In my previous series on Expected Wins Four – probably more appropriately entitled “Expected Points” – I’d taken a look at how the general tendencies of four primary Leagues in Europe (England, Germany, Spain, as the UEFA Champions League) compare to Major League Soccer – Is European Football Really Higher Quality than Major League Soccer?
This time I’m focusing strictly on Europe and offering up how things stand in PWP with the season coming to a close soon. But before digging some things to share about PWP to date:
A reminder – PWP is about two things:
- The End State in that the final Index comes as close as possible to the League Table without using points earned in any of the calculations, and
- Recognizing that soccer is a game that is played in a free flowing environment – picture two amoeba fighting against each other in a confined space…. There is attempted control by the Head Coach that includes tons of preparation to set the stage for ‘an approach’ to earn three points – and then there is the game itself where there is but one time out (halftime) – no namby pamby huddles or official stoppages of play between possessions. Meaning these guys play a full-on, in your face (sometimes literally), non-stop, constantly thinking and reacting to the game that can literally see the ball go in any direction at any time… not purely random but close.
Given that, PWP attempts to tone down all that volatility and parse out general tendencies that fall within the bell curve of activities – it’s not perfect – but it’s bloody good… and yes – I have made a few mistakes along the way (if you don’t work you don’t make mistakes). The latest has been a technical mistake – the relationship of CPWP to the League Table is not an R Squared number (Coefficient of Determination) it is an R number (Correlation Coefficient).
For the stats followers that may be an issue… but even with the Modernized TSR (read here) the CTSR “R” is still generally lower (team to team) and certainly lower (table to table) than CPWP – meaning there still remains room for both statistical analytical approaches in a gmae that is played across the world…
Also, my thanks to some great research by Rob Lowe, a mate with the same passion for footy, who has asked to collaborate with me in the future. He has done some additional regression analysis on the data points of PWP with respect to goals scored and points earned. I should point out that his results show that not all six of the data points in the PWP equation independently-directly relate to goals scored or points earned. For me that is okay – and actually great news for a few reasons…
- Both of my two new statistics (Passes Completed in the Final Third per Passes Completed across the Entire Pitch – Step 3 of PWP) and (Shots Taken per Completed Pass within and into the Final Third – Step 5 of PWP) did statistically relate to Goals Scored and Points Earned (independently). Meaning those new statistics are relevant – both within the context of PWP and outside the context of PWP. It’s this statistical regression type information that should solidify these two new statistics in the world of soccer.
- For both Possession (Step 6 of PWP) and Passing Accuracy (Step 5 of PWP) – as you will see a bit later – those two derived data points were never supposed to directly (independently) relate to goals scored or points earned as a matter of course I have advocated for quite some time that they shouldn’t. PWP was built with the intention that the six derived data points only needed to relate to each other in a stair step relationship recognizing that in every game a team needs to possess the ball, move the ball, penetrate the opponent’s final third, take shots based upon that penetration, put them on goal, and score goals – all while preventing the opponent from doing the same thing.
- Another view on the outcome that Rob has noted – it’s unreasonable to analyze a game of soccer without taking those activities into account. Rob’s positive feedback was that both possession and passing accuracy act as a “smoothing agent” within the Index – I agree but with beginning to learn the nuance of writing an Academic Paper I would put it this way.
- Possession and Passing Accuracy stats have limitations when vewing overall regression analysis relative to goals scored and points earned – but those limitations actually give the overall analyst of soccer a much better understanding about the context of activities that occur when a team is performing better than another team.
- In addition, Passing Accuracy statistics provide a coach a great measurement tool for how well some players may develop and progress into higher levels of competition – to exclude data of this import really ignores some of the most fundamental training aspects a team needs to do in order to improve.
- Also, there is excessive volatility in the percentages associated with Shots on Goal versus Shots Taken and Goals Scored versus Shots on Goal – if I only look at those two things then evaluating a game is all about (pass-fail) – granted winning and losing is pass-fail. But to develop a “winning culture” a grading system perhaps more appropriate is A-B-C-D-F – in other words there are levels of success above and beyond pass-fail – especially when you are a team that isn’t at the very top of the league.
- By having Possession and Passing Accuracy in the equation you get a much larger (explanatory) picture on the culture of success – and as things appear to take shape, the Index itself, gives better clarity to that level of success for teams that are mid-table as opposed to bottom dwellers or top performers…
Now for the grist in Europe – first up – England:
Note that the first two diagrams (in each four diagram grouping) highlight where the highest quantity and highest quality occurs within each competition – after some growing pains (earlier Expected Wins measurements) all four competitions now see the teams that win having the highest averages, in all categories, for both quantity and quality… proving (for the most part) that more is better and more results in more…
All told the correlation, at this time, remains very strong – note that the “R” has replaced the “R2” in my third and fourth diagrams.
If I remove Possession and Passing Accuracy from the CPWP Index – the R value drops to .78 – statistically reinforcing that the Index, itself, better represents the standings in the League Table by including Possession and Passing Accuracy data. Proving yet, another way, that goals scored and shots taken simply do not provide adequate depth on what activities occur on a pitch relative to earning points in the League Table! And if you’ve read Moderning TSR this doesn’t mean ATSR/DTSR or CTSR doesn’t have value – it does…
As things stand today Chelsea take the League and since Man City, Man United, and Arsenal round out the top four (different orders) in both CPWP and CPWP-PI I’d offer it’s those four that advance to the UEFA Champions League next year. The bridesmaid looks to be a two horse race (Spurs supporters may argue that) between Liverpool and Southampton.
Note that Southampton edges Liverpool in CPWP but that Liverpool edges Southampton in CPWP-PI – meaning when excluding Goals Scored – Liverpool has better quality than Southampton – so for Liverpool it’s more about converting Shots on Goal to Goals Scored – while for Southampton it’s more about getting clean sheets and scoring at least one goal; at least in my view – others may see that differently?
In retracing the earlier discussion on the data within the six steps of PWP – as you can see in both the first and second Diagrams (for all competitions) the Exponential Curve (Diagram 1) and well as Power Curve (Diagram 2) the stair step relationship between the data – point to point – are incredibly high… Even more intriguing is how close those “R2” numbers are for both winning, drawing, and losing… really driving home the point, in my view, just how small the margin of error is between winning, drawing, and losing.
For goals scored (for or against) we really are talking about 5 or 6 standard deviations to the right of the bell curve…
Perhaps the most intriguing issue this year isn’t the FC Bayern story – it’s the lack of goal scoring in Borussia Dortmund – when viewing the CPWP Predictability Index clearly Dortmund is offering up all the necessary culture the team needs in order to succeed – with one exception – goal scoring…. wow!
Another surprise may be Wolfsburg I’d pick them, and Bayer Leverkusen to finish two-three in their League Table – both show pedigree in team performance both with and without considering goals scored…
Barcelona and Real Madrid are locked in for the top team battle – my edge goes to Barcelona. I’d offer more here but I’m simply not up on the La Liga as much as I’d like to be…
UEFA Champions League:
The top eight teams that advanced are identified above – given the general success of CPWP relative to the top eight I’d expect FC Bayern Munich, BArcelona, Real Madrid, and Juventus to advance to the semi-finals.
My first of at least 4-5 Academic Papers is soon to be published – my thanks to Terry Favero for helping me work through this new experience – his support, patience, and knowledge in navigating all the nuance associated with writing an Academic Paper has been superb!
All four European competitions show more gets you more – this was not the case for Major League Soccer last year:
When more gets you more in MLS then I sense MLS has reached the BIG TIME – until then I think it’s a great breeding ground for Head Coaches that simply can’t get a job with a soccer club that has huge pockets of money.
Put another way – and many may disagree… I think a Head Coach who really wants to challenge their intellectual grit against another Head Coach can have greater opportunity to do that in MLS than they can by Head Coaching most clubs in Europe.
