Should away teams be more aggressive?

The Portland Timbers traveled to Houston on Sunday in desperate need of three points to get out of the cellar in the Western Conference. They played well in the first half, outshooting the Dynamo 8 – 7 en route to a 1 – 1 tie, while dominating possession. Then Portland came out in the second half much like many away teams do with a tie score, conservatively. The second-half shot charts to the right serve as an indication of the change in strategy.

 

This conjured up a question that constantly bugs me. Should away teams go for wins more often when tied in the second half? Let’s get right to the data. Here is chart summarizing the offensive aggression of away teams during gamestates when the score is tied and the teams are playing with the same number of players. The data presents the proportion of totals earned by the away team in both the first and second halves.

2013 – 2014	Goals%	xGoals%	Shots%
1st Half	44.8% (266)	42.3% (282.9)	43.4% (2948)
2nd Half	34.8% (184)	37.4% (168.6)	39.7% (1654)
P-value	0.017	—	0.007

The away team consistently garners 42% to 45% of these primary offensive stats during the first half, and then drops down to the 35%-to-40% range in the second half. For the proportions of goals and shots, those differences are statistically significant (there is no simple test for xGoals%, but it is probably statistically significant as well).

My instinct is that away teams are capable of playing in the second half as they do in the first half, and that these discrepancies are a product of conscious decision making by away coaches and players. Teams likely change strategy in the second half to preserve a tie. Playing more openly would ostensibly increase the chances of both a loss and win, while decreasing the chances of a tie. However, I would think based on the data above that it would increase the chances of a win more so than the chances of a loss. Since a win would earn the away team an extra two points, while a loss would cost it just one, my gut says teams should go for it more often.

Are away teams playing conservatively because mindless soccer conventionality tells them that it’s okay to get one point on the road? Is this the self-detrimental risk aversion that plagues coaches in other sports, or are these numbers missing something that could justify the conservative play?

I can’t say that I’ve proven anything, but these data suggest the former.

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PWP – Who’s Best and Worst after 8 Weeks

Another exciting week in Major League Soccer.

Most of the headlines belong to New York, Seattle, DC United and New England as those four teams along with San Jose took 3 points; the instant measurement of success.

Duly noted, but a growing indicator in popularity is Possession with Purpose and the composite difference between how well an MLS team attacks versus defends across the broad spectrum of six key performance indicators in attack.  It’s grown enough that after answering my question about Passing Accuracy last Thursday Caleb Porter looked to me, smiled,  and said “Possession with Purpose”.

If you’re not familiar with those Six Steps here they are in a nutshell:

1. Possession,
2. Passing Accuracy across the entire pitch,
3. Penetration (that percentage of passing a team successfully accomplishes within the Final Third),
4. Creation of Goal Scoring Opportunities (that percentage of shots taken relative to successful passing within the Final Third),
5. Putting those shots on goal, and
6. Goals scored

In case you missed it the relationship of the data points supporting PWP Analysis (after 102 games this year) is very strong regardless of winning, losing or drawing; with the Correlation for Winning being; .9898, drawing; .9827 and losing; .9564.  Click Expected Wins (XpW) to read more…

And if not convinced that this effort is taking hold elsewhere it appears Ted Knutson (@statsbomb) has taken up the gauntlet to see how opponents passing behaviors impact defensive activities in the European Leagues; you may find this article of interest as well.

It will be interesting to see what insights Ted can offer on this; especially given he’s got three additional leagues to evaluate.  A great example coming up this week for MLS is the match between DC United and Portland.

DC United average over 18 crosses a game (home and away) playing a Diamond formation (6 of 7 games) – will that pattern continue against Portland or do we see a different defensive approach by Portland to manage (and reduce) that volume of crosses and thereby try to mitigate the strength of Eddie Johnson in the air???  (As noted on occasion by Sir Arthur Conan Doyle — “The game is afoot” replied Holmes to his loyal companion, Watson.)

With that offered here’s how the 19 teams in MLS compare to each other after eight weeks following the PWP guidelines:

PWP Composite Index Through Week 8

The tale of the tape sees Seattle clear the first quarter-mile hurdle ahead of Sporting KC and Colorado.  A strong indication that they are serious contenders for the Shield – and yes you would think so given their position in the Standings and that comprehensive victory against Colorado.

But waiting in the shadows, with three games in hand, is a very potent team called LA Galaxy; nine points from those three games in hand puts them atop the West.  And of note is that LA currently have the best PWP Composite Index of any team in MLS.

Can you hold your breath until July 26th when these two teams meet for the first time on National TV?  And how about the last two games of the regular season – back to back Nationally televised games again… wow……

Talk about a story-line; and all that coming after the World Cup…

But back to the basics; DC United took great advantage of Zach Loyd and his 2nd Yellow (Red Card) in the 39’th minute; scoring four goals and icing the game with Fabian Espindola’s second from an assist by Chris Rofle.

While I didn’t see the game I did get to watch the MLSSoccer.com recap here…  seems a bit dubious that two yellows like that would garner a Red Card but on the first one Loyd was clearly out of position and his pulling back Espindola warranted a Yellow given how tight the Referee’s have called games this year.

As for the second – well – any time you go studs up into a tackle you deserve a Yellow; shame on Loyd for two Yellows… and like Collin (Sporting KC) he put his team at a distinct disadvantage…

Other teams making moves this week included San Jose beating a woeful Chivas while Houston dropped two points by drawing, at home, to Portland. 

What was interesting to me about that game was how pedestrian, at times, the possession for Portland was.  Clearly there is an attempt by Caleb Porter to resurrect the successful possession based approach leveraged last year.

If a player like Gaston Fernandez can pair up more readily with the likes of Valeri and Nagbe then the Rose City should begin to feel better.  A great test comes this next weekend as they entertain another possession based team, DC United.

PWP Attacking Team of the week:  DC United

 

PWP Attacking Team of Week 8

DC United had a superb 84% completion rating in Passing; much no doubt do to Loyd being sent off before the first half.  But hey, if you can’t dominate a team when they are a man down then you’re not a good team… DC United proved they were good this weekend and proved it in style.

As for Seattle; sadly they had to play against an 11 man Colorado.  If not it is likely they would have scored 6 or 7 goals against the Rapids…

Mastroeni will need to work his back-four hard as they prepare for LA this weekend.

PWP Attacking Player of Week 8: Fabian Espindola

PWP Attacking Player of Week 8

Pretty comprehensive as Espindola took great advantage, as did his teammates, with Loyd’s poor performance…

Another player getting big headlines this weekend was Clint Dempsey.  Here’s how Clint lined up playing against the full strength Rapids:  99 touches, 55/59 (93% passing accuracy), 2 Key Passes and 2 Goals.  So a great game for Dempsey and a solid indication that his run of play over the last 3-4 games has been superb…

Other notable team attacking performances this week saw New York completely blast Houston 4-nil; that is two games running where New York matched or exceeded their PWP Index rating for last year – is it any wonder they’ve won the last two games?

As for bottom dwellers, Philadelphia was the only team in the bottom four without a Red Card; worst of the bunch this past week also included Chivas, Sporting KC, and FC Dallas.

Maybe it’s just me but another reason why a team’s Index shouldn’t double count the impact of a Red or Yellow Card – when players get booked (regardless of red or yellow) does it impact overall team PWP performance?  I think so, and I’ll look into that at the half-way point of the season.

I’ll look at teams that lose with and without players that got booked; not sure what I’ll find out but it should be interesting to see if it can be quantified to some extent.

