Tagged: English Premier League

Expected Wins Five – Europe

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:

  1. 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
  2. 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…

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. 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…

Barcleys Premier League PWP Data PointsBarcleys Premier League PWP Derived Data PointsEnglish Premier League CPWP IndexEnglish Premier League CPWP Predictability Index

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…

Germany:

 Bundesliga PWP Data PointsBundesliga PWP Derived Data PointsGerman Premier League CPWP IndexGerman Premier League CPWP Predictability IndexPerhaps 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…

Spain:

La Liga Premier League PWP Data PointsLa Liga Premier League PWP Derived Data PointsSpanish Premier League CPWP IndexSpanish Premier League CPWP Predictability Index

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:

UEFA Champions League PWP Data PointsUEFA Champions League PWP Derived Data PointsUEFA Champions League CPWP IndexUEFA Champions League CPWP Predictability Index

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.

In Closing:

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:

Major League Soccer Expected Wins FourWinners Expected Wins PWP Data Relationships Four

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…

Best, Chris

COPYRIGHT – All Rights Reserved.  PWP – Trademark

Gluck: Updated Possession with Purpose and the New Total Soccer Index

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.

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.

In Summary:

  • 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.

Best, Chris

@ChrisGluck1

Gluck – Predicting Team Standings in Professional Soccer

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.

End State:

  • 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:

mls-2013

  • 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:

epl-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:

bl-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:

spl-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:

uefa-cl-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:

mwc-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:

mls-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:

mls-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:

mls-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.

Closing Thoughts:

  • 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.

Best, Chris

You can follow me on twitter @Chrisgluckpwp.

COPYRIGHT – All Rights Reserved.  PWP – Trademark

Possession with Purpose Total Soccer Index What is it?

In 2014 I created an Index to measure team performance; my goal was to create one number (exclusive of points scored) that could help me tell a story about team performance that isn’t just about goals scored and goals against (Goal Differential).

While I can’t share the internal data points and algorithms anymore I can offer the Index is designed to capture the ‘primary bell curve’ of team activities on the pitch.

Here are diagrams of the Indices for each league/competition originally measured in 2014.  The ‘r’ in each diagram offers the correlation of the Possession with Purpose Total Soccer Index (PWP TSI) to points earned in the league table.

Points earned is not a data point in the algorithm used to create the Index.

 

Since the TSI was first created in 2014 I’ve updated the algorithm to try and exceed the ‘r’ of Goal Differential to the league table – a long-time benchmark of accuracy and one of the primary reasons the statistic Expected Goals was created.

That logic follows the premise that it’s all about goals scored and goals against.

In 2018 I updated my algorithm and for Major League Soccer the TSI now has a greater correlation (r) to the league table than Goal Differential.

 

With World Cup 2018 nearly here I will be testing my Index again – and comparing the accuracy of my new algorithms to what was generated during World Cup 2014.

Here’s the World Cup 2014 Index showing the new TSI compared to the previous TSI and Goal Differential:

The green cell shows the Attacking half of the new TSI has a greater correlation to points earned than either the new Composite TSI or Goal Differential.

The days of using Expected Goals as a predictability model for scoring goals is over.

This should also convince Anderson and Sally that it isn’t all about preventing goals scored; at least not in the World Cup of 2014.

Look to my site if you want to see how your favorite team is comparing against the rest of the world.

Here’s a reminder of what the PWP TSI showed at the end of group stages in World Cup 2014.

Germany and Argentina (the two finalists) were 1st and 3rd in the Index.

If an American it should be pretty obvious the USA was punching way above their weight in making it past the group stages.  If you want to know my thoughts (back then) on the future of Jurgen Klinsmann and Sunil Gulati – click here.

CPWP INDEX GROUP STAGES COMPLETED

Perhaps this years’ Index will be as telling as the one in 2014?

Best, Chris

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

Barcley’s Premier League – How Goes It?

In my latest installment of Possession with Purpose in Europe I have a number of diagrams to offer to include the latest on the PWP Predictability Index.

You’ll note that in every case the PWP Correlation to the League Tables for all four competitions has stayed the same or gotten better.

