Splitting Up Duncan Keith and Brent Seabrook

Outside of Patrick Kane's impressive move to the middle, perhaps the biggest story in Chicago's impressive 7-2-2 start has been Joel Quenneville's decision to split up Duncan Keith and Brent Seabrook. The natural reaction to a coaching move so major is curiosity - why would the Blackhawks decide to split up one of the game's best pairs?

Depth

The most obvious explanation is that the move is Joel Quenneville's way of mitigating the loss of Brian Campbell. On a simple level, separating Keith and Seabrook ensures the Blackhawks will play the vast majority of their even strength minutes with at least one of their superstars on the ice, especially given Nick Leddy's relative inexperience in playing top-4 minutes.

Development

It's pretty obvious that the organization is high on Leddy (Scotty Bowman compared Leddy to Phil Housley), and I can't help but think that their confidence in his ability to eventually play top-4 minutes helped to ease the blow of trading Brian Campbell, as evidenced by the team choosing not to sign or trade for any top-4 defensemen (I believe Montador was primarily signed to solidify the bottom pair, though he obviously has shown the ability to do well in a heavier role).

I think the surprise comes not from Leddy's presence in the top-4, but mostly from who is primary defense partner has been.

Strategy/Usage

I'll note from the outset that using QualComp or any variant thereof is useless at this point in the season. There is just too much variance in strength of schedule to draw inferences from those numbers. What I will use instead is PBP data (h/t Jared).

The first section of data only focuses on Zone Starts and their Corsi numbers based off of where they started a shift.

Keith-Leddy	% of TOI	Corsi Rate
Ozone Faceoff	13.6%	33.277
All neutral	79%	3.127
Dzone Faceoff	7.4%	-38.889

Seabs-Hjalm	% of TOI	Corsi Rate
Ozone Faceoff	13.3%	47.872
All neutral	74.6%	12.54
Dzone Faceoff	12.1%	-28.18

From here we can see that the Seabrook/Hjalmarsson line is much more likely to take a defensive zone draw. We can also see that the Seabrook/Hjalmarsson pairing has performed much better territorially, no matter the situation.

As I said above, I am not using QualComp or any variant of QualComp to adjust for the toughness of the minutes. Instead, I'll use forward pairing as a proxy, as the roles in which Chicago forwards are used are pretty rigid. As we can see below, the Keith/Leddy pairing is most often used alongside Jonathan Toews and Patrick Sharp in any situation. As for Seabrook/Hjalmarsson, the forward they play with most often is David Bolland.

Ozone	Keith-Leddy	Seabs-Hjalm
Toews	41.8%	30.6%
Kane	37.9%	21.9%
Sharp	44.8%	22.5%
Hossa	31.8%	12.8%
Bolland	12.6%	39.4%
None of above	5.5%	14.1%

Neutral	Keith-Leddy	Seabs-Hjalm
Toews	32.7%	19.6%
Kane	38.2%	26%
Sharp	33%	15.3%
Hossa	33.6%	23.1%
Bolland	14.1%	44.6%
None of above	16.4%	8.8%

Dzone	Keith-Leddy	Seabs-Hjalm
Toews	33.3%	10.3%
Kane	32.3%	21.2%
Sharp	47.1%	4.6%
Hossa	23.6%	21.1%
Bolland	21.9%	62.7%
None of above	9.1%	6.8%

As I briefly mentioned above, I believe we can validly infer that the Seabrook/Hjalmarsson pairing has played tougher minutes, mainly because of how much more likely they were to play with David Bolland, whose role for the Blackhawks is well-defined as a shutdown Center. If you guys feel this is an unreasonable assumption, let me know.

Results

Here are the results of the three centers, along with the rest of the ice time, with the Keith/Leddy and Seabrook/Hjalmarsson pairings. As you can see, the Seabrook/Hjalmarsson pairing has gotten better Corsi results with each of the top three lines in the small sample we have.

Forward	Pairing	Corsi/60	Time
Toews	KL	6.063	49.5
Toews	SH	21.352	28.1
Kane	KL	7.643	55
Kane	SH	22.222	35.1
Bolland	KL	2.841	21.1
Bolland	SH	10.154	65
None	KL	-2.857	21
None	SH	-4.604	13

Conclusions/Recommendations

To be honest there are numerous explanations for why the Keith/Leddy pairing hasn't performed as well as the Seabrook/Hjalmarsson pairing. The first is that Seabrook/Hjalmarsson have played together more (in previous seasons) than Keith/Leddy have and the disparity is largely driven by a lack of familiarity. The second is that Nick Leddy isn't as good (yet) as Keith, Seabrook, or Hjalmarsson - it is possible that Leddy is dragging Keith down a bit. Finally, this could merely be variance.

As for my recommendation, I honestly see no issue with keeping these pairings together. As I noted above, all 4 players are off to solid starts, and while there is no doubting the chemistry and effectiveness in a pairing of Duncan Keith and Brent Seabrook, the fact that the Keith/Leddy pairing has done as well as it has speaks volumes to both of those players. The eye test leads me to believe reason #1 above is the best explanation for why there has been a disparity in their possession totals. I believe that as the Keith/Leddy pair grows and each player becomes more comfortable with each other, the net result for the Hawks will be positive, couple that with the long-term developmental benefit of pairing Keith and Leddy, and I see no issue with continuing this pair.

Part III: The Aftermath of the Mike Richards and Jeff Carter Deals

Earlier this summer, I wrote extensively on the deals that sent Mike Richards and Jeff Carter from dry island Philadelphia to L. A. and Columbus respectively, promising a trilogy of sorts. After looking at what the Flyers gained in both the trades and free agency, the final step is to evaluate what the Flyers lost in those deals. While this post is certainly long overdue, the aftermath of last night’s 3-2 Kings victory over the Flyers in their only meeting this season seems like the perfect remaining opportunity to bring closure to this saga.

Beginning with my familiar approach, let’s take a look at both Richards and Carter’s average ice time from last season per nhl.com:

Player	Games Played	ES TOI/Game	Team Rank	PP TOI/Game	Team Rank	SH TOI/Game	Team Rank	Total TOI/G	Team Rank
Richards	81	13:47	4	2:56	3	2:08	3	18:52	2
Carter	80	14:39	2	2:56	4	0:39	6	18:14	4

Unsurprisingly, we see that both guys gave the Flyers a good chunk of minutes in all situations. With the exception of Carter’s reduced role on the PK thanks to the emergence of Darroll Powe, Flyers head coach Peter Laviolette was not afraid to send out either player when he felt he needed a boost in any particular area of the ice. In order to give these minutes their proper context, we will begin by looking into where both players stacked up amongst Flyer forwards in point production, once again thanks to nhl.com:

Player	ES G (Team Rank)	ES A (Team Rank)	ES Pts (Team Rank)	PP G (Team Rank)	PP A (Team Rank)	PP Pts (Team Rank)
Richards	15 (T-5)	24 (4)	39 (6)	5 (T-4)	16 (1)	21 (1)
Carter	28 (T-1)	21 (5)	49 (3)	8 (1)	9 (T-3)	17 (3)

As we can see, both players seemed to match their top-6 ice time with top-6 scoring numbers both at even strength and on the power play. If we take a look at a few more key statistics according to Behind the Net and Time on Ice, it will become quite apparent why Richards and Carter are so good at what they do:

Player	Corsi ON	CorsiRel	Score-Tied Fenwick %	CorsiRelQoC	SF/60	Zone Start %	Zone Finish %
Richards	-1.23	1.1	53.6	0.752	30.6	46.8	50.1
Carter	3.34	7.8	50.5	0.896	29.2	43.8	51.9

Breaking these numbers down, beginning with Richards, his negative Corsi score is perhaps the first thing that stands about his totals. However, if we judge his performance according to Eric T.’s Balanced Corsi, we see that according to his zone start he is actually around 3 shots better per 60 minutes than we might expect. His balanced zone shift is also a little higher than we might expect, and if we couple this data with his extremely impressive 53.6% Fenwick with the score tied, there is a lot here to suggest that Richards is carrying the water at even strength.

