Burnley, Hull City and West Bromwich Albion.

To say Mourinho’s side left points on the pitch is an understatement, but how to quantify it? United’s goals for differential was substantial. Try -16.3, or third worst in the division behind Southampton (-27.6) and Stoke City (-17.2).

Remember, that’s how we quantify finishing measured against the league average. It was a systematic problem of wasting chances with no player posting an xG differential of even +1.0. Jesse Lingard (-3.4), Paul Pogba (-3.3), Marouane Fellaini (-2.8), Zlatan Ibrahimovic (-2.4) and Wayne Rooney (-2.0) were the most responsible parties. Some of those names are gone, but attackers like Marcus Rashford and Antonio Valencia also produced negative differentials.

In this case there seems to be a need to address styles of play. If Mourinho is able to do that and get even average outputs from key attacking players, the shift in goals scored could be significant enough to make United – not City – the team to bring Manchester back to the top.

Now add a new No. 9 to the mix. United’s potential appeal for 2017-18 only increases with Mourinho’s addition of a player who could sway efficiency back in the right direction – if United use him properly. Romelu Lukaku’s +9.9 xG differential might not be sustainable on quite that level, but there isn’t much of an argument against Mourinho having added a finisher who operates at impressive efficiency levels to an attack that’s already bursting with measurable potential.

Lukaku’s xG differential trailed only Harry Kane last season. That begs this question: If Spurs couldn’t win the league last year, is it realistic to think they can now?

Last season might have been Tottenham’s best chance

Tottenham had some of the most quantifiably effective attackers in the Premier League last season, and it goes well beyond Kane.

Kane scored 29 goals in 30 matches, which is impressive enough on its own, even if you normalize the seven goals he scored in two throwaway matches at season’s end. It becomes even more remarkable when considering his 15.7 xG. His league-leading +13.3 xG differential implies he was consistently finishing chances the average player wouldn’t.

He also led the league in 2015-16, but with a considerably lower and more sustainable differential (+5.2). His mark last season was significantly better than next-best Lukaku, and, for comparison’s sake, any of the big names for the Spanish giants. Lionel Messi led in Spain with a +9.3 xG differential, and no one in the Bundesliga, Ligue 1 or Serie A topped that.

It wasn’t just Kane for Tottenham, though it was an alarmingly top-heavy club performance. Spurs scored a league-best 86 goals, which was +17.6 of their expected goals for. But their xGF differential was thanks entirely to three of the top six individuals in expected goal differential being a part of White Hart Lane’s final season. Heung-Min Son (+6.2) ranked fourth and Dele Alli (+5.3) was sixth.

The three scored 61 of the club’s goals despite Kane missing eight matches. Spurs lost none of them and dropped six points, which still wouldn’t have been enough to win the league. The success without Kane hinged heavily on eight combined goals from Son and Alli.

Tottenham’s depth seems questionable and is already under examination with Walker joining City and replacement right back Kieran Trippier suffering a preseason ankle injury that will cost him the start of the season. How Mauricio Pochettino closes the gap between Tottenham and the top with a fully healthy and optimally efficient side is no small question. Consider any personnel concerns that may arise, or any dip in form, and producing the level of efficiency they’d need to win the league seems nearly impossible.

Hugo Lloris’ stellar 2016-17 furthers that point. Tottenham’s expected goals against was 36.0. They conceded just 26, for an xGA differential of -10.0. Lloris and Michel Vorm combined to post the league’s second-best expected save differential with a +10.4 mark, meaning they saved at least 10 goals a league-average keeper would have let by.

For that to be sustainable, Lloris will have to prove Tottenham’s consistent xS differentials of years past – +0.7 in 2015-16, +0.2 in 2014-15 and +1.1 in 2013-14 – were somehow the anomaly rather than the norm.

That’s a glimpse into how Spurs could struggle to entertain Wembley. But even their North London rivals who perform better at those grounds could have similar concerns.