Why? For at least one reason – a Head Coach in MLS really has to do more with less…
Errata – the first MLS slide indicates 654 events – the correct number is 646 events…
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Much has transpired in the world of soccer statistics over the past four years since I first published: Possession with Purpose – An Introduction and some Explanations.
- Three years ago I published my Possession with Purpose – Revised Introduction.
- In 2014 the concept was presented at the World Conference on Science and Soccer 2014.
- Last year the concept was published in Europe and just this year another part of Possession with Purpose was presented at the World Conference on Science and Soccer 2017 (Predictability).
- Now it’s time for a new update that hopefully brings more clarity and simplicity?
CLICK this link for my NEW simplified power point presentation update of Possession with Purpose the Total Soccer Index
- The .pdf version should make it easier to print and use as reference material.
Within you’ll find:
- Definition of TSI
- Purpose of TSI
- Premise of TSI
- Parts of TSI
- Leagues / competitions analyzed
- Application of TSI and its parts
- The data for leagues / competitions analyzed
- Observations & conclusions by league / competition as well as reviewing TSI across leagues / competitions
My thanks to all for your support and kind words throughout the years.
- The sum of the parts has greater correlation to points earned than the parts independent of each other.
- Player A, from Team A, within any given league, has a different correlation to points (performance/outcome) than Player B, Team B, Player C Team C, etc in that same league. In other words outcomes of individual player statistical analyses are NOT EQUAL from team to team and league to league.
- Said differently, clearances or crosses (used as a measurement in fantasy soccer) for one player, on one team, DO NOT have the same weight/value of clearances or crosses for a different player on a different team.
- Same can be said for passes or shots taken, etc.
- Therefore, Calculations such as Expected Goals are not an apples to apples comparison between teams within the same league. Yes, it’s a predictive tool, but flawed/
- The lower the overall correlation of the Total Soccer Index to points earned the greater the parity within the league or competition; this also intuits those are less predictable.
CAN IT BE DONE?
Over the last four years I’ve conducted research on various professional soccer leagues and competitions. To include Major League Soccer, the English, German, and Spanish Premier Leagues, as well as the UEFA Champions League and the Men’s World Cup of 2014.
Here’s my latest analyses on how the Possession with Purpose Index can be used to predict which teams will make the playoffs, qualify for the UEFA Champions League, or make the semi-finals of the World Cup..
Before beginning here’s a rerun on a few important items of interest about Possession with Purpose:
Intent: Develop a simplified, strategic set of performance indicators to better understand the outcome of a game based upon primary inputs.
- A documented method for measuring team performance from those indicators.
- An index that ranks teams for their performance based on this method.
- The index, while excluding points, comes close to matching results in the MLS league table.
- Bonus – unexpected outcome – a tool to predict teams making the MLS Playoffs.
Key events to date:
- Objective index developed in 2013
- Results presented at the World Conference on Science and Soccer 2014
- Approach published in the book – International Research Science and Soccer II – Routledge, Taylor, and Francis 2016
- Leagues/Competitions evaluated
- MLS 2013, 2014, 2015, 2016
- English Premier League 2014
- Bundesliga 2014
- La Liga 2014
- European Championship League 2014
- Men’s World Cup 2014
Major League Soccer 2013 – The Maiden Year for PWP:
- Nine of the top ten teams in the CPWP Index made the MLS Playoffs in 2013
- Internal outputs from team performances showed that teams who cede possession (have lower than 50% possession) can be ranked within the top ten so the index is not biased towards teams that possess the ball greater than 50%
- This doesn’t even include all the internal evidence on the various tactical styles of play each coach advocated.
- Three of the bottom four teams replaced their head coaches as well.
- It’s the initial results here that provided me compelling information to investigate deeper into what the outputs of the index might offer.
- Each subsequent index shows a gold and red star – indicating which team finished first and last in the league table.
English Premier League 2014:
- Winner of the League, Chelsea, finished 2nd in the index.
- All four of the top four teams in the index advanced to the UEFA Champions League; those teams with green bars.
- By week 16, of 38 weeks, the four teams who advanced to 2015 UEFA Champions League were the top four teams in the Index; and they didn’t move out of the top four the rest of the season!
- Three of the bottom four teams in the index were relegated in 2014; those teams with red bars.
Germany Premier League 2014:
- Winner of the League, Bayern Munich, finished 1st in the index.
- All four of the top four teams in the index advanced to the UEFA Champions League; green bars.
- By week 21 the four teams who advanced to 2015 UEFA Champions League were the top four teams in the Index; and they didn’t move out of the top four the rest of the season!
- Augsburg and FC Schalke, who advanced to Europa League, finished 6th and 8th, respectively, in the index (light green bars).
- For those teams relegated (red bars), SC Paderborn, finished worst in the league table and index, while Freiburg was 7th worst in the index and Hamburger SV was 3rd worst in the index.
Spanish Premier League 2014:
- Winner of the League, Barcelona, finished 1st in the index.
- All four of the top four teams in the index advanced to the UEFA Champions League; green bars.
- By week 14 the four teams who advanced to 2015 UEFA Champions League were the top four teams in the Index; and they didn’t move out of the top four the rest of the season!
- Sevilla and Villarreal, the two teams advancing to Europa League finished 5th and 6th, respectively, in the index; light green bars.
- The three teams relegated in 2014 were Cordoba, Almeria, and Eibar. They finished 2nd worst, 3rd worst, and 4th worst (respectively) in the index; red bars.
- Of note; Levante, who finished worst in the 2014 CPWP Index finished last in the 2015 La Liga Standings.
UEFA Champions League 2014:
- Winner and top team in the Index – Barcelona
- Four of the seven top teams in the index advanced to the semi-finals
- Barcelona 1st, Real Madrid 3rd, FC Bayern Munich 5th, and Juventus 7th; green bars.
- By the end of round one the top four teams to make the semi-finals were all in the top 10 for the index; with Barcelona 1st, Bayern Munich 3rd, Real Madrid 4th, and Juventus 9th.
- Poor performers, APOEL Nicosia and Galatasaray finished 2nd and 4th worst (respectively) in the index; red bars.
Men’s World Cup 2014:
- Winner of the World Cup. Germany, finished 1st in the index, with 2nd place finisher, Argentina 5th best in the index.
- Four of the top seven teams to reach the semi-finals finished 1st, 2nd, 5th, and 7th in the index; green bars.
- By the end of round one, the four teams to make it so the semi-finals were all in the top six of the CPWP Index; with eventual winners, Germany 1st, Argentina 3rd, Netherlands 5th, and Brazil 6th.
- With Brazil giving up seven goals to Germany in the semi-finals they dropped from 7th to 18th in the index.
- France, Colombia, Belgium, and Costa Rica are the teams who made it to the quarter finals; light green bars.
- All three teams that failed to earn a point in the World Cup finished worst (Australia), 2nd worst (Honduras), and 4th worst (Cameroon); red bars.
Side note about the Men’s World Cup:
- USA finished 5th worst in the index (blue bar).
- At that time I called for Jurgen Klinsmann to be sacked. Why?
- My two most compelling reasons were:
- Omitting Landon Donovan from the squad (huge reduction in squad mentality/leadership without his presence – plus he was simply the best striker/forward in the USA).
- Replacing Graham Zusi with Omar Gonzalez late on in the game against Portugal – that replacement (a huge tactical error) created a vacancy in the area where Graham Zusi was defending; the exact same area where Ronaldo delivered his killer cross from.
- Two years later, after numerous tactical and mental leadership errors, Jurgen Klinsmann was finally sacked.
- I wonder where our team would be (NOW) if Sunil Gulati would have had the backbone to sack Jurgen Klinsmann back then?
- I’m not afraid to say I told you so Sunil Gulati…
Major League Soccer 2014:
- Four of the top ten teams, after week 1 CPWP Index, made the playoffs; with SSFC, eventual Supporter Shield winners in third. After week 13 Seattle never fell further than 3rd in the Index.