Moving to Carter, his totals are just as impressive. Carter actually was put in tougher defensive spots than Richards, and his Corsi ON score is a little more than 4 shots higher per 60 minutes. His Balanced Corsi is around 7 shots higher than what we might expect from a player put in similar situations, and his BZS is around 3 percent to the good. His Fenwick score, though lower than Richards still suggests that he was also doing a major part driving the play forward for the Flyers considering his zone starts.

What is even more impressive is that the above analysis doesn’t even take into account the elephant in the room: quality of competition. Below is a chart of the toughest CorsiRelQoC scores of every player listed as a Center on Behind the Net last season, minimum 20 games played:

Rank	Player	Team	CorsiRelQoC
1	BRANDONDUBINSKY	NYR	1.436
2	ARTEMANISIMOV	NYR	1.412
3	HENRIKZETTERBERG	DET	1.383
4	DAVEBOLLAND	CHI	1.353
5	PAVELDATSYUK	DET	1.175
6	BRIANROLSTON	N.J	1.084
7	JORDANSTAAL	PIT	1.037
8	PATRICEBERGERON	BOS	1.026
9	OLLIJOKINEN	CGY	1.006
10	STEPHENWEISS	FLA	1.004
11	PATRICKMARLEAU	S.J	0.998
12	NATETHOMPSON	T.B	0.973
13	MARCUSJOHANSSON	WSH	0.953
14	BROOKSLAICH	WSH	0.95
15	BRADMARCHAND	BOS	0.921
16	DAVIDBACKES	STL	0.907
17	JEFFCARTER	PHI	0.896
18	TOMASPLEKANEC	MTL	0.895
19	SAKUKOIVU	ANA	0.879
20	DARRYLBOYCE	TOR	0.857
21	MARTINHANZAL	PHX	0.837
22	JERREDSMITHSON	NSH	0.83
23	STEVEOTT	DAL	0.809
24	DAVIDLEGWAND	NSH	0.805
25	PAULSTASTNY	COL	0.802
26	MIKERIBEIRO	DAL	0.8
27	MARTYREASONER	FLA	0.796
28	BRENDANMORRISON	CGY	0.771
29	MIKERICHARDS	PHI	0.752
30	JORDANCARON	BOS	0.745

Both Richards and Carter show up in the conversation with guys who are playing against some of the toughest players in the league. Though they may not score upwards of 80 points per season, both players are certainly producing at elite levels considering the players that they are expected to face night-in and night-out.

What is more, thanks to JaredL we are able to take a look at how the Flyers performed during the past two seasons with and without either Richards or Carter on the ice:

Player On-Ice	Corsi/60	Time (mins)	Corsi QoC
Both	3.398	211.85	0.646
Richards	1.286	2053.55	0.51
Carter	4.953	1950.467	0.386
Neither	-2.322	3514.417	-0.214

Unsurprisingly, these numbers fall in line with everything else we’ve seen – they were able to send the play in the right direction while eating the majority of the team’s tough-minute assignments. Jared was also kind enough to provide data that looks into how some of the Flyers’ other key players performed in situations both with and excluding one of Richards or Carter on the ice during the same time-frame:

Player On-Ice	With	Corsi/60	Time (mins)	Corsi QoC
Giroux	Either	4.698	1379.317	0.839
Giroux	Neither	4.204	784.9	-0.456
Briere	Either	8.912	895.383	0.069
Briere	Neither	-0.775	1238.717	0.224
Hartnell	Either	2.674	987.267	-0.576
Hartnell	Neither	-1.230	1121.883	0.329
van Riemsdyk	Either	2.194	1148.467	0.528
van Riemsdyk	Neither	4.426	704.967	-0.169

Once again, we see that no matter the situation, each player was better with one of either Richards or Carter on the ice except for James van Reimsdyk whose data has a noticeable discrepancy in quality of competition. In order for the Flyers to remain one of the premier Stanley Cup contenders in the Eastern Conference, it is looking more and more like the big line of JVR, Claude Giroux and Jaromir Jagr is going to be asked to carry the mail against top-tier competition in the absence of Richards and Carter. These numbers seem to suggest that it is certainly possible, but we will have to wait until each plays an adequate number of contests before we can finally say whether Paul Holmgren’s plan will pay off in the long run. So far, the Flyers are off to an excellent start, but Giroux & Co. will have to keep up their play in the absence of what was one of the league's most formidable one-two punches up front.

Driving Play Season Preview: Teams 3-1, The Stanley Cup Favorites

3. Washington


Key Statistics:


Fenwick- 50.4%
Even Strength Shooting%- 7%
Even Strength Save%- .928

2010-2011 Review:


Washington's year last year was filled with up and downs.  Most notable was their extended losing streak in December that provided some sweet Bruce Boudreau rants on '24/7'.  After this lull however, the team played extremely well, finishing first in the Eastern Conference and second overall in total points.  Unfortunately for Caps fans, the playoffs brought another early exit, as the Caps were swept in the Eastern Conference Semis, a series which was much closer than a sweep would indicate.

Offseason Changes:


Where do we start?  George McPhee was a busy man this offseason, with resigning key players (Brooks Laich, Karl Alzner), fleecing teams in trades (Semyon Varlamov for a 1st round pick), signing elite goalies for a back-up's cap hit (Tomas Vokoun), and filling out the rest of his team with veteran players capable of playing tough minutes.  The team added precious forward depth with the additions of Joel Ward, Troy Brouwer, and Jeff Halpern.  They also bolstered their blueline with the addition of Roman Hamrlik.  George McPhee took a team that was already very good and turned them into Stanley Cup favorites.  The Capitals now have it all.

Key Questions for 2011-2012:


Will the Capitals be better territorially this year?

• Last year the Capitals were a middle of the pack team territorially, though some of their signings are players capable of driving the play forward (Joel Ward, Troy Brouwer).  It'll be interesting to see if this has any impact, as Ovechkin, Backstrom, and Semin are the only remaining forwards who can be counted on to control play.  

Was last year's mediocre Power Play just variance or should it be a cause for concern?

• After spending the last handful of years with one of the league's best power plays, last year's Capitals saw their success with the man advantage dwindle, posting the NHL's 16th best Power Play.  Was this bad coaching or bad luck?  Either way, if these problems creep back up it could be a problem, as Washington probably has less margin for error here given their relative weakness at even strength.

