Category: World Conference on Science and Soccer

Gluck: Fourth Year Anniversary Edition

My thanks to everyone who has supported my web site the last four years!

It’s been a learning experience for me and, I hope, for you too.

As the new year starts I’ve got at least five new articles planned; here’s a quick synopsis on what to expect:

  • Following up on Coaching Youth Soccer Part I and Coaching Youth Soccer Part II, I’ll be offering Coaching Youth Soccer Part III – digging into which team statistics to use, why, when, and how to use them.  For those who don’t know me these three articles highlight my coaching philosophy into one three word catchphrase “muscle memory mentality“.
  • Two new individual soccer statistics:   This (may?) be controversial – My intent is to submit two new, professional level, individual, soccer statistics that could transform the player market value system.

Said differently; are private statistics companies, like Prozone Sports, OPTA, and InStat (along with player agents) manipulating the player market value system by ignoring what might be the most logical, intuitive, individual soccer statistics ever?

  • Expected Points – An updated version of my previously created Expected Wins series of articles.  A follow on to what was offered at the World Conference on Science & Soccer 2017, Rennes, France.
  • Expected Goals – A new way to calculate this over-hyped soccer statistic that brings it a bit closer to reality.
  • World Cup 2018 Total Soccer Index; to include predicting the winners after round one is complete.

For now, in case you missed one or two, here’s my rundown on the top five articles in each of the last four years.

In Closing:

  • I called for Jurgen Klinsmann to be sacked after WC 2014 because his tactics and in-game adjustments weren’t up to snuff.  Three years later the rest of the american mainstream soccer media world agreed and Klinsmann was sacked.
  • I called for Sunil Gulati to be ‘ousted’ after WC 2014 because his leadership in helping youth development and head coach selection weren’t up to snuff. Three years later the rest of the american mainstream soccer media world agreed and Gulati is out.
  • In hindsight – I wonder where we’d be in youth soccer development if we’d have made those decisions three years ago?
  • No, I do not favor Caleb Porter as the next US Men’s National Team head coach.  I like Caleb, he’s a stand-up guy and always took time to share and listen.  That said, in my opinion, he’s not (consistently) good enough at reading in game situations and making tactical adjustments that lead to better performances; the exact same issue I had with Jurgen Klinsmann.  .
  • I’m hopeful either Eric Wynalda or Steve Gans are elected as the next United States Soccer Federation President; electing Kathy Carter is a NO-GO in my view as there’s perceived ‘collusion’ between MLS and SUM.  As a retired Air-Force veteran perception is reality until proven otherwise – some may disagree?

I wish you all the best for the new year.





Possession with Purpose – Prozone – and more…

No detailed statistics today – just a narrative to pass on a few tidbits as I prepare my End of Season analysis for Europe.

The news:

The European Season is ending.

  • There’s the winners, the losers, and those that stay afloat to live another year.
  • I’ll peel back the results on the English Premier League, Bundesliga, La Liga, and UEFA Champions League in the next few weeks.
  • For now, in La Liga the PWP Composite Index has a .94 correlation coefficient (r) to points earned in the league table; the Bundesliga sits at .92, the English Premier League sits at .94, while the UEFA Champions League sits at .87.
  • All incredibly strong and far stronger than MLS (.61) this year; last year MLS finished at .87.
  • Speaking of MLS, does a league, where winners display more characteristics of counterattacking, versus just possession-based attacking, detract from predictability?
  • In other words does the lower correlation support a League’s ability to achieve “parity” in professional soccer?
  • If so, is that style/type of football attractive enough to continue to grow footy in the States?
  • If not – does that mean the business model currently set up in the States won’t ever achieve a league “status” that matches the “prestige” most seem to attach to the top leagues in Europe?
  • More to follow…

I think these two video presentations by Hector Ruiz and Paul Power, from Prozone, are worth listening to.