Also of interest is that a number of youth soccer teams, and another writer, have joined the queue in leveraging the PWP approach in analyzing soccer games – what remains, after publishing my Academic Paper (real soon as things go) is my ability to get data quicker and to set up a software system – probably using MS Access – to better enable match reporting.

It’s slow going – but that’s okay…  patience is a good thing…

Now for the grist in the English Premier League:

Last we spoke (after Week 26) here was the latest on CPWP Predictability;

  1. Eight of Ten
  2. Seven of Ten
  3. Eight of Ten
  4. Eight of Ten

In looking at Week 27 the CPWP Predictability Index was Six for Eight (hitting the 75% target).

For Week 28 the CPWP-PI had Man City earning at least a point vs. Leicester City, Chelsea earning at least a point vs West Ham, Man United earning at least a point vs Newcastle, Arsenal earning at least a point vs QPR, Everton earning at least a point vs Stoke, Spurs earning at least a point vs Swansea City, Liverpool earning at least a point vs Burnley, Aston Villa v West Brom dead even, Hull City earning at least a point vs Sunderland, and Southampton earning at least a point vs Crystal Palace.  Last but not least there was an off-game played between Spurs and QPR – the CPWP-PI had Spurs earning at least one point – they did.

  • In every case this week the CPWP-PI got it right with one exception – Stoke City took all three points against Everton!  So that made it ten for eleven in identifying whether or not a team would earn at least one point based upon the CPWP-PI.  In only two cases did the team expected to earn a point didn’t get three points – Aston Villa and Hull City.

For Week 29 the CPWP-PI had Chelsea earning at least a point vs Southampton, Everton earning at least a point vs Newcastle, Man United earning at least a point vs Spurs, QPR earning at least a point vs Crystal Palace, Arsenal earning at least a point vs West Ham, Hull City earning at least a point vs Leicester City, Aston Villa earning at least a point vs Sunderland, Stoke City earning at least a point vs West Brom, Man City earning at least a point vs Burnley, and Liverpool earning at least a point vs Swansea City.

  • Burnley had the upset of the week while Crystal Palace and West Brom continued their good, recent, run of form.  All told CPWP-PI correctly identified seven of ten teams earning points that week.

For Week 30 the CPWP-PI had Man United earning at least a point vs Liverpool, Chelsea earning at least a point vs Hull City, Everton earning at least a point vs QPR, Man City earning at least a point vs West Brom, Swansea City earning at least a point vs Aston Villa, Arsenal earning at least a point vs Newcastle, Southampton earning at least a point vs Burnley, Stoke City earning at least a point vs Crystal Palace, Spurs earning at least a point vs Leicester City, and West Ham earning at least a point vs Sunderland.

  • In every case but one the CPWP-PI correctly predicted what team would earn at least one point except for the loss Stoke City had against Crystal Palace – again – a team in good form since the coaching change!  That makes it nine of ten again this past week.

In summary:

  • Eight of Ten
  • Seven of Ten
  • Eight of Ten
  • Eight of Ten
  • Ten of Eleven
  • Seven of Ten
  • Nine of Ten
  • Totaling 57 of 71 for an 80% accuracy rating

Here’s the CPWP Index after Week 30:

CPWP Through Week 30 EPLHere’s the CPWP-PI Predictability Index for Week 30:

CPWP Predictability Index Through Week 30 EPL

For this next week CPWP-PI has:

  • Arsenal earning at least a point vs. Liverpool
  • Southampton earning at least a point vs. Everton
  • West Ham earning at least a point vs. Leicester City
  • Man United earning at least a point vs. Aston Villa
  • Swansea City earning at least a point vs. Hull City
  • West Brom earning at least a point vs. QPR
  • Chelsea earning at least a point vs. Stoke City
  • Spurs earning at least a point vs. Burnley
  • Newcastle earning at least a point vs. Sunderland, and
  • Man City earning at least a point vs. Crystal Palace
  • Another odd game has Aston Villa earning at least a point vs. QPR

In Closing:

Completion of my Academic Paper on Possession with Purpose nears…  another writer has asked to begin leveraging PWP analysis to their own team writing efforts and there are now three youth soccer clubs using the concepts and philosophy of PWP in trying to help their teams improve – both collectively as well as for their individual players.