2. Vancouver

Key Statistics:


Fenwick- 53.9%
Even Strength Shooting%- 8.2%
Even Strength Save%- .939

2010-2011 Review:


Vancouver was the class of the NHL last year, earning 117 points on their way to winning the President's Trophy.  Their postseason nearly ended in disaster before Alex Burrows scored an OT winner in Game 7 of the first round, and from there they handled Nashville and San Jose en route to their first Stanley Cup Finals appearance since 1994.  The rest, as they say, is history, as Tim Thomas and the Bruins won the final two games of the series as Vancouver began to burn.

Offseason Changes:


Mike Gillis (correctly) resisted the temptation to overreact, as nearly all of their regulars return, with Christian Ehrhoff as the only key piece to leave.  Marco Sturm was their most notable endeavor in UFA.  Most of the offseason work came with re-signing their own players, as Kevin Bieksa, Max Lapierre, Jannik Hansen, Sami Salo, and Andrew Alberts all re-upped this summer.

Key Questions for 2011-2012:


Is Vancouver deep enough along the blueline?

• This is slightly nitty, as Vancouver is clearly an elite team, but one chink in the armor is their depth along the blueline, especially after nothing was done to replace the departure of Christian Ehrhoff. If Vancouver runs into injuries which is a possibility given the history of Sami Salo and (to a lesser extent) Kevin Bieksa, there could be issues, as giving big minutes to players like Andrew Alberts and Aaron Rome is a recipe for disaster.  Keith Ballard returning to form is essential.

1. Chicago

Key Statistics:

Fenwick- 54%

Even Strength Shooting%- 6.5%

Even Strength Save%- .919

2010-2011 Review:

Last season was a disappointment for the Blackhawks.  Coming off a Stanley Cup and the ensuing cap hell, Chicago was really hamstrung with last year's lineup, and it showed, as players such as Fernando Pisani, Jack Skille, Jake Dowell, Nick Boynton, and Jassen Cullimore all played substantial minutes at various points throughout the season.  The team got better later on after adding Chris Campoli and Michael Frolik, but still needed a lot of luck to even make the playoffs.  Chicago ended up losing in 7 games to the eventual Western Conference champions.

Offseason Changes:

The Hawks FO was not shy this summer, as they moved two key cogs from the 09-10 cup run on draft night, sending Troy Brouwer to the Washington Capitals for a 1st round pick.  Later that night they moved Brian Campbell to the Florida Panthers for Rostislav Olesz.  The money freed from the Campbell deal was quickly put into use, as the Blackhawks then acquired and signed Steve Montador, and on July 1st, signed Andrew Brunette, Jamal Mayers, Daniel Carcillo, and Sean O'Donnell.  Sami Lepisto was also signed later in the Summer.

Key Questions for 2011-2012:

Did the Blackhawks do enough to replace Brian Campbell?

• While the Campbell move was a huge win from a cap management perspective, it left the Blackhawks with a huge hole on defense.  The Hawks brass continues to insist that Nick Leddy is indeed ready to fill the void, but that obviously remains to be seen.  Campbell played a huge role for the Blackhawks, one that was often under appreciated by certain types of Hawks fans.  Chicago's possession game is predicated on quick transitions from the defensive zone to the offensive zone.  Losing his skating and his offensive skills will be hard to replace.  The depth should be better than last year, but the Blackhawks could find themselves in trouble if Leddy doesn't take a step forward.

Driving Play Power Rankings from 30 to 1:

30. Edmonton

29. Colorado

28. Dallas

27. New York Islanders

26. Minnesota

25. Ottawa

24. Toronto

23. Florida

22. Phoenix

21. Winnipeg

20. Anaheim

19. Carolina

18. Calgary

17. St. Louis

16. Nashville

15. New York Rangers

14. Columbus

13. Buffalo

12. Philadelphia

11. Boston

10. Montreal

9. Tampa Bay

8. New Jersey

7. Los Angeles

6. Detroit

5. Pittsburgh

4. San Jose

3. Washington

2. Vancouver

1. Chicago

Driving Play Season Preview: Teams 6-4, The Second Tier Elites

6. Detroit Red Wings

Key Statistics:

Fenwick- 53.6%

Even Strength Shooting%-8.5%

Even Strength Save%-.922

2010-2011 Summary

Once again, Detroit was near the top of the league in both territorial play and in points, all this despite losing 26 games from Pavel Datsyuk, 13 games from Dan Cleary, 19 games from Brian Rafalski, and 15 games from Brad Stuart.  Detroit got decent enough goaltending, as well as good years from all of their supplemental pieces.  They simply ran into a slightly better team in the playoffs.

Offseason Changes

The only major move made this summer was the retirement of Brian Rafalski and his subsequent replacement with Ian White.  As Triumph and I chronicled, this was a definite upgrade for Detroit.  White is a superior player who comes at less than half the price.  The saved cap space didn’t really come into play in further offseason moves, though it also gives Detroit a cushion if they needed to make an in-season move. 

Key Questions for 2011-2012

Is Detroit deep enough along the blueline?    

• While Detroit features a formidable top 4, I believe there are legitimate concerns past that point, especially in the event of injury.  Jonathan Ericsson took a big step backward last year, and Jakub Kindl has shown little to give the impression that he wouldn’t be overmatched playing heavy minutes.  Other than that, I think forecasting Detroit’s success is pretty straightforward.  This is largely the same team as years past, and every NHL fan can understand what that means.

5. Pittsburgh Penguins

Key Statistics

Fenwick- 54.3%

Even Strength Shooting%-6.8%

Even Strength Save%-.929

2010-2011 Summary

In a word: injuries.  Pittsburgh’s two best players spent significant time on Injured Reserve, with Evgeni Malkin missing nearly 40 games with various knee injuries and Sidney Crosby missing 41 games after noted headhunter David Steckel viciously ran Crosby in the Winter Classic.*  The Penguins still managed to put together a good season, even finishing first in the league in Fenwick, but the ability to consistently put pucks in the net was glaringly obvious. Thanks to a great season from Marc-Andre Fleury, Pittsburgh was able to remain relevant, finishing with 106 points. 

Offseason Changes

Pittsburgh lost two bottom-6 forwards to division rivals with Mike Rupp’s departure to the Rangers and Max Talbot’s move to Philadelphia. Outside of that, their roster will generally look the same as last year, with the most major addition coming with the signing of veteran winger Steve Sullivan. 

Key Questions for 2011-2012

At what point can we expect Sidney Crosby to return?

• Crosby has already been ruled out of the season opener, which while not a good sign is still not the end of the world assuming Malkin and Staal remain healthy.  But still, the team needs him in the line-up.  A Crosby-less Penguins team still makes the playoff, but #87 is the difference between an elite team and a team that makes it as a bottom seed before losing in the first round.

Should Evgeni Malkin move to wing?

• This only happens if Crosby is healthy, but is a move I think should be made (and is a move a few of us on this blog have talked about for a while).  Malkin’s contributions at Even Strength have fallen each of the last few seasons.  He’s never been great at faceoffs, and center depth (again, assuming Crosby’s health) isn’t much of an issue for Pittsburgh, and I believe the lightened responsibility could help bring his game back to where it was in 2008.   

* - Don’t worry, I’m only joking.