  • In this video (tactical profiling) Hector, who attended my presentation at the World Conference on Science and Soccer last year, talks about his latest efforts that include breaking down the different types of possession in a much greater detail than I ever could with public data.
  • Of note is Hector substantiates my finding that a Head Coach’s tactical approach can be differentiated through tracking possession (passing characteristics) on the pitch.
  • He also helps begin to solve the riddle on measuring which players perform better or worse given those different styles of possession.
  • A soap-box, for me, when looking at my article on ‘Moneyball relative to soccer’, is the inability of modern day soccer statistics to show real value on how well teammates actually influence an individual’s success or failure on the pitch relative to how the team actually plays (what style it works to).
  • Here’s a direct lift from my article referenced above…

Modern day soccer statistics, for the most part, don’t measure the appropriate level of influence teammates, opposing players, and Head Coaching tactics – as such when I say I’m not a Moneyball guy when it comes to soccer it really means I don’t buy all that crap about tackles, clearances, goals scored, etc…

I value players relative to team outputs and I strongly feel and think the more media and supporters who understand this about soccer the less frustration they will (have) in blaming or praising one individual player over another player.

  • In the next video (game intelligence) Paul takes a similar approach in analyzing team behavior like PWP – separating out defensive characteristics from attacking characteristics while also modeling a ‘defensive press’ that measures success or failure in passing based upon whether or not a defender is hindering the attacker.
  • This topic has been one that I have also touched on last year – here’s a direct quote from my article on Hurried Passes.

So what is missing from the generic soccer statistical community to account for the void in Unsuccessful Passes?  Is it another statistic like Tackles Won, Duals Won, Blocked Shots, or Recoveries?

I don’t think so – none of them generated a marked increase in the overall correlation of those three activities already identified.  I think (it) is the physical and spatial pressure applied by the defenders as they work man to man and zone defending efforts.

  • Likewise, Paul also touches on ‘passing vision’ (in my words it’s not the innate vision many of us think of for players) – it’s more a discussion and analyses (I think) on the ‘windows of passing lanes’ available to players and whether or not they have tendencies to play riskier passes versus safer passes in relation to what the defenders are doing.
  • For me this simply means Paul has taken the same defensive pressure data and flipped it to view the success or failure of a player to find another player to pass to or create a shot given the defensive pressure (lanes/vision) that are blocked or open.
  • In simplistic teams (with new event statistics) you can capture and intuit that success or failure by filtering passes as being ‘open or hindered’ and also apply that same filter to create ‘open or hindered’ shots.  My article on this approach was also published some time ago – New Statistics in Soccer (Open Pass and Open Shot)
  • Finally, Paul also speaks to a game of soccer resembling the behavior of a school of fish; I’m not sure I’m convinced that is the best analogy – especially when he talks about under-loading and overloading, but his view does closely resemble mine where the game of soccer perhaps is best represented by a single-cell Amoeba.

All told – two well crafted presentations that begin to open up and really reinforce some of my soap-box issues with soccer statistics since starting my research three years ago.

To be redundant – soccer is not just about scoring goals – there is more to the game than goals scored; these two presentations continue to support my view that the world of soccer statistics needs to continuously get better…

My back-yard / stubby pencil approach to team performance analysis is soon to be published through Rand.

  • I want to express my sincere thanks to Terry Favero – my Co-Author – who helped me navigate the challenging waters of writing an Academic Paper.
  • Terry added considerable value, as well, in researching other works to help set the stage on the differences of PWP versus other efforts developed and published across the globe.
  • Finally, Terry provided superb editorial support – a challenge in that the writing styles one normally sees in a blog are completely unacceptable when writing an Academic Paper.
  • Great fun and the first of at least two to three more.

Last but not least, the Women’s World Cup is beginning.

  • Last year I applied the principles of PWP to the Men’s World Cup – with good order.
  • I’ll refresh everyone on how that took shape and then begin to chart how PWP takes shape for the Women’s World Cup.
  • I wonder what, if any, differences will show in comparing the women’s game to the men’s game?
  • Will the data show the same trends in quality and quantity?
  • Or will we see a reduction in quantity that may end up driving an increase in quality?
  • More to follow.

Best, Chris

COPYRIGHT – All Rights Reserved.  PWP – Trademark

Possession with Purpose – Revised Introduction

It’s time to offer up another revised version of my Possession with Purpose Analysis.

