Prime Creators

Time for a big, long Monday-morning table. Given our attacking buildup data, turns out it’s easy to calculate the number of attacking moves (moves that lead to shots, remember) in which each European player has been involved. That in turn makes it easy to identify each team’s prime creator – the player involved in the most attacking moves per 90, whether it be passes, shots, dribbles, whatever. The cut-off is 450 minutes, here they are:

Team Player Attacks p90
Napoli Lorenzo Insigne 11.72
Arsenal Mesut Özil 10.84
Manchester City Kevin De Bruyne 10.83
Real Madrid Cristiano Ronaldo 10.80
Barcelona Neymar 10.77
Juventus Paulo Dybala 10.38
Paris Saint-Germain Ángel Di María 9.82
Lyon Mathieu Valbuena 9.50
Celta de Vigo Nolito 9.47
FC Bayern München Douglas Costa 9.41
Roma Miralem Pjanic 9.21
Fiorentina Josip Ilicic 8.99
Bayer 04 Leverkusen Hakan Calhanoglu 8.92
VfB Stuttgart Daniel Didavi 8.62
Internazionale Stevan Jovetic 8.53
West Ham United Dimitri Payet 8.48
Milan Giacomo Bonaventura 8.33
Borussia Dortmund Henrikh Mkhitaryan 8.24
Tottenham Hotspur Christian Eriksen 8.20
Liverpool Philippe Coutinho 8.16
Marseille Abdel Barrada 8.15
Sevilla Michael Krohn-Dehli 8.07
Chelsea Cesc Fàbregas 7.98
Empoli Riccardo Saponara 7.65
FC Schalke 04 Julian Draxler 7.57
Swansea City Jonjo Shelvey 7.49
Chievo Valter Birsa 7.48
Palermo Franco Vázquez 7.43
Norwich City Nathan Redmond 7.35
FC Augsburg Caiuby 7.29
Bordeaux Wahbi Khazri 7.26
Atalanta Maximiliano Moralez 7.17
Rayo Vallecano Jozabed 7.16
Southampton Dusan Tadic 7.07
Everton Ross Barkley 7.05
Deportivo de La Coruña Luis Alberto 7.03
Caen Andy Delort 6.92
SV Werder Bremen Zlatko Junuzovic 6.88
Sassuolo Domenico Berardi 6.88
FC Ingolstadt 04 Pascal Groß 6.85
Monaco Stephan El Shaarawy 6.82
Genoa Diego Perotti 6.81
Manchester United Memphis Depay 6.78
Udinese Francesco Lodi 6.75
Málaga Duda 6.69
Eibar Saúl Berjón 6.66
Guingamp Yannis Salibur 6.62
Athletic Club Raúl García 6.58
Lazio Keita 6.56
Atlético de Madrid Antoine Griezmann 6.53
Watford Almen Abdi 6.53
Leicester City Riyad Mahrez 6.49
Nice Jean Seri 6.49
Frosinone Robert Gucher 6.44
Espanyol Marco Asensio 6.39
VfL Wolfsburg André Schürrle 6.31
Valencia CF Daniel Parejo 6.29
Newcastle United Ayoze Pérez 6.27
Las Palmas Jonathan Viera 6.17
Real Sociedad Rubén Pardo 6.16
Lorient Yann Jouffre 6.10
Angers Thomas Mangani 6.06
Crystal Palace Bakary Sako 6.05
Borussia Mönchengladbach Ibrahima Traoré 6.05
Sunderland Adam Johnson 6.03
Montpellier Ryad Boudebouz 5.98
Getafe Pedro León 5.97
Levante Morales 5.86
Rennes Kamil Grosicki 5.82
Nantes Jules Iloki 5.81
St Etienne Nolan Roux 5.76
Lille Sofiane Boufal 5.75
Troyes Corentin Jean 5.72
Toulouse Óscar Trejo 5.67
Hannover 96 Hiroshi Kiyotake 5.65
Sampdoria Éder 5.58
Bournemouth Matt Ritchie 5.52
Bologna Franco Brienza 5.40
GFC Ajaccio Damjan Djokovic 5.35
Verona Federico Viviani 5.27
Carpi Matteo Fedele 5.25
Eintracht Frankfurt Marc Stendera 5.24
Stoke City Marko Arnautovic 5.18
Hamburger SV Lewis Holtby 5.08
Granada CF Rubén Rochina 5.04
West Bromwich Albion James Morrison 5.02
Hertha BSC Vladimir Darida 5.02
Real Betis Joaquín 4.97
SV Darmstadt 98 Konstantin Rausch 4.95
1. FSV Mainz 05 Yoshinori Muto 4.90
Bastia Sadio Diallo 4.86
Aston Villa Rudy Gestede 4.79
1. FC Köln Anthony Modeste 4.74
TSG 1899 Hoffenheim Eduardo Vargas 4.71
Reims Nicolas de Preville 4.71
Sporting de Gijón Alen Halilovic 4.63
Torino Daniele Baselli 4.60
Villarreal Manu Trigueros 4.22