4. San Jose Sharks

Key Statistics from 2010-2011

Fenwick- 53.7%

Even Strength Shooting%-7.2%

Even Strength Save%-.942

2010-2011 Summary

The Sharks had a pretty boring year last year (I mean this in a good way), as they won another Pacific Division title and again came within one postseason round of the Stanley Cup Finals.  San Jose’s biggest story last year was the emergence of Logan Couture, who centered what was San Jose’s best line for most of the year, and whose presence ultimately made Devin Setoguchi expendable (more on this later). 

Offseason Changes

Outside of Washington, San Jose had the busiest summer of any of the NHL’s elites.  The offseason bonanza began on Draft Day, with Doug Wilson sending Devin Setoguchi, top prospect Charlie Coyle, and a 2011 1^st round pick to the Minnesota Wild for Brent Burns.  This was the first of two blockbusters between the Sharks and Wild, as the two teams swapped All-Star wingers, with the Sharks sending Dany Heatley and receiving Martin Havlat.  The Sharks also signed Michal Handzus, ostensibly to play the role of 3^rd line center.

Key Questions for 2011-2012

How will Joe Pavelski do on the wing and whom will he play with?

• Logan Couture’s rise gave Doug Wilson the flexibility to move a top 6 winger in Devin Setoguchi, primarily because he had another top 6 forward who was then being used on the 3^rd line.  I think it’ll be interesting to see what (if any) impact this has on Pavelski’s game.  I also think it’ll be interesting to see what line he plays with, though this will obviously change throughout the year.

Were last year’s troubles on the PK just an aberration or a legitimate cause for concern?

• Known in previous years for having one of the league’s best kills, San Jose had an uncharacteristically bad year on the PK.  Michal Handzus should help up front, and Colin White and Brent Burns should help on the back end, but it still remains to be seen if that is enough, especially with the departure of Jamal Mayers and Scott Nichol.

The final 3 will be posted tomorrow morning.  

Here is a recap of our rankings to date:

30. Edmonton

29. Colorado

28. Dallas

27. New York Islanders

26. Minnesota

25. Ottawa

24. Toronto

23. Florida

22. Phoenix

21. Winnipeg

20. Anaheim

19. Carolina

18. Calgary

17. St. Louis

16. Nashville

15. New York Rangers

14. Columbus

13. Buffalo

12. Philadelphia

11. Boston

10. Montreal

9. Tampa Bay

8. New Jersey

7. Los Angeles

6. Detroit

5. Pittsburgh*

4. San Jose

* - With Sidney Crosby

A Thought Experiment about Goaltending, Fenwick, and Lineup Construction

Before I go any further, I must note that this piece is an introduction, and to be honest, I don't quite know exactly where it will go.  I do know that I'd like you, the readers, to give any input in the comments, as this topic will certainly be revisited in the future.

One of my favorite elements of NHL analysis is looking at line-up construction in the context of the salary cap.  My favorite team, the Blackhawks, are like a number of other teams in that they will almost always spend to the externally imposed cap, but frankly, this analysis can extend to every team in the league, as they will almost always be working with internally imposed constraints.  

The question is simple: What is the best way to put together a line-up that can consistently compete to win a championship?

Here is where Fenwick and Goaltending come into play, to illustrate my point, I ask these questions below:

What is the lower bound of goalie performance for a team with legitimate Stanley Cup aspirations?  Is it saving 87% of shots? 88%? 89%?

What about Fenwick (puck possession)? Is it 44%? 46%? 48%?

Spending big money on a goaltender likely comes at the expense of signing better skaters.  What is the optimal solution? Is it the team that has a goalie saving 90.5% of Even Strength shots but has a Fenwick of 55% more likely to win a Cup than the team that has a goalie saving 93% of Even Strength shots but gets crushed territorially, only managing to Fenwick 46%?

While we can safely assume that there is a correlation between salary and ability in goaltenders, we cannot escape the reality that dollars are fixed, and money spent on goaltenders cannot be spent on skaters.  This makes it difficult for teams that spend large chunks of salary on goalies to build teams that dominate at even strength. There are exceptions to this to the first rule, both in terms of mediocre goalies making big money (Cam Ward), elite goalies making back-up money (Tomas Vokoun, though this is only one year), and in terms of teams who have managed to build a team with excellent goaltending and excellent puck possession (Montreal and Vancouver come to mind), but by and large, teams that spend big money on their goaltenders put themselves at a competitive disadvantage when it comes to competing for a Stanley Cup.

My position is that goaltending, like rebounding in basketball, doesn't matter until it matters.  That is to say it is not as important as say, winning at even strength.  I recognize that this is a controversial position, and I hope that this opens up some discussion.  I will come back to this with more data throughout the season, but right now I want to limit this to a philosophical discussion.

Boston showed us last year that a team can be mediocre 5v5 and still win a cup, so long as the goaltending is on point, but there are few who peg them as favorites to repeat, which is pretty telling when we consider that most of their team will return.  People generally recognize, whether it is conscious or not, that relying so heavily on your netminder is not a recipe for success over multi-year timeframes.

Winning at even strength is important, but are we in the statistics world overrating its importance?  Is it as important as having a world-beater between the pipes?  How does a rising cap change this picture?

Let us know your thoughts, we believe this is a pretty interesting topic.

On Zone Starts

How valuable are offensive-zone faceoffs? How much should we adjust the Sedins' stats to take into account that they take three faceoffs in the offensive zone for every one at the other end? Are coaches using their guys effectively, or should they almost turn them into specialists like Vigneault does in Vancouver? Is it better for a coach to focus on zone starts, matchups or just roll lines to keep his guys fresh and the best playing the most?

These are just a few of the many, many questions that relate to zone starts that come up in hockey analysis. We'll put off dealing with most of those until later, this article will be more of a broad discussion and introduction to what I feel is a novel approach that we'll be using a lot.

The Data

I'm going to start with team stats. This is pretty strange because zone starts aren't a team issue. A team that has more offensive-zone starts than defensive has earned them; good zone starts aren't just handed down to the team by some suit. In contrast, a player only reaps what he sows, as it were, if he or a teammate ices the puck or possibly after a very short shift. Most faceoffs are taken with fresh players that were on the bench when the stoppage occurred. Despite that, using team stats is a good place to start because we can get a pretty good idea how the location of the most recent faceoff affects results.

The data come from a common source: NHL play-by-play and roster reports. In this case, I am using every game available for the 2010-2011 regular season. As usual, it's even strength with both goalies on the ice. Using the roster reports, which say when each player was on the ice during the game, I isolated these 5 situations:

Ozone, first shift - the most recent faceoff was in the team's offensive zone. All players that were on the ice for the faceoff remain on the ice.

Ozone, on-the-fly - the most recent faceoff was in the team's offensive zone. At least one player who was on the ice for that faceoff has left.

Neutral Zone - the most recent faceoff took place in the neutral zone.

Dzone, on-the-fly - the most recent faceoff was in the team's defensive zone. At least one player who was on the ice for that faceoff has left.

Dzone, first shift - the most recent faceoff was in the team's defensive zone. All players that were on the ice for the faceoff remain there.

To clarify, once any of the original faceoff guys have left the ice the rest of the time before the next stoppage is in the on-the-fly category. So the faceoff shift is only that first shift, even if later it so happens that the 10 skaters that were on the ice are out there together.