PWP Defending Team of Week #8:  New England Revolution

PWP Defending Team of Week 8

A clean sheet is a clean sheet and so on… shutting out Sporting is probably easier at home than on the road – the rematches will be big games and Collin is probably pretty narked for that Red Card.  We shouldn’t be surprised though; he’s traditionally untimely in his tackles and with Opara (still injured?) Vermes may be hard pressed to find a suitable replacement.

Anyhow – the top play here was the back-four for New England shutting down Dwyer and Zusi… well done and not a surprise…

PWP Defending Player of Week 8: Chris Tierney

 

PWP Defending Player of Week 8

The toughest pick I had this week was selecting which defender got the award; both AJ Soares and Chris Tierney stood out over the others.

AJ offered up these defending attributes… 30 of 38 in passing for 79% accuracy, 69 touches, 1 tackle won, 2 blacked shots, 2 interceptions, 6 clearances and 3 recoveries.  Pretty close to the same outputs by Tierney – more appropriate though was the fact that the two of them partnered on the Revolution defensive left side, in their own final third in stopping 12 of 38 passes by Sporting KC.

In my view Tierney and Soares were far more productive for their team this weekend than Farrell – this isn’t the first time my PWP Players or teams don’t match what comes out of MLSSoccer.com – different views offer different outputs… both have value.

Congrats to San Jose for their clean sheet and kudo’s for Montreal winning a game that a switched-on Union should have won hands down… wow – what a surprise that outcome was!

Stay tuned for my PWP-Pick-List Week 9;  I’m at 44% success rate and I took a clean hit across the cheek when Montreal and New England took three points while Real Salt Lake gave away two points in that complete melt down against Vancouver…. my, oh my, oh my…

Best, Chris

 

Individual Defensive Statistics: Which Ones Matter and Top 10 MLS Defenders

When a car breaks down, a mechanic’s job is to tell you what caused the failure. He or she can generally pinpoint the problem to a specific part reaching the end of its useful life. But have you ever asked a mechanic why your car is working fine? Or which part deserves the most credit for your car running smoothly? Of course not. That would be a waste of everyone’s time. There are many parts to a car and all are doing their job as designed. We never ask why when things are going well.

The same dilemma exists in assessing soccer defenders. After all, most of how we assess defenders has to do with what goals were not scored. And when all the parts of the defenses are working as designed, goals are avoided. But which defenders deserve the credit when goals aren’t scored? It’s like the pointless car question, which parts of the car deserve the most credit when the car runs smoothly?

To even begin this conversation we need to take stock of what data exists for soccer defenders. And just to be clear, I am going to steer clear looking at a defender’s offensive capability. I want to focus solely on defensive statistics. Whoscored is the only site that offers a collection of defensive statistics, and here is what they have and their definitions.

• Blocked Shot: Prevention by an outfield player of an opponents shot reaching the goal
• Clearance: Action by a defending player that temporarily removes the attacking threat on their goal/that effectively alleviates pressure on their goal
• Interception: Preventing an opponent’s pass from reaching their teammates
• Offside Won: The last man to step up to catch an opponent in an offside position
• Tackle: Dispossessing an opponent, whether the tackling player comes away with the ball or not

These are the defensive-oriented statistics offered by Whoscored that are tracked at the individual player level. Of course, the other vital defensive statistic is shots conceded but those can’t be attributed to any one player. So then, do any of these statistics matter? First there are a couple of assumptions to iron out.

A defender should be judged by the rate at which he accumulates statistics. So to get to that number we need to adjust these statistics to account for the time that the opponent has the ball. For example, Player A who averages 5 clearances per game might be better than Player B who averages 6 clearances if Player A’s opposition had the ball 20% less often. That would mean player A made more clearances given the opportunities provided to him. So I will adjust all metrics by opposition possession.

Since I am trying to assess what goals are not scored, I going to look at the numbers at the team level first. It is only at the team level that goals can be attributed. After that analysis I will attempt to attribute value to the individual metrics.

sources: whoscored, mlssoccer.com

Here are tackles per game per minute of opponent possession against goals scored. Tackles represents the strongest correlation of all the variables. In fact, tackles has a slightly stronger correlation to goals against than shots conceded. Here is a look at the shots conceded as a percent of opponent minute of possession.

sources: whoscored.com, mlssoccer.com

The two points to the far left represent the LA Galaxy and Sporting Kansas City. They appear adept at limiting shots on goal per minute of opposition possession. They also stand out when looking at offsides won.

Rather than show every graph, here is a table of the defensive statistics, their level of impact and the R squared of the impact in predicting goals against.

Statistic	Goals Avoided per Unit	R squared
Clearances	-0.041	27.1%
Interceptions	-0.036	15.1%
Tackles	-0.077	39.4%
Offsides Won	-0.113	16.0%
Blocks % of Shots	-0.017	0.3%

Offsides won is the most impactful of the statistics (has the greatest slope) but there is a weaker correlation than Tackles or Clearances–in other words, there are greater deviations from the trend line. It’s interesting to see that Blocks as a percent of shots has almost no impact on goals allowed.

This is interesting, but what to make of it all? In an ideal world we could compile these statistics into a meaningful metric in order to compare players. The most obvious way to do that statistically would be to run a multivariate regression using all of the statistics.  The trouble with the result is that the statistics end up not being statistically significant predictors when mashed together. So developing a score from these metrics would be a bit of a fool’s errand.

The other option would be to ignore the predictive strength of the variables and just use the goals avoided results as a scalar, multiply them by each player’s statistics, add them up and compile a score. In this case the resulting score would be something we relate to as we could say that this player avoids x number of goals per game. However, this would give offsides won the statistic with the greatest importance despite the fact that the correlation is not strong.

To factor in the correlation we could leave the realm of sound statistical practice. We could multiply the goals avoided scalar by the R square. We could turn that into an index with the highest metric (tackles) equaling 1. If we did that here is the resulting table and values for each metric.

Statistic	Goals Avoided per Unit	R squared	GApU x R2	Index
Clearances	-0.041	27.1%	-0.011	0.37
Interceptions	-0.036	15.1%	-0.005	0.18
Tackles	-0.077	39.4%	-0.030	1.00
Offsides Won	-0.113	16.0%	-0.018	0.60
Blocks % of Shots	-0.017	0.3%	0.000	0.00

Tackles would be the most important statistic followed by offsides won and then clearances and interceptions. It turns out blocked shots have no material value in estimating goals against.

Before I use these numbers to reveal the top 10 MLS defenders, here are the caveats. Obviously this ranking is missing a few vital elements of defending in soccer. The first major omission is positioning. Often a defender being in the right position forces an offense to not make a pass that would increase their chance of scoring. There is no measurement for that but obviously a defender out of position is not a valuable defender. Clearances, interceptions, tackles and offsides won are clearing indicators that the player was probably in position to make the play and they indicate the player succeeding making the necessary play. But offensive attempts avoided are clearly missing.

The other major omission is the offensive play of the defender. A defender who defends well and represents an offensive threat is that much more valuable. But I’m not trying to solve for that here. I leave that for the subject of another post to integrate passing and offensive numbers to build a better score for defenders.

Here are the top 10 MLS defenders based on the score developed through the last week for players with a minimum of four appearances.