Best, Chris

COPYRIGHT – ALL RIGHTS RESERVED.  PWP – Trademark

Catching up with Europe…

It’s been a bit since I last offered anything on Europe – sorry – just a whole lot going on to include putting together an Academic Paper, or five, on Possession with Purpose.

Since it’s been awhile here’s the primary Composite Index for all four areas covered – I’ll try to offer some more insight into the specific competitions a bit later – for now I appreciate your patience and hope this scratches the itch for a wee bit.

Oh – and a surprise at the end about Total Shot Ratio…

La Liga:

La Liga CPWP Index Week 26Clearly Barcelona is now firing on all cylinders – it’s a two horse race with Real Madrid while the next battle looming appears to be Valencia and Atletico Madrid.

Bundesliga:

Bundesliga CPWP Index Week 24Does anyone really think anybody is going to beat out FC Bayern Munich?  Probably not – but the other top three in the League Table are also the other top three here – the leader here appears to be Wolfsburg – and if a betting man that one seems a worthy gamble on them finishing second…

English Premier League:

English Premier League CPWP Index Week 28

 

I wouldn’t say it’s a runaway yet – still some games to be played but the real battle seems to be who finishes fifth – the bridesmaid as some say?  As for Everton – well……….  I’d be very surprised to see Martinez back next year – how can a team so dominant in possession completely lack the ability to finish?  It’s called possession with no purpose – and it may not just be all about their strikers….

UEFA Champions League:

UEFA Champions League CPWP Index After Seven Games

Was anyone not surprised with Monaco defeating Arsenal?  In considering how things are developing it probably should have been foreseen a bit better…

In Closing:

I’ll try to offer up the Predictability Indices later this week in preparation for the Weekend.

By the way, when putting together the Academic Paper on PWP I have had to create two new Total Shot Ratio indicators…

As things have stood so far TSR has merely been an indicator viewed with attacking team data only and it’s never been flipped to see how the opponent behaves in TSR with respect to the other team.

Well I’ve fixed that, if you will.

Now like Attacking PWP, Defending PWP, and the Composite PWP I’ve taken TSR – renamed it to Attacking TSR (ATSR), and created Defending TSR (DTSR /// what the Opponent’s combined ATSR’s are against you), and CTSR – the difference between ATSR and DTSR…

I’ll be offering up more about that in my upcoming paper – you should know now that CTSR has a higher correlation (R^2) to Points Earned in the League Table than the old TSR…

In case you don’t know what TSR is – here’s an explanation pulled (DIRECTLY) from Statsbomb:

“TSR – Total Shots Ratio
A ratio to explain how teams fare against their average competition in the shots battle. Ex: If Manchester City has 20 shots in the match and Newcastle have 10, City’s TSR for that match is .67, Newcastle’s is .33.

James Grayson has written about this frequently on his website here. We care about TSR for teams because it has a reasonably strong correlation to points and goal difference.

In hockey, this is called Corsi.”

So What I’ve done is taken the same approach as what I did when creating Possession with Purpose – I’ve also created a Defending TSR (how the Opponent does against you) – so you have your teams Attacking TSR but also the Opponents Attacking TSR against you – called Defending TSR.

Composite TSR is created by subtracting DTSR from ATSR…  note that CTSR is higher than ATSR with one exception – in other words the difference between the two TSR’s gives you a better picture and better correlation to points earned in the League Table than just plain TSR…

All told though – CTSR does not exceed the R^2 of CPWP – again with but one exception and that exception varies from week to week…

And TSR gives you no objective evidence on team attacking and defending behavior leading up to shots taken or goals scored…  this is not to be critical of TSR – it simply points out the technical weakness in the ratio compared to PWP.

Here’s a snippet of what I mean:

Competition

CPWP to Pts Earned APWP to Pts Earned DPWP to Pts Earned ATSR to Pts Earned DTSR to Pts Earned CTSR to Pts Earned

MLS 2014

0.85 0.79 -0.68

0.74

-0.54 0.75

UEFA

0.87 0.8 -0.76 0.64 -0.4

0.65

EPL

0.92 0.9 -0.85 0.86 -0.35

0.76

Bundesliga

0.92 0.83 -0.81 0.53 -0.41

0.68

La Liga 0.91 0.88 -0.88 0.88 -0.77

0.92

The number in bold is the one with the highest R Squared to Points Earned – at least this week…  and the numbers are those R Squared with respect to the League Table – not indicative of what the CTSR is for each team on a game to game basis – I will publish those a bit later this week… hope that clears up any confusion and appreciate your patience.