Note: I have separated out the team results to keep this post about the general concepts. If you want to see how good your team is in each situation, you can find that here.

Ice Time and Goals

Let's take a look at how much time was spent and how many goals were scored on average in each situation. This will give us a very rough idea how important faceoffs are in the offensive or defensive zone.

Situation	Ice Time	%	Goals	%
Ozone, first shift	452.5	11.4%	21.2	13.8%
Ozone, on-the-fly	765.1	19.3%	32.3	21.0%
Neutral	1538.9	38.7%	54	35.1%
Dzone, on-the-fly	765.1	19.3%	34.8	22.7%
Dzone, first shift	452.5	11.4%	11.4	7.4%
Total	3974.1	100%	153.6	100%

The first thing I noticed is that the first shift only accounts for about 37% of the ice time following a faceoff at either end. Part of that is that I'm being very strict defining the first shift; it would increase if I allowed for one guy to leave the ice, for example. In any case, you might wonder why we focus so much on who is on the ice for a faceoff when so much of a player's ice time after an ozone/dzone faceoff started with him jumping onto the ice.

The goals columns give you a pretty strong hint. Look at the second and fourth rows. Following a faceoff outside the neutral zone, once a change was made more goals were scored by the team that took the faceoff in their defensive zone! We'll later see that this is likely just due to random chance, but it seems clear that if you come on in an on-the-fly change it's more like a neutral-zone start than being on for a faceoff at either end.

Corsi

Let's look at the average team Corsi rate for each situation. I use the average team rate for each situation so we don't have the endogeneity effect I wrote poorly about a couple months ago. In other words, if we simply averaged out all the ice time we'd overestimate how important it is to be in the offensive zone because good teams tend to get more faceoffs in the offensive zone than bad teams so we'd be lumping in team quality with ozone-faceoff value.

Situation	Corsi/60
Ozone, first shift	39.957
Ozone, on-the-fly	2.603
Neutral	0.019
Dzone, on-the-fly	-2.784
Dzone, first shift	-40.103

Here you can see how much having a faceoff in the good zone helps your team out territorially. I'm sure that there is an effect didn't surprise you, but suspect how large it is might have. It's also interesting to note that this almost completely goes away once the first change happens. This shouldn't be a surprise either, teams don't change without the puck leaving the zone, but one might have expected more of a ripple effect. The most common way to change lines is to dump the puck and give the other team possession, albeit starting behind their own net. It does not appear that being able to breakout the Flying V gives you much of an edge.

This is a nice segue back to why we should care so much more about who is actually on for the faceoff and not just ice time afterward. Let's exaggerate and suppose that Henrik Sedin and Manny Malhotra spend the same amount of post-offensive-zone-faceoff time on the ice but Hank's is all first-shift time while Manny doesn't take a single offensive-zone faceoff. Sedin's ozone time will be extremely favorable, and Malhotra's only slightly so. In this extreme scenario we would need to adjust Sedin's stats a lot to take his type of ice time accurately into account. Being out there on the faceoff in front of their goalie is over 15 times as favorable as jumping on the ice after.

Conclusion: More To Come

When I thought of this method of separating out the ice time, I did a little fist pump. While I don't think this, or really any metric, will blow everything else away it seems like a good way to analyze zone starts and give us better insight into player value and coaching decisions. We will be using this and related methods a lot in the future, especially the coming weeks leading up to the season. Coming down the pipe is a new player metric to adjust for zone starts. We'll also do in-depth analysis on zone starts for the two teams that focus the most on them: the recently rivalrous Vancouver Canucks and Chicago Blackhawks. Are Vigneault and Quenneville outsmarting the rest of the league or is it a case of fancy coaching syndrome? If you ask nicely, we could probably do something similar for your favorite team, or even your favourite team.

Here is a link to the team data.

On Luck, Skill and Sample Size in Shooting Percentage

The roles of skill and luck in shooting are an important and often misunderstood part of hockey analysis. This is particularly true when analytical and traditional fans get together. A typical discussion might go something like:

A: Steven Stamkos got 91 points with 45 goals at the age of 21. He's definitely getting 100 points next year, and could easily score 50 goals a season as he improves.
B: Yeah, but he was lucky to make 16.5% of his shots. That's not sustainable and his numbers will probably go down next year, even if he does actually improve.
A: So shooting is all luck? You clearly know nothing about hockey and should actually watch some games instead of just sitting at your computer all day coming up with fancy stats that don't mean anything.

Turns out both guys have a point. Stamkos should probably expect his stats to drop next season because, in addition to goal numbers trending downward for the league as a whole, he's probably not burying 16.5% of his shots. On the other hand, I person B probably should watch more hockey, it is a great game.

A lot of the confusion comes from incorrect either/or thinking. Scoring on a high percentage of your shots is a result of both luck and skill. I'm not just putting down the traditional fans here. Those of us in the analytical community, myself included, are prone to bad thinking as well. While most people ignore or underrate the importance of luck in hockey in general and shooting in particular, we tend to go too far the other way, chalking everything up to luck and ignoring the skill aspect.

Shooting for a high percentage is skill based. Two of our favorite writers, JLikens of objectivenhl fame and Gabe Desjardins from BTN and arcticicehockey have written several articles on the subject.

In case their articles are not convincing enough, let's consider two of the best players in the game: Henrik Sedin and Sidney Crosby. While not necessarily known as snipers, these players have all the skills that one might think lead to their team putting a high percentage of shots in the net. Both have elite vision, passing ability, hands, positioning and, in one case, telepathy. We would all expect their teams to have better shooting percentages when they are on the ice than when they are sitting on the bench or worse. The numbers bear this out. Here is a chart with their teams' performances at even strength with both goalies in net from the last four seasons combined. The stats are courtesy of noted Driving Play reader Vic Ferrari's timeonice scripts, which you can find information on how to use here.

Team	Goals	Shots On Goal	Shooting %
Penguins, Crosby on Ice	236	2160	10.9%
Penguins, Crosby off Ice	414	5347	7.7%
Canucks, Henrik on Ice	273	2624	10.4%
Canucks, Henrik off Ice	359	4709	7.6%

As you can see, the Pens with Crosby shot 3.2 percentage points higher than they did without him. While some of it may be variance, with the number of shots they took with him on, that's a difference of 69 goals or more than 17 goals per season due to better shooting. The Canucks shot 2.8 points higher with Henrik on the ice, a difference of over 73 goals, more than 18 per season, when you consider how many shots they took with him on. For the statistically minded, these shooting-percentage differences are very very very significant. To give you an idea, it varies field to field but the most common benchmark is for there to be less than a 5% chance of results this extreme, or more so, due to variance alone. That's a 1-in-20 chance. For Crosby, there is a 0.00045% chance, or less than 1 in 222,000. For Hank there is a 0.00235% chance of results that extreme due to randomness alone - less likely than 1 in 42,000. Again, 1 in 20 is the usual mark. The data confirm what anyone would guess from watching a few games - Henrik Sedin and Sidney Crosby help their teams shoot better. (Note: if you are a hater and/or think that it's the likes of Alex Burrows and Pascal Dupuis who are driving these results, feel free to be wrong. The point of this is to provide evidence of shooting skill and clearly someone has it when these two are on the ice.)