Rank	Name	Team	Tackles	Intercepts	Off Won	Clears	Defender Score
1	José Gonçalves	New England Rev.	1.6	2.4	2	11.2	7.376
2	Giancarlo Gonzalez	Columbus Crew	2.1	2.9	1.9	9.3	7.203
3	Norberto Paparatto	Portland Timbers	1.8	4.8	1.3	9.3	6.885
4	Carlos Bocanegra	CD Chivas USA	1.5	3.6	2.1	8.9	6.701
5	Andrew Farrell	New England Rev.	2.9	2.4	0.3	8.3	6.583
6	Jamison Olave	New York Red Bulls	1.9	3.1	1.7	6.7	5.957
7	Victor Bernardez	San Jose Quakes	1.5	2.8	0.7	9.5	5.939
8	Matt Hedges	FC Dallas	1.5	3.9	0.9	8.5	5.887
9	Eric Avila	CD Chivas USA	4	2.4	0.8	2.3	5.763
10	Chris Schuler	Real Salt Lake	1.8	2.8	0.5	8.3	5.675

I find it comforting that, for a new metric, Jose’ Goncalves, MLS Defender of the Year in 2013, tops the list. There’s a big drop between the top 2 defenders and Paparatto. There’s also another cliff after Andrew Farrell. But hey, it’s a start.

I hope this was an enlightening ride through the mechanics of defending from a soccer perspective. The next time you’re watching a game, don’t just focus on the breakdowns. Also look for what makes the defense successful.

 

Cumulative PWP: Four-Horse race to the Shield?

Early indications show it may be at least a four-horse race (at the near quarter-mile post) with FC Dallas, Columbus, Sporting, and LA leading the way.

Other favorites as Week 8 begins should include Colorado, Seattle, Real Salt Lake, and maybe a real sleeper (statistics wise) Toronto.

Note any early-season favorites missing? The obvious here are the two incumbent conference champions, New York and Portland. Defensive woes highlight their early season takeaways.

New York’s stategy last year (get more goals than the opponent) has only worked once this year and Portland’s strategy, patience and accuracy in their possession with purpose has taken a back seat to the poorly performing back-four. And in this case, even though four goals against come from Penalty Kicks (set-pieces) what that really means is the back-four (and some defending midfielders – Zemanski in particular) have not done their job.

If PWP is new to you here’s a link to the Introduction and some explanations – another link that may be useful is my new Expected Wins (XpW) article getting down to the basics – winning and the tendencies of teams that win.

Given the early stages of this horse race, here’s my traditional diagram for consideration:

PWP Composite Index Through Week 7

Prime movers this week include LA Galaxy dropping three places with that draw to Vancouver and two goals scored per each team.

Others taking a hit to their Index rating were DC United dropping two places with their hard fought draw against Columbus; Portland with that gut wrenching loss (superb saves by Rimando) away to Real Salt Lake and Montreal – a continued drop of two places after getting spanked by Sporting.

Bottom dwellers continue with San Jose and Chivas moving nowhere – while some might feel keeping Chivas (with a new name) in LA is a good thing I’d offer that moving them out may REALLY help kill the stigma of them simply not being a team that will compete regularly for a Playoff position.

Maybe St. Louis or some other city is better placed to host that organization?

Anyhow, FC Dallas, Columbus (almost by default) and Sporting KC all moved up a notch at the expense of LA while RSL continued their move up the Index as they leapfrogged Vancouver, DC United and Philadelphia.

Bottom line in this is that some teams continue to jockey for overall position but the moves up and down were less dramatic, as a whole, this week, than in previous weeks.  Solid play breeds confidence and confidence breeds success.

In looking at the Attacking side of the equation here’s the teams from top to bottom:

PWP Composite Attacking Index Through Week 7

Can anybody really question Pareja’s approach in Dallas so far this year?  Probably not – a Toronto side came to town with their brand of away football and came away with nil-pwa.

Of the eight top attacking teams seven of them exceed 50% in possession percentage with Real Salt Lake (49.77%) being the lone wolf; go figure that one?!?  That being said four of their first seven have been away games and three of those four away games saw them at ~49%, 43%, and 45%.

So back to some general indicators on the attacking side – all four of the top teams in attack exceed 40% in goals scored from shots on goal – yet none of those teams is in the top four for Shots on Goal versus Shots Taken; those four teams are Montreal, Real Salt Lake, Vancouver and Sporting.  A trend more noticable in my Expected Wins article…

Teams making the most effective use of penetration into the Atacking Third are New England (~29%), Houston (~24%), Philadelphia (~23%), and Columbus at (~23%).  Bottom dwellers in percentage of total passes inside the Attacking Third are Montreal (~17%), Colorado (~17%) with Sporting and FC Dallas at (~18%).

A good indicator for Portland (based upon last year’s averages) is that 18.83% of their possession has been in the Final Third.  What has lacked is controlling individual mistakes and positional play in Defense.

Will Johnson had some frustrated words to offer after that loss in Real Salt Lake (that I won’t quote) – hey – give the guy a break – he’s a fierce competitor and like most any of these guys he simply hates to lose…  but he’s right; professionals get paid to put up their best in tight situations.

If training doesn’t help some get better than it’s time for personnel changes…

Moving onto Defense and the PWP Composite Defending Index:

PWP Composite Defending Index Through Week 7

Like last year Sporting KC is simply tough in defense; and after 7 weeks of play they have now found themselves leading the pack… about time I expect…

Other top performing defending teams include LA, Colorado, Columbus and New England.  A continued presence by DC United should give warning that Olsen seems to be doing better in stopping their goals-against rot from last year.  Is it Boswell who’s made the overall difference?

In looking at the tail end both Chivas and Montreal continue to wallow at the back of the pack while Chicago, under Yallop, can’t seem to gallop at full stride yet either.

A few other notables here; FC Dallas, Seattle and Real Salt Lake are in the bottom ten on the defensive side of the pitch – that strategy was an indicator of New York simply outscoring their opponents.

A run of bad luck, shoddy shoes, dodgy goal keeping, or getting hamstrung with injuries could have a huge impact in their overall outputs.

The teams that should scare people the most are Sporting and LA Galaxy… and with Colorado and Columbus looking to gain confidence (and chemistry in their attack) they too may put paid to rest this idea that a team can simply win more games by outscoring their opponent.

That approach got New York the Supporter’s Shield last year but not the Championship – I think the teams going for it this year want the Championship and/or first place in their respective Divisions’.

In closing…

The plot thickens as does the muck and the mud on the track at the first turn in this yearly Derby. Hurdles await as does time spent at the World Cup, where the stakes for some players are so much higher than others.

Looking forward to an exciting weekend of MLS, and really wish the DC United match against FC Dallas was televised on National TV!

Best, Chris

 

MLS Week 8: Top 50 Shots

Okay, shots. We talk a lot about shots because, well, shots lead to goals. Obviously you can’t have a goal without first attempting a shot. I know that was a deep thought, but just go with me here.

We put a lot of emphasis on shots here and have dug into their expectation leading to goals. It’s backed by the belief that shots are important statistics in correlation to team success. Now there are plenty of caveats to shots and we use them to influence our ideas of what is good or bad. Matthias has taken time to explain at least some of them.

So with all that said you can’t read too much into all of these numbers. Take for instance the fact that Frederico Higuian creates 7.03 shots per 90 minutes. That’s nearly a shot and a quarter more than Brad Davis at 5.79. Is Higuian a better shot creator because he creates one additional shot over the course of a single match? If that shot is from zone 4 or even 5, the value of that single shot becomes marginalized in that specific instance.

Despite all of those various acknowledgements of how this is marginally interesting, and yet mostly a useless exercise, I put together a follow-up of last week’s top 50 individual shots creators in Major League Soccer. I decided it was best to cut up this data and present it via a tiered system to make it a bit more palatable and to highlight the players that have set themselves apart from their peers. Also, this allows me to be a bit creative in the tier process.