My intent here is to:

  1. Provide an update that may help simplify this effort, and
  2. Update new links to articles most have found to be of great interest in the last year.

To begin… Possession with Purpose (PWP):

The End State, as always this is good to know up front:

Create an objective Strategic Family of Indices, with publicly made available data, that has relevance and helps identify (explain) the strengths and weaknesses of team performance ‘outside’ the realm of Points in the League Table.

Of note; this analysis has been presented, and received with great interest, at the World Conference on Science and Soccer of 2014.  So it’s not a fly-by-night attempt to offer up analysis that can’t translate back to the soccer and science industry or help inform the general, or well educated, soccer community (both here and across the pond) about Footy…

The Intent:

Create a Family of Indices that measure the ‘bell curve’ of strategic activities that occur in a game of football (soccer); recognizing that in order to score goals the following activities usually need to occur:

  1. Gain possession of the ball
  2. Move the ball
  3. Penetrate the opponents defending final third
  4. Generate a shot taken
  5. That ends up on target and,
  6. Gets past the keeper

From a statistical (measurement) standpoint those activities are organized into these six categories:

  1. Possession percentage
  2. Passing Accuracy across the Entire Pitch
  3. Passing Percentage within and into the Opponents Final Third compared to overall possession (i.e. = Penetration)
  4. Shots Taken per Percentage of Penetration
  5. Shots on Goal per Shots Taken
  6. Goals Scored per Shots on Goal

It’s not a secret formula but I do retain Copyright.

The Family of Strategic Indices – there are three of them:

  1. Attacking Possession with Purpose (APWP)
  2. Defending Possession with Purpose (DPWP)
  3. Composite Possession with Purpose (CPWP)

APWP Index:  How effective a team is in performing those six process steps throughout the course of a game.  Example:


DPWP Index:  How effective the opponent is in performing those six process steps, throughout the course of a game, against you.  Example:


CPWP Index:  The mathematical difference between the APWP Index and DPWP Index.  Example:

CPWP Strategic Index Week 22

The Analysis:

Simply stated, the analysis stemming from this effort is a comparison and contrast between how a team performs (in the bell curve of these activities) relative to other teams in their league “without” including points in the league table.

Statistical Correlation:

Last year the CPWP Strategic Index Correlation (relationship) to Points in the Table, for Major League Soccer, was .77; this year, at the end Week 26, the R is .85.


In returning back to the End State:

“Create an objective Strategic Family of Indices, with publicly made available data, that has relevance and helps identify the strengths and weaknesses of team performance ‘outside’ the realm of Points in the League Table.”

Given the very high level of Correlation these Indices have, I’d say this Family of Indices has considerable statistical relevance; and I should point out that although the PWP approach is an Explanatory Model it can also be leveraged as a Predictability Model.

After speaking with a number of folks at the World Conference on Science and Soccer (2014) it was agreed that the most effective way to turn this into a Predictability Model is to remove Goals Scored (in both Indices) and ‘see’ how the Composite Index takes shape after that.

Here’s an example of what I mean:

CPWP Predictability Index Week 22

A word or two of caution…

From a purely statistical viewpoint I do not see this as a Predictability Model that has direct relevance yet… why?

For the simple reason that there have not been 15 games played for all teams both Home and Away – teams show a tendency, for the most part to behave slightly different at home versus on the road…

Why the number 15?  I suppose it comes down to Confidence Level in the number of samples that are needed in order to forecast the future based upon the past…  with 34 games played in Major League Soccer you really need 15 games to reach that 95% Confidence Level limit in samples…

All that said, it is extremely inviting/inticing to see that even when Goals Scored (both for and against) are removed the CPWP Predictability Index still has a correlation (R) of .84…

Links to articles that have had extensive views over the last year and a way to get a taste of how PWP analyses might be able to help you, as a writer (through collaboration with me), better inform your audience about the nuance of soccer:

In Closing:

Others in mainstream media sometimes offer up subjective opinions that may not be substantiated with objective data; I won’t do that.

