2011 NHL Review Alan Ryder Hockeyanalytics.Com

Home , Aaron Rome, Aaron Volpatti, Adam Hall, Alexander Edler, Alexandre Bolduc, Alex Auld

2011 NHL Review Alan Ryder HockeyAnalytics.com

Table of Contents

Introduction 3 Player Contribution Basics ...... 4 Threshold Performance ...... 5 Situational PC ...... 6 The Currency of PC ...... 7 Team Performances 9 Goals ...... 10 Lucky and Unlucky Teams ...... 11 Team Success ...... 15 Offense ...... 16 Shots and Shot Quality ...... 18 Defense ...... 22 Goaltending ...... 24 The Shootout ...... 31 Top Individual Performances 35 Forwards ...... 35 Defensive Forwards ...... 40 Defensemen ...... 45 Defensive Defensemen ...... 53 Goaltenders ...... 56 Transitions ...... 57 Rookies ...... 62 Shootout ...... 65 All Star Contributions 67 NHL ...... 67 West ...... 68 East ...... 69 Rookie ...... 70 Green ...... 71 Grey ...... 72 Offense ...... 73 Defense ...... 75 Even Handed ...... 76 Power Play ...... 77 Short Handed ...... 78 Most Valuable Performances ...... 79 All Cap Roster ...... 80 Hall of Fame Watch 85

Introduction

This review is focused on the most outstanding individual performances in the NHL during the 2010-11 (“2011”) regular season. But I will also comment on certain aspects of team performance since individual performances are difficult to assess without understanding the team context.

My tool for measuring individual player impact is Player Contribution (PC)1. It is a calculation that rationally attributes team results to individual players. It is focused on results rather than process. Therefore, importantly, it contains any noise associated with non-repeatable performance (luck). Noise cancellation techniques are available elsewhere to try to separate skill from results2 and I applaud those who try. In any case, PC remains the most comprehensive assessment of individual performance in hockey.

This kind of analysis is done in other sports (and by others in hockey). But buyers beware. The methods used elsewhere may not import so well. Hockey is unlike baseball, football and basketball in two material ways.

The first difference is the position of goaltender – a single player with a disproportionate accountability for goal prevention. The closest match in another major North American sport is the pitcher in baseball. The potential impact of the goaltending role is very large. The actual impact depends on a „first to worst‟ analysis – a large span between best and worst performances implies high value (and low span equals low value).

The second difference is that skaters (i.e. players other than the goaltender) play offense and defense simultaneously. In the other three sports, teams effectively take turns on offense. Football even has offensive and defensive units. While, in football and basketball turnovers can and do happen, such an event is relatively rare. In hockey, however, the puck is a slippery little sucker. Puck control is very challenging and turnovers happen all the time (whether or not the NHL calls them „giveaways‟ or „takeaways‟).

What this means is that, in hockey, offense and defense overlap. Players have concurrent roles and need to be constantly assessing both offensive and defensive opportunities and risks. Forwards have an offensive bias. Defensemen have a defensive bias. But the concurrence still prevails. One cannot truly separate offense and defense in hockey.

The conclusion is that the ebb and flow of opportunity and danger in a hockey game tells us something about individual player impact. The most glaring example of this is in

1 PC is described in http://www.HockeyAnalytics.com/Research_files/Player_Contribution_System.pdf but has been refined considerably since I wrote the paper.

2 There are now too many contributors to the advancement of hockey analytics to name all the names, but they know who they are as they run faster and faster with the larger and heavier baton.

Copyright Alan Ryder, 2011 Hockey Analytics www.HockeyAnalytics.com 2011 NHL Review Page 4 penalties. The taking of a penalty (typically) puts a team on its heels for (up to or maybe more than) two minutes. Defensive risk increases. Offensive potential is reduced. The drawing of a penalty has the opposite effect.

The game has many other „transitions‟ that alter the offensive or defensive „potential‟ of the game. These include the obvious candidates of faceoffs, takeaways and giveaways and the less obvious (and unrecorded) events like the battles for position and possession along the boards and in front of the net. Transitions also include the lightly documented but critical result of moving the puck up (or down) the ice.

A player that generates positive transitions is adding value because he elevates the ratio of offense to defense (and vice versa). On balance each of these other transitions have small impact (relative to penalties), but there are players that consistently transition well and it adds up to something.

Transitions matter a great deal in the same way that probabilities matter. But goals are more like lightning storms than warm or cold fronts. Goals defy the odds and create finite counts from infinite possibilities. Goals char the scorecard, jarring perceptions rooted in a careful visual or analytic assessment of the rest of the game. In other words, while transitions matter, it‟s (nearly) all about the goals.

Player Contribution Basics

The PC method is a system of credits and debits. The credits are for the observed elements of individual performance that aggregate to team success. That part is easy to understand. The debits are to subtract the “marginal” aspects of performance – more on that below.

„PCO‟ is PC from offense, based on „goals created‟ (credits) in excess of a threshold level of performance (debits). To determine PCO a player is credited for creating goals but debited for ice time (greater ice time, especially for forwards and on the power play, means greater offensive expectations).

„PCD‟ is PC from defense, based on „goals prevented‟ in excess of a threshold level of performance. To determine PCD players get credited for ice time (greater ice time, especially for defensemen and on the penalty kill, means more defensive responsibility and exposure to goals against) but debited for goals allowed while on ice.

„PCG‟ is PC from goaltending – again based on „goals prevented‟ in excess of a threshold level of performance. Goaltender contribution is essentially measured by save percentage (credit) in excess of a threshold (debit), factoring in shots faced.

Defense and goaltending are challenging to disentangle. PC is based on the premise that the role of defense is to reduce both the quantity and quality of shots. Goaltending is whatever goal prevention is left over. The assessment of the contribution of goaltending therefore reflects various team defense factors.

Threshold Performance

In the Player Contribution calculations, threshold performance is determined mathematically, by inference. It is determined by observing that (a) the marginal impact of more/fewer goals on wins/points is virtually linear3 over the normal performance range of teams and (b) the “slope” of that linear relationship is the average number of goals scored per game. Marginal or threshold performance is determined by figuring out what level of performance predicts zero contribution to winning when using this linear relationship. This is close to, but not the same as, „value over replacement performance‟ (VORP).

The notion of threshold performance is critical to the analysis of individual performance. If a typical AHL goaltender gets promoted to the NHL and posts an .898 save percentage4, we should think of an NHL regular with a .900 save percentage as not contributing a performance of very much value, there being a large number of others (minor leaguers) lined up to play nearly as well. This is VORP think.

Although not really true, you can think of a „marginal‟ player through the VORP lens – as a borderline NHLer (my AHL goaltender). It is difficult to be precise about where the borderline is, but the PC method draws a line in the sand somewhere near it.

Why subtract out borderline performance? Because performance at that level is worth „nothing‟. Borderline players sit on the end of the bench and / or spend a great deal of time in transit to / from the minors. Marginal performance is so far from average as to be zero valued5.

The (VORP) assessment of marginal (valueless) performance based on the contribution of a replacement player (my AHL goaltender) is a common approach used in baseball analytics where most players are either (a) regulars or (b) replacement players. The

3 This is critical to the success of any measurement of individual contributions to team success. “Linearity” means that individual contributions are additive. Every goal scored or prevented has the same impact on winning percentage. Non-linearity (curvature) would mean that not all goals have the same impact on winning percentage and, by extension, that the attribution of team success to individuals would involve very complex assessments of the nature of the curvative relationship between goals and wins. The relationship between goals and wins is curved for teams winning 70% or more of the time (or losing 30% or more) but those are very rare teams. PC does make an adjustment for whatever curvature (or statistical noise) is detected so that individual performances do sum to team performance.

4 For 2011 my “threshold save percentage” is.898 (based on a league average save percentage of .913). Both are up .002 from last season. Over the 1996-2011 period, goalies playing 5 or fewer games (some partial) have averaged a save percentage of about .885. That is one way VORP might be defined. The standard baseball definition is to average the performance of non-starters. This approach might make you inclined to look at the average performance of goaltenders with (say) less than 30 games played. If you do that you get a threshold level of performance of about .905. My mathematics (not a „view‟) is approximately equivalent to averaging across goaltenders with less than 10 games played.

5 Not exactly. The NHL has a minimum wage. But one can easily adjust for this factor.

Copyright Alan Ryder, 2011 Hockey Analytics www.HockeyAnalytics.com 2011 NHL Review Page 6 application of that thought process (and various rules of thumb derived from it) is tempting but, for hockey, the notion of replacement level performance is much trickier. Other than in goal, especially with player changes every 30-40 seconds, it would be difficult to sort players into the categories of “regular” and “replacement”. A third line forward or third pairing defender is used regularly, frequently in special roles. These players are a core part of a hockey team.

In fact the notion of a “replacement player” is quite tricky in hockey. When the first line centre is injured, the second line centre gets a promotion (gains more ice time). Or perhaps the third line centre is a better fit on the “first” line. Yes, somebody from the “fourth line” is going to get more ice time (and a call up player will dress). But it may not be the centre and players can and do shift position. And it may not be much ice time as second and third line players may get incremental special team duty.

A hockey team is not comprised of “regulars” and “replacement players”. Instead there is an allocation of ice time along the spectrum of superior to inferior players (even in goal). The cascading effect of replacing a player is difficult to model and highly situational. With all of this in mind I stick with my approach to the assessment of marginal performance. And it tests out just fine. Players with any amount of playing time and PC scores of around zero get deployed by coaches as if they were „replacement players‟.

Situational PC

Where we can, PC is measured separately for even handed (EH), short handed (SH), power play (PP) and shootout (SO) situations. This ensures that specialty team performance is assessed relative to marginal performance on specialty teams. In other words, a player who runs up big offensive numbers on the power play is judged against other power play performances while a penalty killing specialist has his offense and defense judged against other penalty killers. Perhaps more importantly, assessing contribution by situation permits a much better assessment of overall performance as the pieces are more easily assessed that the whole.

PC is also determined for transitions. This is mainly about penalty taking and drawing and is best interpreted as an adjustment to the other PC scores. I valiantly attempt to attribute transitions to offense („increases offensive potential‟) or defense („increases defensive risk‟), Components of Player Contribution but transitions are really a shift in balance and have both offensive and Situation Offense Defense Goaltending defensive implications. The Even Handed PCOEH PCDEH Power Play PCOPP PCDPP offensive (mainly penalty drawing) PCGRO and defensive (mainly penalty taking) Short Handed PCOSH PCDSH components are called PCOTR and Transitions PCOTR PCDTR PCDTR. This is a somewhat Shootout PCOSO PCGSO arbitrary split as transition events TOTALS PCO PCD PCG only tilt the „game‟ whereas other

Copyright Alan Ryder, 2011 Hockey Analytics www.HockeyAnalytics.com 2011 NHL Review Page 7 offensive and defensive events involve goals scored (a measurement of offense) or allowed (a measurement of defense). One should think of PC from transitions as the fine- tuning of the other PC scores.

Above is a summary of the component parts of PC.

The ‘Currency’ of PC

Since advancing in the standings (winning) is the one and only team objective, PC is denominated in points in the standings (wins). Goals created/prevented are translated into points in the standings on the same basis that teams do so. A PC „point‟ is scaled to be 1/10th of a standings point and the PC points allocated to a team are therefore 10 x points in the standings. The end result is that offense, defense and goaltending (including shootout performance) are all on the same page, in the same currency. This denomination of player contribution is also „inflation proof‟ – it is unaffected by changes in scoring levels (but is affected by schedule length and the number of regulation ties).

To get a lot of PC points one needs to both (a) play a lot and (b) play well. As (a) and (b) tend to be highly correlated, PC is also a measure of „talent‟. The distortion , if any, has to do with over- or under-playing talent.

As a rough rule of thumb it takes about 100 PC points for a skater to be an all-star candidate (the story with goaltenders is different). At 80 points you would consider a skater to be a team star, 60 is a team leader, 40 is a solid contributor and 20 is a weak link or a role player. With a salary cap of $59.4 million (all figures U.S.) for the 2011 season, a rough guide to player value is $59,400 per annum per PC point or $1,188,000 for every 20 PC points). This is based on a team spending the cap amount and targeting a 100 point season, a comfortable target for a berth in the playoffs. In 2011 the Rangers claimed the final berth in the East with 93 points while the Blackhawks needed 97 points to do the same in the stronger Western Conference. A serious Stanley Cup aspirant would need to target a lower cost per PC point (8 NHL teams cleared the 100 point plateau in 2011, down from 11 in 2009). And, of course the market value of a player may be different due to supply and demand and other factors.

As an illustration I have shown below the cap costs (all dollars are US), PC scores (rounded to the nearest integer) and the dollar cap costs per PC point for the Vancouver Canucks. Note that cap costs in this table are (a) annualized (the actual “cap hit” depends on days on the roster, which is a big factor for those at the bottom of the table) and (b) not salary (cap costs are the average salary/bonus over the contract). Cap costs per point are nonsense when PC is negative or very small and will be higher for players sustaining injuries than for healthier players.

Vancouver was the NHL‟s best team during the regular season. This analysis shows how the Canucks success was driven by high value goaltending and a minimum of salary cap baggage.

Success within the salary cap is always based on strong performances from well-priced players. Vancouver got great value from goaltending. Luongo cost about $23K per PC

Copyright Alan Ryder, 2011 Hockey Analytics www.HockeyAnalytics.com 2011 NHL Review Page 8 point and Schneider, who put in the same kind of performance in more 2011 Vancouver Canucks limited playing time, cost about $9K. Cost per Kesler, Ehrhoff, Burrows and Malhotra Player $ Cap Cost PC PC Point were value leaders, coming in under Roberto Luongo 5,333,333 234 22,765 budget with substantial contribution. It Ryan Kesler 5,000,000 103 48,470 is challenging to get value out of Cory Schneider 900,000 102 8,797 contracts north of $4 million so the Daniel Sedin 6,100,000 86 70,869 Canucks should be very pleased with Christian Ehrhoff 3,100,000 77 40,488 Henrik Sedin 6,100,000 66 92,230 the performance of Kesler. At the other Alexandre Burrows 2,000,000 61 32,759 end of the pay scale Hansen, Torres and Manny Malhotra 2,500,000 53 47,585 Tambellini punched above their weight Dan Hamhuis 4,500,000 51 88,616 class. Kevin Bieksa 3,750,000 48 77,664 Alexander Edler 3,250,000 45 72,809 Salary baggage was generally light. Mason Raymond 2,550,000 43 59,357 The headline numbers of the Sedin Jannik Hansen 825,000 37 22,240 twins were good, but PC recognizes Mikael Samuelsson 2,500,000 35 70,918 that coaching and teammates put them Keith Ballard 4,200,000 25 169,819 on their pedestal and then takes some Raffi Torres 1,000,000 23 43,025 air out of their numbers. Nevertheless Jeff Tambellini 500,000 17 28,915 their matching contracts are not (yet) Aaron Rome 750,000 15 50,392 oversized luggage. Edler had a big Sami Salo 3,500,000 14 245,325 contract but missed 31 games. Bieksa Andrew Alberts 1,050,000 11 93,339 had a bigger contract that he more or Chris Tanev 900,000 7 124,963 less lived up to while missing about Alexandre Bolduc 500,000 5 100,161 20% of the season. Chris Higgins 1,600,000 5 321,794 Lee Sweatt 650,000 4 184,049 Ballard was the biggest bust with a $4.2 Tanner Glass 625,000 3 249,662 cap hit and only 25 PC points in 65 Sergei Shirokov 1,300,000 2 649,103 games. Hamhuis has a big contract but Mario Bliznak 550,000 1 373,791 missed about 20% of the season. Cody Hodgson 1,666,666 1 1,906,266 Salo‟s contract was heavy but he Evan Oberg 1,562,500 1 2,404,860 missed 70% of the season. Aaron Volpatti 612,500 0 1,867,785 Ryan Parent 925,000 0 4,922,418 Peter Schaefer, at $220 million per PC Victor Oreskovich 575,000 0 9,332,668 point (!) was not the worst of the Jonas Andersson 675,000 0 19,687,314 Canucks, just the worst of those who Peter Schaefer 875,000 0 220,108,793 managed to eek out a positive PC score. Yann Sauve 875,000 0 999,999 He dressed for 16 games and did Maxim Lapierre 900,000 -1 999,999 approximately nothing for Vancouver‟s Joel Perrault 510,000 -1 999,999 success. Guillaume Desbiens 550,000 -1 999,999 Rick Rypien 550,000 -2 999,999

The NHL‟s standings are very unfortunate. The problem is the „overtime loss‟.

When a game is not „close‟, teams split two points – the winner collects two points and the loser collects zero. The NHL defines „close‟ as a regulation tie.

But when a game is „close‟, teams split three points – the winner collects two points and the loser collects one. The extra point does not really result from an „overtime loss‟ as both teams effectively win a point in regulation time. It comes from winning the follow- on competition (overtime) or its follow on match (the shootout).

There is very little evidence that overtime and, especially, the shootout are anything other than elaborate coin tosses. While skill is present, random influences are so large as to overwhelm the effects of talent. 2011 Overall What this does is encourage the implicitly NHL Standings collusive behaviour of playing for a regulation Ryder NHL Goal tie. The risk/reward relationship of a game that Team Points Points Differential is tied in the third period is quite asymmetrical. VAN 272 117 70 While a goal scored or allowed in a third period PHI 245 106 35 tie is close to a point gained or lost, a regulation BOS 242 103 49 tie creates the certainty of (at least) a single SJS 239 105 30 point while preserving the potential of two WSH 238 107 17 points. DET 232 104 19 PIT 231 106 28 TBL 227 103 5 A good point system would encourage ANA 225 99 6 competition and discern strength of performance. PHX 222 99 -5 Many would like to simply eschew the point for NSH 221 99 15 an overtime loss. I prefer the following scoring MTL 220 96 11 system – 5 points for a regulation win, 4 points CHI 218 97 32 for an overtime win, 3 points for a shootout win, LAK 217 98 11 DAL 213 95 2 2 points for a shootout loss, 1 point for an NYR 207 93 30 overtime loss and 0 points for a regulation loss. BUF 206 96 16 Each game is worth five points and the more CGY 204 94 17 decisive the victory the greater the reward. Such CAR 200 91 -1 an approach would motivate teams to play to win MIN 197 86 -23 (not just to tie) in the third period and in STL 196 87 6 overtime. The result would be fewer overtime TOR 190 85 -26 NJD 184 81 -39 and shootout games. CBJ 176 81 -42 ATL 169 80 -31 Revised NHL overall standings based on these OTT 169 74 -55 „Ryder points‟, a better measure of relative FLA 155 72 -25 performance, are shown to the right. This NYI 154 73 -31 approach to the standings clearly affects one‟s COL 141 68 -55 view of team performance. EDM 140 62 -66

Ryder points let some air out of Washington‟s season. The Capitals were in overtime 25 times, compiling a 14-11 combined record in OT and the shootout.

Compare that to the Bruins‟ story – just 14 trips to OT (and a poor 3-11 record after regulation time). Ryder points says that the Bruins were a better (regular season) team than Washington, Pittsburgh and Tampa.

You can see that this approach lets the air out of the Penguins‟ (10-3) and Kings‟ (10-2) records in the Monte Carlo event known as the shootout. Both teams slide down in the Ryder point rankings.

This approach would not have changed playoff qualifiers but would have affected playoff seeds. In particular the Kings would have drawn the tough Vancouver matchup in the first round rather than the Blackhawks.

Goals

Also shown in the table above are the goal differentials (GF – GA) for each team. There is an obvious and strong correlation between goal differential and points in the standings. I exclude empty net goals from this calculation because they don‟t contribute materially to winning. In 2011 Phoenix scored a league leading 14 empty net goals. All this really tells us is that they won a lot of close games. Atlanta allowed 15 ENGs – they lost a lot of close games.

The goal differentials shown above would lead you to question the success of Tampa Bay, Anaheim and Phoenix. The Coyotes, in particular, collected 99 NHL points and 222 Ryder points but were outscored by 5 goals on the season, ignoring empty net situations.

These goal differentials generally correlate better to playoff and subsequent season success than do points in the standings. They tend to better reflect true team strength. While winning is what the game is about, one problem with a focus on the results of games is the small number of events being studied (82). Small sample sizes give rise to statistical fluctuations. I call this the “law of small numbers” (which is essentially the opposite of the “law of large numbers”). The study of goals gives a richer picture of teams and especially individuals. An even better story may be told by shot totals (more on that below).

A problem with studying goals is that they come in two flavours – for and against. One solution is goal differentials. Another all encompassing measurement of goal scoring and prevention is „marginal goals‟:

a. goals scored in excess of a threshold, plus b. goals allowed subtracted from a threshold.

Marginal goals, a building block for Player Contribution, have the benefit of putting offense and defense in the same currency so that they can be aggregated and disaggregated at will.

Lucky and Unlucky Teams

The Cost of a Win

Wins are about 94% predicted by goals for and against, marginal goals totals or goal differentials. When teams like Phoenix, Anaheim and Tampa Bay win in spite of a low marginal goal performance they are either very skilled at winning close games or just plain lucky. “Hockey people” will tell you that winning close games is about character. Historical analysis suggests that this is mostly luck. I would not completely rule out some intangible, but nobody has found it yet. Lucky teams tend to regress the following season (and vice versa). But these teams may also be systemically able to win tight games.

To the right is a table of the marginal goals per point during the conventional Marginal Goals per Point part of the game („skating time‟) and during the shootout. The five most In Skating Time In Shootout efficient/lucky teams are highlighted in Team per Skating Point per Shootout Win ANA 2.64 2.59 green and the five least efficient/lucky ATL 2.40 2.27 teams are highlighted in red. BOS 2.76 1.17 BUF 2.59 2.29 Scoring was down in 2011 and an average CAR 2.57 1.61 point in the standings was less expensive CBJ 2.42 3.20 (required fewer goals to obtain) as a CGY 2.77 1.46 result. During skating time it cost, on CHI 2.81 1.76 average, 2.58 goals to generate a point COL 2.55 2.28 DAL 2.44 2.26 (versus 2.64 in 2010, 2.71 in 2009 and DET 2.44 2.49 2.60 in 2008). In a reversal of a trend, it EDM 2.58 2.24 required fewer goals to resolve a shootout FLA 2.84 1.45 in 2011 (an average of 2.17 per shootout) LAK 2.69 2.40 than in the past (2.44 in 2010, 2.25 in MIN 2.40 2.14 2009 and 2.21 in 2008). MTL 2.48 2.86 NJD 2.41 2.28 NSH 2.66 2.30 The Ottawa Senators repeated as the most NYI 2.77 2.01 „efficient‟ team in the NHL during NYR 3.01 2.63 skating time, requiring only 2.35 OTT 2.35 0.85 marginal goals per point. Tampa Bay PHI 2.56 1.58 (2.38) also repeated as one of the NHL‟s PHX 2.45 2.18 most efficient (luckiest?) teams. PIT 2.67 2.40 SJS 2.59 2.27 The chances of a repeat happening STL 2.80 2.67 TBL 2.38 2.48 randomly are quite high. But Toronto TOR 2.40 1.80 (2.40) has now posted a four-peat as one VAN 2.67 1.67 of the league‟s luckiest teams. Other WSH 2.47 2.00 lucky teams were Minnesota and Atlanta AVG 2.58 2.17 (both at 2.40).