- Eventual Cup winners, LA Galaxy, were 11th after week one. By week 8 they were 1st in the Index and did not fall out of the top two after week nine.
- Slow starter award goes to DC United, who were bottom of the Index until the end of week 5; when they finally breached the top ten.
- It was here, along with seeing FC Dallas, at the top of the Index, that reinforced the Index was not overly influenced by teams who have high amounts of possession.
- In other words, the Index would, and does, rank teams in the top ten even when they cede possession and play more direct/counter attacking football.
- Although the first four weeks of the Index didn’t predict more than four of the top ten teams making the playoffs by week eight the Index showed nine of the top ten teams making the playoffs.
- The level of accuracy, from week eight, going forwards never dropped below 70% and reached (and sustained 90% accuracy) by week 25 for the remainder of the year.
- Accuracy in predicting the top ten teams making the playoffs was no worse than 40% (the first four weeks) and no less than 70% throughout the remainder of the year with 90% accuracy first attained by week eight – and sustained by week 25.
Major League Soccer 2015:
- Seven of the top ten teams, after week 1 CPWP Index, made the playoffs; with NYRB, eventual Supporter Shield winners in ninth.
- Eventual Cup winners, Portland, were 8th after week one.
- Slow starter award goes to New England, who started at bottom after week one, but had breached the top ten by week seven.
- At no time did the CPWP Index have less than seven eventual playoff teams in the top ten. And by week seven nine of the top ten teams in the Index were bound for the playoffs.
- Accuracy in predicting the top ten teams making the playoffs was no worse than 70% at any given time – and as high as 90% accurate by week seven.
Major League Soccer 2016:
- Seven of the top ten teams, after week 1 CPWP Index, made the playoffs; with FCD, eventual Supporter Shield winners in first.
- For those who were surprised by the Colorado Rapids this year – you shouldn’t be. By week four, the CPWP Index had Colorado Rapids as third best in MLS; and they didn’t move out of the top four, in the Index, the rest of the year.
- Slow starter award goes to New York Red Bulls; it wasn’t until week 12 that the Red Bulls breached the top four, but by week 14 they found their place at the top of the Index.
- At no time did the CPWP Index have fewer than six of the eventual playoff teams out of the top ten. And by week 25 nine of the top ten teams in the Index were bound for the playoffs.
- Accuracy in predicting the top ten teams making the playoffs was no worse than 60% at any given time – and as high as 90% accurate by week 25.
- The CPWP Index, and the sub-indices for team attacking and defending, show great value in looking to understand where failure/success may be occurring relative to team results.
- It’s evidence – one piece of evidence – that shareholders should pay attention to when looking to make changes – it is not a substitute for what the eye sees or the gut feels.
- I know more can be offered in drilling down into individual statistics relative to these team statistics.
You can follow me on twitter @Chrisgluckpwp.
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No European team can match the league domination that Bayern Munich has shown this year in the Bundesliga. However, in spite of Die Bayern’s efforts to run away with the title, the German premier division is still awash with fascinating stories.
The race for the remaining Champions League spot could not be closer – five teams are separated by a mere two points. And no, that excludes Dortmund, who are floundering in the relegation zone.
To set the stage here’s the five teams vying for that third and final spot: Bayer Leverkusen; Augsburg, Monchengladbach, FC Schalke, and TSG Hoffenheim.
Here’s where they compare with each other in my Composite Possession with Purpose Index:
From this it would seem pretty obvious that Bayern Munich also stood out way above all others in the CPWP Index.
In addition, it’s good to see the Index also shows a marked difference, in overall team performance, between Wolfsburg and the other five teams battling for the final UEFA Champions League spot.
Of all the leagues I evaluate, using my Possession with Purpose Family of Indices, this League usually shows the best overall correlation.
Meaning, for some, it may be far more predictable – in other words perhaps the Bundesliga is a great league to bet on game results?
If you do that sort of thing here’s what the CPWP Predictability Index looks like:
A reminder – the CPWP Predictability Index was developed after I had some great discussions with folks at the World Conference on Science and Soccer 2014.
Myself, Ben Knapper (Arsenal FC Head of Stats) and others at PROZONE sports all agreed that the Index ‘could?’ have value as a predictability model if Goals Scored/Against data was removed.
The teams with Green Bars are the five teams battling for the third and final UEFA Champions League spot – the Purple Bar, Borussia Dortmund, is highlighted simply because they ‘should’ be winning – given their talent – but they aren’t!
But… could this be a model to actually reinforce Borussia Dortmund still remain a team who can make UEFA Champions League next year even though they are 13 points behind Bayer Leverkusen? I wonder what the odds are on that?
If you missed my presentation at the WCSS of 2014 here’s a link – in the seven months of this blog it has been my most viewed/read article.
Here again the top two teams are tops in the Index.
For those thinking the best in attack is what drives success it appears FC Schalke and then Bayer Leverkusen are best situated to push forward – while Augsburg slides way back towards Borussia Dortmund.
In taking a look at FC Schalke versus Bayer Leverkusen what separates them in this Index seems pretty interesting.
- Schalke average more total passes by volume (452 to 399) but within the Opponent’s Defending Final Third Leverkusen average more passes (155 to 120).
- To go with that, Leverkusen averages more possession (52% to 50%) but lower overall passing accuracy both within and outside the Opponent’s Defending Final Third (68%/57% compared to Schalke at 76%/61%.
- Meaning Schalke offer more passes, accurately, prior to entering the Final Third while also offering fewer, more accurate passes, once they’ve penetrated.
Looked at from a Leverkusen viewpoint – Bayer actually possesses the ball more – but is less accurate in that possession. In addition they also look to penetrate far more frequently than Schalke.
When digging into the shots area – Schalke show more patience in taking fewer shots by volume and percentage but both teams end up with roughly the same volume of Shots on Goal and Goals Scored per Shots on Goal (36% for Leverkusen and 34% for Schalke).
- Put another way – each team shows different statistical trends in possession, accuracy, penetrating, creating, and taking shots but their overall results are the same.
- Reinforcing, at least in my view, there are a number of different systematic approaches that will get you to the same place.
Before moving on to Defending PWP I think there is value in taking a look at Augsburg. Earlier this week I did an article on Major League Soccer called “Getting More from Less“.
The intent was to see who did better last year, in MLS, in getting better results with lower team performance. My gut-check example to quantifying the results in MLS was West Ham and their Direct Attacking nature.
What I determined was a team who averaged fewer passes than the League Average (both within and outside the Opponent’s Defending Final Third) with less than 50% possession could be reasonably called a Direct Attacking Team.
In looking at Augsburg here’s their attacking data as it fits that mold.
Overall dead on average in Possession at 50%.
Passing Accuracy (entire pitch), 73% – less than the League Average of 74.25%.
Passing Accuracy within the Opponent’s Defending Final Third (56%) – less than the League Average of 57%.
In looking at volume – Total Average Passes for Augsburg was 413 – the League Average was 435
Total Passes within the Opponent’s Defending Final Third for Augsburg was 114 – the League Average 126.
So on the surface it would appear that Augsburg shows the tendency to play more Direct Attacking, as opposed to a Counter-Attacking ‘tactic’, within a Possession-based game.
For Augsburg – they’ve had eight games that have followed the mode of Direct Attacking – they’ve won five of those games. Pretty solid in getting more from less – but can they sustain that?
The West Ham review showed they have won 7 games out of 11 games where their team averages fell into the Direct Attacking mode.
It would seem Augsburg are almost as successful (percentage wise) in matching West Ham when it comes to winning games where their performance falls below League Average… (63.63% for West Ham versus 62.5% for Augsburg).