Özil only just beating out half a dozen or so other Arsenal players in that free-wheeling attack, de Bruyne sneaking up on a limited number of minutes, and someone explain Villareal to me. Turns out they’re 5th, but they don’t appear to attack much?

Prime Creators

Europe’s Most Direct Teams

I will continue flogging this attacking shape data until I find a good use for it, but here’s a bit of fun: given the average height of team’s attacks, i.e. the amount of ground covered towards their opponent’s goal, and the duration of those attacks, we can calculate the pace at which teams hurtle towards the opposition goal. It’s a pretty nice measure of how ‘direct’ teams are, and here’s who comes out top:

Team Attacking Pace (m/s)
Caen 3.63
SV Darmstadt 98 3.33
Leicester City 3.26
Villarreal 3.24
Crystal Palace 3.17
FC Ingolstadt 04 3.16
Eibar 3.16
TSG 1899 Hoffenheim 3.13
Sevilla 3.13
Sporting de Gijón 3.11
VfB Stuttgart 3.04
Eintracht Frankfurt 2.98
Lille 2.95
Guingamp 2.94
Carpi 2.94
1. FSV Mainz 05 2.94
Troyes 2.93
St Etienne 2.92
Angers 2.91
Toulouse 2.88

You can read more about Caen’s quick transitions and counter-attacking play in this article by Mohamed Mohamed on StatsBomb. It’s worth noting that for the numbers I have available (2012+ outside the EPL), this year’s Caen are currently the fastest attacking side I can find, so they’re probably worth a watch this season. They’re currently sitting 5th in Ligue 1. 2010 Blackburn Rovers are second, with half a season of Big Sam (auditioning for the Inter and Real jobs, if you remember) and half Steve Kean. I’ll leave it to you to dig those tapes out…

Guess who’s propping up the table at the bottom?

Team Attacking Pace (m/s)
Manchester City 2.26
Swansea City 2.24
FC Augsburg 2.20
FC Bayern München 2.17
VfL Wolfsburg 2.07
Fiorentina 2.07
Nice 2.05
Paris Saint-Germain 2.05
Juventus 2.00
Manchester United 1.92

You’ll be happy to hear that Man Utd’s buildup play this year is only the second slowest on record. They were beaten out by none other than… last year’s Man Utd.

One last bonus, the Pep effect:

Season Team Attacking Pace (m/s)
2015 Barcelona 2.78
2013 FC Bayern München 2.33
2012 FC Bayern München 2.33
2013 Barcelona 2.27
2014 Barcelona 2.27
2012 Barcelona 2.24
2015 FC Bayern München 2.17
2014 FC Bayern München 2.16
Europe’s Most Direct Teams

Visualising Attacking Shape

Today I’ve been experimenting with how to visualise the attacking geometry data I’ve been calculating. If you’ve seen the previous posts you’ll know that I’ve been mostly able to calculate width, height and duration for passing moves that lead to shots. I want to use this data to get a feel for how different teams attack and ultimately what types of attack are effective.