Chicago (2.81) also concluded a four-peat – as an unlucky team. The Blackhawks had the fourth best goal differential in the NHL but only just made the playoffs.

A four-peat in the top or bottom five should happen randomly to a given team only about 1 in 1,300 times. The probability of a four-peat somewhere in a thirty team league is much higher – about 2%. This suggests that something odd is going on in Toronto (something that makes this team more successful in close games than in blowouts) and Chicago (an unsuccessful team in close games). I live in Toronto, but I haven‟t seen the Leafs exhibit stronger character in close games.

A case study in close games and blowouts was the 2011 Stanley Cup final. Vancouver won games 1 and 2 with goals in the 60th and 61st minutes respectively. Boston proceeded to blow out the Canucks in games 3 and 4. At this stage the statistical (goal scoring) evidence was that Vancouver was the weaker team. Vancouver shrugged off the big losses – “a loss is just a loss” – and took game 5, by one third period goal. The Bruins responded by smoking the Canucks to set up game 7. At this stage the statistical evidence was still that Vancouver was the weaker team. Sure enough, the better team (goaltender?) prevailed.

Back to the regular season: The Rangers (3.01) were the NHL‟s unluckiest team during skating time, just behind the Hawks in goal differential but also just making the playoffs.

The Blues and Rangers were double-unlucky –ranking as one of the NHL‟s least efficient teams in both conventional and shootout play. New York had a very good 9-3 record in the shootout, but they deserved more. Columbus was the NHL‟s most unlucky shootout team, requiring 3.20 marginal goals to earn a shootout point. They posted a 5-8 record.

Ottawa was the NHL‟s most fortunate shootout team with a 2-5 record despite just 3 goals scored in 22 attempts (in marginal-goal-speak 0.85 marginal goals per point). The Bruins (1.17 marginal goals per point) were also pretty fortunate (2-6) despite awful shootout goaltending.

I have never detected any season to season correlation in shootout efficiency. This is part of the evidence that the event is an elaborate coin toss.

Historically there has been very low season to season correlation in marginal goals per point during skating time. This is part of the evidence that (in) efficiency is just (bad) luck and most likely will not repeat next season – „unlucky‟ teams are more likely to improve and „lucky‟ teams are more likely to regress. However, 2010 and 2011 marginal goals per point were about 55% correlated and the Toronto – Chicago pattern makes one wonder. Baseball eventually discovered that it was not just runs scored and allowed but also closer effectiveness that mattered in winning. There could be a „third variable‟ resent in hockey – or just some randomness that looks like it has a pattern.

Measuring Luck

Below is another way of looking at the question of luck. The blue bars are expected points during skating time, given goals scored and allowed, the red bars are expected

Copyright Alan Ryder, 2011 Hockey Analytics www.HockeyAnalytics.com 2011 NHL Review Page 13 points for the shootout, given goals scored and allowed, and the gold bars are the difference between actual and expected points, or overall luck in the standings.

The rank order is marginal goals during skating time (the blue bars) so that you can see what (a) the shootout and (b) randomness does to the overall result. There are various models one could use to get to expected points. As the answers don‟t vary much I have used a simple one – marginal goals.

This says that the Rangers were a very (16 points) unlucky team in 2011 and are therefore the best candidate for most improved team next season.

Shooting and Saving

But there is more „gold‟ than meets the eye. The blue and red bars above have some luck embedded within them. The best illustration is in the shootout data. The Kings went 10-2 in the shootout. Pittsburgh was 10-3 and the Rangers went 9-3. The actual goals scored and allowed supported those kinds of record – my analysis indicates that they all were expected to earn 11 shoot out points, given goals scored and allowed. But hockey is full of random events and it is doubtful that these teams would have had similar records had they replayed these contests.

During 2011 each NHL team was in 82 competitions, scoring and allowing an average of 224 goals. Studying the (average of) 448 goals scored and allowed roughly doubles the statistical information about team quality that is provided in the points column. Any one goal can be quite a random event and affect the outcome of a game. Patterns of team quality are clearer with a larger database.

An even larger database is developed if one studies shots (an average of 2,492

Copyright Alan Ryder, 2011 Hockey Analytics www.HockeyAnalytics.com 2011 NHL Review Page 14 taken and allowed per team). Shots provide us with about 8 times the statistical fuel of wins.

However … while goals clearly matter directly to winning, shots clearly don‟t. Shots (taken / allowed) are what I call a „first derivative‟ of goals (scored / allowed). In other words they are material drivers of goals but only weaker drivers of winning6. Other obvious first derivatives of goals are shooting percentage (goals for) and save percentage (goals against). For Shooting and Saving completeness, the obvious second derivatives for goals are things like Shooting Save Team Percentage Team Percentage penalties, turnovers, faceoffs and other ANA 10.1% BOS .932 events that tilt the ice in favour of one VAN 9.8% VAN .928 team or another. PHI 9.8% NSH .926 DAL 9.8% NYR .922 These first derivatives tell us something CGY 9.6% MTL .922 about luck. Consider the bookends of CHI 9.6% WSH .920 Anaheim and New Jersey. The Ducks STL 9.5% PIT .919 led the NHL with a 10.1% shooting MIN 9.5% PHX .919 percentage, up from 9.4% in 2010, NYI 9.3% FLA .918 while the Devils were the league DET 9.3% MIN .917 laggards at 7.3%, down from 8.8% in TBL 9.3% CAR .916 2010. There is certainly a great deal of COL 9.2% LAK .916 luck in these results. One would be CAR 9.2% PHI .915 inclined to believe that if these two NYR 9.1% ANA .915 teams had a chance for a do-over of the PHX 9.1% DAL .914 2011 season, both would find BOS 9.1% SJS .914 themselves much closer to average. TOR 9.0% BUF .913 NSH 9.0% CHI .910 To the right is a ranking of NHL teams‟ BUF 8.9% DET .908 shooting percentages. Those teams at LAK 8.8% TOR .907 the top of the list are most likely to PIT 8.8% OTT .907 have been lucky and are most likely to EDM 8.7% NJD .906 have offensive regression next year. SJS 8.6% CGY .906 Those at the bottom are most likely to WSH 8.5% ATL .906 have been unlucky and are most likely ATL 8.4% NYI .905 to have favourable regression to the CBJ 8.4% EDM .903 mean. One can refine this analysis MTL 8.2% TBL .903 deeper (for instance, shooting OTT 8.0% STL .902 FLA 7.7% CBJ .900 percentage is about 20% explained by NJD 7.3% COL .895 power play opportunities), but I won‟t go further here.

6 Ironically, while goals are, by definition, 100% correlated with goals and shots are not, shot counts are more predictive of future goals due to a larger sample size.

Also shown in the table is a ranking of NHL team save percentages. But there is a big difference here. Whereas shooting percentages are a true team statistic (a weighted average of all the individual performances), team save percentages are highly influenced by one (or two) goaltenders. With saves it is much more plausible that skill is in evidence. Regression to the mean is also likely with save percentages, but it is a less powerful force due to larger sample sizes. Again, one can further refine the analysis (e.g. save percentage is influenced by shot count bias and shot quality influences, including short handed situations).

Player Contribution Allocates Observed Team Performance

Note that PC allocates team performance, whether lucky or skilled, to individuals. It does not set out to determine whether a performance is from luck or skill. It translates a player‟s marginal goals into PC points using the marginal goal factors shown above. The implicit assumption here is that these observed team performances are a result of skill. This means that a goal scored (or prevented) by a Senator is worth more PC points than a goal scored (or prevented) by a Ranger (in 2011). You need to do more work to try to separate skill from performance.

Team Success

A marginal goals analysis helps us to deconstruct team performance (during the first 65 minutes of play) into offense (MGO), defense (MGD) and goaltending (MGG). To the right is the composition of marginal goals by team. This analysis ignores the shootout as marginal goals in the shootout are in a different scale.

We don‟t need this analysis to rank overall performance during the conventional part of the game. We know that Vancouver was the NHL‟s top team and that Edmonton was its worst. But

Copyright Alan Ryder, 2011 Hockey Analytics www.HockeyAnalytics.com 2011 NHL Review Page 16 this view lets us make a number of observations:

 The Bruins were the top marginal goals team in the East. Boston had the strongest team MGG (92) in the league AND the strongest MGG since I developed Player Contribution. Who‟s your MVP?

 Vancouver had the second best MGG (84) in the NHL. Interestingly, the Canucks goaltending was middling through about the middle of the season. Then Luongo woke up. Vancouver had the NHL‟s best offense but a below average defense.

 Calgary and Tampa Bay were the NHL‟s two best teams, before one considers goaltending. Unfortunately for the Lightning and Flames, goaltending matters. In the case of the Flames, this cost a playoff spot. Fortunately for Guy Boucher, such problems can be fixed (e.g. Dwayne Roloson) and such a repair has tremendous leverage. More on this later.

 Many other teams suffered in goal. Ironically, both the Blue Jackets and the Blues had blue-paint blues.

 In New Jersey, the NHL‟s best defense was neutralized by the league‟s most awful offense (and, finally, a lack of goaltending).

Offense

A marginal goals analysis helps us to further deconstruct offenses. Below is a summary of marginal goals from offense (MGO) by situation – even handed (MGOEH), power play (MGOPP) short handed (MGOSH) and transitions (MGOTR) which, at the team level, reduce to penalty drawing. Also shown is the change from 2010. I will address the offense in shootouts separately.

Year to year variations in scoring are large in the NHL, evidence of the pronounced effects of randomness in observed offense. The proof is in the mean reversion of shooting percentages discussed above.

Here is what I said last year about Colorado:

“The biggest offensive improvement in the NHL came from the Avalanche. They went from worst to sixth, increasing marginal goals by 51. This looks like it could be a case of mean reversion as they had fallen off 40 (marginal) goals in 2009.”

Look them up in 2011 and you will find more mean reversion – the Avalanche ranked 18th.

Let me now use nearly the same words to describe the 2011 Bruins:

The biggest offensive improvement in the NHL came from the Bruins. They went from worst to fifth, increasing marginal goals by 50. This looks like it could be a case of mean reversion as they had fallen off 70 (marginal) goals in 2010.

Get the picture?

Marginal Goals - Offense

Team vs 2010 MGO MGOEH MGOPP MGOSH MGOTR VAN -8 127 84 41 2 1 DET 36 126 89 35 1 1 PHI 26 125 98 18 9 0 CHI -8 121 86 35 2 -1 BOS 50 113 94 15 7 -3 SJS -12 112 73 38 2 -0 CGY 42 110 76 29 3 3 TBL 30 110 75 34 -3 5 BUF 11 109 88 25 -2 -1 STL 20 105 81 23 3 -1 ANA 4 104 65 37 3 -1 CAR 7 100 73 19 3 6 PIT -19 97 70 16 9 2 PHX 17 95 79 16 1 -0 NYI 13 94 62 20 11 1 NYR 7 93 68 19 7 -0 DAL -6 91 61 23 6 2 COL -14 90 68 21 4 -3 WSH -92 88 70 18 3 -3 ATL -10 87 63 23 2 -0 MTL 5 82 55 27 1 -0 NSH -2 82 71 13 1 -2 TOR 5 82 60 18 1 4 CBJ -2 79 66 10 2 1 LAK -20 78 62 16 -0 0 MIN -9 72 47 22 3 0 EDM -13 60 43 12 4 1 FLA -9 60 56 7 -0 -2 OTT -28 59 43 18 2 -4 NJD -43 40 38 9 -1 -6

Here is more detail on the big swings in Washington and Boston:

Team 2009 2010 2011 Goals 268 313 219 WSH Shots 2,748 2,693 2,566 Shooting Percentage 9.8% 11.6% 8.5% Goals 270 196 244 BOS Shots 2,482 2,599 2,696 Shooting Percentage 10.9% 7.5% 9.1%

The Bruins shooting percentage went from a league best in 2009 to a league worst in 2010 to slightly above average in 2011. Washington went from above average in 2009 to league best in 2010 to below average in 2011. There is some variation in shots, but the main driver of the enormous swings in goals scored is in shooting percentage. Some of that is explained by penalties and some is explained by changes in personnel, but most is explained by (random) variation in shooting success.

Other really big swings in 2011 MGO were in Detroit (+36), Calgary (+42) and New Jersey (-43). The Devils has the NHL‟s worst offense overall (worst even handed and second worst on the power play). A big part of this was the absence of Zach Parise. Calgary had mean reversion going on (having dropped 46 marginal goals in 2010). Detroit had mean reversion (having dropped 62 marginal goals in 2010).

Enough about mean reversion, for now …

Philadelphia had the NHL‟s top even handed offense, Vancouver had the league‟s best power play and Detroit was in between. The three teams were in a virtual dead heat for best offense. The Flyers nearly won it with the second-best (9 MGOSH) short handed offense (which is a very random success), behind the skillful Islanders (11).

Boston would have been in the mix if not for a woeful power play (just 15 MGOPP). The NHL‟s worst power play was in Florida (7 MGOPP).

At the team level, MGOTR (transitions) reduce to a team‟s relative ability to generate power play opportunities (draw penalties). Carolina (with 6 such marginal goals) earned an extra two points in the standings by their ability to draw penalties. This was the sixth year in a row for a strong performance by the Hurricanes in this metric. Tampa (5) and Toronto (4) also did well here. New Jersey (-6) and Ottawa (-4) were the poorest performing penalty drawing teams.

In general, weak offensive teams were not playoff teams while strong offensive teams were. The Kings were the weakest offense to gain a playoff position (MGO of 78). But 105 MGO was not enough for St. Louis.

Defensive Measures – Shots and Shot Quality

Marginal goals analysis is an even more helpful tool for assessing defenses. But, to get at this, it is necessary to separate goal prevention into defense and goaltending. To identify a team‟s contribution from goaltending I compare its goals against, adjusted for shot quality and shot recording biases, to a threshold level (based on the shots allowed).

A goaltender facing no shots cannot make a contribution. When he faces a high number of shots he can make a high contribution. So the number of shots faced is a significant factor in assessing goaltending contribution. For a given number of shots a high (shot quality neutral) save percentage implies a big goaltending contribution (and a low shot quality neutral save percentage implies a small goaltending contribution).

And whatever is not goaltending must be attributable to defense. This is clearest with shots (low shots allowed suggest a strong defense).

If you do this math you are attributing to defense the responsibility for the number and quality of shots on goal. Below are the defensive leader boards for the 2011 season.

Shots

Average shots allowed per game is a Defensive Measures very familiar metric and the dominant part of the assessment of team defense. Avg Shot New Jersey continue to play devilish Team Shots Team Quality defense, moving from 2nd in 2010 to 1st NJD 26.2 TBL 0.877 in 2011 and giving up just 26.2 shots STL 27.7 MIN 0.880 per game. For the third year in a row LAK 27.9 DAL 0.914 CGY 28.5 LAK 0.915 the Kings were a top four shot PIT 28.7 CGY 0.923 prevention team. Calgary moved up CHI 28.7 NYR 0.929 from 7th to 4th and Pittsburgh went from th th TBL 28.7 NJD 0.940 6 to 5 . SJS 28.9 CBJ 0.946 WSH 29.0 BUF 0.952 The Blues were the biggest mover near th nd NYR 29.4 PHX 0.968 the top, moving from 16 to 2 . CBJ 29.8 WSH 0.981 Tampa Bay had a similar improvement th th VAN 30.1 FLA 0.989 – 8 last to 7 best. PHI 30.1 SJS 0.990 DAL 30.5 NSH 0.995 The Bruins (14th to 29th) and Coyotes th th NSH 30.6 CHI 1.007 (12 to 28 ) went the other way. BUF 30.7 PIT 1.007 Teams tend to open up (trade defense DET 30.7 BOS 1.015 for offense) in front of good MTL 31.0 OTT 1.016 goaltending. TOR 31.0 STL 1.019 OTT 31.2 EDM 1.019 Carolina slipped 8 spots in the shots EDM 31.7 TOR 1.024 allowed rankings to claim the title of COL 31.8 DET 1.033 “most open defensive team”. Anaheim FLA 31.8 ATL 1.042 nd is hanging around the hoop (2 worst NYI 32.0 MTL 1.046 th in 2010, 4 worst in 2011). Winnipeg MIN 32.0 PHI 1.056 inherits a similar profile from Atlanta ATL 32.2 CAR 1.059 (4th worst in 2010, 5th worst in 2011). ANA 32.3 VAN 1.090 PHX 32.6 COL 1.101 Shot totals were up again in 2011. BOS 32.7 ANA 1.102 Average shots on goal per game CAR 33.2 NYI 1.119 increased slightly from 30.3 to 30.4. The dispersion of team results („worst to first‟) decreased a fair bit in 2011, from 9.0 to 7.0 shots.

Warning! There are serious issues with something as simple as shot counts. The only objective event around the net is a goal. Saves, misses and blocked shots are all subjective events.

Below is a table of total (for and against) shots recorded for each team at home and on the road. This home versus road, total shots analysis reveals some or all of (a) recording bias, (b) shift in openness of play and (c) randomness. Colorado‟s 8.2% „shot inflation‟ at home could be the result of a more open style of game at home (less open on the road) or an upward recording bias in shots. Minnesota‟s 11.0% „shot deflation‟ at home could be the result of a less open style of game at home (more open on the road) or a downward recording bias in shots. Shots Recorded Note that the home/road ratios are about 25% explained by the prior year data. Home Team Road Home vs Road This suggests some recording bias. COL 2,395 2,591 1.082 DET 2,554 2,704 1.059 Consider the „miss‟. A puck directed NSH 2,361 2,495 1.057 wide of the net but touched by the SJS 2,526 2,662 1.054 goaltender might be a shot in one rink TOR 2,383 2,505 1.051 and a miss in another. What are we to WSH 2,410 2,518 1.045 make of the scoring in a rink where shot NYI 2,451 2,560 1.044 totals are high and miss totals are low? MTL 2,517 2,611 1.037 This might indicate that the scorer has PHI 2,491 2,568 1.031 widened the net. There are other issues. TBL 2,445 2,499 1.022 There are rinks where scorers look lazy ANA 2,464 2,507 1.017 (or overzealous) with the recording of BOS 2,661 2,700 1.015 certain events. VAN 2,526 2,554 1.011 ATL 2,600 2,602 1.001 Scorers in Toronto reported a league CAR 2,620 2,610 0.996 leading 1,353 „misses‟ in the Leaf‟s FLA 2,551 2,540 0.996 defensive end. On the road scorers PIT 2,464 2,454 0.996 reported just 1,126 „misses‟ in the Leaf BUF 2,602 2,586 0.994 zone. In New Jersey scorers reported a OTT 2,477 2,449 0.989 league lagging 686 „misses‟ in the CBJ 2,498 2,439 0.976 Devil‟s defensive end whereas road STL 2,401 2,335 0.973 scorers logged 1,039 „misses‟. Do NJD 2,273 2,208 0.971 Toronto scorers shrink the net? Are DAL 2,416 2,341 0.969 they overzealous in recording misses? LAK 2,365 2,274 0.962 Do New Jersey scorers expand the net? NYR 2,473 2,375 0.960 Are they lazy reporters of misses? EDM 2,435 2,334 0.959 CGY 2,465 2,357 0.956 In assessing defensive performance (see CHI 2,544 2,427 0.954 below) I have attempted to isolate and PHX 2,651 2,491 0.940 correct for reporting biases. An upward MIN 2,516 2,239 0.890 (downward) reporting bias in shots means that we need to reduce (increase) our measurement of defensive performance and increase (reduce) our measurement of goaltending. But this is increasingly art rather than science.

Shot Quality

Shot quality7 is based on an assessment of the characteristics of each shot allowed. The expected goals allowed8 from this assessment, normalized for variations in shots on goal, can be compared to average. My shot quality factors are the ratio of these normalized expected goals to average (a shot quality factor of 0.950 means that shots taken are, on average, 5% less likely to result in goals).

There is pretty strong evidence that shot quality is not very descriptive on offense. To the extent that one can sift through the statistical noise it turns out that the shooter‟s skill supersedes the circumstances of the shot. However on defense, after you have effectively averaged across a lot of shooters, shot quality turns out to be an important descriptor of a team.

There is a clear shot distance recording bias9 in certain arenas. The worst such reporting bias is in Madison Square Garden where the raw data suggests that the Rangers give up (and take) much shorter shots than average (shorter shots are more likely to be goals). But further analysis reveals a big distance recording bias. I address this problem directly in my assessment of shot quality.

The 2011 shot quality leader was Tampa Bay (up from 7th in 2010). Minnesota, Dallas, Los Angeles and Calgary rounded out the top five. The Wild were up from 5th, but the others moved up considerably from the bottom of the heap. The Stars ranked 28th in 2010, LA was 20th (28th in 2009) and Calgary was 23rd.

The Devils slipped from 1st to 7th, Phoenix went from 2nd to 10th and Buffalo slid from 3rd to 9th. The Flyers had the worst fall from grace (4th to 25th).

The Islanders, Ducks, Avalanche and Canucks were the biggest laggards in shot quality. All were around average in 2010. Last season‟s stragglers, the Leafs and Blackhawks, both became average.

One should not necessarily expect a correlation between shots allowed and shot quality. These are two very different dimensions of a defensive profile (but shot counts still matter more). This year the R-squared of these two data sets was 0.19 (19% of one variable is explained by the other).

7 My original approach to Shot Quality is described in http://www.HockeyAnalytics.com/Research_files/Shot_Quality.pdf

8 Expected Goals is the sum of goal probabilities, across all shots. It is a weighted shot / Corsi / Fenwick assessment, the weights being shot quality (the probability of a goal given the circumstances of the shot). It is such a useful measure that it has been borrowed, repackaged, renamed and sold to one or more NHL teams.

9 See http://www.HockeyAnalytics.com/Research_files/Product_Recall_for_Shot_Quality.pdf

Defense

Goals allowed reflect both defense and goaltending. But when you look at shots allowed, adjusted for shot count biases, together with shot quality, adjusted for distance recording biases, you end up with a comprehensive assessment of team defense.

Marginal goals provide a sophisticated look at team defense. Below is a summary of marginal goals from defense (MGD) by situation – even handed (MGDEH), power play (MGDPP), penalty killing (MGDSH) and transitions (MGDTR) which, at a team level, reduces to penalty taking. Also shown is the change in MGD from 2010.