Cech can’t save Arsenal to the top

Spurs’ goalkeeping was great. Arsenal’s was slightly greater, but that has to be of the greatest concern to Arsene Wenger for reasons beyond his No. 1 being on the wrong side of his prime.

Petr Cech helped the Gunners to a league-best +11.7 xS differential, which was the best in the Premier League over the past five seasons.

It’s difficult to see this as sustainable, particularly since Arsenal’s xS differential in Cech’s first season at the club was +4.4. While it should be of some comfort that they added Ligue 1’s most efficient striker in Alexandre Lacazette (+8.3 xG differential) to balance that on the other end, there are further reasons for concern.

Arsenal gave up 44 goals as it was. If we add seven to that, bringing them in line with their 2015-16 save differential, their goals against last season jump to a tie with West Bromwich Albion for eighth at 51. No club in the last 15 Premier League seasons has conceded more than 50 goals and finished in the table’s top four. Put the Gunners at the league average by adding 11 goals to their save differential, and they’re tied with Burnley for 10th in goals against.

And if winning the league is their ultimate goal, Arsenal have a great deal of work to do with a back line and midfield not so dissimilar to last season’s. No club has ever won the Premier League while allowing more than 45 goals.

Maybe that’s where Chelsea finally come in as the London club with the best shot at the title.

A third title in four years?

The Blues conceded 33 goals last season, which was third to Manchester United and Tottenham. That number matters because it was consistent with the club’s expected goals against (31.8). They didn’t have a keeper constantly bailing them out. Their system worked.

The problem for Chelsea comes with scoring, where Antonio Conte got much more last season than his club may be capable of moving forward. Their 85 goals for ranked second to Tottenham, but their +20.6 xGF differential was a full three goals ahead of that previously discussed unsustainable Kane-Alli-Son-powered mark for Spurs. Granted, Chelsea’s productivity was more spread out among attacking weapons, their stability absolutely thrived in a three-back system, and they added Alvaro Morata’s potentially impressive efficiency.

Those three terms – productivity, stability, efficiency – are telling, and they’re more measurable in football than ever. Conte comfortably won a title in his first season at Stamford Bridge by implementing them in impressively quick order.

But that could ultimately mean little this season considering Guardiola’s established plenty of his own.

Can Morata Replicate His Real Madrid Efficiency at Chelsea?

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Let’s start with the positives: Alvaro Morata scored more La Liga goals per minute played than Cristiano Ronaldo and Luis Suarez last season, he required fewer shots per goal than Lionel Messi, and Real Madrid didn’t lose a league match in which he played.

Left at that, Chelsea fans might be thrilled with the idea of a 24-year-old striker who’s already a veteran of Europe’s highest levels lining up in front of Antonio Conte’s midfield. That line of thinking doesn’t properly consider how Morata scored his goals and how he might be asked to finish for the Blues in less conducive types of play. That’s something that can now be quantified with STATS Playing Styles.

On the surface, Morata’s efficiency is hard to not laud. His 15 league goals came at a rate of one every 88.8 minutes, which, among the seven La Liga players with at least 15 goals, was only bettered by Messi (76.5). No one else came close and, for what it’s worth, Antoine Griezmann’s 16 goals required 191.6 minutes each.

The same conclusions can be drawn from Morata’s shooting. He needed just 3.7 shots per goal last season, which was unmatched by anyone with more than 10 La Liga goals – including stars like Ronaldo (6.4) and Messi (4.7).

Getting even more specific by using STATS’ expected goal value metric, Morata was expected to score 10.6 goals. Expected goal value is assigned based on the probability of a goal being scored from the position of the shot. His xG difference of 4.4 was better than not only Ronaldo (minus-1.9) and Griezmann (2.6) but also that of the man he’s replacing – Diego Costa (1.7).

And, most importantly, it resulted in wins. Of the 26 league matches in which Morata saw the pitch, Real Madrid went undefeated and averaged 2.69 points.