Every shred of analysis offered here will include some sort of objective data to support an opinion or conclusion.

Like any other mainstream business; statistical analysis provides objective data as a tool to leverage when looking to make business decisions.  It is not a substitute for the seasoned leadership needed to make final decisions.

I don’t advocate that this analysis is the ‘answer’ or the only tool that substantiates one view – in a soccer match, with 40,000 supporters in attendance, I’ve learned that those 40,000 supporters have 40,000 sets of eyes that see things differently.

On this site, this information and analyses presented, is merely my view, from my eyes, in how I see the game – hopefully, in order to make my future articles of better value, others will add their comments, thoughts, and questions.

Finally, I’m not sure how this will develop but I’ve been approached to provide a manuscript for this analytical effort – for publication in a Sports Science Journal.   More to follow on how that goes.  

Best, Chris

COPYRIGHT, All Rights Reserved.  PWP – Trademark

NOTE:  All data used to generate this analysis stems from OPTA through a number of open/public websites across Europe and America.

My thanks to OPTA and all those open websites for helping to facilitate my own analysis and potential improvements that may arise from this effort.

World Cup 2014 Final; the two best teams? You bet!

If you’ve been following my adventures in Major League Soccer you’ll know that last year the PWP Index did a pretty good job in showing how the team performances played out in comparison to the League Tables (without) including points scored in my calculations.

To be honest, with such a small sample point I really didn’t think the PWP Indices effort would stand up against the Tournament (knock-out based style) of the World Cup.

But after taking a look at all the games (and inputting the team performance from said games) my Indices seem to hold up pretty well – wonder when Pepsi or another company that begins with “P” will consider sponsoring my work?  (just kidding – erhhh maybe not?).

Anyhow – here’s the lay of the land as it was tweeted earlier today:



NOTE:  All games are entered – and the comparison of these games does include the extra games played as the competition has headed towards the finals.

In other words Germany, Argentina, Brazil and the Netherlands all have six games worth of data.  In developing this I figured the more data points for a team the more likely their percentages would be watered down.

So for a team like Spain, who went out in the first round I figured they’d be pretty high up – well they are but the pedigree of the Netherlands, France, Colombia, Argentina, and Germany all put them past Spain EVEN with more games played!

If you’ve read my presentation at the World Conference on Science and Soccer as well as my Introduction into Possession with Purpose you’ll know my measurement methods and data source for this effort.  I can’t thank MLS enough for the publicly available data that allows me to generate my Index formulas.

Perhaps Prozone or someone else might help me obtain the data I need for all the European Leagues, to include the Champions League?

So with the overall accuracy (pretty compelling it appears to me) I’ve put my Composite PWP Predictability Index to test for the final (ahead of time)…

Before offering that Index though here’s how the teams compared against each other in Attacking PWP and Defending PWP:



From an attacking standpoint Germany are top of the table with Colombia 2nd, France 3rd, and Argentina 4th.

And when witnessing that blowout yesterday is that really a surprise, perhaps somewhat, but even prior to that game Germany were 3rd best overall in Attacking PWP – behind only Argentina and Colombia.

So how about the Defending PWP Index?

Notice (below) that Brazil is 17th out of 32 teams; prior to that game against Germany, Brazil were 12th.

So while some favored Brazil – the overall team performance indicators did show that Brazil were behind Germany in both the APWP and DPWP prior to that game.

The same cannot be said for Argentina and Germany – those two split top honors as you can see below as Argentina heads this Index; while Germany is a close 2nd.



Also note, if you’re a supporter of the United States, they were much higher in this Index (21st best) than they were in the Attacking Index (5th worst).

It is worthy (and most probably realistic) that if the United States had taken a stronger attacking stance against Germany, and perhaps even Belgium, they might have been the team getting embarrassed and not Brazil!

Finally, here’s the CPWP Predictability Index:



A pretty close call; in this one Germany has the slight edge in Composite Predictability in comparison to Argentina.

Argentina is #1 in the DPWP Predictability Index (not pictured) and  Germany is 4th best.

Germany is #1 in the APWP Predictability Index and Argentina slides all the way down to 16th best.