Marginal Goals - Defense

Team vs 2010 MGD MGDEH MGDPP MGDSH MGDTR NJD 8 142 98 3 28 14 LAK 15 130 91 4 32 3 CGY 24 124 93 2 27 2 WSH 22 122 88 4 32 -2 TBL 24 121 92 -5 37 -3 STL 18 117 78 9 26 3 SJS 24 116 92 3 18 4 PIT 12 111 81 3 33 -7 DAL 30 106 86 -3 20 3 CBJ 4 105 84 0 28 -7 NYR 7 104 73 4 20 6 NSH 1 101 70 5 22 3 BUF 3 101 77 -2 27 -2 CHI -23 100 73 5 15 8 MIN -7 98 72 3 27 -4 VAN -7 90 66 5 23 -3 DET -14 88 63 3 24 -2 MTL 8 87 65 3 25 -6 PHI -39 86 64 4 22 -4 OTT -26 83 51 5 27 -1 FLA 32 83 53 4 22 4 PHX -28 83 68 3 13 -1 TOR 5 82 65 2 12 3 BOS -24 73 54 3 13 3 EDM 10 73 59 7 14 -7 COL -26 59 53 -0 13 -6 ATL -12 57 45 1 11 1 CAR -16 56 39 2 12 2 ANA -28 51 39 2 13 -2 NYI -34 51 33 2 19 -3

The Devils repeated as the NHL‟s top defensive team (MGD of 142, up 8) in 2011 based on a number two rank for even handed defense (MGDEH of 98) and a league leading penalty avoidance record (MGDTR of 14). Their league lowest total of short handed situations (241) was worth about 6 points in the standings.

Ordinarily such a ranking would result in a playoff spot, but not for the Devils in 2011. All this hard work was undermined (necessitated?) by awful offense and gloomy goaltending.

It was a season of big swings in defense. The biggest gain in MGD came from the Florida Panthers. Over very many years Florida has been a chronically appalling defensive team. My thesis has been that (a) someone thinks that offense sells better near the beach, (b) goaltending has been generally good so “let‟s run and gun” and (c) the team is badly managed and/or coached. But the 2011 version was up +32 to 83 MGD (yet still ranked just 21st). A good part of this gain was on the PK where they had 84.6% success. There was no change in coaching but a new GM (Dale Tallon) was in place.

The leaderboard was dominated by teams getting better. Dallas had a big gain of 30 MGD. San Jose bounced back in 2011 – MGD was up 24 after falling 39 in 2010. Calgary and Tampa Bay were both up 24 MGD. Was this necessitated by inferior goaltending?

The Lightning led in short handed (MGDSH of 43) defense. Tampa‟s penalty killing percentage of 83.8% was bettered by seven teams but all had much better goaltending. The PK% leaders were Pittsburgh (86.1%), Vancouver (85.6%), Washington (85.6%) and Los Angeles (85.5%). When you disaggregate the results into defense and goaltending, Vancouver slides backwards in your assessment of short handed defense (MGDSH of 23) and the other three remain nearly deadlocked.

From my 2010 Report:

“The biggest defensive gains in 2011 were in Philadelphia where the Flyers improved by 36 to 125 MGD in spite of league worst penalty discipline (MGDSHO of -8). They lead in even handed defense (MGDEH of 95) and were tied with Ottawa as the second best team on the penalty kill – MGDSHK of 36.”

In 2011 the Flyers had the largest reduction in defense, where MGD was off 39 to 86. Penalty killing became ordinary. Even handed defense became sub-standard. Mean reversion? In the 2011 off season GM Paul Holmgren decided to blow up his offense (shipping out Mike Richards and Jeff Carter in blockbuster deals) to allow him to upgrade goaltending (he signed Bryzgalov) that was actually better than passable.

In what looks like more mean reversion the Blackhawks were off 23 to 100 MGD.

Anaheim continued to slip defensively. The Ducks MGD was off 28 to rank 29th in 2011, after having dropped 26 MGD the prior season. This team was very fortunate to make the playoffs and then disappeared fast.

The Avalanche continued to slide. Colorado‟s MGD dropped by 26 after falling 30 in 2010.

Detroit‟s defense deteriorated for the third straight season (MGD down 14 in 2011, 16 in 2010 and 29 in 2009) and is now ranked as below average. Yet Lidstrom won another Norris Trophy.

Boston‟s defense was off 24 MGD. There is little doubt that greater confidence in goaltending leads to a more open approach to the game and, by implication, less defense.

“They” say that defense wins. New Jersey failed to win a playoff berth yet led the NHL in team defense. Anaheim was fourth seed in the West with the NHL‟s second worst defense. Boston won a Stanley Cup with a defense that was as productive as that of Edmonton (don‟t misunderstand my comment – the Bruins chose to invest skating energy in offense because of their goaltending).

In 2011, the correlation between defense and winning was weaker than I have seen it in some time. The correlation coefficient for points and MGD was just 35% (versus 69% for MGO and 39% for MGG).

Goaltending

Isolating shots and shot quality lets one better assess goaltending. The impact of goaltending is highest when a strong goalie allows „few‟ goals notwithstanding a high number of shots faced and / or shots of high quality.

Below is a table of the marginal goals from goaltending (MGG) by team (excluding the shootout which is discussed separately)10.

Although it is certainly possible, you won‟t normally find impactful goaltending behind a great defense. It just does not get the opportunity to shine. So it is not so surprising to see the low goaltending contribution in New Jersey, Tampa Bay, Los Angeles and Calgary. This does not mean that goaltending for these teams is necessarily weak (it was in some cases), just that it did not contribute much to overall team success.

For each of the last three seasons Florida has topped this list. That story was the confluence of (a) Tomas Vokoun and (b) really bad defense. But the champion has been dethroned and, after two years of ranking at number two, the Boston Bruins ascended to the top of the 2011 goaltending rankings.

A season ago Tuuka Rask turned the Vezina incumbent into the NHL‟s top number two goalie, and the hockey world wrote Tim Thomas off. I have always been a very big fan of Thomas. But one of the safest bets anywhere is that old guys who have career years

10 This season I changed my MGG/MGD algorithm to „disallow‟ negative MGG. In prior years I had permitted this outcome but I have concluded that it probably results in the over-statement of defence on teams with sub-marginal goaltending.

Copyright Alan Ryder, 2011 Hockey Analytics www.HockeyAnalytics.com 2011 NHL Review Page 25 will swoon the following season. So … who saw an NHL record save percentage coming? Marginal Goals - Goaltending In 2010 “hockey people” concluded that goaltending was over-rated. This is what happens Team vs 2010 2011 when two teams with no-name goaltenders compete BOS 21 92 for the Stanley Cup. The 2011 Stanley Cup will go VAN 40 84 down in history as one of those goaltending years, ANA 33 71 of which there are many. It may surprise you that CAR 28 64 over 40% of all Conn Smythe Trophies have been NSH 26 64 won by goalies. You should not be surprised. MTL 0 62 NYR 8 56 In the past couple of years there has been a fair bit PHI 41 53 of discussion amongst hockey analysts of the PHX 0 52 possibility of „parity‟ (a narrow range of results) FLA -24 50 amongst NHL goaltenders. This is a very important PIT 23 48 conversation as a very narrow range implies low NYI 30 46 value added from goaltending. If parity is the case, WSH 9 42 then goaltender wages are high since parity would ATL -5 35 imply that goaltending assets are quite fungible CHI 2 35 (which implies lower wages). SJS -28 31 DET -20 29 The range of MGG results widened considerably in MIN 14 29 2011 – the best (BOS) to worst (TBL) span was 92 LAK -5 29 goals. In 2010 the spread was just 66 goals (hence TOR 9 27 the blooming parity talk). But this season looked OTT 10 27 more like normal (the span was 98 in 2009, 92 in BUF -34 26 2008, 104 in 2007 and 88 in 2006). DAL -17 23 EDM 3 22 If parity is the case, then PC‟s approach overstates STL -32 10 goaltending contribution as my approach is based COL -38 8 on the historical contribution of goaltending to team NJD -33 6 CGY -54 1 results. I continue to see little current evidence of CBJ -8 0 parity, but the reader should understand that the TBL -8 0 comparison of skater and goaltender contributions is still very challenging and subject to considerable error.

Elsewhere you might read something like:

“Recent statistical studies have suggested that the difference between average and top- level goaltending doesn’t have enough of an impact on the standings to justify breaking the bank for it. While high-priced talent like Roberto Luongo and Tim Thomas are an upgrade over the league-average goalies, spending the extra five or six million somewhere else instead will generally provide greater value overall.”

This is bollocks. The average NHL team spent (cap hit) about $5 million on goaltending in 2011. Boston spent $6.3 million and Vancouver spent $6.2 million. The issue is execution and, yes, there is much wastage. Calgary spent $6.3 million and Tampa Bay spent $4.5 million and both teams got nothing for it. The range of goaltender spending in 2010-11 was Anaheim ($8.7 million) to Chicago ($2.1 million, ignoring the Cristobal Huet buyout) – only a $6.6 million span.

The math on value is very simple. Over the course of a season an average NHL team allows about 2,500 shots on goal. The average NHL team sports a .913 save percentage. Exchange that for a .923 save percentage and you save 25 goals. That would get you about 9 points in the standings (or about 90 PC points). And that is worth around $5.3M in incremental goaltender salary (for a team targeting 100 points in the standings). We are not yet thinking about the elite goaltending in Boston (.932) or Vancouver (.928), merely the very good goaltending of, say, the Rangers or Canadiens. And we haven‟t considered the shootout yet (it ups the value of goaltending by about 10%).

The challenge is to spend the money wisely. Contracts are for future performance rather than for past performance. Paying up for a goalie that has had a limited amount of out-performance is just plain dumb and is the principal reason people want to feel that goaltenders are overpaid. And long term contracts are very risky business at any position. But acquiring credible out-performance is the smart move, in fact the essence of the job of the GM. While mean reversion is a powerful force, individuals revert to their personal mean.

The other reason people want to feel that goaltending is over-rated is the sense that “all your eggs are in one basket”. If you spend a lot of money on a goaltender and he is injured or (worse) goes on vacation for a couple of weeks, then you have a big problem. The Bruins had this problem in April and very nearly drowned in the first round of the playoff pool. Luongo laid an egg in the final, while Thomas was unbeatable. “All your eggs” means risk. And, from that perspective, it is much easier to sign Evgeni Malkin to a really big contract than Marc-Andre Fleury.

But the reality is that hockey teams are simply highly „levered‟ in goal. Even a stingy defense leaves a goaltender with much work to do. Small variations in goaltending are amplified to large results. Henrik Sedin can have an off night, but not Roberto Luongo. Daniel Sedin can have an off season, but it will attract less attention than a crisis of confidence in the crease. Are goaltenders any less consistent than skaters? I don‟t think so. But the leverage means that it frequently feels like netminders are less consistent.

Biggest Improvements in Goaltending in 2011

Philadelphia (+41 MGG)

The most improved goaltending in the NHL in 2011 was in the City of Brotherly Love. It improved so much over a very messy 2010 (-37 MGG versus 2009) … that the Flyers decided to clean house in the off season.

In 2009 Martin Biron carried the bulk of the load (with a .915 save percentage) and Antero Niittymaki provided very solid relief (.912). This was a serviceable performance but both goalies were gone in 2010 in favour of a bet on Sugar Ray Emery that did not go according to plan. Feeling vulnerable in net, the Flyers acquired Michael Leighton from Carolina to serve as the backup. When Emery went down with an injury, Leighton was pressed into service with better results (save percentage of .918 versus .905 for Emery). Things were looking up until Leighton went down and Brian Boucher was suddenly the main man. By the end of the season these three had split the goaltending duties nearly equally but Boucher ended up with the most minutes (1,742) and the worst save percentage (.899), which is a deadly combination.

Boucher was back in 2011 (Emery and Leighton shuffled off into the sunset) with a considerably stronger game (.916 save percentage) in slightly more playing time (1,885 minutes). The main load was carried by Sergei Bobrovsky (3,017 minutes), who posted a solid .915 save percentage.

Apparently this was not good enough. For 2012 the deck chairs have been rearranged again as the Flyers hope that Bryzgalov can carry over his spiffy 2011 save percentage (.921) from the Desert Dogs (his career average is .916). While the goaltending situation is probably stabilized at a higher than historic level, the cost was high and the 2011 goaltending results may turn out to be challenging to improve upon. By the way – Bobrovsky, Boucher and Bryzgaolav each had a Neutral Save Percentage (NSV)11 of around .920 in 2011.

Vancouver (+40)

In 2010 Roberto Luongo posted his worst save percentage (.913) since his rookie year. Mean reversion looked like a good bet and in 2011 he recorded his second best career result (.928). Of course, he will be remembered best as the losing goaltender in the Stanley Cup (which he did with considerable style). But don‟t miss the side story of Cory Schneider. He delivered a .929 save percentage in 1,372 minutes, a very large upgrade from the Andrew Raycroft backup performance (.911) in 2010 and worth over 100 PC points.

What do Boston and Vancouver have in common? The deepest goaltending in the NHL. What is so bad about that? It is hard to hold it together. Schneider and Tuuka Rask are both restricted free agents in 2012. Both want to play. They both look like they will need a pay hike that would be inconsistent with backup roles. In Vancouver I think this plays out with ~25 starts for Schneider in 2012.

It is unlikely that the Canucks get as much out of goaltending in 2012.

11 Neutral Save Percentage is a goaltender‟s save percentage adjusted to reflect variation in team shot quality and scorer bias in shot counts.

Anaheim (+33)

The Ducks used five goaltenders in 2011 but Jonas Hiller was again the main man in the crease and most of the improvement story. His save percentage was up (.924 vs .918 in 2010) but his minutes were down (2,672 vs 3,338) due to struggles with vertigo. Peeling away the layers of the onion shows that he was actually much more valuable in 2011 despite reduced playing time. His NSV went from .914 in 2010 to .932 in 2011, reflecting much tougher working conditions.

But about one third of the overall improvement came from others. In 2010 J-S Giguere (.900 save percentage) and Curtis McElhinney (.917) logged 1,109 and 522 minutes respectively. McElhinney was back with a nearly doubled workload but his save percentage (raw: .890, NSV: .902) did not inspire and the revolving door commenced. Sugar Ray Emery (527 minutes) and Dan Ellis (729) were brought in to salvage the situation (McElhinney and Ellis were swapped in a trade). They delivered .926 and .917 save percentages respectively to account for the uptick in the overall quality of backup goaltending.

Hiller and Ellis return for 2012. I doubt that these players individually can match their 2011 performances, but the once mighty Ducks shouldn‟t have to carry the McElhinney baggage this season and I would expect them to sustain this level of goaltending overall in 2012.

New York Islanders (+30)

I guess the Islanders had to have an uptick in goaltending someday. The Rick DePietro related decisions, the trade of Roberto Luongo and the lifetime employment contract, both turn out to be very bad moves. His situation has hampered strategic decision making for some time.

In 2010 Dwayne Roloson was the main man with 2,897 minutes in 50 games and a .907 save percentage. Martin Biron (.896 in 1,634 minutes) and DiPietro (.900 in 462 minutes) filled out the twine minding time. Collectively this group delivered just 16 marginal goals, which is not very good.

Last season Roloson upped his game (.916), earning a mid-season trade to the goaltending starved but otherwise capable Tampa Bay Lightning. The trade meant, of course, that his contribution to the Islanders was limited (he played 1,206 minutes). DiPietro continued to suck (.886) but was in better health and, with the hope that the lifetime contract could yet prove to be of value, had more time in the net (1,533 minutes). If you put these two performances together you quickly see that they don‟t add up to anything more than they contributed in 2010. The difference mainly came from upgrading the Biron performance to that of Al Montoya (.921 in 1,154 minutes) and Kevin Poulin (.924 in 491 minutes).

DiPietro is, of course, back for 2012. So is Montoya. New is a recycled Evgeni Nabakov. I don‟t see this group delivering the same kind of goaltending that we saw in 2011.

Carolina (+28)

The Hurricanes have been swirling in the wake of Cam Ward‟s playing time. The former Conn Smyth Trophy winner spent some time getting his legs underneath him before turning in a save percentage of .916 in 2009 (and Carolina was +47 MGG). Last season he delivered the same kind of result but injuries held him to just 2,651 minutes in 47 games (versus 3,928 in 68 games in 2009) and MGG was off by 23. In 2011 Ward led the NHL in minutes played (4,318), and upped his save percentage to .923, to fuel the 28 MGG turnaround. One of the reasons Ward played so much is that Justin Peters stunk (.875 save percentage vs .905 in the prior year). And this undermined the gains that Ward delivered.

In 2012 Carolina will again sink or swim with Cam Ward‟s performance and health.

Nashville (+26)

The story was pretty simple with the Predators – Pekka Rinne was terrific, sporting a .930 save percentage in 3,789 minutes. His save percentage was way up from 2010 (.911) and this kind of performance moved his playing time up as well (from 3,246 minutes in 2010). The real Rinne is probably in between (and .930 is a lofty performance) so we can expect some regression in 2012. Backup Anders Lindback chipped in a nice .915 save percentage (in 1,131 minutes) which was an improvement of the work of Dan Ellis (.909 in 1,715 minutes in 2010) and may also be hard to sustain.

Biggest Deteriorations in Goaltending in 2011

St. Louis (-32)

The real story in St. Louis was not the replacement of Chris Mason (.913 in 3,512 minutes) with Jaroslav Halak (.910 in 3,294). That competition was nearly a draw. No the tale to follow was that of Ty Conklin. As the principal backup (1,451 minutes) in 2010 he sported a sizzling save percentage of .921. In 2011he simply sucked (.881 in 1,285 minutes).

Depth matters. The outlook is for improved backup goaltending in 2012 (although Brian Elliott‟s career save percentage is just .901).

New Jersey (-33)

While I have been letting some air out of the Brodeur balloon for years, I cannot deny that the future hall of famer has been a material asset to the New Jersey Devils. But it had to happen sometime. And it did. The Brodeur run is probably over. After posting a solid .916 save percentage (in 4,499 minutes) 2010, Brodeur slumped to .903 in 2011. As one might expect, the playing time declined with the performance (3,116 minutes). The good news for the Devils was the work of Johan Hedberg who delivered a respectable .912 save percentage in 1,717 minutes. The bad news was that this performance was off from that of Yann Denis (.923) in 2010 (in just 467 minutes).

I have to say that 2012 does not look good for the Devils. Although he has cleared a .910 save percentage in each of his last two seasons, Hedberg‟s history suggests that he is a marginal NHL goaltender. And Brodeur may now be as well.

Buffalo (-34)

The Sabres were +27 MGG in 2010 on the strength of a very hot hand. Ryan Miller delivered 4,047 minutes (in 69 games) of high quality goaltending – a stellar .929 save percentage (.924 NSV) and a Vezina Trophy. This was the second consecutive jump in performance from Miller, who posted a .918 save percentage in 2010, up from .906 in 2008. However, .929 is a save percentage that can be sustained by very few (any?) goaltenders and, for 2011, mean reversion kicked in - .916 in 3,829 minutes. This was not quite the whole story. Backup goaltending in 2010 was largely comprised of Patrick Lalime (.907 in 854 minutes). In 2011, Jhonas Enroth got more number-two minutes (769) and matched Lalime‟s save percentage from the prior year. But Lalime also got some playing time (365 minutes) and disappointed (.890).

Colorado (-38)

In Colorado the loss of Jose Theodore‟s 2008 performance (.910 save percentage) was the root cause of a 34 MGG slump in 2009. But Avalanche goaltending bounced back in a big way in 2010 (+44 MGG) with the arrival of Craig Anderson (71 games, 4,235 minutes, .917 save percentage). The problem with 2011 was that Anderson lost the handle and his save percentage slumped badly to .897. This kind of thing trims your playing time (1,810 minutes) and, in this case, resulted in exile to Ottawa in a mid season trade (where the sizzle returned to his play).

Peter Budaj ended up carrying the bulk of the load (2,439 minutes in 47 games) but, with a save percentage of .895, was no better than Anderson. His performance was well off his 2010 pace (.917) but consistent with a profile (.899 save percentage in 3,232 minutes) that resulted in the Anderson acquisition. Brian Elliott, acquired in the Ottawa trade was also uninspiring (.891 in 690 minutes).

Could Colorado goaltending get worse in 2012? Probably not. It might even get a lot better. The Avalanche completely cleaned house, acquiring Semyon Varlamov from Washington to be the main man in the blue paint (2011: .924 in 1,560 minutes, 2010: .909 in 1,527). He figures to get a lot of ice time as his back up is the very long in the tooth J-S Giguere (2011: .900 in 1,633 minutes).

Calgary (-54)

In Calgary, the steady erosion of Miikka Kiprusoff‟s play seems to be confirmed. He went from a save percentage of .923 in 2006 to .917 in 2007 to .906 in 2008 to .903 in 2009. In 2010 we saw the second coming of Kipper (.920 in 4,235 minutes), but 2011 was a return to the trend line (.906 in 4,156 minutes). A 14 point erosion in save percentage is a big swing for a goalie with all those minutes (third in the NHL behind Cam Ward and Carey Price). But digging deeper reveals that the story was actually

Copyright Alan Ryder, 2011 Hockey Analytics www.HockeyAnalytics.com 2011 NHL Review Page 31 nearly twice as bad – a reduction in NSVfrom .923 to .898. You see, the Flames were a different defensive team in 2011 with a much improved shot quality profile.

The Sad Senator Saga

There was not much change in Ottawa (+10) including change itself. But it is sure is fun to continue to follow the bouncing puck:

Where should I start? How about … Martin Gerber was acquired for the 2007 season to succeed Domenic Hasek who was acquired to lead the Senators out of goaltending purgatory to the Promised Land (the story is much too long to start with, say, Patrick Lalime). The problem with Gerber was that he got off to a rough start. Ray Emery surprised and won the starting job.

The 2008 season opened with the Senators seeking to trade Gerber but an injury to Emery made Gerber the go-to guy in the early season. He was white hot so Sugar Ray sat for a while and began to pout. He got his chance as Gerber cooled considerably, but his performance was not compelling and he returned to the bench (and to pouting).

Emery‟s behavior got him sent to Siberia (no, not Tampa Bay) for 2009. Enter, stage right, Alex Auld, who posted a respectable .911 save percentage, and, stage left, Brian Elliott, (.902). At the 2009 trade deadline Pascal Leclaire, who was injured at the time, was acquired and penciled in as the saviour.

But in 2010 Leclaire played poorly (.887) and Elliott was so much better (.909) that he got the lion‟s share of the playing time (3,038 minutes).

In an unusual fit of patience, both goalies were back in 2011. Elliott (.894 in 2,293 minutes) was the great failed hope. Leclaire was a better (.908) but was hampered by injuries for most of the season and could only deliver 763 minutes. The Senators used 4(!) other goalies in 2011. Mike Brodeur (.833) got in just a few minutes over four games. Robin Lehner (341 minutes) failed to deliver (.888). The much travelled Curtis McElhinney was picked up off the scrap heap (a waiver claim from Tampa Bay who had acquired him only for the purpose of dumping the Dan Ellis contract), but made a contribution (.917 save percentage in 399 minutes).

And then the latest savior was installed. Craig Anderson, who was struggling (.897) with the altitude in Colorado, was acquired and sizzled (.939) for the rest of the season (1,055 minutes). The difference was noticeable if not repeatable.

The Shootout

My method for assessing shootout performance for goaltenders is the same as for skating time. To get marginal shootout goals saved (MGGSO) I compare save percentages to a

Copyright Alan Ryder, 2011 Hockey Analytics www.HockeyAnalytics.com 2011 NHL Review Page 32 threshold and then multiply the difference by the number of attempts faced. For skaters I use the same kind of logic to derive MGOSO 12.

Below is some data from the shootout from its inception.