Augsburg, like West Ham, are pretty high up in the Defending PWP Index (Hammers are 6th best in the EPL DPWP Index versus Augsburg who are 4th best here).
So the value of a higher team performance in defending helps sustain success with the lower volumes offered up in attack.
Meaning the will of Augsburg rides more with a collaborative approach, in overall team play, than strictly an attack dominated performance.
Monchengladbach is next highest here, while TSG Hoffenheim doesn’t seem to shine in either Index.
I’d expect some long odds on TSG making that third and final UEFA Champions League spot…
So what separates Monchengladbach from TSG?
- Goals Against – for Monchemgladbach their GA is .94 – for TSG it’s 1.47 – is that down to Mochengladbach simply having a better Goalie?
- Maybe… their opponent’s actually average more Shots on Goal (5.35) compared to TSG, whose opponent’s average 4.5 Shots on Goal.
Opponents for both teams average total passes, both within and outside the Defending Final Third, greater than the League Average – so by and large most opponents are playing possession based attacking against these two sides.
Where it gets interesting is the volume of successful passes by their opponents after they’ve entered their Defending Final Third.
- In the case of TSG, the opponents average 20 fewer successful passes, with almost the same amount of shots taken and shots on goal.
- Meaning, to me, TSG are finding themselves out of position more often as the screws tighten – hence the greater Goals Against.
In other words one team may be playing more man-to-man while another team may be playing more zonal?
I’m not sure which – those with video or access to X,Y coordinates may know that better?
Anyhow – clearly the data points towards one team having a different defensive scheme that may also include Mochengladbach simply having a much better Goal Keeper.
Half the season remains and while Bayern is basically blowing the Bundesliga away there are others who are still making this league worthy to watch.
Will it be the West Ham of the Bundesliga (Augsburg)? Can Borussia Dortmund pull it back? How about the other challengers who appear more steady, like FC Schalke, Bayer Leverkusen, or Monchengladbach?
And does TSG Hoffenhein really have a chance as well? For some I bet UEFA Champions League is the goal for next year – but others might also be shooting for Europa too.
And this doesn’t even broach the topic about who gets relegated – Might that Borussia Dortmund ends up in that race instead? Wow…….
Jürgen Klopp would get clobbered if that happens!
More to follow…
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You can follow me on twitter @chrisgluckpwp
Republication/update: My intent, this past year, was to update my series on Expected Wins, with EW-5 – that has changed. After conducting research and analyses, and seeing my work published in London, England I’ve decided to rename this series Expected Losses instead of Expected Wins.
- Why, because my data analyses is beginning to show it’s easier to track and predict losses as opposed to ‘draws’ or ‘wins’.
But to sustain the integrity of the ‘thinking process’ I’m only going to edit the first part of this article and remind folks about the previous research published:
- Expected Wins Original – Published April 2014
- Expected Wins 2 – Published May 2014
- Expected Wins 3 – Published September 2014
What follows is the original, unedited post offered in November of 2014. I think if you read this article below you may find it striking given the current conditions with US Soccer and the US Men’s National Team!
Jurgen Klinsmann made a statement the other week about his preference that players working to make the USMNT play in Europe not in America.
Lots of hoo-haw followed with opinions being thrown out there by just about everyone.
As far as I know no-one has, as yet, come up with a way to quantitatively measure which league, leagues, or competitions are higher quality.
This is my attempt to do that using my Possession with Purpose Analysis.
Be prepared for a few charts – sorry – it is what it is and a statement like Klinsmann’s deserves to have some quantitative analysis thrown towards it.
Finally, if you missed Expected Wins 3 here is a link to give you some history on this quantitative analysis.
Now for the grist, first the array of Expected Wins 4 diagrams for each league/competition I cover, Major League Soccer, English Premier League, La Liga, Bundesliga, UEFA Champions League, and the World Cup of 2014.
Major League Soccer – End of Season:
English Premier League after 240 Events (120 Games):
La Liga after 238 Events (119 Games):
Bundesliga after 214 Events (107 Games):
UEFA Champions League after Round 5 – 160 Events (80 Games):
World Cup 2014 – End of Competition:
In each of the diagrams I highlighted in green the category that had the highest volume for all my PWP Data Points.
For example, just above, in the World Cup of 2014 the winning team had the highest volume of activity for every single PWP data point.
The same holds true for the UEFA Champions League, La Liga, and the English Premier League.
The conclusion here? Volume speaks volumes…
Greater numbers of passes both outside and within and into the Attacking Final Third (RESULT) in MORE Shots Taken, MORE Shots on Goal and MORE Goals Scored!
In the case of the Bundesliga (an oft mentioned counter-attacking league) it’s the losing teams that offer MORE Possession and MORE overall Passes but when it comes to the Attacking Final Third it’s the winning teams who do MORE with MORE!
With respect to the MLS – a contrast to be sure. MORE Passing outside and within, and into, the Attacking Final Third gets you LESS when it comes to Shots Taken, Shots on Goal, and Goals Scored.
Why is that?
I’d offer it’s down to playing a game that has less overall ball control from the players – in other words there is less quality on the pitch to take advantage of the MORE for MORE systematic outputs we see from all the other leagues/competitions; others may have a different view.
For me, this is an early indicator that what Jurgen Klinsmann offered is quantitatively accurate!
Before moving on here’s how all the leagues and competitions compare to each other in one diagram for winning teams:
The UEFA Champions League leads all competitions/leagues in the average volume of Passes Attempted, Passes Completed, Passes Attempted within and into the Final Third, Passes Completed within and into the Final Third, Shots Taken, Shots on Goal, and Goals Scored.
If volume of activity (were?) to be a quantitative measure of quality then it’s pretty clear the UEFA Champions League HAS the highest quality of all these competitions.
And what teams comprise the UEFA Champions League? Teams from Europe…
But there is more to Possession with Purpose than just volume; here’s how the PWP Data Relationships show:
In looking at the percentages here’s where it gets interesting – and reinforces what I’ve felt and thought all along, patience in creating time and space in the Attacking Final Third has value.
In terms of Possession Percentage, Passing Accuracy across the Entire Pitch, and percentage of Penetrating Possession within and into the Attacking Final Third the UEFA Champions League, again, exceeds all other competitions.
Where the patience virtue comes in is when it comes to the percentage of Shots Taken per Penetrating Possession – the UEFA Champions League is lowest (14.98%).
So in returning back to the volume of Shots Taken per penetrating possession.
The UEFA Champions League has the highest volume of Shots Taken but the lowest percentage rate.
So even with the third worst percentage of Shots on Goal per Shots Taken and the second worst percentage of Goals Scored per Shots on Goal this competition still has the highest volume of Shots on Goal and Goals Scored.
For me this is another quantitative means to substantiate what Jurgen Klinsmann offered about encouraging Americans to get better by playing in Europe.
Is it better to play on a winning team in a league where there is less overall control of the ball, on the pitch for 90 minutes?
Or is it better to play on a losing team (for 90 minutes), against top quality players, in a league where there is superb control of the ball across the entire pitch for 90 minutes?
Which competition forces you to concentrate more recognizing that the smallest positional error will completely punish your team?
In other words…
If you were a good player and you wanted to get better, would you prefer to play in a league where there are fewer passes and a more wide open play that doesn’t stretch your talent to control the ball?
Or…. would you rather play in a league where the ball is zipping about (by over 100 to 300 passes more) forcing you, in turn, to zip about yourself to try and better manage that game yourself with your teammates?
If I were a player in today’s market there is simply no need to consider answering that question any further – I’d play in Europe OR at least strive to play in Europe!
How about you?
If you’re new to Possession with Purpose and this analytical approach read here for an introduction.
By the way – even if you feel or think you don’t need this type of data to substantiate which leagues or competitions are better today – it will provide a great benchmark in looking at how the future takes shape in MLS.
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You can follow me on twitter @chrisgluckpwp
Is Borussia Dortmund really that bad?