As of the 12th of March I have published that additional article speaking to TSR and the recommended changes to the overall effort… it’s here:  Modernizing TSR

Best, Chris

COPYRIGHT, ALL Rights Reserved.  PWP – Trademark

 

 

Chelsea sits atop… Saints continue to March…

For most, the stunning team this year continues to be Southampton – worthy view as the Saints continue to march towards Europe.

I’m not on their bandwagon yet as nearly half the season remains – but if they keep up their team performances, as they have the first 21 games, it is likely they squeeze out either Man United or The Arsenal…

Wouldn’t that shake up things up a wee bit?

As for now, here’s my CPWP Index and how the teams compare, in overall performance without using points, after Week 21:

CPWP Index English Premier League Through Week 21

General thoughts:

There appears to be a four tiered level of performance so far – with Man City and Chelsea at the top; Man United, Southampton, and Arsenal next – followed by Everton, Liverpool, and Swansea – while West Ham and Spurs continue to stay in the race.

Even here Southampton are near the top – it’s no fluke they are where they are in the League Table.

As for West Ham and Spurs – those two London sides, along with The Arsenal need to pick things up a bit or they may be stuck in Europa League next year.  Somehow for The Arsenal I don’t think that’s a goal… Allardyce and Pochettino —> maybe?

But Wenger, no – it would likely lead to many dissenting voices and the unwise move of sacking him.  Personally I think he’s one of the best Head Coaches, ever, in Soccer…

So you know – since Pardew was sacked by Newcastle, prior to Game 21, I will be able to do a compare and contrast later this season – especially since he’s now coaching Crystal Palace… I wonder how those two teams will look at the end of the season?

I’ll also poke around West Brom too; now that Pullis is in charge.

Correlation – R2 = .92; continues to remain relevant and strong.

Attacking PWP Index:

APWP Index English Premier League Through Week 21

Defending PWP Index:

DPWP Index English Premier League Through Week 21A few thoughts…

The two teams at the top of the table are the two teams at the top of both the APWP and DPWP Index.

If I were a betting man I’d bet Newcastle brings in some defensive support rather quickly – if they don’t perhaps they fall as far down as the relegation zone?

Liverpool clearly need more support up top – they lack goal scoring and there is the Capt. Obvious that Suarez is missed – clearly Balo-telly is lacking.

West Ham continues to punch way above its weight – can they sustain that approach?

I’d imagine Allardyce will be shopping for another defender to two to strengthen his bench for a sprint run to the finish…

I’d also imagine Spurs will look to do the same thing – they are surviving because Kane scores goals – but as seen this last weekend – they are also taking it in the shorts because they can’t prevent goals against.

Giving away two goals to Crystal Palace is shameful…

Wow – might DeAndre Yedlin get a look in soon?  He had 60 minutes with the youngsters the other day but may need another few weeks to get adjusted; time will tell.

CPWP Predictability Index:

CPWP Predictability Index English Premier League Through Week 21

I include this for others more than myself.

In a trial run for the MLS, going strictly with this Predictability Index, I varied from 35-70% accurate (week to week) on picking the winning team based upon the “home and away PWP Predictability Index”.

But since home teams won 155 times in MLS, as opposed to losing just 77 times, it’s a good bet the home team wins or draws every single game regardless of any predictability model.  For more details on that information read here:  The Comforts of Home in MLS.

I make no case that this IS a solid betting tool but many bet on soccer and the usual predictability products vary in accuracy with a reasonable model offering up 30% accuracy.

I’d be more inclined to offer that this model is probably more accurate for some teams as opposed to other teams – my research continues to indicate that some basic statistics for some teams have little to no relationship on what some basic statistics are for other teams…

In other words, one team may show a reasonable (game to game) correlation between possession and winning while another team may not.