IBC Root Beer Tier – “The Best of the Best.”

	Player	Club	POS	MINS	G	A	SHTS	Key Passes	Sh-C	Sh-C p90
1	Marco Di Vaio	MTL	F	326	1	1	24	4	29	8.01
2	Clint Dempsey	SEA	M	393	6	3	23	7	33	7.56
3	Federico Higuain	CLB	F	538	4	2	20	20	42	7.03
4	Robbie Keane	LA	F	450	4	1	22	12	35	7.00
5	Pedro Morales	VAN	M	472	1	2	19	15	36	6.86
6	Thierry Henry	NY	F	449	2	0	23	9	32	6.41

Oh, yeah… Marco Di Viao. He’s also pretty good at this whole soccer thing. I guess we can all say that we could have guessed every singl–what the hell is Pedro Morales doing in there??? I guess that probably explains a lot about what’s been happening in Vancouver. He’s second overall in total Shots Created and he could very well be a shoo-in for MLS Newcomer of the Year.  He’s like the offensive equivalent of what Jose Goncalves was last year to New England. I only have one question: who is this Camilo guy everyone was talking about?

Stewart’s Root Beer Tier – “You don’t have IBC? Who doesn’t have IBC?”

	Player	Club	POS	MINS	G	A	SHTS	Key Passes	Sh-C	Sh-C p90
7	Landon Donovan	LA	M-F	450	0	2	13	14	29	5.80
8	Brad Davis	HOU	M	311	0	2	3	15	20	5.79
9	Graham Zusi	KC	F-M	450	1	3	9	16	28	5.60
10	Diego Valeri	POR	M	579	1	0	19	16	35	5.44
11	Dom Dwyer	KC	F	427	4	0	22	3	25	5.27
12	Leo Fernandes	PHI	F	436	2	1	13	11	25	5.16
13	Lloyd Sam	NY	M	621	1	3	12	20	35	5.07
14	Mike Magee	CHI	F	450	1	2	15	8	25	5.00
15	Giles Barnes	HOU	M	527	0	1	22	6	29	4.95
16	Justin Mapp	MTL	M	585	0	3	11	18	32	4.92
17	Michael Bradley	TOR	M	433	1	0	6	17	23	4.78
18	Mauro Diaz	DAL	M	604	2	3	13	16	32	4.77
19	Quincy Amarikwa	CHI	F	548	4	1	16	12	29	4.76
20	Felipe Martins	MTL	M	626	1	2	18	13	33	4.74
21	Gilberto	TOR	F	423	0	0	13	9	22	4.68
22	Cristian Maidana	PHI	M	425	0	2	11	9	22	4.66
23	Deshorn Brown	COL	F	448	1	0	19	4	23	4.62
24	Chris Wondolowski	SJ	F-M	450	3	0	20	3	23	4.60
25	Fabian Espindola	DC	F	531	2	2	11	14	27	4.58
26	Michel	DAL	M-D	401	3	2	11	7	20	4.49
27	Lamar Neagle	SEA	F	506	2	2	16	6	24	4.27
28	Obafemi Martins	SEA	F	620	2	4	13	12	29	4.21
29	Erick Torres	CHV	F	603	6	0	22	6	28	4.18
30	Javier Morales	RSL	M	527	0	2	7	15	24	4.10

Justin Mapp has the same amount of total Shots Created as Mauro Diaz in almost 20 minutes less field time. Try thinking about that next time you’re frustrated by Mapp’s hair line. Try.

Dom Dwyer does not go away. This guy could be someone that we may need to start legitimately talking about in the coming weeks. You should probably add Leo Fernandez and Lloyd Sam to that obnoxious hype list too.

Speaking of Sam, I added him to my MLS Fantasy Roster for tonight, hedging the bet that he finally scores a goal. At last look, the guy currently holds the highest xGoal predictor score without actually scoring a goal. If there was ever a guy that was “due” to score a goal, it’s him and I’m virtually betting on it happening.

On the note of not scoring goals, “Hi, Landon Donovan“. Who, in case you didn’t notice, is still a good player even when not putting the ball in the back of the net. Because, you know, skillz.

 

Barqs Root Beer Tier – “Old Reliable”

	Player	Club	POS	MINS	G	A	SHTS	Key Passes	Sh-C	Sh-C p90
31	Dwayne De Rosario	TOR	M	254	0	0	10	1	11	3.90
32	Mauro Rosales	CHV	M	626	0	3	10	14	27	3.88
33	Kenny Miller	VAN	F	537	3	1	14	8	23	3.85
34	Bradley Wright-Phillips	NY	F	358	1	0	12	3	15	3.77
35	Darren Mattocks	VAN	F	580	2	3	13	8	24	3.72
36	Jack McInerney	MTL	F	436	2	1	13	4	18	3.72
37	Will Bruin	HOU	F	539	3	1	14	7	22	3.67
38	Baggio Husidic	LA	M	344	1	1	7	6	14	3.66
39	Bernardo Anor	CLB	M	497	2	0	16	4	20	3.62
40	Hector Jimenez	CLB	M	523	1	2	9	10	21	3.61
41	Teal Bunbury	NE	F	630	0	1	14	10	25	3.57
42	Diego Fagundez	NE	M-F	584	0	0	19	4	23	3.54
43	Sal Zizzo	KC	F	433	0	2	10	5	17	3.53
44	Kenny Cooper	SEA	F	358	2	1	12	1	14	3.52
45	Benny Feilhaber	KC	M	539	1	1	8	12	21	3.51
46	Juninho	LA	M	448	0	2	8	7	17	3.42
47	Andrew Wenger	PHI	F	528	2	0	14	6	20	3.41
48	Eric Alexander	NY	M	451	0	3	7	7	17	3.39
49	Alex	CHI	M	512	0	0	12	7	19	3.34
50	Saer Sene	NE	M	355	0	0	8	5	13	3.30

 

There are roughly 19 names here and I’m not going to go through them all. But key surprises are Jack McInerney, who everyone continues to think is “slumping” when he’s not scoring goals. Baggio Husidic is making waves in that flashy new diamond attack in LA. Husidic is filling the hole that once upon a time existed out wide and makes the Robbie Rogers-trade look worse and worse, as he likely won’t make it past a bench position upon return. Bernardo Anor has been doing a lot for Columbus out of the midfield but, perhaps, the bigger story than Anor–or even the LA trade for Rogers–is that fact that Gregg Berhalter pretty much stole Hector Jimenez who is looking brilliant in his new Crew colors.

Lastly, three other off season moves are having impacts with their new clubs.

1. Teal Bunbury is finally being “the other guy” and taking shots in New England. Lord knows they need to start converting those opportunities.
2. Sal Zizzo wasn’t exactly a headline move this off-season, but since being let go by Portland this past off-season he’s been a gold staple in the Sporting KC line-up.
3. Kenny Cooper is having himself a quietly productive first season in the Emerald City. Yes, it’s towards the bottom of the line-up and it doesn’t really mean much of anything. But he’s been reliable and fits in with Clint Dempsey and Oba Martins, playing the third/fourth fiddle and doing whatever needs to happen. Great role for him and he’s doing it well.

There are a lot of things to take away from this. Like why didn’t I just make two tiers: IBC Rootbeer and Barqs, which is basically all you’re going to go with unless there is some local brewed Root beer that you want to try for funsies. Anyways, some information here. Not necessarily good information, but at this stage of analysis and data when it comes to MLS, and really soccer in general, what is “good” information?