Shootout Statistics

Statistic 2006 2007 2008 2009 2010 2011 All Shootouts 145 164 156 159 184 149 957 Attempts 981 1215 1057 1059 1398 1059 6769 Goals 330 398 344 357 449 324 2202 Attempts per Shootout 6.77 7.41 6.78 6.66 7.60 7.11 7.07 Goals per Shootout 2.28 2.43 2.21 2.25 2.44 2.17 2.30 Shooting Percentage .336 .328 .325 .337 .321 .306 .325 Shooting Threshold .131 .141 .202 .202 .148 .212 Save Threshold .533 .531 .472 .461 .531 .483 Goalie Attribution .390 .431 .621 .599 .461 .691

Other than in 2010 the number of shootouts has been relatively stable (this is a function of what is going on during the previous 65 minutes of „skating time‟). There was some chatter a year ago about the increase in overtime ties and overtime games. It is probably nothing but random noise. .

In 2011 the average number of attempts per shootout was a bit above historical average and the number of goals per shootout was slightly below average. This means that the shooting percentage was below average (in fact the lowest in history). This is probably just variation, but I think that goaltending is more coachable than shooting and there could be a trend going on here.

The shooting and save thresholds I have used in my calculations are also shown. The driver of this is the final statistic – „goalie attribution‟. Goalie attribution is a measure of the relative team-to-team variation in shooting percentages and save percentages. Zero team-to-team variation in save percentages would imply that shootout success was determined 100% by the shooters. Likewise zero team-to-team variation in shooting percentages would imply that shootout success was determined 100% by the goaltenders. A higher variation in goaltending means that goaltending is relatively more valuable. In 2011 we observed the highest variation in team-to-team save versus shooting percentages in the brief history of the shootout and I attributed 69% of the shootout event to goalies.

Player Contribution is focused on measuring results rather than skill so I have been sticking with the inference of the data. But the observed fluctuation of the relative success of goaltenders and shooters is likely nothing more than randomness at work. If

12 For a full description of my method see http://www.HockeyAnalytics.com/Research_files/Shootout_at_the_Oval_Corral.pdf

Copyright Alan Ryder, 2011 Hockey Analytics www.HockeyAnalytics.com 2011 NHL Review Page 33 you study the team-to-team variations over all six shootout seasons you get a goalie attribution slightly above 50%. That could be the right factor but we won‟t really know for a long time.

Below is a summary, by team, of the shootout in 2011 – shootout wins and marginal goals from offense and goaltending.

So far as I can tell the shootout is a lottery of two dimensions – opportunities and success. In 2009 Phoenix went 3-3 in the shootout. In Marginal Goals - Shootout 2010 nearly one game of four Coyote games was decided by a shootout and they went 14- Team SW MGOSO MGGSO 6 (very reminiscent of the 2008 Oilers who ANA 4 1 9 went 15-4). But in 2011 … 5-6. ATL 5 3 8 BOS 2 1 1 In 2011 the Calgary Flames had the most BUF 5 7 5 chances (16) while the Devils had the fewest CAR 5 2 6 CBJ 5 3 8 (5). Both teams were quite ordinary (9-7 and CGY 9 8 10 2-3 respectively). CHI 6 4 7 COL 6 2 12 Los Angeles and Pittsburgh led the NHL in DAL 5 6 5 shootout wins (10). The Kings were slightly DET 4 1 9 better (10-2) than the Penguins (10-3), but EDM 2 -2 6 both had 24 marginal goals. FLA 4 1 5 LAK 10 10 14 SO MIN 3 5 2 LA logged the most MGO (10) in the MTL 3 1 7 league on the back of Jarret Stoll‟s 9 goals in NJD 3 2 5 10 attempts. Tied for second were Calgary NSH 6 2 11 and St. Louis. The Flames trotted out Alex NYI 4 4 4 Tanguay in each shootout and he certainly NYR 9 5 18 delivered (10 goals). OTT 2 -2 3 PHI 3 3 2 This is the second year in a row that PHX 5 5 6 PIT 10 6 18 Pittsburgh had an exceptional shootout SJS 5 3 9 record. The thread was a repeat of the STL 4 8 3 NHL‟s (team) best shootout save percentage. TBL 6 0 15 Save percentages are much more credible TOR 5 4 5 than shooting percentages (much more data). VAN 4 4 3 Fleury might just be the best one-on-one WSH 5 3 7 goaltender in the NHL.

Only team to better the Penguins in goal was Colorado (.926 – 25 saves in 27 attempts).

The Rangers went 9-3 in the shootout, tying the Penguins for the most MGGSO (18) on the basis of Henrik Lunqvist‟s slightly-better-than-Fleury shootout save percentage (.848). Actually, Lundqvist leads the NHL in career shootout wins. So maybe he is the NHL‟s best one-on-one goalie …

Edmonton suffered the NHL‟s worst shootout record (2-9). Goaltending was weak (.634 save percentage) but the shooting was worse (.174).

Ottawa was the only team with a worse shooting record (.136) than Edmonton while Buffalo and St. Louis had the hottest hands (.462 and .421 respectively). Several teams were weaker than the Oilers in goal. The Wild were the worst (only 17 saves in 32 attempts). For the record, the Bruins were among the weakest in goal (13 saves in 24 attempts). Thomas is not a strong one-on-one goaltender.

While the shootout looks like a lottery, ignoring it is dangerous math. Over 10% of NHL games get resolved in this contest. That means that a goal scored or prevented after skating time in nearly as valuable as an earlier event. Think twice about Alex Tanguay‟s 10 shootout goals.

Top Individual Performances

Hart Trophy

The Hart Memorial Trophy is awarded to the player judged to be “the most valuable to his team”. The Ted Lindsay Award goes to the NHL‟s “Most Outstanding Player” as selected by fellow members of the NHLPA.

This year‟s “finalists” (the top three vote getters) for the Hart Trophy were Corey Perry (Anaheim), Daniel Sedin (Vancouver) and Martin St. Louis (Tampa Bay). The players put Perry, Sedin and Steve Stamkos (Tampa Bay) on the final ballot.

Although a literal read of “most valuable player to his team” means that a goaltender must win this prize each year, the award has typically (nearly 90% of the time) been presented to the NHL‟s most impactful skater, as judged by the voters. In fact the Hart Trophy has usually gone to a forward (about 80% of all Hart Trophies) and, especially, the points scoring leader (about 50% of the time). The players have shown an even greater bias towards forwards in their voting for the Lindsay award for the “most outstanding” player.

So it is not surprising that Daniel Sedin and Corey Perry topped the balloting for the Hart Trophy Voting Hart Trophy. Voting results (points) for Player Team Points the Hart Trophy are shown to the right, Corey Perry ANA 1,043 showing that it was a tight, two way race. Henrik Sedin VAN 960 Perry was the top choice on 67 ballots Martin St. Louis TBL 332 while Sedin topped 51 ballots. For the Pekka Rinne NSH 175 th record, Stamkos was a very distant 11 in Tim Thomas BOS 171 the Hart voting. Jonathan Toews CHI 107

Forwards

Here is the headline case for each of the Hart/Lindsay „finalists‟:

 Perry was the NHL‟s only 50 goal scorer, earning the Maurice Richard Trophy. He got very hot in the last half of the season and carried the Ducks on his back to a playoff spot.  Sedin was the NHL‟s leading point scorer (104 points), earning the Art Ross Trophy. Brother Henrik was the Hart Trophy winner in 2010, bringing some brand to the family name. Did this unprecedented story of twins at the top of a professional sport encourage voters to select the bookends as MVPs in successive seasons?  St. Louis was, in a quiet way, the runner up for the Art Ross (with 99 points), a former Hart Trophy winner and the setup man for teammate Stamkos.

 Stamkos might be the NHL‟s best trigger man. He was second to only Perry in goals, having shared the Maurice Richard Trophy in the prior season with Sidney Crosby.

My analysis says that Jonathon Toews was a nose better than Martin St. Louis, earning my Wayne Gretzky Award as top forward. Wayne Gretzky Award The analysis also says that Sedin and Top Forward Stamkos were well off the pace, neither being the most valuable forwards on their Player Team PC teams. The leading PC scores for forwards Jonathan Toews CHI 116 are shown to the right. Martin St. Louis TBL 115 Alex Ovechkin WSH 103 The lens of Player Contribution enables us Ryan Kesler VAN 103 Corey Perry ANA 99 to break down these performances and Loui Eriksson DAL 99 determine who was the NHL‟s most Thomas Vanek BUF 95 valuable forward, and why. Shown on the Alex Tanguay CGY 93 next page are the details of the PC Claude Giroux PHI 92 calculation for the top 30 forwards. Anze Kopitar LAK 90 Jarome Iginla CGY 89 Let‟s start with shooting fish in a barrel. Daniel Sedin VAN 86 Daniel Sedin led all NHL forwards with 33 Steven Stamkos TBL 86 PCO on the power play based on a league leading 18 goals and 42 points in 296 minutes. St. Louis was just off his point pace (with 41) but got there mainly as the setup man (37 assists) and occupied 370 minutes of ice time getting there. PC digests this and awards 27 PCOPP. His PP partner, Steve Stamkos, had 373 minutes (tops amongst forwards), 17 goals, 19 assists and 29 PCOPP. This PC score is a bit higher than that of St. Louis because of the vast difference in goals (notwithstanding the fact that PC sees the power play as a team effort). Ryan Kesler (28 PCOPP) and Corey Perry (26) were in the same zone.

A notably weak performance with the man advantage came from Alex Ovechkin. He collected 7 goals and 17 assists in 354 minutes. This power play result explains a great deal of Ovechkin‟s drop in goal scoring and PC was not so impressed by this result (11 PCOPP).

But the Alexander the Great was one of the league‟s top even handed weapons. His 61 points (25 goals and 36 assists in 1,330 minutes) was bettered by Corey Perry (32, 30) however the Anaheim winger had more ice time (1,407 minutes) than any other forward (save for Ilya Kovalchuk). PC synthesizes this (and some other factors) and awards 58 PCOEH to each of Ovechkin, Perry and Stamkos (28 goals, 27 assists, 1,256 minutes). St. Louis is not far off the even handed pace with 55 PCOEH (27 goals, 31assists, 1,312 minutes).

2011 Player Contribution – Forwards (items may not total due to rounding)

PCO PCD Player Team POS PC EH PP SH TR SO PCO EH PP SH TR PCD Jonathan Toews CHI C 116 39 17 1 13 15 86 12 0 7 11 30 Martin St. Louis TBL R 115 55 27 -1 1 0 82 17 -3 2 17 33 Alex Ovechkin WSH L 103 58 11 0 4 9 82 18 2 0 2 21 Ryan Kesler VAN C 103 35 28 5 14 2 84 11 1 6 1 20 Corey Perry ANA R 99 58 26 10 4 -1 97 5 0 2 -5 2 Loui Eriksson DAL L 99 35 19 3 -1 0 56 18 0 8 16 43 Thomas Vanek BUF R 95 43 21 0 2 16 82 8 -1 -1 6 12 Alex Tanguay CGY L 93 38 8 -1 -2 32 75 8 0 2 7 18 Claude Giroux PHI R 92 41 12 11 7 1 72 9 1 7 4 20 Anze Kopitar LAK C 90 40 7 0 3 4 54 17 1 8 10 36 Jarome Iginla CGY R 89 50 18 0 1 -1 68 12 0 1 8 21 Daniel Sedin VAN L 86 50 33 0 -9 0 73 11 1 1 1 13 Steven Stamkos TBL C 86 58 29 0 3 -6 83 17 -3 2 -14 3 Pavel Datsyuk DET C 84 39 13 1 6 5 64 8 0 2 10 20 Brad Richards DAL C 82 39 16 0 -7 11 58 15 -1 -1 12 25 Bobby Ryan ANA R 81 57 6 1 4 5 73 6 0 2 -1 7 Sidney Crosby PIT C 80 47 13 2 8 1 71 5 0 1 2 9 Jarret Stoll LAK C 80 15 6 4 6 29 59 10 1 7 3 20 Rick Nash CBJ L 79 51 5 0 2 11 68 12 0 -4 2 10 Jeff Carter PHI C 78 52 10 -1 -1 -3 58 13 1 3 4 20 Michael Grabner NYI R 78 41 3 15 2 0 61 6 0 6 6 17 Logan Couture SJS C 76 36 12 -1 2 1 51 19 1 4 2 26 Joe Thornton SJS C 76 19 27 4 3 0 52 11 1 6 6 24 Mike Ribeiro DAL C 76 33 14 -1 -3 17 61 12 0 -3 6 15 Jeff Skinner CAR C 75 41 7 0 12 12 72 5 0 0 -2 3 Joe Pavelski SJS C 75 18 25 3 6 0 53 13 0 1 8 22 Patrick Marleau SJS L 74 36 22 4 -6 -3 54 9 0 0 11 20 Dustin Brown LAK R 74 36 7 -1 10 2 54 17 1 8 -5 20 Danny Briere PHI C 74 53 9 0 4 7 73 10 0 0 -10 0 Patrick Kane CHI R 71 42 13 0 0 5 60 8 1 0 3 11

There is much analysis yet to do. But the headline stuff is behind us and the PC scoreboard looks like this: Stamkos (87), Perry (84), Sedin (83) and St. Louis (82). Note that Sedin is about to fade badly from this race

A surge of shorthanded offense (4 goals, 1 assist), worth 10 PCOSH, pushed Perry into the lead. While short handed, nearly any offense is a bonus and Perry‟s 135 minutes of ice time is therefore lightly taxed by PC. Nevertheless it was no real contest as St. Louis (38 minutes), Stamkos (27) and Sedin (9) had little opportunity to compete. Perry is now up to 94 PC but, like Sedin, his engine is about to stall.

Offensive transitions are mainly about penalty drawing. But the other transition things add up slowly for those that can do them well. Now comes the stories of Ryan Kesler and Jonathan Toews who, at this stage, are well off the PC pace with 73 and 57 points respectively.

The leading offensive transition scores in 2011 belonged to Kelser and Manny Malhotra (14 PCOTR) of the Canucks. Both carried the very heavy load of pushing the puck up the ice so that the Sedin line could gain the glory. Consider this data:

EH Zone Starts Faceoffs Player Off Def Ratio Won Lost Ratio Henrik Sedin 569 228 71.4% 721 666 52.0% Ryan Kesler 394 394 50.0% 859 637 57.4% Manny Malhotra 155 466 25.0% 778 483 61.7%

This is a stark picture of offensive opportunity (and defensive load). Malhotra was routinely trotted out to move the puck up the ice while the Sedins were given the opportunity to finish. And Malhotra did the job, gaining possession in the faceoff circle 62% of the time.

Kesler‟s positioning was clearly in between that of Malhotra and Henrik Sedin. He added to his PCOTR by being +44 on turnovers (versus +22 for Malhotra and +5 for Sedin). In addition he drew 37 minor penalties (versus 16 for Malhotra and 14 for Sedin). There is more complexity to this analysis, but the picture is pretty clear.

With the ice already tilted in his favour, Daniel Sedin went -9 on his transition game (-14 in turnovers and 14 drawn penalties).

The Toews transition tale is like that of Kesler. He was the go-to face off man, winning 57% (221 extra possessions), +63 on turnovers and drew 32 penalties.

And his story continued into the shootout where he scored 11 times in 16 tries for 15 PCOSO. This turned out to be the performance that won Toews the Gretzky Award, but everyone missed it because the shootout is routinely ignored. Ovechkin helped himself in the shootout (4 goals in 10 tries) and Thomas Vanek crept up the leaderboard with a 5 for 6 result in the shootout. Stamkos hurt himself going 0 for 7.

The aggregate PCO leaders came in with Perry setting the pace at 97. Behind him was the field: Toews 86, Kesler 84, Stamkos 83, Ovechkin 82, St. Louis 82 and Thomas Vanek (82). Daniel Sedin‟s awful transition story set him back badly and his PCO score (73) was well off the pace.

Where Perry ruined his profile was on defense. He had the worst even handed goals against average (2.94) of any of the contenders on a team that had quite good goaltending. His penalty killing was weak (8.00 GAA), unwinding his short handed scoring contribution. And he took too many penalties (37). Overall he was a nearly marginal defensive forward (2 PCD).

I assessed Tampa Bay‟s defense as the fifth best in the NHL. They were tops in shot quality and ranked 7th in shots allowed (a more important factor). This team performance came from the individual players, so Lightning players have strong PCD scores in 2011.

Stamkos and St. Louis were glued together for the 2011 season. Under these circumstances PC has a hard time differentiating performance and comes to the conclusion that their defensive contributions (nearly) match.

While even handed Stamkos and St. Louis were no better than their teammates. But they had a ton of ice time (St. Louis ranked 6th amongst NHL forwards in even handed ice time and Stamkos was ranked #13) and therefore earn a ton of the credit. PC declared St. Louis and Stamkos to be two of the top even handed forwards in the NHL.

Both players dissipated what little credit they received on the penalty kill with poor power play defense (yes, there is such a thing).

And then they diverged radically.

Martin St. Louis keeps his nose cleaner than just about any player in the NHL. He took just 6 minor penalties in 2011. Steve Stamkos, on the other hand, was assessed with 32 minor penalties. As a rough rule of thumb, a minor penalty is worth about one quarter of a goal (in both goals allowed and lost offense). The 26 penalty difference therefore roughs out to 6.5 goals or about 25 PC points. Tampa was a little more efficient at translating goals into points and this stretches out the penalty impact a bit. Tampa‟s weak goaltending also serves to amplify the difference and the two players end up a whopping 29 PC points apart.

So Stamkos undisciplined play meant that his PCD score comes in at just 3. And that took him out of the running.

Meanwhile St. Louis turned in a gleaming PCD score of 33 to set the PC bar at 115 for forwards.

Ovechkin had a leap for the bar with a PCDEH score of 18. But his 18 minor penalties were too much to baggage to carry. Kesler had a similar PCD score, helped by 210 minutes of penalty killing time. But his even handed defense was worse than that of Ovechkin and his penalty profile was about the same.

In the end Toews cleared the bar by an inch with a PCD score of 30 based on a defensive profile much like that of Kesler but with fewer penalties. The Gretzky Award winning profile: outstanding two way player with special shootout skills.

Player Contribution considers a lot of factors. I am not confident that its deals so well with quality of teammates or competition. So let‟s examine the colour on that matter:

 Toews had a revolving door of solid teammates that included Patrick Kane (71 PC, 73 GP), Patrick Sharp (58, 74) and Marian Hossa (50, 65). Ovechkin spent a great deal of time with Nicklas Backstom (68, 77). While even

handed, St. Louis and Stamkos played together about 90% of the time. Corey Perry had Ryan Getzlaf (47, 67) about 95% of the time. It was closer to 100% of the time for the Sedin twins (Henrik was good for 66 PC in 82 games). Kelser was less fortunate. Overall Perry and Kesler probably had the lowest quality of teammates while St. Louis and Stamkos were most advantaged.

 Kelser had tougher assignments than did Sedin, but neither faced very stiff competition due to Vancouver‟s light divisional schedule. Stamkos and St. Louis (again) had nearly matching competition profiles. Ovechkin played in the same division. The three of them had middling competition. But Toews and Perry seemed to have the toughest assignments of those players on the leaderboard.

The colour suggests that Toews widens the gap over St. Louis. Hart Trophy voters had him ranked fourth amongst forwards.

Hart voters completely missed the performance of Loui Erikson. PC has liked him for years and, in 2011, ranked him with Corey Perry. He impressed PC with his defense (more on that below) which, of course, hockey journalists have no way to assess (but now you do). His name was not on a single Hart ballot and was ranked 7th in all-star voting at left wing.

Thomas Vanek was also completely ignored but, as I pointed out above, was about as impactful offensively as any player not named Corey Perry. He was ranked 7th in all-star voting at left wing and was also not on a single Hart ballot. His secret weapon was the shootout, which voters fail to value.

Alex Tanguay had the same secret weapon (more on his exceptional PCOSO below).

Let me close by remarking on the performance of Sidney Crosby who ranked 17th amongst forwards in PC. The fact that he missed exactly half the season, with concussion problems, makes it easy for us to extrapolate his PC line to a full season. Below I have compared his PC line to that of Ovechkin‟s 2008 season, which will be remembered as one of the finest in history.

PCO PCD Player Season PC EH PP SH TR SO PCO EH PP SH TR PCD Sidney Crosby Full 2011 160 94 27 3 16 1 142 11 1 3 4 19 Alexander Ovechkin Actual 2008 162 95 36 8 0 -1 138 13 1 1 9 24

Defensive Forwards

The Frank Selke trophy goes to the best defensive forward in the NHL. Having no metric for defense on which to rely, the voters rarely get this right. Reputations tend to rule. The three finalists for this trophy were the leaders from recent votes, Pavel Datsyuk (the imcumbent) and Ryan Kesler, and Jonathon Toews. Kesler won his first Selke Trophy in a landslide, being the top name on 105 of 124 ballots.

My Bob Gainey Award winner, for the top defensive contribution by a forward, was Bob Gainey Award Travis Zajac of the Devils, who was named Top Defensive Forward on just two ballots and finished 25th in the th Selke voting. I had him ranked 5 in 2010. Player Team PCD Travis Zajac NJD 47 Of the finalists PC had Toews ranked the Loui Eriksson DAL 43 best. Datsyuk and Kesler were deep and Adam Hall TBL 39 both were ranked third best on their teams. Dana Tyrell TBL 38 Voters might be adding what I call PCOTR Samuel Pahlsson CBJ 38 to defense (I doubt it because they can‟t Nate Thompson TBL 37 evaluate it), in which case Kesler‟s stature rises considerably. But I would still have him ranked behind teammate Malholtra.

Below are the details for the PCD calculation for the top defensive forwards in 2011.

This list may surprise many people, so I should start with a quick review of the component parts. PCDEH is even handed defensive contribution. While even handed, forwards have a lesser defensive role. So this part of the game may not be as valuable as short handed defense (PCDSH), where forwards are much more thoroughly engaged in goal prevention even though much less playing time is involved. If you are 2011 Player Contribution not asked to kill penalties, PCD for Forwards you can‟t contribute. If you do kill a lot of penalties and Defense (PCD) do it well, that is a valuable Player Team POS EH PP SH TR PCD contribution. PCDPP Travis Zajac NJD C 16 0 12 19 47 (power play) is really only Loui Eriksson DAL L 18 0 8 16 43 included for completeness – Adam Hall TBL R 15 0 15 8 39 the number is never large. Dana Tyrell TBL C 16 0 15 7 38 Samuel Pahlsson CBJ C 16 0 16 5 38 In simple terms, all of these Nate Thompson TBL C 16 0 13 7 37 Anze Kopitar LAK C 17 1 8 10 35 PC scores involve a credit Martin St. Louis TBL R 17 -3 2 17 33 for ice time and a debit for Michal Handzus LAK C 12 1 11 8 32 goals against such that a Patrik Elias NJD L 12 -1 10 11 31 marginal player gets a zero Jonathan Toews CHI C 12 0 7 11 30 score. John Madden MIN C 10 0 10 10 30 Teddy Purcell TBL R 17 0 0 12 29 PCDTR is about the effect Nicklas Backstrom WSH C 18 1 6 4 29 of game transitions that I Mike Grier BUF R 11 0 10 7 28 allocate to defense, mainly Brooks Laich WSH C 17 1 12 -2 28 penalty avoidance. Ilya Kovalchuk NJD L 13 0 2 13 28 Penalties are obviously Daniel Winnik COL C 18 0 7 3 28 Rod Pelley NJD C 14 0 6 6 27 very significant „tilts‟ in the Tyler Bozak TOR C 6 0 6 15 27 game and the taking of

Copyright Alan Ryder, 2011 Hockey Analytics www.HockeyAnalytics.com 2011 NHL Review Page 42 penalties is a bad thing. Certain players do their jobs without taking penalties, and that is a valuable thing.