The data is still a bit problematic. I’m only interested in attacking buildup – shots from free-kicks, or directly after turnovers don’t show up because there’s only one event in the move, the shot itself. There’s also a bit of fuzziness that perhaps over-eagerly associates passages of play with an attack – this is because of quick changes in possession. Basically you have two options:

  1. Reset the buildup whenever the attacking team loses the ball. This means you’re incredibly sensitive to attempted clearances or aerial challenges.
  2. Allow a little leeway for the attacking team to win possession back.

I chose the latter – after an unsuccessful pass which gives the opponents the ball, if the attacking team can get the ball back within 5 seconds, it’s credited as part of the same attacking move. It results in us capturing many more moves around the box (where deflections, clearances and aerial challenges are common) at a cost of elongating some moves in the middle of the park where you might argue that the ball is actually evenly contested. There are other caveats that I hope are sensible: I don’t track shots after rebounds unless they grow into their own move, otherwise I’d risk measuring the build-up play twice. I also don’t track moves across dead-ball situations, so fast throw-ins or free-kicks don’t get added to previous build-up play.

Once you have that data to build upon, it’s very easy to take some averages and lose interesting truths – by averaging out Tottenham’s numbers, for example, you lose sight of their fast vertical attacks as they’re swamped by patient side-to-side buildup play. So instead of creating a team-by-team visualisation, I’m attempted to cram all of a team’s attacks in a single game onto one image. My hope is that this lets you look how and where they’re attacking at a glance – what parts of the pitch, how wide the move is, how long it took, how much vertical space it gained. Just the sheer volume of space a team uses while attacking should give a fairly good indicator of their control in a match.

Anyway, let’s see – I’d appreciate any comments about these. It’s possible it’s too much for one visualisation, and perhaps they’re a bit garish when you have a team with tons of shots. But hopefully you’ll agree that there’s some interesting information to be gleaned just from a quick glance.

Let’s start with a busy one, this is Tottenham’s attacking play against Aston Villa:


The boxes are the bounds of an attack, so you can see how wide and how high it went. The colour represents duration – faster attacks are more red, slower attacks with more buildup are green. What can you see here beyond a bit of a mess? Well, tons of shots, for one. Some slow, expansive buildup play, but plenty of more faster penetrative moves too, especially through the centre and to the left of the penalty box, where the first and second goals came from.

Here’s the reverse, with Aston Villa’s attacks from that game:


Much less going on here, a lot of wide, flat moves, not a ton of penetration.

Here’s Liverpool against Chelsea:


Lots going on in the middle, including a few signs of pace. Chelsea’s chart is pretty abject though:


I mean, at least they’re starting high up the pitch, but these slow, spacey moves don’t seem that scary, and they’re not pushing far into the box. Those tiny, slightly redder boxes? I thought they were a bug, but no – the one near the half way line is Oscar winning the ball and shooting from 40-odd yards. The one in the box is Falcao winning a header after a rebound of Sakho from an Oscar shot (remember we don’t follow moves across rebounds).

But if you want pure comedy value, let’s have a look at Crystal Palace’s 0-0 draw with Man Utd:


Not a lot going on here, but Palace one of teams with shortest moves in the league and that shows here, on top of a little bit of excitement on that right-hand side of the box. But forget all of that, up next is the single saddest chart I have ever seen in my life:


I shit you not. Now, this isn’t every shot Man Utd took, they had a free-kick on target if you remember, and those don’t show up in this data. But seriously, this was what their slow, rambling build-up looked like when it actually happened. Good clean sheet, though.

So… the busier these get the harder they are to parse, I think, but I still like them. If anyone has any ideas for different ways they’d like to see this data mangled, by all means get in touch. Have REPL, will program. And if there are any particular games you’d like to see this way, just ask and I’ll tweet them out.