A distinct difference in Attacking and Defending Predictability based upon previous team performance while excluding goals scored…

In closing…

The overall Composite PWP Predictability Index indicates Germany is better in attack and Argentina is better in defense; the Predictability Indices indicate the same outputs.

For me, and my PWP calculations this should make for a brilliant final this weekend!

No personal prognostications from me – my objective team performance indicators point one way in attack and one way in defense; usually in games like these the better defensive teams win…

Best, Chris

Possession with Purpose – Predictability Indices – Major League Soccer

After some superb discussion at the World Conference on Science and Soccer folks back in 2014 I first wrote this article; I’ve since improved the Total Soccer Index (though I haven’t published the new algorithm).

Here’s my most recent article on predictability (Predicting Team Standings in Professional Soccer) – it was this article that led to me presenting the PWP TSI Predictability topic at the WCSS 2017 (Rennes, France) last year.

Anyhow…  back to this article.

To do this we agreed that Goals Scored needed to be removed from the equation.  In doing that here’s how the Composite PWP Index offers up an Expected Wins Index number for MLS teams (both home and away) and then separately for home and away games.

I took this extra step since most feel or think that teams who play at home have a better chance of winning than teams who play away from home; and indeed the average for home teams this year is 1.58 points, per game, versus away teams being 1.09 points per game.

Caveats prior to the diagrams:

  1. There will always be an issue with the sample size when looking at a predictability model based upon team performance (within a single game) as opposed to specific individual actions by players like shots taken and shots on goal – repeatability here is not those specific instances of activity but the ‘comprehensive instances’ of ‘team activities within a game’…
  2. For me that represents the primary bell curve of the game as opposed to, in my view, the 3rd or 4th standard deviations of the bell curve where goals are scored… I hope that makes sense???
  3. There are only 17 home and 17 away games – again that sample size is extremely small – but the volume of team activities within those games ‘should’ provide a general (bell curve) picture on what regular activities a team takes in order to score goals and/or prevent goals being scored.
  4. The Predictability Indices are the PWP Indices (minus) the percentages of Goals Scored versus Shots on Goal.
  5. No additional analysis to go with the CPWP, APWP and DPWP Predictability Indices – in my view there simply aren’t enough data points yet; when all the teams have reached 10 games played (both at home and away) I’ll break open the analysis as a real predictive tool to try and predict a win, draw or loss.
  6. For now consider they represent a ‘visual diagram’ that also includes the current Correlation (R) the Indices have with respect to total points or an average of points per game played in MLS.

The Composite PWP Predictability Index (PI):  The CPWP PI has a best Correlation with respect to Average Points earned in the MLS League Table (R) .52

CPWP Home and Away Predictability Index Week 15 MLS

CPWP Home and Away Predictability Index Week 15 MLS

The CPWP PI for Home games has a best Correlation with respect to Average Points earned in the MLS League Table (R) .66:

CPWP Home Predictability Index Week 15 MLS

CPWP Home Predictability Index Week 15 MLS

The DPWP PI for Home games has a best Correlation with respect to Average Points earned in the MLS League Table (R) .60:

DPWP Home Predictability Index Week 15 MLS

DPWP Home Predictability Index Week 15 MLS

The APWP PI for Away games has a best Correlation with respect to Sum of Points earned in the MLS League Table (R) .58:

APWP Away Predictability Index Week 15 MLS

APWP Away Predictability Index Week 15 MLS

In closing….

The visual diagram with the best Correlation to Points in the MLS League Table is CPWP-PI with an R of .66; and the second best is the DPWP-PI with an R of -.60.

So from a, point going forward approach, it would seem to me that the best visual diagram to use when offering up analysis later this year is the CPWP-PI compared with “Average” Point taken per game as opposed to the “Sum” of Points in the MLS League Table.

We will see if that holds true in a few weeks time; thanks for your patience.

Best, Chris


World Conference on Science and Soccer – My Presentation on Possession with Purpose

Roughly 10 days before the Kickoff to the first ever World Conference on Science and Soccer held in the United States I got a phone call from the Conference President and Coordinator Terry Favero asking me if I was interested in making a presentation on Possession with Purpose.