A good example – Stoke City averages roughly 48% possession – their game to game correlation of possession to points earned is (R2) -.52 – meaning — over the course of this season so far Stoke City are more likely to earn points if a particular games’ possession is less than their average.

On the other hand a team like Chelsea – who averages ~58% possession has an (R2) correlation of .13…. meaning their is simply NO RELATIONSHIP between possession percentage and taking points in the league table – they can pretty much take points by either falling above or below their league average of 58%.

I will be doing a new article on Possession in the very near future – it’s an intriguing statistic that is abused in a big way – an aggregate R2 of .77, for a league, does not mean Possession is the overwhelmingly best indicator for team success.

But it does mean it’s a good indicator that one system of football is consistently being used to garner more points earned then another system of football… that would be ‘possession-based’ versus ‘direct-attack-based’…

In Closing:

It’s the winter break for me just like it is the teams – plenty going on to include co-hosting a podcast with Stephen Brandt (@Yellowcardedpod).

Our upcoming guests, in the next two months, include Commissioner Peterson from the North American Soccer League, Jamie Clark, Head Coach for the University of Washington, John Galas, Head Coach Lane United FC (USL PDL), and someone from the Portland Timbers organization – to be determined.

A new article, to be published by @7amkickoff, will speak specifically to how The Arsenal is performing in some key (game to game) areas.  This is hopefully the first of many articles where my PWP approach will be leveraged by other highly respected writers…

To set the stage for future articles leveraging PWP @7amkickoff provides his introduction to this approach as well as a great synopsis other Soccer statistics in general, to include Total Shots Ratio, published by Grantland, and Michael Caley’s discussion on Expected Goals.

So if you’re a writer, with an interest in leveraging my analytical approach, as part of the overall product you provide your readers let me know how I can help with that.

Best, Chris

COPYRIGHT, All Rights Reserved.  PWP – Trademark
You can follow me on twitter @chrisgluckpwp

Getting More from Less… Major League Soccer

If you’ve read my previous article on Expected Wins 4 (Is European Football Really Higher Quality than Major League Soccer) you’ll know that there are teams out there who can, and do win, ‘without’ exceeding 50% possession.

In my next evolution of analysis, using the Family of Possession with Purpose Indicators on Major League Soccer, here’s some more granularity to go with that observation.

The filters set up for this effort are pretty simple – five of them to be exact:

  1. Teams who won games in MLS last year with less than 50% Possession,
  2. Teams who won those same games with less than the league average in overall Passing Accuracy (77%) and,
  3. Teams who won those same games with less than the league average in Passing Accuracy within the Opponent’s Defending Final Third (66.8%),
  4. Teams whose volume of Pass Attempts fall below the League Average (428.01), and
  5. Teams whose volume of Pass Attempts, into the Opponents Defending Final Third, fall below the League Average (117.54).

Why this approach?

To highlight what teams, and what volume of games those teams won, where ‘CONTROL’ of the game would most likely be interpretted as ‘minimized’ given a poorer ‘team performance’.

In addition, I also sense it may be a good way to differentiate between teams who use a Counter-Attacking “tactic” as part of their Possession-based game versus a team more inclined to play a Direct Attacking style/system.

The really hard part here is I’m not using video and I don’t have access to X,Y coordinate data – this is all put together using public data.

However viewed I hope you find this interpretation beneficial.

In setting the stage for the teams who did best getting more from less here’s the raw data to consider:

There were 234 games last year where a team won in MLS.

Of those 234 games, 122 of them the winning team had lower than 50% Possession.

In other words, 52.14% of all games won last year saw the winning team possess the ball less than 50% of the time.

Of those 234 games, 70 of them the winning team had less than 50% Possession and less than 77% Passing Accuracy.

In other words, only 29.92% of all games won last year had the winning team performance fall below League average in Possession and Passing Accuracy.

Of those 234 games, 53 of them the winning team had less than 50% Possession, less than 77% Passing Accuracy (across the entire pitch) and less than 66.8% Passing Accuracy in the Opponent’s Defending Final Third.

In other words, only 22.65% of all games won last year had the winning team performance fall below League average in Possession and Passing Accuracy (both within and outside the Opponents Defending Final Third).