Doubtful, but it’s results like these that are a nightmare for supporters, members of the Coaching staff and Front Office types alike.
So with the ability to evaluate team performance (outside of just results) what better team to run through the Possession with Purpose grinder?
(Edit) – Latest sees them lose to Eintracht Frankfurt 2-nil!!!! Really – oh my!
To begin – my weekly update on the CPWP Strategic Index:
So… third worst in the League Table Dortmund and sixth worst in the Index.
Not much difference. So perhaps Dortmund is experiencing more than just bad luck?
The first place I’ll start is team Attacking performance compared to others; here’s the APWP Strategic Index for your consideration:
Since they average just 1.17 points at home and .67 points on the road I won’t peel back how they perform home and away – no point – there are poor in team performance either way. For now the PWP key indicators:
Overall 57.51% (2nd highest in Bundesliga). Can you say this team has no possession with purpose?
They are 2nd best overall in possession and tied for sixth worst in overall goals scored!
Now a game is not won or lost solely on possession – there is more to PWP, and the game, than that.
Overall 76.95% (4th highest in Bundesliga). So with strong possession numbers they also have significantly higher passing accuracy percentages.
In other words they do a great job of passing the ball overall. Oddly enough that passing accuracy of ~77% is still 1.25% below the average for teams in Major League Soccer. I wonder… are the majority of players in MLS just as skilled in passing the ball as those in the Bundesliga?
Montreal Impact – who finished 4th worst in the MLS CPWP Strategic Index had an average passing accuracy of 76.90%; only .05% points different than Borussia Dortmund.
Is this an early indicator that the team performance in attacking IS as bad as it looks?
Percentage of Penetration per Possession:
Overall 24.19% (5th highest in Bundesliga). It should be noted that a partner, at that position, is Werder Bremen, they sit just behind Dortmund at 23.90% and are just one point behind them in the League Table.
So it doesn’t necessarily mean a good thing to penetrate at a high frequency – sometimes lower penetration percentages yield good results.
For example Wolfsburg, who are 2nd best in the League Table, are 12th best (20.49%) yet their average goals scored is 2.00 per game.
Of note, Dortmund’s passing accuracy within and into the Attacking Final Third is 60.76%; that average is still 5th highest in Bundesliga – so it’s not the drop-off in passing accuracy causing issues in attack.
Shots Taken per Penetrating Possession:
Overall 17.57% (12th highest or 6th worst).
So a remarkably high percentage of penetrating possession yet a lower, than average, percentage of shots taken drops off considerably. Again, this is not necessarily bad. For some teams this number is lower, for example Bayern Munich has the lowest percentage of shots taken per penetrating possession (13.27%).
And Wolfsburg, who sits 2nd in the League Table sits at 21.26%.
I would submit Dortmund is getting shut down easier as they penetrate the opponents 18 yard box – meaning, for me:
- A lack of vision, by a midfielder or two, in creating cutting passes that open up the angles to take better shots, and
- A striker, or two, who simply fail to take advantage of time and open space when they find that time and open space.
Shots on Goal per Shots Taken:
Overall 31.28% (6th worst in Bundesliga).
Speaking again to this team not executing well enough to create the appropriate time and open space to take quality shots. Recall that Bayern Shots Taken per Penetrating Possession was 13.27%; their overall Shots on Goal per Shots Taken shoots up to 40.54%.
Even Wolfsburg, who are 2nd to Bayern sit at 40.31% in this indicator.
Reinforcing, in my opinion, the need for Dortmund to do a better job in creating time and space!
Goals Scored per Shots on Goal:
Overall 18.41% (2nd worst in Bundesliga).
Not much to offer here that hasn’t already been offered – the striking partnerships and attacking midfield support is simply not good enough to work their way past a packed 18 yard box… the quality needs to get better – and perhaps that quality gets better by slowing down the overall volume of passes and penetration.
In other words play the defense back-four a bit deeper in order to lull the opponent into over-committing a bit more… a typical counter-attacking strategy used by many in the Bundesliga already.
By the way – even Montreal Impact, in the MLS sits at 35.83% when it comes to scoring goals based upon shots on goal! And no single team in MLS was worse than 19.53% – with the average at 32.81%.
If supporters who follow Montreal Impact are disappointed given how poorly that team performance was I can’t even begin to imagine how disappointed the entire family of Borussia Dortmund is at this stage of the season.
Some significant progress really needs to be made in team performance if this team is to get better results!
In moving on to Defending team performance and the DPWP Strategic Index:
Borussia Dortmund are 5th worst in the Index – so not strong in attacking nor defending team performance!
Opponent Possession Percentage:
Overall 42.49% (2nd lowest in Bundesliga).
Noted, but as we’ve seen in all the leagues I analyze possession percentage, alone, is not a good indicator.
Opponent Passing Accuracy:
Overall 69.63% (3rd lowest in Bundesliga).
Given what I feel is a higher amount of counter-attacking football in Bundesliga this percentage is not surprising.
What is more surprising, however, is that the opponent’s for Dortmund have just a 49.33% passing accuracy within the Dortmund Defending Final Third. That is alos 3rd lowest (best) in Bundesliga.
Basically what this means is the opponents of Dortmund really don’t pass the ball very well – or – they play longer balls or offer quicker play given Dortmund attackers being caught out of position during turnovers (anywhere).
For me, this speaks to Dortmund playing somewhat deeper and somewhat less aggressive in attack – in this case give up the idea of trying to emulate FC Bayern Munich and instead look to play more counter-attacking more often.
Opponent Penetration per Possession:
Overall 18.25% (2nd lowest in Bundesliga).
In adding up the details so far, Dortmund yield the 2nd lowest amount of possession, play opponents who are 3rd worst in passing accuracy and 2nd worst in penetration, yet they give up 1.58 goals against per game!
Opponent Shots Taken per Penetrating Possession:
Overall 20.42% (6th highest in Bundesliga).
Again, the numbers are showing a very poor pattern of team performance.
Opponent Shots on Goal per Shots Taken:
Overall 44.85% (2nd highest in Bundesliga).
Goals Scored per Shots on Goal:
Overall 43.69% (2nd highest in Bundesliga).
Complete bollocks is what I would offer; their overall team performance really is as bad as their results!
Borussia Dortmund play against opponents who are downright terrible in possession, passing accuracy, and penetration, yet…
When it comes to Defending their own Final Third the opponents are downright SUPERB when it comes to taking shots, that end up as shots on goal and goals scored.
I did some analyses on the Portland Timbers this year – and their early pattern of defense showed the same results as Dortmund.
In the end, after at least two tactical adjustments in defending, the Timbers finally got squared away. From a tactical viewpoint the corrective action was to drop deeper, roughly 10 yards deeper, and clog the 18 yard box a bit more.
In turn, this adjustment led to an increase in goals scored and a reduction in goals against.
Perhaps this is a reasonable tactic that Dortmund take as this year continues?
I’m not sure, but another diagram to consider is the CPWP Predictability Index shown below:
In looking at the Predictability rating it shows Dortmund’s position excluding goals scored and goals against. By all accounts this Index tends to support that Dortmund should be doing much better than they are.
One way to interpret this Index is to say that performance, outside and leading into the Final Third (on both sides of the pitch) is solid, where the weaknesses show themselves are in 1) the final creation/finishing, and 2) the final defending/goal keeping.
If that is reasonable then their current issues are not just down to one or two players; it’s more systemic.
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You can follow me on twitter @chrisgluckpwp
When a team is simply the best a picture speaks a thousand words…
Rarely do I ever focus on just one game in my analyses but I think it’s worthy to spend just a wee bit of time on the Bayern – Bremen match to really drive home what my Family of Indices can show.
Here’s how the two teams matched up in Week 8 using my PWP data array:
I’m not sure the obnoxious dominance of FC Bayern Munchen can be pictured any more clearly than this without some creative graphics.