All that, yet in the past two seasons Morata has failed to assert himself as a top striker for Juventus and Real Madrid. The why involved here often feels like something a manager sees on the pitch that we can’t always accurately quantify. Again, that’s no longer the case.

There’s some validity in arguing his numbers were better because he was frequently used as a substitute and able to put more effort into his average of 53.9 minutes per appearance than a 90-minute player. However, he scored 11 of his goals in his 14 starts, so there’s something more to it than simply coming on with fresh legs.

His numbers start to come back to the realm of normal when considering nine of his goals came against the bottom six teams in the La Liga table. Then consider that over the last three seasons the bottom six clubs in La Liga have allowed 72 more goals than the bottom six of the Premier League, and Morata’s appeal begins to fall off a bit.

But that’s mostly surface-level stuff. It gets more interesting with club specifics. Here’s why such impressive productivity probably isn’t possible for Morata as a starter in the Premier League.

It can be argued that what makes those elite-level scorers 90-minute players is an ability to score in various playing styles. It’s no surprise that even goal scorers like the diminutive Messi lean on crossing more than any other playing style to score goals. It’s a proven attacking method that will always have its place in football. Seventeen percent of Messi’s shots and 30 percent of his goals occurred in the presence of a crossing style. Ronaldo: 28 percent on shots and 28 percent on goals. Suarez: 22/26. Costa: 33/37.

Morata’s crossing percentages were 44 percent for shots and 52 for goals, which isn’t necessarily a good thing for someone who’s about to change systems.

It follows that his finishing might be limited if he’s not playing for a club that doesn’t distinguish themselves from others in that way.

You guessed it. Chelsea didn’t distinguish themselves from the league when it came to crossing. They were exactly at the league average under Jose Mourinho and Guus Hiddink in 2015-16 and -3 percent under Conte’s league-winning side.

Chelsea’s overall 2016-17 playing styles measured against Premier League averages (0%).

That’d be all well and good if Madrid was also around the La Liga average, but they’re not. Rather, it becomes especially alarming for Chelsea when comparing their playing style under Conte to Real’s. The teams were similar with certain styles, but Real Madrid thrived at 40 percent above the La Liga crossing style average.

Real Madrid’s overall 2016-17 playing styles measured against La Liga averages (0%).

Now let’s get back to the fact that Morata came on 12 times as a substitute and try to quantify what that could mean for him. In the 60- to 90-minute range, Real’s attacking threats went wild, particularly when the score was even or they were losing. Real’s crossing style increased to 143 percent of the league average in those circumstances.

Real Madrid’s playing styles when tied or losing in the 60- to 90-minute range.

Compare that to Chelsea in the same scenario (+24 percent crossing), and the way Morata could be forced to play in late-match situations with tight scores at Stamford Bridge might seem a bit foreign without balls flying into the box at a level he’s used to – and that’s without even mentioning the luxury of those fresh legs he often had with Real.

Chelsea’s playing styles when tied or losing in the 60- to 90-minute range.

Morata may very well show progress as a young striker that wasn’t possible in his reserve roles at his past clubs. He may very well score 15 goals for Chelsea. He may very well score 20 like Costa did last season. He’s just unlikely to do it at last year’s rate.

LMA Chairman Wilkinson: STATS Has ‘Anticipated What the Future Might Bring’

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Howard Wilkinson’s managerial career was at its apex around the time the Premier League was formed, yet he remains the last English manager to win the country’s top flight. That came with Leeds United in 1991-92 in the old First Division’s final campaign, and the Premier League’s subsequent 25 seasons have been won by Italian, Scottish, French, Portuguese and Chilean managers.

Wilkinson has seen analytics and video analysis revolutionize the game during that time. What’s remained a constant is the value in beating opponents to the facts, and much of that now hinges on innovations from data providers.