PWP Week 7: Zusi has a Sporting impact as Moor Rapidly manages threat of Earthquakes

Week 7 got an early start with a first for New York this year – a win. Was there anything else that stood out this week, and who managed the top spot?

To kick off my PWP for Week 7, and only week 7, here’s my traditional diagram showing the highs and lows and everyone in between..

PWP Strategic Composite Index Week 7

The Capt. Obvious here is the 4-nil thrashing that Sporting KC put on Montreal; if there is a Head Coach on the hot seat, in the early days of 2014, it’s likely to be Frank Klopas; wow…

What may be surprising to you is that Dom Dwyer did not get my PWP Attacking Player of the Week; why?

Because most good strikers score goals – what’s critical in my view is the amount of set-up and overall interaction that goes with creating those goal scoring opportunities.  And as much as I’d like to favor Dom Dwyer, he had just 58 touches with 11 passes, 5 of them unsuccessful for a 54% passing accuracy…  good but not great in my view.

Other teams getting worthy results this week were Seattle, Real, and Dallas in addition to New York, hopeful of taking three points but somewhat satisfied with one point are New England, San Jose and DC United; disappointed with draws were most probably Chicago, Colorado and Columbus.

In considering Sporting KC scored three, plus got an own-goal by Montreal, how did their Six Steps in the PWP Process play out?  Below are the overall outputs:

PWP Attacking Process Sporting KC Week 7

In case you missed it one of my newer focus areas this year is passing accuracy.

For now I think there is great value in recognizing how much influence 81% passing accuracy has across the entire pitch; even more so within the Final Third.

For this game Sporting were successful in completing ~71% of their passes in the Final third; that accuracy led to having 58% of their shots taken go on goal and a 57% success rating in having those shots on goal score goals.

In simple terms it almost didn’t matter where the shots were taken that scored (2 outside the 6 yard box and 1 outside the 18 yard box) – plus an own goal (from between the corner of the 6 and 18 yard box).

To get a better picture on that relationship between passing, penetration and goal scoring you may want to read this latest on Expected Wins.

For now here’s my PWP Attacking Player of Week 7:  Graham Zusi.

PWP Attacking Player of Week 7

Some pretty comprehensive play by Graham Zusi.  His volume of touches, passing accuracy, and work within the midfield (in defense) as well as his accuracy (final third) was crucial in creating scoring opportunities for Sporting.  What speaks more to me about Graham is his continued growth in playing on both sides of the ball.  That rigor and discipline will do well to help him and his teammates in the World Cup this year.

Of note is that Graham offered up five successful crosses; that’s more than the per game average for all these teams in MLS this year: Colorado, Chivas, DC United, FC Dallas, New England, Portland, Philadelphia, Real and Vancouver.

By the way, the most successful team in delivering crosses this year is LA; with a 34.06% success rate.

Toronto is next at 32.21% while Sporting is 3rd best at 31.69%.  Bottom of the league in offering up successful crosses per game is Portland at just 16.34%.

Moving on to the Defending PWP team of Week 7:

PWP Defending Process Colorado Week 7

This one may have come as a surprise but in looking at the attack of San Jose it’s no wonder Colorado looks this good when defending against them.

All told San Jose had no shots on goal and no goals scored with minimal penetration generating just 6 shots, 2 of which were blocked.

Bottom line is that Colorado basically snuffed out just about everything San Jose had to offer.

So who is my PWP Defending Player of the Week?

All told O’Neill, Piermayr and Klute all had great games with O’Neill completing 49 of 52 passes playing right fullback.  Hard choice this game by my award goes to Drew Moor.

In a league where top flight Center-Backs are needed, Moor did a great job controlling the 18 yard box against a team that loves to cross the ball.

San Jose completed just 5 of 23 crosses – and for a guy like Wondolowski, who lives of crosses, Moor did a stand-up job.

Here’s the highlighted statistics I picked out for him this game.

PWP Defending Player of Week 7

In Closing…

Week 7 has come and gone and the chase continues; some look to be dropping back a bit further while others rise to the top on a regular basis.

Next up I’ll get into the Composite Index for all games played to date.

For now know that it’s getting pretty packed up top – but clarity on the five playoff spots for each conference will take a while to sort itself out, as it should.

Best, Chris

How it Happened: Week seven

I hate to be a disappointment, but Easter weekend means I only got to review two matches instead of the usual three. One was a doozy: a premier matchup of Western Conference powers, while the other had a pretty incredible final five minutes. On to the show (and if you’re really jonesing for some analysis of Chivas-Seattle from Saturday night, I’ll probably tweet some thoughts when I catch up on it later this week).

Real Salt Lake 1 – 0 Portland Timbers

Stat that told the story for Salt Lake: 23/37 passes in attacking center of the field

Stat that told the story for Portland: 7/12 passes in attacking center of the field

 

We’re breaking new ground with this one: I’m combining both teams’ stats for this game. These two teams have had drastically different starts to the season, with RSL grinding out results against a very difficult schedule and Portland failing to do the same against an easier slate. Still, the margin of quality between these teams is pretty slim, and that fact was borne out this weekend.

From a Real Salt Lake standpoint, this game was pretty much par for the course for 2014 and really the last five seasons. Aside from a few surprising miscues in possession that gifted chances to the Timbers, RSL’s diamond midfield was good in possession and solid in defense. They found a weakness in Portland’s defense by attacking the channel to the right of the Timbers’ centerbacks (that’s where all the incisive passes above, and Ned Grabavoy’s goal, came). Even though they weren’t at their clinical best, using tiki-taka passes to break through the backline, RSL did their job and got three points at home.

As a Timbers fan, it’s yet another missed opportunity for Portland to get that elusive first win of the year. Theories of what’s plaguing the 2014 Timbers are abound, and like ghost stories or craft beers, I have my likes and dislikes. I’ll say two things on PTFC here: (1) their demise is overstated. Portland has hit the post like a million times already this year,* and the Timbers have only been outscored by four goals (coincidentally the number of penalties they’ve given up). Once those two areas regress to the mean, it’s likely the Timbers will start to earn points and earn them fast.

*Portland leads the league in posts and crossbars hit during even gamestates with four.

But that brings me to (2): the Timbers aren’t playing as well as they did for much of last season. They are a team that thrives on possession when at their best, yet they’ve been out-possessed in each of their last five games. It’s like Portland is always flooring the engine, pushing the ball vertical to rush into shots instead of occasionally using cruise control and slowing the game down. A huge issue for them in this game was their lack of penetration in attack, as illustrated by the image above. Still, the game went back and forth with Portland and RSL both controlling the game for portions, and only the quality finish by Grabavoy instead of the fluffed chances by Maxi Urruti decided the result.

Chicago Fire 1 – 1 New England Revolution

Stat that told the story for New England: Teal Bunbury playing out of position in his position

That stat above makes no sense, so I’ll let someone much wiser than me explain.

Bunbury has been playing up top for New England for the entirety of this season, and while he’s always been thought of as a striker, he fits better as a winger in the Revolution’s system. His speed is his greatest asset while his finishing leaves something to be desired, two sure signs that lone striker isn’t necessarily your best fit. At center forward in this one, Bunbury gave a lot of great effort and the team tried to set him off to the races behind Chicago’s backline. But it was never particularly successful. Late in the match, Bunbury was shifted out wide as Jerry Bengtson came on, and he promptly created a chance out of nothing by simply running really fast around Chicago’s left back. I’d love to see more of that and less of Bunbury struggling up top in the future for New England.