Visualising Attacking Shape

Attacking, Fast and Slow: Tottenham Edition

One of the numbers that stuck out to me when I calculated the data in Attacking, Fast and Slow, was the slow pace of Tottenham’s attack. We know Pochettino values winning the ball back high up the pitch and launching fast-paced counter-attacks, so why isn’t that clearer from the data? In the light of Jake Meador‘s piece today which had a few commenters quite rightly puzzling over my numbers, I thought I’d look deeper and work out where the bugs were in my approach, and how better to present the data so it captures the nuances in Tottenham’s attack.

First off, there were issues with my data, and I’ve added a note and updated numbers to the the last post. Luckily, most of my conclusions remain correct (and in fact the correlation of attack duration from year to year is even stronger in the fixed data), but one of the big movers are indeed Tottenham, who now reside in the bottom half for attack duration.

Let’s look in more detail at exactly how quick each team’s attacks are. Here I’ve broken attacks down into 5 second buckets up to 30s, and sorted by the 0-5s bucket:

Team 0-5s 5-10s 10-15s 15-20s 20-25s 25-30s 30s+
Southampton 47 22 20 13 10 4 28
Tottenham Hotspur 40 20 21 15 18 11 29
Arsenal 39 21 32 25 17 12 35
Liverpool 38 27 16 9 11 7 38
Aston Villa 34 17 9 7 8 5 23
Leicester City 34 30 28 21 8 2 20
Norwich City 33 23 12 16 13 7 29
Crystal Palace 33 21 19 13 9 4 17
Manchester City 33 24 30 16 14 13 48
Bournemouth 30 22 10 10 6 7 22
Watford 30 22 21 11 11 5 25
Chelsea 28 17 23 11 10 11 29
West Bromwich Albion 25 14 14 8 5 5 20
West Ham United 25 27 15 16 8 9 26
Sunderland 24 9 14 9 11 6 18
Everton 23 16 15 18 7 10 29
Newcastle United 19 23 14 10 7 9 23
Swansea City 18 26 8 17 15 8 32
Stoke City 16 14 15 6 14 6 20
Manchester United 16 14 10 8 9 34

And here’s what that looks like stacked up together:

Well that matches our intuitions much better – the two teams we know share Pochettino’s desire for quick attacks off turnovers are right there are the top, with more shots within 5s than anyone else, and with 10s numbers that stack up pretty well too. I initially worried that these numbers might just be a side-effect of weird corner numbers, but Tottenham and Southampton sit 8th and 9th in corner count.

If you look at Tottenham’s numbers in the aggregate, they’re slowed down by patient build-up play. Despite the contrast in the chart above, they can be similar to Man Utd – moving the ball from side to side, waiting for an opportunity to open up. If you remember my passing gains chart, Tottenham’s passing on average in the centre of the field is backwards. They probe forwards on the wings, recycle backwards into the centre. Eventually this leads to shots that have taken a lot of time and space in the build-up, and I’ll certainly look for better ways to categorise this. But hopefully with the approach above, people are at least now seeing the Tottenham they know and love.

Attacking, Fast and Slow: Tottenham Edition

Attacking, Fast and Slow

Note 05/11/2015: the original numbers published here were based on some faulty data – I found attacking moves that persisted even when the opposition won the ball back. This had the effect of making most moves seem longer and wider. Fortunately, after fixing that, Man Utd stay at the top and Leicester at the bottom, the changes at Newcastle and West Ham still seem real, and the correlation from year-to-year is now even stronger. Many thanks to the commenters on this post whose Tottenham spidey-sense caused me to take a second look.

I’ve been curating some data so that I can look at teams’ attacking buildup play. There’s some more in-depth stuff coming, but I thought it was fascinating to just look at the basic geometry of different teams’ attacks. So, let’s measure the passing moves that lead to shots (rebounds and direct free kicks excluded), starting with a turnover or dead ball situation. For each team I’ve calculated:

  • the average ‘X’ position, this is the position of the ‘centre’ of the move, as a percentage up the the field towards the opponent’s goal, 50 being the half-way line
  • the average width of the move, sideline to sideline, with 50 being half the pitch
  • the average height of the move, box to box, again 50 being half the pitch
  • the average duration in seconds