So is Werder Bremen really as bad as this one game shows?
Before Week 8 here’s where they stood in the CPWP Strategic Index:
Sixth from the bottom, so in the space of one week they’ve gone from 6th worst in overall PWP to worst…
I’ll call that the Bayern Bruise… both Stuttgart, FC Koln, Paderborn, and Hamburger have felt that to some extent as well…
That being said, Bremen have played all the top teams in the Index apart from FSV Mainz and Mochengladbach – so is it any wonder their near bottom?
Hmmmm… not so sure but they have yet to play Hamburger, Stuttgart, Frankfurt, Paderborn, Augsburg, or Dortmund. Most likely meaning, with the exclusion of Dortmund, some points are to be had.
Can they get them though? I’m not so sure.
After Week 8 they are sixth bottom in the APWP Strategic Index – and yes, they have played most of the top teams in the Bundesliga – and when peeling back the attacking team performance data it’s not anemic by any stretch.
They are 7th best in converting Shots on Goal to Goals Scored (>35%)… usually that means a bit of patience to go along with a bit of time and space to get goals.
They are 10th best in having their Shots Taken be Shots on Goal (>35%)… another indicator that time and space is being created to generate accurate shots – even against some of the better teams in the Bundesliga.
They are 7th lowest in taking Shots per penetrating possession (>17%) – for the most part a lower percentage here is not a bad thing – it usually indicates patience, along with taking a bit more time to create space.
Indeed, the top team in having the lowest percentage of Shots Taken per penetrating possession is FC Bayern (11.55%).
They are also 5th best in their percentage of possession resulting in penetration (24.45%).
Where things go pear shaped is overall Passing Accuracy and Possession; they are the worst team in the Bundesliga when it comes to Passing Accuracy (64.39%) and only Paderborn has less possession (37.68% to 43.93%).
So what’s that mean?
From an attacking standpoint in and around the 18 yard box all seems very good – usually meaning they have at least one good midfielder with vision and at least one good striker who can score goals.
But, with the poor passing accuracy and overall possession it may also mean there are some defensive weaknesses bleeding over to impact that attack, like having too many turnovers in their defensive half, or/and
Playing the ball a bit too quickly out of their Defending Half, or/and
Their back line may be defending too high, or/and
Their central midfielders just aren’t good enough to control the run of play between the Defending Final Third and Attacking Final Third…
So in considering potential Defending issues bleeding over to impact the Attack here’ how they compare to others in the Defending PWP Strategic Index:
Dead last – of course some of that may have to do with the Bayern Bruise syndrome – but even after Week 7 Werder Bremen was still 2nd worst. So the Bruise is there but not as deep based upon Bayern as one might think.
In terms of overall performance here’s a few observations for consideration:
Opponents average 73.25% Passing Accuracy – in other words the opponent is doing better at completing passes than Werder Bremen – weaknesses, it would seem reasonable, exist in the overall talent of this team compared to others…
We already know they are second worst in overall possession. Now is that down to how the Coach likes to run a specific system – or is that down to simply having weaker players than the opponent?
Not sure yet – but it’s a good bet that Werder Bremen is looking to play counter-attacking football and that style, coupled with poor passing accuracy is compounding the issue.
In terms of goals scored against – even when you take the six goals out of the equation that Bayern scored – Werder Bremen still average 2.29 goals against per game.
The worst in the Bundesliga – so now only do they have a lower skill level in overall passing it would seem to be that they also have a back four – and goal keeper – who simply aren’t good enough at closing down the time and space the opponent needs to score goals.
A similar pattern appeared with Philadelphia Union this year in Major League Soccer – the solution to stop that goal rot was simply a move by the new Head Coach to have his defenders drop deeper – about 10 yards deeper to be exact.
When that happened the goals against for the Union went from 1.71 to 1.25…
It’s still early days but eight weeks are gone and trends ARE forming – Werder Bremen is NOT showing the team indicators that point to a side who’s had bad luck – they are pointing to a side that aren’t that good…
But it’s not too early to remember that the best indicator for a team taking a nose dive in overall performance is defending – and right now Werder Bremen is not defending as well as a team should do if they expect to finish near mid-table as they have in the past.
If things continue like this it is likely this team gets relegated – and an offering up of that after just eight weeks should be enough time for the organization to make the appropriate changes to right the ship…
It’s a tough hill to climb but if 13th or 14th is to be realistic again this year then things need to change pretty bloody quick.
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If you’ve read these two previous articles, Expected Wins and Expected Wins 2, you know I look at how teams perform, on average, (win, lose, or draw) with respect to my primary data collection points for Possession with Purpose.
What will be added, in Version 3 (V3), will be a compare and contrast between all the leagues I evaluate in my Family of Indices.
Results of looking at the diagrams and reading through my observations should help clarify analyses like (ABAC, ABCB) doesn’t really have relevance to teams that win, lose or draw – at least not this year. (Note – two links – two different sites published roughly the same analysis)…
Don’t get me wrong – I’m not taking a personal dig at the grueling work associated with the analyses.
It has great value, but more from a tactical viewpoint in how passing is executed, not from a (bell curve) – volume/success of passing rate – relative to possession and penetration into the Final Third, that helps a team create and generate shots taken leading to goals scored; or… when flipped, leading to goals not scored.
And as pointed out by a (shomas) on the article, that surfaced on MIT, if anything, it adds predictability to what a team will do – and the more predictable a team, the more likely the opponent can defend against them better…
For me – I would have thought the GREATER the variation in that cycle(ABAC, etc…) the better… others may view that differently?
In addition, I think there could be more value, to the information, if it was segregated by league – more later on that…
To begin – here’s a reminder of what Expected Wins looked like in Major League Soccer after 92 games (184 events):
The term ‘event’ is used, as opposed to game, to clarify that each team’s attacking data is include in this analyses – and that the greater the volume of data points the stronger the overall statistical analyses is; i.e. sampling 15 data-stream points is not the same as sampling 1000 data-stream points.
Biggest takeaway here is the strength of correlation these seven data points have to each other (i.e. their representation – in my opinion – of the primary bell curve of activities that occur in a game of soccer)…
In every case, in every diagram that follows, all the Exponential trends exceed .947; and in every case the relationship for the winning teams is higher than the relationship for losing teams… speaking to consistency of purpose and lower variation in my view.
In general terms. this is my statistical way of showing that a goal scored is tantamount to a 5th or 6th standard deviation to the right from the normal bell cuver of activities that occur in a game of soccer.
Said another way – I don’t evaluate the tail – when measuring the dog’s motion – I evaluate the dog; recognizing that the tail will follow, to some degree, what the motion of the dog will be… and… that even if the motion of the dog is somewhat different, the tail will normally behave in the same way.
Therefore, it’s not the tail that should be analyzed – it’s the dog… others may view that differently.
Here’s the same diagram for the MLS after 366 events:
Oh… the green shaded areas are meant to show those data points that are higher for those particular categories; in other words the Volume of Shots Taken for winning teams (after 366 events) was higher than that of losing teams – but the volume of passes completed in the Final Third was higher for losing teams than winning teams… more on that later.
Here’s the diagram after 544 events in MLS:
Note the shift – only the volume of Final Third Passes Attempted is now higher for losing teams – all other data categories see the winning teams with greater volume.
For me, what this reinforces is the issue of time and space as well as patience – three statistics never measured in soccer (publicly at least)… again, reinforcing, for me, that shot location only has value relative to the time, space, and patience of the team in creating that time and space for that shot.
Statistically speaking, what that means, to me, is that Expected Goals; a very popular (and worthy) statistical calculation, needs to be refined if it’s to have greater value as a predictive tool/model… I’d be interested to hear / read the views of those who work Expected Goals efforts…
Now here’s the European Leagues I’ve added to my PWP Family of Indices analyses; first up the English Premier League:
Note that the pattern, here, after 100 events, resembles the same pattern for MLS after 544 events… worthy.