Exhibit A for penalty avoidance is usually Martin. St. Louis. He took just 6 minor penalties all year, a repeat of his 2010 performance. One must factor that into a view of defense or you are missing something (see my commentary above on St. Louis versus Stamkos).

Before spending more time on St. Louis and the plethora of Lightning players near the top of this list, we should start at the top with Travis Zajac. Below is a comparison of the 2010 and 2011 lines on his defense.

Travis Zajac MOI Defense (PCD) Season EH SH EH PP SH TR PCD 2010 1274 148 16 0 12 19 47 2011 1240 172 16 0 6 8 30

PC says that, while even handed, he was about the same player in 2011. As a raw indication of his performance, however, his even handed goal against average deteriorated from 1.79 in 2010 to 2.47 in 2011. So why the same PC score? Martin Brodeur. New Jersey goaltending was off materially in 2011, inflating goals against averages everywhere. PC tries to neutralize for that effect and comes to the conclusion that it was the same old Zajac.

Zajac‟s team-leading PCDEH score of 16 was strong but not amongst the league leaders: Logan Couture led the way with 19 PCDEH while Ovechkin, Nicklas Backstrom, Loui Eriksson and Daniel Winnik each had 18.

Toews came in at 12 PCDEH. He played 1,257 even handed minutes and posted a 2.24 GAAEH in front of league-average goaltending. Kesler, playing in front of elite goaltending, recorded a 1.89 GAAEH in 1,173 minutes. While even handed, Datsyuk had less ice time (867 minutes) and an inferior goals against average 2.63 GAAEH (in front of better goaltending) and came in at 8 PCDEH.

There were many players with lots of playing time (>800 minutes) and much better looking goals against averages. The leaders were Torrey Mitchell (SJS, 800 MOIEH, 1.50 GAAEH, 14 PCDEH), Logan Couture (SJS, 1149, 1.57, 19) and Brooks Laich (WAS, 1076, 1.62, 18). These results reflect individual, team, competition and goaltending dynamics, but none of these performances was in front of exceptional goaltending.

Marginal even handed defense is illustrated by Kevin Porter (COL, 880, 3.68, 1). But a couple of higher profile players, Jason Spezza (OTT, 915, 3.61, 2) and Eric Staal (CAR, 1302, 3.50, 2), were just about as bad. Compare Spezza to teammate Chris Neil (2.69 GAAEH) and Staal to rookie teammate Jeff Skinner (2.87). Seven players posted league worst PCDEH scores of -2, including Jamie Langenbruner (4.31 GAAEH) during his days with the Devils. In New Jersey that kind of performance is just not allowed.

Zajac‟s penalty killing contribution was improved in 2011. He got about 20% more playing time but doubled his PCDSH. Again, this was a solid performance, but hardly a league leading result. He got top pairing minutes (172) and delivered a solid 5.25 goals against average (in front of weak goaltending).

The league leading PCDSH score of 16 came from Samuel Pahlsson. He was last season‟s Gainey Trophy winner and it appears to have been no fluke:

Samuel Pahlsson MOI Defense (PCD) Season EH SH EH PP SH TR PCD 2010 1045 227 15 0 17 2 33 2011 1018 233 16 0 16 5 38

In 2010 Pauhlsson‟s penalty killing play was bettered by only two players. This season, says PC, nobody contributed more while short handed. His 6.43 GAASH may not impress you, but Columbus had essentially no goaltending. His 227 minutes were bettered by only 7 players.

One player that came close in playing time and PCDSH was Adam Hall who, as you can see, looks a lot like Pahlsson overall:

MOI Defense (PCD) Player EH SH EH PP SH TR PCD Adam Hall 973 231 15 0 15 8 39 Samuel Pahlsson 1018 233 16 0 16 5 38

Both played in front of terrible goaltending. Hall had a slightly better GAASH (5.98) but a slightly higher GAAEH (2.41 versus 2.36 for Pahlsson). Hall took four fewer penalties.

There were many players with lots of playing time (>150 minutes) and much better looking short handed goals against averages. The leaders were Jannick Hansen (VAN, 198 MOISH, 2.73 GAASH, 11 PCDSH) and Alex Burrows (VAN, 163, 3.69, 8). Both, of course, played in front of exceptional goaltending. Other leaders were Matt Cooke (PIT, 184, 3.91, 12) and Matt Cullen (MIN, 157, 4.21, 13).

Marginal penalty killing is illustrated by Tim Brent (TOR, 156, 10.03, 0), Patrick Marleau (SJS, 163, 10.30, 0) and R.J Umburger (CBJ, 161, 10.78, 0). Umburger can be compared directly to Pahlsson. Marleau and Brent both led their teams in short handed ice time when everyone else had lower goals against averages. I guess both coaches were afraid of the rest of their benches. Both PKs were quite bad in 2011.

Jordan Eberle (EDM, 21, 20.56, -5), Rick Nash (CNJ, 47, 22.48, -4) and Fredrick Modin (ATL, 36, 21.51, -4) each butchered the PK in very limited ice time and delivered league worst PCDSH scores. This is the kind of performance that, I supposed, frightened the coaching staffs in Toronto and San Jose.

The Selke Trophy finalists did not stand out here either. Toews had 7 PCDSH (157 minutes, 6.13 GAASH) while Kesler had 6 (210 minutes , 6.13 GAASH in front of Luongo

Copyright Alan Ryder, 2011 Hockey Analytics www.HockeyAnalytics.com 2011 NHL Review Page 44 and Schneider). Pet peeve: Datsyuk is not asked to kill penalties (just 37 minutes in 2011). You can‟t contribute if you don‟t play. For this reason alone Datsuk should not have been a serious candidate for the Selke Trophy.

Where Zajac wins the Gainey prize is with his defensive transition game where he led NHL with 19 PCDTR. This is mainly from penalty avoidance (just 7 minors). But he was +26 on turnovers and +120 on faceoffs, both of which tilt the ice away from your net. Other transition leaders were St. Louis (17), Loui Eriksson (16), Tyler Bozak (15) and Ilya Kovalchuk (13).

Toews (11 PCDTR) and Datsyuk (10) had solid defensive transition scores. Kesler (1) was about league average.

Eriksson‟s defensive transition performance vaulted him to 2nd overall in PCD (43). Just in arrears were Adam Hall (39), Dana Tyrell (38) and Nate Thompson (37). All three play for Tampa. The trio was the second most regular line combination for the Lightning (about 10% of all even handed shifts) behind Stamkos-St. Louis-Downie. Hall and Thompson were the lead penalty killers.

PC can‟t really distinguish the defense of players while they share the ice (no statistical method can). So it is not so surprising that the three end up in the same general zone. My approach to transitions is based on observable individual events. Yet the three still end up in the same zone.

Here is the profile of these players. I have thrown in St. Louis, Teddy Purcell and Domenic Moore so that we can have a look at the Tampa Bay phenomenon all at once:

MOI Defense (PCD) Player EH SH EH PP SH TR PCD Adam Hall 973 231 15 0 15 8 39 Dana Tyrell 801 132 16 0 15 7 38 Nate Thompson 961 215 16 0 13 7 37 Martin St. Louis 1312 38 17 -3 2 17 33 Teddy Purcell 918 2 17 0 0 12 29 Domenic Moore 968 163 8 1 9 -8 9 Steve Stamkos 1256 27 17 -3 2 -14 3

We have already seen how Stamkos and St. Louis are indistinguishable except for their transition game. If you track down the details you see that Hall and Thompson were likewise joined at the hip. These two end up with nearly matching PDCEH scores. Their time apart on the PK distinguished Hall as the more (slightly) impactful player.

After a promising start to his career in Nashville, having jumped directly to the Predators from US college hockey, Hall started to look like a marginal player with the Rangers, Wild and Penguins in 2007 and 2008. In 2009 he joined the Lightning for more of the same and 2010 saw him in the minors at the age of 28. In 2011 he was installed firmly in the third line role and clearly earned the respect of the coaching staff. As I said before, he looks a lot like Pahlsson, which is praise coming from PC.

Nate Thompson was a part-timer with the Islanders and Lightning until 2011 when he emerged as the prototypical third line centre. As a centre, Thompson may look more like Pahlsson than does Hall.

While even handed Tyrell was less well connected to Hall and Thompson, but the three still shared a great deal of even handed ice time. Tyrell was number four on the PK depth chart, playing most commonly with Domenic Moore. But you can see that he might have been some kind of secret sauce as he sported a 3.19 GAASH and a 2.02 GAAEH. His PCD scores reflect superior performance in playing time that was likely limited by his rookie status. Although he matches the PCD lines of Hall and Thompson very well, his ice time was lower, his PK work was largely independent and he is individually assessed on transitions.

The Moore/Tyrell comparison on the penalty kill reinforces this. Tyrell was much better than Moore when they played apart. Moore‟s most common PK partner was Tyrell, but number two was Sean Bergenheim. Both had better records than did Moore.

Tyrell, Pahlsson and Rod Pelley (NJD) are the co-winners of my Defense First Award for forwards. Tyrell and Pahlsson, last year‟s champion, each had 38 PC points, all of which came from defense. Pelley had 27 PCD and -11 PCO (based on just 3 goals and 7 assists).

The analysis says that Tampa Bay‟s goaltending was the worst in the NHL with a .903 save percentage and marginal neutral save percentage. Tampa‟s shot counts look about normal so all of this neutralization comes from shot quality. According to my analysis, Lighting skaters did the best job in the league of keeping the puck out of harm‟s way. This analysis is based on road games and is therefore unaffected by Tampa Bay scorer bias.

The conclusion that Tampa‟s goaltending is marginal means that PC allocates all observed goal prevention to the skaters. This puts Tampa‟s defensive numbers on steroids and makes them a bit suspect.

St. Louis took his PCDEH score from 8 in 2010 to 17 in 2011. I think that all of this is improvement is quite measurable and reconcilable as his GAAEH went from 3.26 to 2.65 while (raw) save percentages deteriorated slightly. So I think that it is clear that St. Louis was much better defensively in 2011. The story was similar for Stamkos. This also suggests that the 2011 Tampa Bay defensive story was real. That becomes important in a minute.

Defensemen

Finalists for the Norris Trophy in 2011: Zdeno Chara, Nicklas Lidstrom, and Shea Weber with Lidstrom winning the trophy for the 7th time. None were „finalists‟ in 2010, although Lidstrom did finish fourth in the voting.

The voting was actually quite tight. Weber was third ranked at the top of the ballot (32 Norris Trophy Voting first place selections versus 33 for Chara and 35 for Lidstrom) but was the most Player Team PC popular second choice (41 votes) by far. Nicklas Lidstrom DET 736 Shea Weber NSH 727 While it is common for PC to diss certain Zdeno Chara BOS 688 highly regarded defenders, for the first Lubomir Visnovsky ANA 573 time in memory PC has turned up a list of Keith Yandle PHX 312 top defensemen that looks very little like Chris Letang PIT 144 popular opinion. Below I show the top six PC performances in 2011 by defensemen. You can see that PC nominates three players, Alex Pietrangelo, John Carlson and Brett Clark, ahead of Lidstrom for my Bobby Orr Award for the top contribution by a defenseman.

To paraphrase Ricky Ricardo – “PC, you‟ve got some „splaining to do!”. To do that out one needs to examine the details Bobby Orr Award and, on the next page, I have provided the Top Defenseman PC breakdown for the top contributions by defensemen in 2011. As you can, there are Player Team PC many ways for a defender to add value. Alex Pietrangelo STL 90 PC provides a way for you to add up the John Carlson WSH 90 component parts. That makes sorting these Brett Clark TBL 90 top defensemen a much more objective Nicklas Lidstrom DET 88 Dan Boyle SJS 82 exercise. But PC has its limitations and I Keith Yandle PHX 81 will declare, up front, that PC may not have these players in the right order. It is very tough for a defender to be a top contributor without doing something on offense. Most observers are not effective at identifying defense so, in fact, Norris voters tend to be biased towards offensive contribution.

Which is why, at the all-star break, many were touting Dustin Byfuglien as the NHL‟s top blueliner. PC says that he was, in fact, the most valuable offensive performer amongst defenders. His 20 goals were tops amongst defensemen. Add 33 assists and adjust for context and PC gets him to 55 PCO.

Big Buff started strongly, but Lubomir Visnovsky reeled him in over the last half of the season finishing with 18 goals and 50 assists to lead all defensemen in scoring points. PC assessed his offensive contribution at 54 PCO, just a hair behind Byfuglien. His 36 PCOEH was just ahead of Buff‟s (35) based on 13 (versus 12) goals and 24 (versus 17) assists. This additional offense was partially due to more ice time (1,597 vs 1,553 minutes). Byfuglien‟s PCOEH is improved slightly by noting his 3 single assists (Visnovsky had none), which are more valuable than garden-variety assists.

2011 Player Contribution – Defensemen (items may not total due to rounding)

PCO PCD Player Team POS PC EH PP SH TR SO PCO EH PP SH TR PCD Alex Pietrangelo STL D 90 24 7 1 0 0 32 26 8 10 14 58 John Carlson WSH D 90 25 4 0 0 0 30 41 1 14 5 60 Brett Clark TBL D 90 8 14 0 -2 0 19 45 -7 19 13 70 Nicklas Lidstrom DET D 88 22 27 0 -6 0 43 19 4 9 12 44 Dan Boyle SJS D 82 16 21 0 -2 10 46 27 3 8 -2 36 Keith Yandle PHX D 81 26 14 0 1 0 41 31 5 1 3 40 Niklas Kronwall DET D 80 18 12 0 -1 0 28 32 2 16 3 52 Lubomir Visnovsky ANA D 79 36 20 0 -1 -1 54 16 2 1 6 25 Christian Ehrhoff VAN D 77 18 23 1 -2 0 40 24 4 12 -3 37 Brent Burns MIN D 75 29 12 0 -2 2 41 23 3 15 -7 34 Shea Weber NSH D 75 24 10 3 0 0 36 25 6 8 0 39 John-Michael Liles COL D 74 19 12 0 3 0 33 21 0 10 9 41 Fedor Tyutin CBJ D 74 13 3 0 -2 2 16 33 -1 17 9 58 Trevor Daley DAL D 73 14 4 0 -1 0 17 44 -1 5 7 56 Andy Greene NJD D 73 8 2 -1 -2 0 7 35 1 16 14 65 Dustin Byfuglien ATL D 72 35 21 0 1 -2 55 20 -2 1 -3 17 Kris Letang PIT D 71 16 11 2 4 1 33 28 3 8 -1 38 Alex Goligoski PIT/DAL D 70 19 14 1 -1 -1 32 30 1 5 2 38 Mark Giordano CGY D 69 8 17 0 2 0 26 30 2 12 -2 42 Erik Karlsson OTT D 68 22 14 0 -1 4 38 15 4 13 -2 30 Duncan Keith CHI D 68 11 15 2 -6 0 22 22 6 9 10 47

Visnovsky (5 goals, 26 assists) also outscored Buff (8, 16) on the power play in similar ice time. PC sorted that out (including 12 versus 9 first assists) and gave 21 PCOPP to Byfuglien (20 to Visnovsky).

As the Norris Trophy winner and the defensive benchmark of our times Nick Lidstrom will be the reference point for all others in this discussion. He came in with the NHL‟s second best official offensive tally – 16 goals and 46 assists for 62 scoring points. He did this mainly on the power play (7 goals, 32 assists), leading all defensemen with 27 PCOPP. His even handed offense was strong (22 PCOEH) but trailed that of Visnovsky (36), Byfuglien (35), Brent Burns (29), Keith Yandle (26), John Carlson (25), Alex Pietrangelo (24) and Shea Weber (24).

Lidstrom‟s overall PCO score was hurt by his transition game and a PCOTR score of -6. In 2011 he failed to draw a single penalty, was neutral on turnovers and nearly neutral in his even handed zone start profile. Nevertheless the future hall of famer was ranked 4th in PCO (43) amongst defensemen behind Byfuglien (55), Visnovsky (54) and Dan Boyle (46), who accumulated 10 PC points by going 3 for 3 in the shootout.

Shea Weber (16 goals, 32 assists) was back at 36 PCO and Zdeno Chara (14, 30) was at 31 PCO. Carlson (7 goals, 30 assists, 30 PCO) and Pietrangelo (11, 32, 32) looked roughly like Weber while even handed and like Chara overall. Carlson‟s numbers seem smaller but he did most of his work while even handed, where it is tougher to put up the numbers, and got less power play time. PC adjusts for things like this. Only four defensemen came in with a higher PCOEH score.

Turning to defense …

Neither of Byfuglien or Visnovsky were strong enough defensively to stay in the race. Neither was asked to kill penalties (8 and 35 minutes of PK ice time respectively). Neither was strong while even handed (20 and 16 PCDEH respectively). Visnovsky, however, still finished fourth in Norris voting.

Our benchmark is, of course, Lidstrom. Here is a comparison of his PC scores since the lockout:

PCO PCD Nicklas Lidstrom Team POS PC EH PP SH TR SO PCO EH PP SH TR PCD 2006 DET D 143 25 35 -1 -1 0 58 32 7 29 17 85 2007 DET D 130 16 24 0 2 0 42 50 5 21 12 88 2008 DET D 121 25 23 -5 0 0 43 48 3 17 10 78 2009 DET D 117 23 27 -4 1 0 47 37 7 12 14 70 2010 DET D 100 18 16 2 -4 0 33 31 7 17 12 67 2011 DET D 88 22 27 0 -6 0 43 19 4 9 12 44

While there is some noise in here, one can see the aging of this player – his overall and defensive contributions have declined between 5% and 10% per year (until 2011). This is a much slower than normal deterioration and is slower than most elite players. His offensive production fell in 2010 (and he slipped to fourth in the Norris balloting) but returned to form in 2011.

On defense last season he showed a break from this trend. Lidstrom aged a lot. His transition game (mainly penalty taking) was unchanged, but all other aspects of his defense eroded. His even handed GAA jumped from 2.20 to 2.93 and his minutes were down (1,524 to 1,373). Short handed playing time was up slightly (332 minutes versus 320) but the results were a fair bit worse (GAA of 7.40 versus 4.23). Yes – the goaltending behind him went from above average (.917 NSV) to below average (.910), but PC adjusts for this.

In 2011, on defense, we did not see the „same old Lidstrom‟, we saw „old Lidstrom‟. And that opened the doors for others to shine.

Shea Weber was more valuable while even handed (25 PCOEH versus 19). His GAAEH was 2.36 (in front of pretty good goaltending). PC says that was worth about half of the difference with the other half coming from a lot more minutes (1,604). Weber‟s PK contribution was about the same as that of Lidstrom. In 299 minutes he got to 8 PCDSH.

However he was off Lidstrom‟s overall PCD pace because of his penalty taking (28 minor penalties versus 10 for Lidstrom).

While Zdeno Chara was in between Lidstrom and Weber while even handed (23 PCDEH), his penalty killing work was brutal. He turned in a GAASH of 7.37 in front of lights-out goaltending. The Bruins PK was slightly better than average, but did I mention the lights-out goaltending? Chara‟s GAASH was the worst result of any of the Boston regulars (I know – he faced tougher competition …). Overall his PCD score was 29.

So neither of these guys was better than Lidstrom.

Last year I said:

“If there is a more over-hyped defenseman in the NHL [than Zdeno Chara] it is Jay Bouwmeester”.

I relent.

Chara remains the most over-hyped defenseman in the NHL – second in the Norris balloting but PC ranked him #34 with 60 PC. In 2011 Bouwmeester came in at 56 PC (versus 60 in 2010). This is a very solid season for a defender, but his high cost ($6,680,000 cap hit) means that he had the highest cost per PC point on the leaderboard ($119,696).

So now it is time to explain why Brett Clark, John Carslon and Alex Pietrangelo each ranked (ever so slightly) ahead of Lidstrom. The latter two delivered PCO more than 10 points off Lidstrom‟s pace so they have a hill to climb on defense. Clark had one of the weakest offensive profiles on the leaderboard. So he has a mountain to climb.

This analysis says that, while even handed, Pietrangelo (26 PCDEH) was the defensive equivalent of Shea Weber. His GAAEH was worse (2.59 versus 2.36) and he played fewer minutes (1,344 versus 1,604). But PC says that Pietrangelo was materially disadvantaged by goaltending (.902 NSV versus .923) and calls the result roughly a draw. In fact, PC says that Pietrangelo (76 PC before defensive transitions) was Shea Weber (75 PC), without all those messy penalties (just 7 minors – a performance worth 14 PCDTR).

He was clearly the top defenseman on what was a pretty good defensive team. While his zone starts were favourable for him (PC adjusts for that) his quality of competition was second only to Barret Jackman. I have the Blues ranked as the 6th best defensive team in 2011 based largely on the 2nd lowest shots allowed. Not bad for a 20 year old who had played just 17 games in the NHL prior to last season?

Pietrangelo overtook Lidstrom by being stronger across the entire defensive spectrum. He played a bit less while even-handed (1,344 minutes) but had a lower GAAEH (2.59) in front of inferior goaltending and PC awarded him 26 PCDEH (versus 19 for Lidstrom). He picked up another 4 points with power play defense (0.00 GAAPP), 1 point on the penalty kill (a 6.51 GAASH) and 2 points in defensive transitions.

He was not named on a single Norris ballot. He was also ineligible for the Calder Trophy in what you would have to think of as his rookie season.

John Carlson looked a lot like Pietrangelo on offense, giving up 3 PC points on the power play and ending with 2 fewer PCO. His defensive profile was quite different but added up to 2 more PCD to end up tied with the Blues blueliner. Versus Pietrangelo, Carlson gave up 9 PCDTR (mainly from 10 extra minor penalties) and 7 PCDPP but clawed 4 points back while short handed and then surged back with 41 PCDEH, the 4th best total in 2011. In 1,485 minutes of even handed play he had a sizzling GAAEH of 1.90 (in front of average goaltending). While short handed (191 minutes) he delivered a GAASH of 4.72.

He was clearly the top defenseman on what I have ranked as the 4th best defensive team in 2011 (Mike Green might complain about that evaluation but he missed 33 games), generally facing the toughest competition. Not bad for a 20 year old who had played just 22 games in the NHL prior to last season? He was also not named on a single Norris ballot.

Carlson and Pietrangelo were unheralded youngsters who snuck up out of nowhere. But Brett Clark‟s story could not be further away. For the longest time he looked like he would never make it to the NHL. After a couple of tries with the Canadiens in 1998 and 1999 he looked to be settling in to a minor league career. Finally, for the 2006 season, he made the grade to commence a 5 year stint with the Avalanche.