To say the least I was pleasantly surprised, elated and nervous all at the same time; me – just a wee blogger locked up here in the great northwest; a hot bed for soccer being asked to offer my work on Possession with Purpose.

In short; after a some discussion and clarification I said yes; and four days later had submitted this presentation for discussion.

Before showing the diagrams, my first order of business is to thank Terry Favero, and then also add my thanks to some great folks at Prozone Sports, New England Revolution, Portland Timbers and Arsenal FC for making the presentation and discusssion truly superb!  Wow – what a great experience.

Without further ado; let the diagrams begin…

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Wrapping up the hour long presentation/discussion with a few takeaways that come to mind…

Most agreed that the critical penetration numbers to focus on were passes “within” the Final Third and not just passes that “penetrate” the Final Third.

Most agreed that crosses ‘were’ passes – though there also remains value in considering crosses separately – but they should be included in the overall analysis of passing accuracy within the Final Third.

New Soccer Statistics?

  • Additional discussion centered on the potential need for a couple of new statistics – “failed assists” was one – …there is value in knowing what players offer up what volume of potential goal scoring opportuinities even if they fail – especially those that fail as a result of a defensive clearance.
  • In that example the defender gets credit for stopping a cross but the player who offers the cross that is good enough to require a clearance gets no statistical credit for it… that may change in the near future.
  • Another additional new statistic considered was the ‘penetrating pass’ statistic – where individual players who generate penetrating passes into the Final Third are recognized…  it’s hard to measure vision but many agreed this may be a statistic that could help measure ‘vision’…

The slide highlighting the changes in MLS Coaches from 2013 to 2014 also peaked some interest – indeed – like last year – the cycle has begun again this year with the sacking of John Hackworth.

I’ve done two separate articles on that and won’t go into any more detail other than to say – my team performance indicators lean towards that move being one of senior leadership panic (with the lack of wins) more than anything else.

Granted wins matter – but the last slide really drives home how an organization, loyal to their Head Coach, can turn things around with minimal changes in personnel and faith in the system being used.

Best, Chris

MLS Soccer – Week 14 – The best and worst in Possession with Purpose

Been a really busy past two weeks for me and it’s good to nestle back into a routine offering for your consideration.  That being said I should appropriately note that I met some really superb people this past week at the World Conference on Science and Soccer.

It’s a small world when you meet someone who knows where Thetford, England is – and – has been there before!

Anyhow, I digress, back to American Major League Soccer and the results of Week 14.

There were plenty of surprises again this week, parity gone wild I suppose and none greater for most than Chivas, of all teams, drawing at home, erh, on the road, erh, at home on the road, against LA Galaxy; I’ll bet Arena was pretty upset with that result!

Not to be outdone, New York took three points from New England while Portland finally got a win in Rio Tinto (their third straight road win!) and Sporting spanked spurting Houston.

So who, exactly, after all those games, was the best of the best in attack?

APWP Index Week 14 MLS

APWP Index Week 14 MLS

Vancouver – aye – three goals on the road in Philadelphia saw them just edge out Portland by less than a hundredth of a point – the final difference really came down to having fewer shots on goal while scoring the same amount of goals.

It’s interesting to see that both teams actually had less than 50% of the possession.

In a side discussion, at the WCSS last week, we talked whether or not the Index had a bias towards possession; most seemed to agree that the bias in PWP is towards ‘accuracy’ and perhaps ‘goals scored versus shots on goal’; not possession.

On the bottom end was San Jose, the prototypical direct attacking team, who scored no goals even though 18% of their  11 shots taken were on goal.  Of course that shouldn’t be a surprise though – San Jose are not very good on the road this year – taking just 4 points out of their current 16.  More later on their passing accuracy as well…

So how did things go on the defending side of the ball?

DPWP Index Week 14 MLS

DPWP Index Week 14 MLS


The top defending team this week was DC United; holding a very powerful possession based team, Columbus, who had just 10 shots taken with only 2 testing Bill Hamid; bottom line here is that draw for Columbus saw both Toronto and New York leap-frog them into the top five; it probably didn’t help not having Higuain running the attack.