Stat that told the story for Chicago: 11 turnovers in their own half by Bakary Soumare and Jhon Kennedy Hurtado

Chicago played well enough to win this game, and probably should have. If not for a poor penalty kick in stoppage time that was easily saved by Bobby Shuttleworth, the Fire would’ve left with three points instead of yet another draw. The draws are getting to be ridiculous for Chicago (6 in 7 games!), but they really have no one to blame but themselves. In addition to the penalty fiasco, the goal they gave up immediately followed one of those 11 turnovers by Chicago centerbacks. Patrick Nyarko was the one who gave up the penalty, but Soumare and Hurtado deserve at least a share of the blame. This was hardly an isolated incident for Chicago – their centerbacks have been shaky all season. Think they regret trading away Austin Berry right about now?

 

Agree with my ideas? Think I’m an idiot? I love to hear feedback: @MLSAtheist

Week 8: My PWP Pick List

Two weeks in and my PWP-Pick-List is doing pretty well:

If you tracked my picks from last week I nailed the wins by Seattle, Real Salt Lake, Sporting, FC Dallas, and the two draws – Vancouver v LA Galaxy and Chicago v New England.  That’s 5 for 9 in my first week (Week 6) and 6 for 10 in my second week (Week 7).

With that said, and if you’ve read my latest article on Expected Wins, (XpW) you’ll know that I will no longer be picking draws as an outcome – granted they will happen, but since no team really goes into a game expected a draw then my picks won’t either.

For now XpW won’t be part of my PWP-Pick-List.  Each team has only played 5-7 games so far, and that’s not enough individual sample points to support a reasonable correlation (R2) that has relevance.  Figure by Week 17 I’ll start to include the R2 for each team (home and away games) and then by Week 24 I will start to separate out the R2 for Home games versus Away games.

For now my source in this effort is strictly my subjective view on the objective data that I collect as part of my Possession with Purpose analysis.

To begin, your Week 8 picks:

New York Red Bulls hosting Houston Dynamo:  This is a hard call; Houston has David Horst back but Sarkodie is missing due to that red card last weekend.  It seems to me that when all four of the back-four are in and playing this team is really tough to beat.  That being said the Red Bulls got two goals against an improving Union side last week and they don’t have a short week to prepare like Houston.  Bottom line here is I see New York winning this game.

Seattle at home to Colorado:  Dempsey didn’t score against Chivas but he didn’t need to – instead he began to show his value in creating space and assisting others in scoring goals.  That additional value adds tremendous strength to the Sounders attack.  On the other hand, Colorado is no slouch when it comes to winning away games so this will be a huge test to the Seattle back-four.  Can they contain Brown?  I think so and Seattle wins…  though I wouldn’t be surprised to see this game end 2-1 or 3-2 given the weaker center with the Seattle back-four.

Philadelphia travels to Montreal:  In short – I simply don’t see Montreal winning, or even getting a draw at home against a Union side that probably could have done better this past weekend. The Impact have one of the poorest performing teams on both sides of the ball, and Klopas (imo) simply runs an archaic (direct attacking) system that no longer belongs in the MLS – more mounting losses for Monreal, and by the summer transfer window I could see Klopas being given the heave-ho.  Union win…

DC United entertain FC Dallas:  A resurgent DC United with a quality striking partnership of Johnson and Espindola is working well as Kitchen runs the single pivot.  A great matchup where DC United is likely to have more of the possession.  That said Diaz and the creative midfield for Dallas can win this one and keep their strong start alive.  If I would bet on a draw it would be this one but I think the edge goes to Dallas.  IF DC United win this one then the Eastern Conference really needs to be considered about the positive confidence they’ll gain with three points.  If there was a game to be played on National TV this next weekend this would be a good one.

Columbus at home to New York:  A short rest for the Red Bulls against a well rested Crew that are probably disappointed they didn’t take three points from DC United.  I think defense wins this game and in my view the defense for Columbus is better than what New York offers.  Crew win…

Sporting KC travel to New England:  The team formerly known as the wizards offered some offensive magic against a fast fading Montreal this past week and the Revolution will need to be in fine fiddle to control the volume of successful crosses I’d expect to see this game.  Can the New England defense hold and will the ability of the KC back-four be enough to contain a Revolution side who have struggled at times to score this season.  All told I’m not quite sure – I’d like to offer this as a draw as well but I think the improving attack, to go along with the best defense in MLS, gives Sporting the edge.  I won’t always pick Sporting to win every game this year, and against some Western Conference teams I won’t, but for now SKC wins.

Real Salt Lake at home to Vancouver:  Real continue to show quality versus quantity and they also continue to move up the ladder in my Composite PWP.  Vancouver had two very tough games against LA back to back and the wicked attack (with a healthy Plata) won’t get any easier in Rio Tinto.  Real Salt Lake wins…

San Jose versus Chivas:  The Earthquakes have yet to win a game this year and no better opportunity to do that than this week.  Their continued use of crossing as a prime source for creating goal scoring opportunities should get them that three points provided Torres can be controlled in attack.  He’s shown an ability to score as well so this one probably doesn’t see either team getting a clean sheet but I do think the Earthquakes take three.

Portland travels to Houston:  Are the cards right for the Timbers to get their first three points?  We saw Nanchoff come on as a late sub and Valeri, along with Kalif and others, seemed to struggle with their passing accuracy.  Having vision and accuracy in tight spaces is what separated the Timbers last year from the Timbers this year.  That and a healthy, well communicating back-four led by Ricketts.  That being said Houston are coming into this game on short rest and Kinnear will want his players to stamp their irritating level of physical play early on.  This is likely to be a VERY physical game for both teams but the edge for the Timbers needs to be real sharp as they are simply fed up with not winning.  I think the Timbers find the back of the net and win.  If it’s Urruti great; but in this game, Valeri needs to score.

All for now and not an easy thing for me to ignore picking draws – but I remain steadfastly stubborn and stubbornly steadfast that teams don’t enter games with an intent to get one point – so in my picks I won’t either.

Best, Chris

Expected Wins in MLS

Over the two and a half years I’ve been developing Possession with Purpose you’ve heard me go on about this game not just being about scoring goals it’s about winning.  I don’t mean that in the sense that you don’t need to score goals to win; you do. 

But what separates winning from losing statistics wise?  And if there is separation, what is it, and what value does it bring?

I’m not sure I have ‘the’ answers but I do have ‘some’ answers…

To begin here are the 7 primary data points I collect and calculate ratios with in my PWP Six Step Process analysis:

1. Passes Attempted Entire Pitch
2. Passes Completed Entire Pitch
3. Passes Attempted Final Third
4. Passes Completed Final Third
5. Shots Taken
6. Shots on Goal
7. Goals Scored

I collect these data points for every team, for every game; all 646 from last year and up to 102 (61 Games) so far this year.

In looking at the data this year the below diagram offers up the averages of those 7 data points, for all games, up to the end of Week 6. 

The blue bar is the overall Average for all games regardless of points earned, the green bar is the Average for all games where teams took three points, the amber bar is the Average where teams took one point, and the red bar is the Average where teams got nil-pwa.  

Expected Wins PWP Data Points

Facts as they exist today after 102 games in 2014:

The table just beneath the bar graph indicates the raw numbers (averages); for example the average Successful passes for teams that lose (in the Final Third) is 73.13; their average Shots taken is 13.39; their average Shots on goal is 4.10 and their average Goals scored is .58.