Moving on to the Bundesliga:
A pattern similar to MLS after 366 events; will this pattern morph into something different as the league continues? Possibly – the MLS pattern has changed so perhaps this one will too?
Now for La Liga:
A completely new pattern has taken shape – here “volume” speaks volumes!
Is this unique? Nope… It also happens to be the same pattern as the World Cup 2014 pattern – below:
Will that pattern show itself in the UEFA Champions League? I don’t know but we’ll find out…
So what’s it all mean? The “so-what”?
Before attempting to answer that, here’s two different diagrams plotting these data points for winners and losers (in reverse order) for the leagues I evaluate:
Now the grist:
The red shaded areas are where the losing teams’ average exceeds the winning teams’ average in the volume of those activites – the green shaded areas are highlighted for effect. Green shaded areas for the volume of Shots on Goal and Goals Scored indicate that those numbers are virutally the same, for winning teams, in all the activities measured…
Now, back to the so-what and what’s all mean?
For me this reinforces that the “pattern” of passing (ABAC, ABCB, etc…) that gets you into the Final Third has no relevance to the volume of Goals Scored.
And, it also reinforces that different motions of the ‘dog’ will generate the same tail wagging outputs – therefore it’s the analysis of the dogs activities that drive greater opportunities for improvement.
The averages for winners in the activities measured all behave somewhat differently – granted some patterns might be the same but the volumes are different.
And when volumes change, the game changes, and when the game changes, the strategic or tactical steps taken will change – but… the overall target should still remain the same (on average) – put at least 5-6 shots on goal and you ‘should’ score at least two goals… getting to that point remains the hard part!
Bottom line here:
These leagues are different leagues – and the performances, of the teams, in those leagues are different when it comes to winning.
Therefore, I’d offer that comparing a striker’s ability to score in one league is completely different than an expectation an organization might have in how that striker may score in another league.
Said another way – a striker who scores 20 goals in the Bundesliga, a league that shows winning teams play to a more counter-attacking style, might not perform as well in a league like the EPL; which looks to offer that winning teams play a more possession-based style.
Perhaps??? another good example… a striker playing for a team that counter-attacks, is more likely to have greater time and space to score a goal, than playing in a possession-based team where time and space become a premium because the opponents play far tighter within their own 18 yard box.
But, as mentioned before – since no-one statistically measures (publicly) the amount of time and space associated with passing, and shot taking, we can’t peel that onion back further. I have suggested two new statistics that may help ‘intuit’ time and space – that article is “New Statistics? Open Shots and Open Passes”: here.
For the future… I’m interested in seeing how these analyses play out when separating out teams who show patterns of counter-attacking, and perhaps direct play, over teams that show patterns of possession-based football.
In addition, I’m also keen to see how these take shape when reversing the filter and organizing this data based upon whether or not a team is defending deeper, or more shallow.
The filter there will come from looking at the opponent averages for passing inside and outside the Final Third…
It seems reasonable to me (others may view this differently?) that the if a team lacks goal scoring they need to find the right midfielders and fullbacks that are good enough to create the additional time and space the strikers need in order to score more goals.
And that doesn’t even begin to address the issues in defending – which statistics continue to prove year in and year out as being more critical to winning than attacking.
Given all this information, I may have missed something – I’m always looking for questions/clarifications so please poke and prod the diagrams and analyses and comment as time permits.
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You can follow me on twitter @chrisgluckpwp
Perhaps still too early? I don’t think so – at least not with who’s the best – clearly FC Bayern Munchen are firing on all cylinders. So…………
What to do?
Well, I’ll be ignoring FC Bayern Munchen in this effort because they are simply head and shoulders above everyone else… give me about another month or so and I’ll do a special week on Bayern.
For now my focus goes to FSV Mainz (eight points), TSG Hoffenheim (eight points) and FC Paderborn (eight points).
And yes, there are games being played this week where the data you are offered will not be up-to-date —> I gotta have a stop/start point somewhere – so I chose Monday evening… 🙂
Now, to begin, here’s my customary link for those new or wanting a refresh on Possession with Purpose – An Introduction and Explanations…
And now my CPWP Strategic Index through Week 4:
I’m not sure the clarity can be any more clear that Bayern is clearly the leader in PWP.
For now it’s worthy to note that my PWP End State, ””try to match the league table as close as possible without using points”’ looks pretty good as the 6 best teams in CPWP match the six best teams in the Bundelisga League Table – not one-for-one, but close enough to again lend credence to this effort.
Statistically speaking, the correlation (R2) to average points in the league table is .75; still strong.
Will these teams stay in these positions as the season wears on? Maybe Bayern will but the others? Probably not – but it helps to begin peeling back info on certain teams now to get a better sense of their progress (success or failure) for the future…
Anyhow – time to peel back the attack of Hoffenheim, Paderborn, and Mainz in my APWP Strategic Index:
It should be worthy to note that Hoffenheim, Mainz, and Paderborn fall below Werder Bremen, Hertha Berlin, and Wolfsburg – in short what that means is the three teams I’m focusing on have better team defending performances than those other three teams…
Defense usually wins out when both teams are good in attack – so it will be interesting to see how these teams compare as the season progresses; for now here’s some key attacking statistics I’ve seen w/r/t Hoffenheim, Mainz, and Paderborn:
- Passing Accuracy – a surprise here for me is that all three of these teams, average in passing accuracy, falls below the league average of 74.13%; Hoffenheim ~66%, Mainz ~72%, and Paderborn ~71%.
- At first glance, without watching any of their games, I’d offer these three teams tend to play counter-attacking football where the intent is to take advantage of the opponent getting out of position. Another indicator to support that is overall possession – Mainz sits on ~49%; while Paderborm and Hoffenheim are lowest and 3rd lowest in the Bundesliga, respectively (37.69% and 42.96%).
- Without looking ahead, a key indicator to me that supports my initial view is the volume of passes the opponent has in their Defending Final Third – more later…
- In terms of Shots Taken per penetrating possession – Hoffenheim are below average (resembling teams that I’d attribute the word patience to) at 15.38%, while both Mainz and Paderborn are slightly above average (21.75% and 22.03% respectively).
- When it comes to converting Shots Taken to Shots on Goal – Hoffenheim, again, is below average (~28%) while both Mainz and Paderborn are above average (~48% and ~38% respectively).
- In looking at Goals Scored – all the teams are above average with Hoffenheim the highest (~60%) – while Paderborn is next up at ~40% and Mainz (9th overall) at ~33%.
What’s all that mean?
- Well it appears to me that Hoffenheim best represent a team who counter-attacks but does so with caution/patience – in other words there isn’t as much ‘abandon’ in their run of play when penetrating… i.e. they look to catch their opponent out of position, and when they do they are very good at executing in that small window of opportunity.
- Perhaps someone who watches Hoffenheim more closely can add some thoughts in the comments section?
- With respect to Paderborn and Mainz; again, without seeing them play, I’d offer they adopt a slightly riskier (more direct?) approach to penetration when they can.
- And that increase in risk may drive down their patience and accuracy in creation and generation of shots – which in turn drives down their efficiency in goal scoring based upon their volume of shots on goal.
It should be noted, however, that all three teams have eight points after four games – and given those apparent strategies is it surprising to see that FSV Mainz and Paderborn drew 2-2 the first game of the season?
In moving on to my DPWP Strategic Index:
Recall that Hertha Berlin, Werder Bremen, and Wolfsburg were all stronger in APWP than the three teams I’m focusing on this week – when viewing DPWP, Hertha is bottom, Werder Bremen is 2nd bottom and Wolfsburg are almost near mid-Index…
On the other hand Paderborn, TSG Hoffeneheim, and FSV Mainz are all in the top half… kind of continues to reinforce that a team who defends better will get better results…
So here’s a look at the volume of passes and passing accuracy percentage for their opponent’s in their Defending Final Third.