However viewed the real difference maker between Toronto and DC United really came down to DC United playing against a more possession based team who is routinely very accurate in their passing; averaging 79.99%; the best in MLS at this time.  Well done DC United!

Another view is that Toronto was playing against San Jose who was, this week, 3rd worst in overall passing accuracy this week and 2nd worst in passing accuracy after penetrating the Toronto Final Third.

And since we know that Toronto yields the greatest volume of opponent passes in their own defending third it’s a pretty pathetic performance when converting just 53.08% of those passes.

As for the worst in defending this past week; Philadelphia takes the honors.

Vancouver had just 42.11% of the possession while being 5th worst in Final Third Passing Accuracy but they were completely dominating when it came to putting shots on goal and goals scored; 67% and 75% respectively.

In looking at the Composite Possession with Purpose (CPWP) Index….


CPWP Index Week 14 MLS

CPWP Index Week 14 MLS


For the first time this year Portland has taken those honors – how did they do it?  A good article to read that peels that back a bit is here… some other thoughts not included are…

They had less possession yet were 2nd best this week in passing accuracy across the entire pitch and 3rd best in passing accuracy within the attacking final third.

In addition, Portland put 82% of their shots on goal and scored on 33% of those.

Bottom line on this effort was taking advantage of space and leveraging an increasingly dangerous Fenando Adi; a true target #9 with nous and deceptively brilliant foot/heading skills!

Saying that is not to diminish the value of Sporting and New York also taking 3 points on the road; it was incredible to see New York defeat a very strong home side in New England.

No-one this year has been better at home compared to on the road – and all that without Thierry Henry and Tim Cahill; while also nursing a much-maligned Red Bull back-four.  I wonder if we see Ibrahim Sakagya play central defending midfielder again this year?

As for Sporting KC hadn’t won a game since May 10th against Montreal – so that 2-nil win at BBVA Compass Stadium had great value.

That being Houston is not the team some might think they are.  Their current points total is deceptive; they have played 16 games and have taken just 17 points.  Montreal might be at the bottom of the league standings – but when it comes to the overall CPWP through Week 14 they are higher and they have four games in hand against both Philadelphia and Houston…

Might Frank Klopas be getting things better organized as the mid-point in the season draws near?  I imagine he needs to; it can’t be easy replacing the Head Coach who actually got the Impact into the Playoffs, last year, at the expense of the team you just got fired from.

In closing…

We are nearing the mid-season point and the overall Composite PWP continues to take shape.

For me, it’s still too early to try and leverage PWP as a predictive model (need at least 17 games for each team really) – that being said I might have to purge Goals Scored from the Index to really put it to test – I’ll do that after week 20 and see what the Expected Wins relationship looks like…

Best, Chris

Next Up – MLS Soccer – PWP through Week 14 – Tomorrow…


MLS Possession with Purpose Week 13 – Plenty of surprises…

Some stunners and bummers this week for plenty of soccer supporters across North America; who’da thought Montreal would get a clean sheet against New England and Real Salt Lake would get completely schooled by Seattle…

Others like Philadelphia reinforced they do not want to be a bottom dweller, as some suspect this year, by beating up on Chivas, and DC United took advantage of a depleted Sporting KC to take three in DC.

For sure this week, like a few others this season, reinforced why games need to be played.

So who was tops this week in Attacking PWP (APWP) – it may surprise you – (Columbus Crew) it did me for a start, but in review, the overall data supports the basic intent of PWP –

    • A documented method for measuring team performance from my six step process.
    • 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.

So here’s a look at the top five teams in APWP this past week and some comments to follow for consideration:

Top 5 APWP Week 13

Top 5 APWP Week 13

A couple of things…

Note the Completed passes in the Final Third vs Completed Passes across the Entire Pitch (4th column from the left).  Three teams in the top 5 APWP this week all faced teams who attempted to bunker in; how can we tell that?

