Tagged: Goals Scored

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

Can Jozy Altidore bring Toronto to the Playoffs?

I’ll try to offer some thoughts on this a bit later but to first understand a possible answer to this question I felt it worthy to conduct a compare and contrast between two teams –  (LA Galaxy and Toronto FC).

To begin; here’s a reminder on how these two teams finished in the Composite Possession with Purpose Index last year – remembering also that LA ended up with 61 points and Toronto had 41 points:

CPWP STRATEGIC INDEX END OF SEASON 2014 COMBINED

If Possession with Purpose is new to you I suggest you read here: Possession with Purpose.  For statistical purposes the R2 (R squared) for the Index compared to points earned was .85.

Next up – the Big Picture:

The Big Picture

Reading from left to right:

  • Average PWP Composite Index – the numbers here represent the difference between the subtracting the PWP Defending Index (grouping 3) from the PWP Attacking Index (grouping 2) for each team; LA being the dark blue bar and Toronto being the red bar.
  • In other words 2.31 from 2.53 = .21 for LA and 2.42 from 2.33 = -.09 for Toronto. (a difference of .30)
  • The 4th grouping – Composite PWP Predictability is the Composite PWP Index (minus) all statistical data associated with a goal scored/goal against – in other words it’s a pure representation of the primary team activities occuring on the pitch exclusive of goals scored.  The R2 for the Predictability Index is .69.
  • Next over is average Goals Scored for each team throughout the year for each game.
  • This is followed by the average Goals Scored by the Opponent against each team throughout the year.
  • Second from last is the average Goal Differential – the same logic applies here that is used to create the Composite PWP Index – subtract Goals Scored by the Opponent Goals Scored against that team.
  • Last and most important – the average points earned for each team for each game.
  • In every case LA exceeded Toronto.

So why were LA better – was it just down to goals scored, higher accuracy in goals scored, or something else?

A way to answer that is by peeling back some differences in team performance.

For example…  In the diagram above the difference between LA and TFC, in APWP (grouping 2), is 2.52 – 2.33  = .19.  Meaning the overall difference in collective team performance of those two teams is 19%.

So where do those percentage point differences occur in looking at the six quality measurements of APWP?

Here’s the APWP diagram that peels back the six primary categories used to create the Index:

Quality Attacking PWP

I’ve highlighted two areas and included a smaller area where the word ‘wash’ appears.

“Wash” simply means those two areas balance each other out – the real differences come from looking at the ligh green shaded areas.  Those areas were:

  • Possession percentage – LA exceeded Toronto by ~6%
  • Passing accuracy – LA exceeded Toronto by ~5%
  • Penetrating the opponents defending final third – LA exceeded Toronto by ~3%
  • Goals scored per shots on goal – LA exceeded Toronto by ~6%

All told roughly 1/4 of the overall difference in team performance (quality) came from goals scored per shots on goal…

Meaning LA performed better in scoring goals but they also performed far better in three other areas, possession, passing accuracy and penetration.

That, alone, may be able to help answer the question about Jozy Altidore but attacking is only one part of the game – how about Defending PWP?

Quality Defending PWP

Toronto were worse than LA by 11% points 2.31 – 2.42 (lower is better)

In looking at the DPWP diagram (above) I’ve taken the same approach – the light green shaded areas show differences while the ‘Wash’ area shows where the teams percentages roughly balance each other out.

The difference in LA team performance, again, comes in preventing their opponents from having more control over the game leading up to (and) preventing goals scored against.

In other words LA simply had better overall team defending performances where goals scored was a wash.

In Closing:

Before offering my final thoughts on Jozy Altidore another quick example.

FC Dallas, who made the Playoffs last year, had similar team performances in quality to Toronto – with one exception.

FC Dallas had a 43.87% accuracy rating in converting shots on goal to goals scored compared to Toronto’s 31.21%.

But FC Dallas didn’t reach the pinnacle.

Bottom line at the Bottom:

My view is this: The addition of Jozy Altidore might help Toronto reach the Playoffs but it is unlikely it will lead to Toronto winning the Championship – if they do the Reds will probably play to the style of FC Dallas – and so far that style of attack has not led to a Championship – at least not in the last four years.

What do you think?

Best, Chris

COPYRIGHT, All Rights Reserved.  PWP – Trademark.

Major League Soccer – Week 28 – A Union divided? Not now…

Twenty eight games in – the screws are tightening and the pucker factor hit the Vancouver Whitecaps big time; see here: Valeri’s vicious volley from Villafana vanquishes Vancouver.

For me though, the real story is how the tables have turned in Philadelphia – I’ll get to that in just a wee bit – for now here’s my usual Possession with Purpose Family of Indices:

CPWP Strategic Index Week 28 MLS

CPWP Strategic Index Week 28 MLS

At this stage the top ten teams above the red line are the top ten teams in the Index.  Good; the End State of trying to match the league table without points seems to be holding steady and the correlation this week (R2) remains a steady and strong .82.

There are at least two key issues this week – who continues to push up the table to make the Playoffs and who continues to push for the Supporter’s Shield – Seattle took a hit this week – but – then again they won the US Open Cup – winning silver is never a bad thing.