By the way, for those curious, in only 19.66% of all games lost this year (234) did the losing team EXCEED the League Average in Possession and Passing Accuracy (both within and outside the Opponent’s Defending Final Third).

So more teams got more from less than teams who got more from more…

Here’s the teams who got more with less, and how many times they were successful in that effort:

MORE FOR LESS BY TEAM 2014

The Red Bars signify Eastern Conference Teams while the Blue Bars show Western Conference Teams (last year).

For now it should be noted that DC United took 24 of 59 Points where they performed far below league average in passing.

In addition, New England also took 21 of their 55 Points in games where they performed far below league average – and six of those seven wins came after Game 25 – in other words after they signed Jermaine Jones!

With respect to Philadelphia – five of their six wins, using this filter, came after Jim Curtin replaced John Hackworth.

In looking at Toronto – all of their five wins, in this fashion, came in the first 11 Games of the season – two things perhaps to consider from this:

  1. Other teams in MLS figured out the counter-attacking/direct attacking nature of the team and changed their defending habits accordingly, or
  2. They had an injury or two that impacted this style of play and, under Nelsen, were unable to recover from a key attacker being missed.

Of note – Chicago recently brought in two DP Strikers – is that a signal to the rest of MLS that Frank Yallop really intends to go all out in this type of attacking approach?

Finally, FC Dallas appeared to be the more counter-attacking/direct attacking team in the Western Conference – and this data appears to substantiate that.

Oscar Pareja’s approach was good enough to make the Playoffs last year – but with Houston (under Owen Coyle) and Sporting, another possession-based team, set to join the Western Conference, might we expect to see Pareja take a different approach next year?

East meeting West:

MORE FOR LESS BY CONFERENCE 2014

Pretty telling if you ask me…

A marked difference in volume of teams that got more with less in the Eastern Conference.

This provides some pretty good evidence to support those having the belief or feeling that the two conferences played different styles…

Now what?

Well, for me, over the past few years I’ve found it pretty hard to differentiate between a team that works towards Direct Attacking, as a style, as opposed to Counter-Attacking.

And to be honest I’m not sure what the difference is; at least up until now.

Here’s my draft definition on how to define a team that Counter Attacks (as a tactic) as opposed to using Direct Attacking (as ‘the’ tactical system/style/approach).

  • The league average for passes attempted across the entire pitch is 428.01.
  • So for the purposes of this effort all teams that fall below that average will be viewed as Counter-Attacking teams until I see that their volume of passes attempted in the Opponent’s Defending Final Third also falls below that League average of 117.54.
  • My rationale is this – a consistent trend of low volume in passes attempted both within and outside the final third indicates to me that the team is attempting to play longer or quicker balls into the final third – that have less chance of being completed – in other words looking to penetrate with less overall control of the ball.
  • I welcome any additional thoughts on this…

In looking at these 52 games:

  • Only one game did the volume of Pass Attempts exceed the League Average of 428.
  • In that one game the volume of Pass Attempts within the Opponents Defending Final Third did not exceed the League Average.
  • DC United had that game.
  • Only 11 games saw the volume of Pass Attempts in the Opponents Defending Final Third exceed the League Average of 117.
  • New England had five of those games, Seattle had one, DC United one, Vancouver one, and Philadelphia three.
  • Therefore in 40 of the 52 games played, using this filter, it would appear that the team that won played Direct Attacking Football.
  • Meaning the teams that performed best in Direct Attacking football were DC United (7), Toronto (5 under Nelsen), Dallas (5), and Chicago (3).

Gut-Check on my Direct Attacking hypothesis – a pretty well known/attributed Direct Attacking team in the English Premier League is West Ham.  

Of their 19 games this year every single game saw their total Pass Attempts fall below the League Average of 426.73.

In 11 of those games their Pass Attempts, within the Opponents Final Third, fell below the League Average of 131.82.

They won seven of those 11 games.

In conclusion, the gut-check pans out – it appears that the outputs from West Ham match those developed based upon what is seen in MLS.

The data also confirms that Sam Allardyce, and his Hammers, are doing a pretty good job of executing that system as well.

In closing:

Doing more with less had a significant advantage for DC United, New England, Philadelphia, and Toronto – all those teams, tops in this filter, are in the Eastern Conference.