Let's now look at the role of luck on shooting percentage. To do this, I will run simulations comparing the results of a typical team that shoots well and one that does poorly. In this article on objectivenhl, which is worthy of being linked again, JLikens finds that the average team shoots at an 8.1% clip 5-on-5, with a standard deviation of 0.48%. Going by this, a team that is good at shooting, let's say 7th or 8th best in the league, would have a true 5-on-5 shooting percentage of something like 8.42%. On the other hand, a team that is bad at shooting, say 7th or 8th worst in the league, would be expected to score on about 7.78% of their shots.

Let's see how things shake out. Below is a chart giving the results of 10,000 simulations for various numbers of shots where team A has a true shooting percentage of 8.42% and team B shoots at 7.78%. The first two columns tell you the given time period and number of shots for each team. The next three columns tell you how often the team good at shooting outshot the bad (column 3), the bad team outshot the good (4) and how often they had an equal shooting percentage (5). The last two columns give what percent of the time someone looking at the data, and not knowing the underlying percentages, would get statistical signficance at the 5% level. Notice that in the last column, the statistical test would reveal that B is significantly better at shooting than A despite their shooting skill actually being over half a percentage point worse.

Time period	Number of Shots	A scores more	B scores more	Goals scored equal	A > B Significant	B > A significant
One Period	8	31.9%	28.7%	39.4%	1.3%	1.1%
One Game	24	42.6%	36%	21.4%	6%	4.5%
1/4 Season	500	62.3%	33.2%	4.5%	10.5%	2.2%
1/2 Season	1,000	68.6%	28.5%	2.8%	13.4%	1.4%
1 Season	2,000	76.4%	21.7%	1.9%	17.9%	0.8%
2 Seasons	4,000	85%	14%	1%	27.8%	0.2%
3 Seasons	6,000	90.1%	9.3%	0.6%	36.1%	0.1%
4 Seasons	8,000	93.6%	6%	0.4%	43.7%	0.1%
5 Seasons	10,000	95.6%	4.1%	0.3%	50.3%	0%

You probably didn't find the results surprising for that first row, representing a period of play. The most common outcome, happening about 40% of the time, is that the two teams remain tied, most often at 0. The team that shoots better due to getting higher-quality shots, hitting the corners better and so on is only slightly more likely to be the one that is ahead if you know that one of them is. Less than 32% of the time will the better team find themselves ahead after a period in which both get the league average 8 shots, whereas they'll be behind almost 29% of the time.

Lower on the chart it gets more troubling, especially for us bloggers. The most common sample point for analysis is half a season. Generally the best way to study the persistence of something is to split the season in half, typically first half vs second half or even-and-odd numbered games, and compare the two samples. This works well because teams should be the same or very similar. If you study something over multiple seasons you aren't getting the same teams every year due to player and coaching changes. In half a season, the team near the top in shooting skill has only about a 2 in 3 chance of outscoring the team near the bottom with the same number of shots. There is also little chance, roughly 13%, of finding that the better team is significantly better at shooting if you were looking at the data. Even over a whole season of shooting data, there is a 1 in 4 chance that the worse team will get better results. It isn't until we get several years worth of shooting results that it tilts heavily in favor of the better shooting team and that's not realistic because teams change so much each offseason and the simulations assumed the same percentage each season.

As you can see, luck plays a huge role for all reasonable sample sizes. This is the fundamental reason why shooting stats are better than goals. Luck is less of a factor for number of shots taken than number of shots made, so they are more reliable indicators of skill over samples of a season or less. If over a season there is a 1 in 4 chance that a good-shooting team is outshot by a bad-shooting team then it's tough to say that a team's results are due to skill and not just random luck.

In a future installment I will look at how persistence is affected by sample size.

On The Strange Results Of The Winnipeg Thrashers

Some people may have forgotten this, but in December of 2010, the Thrashers were primed for a playoff berth. Mainstream journalists sat up and took notice. After their game against the Maple Leafs on December 20th, the Thrashers were 19-11-5, with a point percentage of .614. This was finally the year for them - they'd gotten rid of Ilya Kovalchuk, acquired Dustin Byfuglien, and the team was better off. We know what happened next; they went 13-25-7 over their remaining 45 games and finished with the 6th worst overall record in hockey. Then they moved to Winnipeg.

But something strange happened along the way - by 'advanced metrics', the team got better, even as it did worse. Here's a look at Atlanta/Winnipeg's first half and second half even-strength Fenwick with the score tied by player, with a minimum of 10 total games. Fenwick % is shots on goal + missed shots on goal by Team X (here, Atlanta) divided by the total number of shots and missed shots taken. A player's Fenwick % is shots on goal + missed shots FOR while he is on the ice divided by total shots on goal + missed shots by both teams. We're only looking at the results while the score is tied because teams change their strategies when ahead or behind, which fouls up the numbers. (All numbers here courtesy of timeonice.com)

Player	GP	1st Half Fenwick	GP	2nd Half Fenwick	Difference
Andrew Ladd	39	0.513	40	0.515	0.002
Dustin Byfuglien	40	0.5	39	0.558	0.058
Johnny Oduya	37	0.425	40	0.532	0.107
Chris Thorburn	36	0.452	40	0.532	0.08
Anthony Stewart	39	0.479	36	0.456	-0.023
Ron Hainsey	35	0.461	40	0.521	0.06
Bryan Little	33	0.496	41	0.531	0.035
Tobias Enstrom	40	0.477	31	0.526	0.049
Nik Antropov	31	0.46	40	0.514	0.054
Evander Kane	34	0.467	34	0.545	0.078
Zach Bogosian	30	0.456	38	0.514	0.058
Alex Burmistrov	36	0.398	32	0.592	0.194
Eric Boulton	28	0.496	31	0.503	0.007
Rich Peverley	39	0.474	18	0.488	0.014
Brent Sopel	33	0.48	19	0.444	-0.036
Niclas Bergfors	29	0.488	22	0.513	0.025
Tim Stapleton	8	0.469	34	0.543	0.074
Fredrik Modin	23	0.379	10	0.535	0.156
Jim Slater	32	0.465
Ben Eager	31	0.375	1	0.333	-0.042
Blake Wheeler			23	0.598
Mark Stuart			22	0.561
Patrice Cormier	2	0.238	18	0.465	0.227
Rob Schremp			15	0.592
Freddy Meyer	7	0.344	7	0.5	0.156
Radek Dvorak			12	0.608
Ben Maxwell			12	0.516

We see that in the first half, Atlanta was well into the negative - only two players managed to hit 50%. Their goal differential, however, was +3 despite a 46.3% Fenwick percentage. In the second half, the story was reversed - few players were in the red. Yet their goal differential with the score tied was -2 in spite of a .529 Fenwick %. We know that Fenwick % with the score tied is a better predictor of future results than Goal %, so by these measures, Atlanta/Winnipeg could be looking at a resurgence next year.

A nice chart contributed by JaredL shows the relationship between Fenwick % and Goal % as the season progressed:

We see the Fenwick % rising as the Goal % drops. What could cause the Fenwick to jump? I can think of three things that would cause the improvement:

A: Personnel Changes - The Thrashers made a few moves towards the end of the year, they brought in Radek Dvorak, Mark Stuart, and Blake Wheeler while they shipped out Brent Sopel , Niclas Bergfors, and Rich Peverley. Wheeler and Dvorak's 2nd half Fenwick while tied definitely beats Bergfors's and Peverley's.