The Lightning signed him as a free agent for the 2011 season and the Hockey News had a not so flattering commentary:

ASSETS: Moves the puck efficiently and is a good shot-blocker. Uses his mobility to make up for mistakes in the defensive zone, either by himself or his partner. Is conscious of the transition game.

FLAWS: Struggles with big forwards in front of his own net. Tends to make the occasional blunder from behind the blueline. Isn't a physical player at all.

CAREER POTENTIAL: Puck-moving and shot-blocking defenseman.

Here is what he did in 2011:

His even-handed offense hardly inspired. In 1,197 minutes he delivered an Andy Greene like 3 goals and 11 assists for a PCOEH of 8. His 14 PCOPP in 235 minutes was a better effort, ranking behind only 9 defensemen and coming in at the same kind of level as Sergei Gonchar and P.K. Subban. Clark‟s career has hinted at this kind of profile (however his PCOPP was just 1 in 162 minutes in 2010), but his numbers likely benefited from being designated as the premier power play point man in support of the likes of St. Louis and Stamkos.

PCO of 19 was hardly an auspicious start. But his defensive story really smoked.

While even handed he posted a very strong GAAEH of 2.05. Many defensemen did better, but goaltending is a huge consideration here. A useful comparison is Andrej Meszaros, who matched Clark‟s GAAEH. The Lightning had terrible goaltending (.903 save percentage) whereas the Flyers were better than average (.915). PC awards Meszaros 29 PCDEH for this result but Clark gets 45 PCDEH. If you scale back the ice time of Meszaros (he played 151 extra minutes) you scale back his PCDEH to 23. Clark was on-ice for 478 shots whereas a scaled back Meszaros would have allowed 596. If you exposed those shots to Tampa‟s inferior goaltending he would have been on-ice for 11 goals more than Clark. The two players share the same GAAEH, but when you adjust for goaltending context Meszaros is a long way back of Clark‟s performance.

Clark had a better record of shot prevention in front of markedly inferior goaltending. This accounts for about 14 of the 22 point difference. The remainder is due to shot quality differentials between the two teams, which PC allocates over the whole team.

When you compare Clark to his teammates you see second-pairing even handed minutes (1,197) behind Victor Hedman (1,369 minutes, 2.67 GAAEH) and Pavel Kubina (1,255, 2.29). But when you study quality of competition you conclude that Tampa‟s coaching did not materially differentiate. Mattias Ohlund (1,133, 2.86) and Mike Lundin (1,196, 2.71) got the toughest assignments. All of this suggests that Clark‟s defensive numbers may have been enhanced a bit by coaching.

No NHL defender had a higher PCDSH score than did Clark (19). His 1.56 GAASH in just 116 minutes was lights out. But he undoubtedly got the light duty assignments as his ice time ranked him #5 on Tampa‟s PK depth chart. Nevertheless, results are results and PC sets out to find them.

Tampa Bay (and Clark) had poor power play defense. PC blames that mostly on blueliners. Sub-marginal goaltending amplifies the results and PC takes away 7 points here.

Clark‟s teammate Mike Lundin (with just 6 minor penalties,) tied for the NHL lead (14 PCDTR) in defensive transitions with Pietrangelo and Andy Greene, but Clark was number four (13 PCDTR, 7 minors). I have harped on this before – penalties have a cost. Again, marginal goaltending amplifies this (a penalty puts weak goaltending more at risk).

In summary, Clark‟s raw defensive numbers are very good and when you adjust for goaltending they become excellent.

PC tries to measure the important circumstances of performance so as to refine our view of a player. By far the largest circumstantial factor concerning our assessment of defense is goaltending. Washington‟s goaltending was the best amongst the four teams represented in this list. Tampa‟s was the worst. PC deals with this directly but another way to take goaltending out of the equation it to study shots allowed, where Lidstrom sticks out like a sore thumb:

Shots / 60 Player EH SH Alex Pietrangelo 22.6 36.8 John Carlson 24.7 33.0 Brett Clark 24.0 36.8 Nicklas Lidstrom 29.7 50.1

This, of course, leads you to consider quality of competition13 before you reach any conclusions14. While Pietrangelo and Carlson were generally deployed as „top pair‟ guys, Clark was not. His quality of competition was the weakest of PC‟s top four defensemen. In absolute terms, quality of competition would rank the top four something like: Lidstrom, Carlson, Pietrangelo and Clark. To reconcile Lidstrom‟s shot and QoC information – it looks like he faced tougher opposition but, in a best against best contest, he may have come out the loser.

Another factor is teammates. Carlson had a pretty steady date with Karl Azner to their mutual benefit. Pietrangelo‟s partners shuffled around. Clark and Lidstrom were in between (most commonly with Victor Hedman and Brad Stuart respectively). Overall Carlson played with the strongest teammates, followed by Clark, Lidstrom and then Pietrangelo.

When discussing team results I pointed out that PC allocates team points to individuals, regardless of whether they were a consequence of performance or luck. In other words, PC makes no attempt to identify the element of randomness that shows up in performance. The only „unlucky‟ team (a low ratio of points in the standings to marginal goals) represented in this top six discussion is St. Louis. The other teams were all on the lucky side of average. If one adjusts the PC scores for team luck, Pietrangelo „surges‟ into the top position (by 12 PC points over Carlson and 15 points over Brett and Lidstrom).

I thought last season was a difficult one but in 2011 PC called this (just about) a four way tie and left it up to me to decide. Note the dramatically reduced PC scores for top defensemen in 2011 which imply that the race was wide open. Lidstrom‟s performance was clearly off in 2011, but the voters hardly got it wrong (although it seems to me that they lucked into the selection as neither Weber nor Chara were deserving).

Of PC‟s four „finalists‟ Brett Clark seems the easiest to disqualify based on his pedigree and context. However, his defensive story is only dismissed if you believe he had low quality of competition. Lidstrom is, of course, easiest to choose, especially if you believe

13 See www.BehindTheNet.ca.

14 Quality of competition is difficult to assess. First of all it relies on some holistic measure of “quality”. Plus/minus is the first approximation of “quality”. Corsi is a much better approximation. But it is still a deficient measurement for a number of reasons. The best measure of quality that I know is Player Contribution. But to use quality of competition in PC creates a problem of “circularity” (the measurement cannot be made until the measurement is made). The correct approach involves the simultaneous solution of about 1,000 equations in 1,000 variables or an iterative approach.

Copyright Alan Ryder, 2011 Hockey Analytics www.HockeyAnalytics.com 2011 NHL Review Page 53 in high quality of competition. But I am going to going to stick with PC‟s choice of Alex Pietrangelo as the Bobby Orr Award winner in 2011. The mathematical margin was 0.3 PC points (over Carlson), but I think he had the weakest profile of teammates and played for one of unluckiest teams in the NHL (a significant factor in connecting individual and performances).

Defensive Defensemen

The list of top defensemen is usually highly influenced by offensive play. The NHL needs a defenseman‟s version of the Selke Trophy. Mine is the Rod Langway Award, for the top defensive contribution to team success by a defenseman.

Who were the best defensive defensemen in the NHL in 2011? The list is to the Rod Langway Award right. And the PCD details are provided Top Defensive Defenseman below for the top 20 defensive defenders. Player Team PCD If you were paying attention above you Brett Clark TBL 70 would have realized that the winner of my Andy Greene NJD 65 Rod Langway Award is the unlikely Brett John Carlson WSH 60 Clark. Paul Martin PIT 60 Henrik Tallinder NJD 59 To summarize his performance: league Fedor Tyutin CBJ 58 EH SH leading PCD (45) and PCD (19), a Alex Pietrangelo STL 58 killer combination. While even handed he posted a GAAEH of 2.05 in 1,197 minutes. His 1.56 GAASH in just 116 minutes of PK play was lights out. He also took just 7 minor penalties to drive a 13 PCDTR score. The qualitative assessment is above.

Rounding out the leaderboard was Andy Greene, Carlson, Paul Martin, Henrik Tallinder, Fedor Tyutin and Pietrangelo. The profiles, of course, varied.

After a breakout year in 2010 in which he ranked fifth in PCD, Greene moved to second in 2011. Of course, this starts with solid even handed play (35 PCDEH). His 2.57 GAAEH was actually the highest of the regular defensemen but he got a lot of ice time (1,538 minutes) and you should note that PC is essentially 'performance' x 'opportunity'. His story continues with a strong penalty killing work (16 PCDSH, 5.36 GAASH, 190 minutes) and an unsurpassed 14 PCDTR (just 10 minor penalties). Note that goaltending collapsed behind him but PC sees right through this:

PCD Andy Greene Team POS EH PP SH TR PCD 2010 NJD D 42 4 7 14 67 2011 NJD D 35 1 16 14 65

Greene‟s teammate Tallinder had even stronger even handed defense (41 PCDEH), where he had a 2.42 GAAEH in even more ice time. His 1,609 even handed minutes ranked third

Copyright Alan Ryder, 2011 Hockey Analytics www.HockeyAnalytics.com 2011 NHL Review Page 54 in the league behind only Duncan Keith (1,744) and Jay Bouwmeester (1,628). Tallinder and Greene did NOT spend so much even handed time together, so you should not conclude that there is cause and effect with these two players. His overall PCD was held back by uncompetitive PCDTR and PCDSH scores.

2011 Player Contribution Defense – Defensemen (items may not total due to rounding)

PCD Player Team POS EH PP SH TR PCD Brett Clark TBL D 45 -7 19 13 70 Andy Greene NJD D 35 1 16 14 65 John Carlson WSH D 41 1 14 5 60 Paul Martin PIT D 30 3 16 11 60 Henrik Tallinder NJD D 41 3 11 4 59 Fedor Tyutin CBJ D 33 -1 17 9 58 Alex Pietrangelo STL D 26 8 10 14 58 Karl Alzner WSH D 41 0 10 7 57 Rob Scuderi LAK D 36 0 10 10 56 Trevor Daley DAL D 44 -1 5 7 56 Jan Hejda CBJ D 29 0 19 7 56 Mike Lundin TBL D 30 -1 11 14 53 Brian Campbell CHI D 34 4 5 10 53 Niklas Kronwall DET D 32 2 16 3 52 Greg Zanon MIN D 39 0 13 0 51 Jeff Schultz WSH D 28 0 13 8 50 Jay Bouwmeester CGY D 38 2 4 5 49 Jason Demers SJS D 36 4 6 3 49 Andrej Sekera BUF D 28 2 10 8 49 Marc-Edouard Vlasic SJS D 33 2 2 9 47 Duncan Keith CHI D 22 6 9 10 47

Paul Martin is a refugee from the Devils‟ defenseman factory and his pedigree shows. Note that, like Carlson, his goaltending support was good. This shows up in his goals against averages - 2.17 in 1,354 even handed minutes and 3.97 in 211 short handed minutes. As is the case with most of the PCD leaders, his PCDTR score was solid.

Fedor Tyutin, like Clark, Greene, Tallinder and Pietrangelo, played in front of weak goaltending. He posted a 2.68 GAAEH in 1,364 even handed minutes and 6.62 GAASH in 218 short handed minutes. His ice time profile is very similar to that of Martin. PC says they had about the same impact, so you can see the goaltending effects in the goals against averages.

The top defensive performances while even handed came from Clark (45), Trevor Daley (44), Tallinder (41), Pavel Kubina (41) and the Washington duo of Carlson (41) and Azner (41). These two were a regular pairing (together about 27% of all defensive time)

Copyright Alan Ryder, 2011 Hockey Analytics www.HockeyAnalytics.com 2011 NHL Review Page 55 and PC cannot reasonably separate the defense of two players under such circumstances. Together, however, they had a superlative record with GAAEH of 1.90 and 1.84 respectively (in front of better than average goaltending). Daley‟s GAAEH was 2.11 in 1,533 minutes in front of below average goaltending. Kubina is part of the Tampa story (2.29 GAAEH, 1,255 minutes).

Tying Clark for the league lead in penalty killing impact (each with 19 PCDSH) were Jan Hejda (CLB), Zbynek Michalek (PIT), Willy Mitchell (LAK) and Chris Phillips (OTT).

Repeating on the leaderboard from 2010 were Greene, Greg Zanon, Tyutin and Bouwmeester.

Washington, by my reckoning the NHL‟s fourth best defensive team, placed three defenders on the list – Carlson, Alzner and Schultz. The perennially strong Devils, the league‟s top defensive team, placed two (Greene and Tallinder) as did the fifth best Tampa Bay (Clark and Lundin), 10th place Columbus (Tyutin and Hejda) and 7th best San Jose (Demers and Vlasic).

I have been following Marc-Edouard Vlasic since he was in diapers. In my assessment of defensive contribution Vlasic was third in 2007, first in 2008 and second in 2009. At that stage of his development I called him “Nick Lidstrom without the offense”. Here is the before and after for Vlasic:

PCD Marc-Edouard Vlasic Team POS EH PP SH TR PCD 2007 SJS D 30 5 16 18 69 2008 SJS D 47 3 14 16 80 2009 SJS D 37 3 13 12 65 2010 SJS D 28 0 11 7 46 2011 SJS D 33 2 2 9 47

Last season Vlasic missed 18 games, but he had no such excuse in 2011. This season his penalty killing was brutal. His 9.54 GAASH was the worst on the leaderboard. While his 182 short handed minutes led the Sharks, his results did not appear to be due to quality of competition. Rather, this would appear to be another case of under-coaching. Vlasic was treated a top-pair defender when his short handed work was out of whack. With a more historic short handed effort and more historic discipline he would have been near the top of the list.

In 2008 Vlasic was my choice for the Stay-At-Home-Defenseman of the year (highest differential between PCD and PCO). In 2009 it was Sean O‟Donnell (PCD of 55, PCO of -4). In 2010 the winner was Greg Zanon (68, 4). The winner in 2011 is Andy Greene (65, 7), with Karl Alzner (57, 1) in hot pursuit.

As I consider penalty avoidance to be an element of defense, it is not surprising that most of these players were above average in penalty avoidance. Greene, Pietrangelo and Lundin led the way with 14 PCDTR points followed by Clark (13) and Lidstrom (12).

Goaltenders

The Vezina Trophy goes to the goalkeeper adjudged to be “the best at this position as voted by the general managers of all NHL clubs”. I always struggle with this definition. If a goalie has great stats and plays 70 games, should he lose this award to another with „better‟ numbers but in only 45 games? I don‟t think so. I prefer a “most valuable” definition (PC is an impact measure) for my Patrick Roy Award. Voters tend to have the same view, however their value measurement system and mine seem to be somewhat different.

This season the issue becomes crystal clear. Finalists for the 2011 Vezina Trophy were Roberto Luongo, Pekka Rinne and Tim Thomas. The Bruins‟ backstop won the trophy rather handily with 17 of 30 votes. Rinne out-balloted Thomas for the Hart Trophy but placed behind him in All-Star voting (same voters).

PC sees this though the „contribution‟ lens and says that Cam Ward was the most valuable goalkeeper in 2011. He was not named on a single Hart ballot and finished 7th in the Vezina balloting (only named on 2 of 30 ballots as one of the NHL‟s three best goaltenders).

The salient details are shown to RO SO the right. PCG and PCG Patrick Roy Trophy are PC scores from goaltending Top Goaltender in regulation/overtime and the shootout respectively. The PC Player Team PCGRO PCGSO PC total includes some spare Cam Ward CAR 271 44 319 change from offense and Tim Thomas BOS 269 7 278 defense (penalties). Pekka Rinne NSH 212 49 255 Carey Price MTL 223 22 243 From this, it is easy to jump to Roberto Luongo VAN 224 9 234 the shootout as the Jonas Hiller ANA 196 36 232 differentiating aspect of Ward‟s performance. The Carolina twine-minder stopped 19 of 25 shootout attempts (.760 save percentage) versus just 10 of 19 (.526) for Thomas. When you watch Thomas you get the sense that his strengths are his mobility and reflexes. These skills are not emphasized in the shootout and he has never been an impressive goaltender in this contest. Ward‟s performance was a bit better than league average but Carolina was a lucky shootout team and that puts his better than average performance on steroids, delivering 44 PCGSO. The performance of Thomas was nearly marginal.

The most impactful shootout performances came from Henrik Lundqvist (64 PCGSO), Jonathon Quick (62) and Marc-Andre Fleury (57). A good part of this was opportunity - they ranked first, second and fourth in shootout attempts (46, 44 and 38 respectively). But these three also delivered the performance - save percentages of .848, .818 and .842 respectively.

The rest of the Ward versus Thomas analysis is relatively simple. Thomas played better (.938 save percentage versus .923). Ward played more (a league leading 4,316 minutes versus 3,364). In terms of points in the standings, PC saw this as roughly a draw.

Thomas got the press and he deserved it, setting a modern era save percentage record. His neutral save percentage was .939, indicating that his save percentage was not materially affected by his circumstances.

There is no doubt in my mind that Thomas was the „best‟ NHL goaltender in 2011.

Ward‟s NSV of .927 tells you that there were some adverse circumstances in Carolina (mainly inferior shot quality). Note that, during skating time, Carolina was a luckier team than the Bruins. But, if you de-luck the PCG scores, Ward remains 12 PC points ahead.

I am comfortable with the conclusion that Ward made the most valuable contribution in the blue paint in 2011.

The General Managers who vote for the Vezina typically ignore the shootout. They placed Rinne clearly ahead of Luongo in the voting yet PC had them in a different order before the shootout. The Vancouver netminder had a .928 save percentage and 38 wins. Rinne posted 33 wins and a .930 save percentage. These voters normally like wins but I think that Luongo‟s results were discounted because he played for the NHL‟s top regular season team. PC care‟s not about wins (a team metric). So it is important to note that Luongo‟s NSV was .932 (in 3,590 minutes) and Rinne‟s was .927 (in 3,789 minutes).

Like Thomas, Luongo had a weak shootout record (.538 save percentage). And this is what let Carey Price sneak into fourth place. He posted a .923 save percentage (.924 NSV) in 4,206 minutes (second only to Ward) and then posted a .750 save percentage in the shootout.

Transitions

The best example of a transition is the taking of a minor penalty. Such an act (typically) puts a team a man down for (up to) two minutes. It clearly tilts the ice against the defending team and results in a higher expectation of goals allowed and a lower expectation of goals scored. As a rule of thumb, a minor penalty costs about 25% of a goal. Penalty drawing is the mirror image of this, tilting the ice in favour of the drawing team.

These penalty transitions have an important goaltending effect – taken penalties will increase both shots allowed and their quality (danger) while drawn penalties reduce shots allowed (without a material impact on shot quality). Once you think about increasing (6 players in the game) or reducing (only 5 players in the game) reliance on goaltending you can conclude that the effects are not completely symmetrical. Also, the effects of penalty taking relate to team goaltending. This is easy to see if you imagine the case of a team with a „perfect‟ goaltender (penalties taken only cost two minutes of lost offense) versus the case of a team with „no‟ goaltending (penalties taken are virtually a conceded goal

Copyright Alan Ryder, 2011 Hockey Analytics www.HockeyAnalytics.com 2011 NHL Review Page 58 but, because of that, there is little lost offense). Penalty drawing effects therefore are better seen against league average goaltending.

Face-offs tilt the ice from its neutral position in favour of the winning team. A defensive zone starts indicate that an adverse tilt in the ice already exists. An offensive zone finish suggests a positive tilt has been achieved. Giveaways and takeaways tell us about shifts in puck possession and tilts in the game.

I have been incorporating these other transitions into PC, but they don‟t add up to much relative to the impact of minor penalties (or I am still looking at it the wrong way). So when I talk about transitions, think „penalties‟.

Clean and Impactful Play

The Lady Byng Memorial Trophy goes to the player “adjudged to have exhibited the best type of sportsmanship and gentlemanly conduct combined with a high standard of playing ability”. Voters tend to go down the list of top scorers until they find someone with low penalty minute totals. In 2011, Martin St. Louis and Loui Eriksson were two of only three players with fewer than 20 penalty minutes among the top 40 point scorers. And they were two of the Lady Byng Trophy „finalists‟. In an unusual development, a defenseman (Nicklas Lidstrom) was the third finalist.

In honour of Frank Boucher, a seven time Lady Byng Trophy winner (in fact they gave him the original trophy and now award a second generation version), let me present the Frank Boucher Award to the player who best combines both clean and impactful play. This is close to the Lady Byng definition. The word “combines” is an “AND” condition. With “AND” conditions you multiply (with “OR” conditions you add). You need both factors to be strong to get a good “AND” rating.

My “Frank” points are therefore:

Player Contribution (my measure of impact) x (50 – PIM) (my measure of clean play).

Fifty minutes is a pretty arbitrary part of this formula. In fact the formula is pretty arbitrary.

The voters chose Martin St. Louis as the Lady Byng man (115 PC points, 12 PIM) for the second year in a row. Frank Boucher Award Clean and Impactful Play This is a very arbitrary award and my formulaic approach is meant to simulate Player Team Franks voter behaviour. But voters completely Martin St. Louis TBL 4356 ignored Brett Clark (90, 14) and Brian Loui Eriksson DAL 4155 Campbell (65, 6). With no way to measure Brett Clark TBL 3231 defense, the Lady Byng voters typically Michael Grabner NYI 3123 downplay defensemen in their voting, with Pavel Datsyuk DET 2945 Brian Campbell CHI 2855 the exception of larger-than-life Lidstrom

(88, 20). He placed 10th in the Frank rankings but 2nd in Lady Byng voting.

Voters ranked Loui Eriksson in third, but my formula had him in second (99 PC, 8 PIM). The formula ranked Michael Grabner (78, 10) much higher than did the voters (21st). Patrick Marleau was the only other top 40 scorer with fewer than 20 minutes of penalties. Not surprisingly he ended up 4th in the balloting. With 74 PC and 16 PIM he placed 11th in the Franks.

Defensive Transitions

Below is a list of the seven highest defensive transition contributions in the NHL in 2011. The formula to determine PCDTR is dominated by the piece tracking penalty avoidance, and that part is basically ice time x (average minor penalties – actual minor penalties). So this is a list of players with considerable ice time who did whatever they did, on offense or defense, without cheating (much). Each contributed around 1.5 points in the standings with their discipline.

I have already remarked on many of these players Defensive Transitions – Best before so I won‟t spend more on them. Player Team POS Minors PCDTR Travis Zajac NJD C 7 19 Also shown are the worst Martin St. Louis TBL R 6 17 defensive transition Loui Eriksson DAL L 4 16 players. Each of these guys Tyler Bozak TOR C 7 15 played a great deal, took a Andy Greene NJD D 10 14 lot of minor penalties and Alex Pietrangelo STL D 7 14 hurt their team around 2 Mike Lundin TBL D 6 14 points in the standings. Defensive Transitions – Worst Most of these are „tough guys‟. All, except for Player Team POS Minors PCDTR Cooke, had more than 170 Cody McLeod COL L 36 -24 minutes of penalties. Only Steve Downie TBL R 33 -24 Cooke and Downie had Brad Staubitz MIN D 29 -19 fewer than 10 fights. Only Derek Dorsett CBJ R 32 -18 Cooke and Downie had Theo Peckham EDM D 38 -16 more goals than fights. Chris Neil OTT R 35 -15 Matt Cooke PIT L 37 -15 McLeod‟s -24 PCDTR score overwhelmed is other, limited contributions (he had 0 PCO) and he ended up with a league worst skater PC score of -12. Chris Neil also had a negative PC score (-2) but the others were in positive territory (Staubitz was barely there with 3 PC).