In terms of making the Playoffs – tight races for sure.  Some teams have a possible 18 points to get while some others have 15 points to get – with that many points available Vancouver, Philadelphia, Colorado, Toronto, Houston, and even San Jose are still in the hunt.

Moving on to the APWP Strategic Index and peeling back changes to the Philadelphia Union: 

APWP Strategic Index Week 28 MLS

APWP Strategic Index Week 28 MLS

LA Galaxy continue to be attack mad – and some familiar faces appear up near the top as well – remember Portland and New York from last year?  Well… they are still here and still dangerous.

But this isn’t about those three teams – today’s focus is about Philadelphia and how the Union have come together.  In order to see that let’s peel back how they differ from earlier this year with John Hackworth leading the cause.

Here’s the statistical details – do they show any changes?  

  • The average number of total passes with John was 454 per game; under Jim it’s 367 per game – a HUGE difference!
  • The average amount of possession with John was 50.85%; under Jim it’s 44.04% – a HUGE difference!
  • The average penetration per possession under John was 22.04%; under Jim it’s 26.14% – in terms of volume that also represents a HUGE difference!
  • The average Shots Taken per penetrating possession under John was 20.11%; under Jim it’s 19.06% – not big but worthy…
  • The average Shots on Goal per Shot Taken under John was 29.83%; under Jim it’s 38.30% – a HUGE difference!
  • The average Goals Scored per Shots on Goal under John was 36.78%; under Jim it’s 41.14% – a HUGE difference!
  • The average Goals Scored under John was 1.17; under Jim it’s 1.93 – a HUGE difference!

In all, there are considerable differences in team attacking performances under the direction of John Hackworth versus Jim Curtin.

This isn’t offering that one coach is better than the other; what it does offer – however – is that with a slightly different playing style – the output of a team, with the same players, can change.

Top be precise, the volume of passes, and percentages of possession, penetration, shots on goal, and goals scored are considerably different; and those differences do lead to an increase in goals scored and total points.

Said a different way – the Union are possessing the ball less – which in turn means the opponent is possessing the ball more, which, in turn,  means there is more time and space in the opponent’s own Defending Final Third if the opponent loses the ball and the Union can capitalize on that open space.

Might the Union Defending team performance indicators support that?  Let’s see; here’s the DPWP Strategic Index:

DPWP Strategic Index Week 28 MLS

DPWP Strategic Index Week 28 MLS

In looking specifically at the Union; here’s the breakdown on the Union Defending team performance outputs under John Hackworth versus Jim Curtin:

  • The opponent average number of total passes with John was 440 per game; under Jim it’s 468 per game – a big difference!
  • The opponent average amount of possession with John was 48.90%; under Jim it’s 55.96% – a HUGE difference!
  • The opponent average penetration per possession under John was 21.26%; under Jim it’s 21.25% – no difference!
  • The opponent average volume of passes in the Union Defending Final Third with John was 101.50; under Jim it’s 126.27 – a large increase in volume of penetration.
  • The opponent average volume of passes completed in the Union Defending Final Third with John was 69.07; under Jim it’s 81.05 – an increase in volume of completed passes in the Union Defending Final Third.
  • The opponent  average Shots Taken per penetrating possession under John was 19.49%; under Jim it’s 13.95% – a worthy difference…
  • The opponent average Shots on Goal per Shot Taken under John was 39.61%; under Jim it’s 37.78% – a worthy difference…
  • The opponent average Goals Scored per Shots on Goal under John was 36.90%; under Jim it’s 34.12% – a worthy difference…
  • The opponent average Goals Scored under John was 1.71; under Jim it’s 1.25 – a HUGE difference!

In all, there are worthy differences in team defending performance between John and Jim.

In answering the leading question into DPWP – the answer is yes…

  • The volume of penetration has increased markedly under the leadership of Jim Curtin in comparison to John Hackworth – it’s that difference that leads many to believe that the defensive line of the back-four has dropped deeper…
  • In addition, with dropping deeper, it’s expected that the space will get tighter – with less space, and time, opponent shots taken and shots on goal volume should decrease.
  • Under John, the opponents volume of shots taken was 12.36 per game with 4.79 shots on goal per game – under Jim, shots taken is 11.40 per game while shots on goal is 4.00 per game.
  • So they not only decrease in volume, they also decrease in percentage as noted in the bullets above.
  • Finally, under John Hackworth, Goals Against were 1.70 per game; under Jim Curtin they are 1.36.

Bottom line here – the Union are simply better in defending, and in turn, their deeper drop, in defending, has led to an improved attack.

In Closing:

For those only interested in Total Points – under John Hackworth – the Philadelphia Union had earned 11 points in 14 games; under the guidance of Jim Curtin (now) the team has 27 points from 15 games.

If that pattern continues (1.8 points per game) the Union could finish with 47 points – and in an Eastern Conference – that just may be enough to make the Playoffs.

All for now …

Later this week, my run down on the English Premier League, La Liga, Bundesliga, and a special review on Expected Wins looking at all four leagues together…

Looking to answer this question – is comparing individual players on Barcelona to FC Koln, to Southampton, to LA Galaxy worthy given that the four leagues all have different patterns to winning – or do they?

Best, Chris

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