Here are the percentages derived by comparing the relationship of each of these points(part of my PWP analysis) working left to right:

• Teams that win average 50.30% Possession versus teams that lose average 49.70% Possession.
• Teams that win average 76% Passing Accuracy across the Entire Pitch. /// teams that lose average 74% Passing Accuracy across the Entire Pitch.
• Teams that win average 71% Passing Accuracy in the Final Third. /// teams that lose average 64% Passing Accuracy in the Final Third.
• Teams that win average 22% of all their Passes Attempted in the Final Third /// teams that lose average 25% of all their Passes Attempted in the Final Third.
• Teams that win average 17% Shots Taken vs Completed Passes in the Final Third. /// teams that lose average 18% Shots Taken vs Completed Passes in the Final Third.
• Teams that win average 40% Shots on Goal vs Shots Taken. /// teams that lose average 31% Shots on Goal vs Shots Taken.
• Teams that win average 45% Goals Scored vs Shots on Goal. /// teams that lose average 14% Goals Scored vs Shots on Goal.

Observations:

While 2% difference in overall Passing Accuracy might not mean much it should be noted as a reasonable indicator on how well a teams’ Passing Accuracy will be in penetrating the Final Third.

That 2% difference translates this way.  When a team makes 500 pass attempts.  76% * 500 Passes equals = 380 Completed Passes.  74% * 500 Passes equals 370 Completed Passes.

Any one of those unsuccessful passes could be the pass that gets you that goal or leads to the Opponent making an interception (quick counter) that gets them a goal.

Perhaps it is easier to understand why some coaches say control of the game and possession adds value?  Those teams that are more accurate in their overall passing are more likely to win.

In looking at Passing Accuracy within the Final Third there is a clear difference between winners and losers; winning teams are 9% better in Passing Accuracy within the Final Third… this is not about volume of passes – it’s about the accuracy of those passes.

To put that into perspective say a team attempts 100 passes in the Final Third; 71 of those passes (71%) are successful for the winning team whereas  only 64 (64%) are successful for the losing team.

That difference of 7 (within the tight confines of the Final Third) could make a BIG difference; those 7 extra completed passes could be 7 through-balls, key passes, or crosses that lead to a goal versus no goal.

Note that losing teams take more shots (on average) per pass completed (18%) than teams that win (17%).

Is that an indicator that the less effective team is trying to compensate for lower skill levels/overall passing accuracy by increasing their shots taken totals?  I think so.

And when looking at the ability of a winning team to put a shot taken on goal (a more accurate shot) the winning teams do that 9% better than losing teams.

And that initial accuracy then translates to a huge, if not inordinately large, difference between a team that wins versus loses; 45% of shots on goal are goals scored for winners versus 14% for losers.

Now for the second diagram and the R2 for the overall average, wins, draws, and losses with the backdrop lines being the real numbers for all 102 games this year..

The “x and y” axis represent the same things as they did in the first diagram.  The Blue, Green, Yellow and Red lines represent the averages ‘in trend-line format’ seen in the above diagram with their corresponding exponential correlations.  

I selected the Exponential Relationship as opposed to a Linear Relationship because I think it best represents the drop off in passes (in total) versus those just within the Final Third; the R2 will remain the same regardless.

 

Expected Wins PWP Data Points Correlations

Observations:

First off – all those lines are the 102 games worth of data that populate the diagram – it is that data that also formed the ‘averages’ for the first diagram…

That tight difference in R2 means there is a very tight margin of error between winning, losing and getting a draw; and if you’ve watched a game you know a single mistake can cost you three points.

However tight, there is a difference between the R2 for winning teams versus losing teams.  Is that statistical difference associated with those percentage differences indicated in the first diagram?

I think so, and while Possession (itself) is not “the” prime indicator on whether a team wins or loses it is “an” indicator that should be considered, when viewing overall passing accuracy within and outside the Final Third.

Perhaps the TV pundits will take more time to show better graphics where the Final Third data (in possession percentage) is separated out from the overall possession data?

Perhaps another view that may be helpful to others is the ‘space available’ that gets leveraged in creating that goal scoring opportunity?

I don’t know if this data is representative for teams in Europe – but the data certainly supports that view for teams in Major League Soccer.

To reinforce the End State (winning) from a different viewpoint. 

Last year the top five teams in volume of shots taken versus passes completed in the Final Third were Chicago, (26%), Philadelphia (26%), FC Dallas (26%), Montreal (25%) and Columbus (23%).

Only one of those teams made the MLS Playoffs – Montreal.

This year the top three teams with the highest volume of shots taken versus passes completed in the Final Third are Montreal (28%), Chicago (28%) and San Jose (26%); two of those three teams are the current bottom dwellers in the Eastern and Western Conferences.

In all this I’ve not talked anything about defensive play… more later this year on how teams perform without the ball with specific focus on defensive efforts (collectively and by individual defensive action) within the Final Third.

For now I offer these questions:

• Do you think teams that defend better do so as a team (collectively) or is it individual actions like clearances, tackles, interceptions or recoveries that stand alone?
• And does the general formation they play to (advertised as ‘the formation’ in the MLS recaps) show results differently in how a defense performs?
• And does the relationship of the individual or collective defensive activities relate better to unsuccessful passes in the Final Third?

My intent will be to answer these questions, and more, as the data piles up (figure once the 17 game mark is reached, for most MLS teams, I will have enough to offer a reasonable view on what is and isn’t of value.  With respect to the data discussed here – I have the 102 games here and the 646 games from last year.

When circling back to my overall PWP Composite Index – here it is put another way…

• The Attacking Index is the relationship those seven data points have with respect to the six steps in the PWP Process.
• The Defending Index is the relationship the Opponents seven data points have with respect to the six steps in the PWP Process.
• The Composite Index is the difference between those two Indices.
• This year, at this time, the overall Correlation of that analysis is an R2 of  .7658 – the R2 for Goal Differential is .8729.
• The R2 for Goals Scored is .5083 and the R2 for Attacking PWP is .5865
• The R2 for Goals Against is -.6754. and the R2 for Defending PWP is -.6225
• Bottom line here is that the PWP Composite Index has the 2nd highest R2.  With that you should have a better feel for what goes on behind the scenes to get there as opposed to just looking at Goal Differential.
• The more data points collected the more relevant the R2.
• How this plays out by the end of the season is unclear but as a reminder the overall PWP Composite Index was 90% accurate by the end of the 2013 in showing what teams would make the playoffs and what teams wouldn’t.
• And two of the top three teams in the Composite PWP Index for 2013 were in the MLS Championship Finals…
• Starting for Week 8 my PWP-Pick-List will offer up my prognostications about a team either winning or losing… no more draws will be offered up as no one team ever goes into a regular season game wanting to get a draw.  A draw is good but the intent of a Head Coach is to win first.

In closing…

The repeatable statistic in this effort is wins, draws and losses…

Expected Wins is all about what it generally takes to win a game versus lose a game; it’s not about getting a draw.

Expected Goals is an ‘effect’ relative to Expected Wins and the ‘causing’ relationship between those seven data points; i.e. the combined effort of a team as it possesses, passes and penetrates with purpose.  Hence my phrase offreed up some time ago “quality beats quantity”.

And yes, set-pieces win games, and sometimes the team getting those and scoring from those does that against the run-of-play; I suppose that is why the R2 for wins, draws, and losses is so close.

However viewed, teams play to win and score goals.  Various strategies and tactics may be used depending upon location, game state, game conditions, team formations, player selections, or what’s needed to move on, if in a knock-out or other tournament type condition.

It will be interesting to see how this analysis unfolds for the World Cup this year… more to follow… Here is the link on more to follow for MLS this year… Expected Wins 2 (92 games /// 184 events)

Bottom line at the Bottom:  For the MLS, every team wants to win every game – those teams that are more successful in winning are those teams that:

1. Have slightly more possession,
2. Have better passing accuracy, 
3. Have more patience in penetrating the Final Third,
4. Take slightly fewer shots,
5. Put more shots on goal and,
6. Score more goals.