This information also supports the views, by many, that the two Conferences are different; the Eastern Conference has more teams that were successful in doing ‘more with less’ and more teams, who were more successful, in their Direct Attacking style/system.

It seems reasonable to me that this is a way for me to better quantify the difference between a team that counter-attacks as a ‘tactic’ versus a team that prefers to play more direct.

Best, Chris

COPYRIGHT, All Rights Reserved.  PWP – Trademark

You can follow me on twitter @chrisgluckpwp

 

Chelsea and Man City Lead the Pack

The headline is Capt. Obvious; especially when the League Table sees both these teams beginning to separate themselves from the others.

The question for most is who qualifies for Europe in positions three and four while Man City and Chelsea go toe-to-toe for the League Championship.

Too early you say?  Not for me.

By Week 19, the Composite Possession with Purpose Index, in Major League Soccer had already nailed the League Champion, LA Galaxy, as being best in overall team attacking and defending performance.

Of course that didn’t translate to the Supporter’s Shield winner, but, then again, Major League Soccer doesn’t have an equal schedule, so the only real measurement to go by is the Champion crowned after the Playoffs are finished.

With that said, there were some teams who did move up and down in the CPWP Index (and MLS League Tables) after the halfway point.  So I suppose it’s possible Man United, Arsenal, or someone else could close the gap, and make it a three horse race?!?

In moving on though I’m not seeing that – at least not yet.  Why?  Well given my CPWP Index after Week 17, just below, it seems pretty clear both Man City and Chelsea are performing much better than the others:

CPWP Strategic Index Week 17

Given that my main focus today is sorting out the picture for the two remaining spots for next years UEFA Champions League.

I’ll call them my Bubble Teams (lacks creativity most likely, but hey… it’s late).

I see five with a chance.

Manchester United, Arsenal, Southampton (really?), West Ham (really?), and Spurs (really?).

At this stage, all five of these teams are within five points of each other at near the half-way point.

Others like Liverpool, Everton, Newcastle, and Swansea aren’t shut out (yet)…  but I sense those teams probably need more than one player to give them that edge and Everton blew their chance this weekend in getting thumped 3-nil by Southampton…

As for Liverpool – they need more than a striker in my opinion (they need another defender too) and I just don’t think they have the money to upgrade.

Brendan Rogers can go on all he wants about his team getting their form back – but in my view – he’s giving lip service to save face after that debacle in signing Balotelli.

So with that said – three new diagrams for your consideration; the first being the Game to Game CPWP Index outputs for the five teams under consideration:

CPWP AMBER BUBBLE BAR TEAMS THROUGH WEEK 17First off – my apologies if there are too many lines here – I tried to stay with team colours – hope you don’t mind…

The diagram itself – you’ll probably be seeing more of these (with just one or two teams more likely in the future).  You can click to enlarge.

The line graphs – most should know by now the CPWP Index is the difference between the Attacking PWP Index and Defending PWP Index.  As is always the case with the CPWP Index – Higher is Better.

Note the frequency of change from game to game in some cases.  To get a better understanding of how much variation there is for each team, week to week, I calculated the Standard Deviation.

Those numbers are provided at the bottom – in this case the lower the number the better.  In other words the lower the number the less deviation a team had, from week to week, in how they performed (in total).

I’ll not offer that Lower = Better Team; at least not yet – but in this case I am going to assume that lower means more consistency.  Sometimes being more consistent doesn’t mean better.  Chivas USA were one of the most consistent teams last year – sadly that consistency was centered around consistently losing…

With that being the case; West Ham is most consistent (.36) with Spurs next (.52), than Man United (.54), followed by The Arsenal (.58) – then Southampton (.67).

Next up the Attacking PWP Index for my Amber Bubble Bar Teams – I suppose that is a goofy name – I’ll change it next week…  suggestions are welcomed!

APWP AMBER BUBBLE BAR TEAMS THROUGH WEEK 17As with the CPWP Index, higher here in the APWP Index is better.

It’s interesting to note that all five of the teams here are pretty much even at this stage – trending up is Southampton (after that lull for three weeks) while Man United seems to be taking a bit of a dip.