“Without the facts, it’s very difficult to make effective decisions,” said Wilkinson, the League Managers Association chairman. “And although intuition comes into it, intuition only comes with experience. Therefore, the two are linked, and the longer you use data analysis, the better you become at making those intuitive leaps, which are necessary.”

STATS has taken such expert opinions into account in its attempt to revolutionize football analysis with STATS Edge – an intuitive search and analytics application that leverages artificial intelligence so clubs can find specific game clips and analyze complex patterns with speed and accuracy never before possible.

“The reason STATS and their forebears have been around so long and have been successful is that they’ve not only moved with the times, they’ve anticipated what the future might bring,” Wilkinson said. “And that plus the amount of games, players they’ve analyzed has allowed them to build models, which are models for football, not just for that club.”

Crossing Over: Lukaku’s Success Will Depend Heavily on Manchester United’s System

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STATS’ playing styles data shows the striker’s goal efficiency could flourish at Old Trafford – if his manager puts him on the end of crosses and allows him to operate in space

To some, Jose Mourinho’s frustration with wanting more from Manchester United’s transfer window will be received as the manager being his contrarian self. His club just spent big to bring on the Premier League’s No. 3 scorer over the past four seasons as he enters his prime.

To others, his complaints are valid given the insipid nature of the Red Devils’ finishing last season and the subtraction of two names in a historical class that newcomer Romelu Lukaku has years of remaining work to join – Zlatan Ibrahimovic and Wayne Rooney.

The second of those names is one of only three players to reach 50 Premier League goals at a younger age than Lukaku, so the traditionally sexy question of whether a high-profile move to Old Trafford from Goodison Park can benefit Lukaku’s career the way it did Rooney’s is going to linger.

Forget all of that for now.

There are more fascinating ways to consider the Lukaku move, and the real predictive analysis has far less to do with Mourinho’s mouth or Rooney’s legacy after a season in which the England great’s withdrawn role was anything but comparable to what Lukaku’s will be.

What’s of more relevance – and can be properly considered now with a dig into quantifiable player- and team-tendency data – is that the 24-year-old Belgium international is entering a United system in which he seems to have the opportunity to succeed on levels similar to those he enjoyed last season at Everton. He can even surpass them if he can become more effective in attacking situations without goal-facing space.

It’s noteworthy that Lukaku went through the league last season with only one goal from the penalty spot and one from a free kick. Virtually all of his scoring threat comes from the run of play, so he’s a particularly worthwhile player to evaluate with playing styles.

Lukaku scored nine of his 25 league goals off of crosses last season, despite operating in an Everton system with a playing style that came in just below the league average of time spent in crossing scenarios.

In a comparison of the 2016-17 styles of United and Everton against league averages, Everton rarely differentiated themselves and were at -3 percent of the league crossing average. Manchester United were positive 10 percent.

The playing style web shows the league average as the 0% differentiation line.

Switch Lukaku’s shirt from blue to red and, without even looking at the data, the first thoughts that come to mind are promising with outside players such as Antonio Valencia and Marcus Rashford – and possibly Ivan Perisic if United eventually agree on a price with Inter Milan – putting balls into the box with frequency that Everton couldn’t match. Playing style numbers back that up.

Where the Toffees did distinguish themselves some stylistically were in counter attack (+14) and fast tempo (+12 percent). Notice United’s similar counter (+15) and a drastic increase in fast tempo (+81), which one would think bodes well for a No. 9 threat such as Lukaku who’s physical profile at least passes the eye test in comparison to Ibrahimovic.

What’s more is the playing style presence during their goals linked up for the top two categories. Lukaku existed in a crossing style during 36 percent of his goals and 20 percent came from direct play. Ibrahimovic: 31 percent crossing and 19 percent direct play. But that doesn’t mean Ibrahimovic was necessarily effective in Mourinho’s system.