Best, Chris

Looking for the model-busting formula

Well that title is a little contradictory, no? If there’s a formula to beat the model then it should be part of the model and thus no longer a model buster. But I digress. That article about RSL last week sparked some good conversation about figuring out what makes one team’s shots potentially worth more than those of another team. RSL scored 56 goals (by their own bodies) last season, but were only expected to score 44, a 12-goal discrepancy. Before getting into where that came from, here’s how our Expected Goals data values each shot:

1. Shot Location: Where the shot was taken
2. Body part: Headed or kicked
3. Gamestate: xGD is calculated in total, and also specifically during even gamestates when teams are most likely playing more, shall we say, competitively.
4. Pattern of Play: What the situation on the field was like. For instance, shots taken off corner kicks have a lower chance of going in, likely due to a packed 18-yard box. These things are considered, based on the Opta definitions for pattern of play.

But these exclude some potentially important information, as Steve Fenn and Jared Young pointed out. I would say, based on their comments, that the two primary hindrances to our model are:

1. How to differentiate between the “sub-zones” of each zone. As Steve put it, was the shot from the far corner of Zone 2, more than 18 yards from goal? Or was it from right up next to zone 1, about 6.5 yards from goal?
2. How clean a look the shooter got. A proportion of blocked shots could help to explain some of that, but we’re still missing the time component and the goalkeeper’s positioning. How much time did the shooter have to place his shot and how open was the net?

Unfortunately, I can’t go get a better data set right now so hindrance number 1 will have to wait. But I can use the data set that I already have to explore some other trends that may help to identify potential sources of RSL’s ability to finish. My focus here will be on their offense, using some of the ideas from the second point about getting a clean look at goal.

Since we have information about shot placement, let’s look at that first. I broke down each shot on target by which sixth of the goal it targeted to assess RSL’s accuracy and placement. Since the 2013 season, RSL is second in the league in getting its shots on goal (37.25%), and among those shots, RSL places the ball better than any other team. Below is a graphic of the league’s placement rates versus those of RSL over that same time period. (The corner shots were consolidated for this analysis because it didn’t matter to which corner the shot was placed.)

 

RSL obviously placed shots where the keeper was not likely at: the corners. That’s a good strategy, I hear. If I include shot placement in the model, RSL’s 12-goal difference in 2013 completely evaporates. This new model expected them to score 55.87 goals in 2013, almost exactly the 56 they scored.

Admittedly, it isn’t earth-shattering news that teams score by shooting at the corners, but I still think it’s important. In baseball, we sometimes assess hitters and pitchers by their batting average on balls in play (BABIP), a success rate during specific instances only when the ball is contacted. It’s obvious that batters with higher BABIPs will also have higher overall batting averages, just like teams that shoot toward the corners will score more goals.

But just because it is obvious doesn’t mean that this information is worthless. On the contrary, baseball’s sabermetricians have figured out that BABIP takes a long time to stabilize, and that a player who is outperforming or underperforming his BABIP is likely to regress. Now that we know that RSL is beating the model due to its shot placement, this begs the question, do accuracy and placement stabilize at the team level?

To some degree, yes! First, there is a relationship between a team’s shots on target totals from the first half of the season and the second half of the season. Between 2011 and 2013, the correlation coefficient for 56 team-seasons was 0.29. Not huge, but it does exist. Looking further, I calculated the differences between teams’ expected goals in our current model and teams’ expected goals in this new shot placement model. The correlation from first half to second half on that one was 0.54.

To summarize, getting shots on goal can be repeated to a small degree, but where those shots are placed in the goal can be repeated at the team level. There is some stabilization going on. This gives RSL fans hope that at least some of this model-busting is due to a skill that will stick around.

Of course, that still doesn’t tell us why RSL is placing shots well as a team. Are their players more skilled? Or is it the system that creates a greater proportion of wide-open looks?

Seeking details that may indicate a better shot opportunity, I will start with assisted shots. A large proportion of assisted shots may indicate that a team will find open players in front of net more often, thus creating more time and space for shots. However, an assisted shot is no more likely to go in than an unassisted one, and RSL’s 74.9-percent assist rate is only marginally better than the league’s 73.1 percent, anyway. RSL actually scored about six fewer goals than expected on assisted shots, and six more goals than expected on unassisted shots. It becomes apparent that we’re barking up the wrong tree here.*

Are some teams more capable of not getting their shots blocked? If so then then those teams would likely finish better than the league average. One little problem with this theory is that RSL gets it shots blocked more often than the league average. Plus, in 2013, blocked shot percentages from the first half of the season had a (statistically insignificant) negative correlation to blocked shots in the second half of the season, suggesting strongly that blocked shots are more influenced by randomness and the defense, rather than by the offense which is taking the shots.

Maybe some teams get easier looks by forcing rebounds and following them up efficiently. Indeed, in 2013 RSL led the league in “rebound goals scored” with nine, where a rebounded shot is one that occurs within five seconds of the previous shot. That beat their expected goals on those particular shots by 5.6 goals. However, earning rebounds does not appear to be much of a skill, and neither does finishing them. The correlation between first-half and second-half rebound chances was a meager–and statistically insignificant–0.13, while the added value of a “rebound variable” to the expected goals model was virtually unnoticeable. RSL could be the best team at tucking away rebounds, but that’s not a repeatable league-wide skill. And much of that 5.6-goal advantage is explained by the fact that RSL places the ball well, regardless of whether or not the shot came off a rebound.

Jared did some research for us showing that teams that get an extremely high number of shots within a game are less likely to score on each shot. It probably has something to do with going for quantity rather than quality, and possibly playing from behind and having to fire away against a packed box. While that applies within a game, it does not seem to apply over the course of a season. Between 2011 and 2013, the correlation between a teams attempts per game and finishing rate per attempt was virtually zero.

If RSL spends a lot of time in the lead and very little time playing from behind–true for many winning teams–then its chances may come more often against stretched defenses. RSL spent the fourth most minutes in 2013 with the lead, and the fifth fewest minutes playing from behind. In 2013, there was a 0.47 correlation between teams’ abilities to outperform Expected Goals and the ratio of time they spent in positive versus negative gamestates.

If RSL’s boost in scoring comes mostly from those times when they are in the lead, that would be bad news since their Expected Goals data in even gamestates was not impressive then, and is not impressive now. But if the difference comes more from shot placement, then the team could retain some of its goal-scoring prowess. 8.3 goals of that 12-goal discrepancy I’m trying to explain in 2013 came during even gamestates, when perhaps their ability to place shots helped them to beat the expectations. But the other 4-ish additional goals likely came from spending increased time in positive gamestates. It is my guess that RSL won’t be able to outperform their even gamestate expectation by nearly as much this season, but at this point, I wouldn’t put it past them either.

We come to the unsatisfying conclusion that we still don’t know exactly why RSL is beating the model. Maybe the players are more skilled, maybe the attack leaves defenses out of position, maybe it spent more time in positive gamestates than it “should have.” And maybe RSL just gets a bunch of shots from the closest edge of each zone. Better data sets will hopefully sort this out someday.

*This doesn’t necessarily suggest that assisted shots have no advantage. It could be that assisted shots are more commonly taken by less-skilled finishers, and that unassisted shots are taken by the most-skilled finishers. However, even if that is true, it wouldn’t explain why RSL is finishing better than expected, which is the point of this article.