- Here, I expected these numbers to be slightly higher than others – to indicate some ceding of possession and space higher up the defending final third.
- Of the three, Paderborn had the lowest percentage of opponent penetration in their defending final third (19.46%) while ceding the 6th highest volume of passes in their defending final third (131 per game)
- Hoffenheim yields the 5th highest percentage of opponent penetration in their own defending third (24.68%) while yielding the 4th highest volume of passes (134.50 per game) in their own final third.
- Mainz yields the 6th highest percentage of opponent penetration in their own defending third (24.40%) while yielding the 11th highest volume of passes in their own defending final third.
All told it would appear that all three teams do cede possession and penetration into their defending final third more than most other teams.
In looking at the bottom line (opponent goals scored per game) Hoffenheim average .5 Goals Against while Mainz and Paderborn (before the Bayern thrashing) averaged 1.00 Goals Against per game.
What is missing?
- Borussia Dortmund… wow – talk about a slot start.
- How well these teams perform on the road versus at home – not enough data yet really.
- How each of the teams do against FC Bayern Munchen – playing Bayern will (usually) negatively impact performance.
- Actually being able to watch the games to pulse the statistical expectations based upon lessons learned from tracking statistics and watching the English Premier League and Major League Soccer – this is where I need your help.
- Overall, simply more data – it’s almost rude to expect that four games of data is going to provide anything other than a great start point to begin trending as week 12 or 13 approaches.
- Can you Adam and Eve it on this strike by Moritz Stoppelkamp, a player from FC Paderborn, – statistics simply can’t account for a goal scored like that!
Next up a look at La Liga and then Expected Wins 3… a statistical look at differences between teams that win, lose or draw in the EPL, MLS, Bundeliga, La Liga, that includes a review of the World Cup 2014 outputs…
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For those not familiar with this phrase – Passing domina temprana (Passing dominates early) – get used to it as my Possession with Purpose analyses moves to La Liga.
I’ll get to the details behind that view a bit later but first a look at the traditional analysis on PWP plus an early focus, like with the Bundesliga, on the slow starters.
The Composite PWP (CPWP) Strategic Index through Week 3:
The clear leader here is Barcelona – as noted last week a team passing Barcelona might find it difficult (both on the pitch and in the league table).
Knowing that I’ll prefer to wait on digging into Valencia, Seville, Real Madrid, and Atletico Madrid till a bit later.
For now, since this is a relegation league, like everyone else in the World apart from Major League Soccer, let’s take a peak at teams who’ve opened at a snails pace: Levante, Espanyol, Cordoba, Almeria, and Rayo.
- Levante – bottom feeder – the worst in team performance to begin – enough said.
- Espanyol – while they sit on just one point they are near mid-table in CPWP – that means they are either performing pretty good in attack – or they are performing pretty good in defense – or – they are weak in both, but not REALLY weak yet…
- Cordoba – On two points and near bottom; Malaga have four points and are placed further down – perhaps??? the APWP and DPWP will help shine a light on that?
- Almeria – not quite as good in overall performance compared to Espanyol – but they are higher up the CPWP food chain.
- Rayo – like Almeria and Cordoba they are on two points – oddly enough they are on the positive end of the CPWP Index – more to follow on that.
Next up Attacking (APWP) Strategic Index:
As for the bottom feeders… here you go:
- Levante – again – bottom of the pile. They almost look oxygen starved given their major drop off to the right of Villareal…
- Espanyol – mid-table of the Index – so not overly dominant in APWP – perhaps this means they are roughly mid-table in the DPWP Index?
- Cordoba – about 1/3rd the way up from bottom – nothing eye catching at the moment and certainly showing better team attacking than Malaga.
- Almeria – like Cordoba – about 1/3rd of the way from bottom; are both these teams showing early indications they might be better placed, in the league table, a bit later this year? Hard to say – we will have to wait and see.
- Rayo – again, up near the top half – I suppose that means their DPWP leaves a bit to be desired. Of course the other issue might be who they’ve already played so far this year… Elche, Deportivo, and Atletico Madrid… somehow; even without watching this team play I suspect they won’t stay in the bottom third for long… It would be interesting to hear thoughts from those who follow La Liga a bit closer though.
Moving on to Defending (DPWP) Strategic Index:
As expected – a team with huge passing numbers is likely to be in the top half (at least huge by Barcelona standards). More interesting, and good stead for Villareal, is their position near the top of DPWP.
In looking at the early relegation battle here’s how the bottom five look:
- Levante – near bottom; and given past history on some teams in MLS – I’d say they are an early bet to get relegated – even after just three weeks; provided their defense doesn’t perform better compared to others.
- Espanyol – ah… here’s where things get a bit dodgy; they seem okay in attack and overall yet their defense is what is letting them down. Does that continue? We’ll see…
- Cordoba – like Espanyol – they are near bottom in DPWP – that means of course, that the opponents are not only completing good numbers of passes, but it also means they are penetrating, creating and generating shots taken that hit the back of the net – all told they’ve conceded four goals and scored just two.
- Almeria – a bit higher up the DPWP Index, this may provide an early indication that this team is slightly better than the two points that they have. More to follow…
- Rayo – again quite good and not expected given their APWP and CPWP – those two draws against Deportivo and Atletico Madrid have done them well… as noted in the APWP thoughts; I’d offer this team may not stay in the bottom third for long.
Now for the “more to follow” on this league being a passing league – the CPWP Strategic Index for teams where they have exceeded the league average in volume of passes (415):
Note that Rayo and Levante are in this mix… In considering the poor performances for Levante so far this season is it better or worse that they are attempting to mix it up with some of the other teams who are really – really good at passing?
I wonder if Levante also has games that are below the league average of 415 passes?
To answer that question here’s the CPWP Strategic Index where teams’ passing volume has not exceeded the league average:
Only Rayo is not in the mix for the current bottom dwellers – again that seems to reinforce that Rayo may end up being a bit higher in the table as the season plays on.
In addition, note that Villareal were a better team in overall performance (positive ~.4) when exceeding the league average compared to (~-1.2) when falling below the league average. Having played Barcelona skews that Index rating here I’m sure…. On the flip side they defeated Levante and drew nil-nil with Granada.
And of the teams that don’t pass a lot – does this show (already?) that teams like Deportivo, Eibar, Atletico Madrid, and Real Sociedad are better in counter-attacking and direct attacking than a team like Eiche, Villareal, or Athletic Club?
I’m not sure – but it sure does raise some interesting questions as PWP comes to La Liga.
Before moving on; I wonder how this Index will look at the halfway point of the season… time will tell.
A wrap up of sorts for the five bottom dwellers with a focus on overall passing accuracy:
- Levante – 3rd worst = 70% – the key stat here appears to be goals scored – they have none.
- Espanyol – 8th worst = 75.08% – the key stat here appears to be the opponents ability to put a shot taken on goal – 44.09% – 2nd worst
- Cordoba – 10th worst = 76.62% – the key stat here appears to be lack of penetration (17.27% of their possession results in penetration) 3rd worst
- Almeria – 7th best = 77.72% – the key stat here appears to be controlling time and space in defending – as the opponent percentage of penetration increases so does the percentage of shots taken, shots on goal, and goals scored; in other words their defending percentages get worse as the opponent draws nearer the goal.
- Rayo – 6th best = 78.27% – the key state here appears to an inordinately high percentage of shots on goal faced versus the 2nd lowest amount of possession, by percentage, of their opponents.
Overall, even after just three weeks and the dominant indication on how passing influences CPWP, the Index is still not overly influenced by it when peeling back overall performance.
Still early days though, and the race to avoid relegation has begun.
I’ll not ignore the top half of the table but I’ll also not ignore the bottom half.
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