B: Coaching Adjustments - It was Craig Ramsay's first year coaching the Thrashers, and perhaps the players had not figured out his system until the second half.

C: Player Improvement - Dustin Byfuglien played some defense for the Blackhawks last year, but this was his first year playing defense full-time. Promising youngsters Zach Bogosian, Evander Kane, and Alex Burmistrov had not played very much in the NHL. Burmistrov's jump was especially impressive.

But what of the drop in goals? I can think of two reasons for that:

A: Blind Luck - The Thrashers simply didn't get the bounces. Over such a small sample, chance will always be a factor. No one said that hockey was fair.

B: Changing Strategy - What if the Thrashers were responding to their difficulty in scoring goals by simply firing more pucks at the net? It's possible, but I doubt very much that it would result in such a wild change in Fenwick.

Still, this change in goal differential involving score tied Fenwick is one thing, but you don't get to a 14-19-6 second half record without other things going wrong, and it seems like just about everything else did. Here's a look at their Special Teams split into first and second halves:

Special Teams	Power Play	Penalty Kill
First Half	20.9%	80.9%
Second Half	14.0%	74.3%

And here's a graph showing Fenwick shooting percentage, both for and against, for the season:

We can see, again, that the opponent's shooting percentage improves while Atlanta's gets worse.

So who are the Winnipeg Jets going to be next season? It's difficult to say. They moved to a different city and switched coaches, but the personnel are going to remain pretty much intact. The team is still in the Eastern Conference despite moving to Winnipeg, which will lead to increased travel. They've yet to sign Zach Bogosian. Frankly, I don't know. For our upcoming series on Driving Play predicting the 2011-12 season, I inexplicably ranked them as #15 in the Conference - last overall. I doubt they'll make it there, but in spite of their second half Fenwick, I still think it will be a long winter in Winterpeg.

Part I: The Aftermath of the Mike Richards and Jeff Carter Deals

On June 23rd, 2011, Flyers General Manager Paul Holmgren sent shockwaves through the hockey world when he dealt arguably the two most notable faces of the franchise – Mike Richards and Jeff Carter – to Los Angeles and Columbus respectively. Since then, much has been (and will continue to be) written about possible motives behind what he and team owner Ed Snider were pondering to make such bold moves. So far, speculation has included both off-ice issues as well as the need to create salary cap space for newly signed goaltender Ilya Bryzgalov. Starting with the former, Richards’ tumultuous relationship with members of the Philadelphia media is no secret. For the last few seasons, there have been accusations that he (and Carter) enjoyed a lifestyle where partying was the main focus, leaving hockey on the back burner. Richards’ leadership inside the locker room hasn’t been looked upon any more favorably. It has been rumored that a longstanding rift between the team’s young stars and seasoned veterans – most notably Chris Pronger – could also have played a factor in the stars’ departure from the team. Whether or not these accusations have merit, it is certain that the moves will accomplish one of the team’s likely intended goals: a culture change inside the dressing room.


In the aftershock of what happened almost four weeks ago, another highly-debated question has naturally emerged: are the Flyers still one of the premier Stanley Cup contenders in the Eastern Conference? In order to answer such a question, I am going to break my study into three parts. Part one will look into the deals for Richards and Carter themselves, evaluating what it was that the Flyers added to their lineup. Part two will evaluate Philadelphia’s signings on July 1 and speak to where Jaromir Jagr, Maxime Talbot, and Andreas Lilja fit into the equation. Finally, part three will decipher what the Flyers lost when they made the decision to deal their captain and his swift sidekick.


Of course, trying to answer our question is a bit of a double-edged sword – only time will tell if Holmgren’s return of Wayne Simmonds, Brayden Schenn, a 2012 second round pick, Jakub Voracek, the 8th overall selection in this year’s draft (Sean Couturier), and a third round selection in this year’s draft (Nick Cousins) were an adequate return for both superstars. Fortunately, we can still attempt to decipher what the numbers tell us about these players (and even draft picks). In order to do this, I like to start by looking at players’ average ice time per game. This tells us 1) what situations the players are being used in, and 2) how often they are being used. Per nhl.com, here are the numbers for Simmonds and Voracek, the two players coming to Philadelphia who saw significant ice time at the NHL level last season:

From these numbers, we can conclude that Simmonds played a bottom-six checking role in Los Angeles, the same role that he will most likely see in Philadelphia. Voracek, on the other hand, was one of the Jackets’ top forwards, ranking in the top 5 on his team at even strength and on the PP. This is good news for the Flyers – they will need him to replace any and all minutes in both situations without Richards and Carter in the fold.
With our ice-time analysis complete, we can now attempt to give this raw data its proper context.

 

What do these numbers tell us? Starting with Simmonds, he was asked to play a moderately defensive role against the toughest competition of any forward on the team (min. 20 games played). However, his zone start percentage should probably see an expected Corsi score of zero or slightly worse (see chart), and instead Simmonds sits at -4.02 . DobberHockey tells us that he most often played with Michal Handzus and Alex Ponikarovsky (21.25%), and Handzus and Kyle Clifford (15.33%). Of these forwards, Handzus and Ponikarovsky both have Corsi scores around what we would expect for someone given their roles, but no player seems to be “carrying the water” as we like to say. Unfortunately for the Flyers, Simmonds is no exception and his low scores in just about every category show that he cannot send the play in the right direction on his own against the opponent’s best players.


Voracek, on the other hand, is an interesting case in and of himself. Once again using the expected Corsi graph linked, Voracek actually slightly over-performs what we might expect from somebody given his zone start percentage. However, his impressive Corsi scores and Fenwick percentage are perhaps correlated with a few points of interest. First, his aforementioned high zone start percentage gave him an immediate advantage in generating shots towards the opponent’s net as he quite often started his shifts in prime scoring position. Second, his competition was anything but impressive, actually averaging a negative relative Corsi score. Finally, DobberHockey shows us that among his three most common line combinations, Rick Nash was on the ice a healthy 57.81% of the time. I hardly think explaining why playing with Nash would be beneficial to Voracek, but it is worth noting that Nash was among the league’s leaders in shots last season – his total of 305 ranked 6th in the entire NHL. Though Nash’s Corsi score of 4.49 may be lower than expected considering his own 57.1% zone start, taking into consideration how often he shoots it is easy to see how Voracek’s own score was undoubtedly affected for the better. It will be most interesting to see if Voracek can repeat such gaudy scores without a line-mate sporting the credentials of Mr. Nash.


We have already noted Voracek’s 2:57 of average PP time per game in ’10-11 which will be immensely valuable to Philadelphia in the absence of Richards and Carter. Though he ranked amongst the team’s leaders in said category, however, he only registered 8 total points for his efforts on the man advantage. Perhaps it is unsurprising that Columbus’ Power Play ranked 8th in the league in shots for/60 minutes with Nash in the fold (remember: shots are a better indicator than goals), but for a team that saw success in generating pressure on the opponent, Voracek’s totals still seem low. However, some of this effect can be explained when we realize that Columbus’ opponents saved 91.1% of all shots while on the PK according to Behind The Net. Thanks to mc79hockey, we know that the historic average is around 86.6%, a full 4.5% disparity. Had Columbus’ opponents not been so lucky, both the team and Voracek most likely would have sported slightly higher power play production.