From a consistency standpoint – West Ham again lead the pack here (.24) while Arsenal sits at (.29), Spurs at (.31), followed by Man United (.34) and Southampton, again the least consistent, sitting at (.40).  Again – lower is better…

With APWP – I tend to believe that consistency in attacking is a good thing; especially given that rotation of home and away games – for me that shows a team is comfortable in how it attacks.

But…. the drawback here is that consistency in attack also sometimes means a lack of vision in changing things up a bit to play less predictable.

A great example of that this past weekend was The Arsenal going into Liverpool and almost taking three points while playing to an attacking style most would normally attribute to Sam Allardyce…

Moving on to the Defending PWP Index:

DPWP AMBER BUBBLE BAR TEAMS THROUGH WEEK 17

In the case of the DPWP Index – Lower is Better; to remind those – this number is the Attacking PWP number of the Opponent as they attack you – if higher is better when you attack – then it stands to reason a good defending team performance means a lower number.

After Week 17 it would appear all but The Arsenal are near each other  – that two goals conceded against Liverpool no doubt had influence.

With respect to consistency West Ham (AGAIN) lead the pack in being most consistent (.27); with Spurs next (.37), followed by Man United and The Arsenal tied at (.41) and last (AGAIN) Southampton at .47.

For me, consistency here is good, very good, provided points are being earned in the League Table.

By the way – it’s this deviation or consistency that I also look for in viewing Home and Away games to see if a team changes it’s style.

For example the Standard Deviation for West Ham in Away games is .18 while for Arsenal it’s .42 – indicating that Wenger will change their tactical approach depending upon their opponent while Allardyce won’t.

Since all five of these teams are within five points – it seems reasonable that all these teams are getting points.

So what, in the end, are my thoughts after taking this info in?

Before offering that here’s my traditional Indices starting with the APWP Index:

APWP Strategic Index Week 17

Quick observations…

Spurs are consistent in attack – but not consistent in being strong.

Southampton are not consistent in attack – and they are dropping back further and further compared to about 5 weeks ago.

Man United and Arsenal remain dangerous in attack – and remain consistently dangerous as well.

West Ham continues to remain high up this Index – a challenge to be sure – but what bodes well is they are also consistent in that attacking performance.

Now the Defending PWP Index through Week 17:

DPWP Strategic Index Week 17

A few observations…

While Southampton is not very consistent in team defending – at least for now they are not very consistent in a good way – what happens if that inconsistency begins to swing towards the opponent performing better?  A likely slide I’d expect.

West Ham are not only consistent – they remain consistently good – again can that pattern hold?

The Arsenal and Man United remain near the best in team defending performance – quite an achievement given the new approach in Manchester and the injuries in London…

Like in APWP, Spurs lack in overall performance compared to many teams lower in the league table.  The real test comes when they entertain Man United and Chelsea at White Hart Lane, on short rest, just after Christmas.

In Closing:

I think all of these teams will be in the mood to shop for a player, two, or three come January.

Who do I think each team looks to add – from an individual, player standpoint, I haven’t got a clue…

But from a team standpoint here’s my initial expectations:

West Ham looks to add another midfielder and another defender – they are solid and the Allardyce style is working – but do they have the legs to compete the entire season?  I don’t think so – at least not without at least one more defensive thinking/positioning type player given the Allardyce style of football.

Man United looks to add a defender – most probably a center-back who can handle playing 3 or 4 at the back.  But can they afford to?  Lots of money spent already but I’d expect at least one new signing during the transfer window.

Southampton looks to add some more firepower by adding an attacking winger and/or striker – goals will need to be scored to keep them afloat if their defending remains inconsistent.  I also think they could do with another defender if they really are intent on making a run for Europe.

Spurs – hmmm… tough one here – I could see them adding a defender (maybe two?), and a midfielder/forward – they have points in the league table but their team attacking and defending performance lags far behind many other teams with fewer points.

Arsenal – I’ve already opined I think Arsenal need a new Central Defending Midfielder – I also think they need another Center-back and perhaps some more depth at Fullback.

Finally, I will take another look at the bubble teams in about 3 weeks time – there are plenty of games this holiday season and at least a nine point swing could occur.

Best, Chris

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