By the lower percentage of penetration versus completed passes for Columbus (13.80%); LA Galaxy (14.48%) and Philadelphia Union (16.30%).  And when viewing other teams who have played against these teams the results are similar…

When Seattle played Chivas earlier this year they had just 13.94% of their total passes completed in the final third; against Toronto they did slightly better at 18%.

Columbus versus Chicago was 16.59%, LA versus Chivas was 15%, FC Dallas versus Chivas was 15%, Portland versus Chivas was 14% – so there is clearly a pattern.

It’s probably not as obvious with Toronto as Chicago or Chivas but a realistic assumption can be made that some outputs in PWP will help indicate what pattern of defense a team might encounter.

So how about the attacking portion that really matters – shots on goal and goals scored?

In the case of Columbus and LA both hit the magical 100% and that is what put them in the top five of APWP.

That’s not a bad thing; on the contrary it actually reinforces in my mind how fragile the game of soccer can be when it comes to mistakes and their impacts on the game.

Consider the overwhelming domination that Seattle had this past weekend; their inability to be ‘top of the heap’ in APWP is not a negative on the team.

Where the complete domination shows up is when you add in the Defending PWP…

Defending PWP Week 13

Defending PWP Week 13

It’s pretty clear here that three teams stood out from the rest; Colorado (3-nil clean sheet), Philadelphia (3-nil clean sheet) and Seattle (4-nil clean sheet).  And that defensive dominance will carryover to the Composite PWP Index shown a bit later.

For now though take a look at the #4 team in DPWP – Montreal Impact – many might have considered that 2-nil win against New England a surprise…

But here’s an interesting tidbit of information about New England in Composite PWP this year.

At home New England perform better than their opponent in APWP 2.42 to 1.91 while on the road their APWP is 2.24 versus their opponent APWP is 2.44; in other words New England are far less productive performing on the road than at home.

Given that, and Montreal showing tendencies in performing better at home, perhaps it isn’t such a big surprise after all?

Here’s the differences between home and away for all teams in MLS at this time:

Home versus Away - Who is better and worse in MLS after Week 13

Home versus Away – Who is better and worse in MLS after Week 13

Bottom line here is that Chivas USA are clearly (far right amber bar) much much better in overall APWP on the road than at home; is it any wonder given their average audience is about 5 people… just kidding…

On the other side we already know about New England – but other teams not liking the road, so much in team performance, are Houston, San Jose, Colorado, Real Salt Lake and Toronto.

Road warriors, though not dominate / winning road warriors also include Chicago Fire (don’t forget that 5-4 win in Red Bull Arena), Philadelphia, Columbus and Portland.

The other takeaway here is how strong and equally consistent are Vancouver and LA Galaxy; there’s almost no difference in their PWP on the road versus at home.

One could argue the same for Portland but with them giving away so many PK’s this year, plus Red Cards (to begin with), there really isn’t value in offering up consistency with the Timbers until after they start playing mistake free football.

In closing, here’s the top to bottom in Week 13 Composite PWP…

Composite PWP Index Week 13

Composite PWP Index Week 13

A few final thoughts and an update of sorts in general… 

Portland did quite well in scoring goals in the run of play this week, and they really proved how effective they can play in direct attacking – Adi has added value; when – not it – but when they get mistake free in the back-four they should push their way up the table…

That might be looking at the Timbers through rose colored glasses, so be it… it is what it is.

With respect to my weekly Attacking and Defending PWP Players of the Week; sadly I can longer offer up these awards.  There is simply too much time needed to dig through the new MLS Chalkboard to come up with relevant individual player statistics to support one player over another.

On the one hand some of the new format works well; on the other hand it has completely hampered additional, detailed, defensive analysis…  notice that ‘blocked crosses’ is no longer a statistic that is made publicly available.

Finally, and I’m a bit jazzed about this; I got a phone call late last week from the folks organizing the World Conference on Science and Soccer, asking me to present my Major League Soccer Possession with Purpose Index analysis.  The better part of last week and early this week I’ve been putting the finishing touches to that presentation.

When I get it done and the Conference is completed I will post it here on my blog site.  Really looking forward to listening in to all the presentations.

Best, Chris