Let’s have a look, ordered by duration:

Team Average X Width Height Duration
Manchester United 50.3 54.0 42.6 28.7
Manchester City 48.1 55.8 43.7 25.6
Swansea City 44.2 55.7 42.7 24.0
Everton 49.7 55.5 42.8 22.4
Newcastle United 44.5 55.2 43.6 22.2
Chelsea 44.1 52.2 43.3 21.9
Stoke City 43.0 54.1 44.5 21.0
Liverpool 43.2 50.1 39.6 20.9
Norwich City 55.4 51.5 38.9 20.1
Arsenal 46.3 49.2 45.0 19.8
Tottenham Hotspur 43.1 50.3 41.7 19.8
West Bromwich Albion 47.8 50.9 40.5 19.8
Sunderland 47.0 51.9 42.1 19.6
Aston Villa 45.8 50.5 40.0 19.3
Southampton 48.3 50.3 38.6 19.3
West Ham United 48.5 52.8 40.3 19.1
Watford 44.9 48.2 41.3 18.6
Bournemouth 55.0 50.1 33.8 17.9
Crystal Palace 47.3 48.9 38.9 16.9
Leicester City 51.0 45.5 40.9 16.0

The incredibly ponderous Man Utd sit at the top of the table, giving themselves on average 28 seconds with the ball in the buildup to their shots. At the bottom are Leicester City – could they be the most direct team in the Premier League? Looking at their width number, they also seem to use less space on average in their attacks than any other team. Part of the reason is that the space you have to cover and the time it takes to cover it are of course tightly linked, but look at West Ham – short-lived attacks but making use of much more width.

What’s more interesting about these numbers it that they seem to hold over from season to season. Part of that is obviously the quality of players at a club – Leicester’s success aside, you would probably bet on the wider, slower teams in the top half of the table to secure European places over the bottom half. Better players can keep the ball longer, and can move the ball about the park more easily, so we’d expect the best teams to have higher width and duration numbers. That said, I did a quick check and the average buildup time for goals is the same as all shots, around 18-19 seconds – there’s no indication that quicker or slower is necessarily more effective in creating goals.

Here’s last year’s table:

Team Average X Width Height Duration
Manchester City 47.0 54.0 43.3 25.8
Everton 43.9 54.3 44.0 25.1
Manchester United 47.1 59.3 40.3 25.0
Chelsea 50.0 52.1 40.8 24.0
Liverpool 44.6 54.3 43.7 23.3
Southampton 47.9 52.8 40.2 21.3
West Bromwich Albion 44.1 51.5 39.6 21.2
Arsenal 50.6 48.3 40.1 21.1
Aston Villa 46.9 54.5 40.5 20.9
Swansea City 42.9 52.6 39.7 20.5
Tottenham Hotspur 43.2 52.5 40.2 20.4
Sunderland 45.7 51.9 39.5 20.3
Stoke City 44.3 51.8 40.4 19.4
Hull City 48.0 53.1 39.1 19.4
Queens Park Rangers 47.5 49.4 37.5 17.3
West Ham United 51.6 47.7 36.7 16.5
Leicester City 49.5 45.2 37.8 16.0
Newcastle United 48.3 46.2 37.8 15.9
Crystal Palace 47.8 46.1 38.2 15.5
Burnley 53.7 50.5 37.3 15.3

Almost all teams post similar numbers (duration has an R2 of about 0.8), and again you could easily explain that as player quality, but for the radical changes at Newcastle, who sacked John Carver and replaced him with Steve McClaren over the Summer. They’re now taking a whole extra 6 seconds in the buildup to their shots, and using 9% more of the field to do it in. West Ham brought in Slaven Bilic and have added 2.5 seconds and 5 percent more space. There are more outliers that spoil the story a bit – Man Utd were very wide in 2014, less so now, and both they and Swansea are building up a lot slower this year), but I think these duration and width numbers – how fast, how directly you attack – are a very clear part of a manager’s signature.

Attacking, Fast and Slow