Downie can contribute in other ways (he had 30 PCO and 17 PC). He also is one of the NHL‟s top pests, as is evidenced by his PCOTR score of 9. Matt Cooke is also a rounded player with 26 PC (after the negative PCDTR score).

The 10th worst PCDTR score came from Steve Stamkos. I discussed that earlier, comparing him to Martin St. Louis.

The top 10 PCDTR players averaged 76 PC points while the bottom 10 (including Stamkos) averaged 23 PC points. So penalty avoidance is well correlated with overall value.

Offensive Transitions

I think penalty drawing is an indication of an ability to play an up-tempo game. It is probably the best statistical indication of aggressive play. And penalty drawing is the dominating part of offensive transitions (PCOTR).

The list of the top PCOTR scores is shown to the right. Offensive Transitions – Best While penalty taking drives TR the PCD scores, penalty Player Team POS Minors PCOTR drawing is a less dominant Ryan Kesler VAN C 37 14 part of PCOTR. Manny Manny Malhotra VAN C 16 14 Malholtra demonstrates Jonathan Toews CHI C 32 13 that, standing out with very Paul Gaustad BUF C 25 13 few penalties drawn. In Steve Ott DAL C 33 12 fact, he had a PCOTR score Darren Helm DET C 38 12 Jeff Skinner CAR C 53 12 of -1 from penalty drawing alone. Offensive Transitions – Worst

Malholtra, Kesler, Toews Player Team POS Minors PCDTR and Gaustand each had Andrew Cogliano EDM C 14 -10 TR more than 10 PCO from Ryan Getzlaf ANA C 13 -9 sources other than penalty Daniel Sedin VAN L 14 -9 drawing. Derek Stepan NYR C 15 -8 Brad Richards DAL C 9 -7 Carolina rookie Jeff Patrik Elias NJD L 14 -7 Skinner led the NHL with Derick Brassard CBJ C 14 -7 53 minor penalties drawn and all of his 12 PCOTR was attributable to that. He was followed by Dustin Brown (50), the captain of the Kings and last year‟s leader.

Note that all of the top seven PCOTR players are (listed listed by the NHL as) centres. With the exception of Skinner these guys took a lot of faceoffs and did it well. As a group the top six won 4,403 and lost 3,241 and averaged nearly 200 net faceoff wins over the course of the season.

As a group they collected credit for 354 takeaways and were debited with just 187 giveaways.

At the other end of the spectrum, seven forwards had PCOTR scores of -7 or worse. Others were penalized less but this group averaged 1,440 minutes of playing time and, on average, drew a minor penalty once every 6 games. Five were centres, although Elias took a fir number of faceoffs. As a group (excluding Sedin) they won 2,411 and lost 2,975. As a group the takeaway/giveaway numbers were 260/351.

The top 10 PCOTR players averaged 59 PC points while the bottom 10 averaged 42 PC points. So PCOTR scores provide some colour but may not be that highly correlated with value generation.

Net Transitions

Looking at net transitions allows us to sum up the effects of penalty taking, penalty drawing and other ice tilting effects:

PCTR = PCOTR + PCDTR.

While there is a notable correlation between taking and drawing penalties, for the most part, those taking a lot of penalties do not make up for it by drawing penalties. And the impact of penalty avoidance is generally not watered down by the failure to draw penalties. In other words: avoiding penalties is good, drawing penalties is good, doing both is both better and possible.

Net Transitions – Best

PCTR Penalty Penalty Player Team POS Taking Drawing Other Total Jonathan Toews CHI C 5 3 16 24 Manny Malhotra VAN C 2 -1 20 21 Travis Zajac NJD C 14 -6 12 20 Tyler Bozak TOR C 11 -1 9 19 Darren Helm DET L 5 9 5 19 Martin St. Louis TBL R 18 3 -4 17 Pavel Datsyuk DET C 7 1 9 17

Net Transitions – Worst

PCTR Penalty Penalty Player Team POS Taking Drawing Other PCTR Cody McLeod COL L -24 2 0 -22 Derick Brassard CBJ C -8 -3 -7 -18 Ryan O'Byrne COL D -15 -1 1 -15 Jonathan Ericsson DET D -11 -2 -2 -15 Steve Downie TBL R -24 9 0 -15 Mattias Ohlund TBL D -13 -2 0 -15

You can see that the worst transition players generally spend a considerable amount of unpaired time in the penalty box. Cody McLeod took 36 minors but did little to redeem himself. His overall PC score came in at -12, the lowest amongst skaters. Downie took 33 minors but drew 33 as well. Note how PC does not see this as a wash in this case – Tampa‟s goaltending was awful and symmetry would only hold in front of average goaltending.

The best transition players tended to get to the top of the class either through penalty avoidance or doing the „other‟ things well. Choir boy St. Louis has been discussed already. His penalty avoidance was extra-valuable in front of Tampa‟s crummy netminding. Malhotra was an unsung hero with the Canucks and his heavy lifting was worth 2 points in the standings. Toews was not quite as valuable in this regard but his 16 „other‟ PCTR turned him into the Wayne Gretzky Award winner.

The top 10 PCTR players averaged 73 PC points while the bottom 10 averaged 24 PC points. Good transition players are generally very good players and poor transition players are generally weak players.

Rookies

A lot of famous names have won the Calder Trophy as the NHL‟s top rookie. But a very large number of very good hockey players never got their name on this trophy. Of the NHL‟s top ten all time leading scorers only one, Mario Lemieux, was awarded the Calder (the others – Wayne Gretzky, Mark Messier, Gordie Howe, Ron Francis, Marcel Dionne, Steve Yzerman, Joe Sakic, Jaromir Jagr and Phil Esposito). With this kind of history, I am thinking that Sidney Crosby is happy that he lost out to Alexander Ovechkin in the 2006 voting.

The „finalists‟ for the Calder Trophy were Logan Couture, Michael Grabner and Jeff Skinner, who grabbed most of the interest from voters and won. Skinner was at the top of 71 ballots, but Couture was topped 41 ballots and received strong “secondary support” in the balloting, which lets voters name and rank five players, such that the overall point count was close (Skinner 1,055 – Couture 908).

This was a really big rookie year.

In 2010 just two rookie goaltenders, Jimmy Howard and Tuuka Rask, stood out. This season no new goaltender shone as brightly as those two, but several made their mark and six of the top seven rookie contributions came from the blue paint.

Last season‟s top rookie contribution, from a skater, was posted by defenseman Tyler Myers (88 PC). The top skater score in 2011 came from defenseman John Carlson (90). While the next five skaters were clustered around 50 PC points last season, in 2011 the next five averaged 69 PC.

The top thirteen (six skaters plus the top goaltenders) PC scores in 2011 from rookies are shown below.

Corey Crawford topped the list by becoming Chicago‟s go-to goalie, playing Mark Messier Award in 57 games. His headline stats (33 wins Top Rookie and 2.30 goals against average were impressive and placed him fourth in the Player Team PC Calder Trophy voting. The things that PC Corey Crawford CHI 156 focuses on (3,337 minutes and .919 NSV, James Reimer TOR 130 based on a .917 raw save percentage) also Sergei Bobrovsky PHI 126 impressed. The Blackhawks may have Cory Schneider VAN 102 hoped for this level of performance, but John Carlson WSH 90 had Marty Turco in mind for more playing Devan Dubnyk EDM 85 Michal Neuvirth WSH 84 time. To put Crawford‟s performance in Michael Grabner NYI 78 perspective, his numbers were much like Logan Couture SJS 76 those of Ondrej Pavelec (3,225 minutes, Al Montoya NYI 76 .919 NSV, 162 PC), Tomas Vokoun Jeff Skinner CAR 75 (3,224, .921, 177) and predecessor Anti P.K. Subban MTL 60 Niemi (3,524, .917, 156). Tyler Ennis BUF 58

Crwaford‟s numbers were also somewhat like those of Sergei Bobrovsky (3,017, .919, 126) who won the tussle for ice time in Philadelphia and then was demoted in the off-season. He was seventh in Calder voting.

James Reimer started the season fourth on the Maple Leafs‟ depth chart, getting his chance to play only around mid-season. He had a hot hand from the beginning and the goaltending starved Toronto team played every card in that hand. In 35 starts and 2 relief appearances (2,080 minutes) he posted a .922 NSV (.921 raw save percentage) and was credited with 20 wins. Other Toronto goalies posted just 17 wins in 42 starts. Reimer was just 15th in Calder voting based on less playing time.

Cory Schneider is the Tuuka Rask of the West. He is ready to go (.932 NSV) but stuck behind an elite and clear number one goaltender so that the playing time is just not available (1,372). The Canucks may play him more in 2012, especially if Luongo gets off to one of his infamous slow starts.

Devan Dubnyk‟s story was somewhat like that of Reimer (33 starts, 2,061 minutes, .918 NSV). Michal Neuvirth was less impressive (.909 NSV) in more playing time (2,689 minutes).

Let‟s move on to the skaters. PC says this one was a no-brainer, but the voters did not see John Carlson as the next Tyler Myers. As I have already discussed, Carlson produced at all star levels yet he was fifth in the Calder voting, just slightly ahead of the more flamboyant PK Subban.

The voters, instead, chose Jeff Skinner out of what PC identified as a pack of credible rookie performances by forwards.

Below is the PC detail for the top six rookie skaters:

PCO PCD Player Team POS PC EH PP SH TR SO PCO EH PP SH TR PCD John Carlson WSH D 90 25 4 0 0 0 30 41 1 14 5 60 Michael Grabner NYI R 78 41 3 15 2 0 61 6 0 6 6 17 Logan Couture SJS C 76 36 12 -1 2 1 51 19 1 4 2 25 Jeff Skinner CAR C 75 41 7 0 12 12 72 5 0 0 -2 3 P.K. Subban MTL D 60 15 14 0 8 -1 35 19 3 13 -11 24 Tyler Ennis BUF C 58 27 9 0 0 9 45 10 0 0 3 14

To me this is a really interesting analysis with each player setting benchmarks for the others. Skinner won the prize so let‟s start with him.

The Calder trophy winner‟s even handed offense (25 goals, 20 assists) set the bar for forwards. But PC says that Grabner was just as valuable notwithstanding lower output (26, 15). Why? Grabner had 2 unassisted goals and 67% of his assists were primary versus just 45% for Skinner. Also, it took him just 960 minutes of play for these totals (versus 1,109 for Skinner).

Skinner also put up a wow performance in offensive transitions. His PCOTR score of 12 was driven by a league leading 53 minor penalty draws. On the power play he had 260 minutes ice time, so PC was not that impressed by his 9 goals and 12 assists. Skinner went 4 for 10 in the shootout for 12 PC points. But he looks to be all offense as he generated just 3 PCD. The voters would have missed the nuances of his defense, power play, shootout story and transition game and focused on his rookie leading 63 scoring points.

Grabner never had a shootout chance, so his PCOSO score is zero. And he did not draw penalties like Skinner (just 20 minors). But his wow stat is his short handed offense (15 PCOSH) based on 6 goals (3 unassisted) and 1 assist. His penalty killing was actually very good too but he had just 116 minutes of playing time and so his PCDSH got to just 6. Grabner gets to a slightly higher PC score than Skinner (78 versus 75).

Couture came in at the same level (76 PC) with even handed offense that was a bit off the Skinner/Grabner pace (22 goals, 20 assists, 1,149 minutes, 36 PC) but better power play work (10, 4, 174, 12). Where he rocked was on defense where his 19 PCDEH was the foundation of a 25 PCD score.

PC calls these three forwards about the same. When you remove team luck from this, Grabner moves up and Skinner moves down. When you remove individual luck from this you might let a bit of air out of Grabner‟s goal-scoring numbers. He also had the best quality of teammates. As is common with a young sniper, Skinner played against slightly weaker competition. Voters may have also considered age. Skinner was the only member of the 2010 draft class under consideration and projects to a better career given his entry age.

Tyler Ennis is off the pace across the board, but his shootout contribution (3 goals on 4 attempts) was noteworthy. He finished 11th in the voting.

PK Subban is a hard guy not to notice and finished 7th in the voting. He plays a very forward in-your-face game that makes him look great at times and awful at other moments. His penalty killing was strong. His power play work was good. He drew a lot of penalties but he needs to work on his discipline (-11 PCDTR).

Shootout

There were 149 points contested in the shootout in 2011, down 35 from 2010. About the same number of games (148) were resolved in overtime, up 31 from 2010. PC responds to this by attributing less value to efforts in the fifth period in favour of those in the fourth period.

The sixth annual Wyatt Earp Award, as the most valuable shootout gunslinger, goes Shootout Awards this season to Alex Tanguay. He was successful in a league leading 10 out of a Wyatt Earp Award league leading 16 attempts. His 32 PCOSO Top Shooter points represented about 30% of his total (93 PC points). Most people would have Player Team PC picked Tanguay for this award and, in this Alex Tanguay CGY 32 Jarret Stoll LAK 29 case, PC confirms it for you. Radim Vrbata PHX 21 Tyler Seguin BOS 20 Jarret Stoll was nearly as impactful, potting Mike Ribeiro DAL 17 9 goals in 10 tries for the Kings, driving Frans Nielsen NYI 16 the teams to a 10-2 shootout record. Thomas Vanek BUF 16 Jonathan Toews CHI 15 Radim Vrbata repeated from the 2010 leaderboard with goals in 7 of 11 tries (in Cork Award 2010 he went 8 for 18). The limited Top Stopper history of the shootout suggests that the match is more of a lottery than players Player Team PC would like to admit, but Jonathon Toews Henrik Lundqvist NYR 64 also repeated from the 2010 leaderboard Jonathan Quick LAK 62 with 5 goals in 11 attempts. Marc-Andre Fleury PIT 57 Craig Anderson OTT 52 Mike Ribiero had 6 goals (10 tries) and a Pekka Rinne NSH 49 number of players had 5 in the shootout. Miikka Kiprusoff CGY 45 Of those Thomas Vanek had the fewest Cam Ward CAR 44 tries (6). Frans Neilsen took 8 attempts for the same result.

Rookie Tyler Seguin scored 4 times in 8 attempts. Boston went 2-6 in the shootout for two points in the standings. When you work through the performance of the goaltenders and other shooters you come to the conclusion that Seguin‟s 4 goals were worth about 2 points (20 PC) and the others netted to nothing. For instance, other shooters scored just 2 goals in 16 attempts.

The worst shootout record belonged to Steve Stamkos (0 goals, 7 attempts) His PCOSO score of -6 was matched by Matt Duchene (0 for 6) and Daniel Alfredsson (0 for 3). Ottawa was a really lucky shootout team, generating just 1 marginal goal yet winning 2 of 7 shootouts. This situation amplifies individual success or failure and this is why Alfredsson‟s record scales his PCOSO score to that of Stamkos.

For goaltenders I present the Cork Award for the best stopper in the shootout. As with all of PC, this can be thought of as “performance” x “workload” and most of the leaders had a high exposure to the shootout.

The exception was Craig Anderson who faced just 12 shots. But his 11 saves in the context of Ottawa‟s terrible shootout performance added up to 52 PC points. How does a team with just 2 points from the shootout end up in this situation? It means that the rest of the team was -32 in the fifth period. In fact Brian Elliott had, by far, the NHL‟s worst shootout performance, stopping just 2 of 8 attempts. In the PC calculation his performance is effectively amplified by Ottawa‟s good luck in the shootout and he ended up with a PCGSO score of -19.

The busiest goalie in the shootout was Henrik Lundqvist. He faced 46 attempts and allowed just 7 goals and PC gave him 64 points for those 39 saves. The Rangers went 9- 3 in the shootout. Jonathan Quick had a similar record – 8 goals allowed in 44 attempts. The Kings won 10 of 12 shootout contests. The next highest workload (41 attempts, 29 saves) belonged to Miikka Kiprusoff, but he was out-played by Marc-Andre Fleury (38, 32) and Pekka Rinne (34, 27).

NHL

NHL First Team Second Team Position Name Team PC Name Team PC LW Alex Ovechkin WSH 103 Loui Eriksson DAL 99 C Jonathan Toews CHI 116 Ryan Kesler VAN 103 RW Martin St. Louis TBL 115 Corey Perry ANA 99 D Alex Pietrangelo STL 90 Brett Clark TBL 90 D John Carlson WSH 90 Nicklas Lidstrom DET 88 G Cam Ward CAR 319 Tim Thomas BOS 278

The NHL All-Star Team is selected by the hockey writers.

In goal they had Tim Thomas and Pekka Rinne. As discussed above, although Thomas played better than Ward, he played less and had a poor shootout record. Ward was 9th in the voting and I think that was a terrible oversight.

On defense the voters‟ All-Star team was comprised of Lidstrom, Weber, Chara and Visnovsky. I spent a lot of time on PC‟s assessment before. The ranking here is per the calculations and the ties are broken in the decimal places I don‟t show. What I will add here is that PC had Visnovsky ranked 8th, Weber 11th and Chara 33rd. Pietrangelo, Carlson and Clark received no all-star votes.

PC put Toews and Kesler on the all-star team. The voters had them ranked 3rd and 4th, electing Henrik Sedin as the first team centre. This is a big miss on the part of the voters:

Centre Team PC Jonathan Toews CHI 116 Ryan Kesler VAN 103 Anze Kopitar LAK 90 Steven Stamkos TBL 86 Pavel Datsyuk DET 84 Brad Richards DAL 82 Sidney Crosby PIT 80 Jarret Stoll LAK 80 Jeff Carter PHI 78 Logan Couture SJS 76 Joe Thornton SJS 76 Mike Ribeiro DAL 76 Jeff Skinner CAR 75 Joe Pavelski SJS 74 Danny Briere PHI 74 Jason Spezza OTT 70 Travis Zajac NJD 68 Nicklas Backstrom WSH 68 Alex Steen STL 67 Henrik Sedin VAN 66

You can see that the voters‟ choice for the second term centre (Stamkos) is a better choice. But, as I pointed out before, there is at least one big hole in his game.

On right wing the voters agreed with PC but flipped the order. Given that he won the Hart, it is no surprise that Corey Perry was the voters‟ first team right winger over Martin St. Louis.

On left wing the voters committed the Sedin sin again by electing Daniel over Alex Ovechkin and Loui Eriksson, the choices of the PC system. But Daniel was not as far off the pace as his brother. PC had him in fourth behind the unusual profile of Alex Tanguay. Eriksson was ranked 7th in the voting, another big miss.

Repeating from my 2010 All-PC team were Ovechkin and St. Louis.

West

West First Team Second Team Position Name Team PC Name Team PC LW Loui Eriksson DAL 99 Alex Tanguay CGY 93 C Jonathan Toews CHI 116 Ryan Kesler VAN 103 RW Corey Perry ANA 99 Jarome Iginla CGY 89 D Alex Pietrangelo STL 90 Dan Boyle SJS 82 D Nicklas Lidstrom DET 88 Keith Yandle PHX 81 G Pekka Rinne NSH 255 Roberto Luongo VAN 234

About half of the All-PC team comes from the West.

New faces here include the two goaltenders. Rinne and Luongo were the most obvious candidates, but Jonas Hiller was just 2 points off Luongo‟s pace.

Iginla and Tanguay are the new faces on the wings. On defense the new faces are Yandle, an honourable mention from last year, and Boyle, a repeat from 2010. Lidstom was the only other repeat from last season, although Toews got an “honourable mention”.

This is a pretty balanced team with only Vancouver and Calgary having multiple representatives.

Honourable mention goes to two members of last year‟s team, Anze Kopitar (90) and Pavel Datsyuk (84), as well as Daniel Sedin (86), Brad Richards (82), Bobby Ryan (81), Jarret Stoll (80) and defenseman Niklas Kronwall (80).

East

East First Team Second Team Position Name Team PC Name Team PC LW Alex Ovechkin WSH 103 Nikolai Kulemin TOR 65 C Steven Stamkos TBL 86 Sidney Crosby PIT 80 RW Martin St. Louis TBL 115 Thomas Vanek BUF 95 D John Carlson WSH 90 Andy Greene NJD 73 D Brett Clark TBL 90 Dustin Byfuglien ATL 72 G Cam Ward CAR 319 Tim Thomas BOS 278

According to PC, half of the 12 NHL all-stars were from the East. But the lack of depth in the Eastern Conference shows up in this all-star team.

The new faces (versus the NHL all-star team) are Greene and Byfuglien on defense, Stamkos and Crosby at centre and Vanek and Kulemin on the wings.

Crosby? Yes – King Crosby did in half a season what ordinary superstars do in a full season. The list of top centres (above) shows a lack of depth in the East.

Kulemin? Below is the list of the top left wingers15 in 2011. After Ovechkin, they‟re all from the West:

Left Wing Team PC Alex Ovechkin WSH 103 Loui Eriksson DAL 99 Alex Tanguay CGY 93 Daniel Sedin VAN 86 Rick Nash CBJ 79 Patrick Marleau SJS 74 Henrik Zetterberg DET 70 Ryane Clowe SJS 69 Jamie Benn DAL 67 Nikolai Kulemin TOR 65

Vanek? A very good performance from a player that the Sabres had to pay dearly to keep several years ago (his 95 PC cost $7.1 million in cap hit in 2011).

Ovechkin, Stamkos, Crosby and St. Louis all repeat from last year. Andy Greene repeats from 2010 as well. He is joined on defense by Big Buff.

Tampa Bay placed three on the team and the Capitals placed two.

Carey Price deserves honourable mention with 243 PC points but no all-star berth. The only other player from the East that deserves a special note was Claude Giroux (92).

15 Forwards can shuffle their positions a great deal so any list by position may have some noise in it.

Rookie

Rookie First Team Second Team Position Name Team PC Name Team PC F Michael Grabner NYI 78 Tyler Ennis BUF 58 F Logan Couture SJS 76 Taylor Hall EDM 47 F Jeff Skinner CAR 75 Brad Marchand BOS 46 D John Carlson WSH 90 Mark Fayne NJD 49 D P.K. Subban MTL 60 Cam Fowler ANA 47 G Corey Crawford CHI 156 James Reimer TOR 130

Because younger players move positions around so much I have simply identified the top six forwards (most of whom are listed as centres in your program).

I have already talked about most of these guys. Subban could be an elite defender one day if he channels himself properly. Fayne and Fowler look like very solid defenders. During last season‟s Stanley Cup run I had to keep reminding myself that Marchand was a rookie.

Sergei Bobrovsky, at 126 PC, was just a hair behind Reimer. Honourable mention also goes to Edmonton‟s Jordan Eberle (44). His performance was not far off that of Tay;or Hall, the number one draft pick

How did the Class of 2010 do?