One can argue Lukaku did more with less last season than the big Swede by looking into STATS’ expected goal values, which is an efficiency metric determined by the likelihood of a goal being scored based on the position from where a player’s shots were taken. Lukaku’s xG for the season was 15.1, and of the 25 he scored, he needed 4.4 shots per goal. His +9.9 differential was unmatched in the Premier League.

Ibrahimovic’s xG was 19.4. He scored 17 – which on its own isn’t necessarily relevant in comparison with other players considering his late-season knee injury – but it’s worthwhile to note his -2.4 differential and that the goals he did score came at a rate of 7.1 shots per.

Here’s where the question of how Lukaku can still grow as a player comes in and what United might need to do to maximize his efficiency if he ends up struggling in different styles.

There’s little yet to support Lukaku can be the kind of player Ibrahimovic has often been with back to goal and tighter marking while playing for clubs with such possession-based, attacking-third threats. The Belgian has on occasion been criticized for a heavy touch, which may be on display with more time operating in less space within scenarios of sustained threat and build up.

At least in the Premier League, it’s hard to say he’s ever experienced the tight quarters he may see with United, who operated last season 30 percent above the league average of sustained threat and 41 percent higher in build up. But the Everton managerial change away from Roberto Martinez’s style before last season might have stunted any growth that was happening. That, or it might show how Mourinho can tinker his system to get immediate results from Lukaku.

Everton’s build up in 2015-16 was 25 percent higher than the league average, so far closer to Manchester United’s ’16-17 rate than Everton’s under Ronald Koeman (+4). Forty-six percent of the playing style presence during Lukaku’s scoring was crossing, but Everton’s crossing style (+5) didn’t exactly exploit that to great ends. Twelve percent of Lukaku’s goals came from build up.

Now consider his efficiency. In that final season with Martinez, Lukaku scored 18 goals but had an xG of 21.2 with a 6.7 shots-per-goal rate.

Considering his efficiency under Koeman, it follows that Martinez’s system probably didn’t provide the best styles for the striker to convert opportunities.

So for Mourinho, it might be more about maximizing the playing styles in which players such as his new striker can succeed rather than continuing to buy, buy, buy until the end of the window.

It can be statistically argued he didn’t maximize Ibrahimovic after signing him last year, and Mourinho’s first season at Old Trafford ended with the Red Devils eighth in the league with 54 goals (excluding own goals for). That was -16.3 of their expected goal value (70.3). They were outscored by Bournemouth, and the Red Devils’ differential between goals for and expected goals for was worse than every club other than Southampton (-27.6) and Stoke City (-17.2).

Juan Mata scored six league goals, but no one else other than Ibrahimovic topped five. Players not putting the ball in the net – on the surface, that seems like something a manager should be able to vent about. But playing style? That falls on the manager.

Consider the sequence of events and place blame accordingly.

Allardyce: Video’s ‘Small Gains Are So Important’

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Sam Allardyce recalls the time around the turn of the millennium when statistical and video analysis came to the Premier League. Analytically minded teams had a substantial advantage over others before match-preparation tools grew in popularity.

In the nearly 20 years since, it’s gone from innovative to mainstream to inundated, but the benefits remain in matters of methodical proficiency. Now more than ever, it’s about streamlining the process to reach conclusions faster and implement the findings into training earlier.

That’s exactly how STATS plans to revolutionize football’s analysis process this summer with the launch of STATS Edge – a search and analytics application that leverages artificial intelligence so clubs can find specific game clips and analyze complex patterns with speed and accuracy never before possible.

“Video clips are massively important. Short bursts of information. Not just on (your own players), but also what we do on the opposition pre-match and post-match,” Allardyce said.

“If you talked about ’99-2000 when statistical analysis came in, you could gain 5-10 percent because not everybody wanted it, not everybody wanted to use it, not everybody had it. So it was much easier then to gain a bigger percentage advantage on how you applied that to your team. But now it’s like everybody’s doing it and the gains are so small now, but those small gains are so important.”