Moving on to the relative unknowns of what the Flyers got back in the deal, on the surface Brayden Schenn and three draft picks may seem like an appetizing return. However, Derek Zona’s study on draft picks and their value tells us something slightly different. Putting Schenn aside for a moment, what can we realistically expect from the first, second, and third round picks that the Flyers gained? Zona’s study is particularly excellent because it shows the historical chance of drafting a “top” player with a certain selection. He notes to “...consider the 'Top Players' to be top five forwards and top three defenseman [on their team].” Knowing what we know about Richards and Carter, I don’t think anybody would argue that the Flyers subtracted two established “top 5” forwards from their lineup. However, the article also notes that the odds of drafting such a player with the number 8-13 selections (they selected Couturier 8th overall) is a mere 41.2%. Looking at the other two picks, the 68th overall selection this season which turned into Nick Cousins has a 7.4% chance of turning into a Richards or Carter-esque player. Considering the Kings figure to be among the top western conference contenders next season in the wake of their offseason, I would most likely expect the 2012 second round pick to fall within this same range. The fact that the Flyers didn’t receive higher than a 50% chance to replenish their lineup with two established stars puts a bit of a hindrance on their returns.


Adding this to the fact that both Richards and Carter were on long-term, cap-friendly deals, and I’m not sure that there is a net positive to be found here. Perhaps Sean Couturier or one of the other selections will make a difference, saving the Flyers money in the short-term should they produce while on an entry level contract. So far, all indications are that Brayden Schenn will be given every possible opportunity to make the final roster, but much like Couturier, there are still question marks surrounding his development. Unfortunately, prospects are called prospects for a reason – there is no guarantee that they will meet development expectations. Considering what the Flyers gave up in these deals, while the return could most certainly prove lucrative, the odds simply do not stack up in their favor.

Putting Skaters in a Context: The World of Advanced Hockey Metrics

With the world of advanced hockey metrics continually improving, we are now beginning to see hockey players evaluated in more diverse ways than ever before. Since the beginning of many a hockey fandom, a quick glance at a skater’s goals, assists and total points has been the measure that grades offensive prowess across the league’s scorers. Now, however, the emergence of a few newer (and quite frankly, better) statistics allows us to take these age-old points totals and put them in a context, showing just how valuable a player may or may not be to his team’s success. Here at Driving Play, while attempting to evaluate different players across the league we will be commonly referring to many of these newer statistics within our analysis. Below is a quick list that will attempt to make clear just what we may be referring to if an unfamiliar term happens to appear within one or more of our posts.

A Corsi Number – Similar to a +/- statistic, Corsi gives a player a (+) upon the event of his team generating either a shot on goal, a missed shot, or a blocked shot directed at the opponent’s net while he is on the ice. Similarly, a player earns a (-) if the opponent generates a shot on goal, missed shot, or a blocked shot directed at his own net. Sometimes this can be expressed as a percentage, i.e. the percentage of the total shots that are directed at the opponent’s net while a player is on the ice. Corsi can also be expressed in a “Relative Corsi” number which is the difference between a player’s on-ice Corsi score and the shot differential while he is on the bench. Relative Corsi is generally used to look at which players are having the most positive effects on shot totals relative to their teammates.

A Fenwick Number – Since many consider shot-blocking a measurable skill in the hockey world, a Fenwick number is the same as a Corsi number, except blocked shots are taken out of the equation. So, a player will earn a (+) if his team generates a shot on goal or a missed shot whilst he is on the ice, and a (-) if either event occurs for the opponent.

Quality of Competition (QUALCOMP) – The fact is, all ice time in the NHL is not created equal. Having to line-up toe-to-toe with Sidney Crosby is a much different task than Jesse Winchester, the hockey player or the musician. QUALCOMP more or less weighs the on-ice +/- (the familiar statistic measured in goals) of a player’s opponents relative to the rest of his teammates, and averages this rating across every player faced during the season. The higher the resulting rating, the better the competition a player is facing and vice versa. There is also a CorsiRelQUALCOMP number which does the same thing, except uses Relative Corsi instead of +/-.

Quality of Teammates (QUALTEAM) – Similar to QUALCOMP, QUALTEAM weighs a player’s teammates using the exact same formula as QUALCOMP. Just like QUALCOMP, a player’s QUALTEAM rating will be higher if he is playing with first-line teammates and vice versa if he is playing with fourth-line enforcers. Also similarly, CorsiRelQUALTEAM will measure a player’s teammates using Relative Corsi.

Zone Start Percentage – A zone start percentage measures the percent of the time any player starts his shift in the offensive zone. As you might expect, players with a high defensive prowess are often called upon to start in the defensive zone frequently, and vice versa is true for those players who are more inept in their own end. This particular statistic is important in that it can directly affect a player’s aforementioned Corsi or Fenwick percentage since players who are starting in the offensive zone more frequently will have an easier time generating more shots towards the opponent’s net. What’s more, players who are more immediately deployed in defensive roles will have a harder time finding shot opportunities than their counterparts who are already starting in prime offensive positions. 

Score Effects – Within the ebbs and flows of a hockey game, it has been a long-believed ideal that teams will go into more of a “defensive mode” while ahead and try and get just about every shot possible on net while behind. Using Corsi and Fenwick percentages, it has been shown that teams who enjoy an advantage in the score are commonly outshot at improving rates as the game progresses and vice versa. With the score tied, the disparity in shot totals is most close to even which is why many advanced hockey statisticians choose to look at Corsi/Fenwick with the score tied at even strength to put players’ ice time on a level playing field.

Coming back to the original point regarding putting different skaters in a context, we are now able to more closely examine the situations that different players are playing in. For this reason, it is now much easier to come to a conclusion about their value to their respective teams. Before these statistics came into play, we could look at two players, Patrice Bergeron and Ville Leino for example, who had similar point totals during the regular season (57 and 53 respectively). In a vacuum, it may seem as if they are both comparable players toward Boston and Philadelphia’s total success. However, a little scratching beneath the surface reveals that Bergeron played against much tougher competition than Leino, and Leino enjoyed the luxury of skating with better teammates. Leino started in the offensive zone a walloping 62.3% of the time compared to Bergeron’s 42.7%, showing us that Leino was given far more prime scoring opportunities to begin his shifts which undoubtedly had a positive effect. Finally, Bergeron’s Corsi and Fenwick percentages with the score tied at even strength were 52.7 and 52.8% respectively, compared to Leino’s 54.9 and 53.1%. While a higher percentage of the on-ice shots were directed at the opponent’s net while Leino was on the ice, we have of course already noted that Bergeron faced tougher opponents and played with worse teammates than Leino which gave Leino an advantage in putting up better numbers in these categories. Had Leino, a notoriously subpar defensive forward (see: 2 seconds of average shorthanded time-on-ice/game in ’10-11) been given minutes similar to Bergeron’s, the point totals most certainly would not have looked anything similar. Considering the minutes they were given, Bergeron most certainly had an excellent season while Leino performed at a level around what we might expect from a forward given “softer” minutes during each game.