Class of 2010 Name 2010 2011 1st Team LW John Tavares 52 43 C Matt Duchene 56 56 RW T.J. Galiardi 43 13 D Tyler Myers 86 64 D Erik Karlsson 51 68 G Jimmy Howard 244 118 2nd Team LW Jamie Benn 45 67 C Rob Schremp 36 26 RW Niclas Bergfors 38 28 D Victor Hedman 46 52 D Cody Franson 44 47 G Tuukka Rask 186 70

Howard and Rask were about half the men they were in 2010. In the case of Rask this was just the musical chairs of playing time. Howard, on the other hand, had no such excuse. However it is not such an uncommon phenomenon to have a hot young goaltender regress.

Of the others Benn and Karlsson had the biggest jumps. As an unknown, inexpensive, offensively minded defenseman Karlsson should be in your 2012 hockey pool. Tavares,

Myers, Galiardi, Schremp and Bergfors had material declines. I know that Tavares‟ 28 goals and 38 assists sounds really impressive, but he took a lot of ice time to get there (1,231 and 277 minutes while even handed and on the power play respectively) and his defense is awful.

The Class of 2009:

Class of 2009 Name 2009 2010 2011 1st Team LW Chris Versteeg 57 52 48 C Patrik Berglund 57 20 41 RW Bobby Ryan 58 66 81 D Drew Doughty 48 104 67 D Matt Hunwick 37 28 16 G Pekka Rinne 187 142 255 2nd Team LW James Neal 50 54 53 C T.J. Oshie 49 63 55 RW Blake Wheeler 50 29 41 D Brian Lee 37 13 20 D Zach Bogosian 35 38 29 G Steve Mason 169 23 29

Rinne is the biggest story from the 2009 class, jumping to elite status in his third season. The only other nice jump up came from Bobby Ryan. Drew Doughty had that super sophomore year that he could not come close to in 2011. The others have been drifting sideways, or worse.

Green (23 and under)

Green First Team Second Team Position Name Team PC Name Team PC LW Jamie Benn DAL 67 Milan Lucic BOS 43 C Jonathan Toews CHI 116 Anze Kopitar LAK 90 RW Claude Giroux PHI 92 Bobby Ryan ANA 81 D Alex Pietrangelo STL 90 Kris Letang PIT 71 D John Carlson WSH 90 Erik Karlsson OTT 68 G Carey Price MTL 243 Ondrej Pavelec ATL 162

I lowered the age limit for this team in 2011. It actually did not change the picture very much.

Forwards tend to peak at an early age, but the only 23-and-under member of the NHL All-PC team was PC‟s MVP, Jonathan Toews (22). Giroux (22) made such an impact in Philadelphia that Mike Richards and Jeff Carter became expendable. Kopitar (23) was an honourable mention last season. As noted above, Bobby Ryan (23) has shown a lot of growth (something that is not automatic in a young player).

This team is a bit thin on the left wing. Other forwards deserving honourable mention are Sidney Crosby (age 23, 80 PC), Steven Stamkos (20, 86) and Patrick Kane (22, 71), who were members of last year‟s team, and the trio of rookies discussed above: Grabner (23, 78), Couture (21, 76) and Skinner (18, 75). Ovechkin and Eriksson graduated from the 2010 team and now are cornerstones of the All-PC team.

Defenders generally take longer to hone their craft, but Pietrangelo (20) and Carlson (20) are on PC‟s All-NHL team. Letang (23) is now recognized as one of the NHL‟s best defensemen. And Karlsson (20) has shown a lot of growth. Honourable mention goes to Drew Doughty (21, 67) and Tyler Myers (20, 64), members of this team in 2010. Mike Green and Keith Yandle graduated from the 2010 team (Yandle was the only victim of a lowered age limit).

Goalies generally require the most seasoning. But Carey Price (23) has achieved an elite level of play and looks like Canada‟s future international goaltender. Montreal made the right call investing in Price and dispatching Halak to St. Louis. Pavelec (23) looks like a solid netminding foundation for the Jets‟ building process.

Note that, for both of the Green and Grey teams, I used the player‟s age as of January 1, 2011 (mid season) to determine eligibility.

Grey (33 and over)

Grey First Team Second Team Position Name Team PC Name Team PC LW Patrik Elias NJD 62 Ray Whitney PHX 47 C Danny Briere PHI 74 Andy McDonald STL 61 RW Martin St. Louis TBL 115 Jarome Iginla CGY 89 D Nicklas Lidstrom DET 88 Dan Boyle SJS 82 D Brett Clark TBL 90 Lubomir Visnovsky ANA 79 G Tim Thomas BOS 278 Tomas Vokoun FLA 177

Carry-overs from the All-NHL team are St. Louis (35) and Lidstrom (40), who were the only repeats from 2010, and Clark (34) and Thomas (37), who was a 2009 Grey Team member. Clark was the “rookie of the year” amongst skaters. St. Louis was the team‟s MVP.

Boyle (34) was a Western All-Star and Visnovsky (34) was close. Kimmo Timonen (age 35, 65 PC) was a member of last year‟s team and put in another solid season. Other older defensemen with fine seasons were Stephane Robidas (33, 64), Zdeno Chara (33, 60) and Joe Corvo (33, 59).

Ray Whitney (38) has now made this team four years running. Iginla, Briere and McDonald are all 33 years old and now eligible for the Grey team. Elias (34) makes his first appearance in his first year of eligibility as well. Honourable mention goes to the ageless Teemu Selanne (40, 62).

Martin St. Louis (34) was the Grey Team (skating) rookie of the year, with 90 PC points and a growing trophy collection. Alfredsson (37) and Whitney (37) three-peated from 2008 and 2010. The other forwards were Andrew Brunette (36)¸ Saku Koivu (35) and Vinny Prospal (34). Honourable mention goes to Jamie Langenbrunner (age 34, 57 PC), Teemu Selanne (39, 56), Mike Knuble (37, 55) and Alex Kovalev (36, 52).

Graduating to the Grey Team in goal was Tomas Vokoun (34) after a long career atop the PC goaltender rankings.

But here is the story with age:

Grey Team 2010 Name 2010 2011 1st Team LW Andrew Brunette 64 44 C Saku Koivu 56 33 RW Martin St. Louis 91 115 D Chris Pronger 102 32 D Nicklas Lidstrom 100 88 G Evgeni Nabokov 244 DNP 2nd Team LW Ray Whitney 51 47 C Vinny Prospal 51 17 RW Daniel Alfredsson 77 19 D Brian Rafalski 83 53 D Kimmo Timonen 73 65 G Martin Brodeur 161 7

The members of last year‟s Grey team had very substantial declines in performance. Only Martin St. Louis managed to up his game. A more normal pattern is a decline of about 20% in PC. Examples are Lidstrom and Timonen. Both were off about 12%. Whitney is aging gracefully (-8%). But most of last year‟s team fell off a cliff (Prospal and, to a lesser extent, Pronger were held back by injuries).

Offense

Offense First Team Second Team Position Name Team PCO* Name Team PCO* LW Daniel Sedin VAN 74 Alex Ovechkin WSH 73 C Steven Stamkos TBL 89 Ryan Kesler VAN 82 RW Corey Perry ANA 98 Martin St. Louis TBL 82 D Dustin Byfuglien ATL 57 Nicklas Lidstrom DET 43 D Lubomir Visnovsky ANA 55 Keith Yandle PHX 41

* PCO excluding shootouts.

Shootout performance has proven to be somewhat non-repeatable. So my evaluation of offense, for this purpose, is PCO before the shootout. Here is how PCO* compares to

Copyright Alan Ryder, 2011 Hockey Analytics www.HockeyAnalytics.com 2011 NHL Review Page 74 scoring points for the „scoring‟ leaders in the NHL (I carry lots of decimal places in the calculations so watch out for rounding):

PCO Player Team POS G A Pts EH PP SH TR PCO* Corey Perry ANA R 50 48 98 58 26 10 4 98 Steven Stamkos TBL C 45 46 91 57 29 0 3 89 Martin St. Louis TBL R 31 68 99 55 27 -1 1 82 Ryan Kesler VAN C 41 32 73 35 28 5 14 82 Daniel Sedin VAN L 41 63 104 50 33 0 -9 74 Alex Ovechkin WSH L 32 53 85 58 11 0 4 73 Claude Giroux PHI R 25 51 76 41 12 11 7 71 Jonathan Toews CHI C 32 44 76 39 17 1 13 71 Sidney Crosby PIT C 32 34 66 47 13 2 8 70 Jarome Iginla CGY R 43 43 86 50 18 0 1 69 Bobby Ryan ANA R 34 37 71 57 6 1 4 68 Danny Briere PHI C 34 34 68 53 9 0 4 66 Thomas Vanek BUF R 32 41 73 43 21 0 2 66 Eric Staal CAR C 33 43 76 38 19 6 -1 61 Michael Grabner NYI R 34 18 52 41 3 15 2 61 Henrik Zetterberg DET L 24 56 80 33 24 1 2 61 Jeff Carter PHI C 36 30 66 52 10 -1 -1 60 Jeff Skinner CAR C 31 32 63 41 7 0 12 60 Pavel Datsyuk DET C 23 36 59 39 13 1 6 59 Teemu Selanne ANA R 31 49 80 34 28 0 -4 58

The PC calculation essentially adjusts scoring points in the following fashion:

 Goals are given more weight than assists. There is actually much more to this re- balancing but my position is that a scoring point is a very crude and inaccurate assessment of offense. This is why players with high (relative) assist levels, such as St. Louis and Zetterberg, slide down in the rankings and Perry and Stamkos rise.

 There is some credit for “plusses” that don‟t show up in the scoring totals at all. This is especially true on the power play where team play is amped. Toews and Staal were both on-ice for 24 even handed goals where they were credited with no scoring points. But Crosby had just 4 (in half a season of work) and Grabner and Selanne each had just 7. On the power play, Kesler had 26 no-point plusses and Stamkos had 21.

 Ice time is „taxed‟ to get to value added above that of a marginal player. This is explains why Crosby (41 games) and Datsyuk (56) move up the list. These two had just 899 and 1,082 minutes of play respectively. But of those players who got

in close to a full season of play ice time ranged from 1,830 minutes (Perry) down to 1,146 (Grabner). So Grabner goes up and Perry goes down.

 The rate of tax is situational. Much more offense is created on the power play and much less while short handed. This means that marginal performance is higher on the power play and lower while short handed. The offense generated on the penalty kill by Grabner (6 goals, 1 assist), Giroux (3, 4) and Perry (4, 1) is „taxed‟ lightly and stands out. On the power play, Ovechkin recorded 7 goals and 17 assists in 354 minutes for 11 PCOPP. Jeff Carter delivered less (8 goals, 9 assists) but occupied just 235 minutes of ice time. PC gave Carter roughly the same score (10 PCOPP) as he left 119 minutes of ice time for someone else to use. In other words, Ovechkin‟s work in 119 extra minutes was nearly marginal. PC lets some air out of the power play records of Stamkos (373), St. Louis (370), Staal (361) and Ovechkin (354) as the leaders in power play ice time. Selanne (16 goals, 18 assists, 253 minutes, 28 PCOPP) and Zetterberg (10, 20, 260, 24) end up with PCOPP scores like those Stamkos (17, 19, 373, 29) and St. Louis (4, 37, 370, 27). They produced less but consumed less ice time.

 The tax rate varies by position. Less offense is generated by defensemen (the marginal level of performance is lower), especially while even handed. Dustin Byfuglien‟s record of 20 goals and 33 assists looks a lot like that of Jussi Jokinen (19 goals, 33 assists), but Big Buff gets 57 PCO and Jokinen settles for 35.

 Penalty drawing does not show up in the „points‟ column. But drawing penalties generates observable offense (see Skinner). Other transitions also tilt the ice in favour of (see Toews and Kesler) or against (see Sedin) teammates.

 PC is denominated in points in the standings. Individual performance is scaled by a team‟s ability to translate its offense and defense into points, whether by good fortune or through skill (an ability to win close games). In 2011 Tampa Bay was very efficient in translating goals into wins, improving the PC scores of Stamkos and St. Louis by about 8%. Chicago was inefficient and Toews takes part of the blame and a haircut of about 6% in his scores.

Defense

Defense First Team Second Team Position Name Team PCD Name Team PCD LW Loui Eriksson DAL 43 Patrik Elias NJD 31 C Travis Zajac NJD 47 Dana Tyrell TBL 38 RW Adam Hall TBL 39 Martin St. Louis TBL 33 D Brett Clark TBL 70 John Carlson WSH 60 D Andy Greene NJD 65 Paul Martin PIT 60

Andy Greene and Martin St. Louis repeat from last season. Zajac received an honourable nod in 2010.

As discussed above, the defense of Martin St. Louis is largely comprised of penalty avoidance (something he does very well). Three other Lighting players are on this roster and I discussed this at length earlier. Tampa Bay was a good defensive team. 1-3-1 anyone? New Jersey has historically been a strong defensive team. Three Devils are on the team and Paul Martin is one that got away. For the record, in assessing defense, it is challenging to take the team out the player.

Centres have a generally higher defensive responsibility. Honourable mention should go to centres Samuel Pahlsson (38), Nate Thompson (37) and Anze Kopitar (35).

Even Handed

Even Handed First Team Second Team Position Name Team PCEH Name Team PCEH LW Alex Ovechkin WSH 82 Loui Eriksson DAL 69 C Jonathan Toews CHI 75 Anze Kopitar LAK 70 RW Martin St. Louis TBL 89 Jerome Iginla CGY 71 D John Carlson WSH 72 Alex Pietrangelo STL 64 D Trevor Daley DAL 65 Brett Clark TBL 64

PCEH = PCOEH + PCDEH + PCOTR + PCDTR

The NHL‟s so-called more open game really is not. The reality is that there is more scoring mainly because there is less even handed time. But about two-thirds of the game is played even handed. And you don‟t need a degree in math to figure out that this still matters more than power play time.

My definition of PCEH includes ALL of the „transition‟ factors, mainly penalty drawing and penalty taking. Note that this is a simplification as penalties are drawn/taken when not even-handed. While the NHL does give enough information to split it out it is a considerable amount of work. I have better things to do.

St. Louis was the NHL‟s top even handed player (89 PCEH) and one of only two players to repeat from last season‟s team. Ovechkin was the other, ranking second overall in even handed play. Crosby would have repeated if not for a large headache.

Toews is your number one even-handed centre. Kopitar was similar in his scoring profile. His even handed defense was better, but Toews had top transition numbers.

Eriksson and Ovechkin‟s were the two top defensive forwards on this team. Eriksson bettered Ovechkin‟s transition game (which has been improving) but could not compete on offense.

Iginla made the team with his defense. His even handed offense (50 PCOEH) was bettered by Ovechkin (58), Perry (58), Stamkos (57), Ryan (57), St. Louis (55), Briere (53), Carter (52) and Nash (51), but he was out-defensed by only St. Louis.

On defense the new name is Trevor Daley who trailed only Brett Clark in even-handed defense. Keith Yandle nearly repeated with 62 PCEH.

Power Play

Player Contribution reduces to “performance” x “ice time”. Here is where playing time really matters. This is not a list of the “best” power play performers, it is a list of the biggest contributions on the power play. Frequently this list is dominated by the brute force of ice time, but this season the finesse shone through.

Power Play First Team Second Team Position Name Team PCPP Name Team PCPP LW Daniel Sedin VAN 34 Dany Heatley SJS 27 C Ryan Kesler VAN 29 Joe Thornton SJS 26 RW Teemu Selanne ANA 28 Corey Perry ANA 26 D Nicklas Lidstrom DET 31 Dan Boyle SJS 24 D Christian Ehrhoff VAN 27 Lubomir Visnovsky ANA 22

PCPP = PCOPP + PCDPP

As you can see, success was a team effort.

Daniel Sedin (18 goals, 24 assists, 296 minutes) was the NHL‟s top power play performer by some distance. Kesler (15, 15, 297) was a very regular compatriot. The Canucks had the NHL‟s top power play and placed three players on the first PP team, including Christian Ehrhoff (6, 22, 281). Henrik Sedin (8, 27, 295) came in just of the all-star pace at 24 PCPP.

San Jose ranked second overall and placed three players on the second team. The number one unit was Heatley (11 goals, 19 assists, 258 minutes, 27 PCPP), Thornton (9, 24, 271, 26), Joe Pavelski (11, 17, 249, 25), Patrick Marleau (11, 15, 274, 22) and Dan Boyle (7, 10, 326, 24).

The ageless Selanne (16 goals, 18 assists, 253 minutes) was frequently accompanied by Perry (14, 17, 288). The Ducks‟ PP ranked third overall and they placed three players on this team including point man Visnovsky (5, 26, 336).

Heatley and Selanne are the only repeats from 2010.

Lidstrom (7, 32, 332) was the only player to break the west coast power play cartel and was the NHL‟s second most valuable PP contributor.

The duo of Stamkos (17 goals, 19 assists, 373 minutes, 26 PCPP) and St. Louis (4, 37,370, 24) used up too much ice time to make the team.

The worst performance on the power play was probably that of Jacub Voracek of Columbus. He spent 237 minutes with a man advantage and delivered just 2 goals and 6 assists. PC assessed that at -1 PCPP.

Short Handed

Short Handed First Team Second Team Position Name Team PCSH Name Team PCSH F Frans Nielsen NYI 24 Michael Grabner NYI 21 F Jamie Benn DAL 22 Matt Cooke PIT 20 D Willie Mitchell LAK 21 Zbynek Michalek PIT 19 D Jan Hejda CBJ 20 Brett Clark TBL 19

PCSH = PCOSH + PCDSH

For forwards it is common to get to the head of this class with offense. The short handed offense generated on the penalty kill by Frans Neilsen (7 goals, 1 assist), Michael Grabner (6, 1), Jamie Benn (4, 2) and Matt Cooke (3, 3) were the reasons for their first team positions at forward. His scoring (with some defense) makes Nielsen the short handed player of the year.

Brad Marchand actually had the NHL‟s best short handed scoring record of 5 goals and 1 assist in just 121 minutes for a league leading 13 PCOSH. But his penalty killing record was not so strong (3 PCDSH).

Of the four forwards Matt Cooke had the greatest impact in the defensive zone. But none of these four were elit penalty killers. If you ignore the offense and just look at penalty killing you get the following results (which do not look very different for defenders).

Penalty Killing First Team Second Team Position Name Team PCDSH Name Team PCDSH F Samuel Pahlsson CBJ 16 Dana Tyrell TBL 15 F Adam Hall TBL 15 Max Talbot PIT 14 D Jan Hejda CBJ 19 Brett Clark TBL 19 D Willie Mitchell LAK 19 Chris Phillips OTT 19

With a league leading MGDSH of 37, Tampa Bay placed three players on the All-PK team. With awful goaltending, the Lightning still managed to rank 7th in the conventional metric of penalty killing percentage. As noted before, Hall and Tyrell were not a regular PK pairing and Clark was way down the depth chart on defense.

Chris Philips is now a three-peater on the top PK list. His 290 minutes of ice time was just off the league lead (Anaheim‟s Toni Lydman led with 291) and he had a solid 5.78 GAASH for 19 PCDSH. Clark had a stunning 1.56 GAASH in just 116 minutes of PK play in front of poor goaltending. Hejda spent 219 minutes short handed with a 6.09 GAASH (again, poor goaltending). Mitchell, playing in front of better goaltending, had a 3.09 GAASH in 194 minutes.

These performances would seem to be hard to compare, but PC does that for you leveling out the effects of ice time and goaltending.

As you can see, each of the defenders had the same PCDSH score of 19. Michalek also posted 19 PCDSH but he sorted out of the top four based on the decimal places. Pittsburgh led the NHL in the conventional metric of penalty killing percentage (86.1%). After factoring in the strong goaltending, the Penguins slip to second in MGDSH with 33. You can see that Talbot and Cooke had something to do with that.

Sammy Pahlsson (6.43 GAASH, 233 minutes) was the only player to repeat as a forward. Teammate Derek Doresett (3.56 GAASH, 118 minutes) missed the team by a few decimal places.

Most Valuable Performances

In a sense value is a relative thing. When two players produce the same outputs, a team would prefer the player with the smaller paycheck. And, in today‟s salary cap era, certain contracts are seen as liabilities because no plausible performance can justify the cost.

In this spirit I present the All-Value teams for 2011:

All Value First Team Second Team $ PC $ PC Position Name Team Cost Name Team Cost LW Jamie Benn DAL 12,245 Lauri Korpikoski PHX 12,903 C Frans Nielsen NYI 8,717 Nate Thompson TBL 13,112 RW Claude Giroux PHI 8,942 Michael Grabner NYI 10,801 D Jason Demers SJS 8,837 Andy Greene NJD 10,145 D John Carlson WSH 9,391 Mark Fayne NJD 11,057 G James Reimer TOR 4,579 Corey Crawford CHI 5,131

PC Cost is the Cap Cost per PC point. I used the annual cap cost (in US dollars) per annum, rather than the per diem approach used in the NHL‟s CBA, to screen out players with limited playing time but high per game PC scores.

Obviously a lower PC Cost is better and the table above shows the value leaders. To put these costs into perspective, a salary cap of about $56.7 million suggests that an average player on a playoff bound team should cost around $56,700 per annum per PC point16.

Greene and Nielsen are repeaters from 2010. In fact Nielsen records a three-peat. Repeats are uncommon as it tends to be the nature of the group that they either have a very unusual year or they are coming off an old contract.

Nielsen remains on his contract through the coming season. Benn, Carlson and Fayne also have unexpired contracts.

16 A team with playoff aspirations needs to target a 100 point season. This translates into 1000 PC points and gives you my average cost per PC point. A Stanley Cup team is likely to be better than this and needs to have a lower average cost per PC point.

James Reimer was the value leader in 2011 with 130 PC for $597,000 of cap hit. Crawford cost $800,000 for 156 PC. Jimmy Howard was the obvious value leader in the NHL in 2010 and was the third ranked goalie in 2011 (still at a cap cost of $717,000).

Among skaters the value leader was again Frans Nielsen, who delivered 60 total PC points based on 13 goals, 31 assists, 1,261 minutes, 8 shootout goals and much more. His salary cap hit was at the minimum - $525,000.

The most valuable performance by a player in a defending role belonged to Jason Demers – 61 PC points at a cap cost of $543,000. The best PC outputs on the team came from Giroux (92 PC at a cap cost of $822,000) and Carlson (90, $846,000).

All Cap Roster

If all NHL players had been free agents at the beginning of the 2011 season and could have been signed for their then current cap cost, who would you want on your team? Herein I present my All Cap roster. This is a list of 23 players you might want to have on your team if you were prepared to max out your cap costs while attempting to max out performance.

This was a pretty subjective exercise. I am sure there is a mathematical solution to this optimization problem. But I know that any solution would involve a lot of variables and constraints and would tax my computer (never mind my programming skills). So I did this by eye.

The rules I used to put this together and evaluate the output are:

 Cap Cost < $56,700,000

 14 forwards, 7 defensemen, 2 goaltenders.

 Players play in position and are seeded into a depth chart for each situation.

 Players are attributed ice time (MOITOT) based on their position in the depth chart:

o The prima goalie gets 3,700 minutes (about 61 games). The second fiddle gets 1,300 minutes (about 21 games).

o Even handed, first line forwards are assumed to play 1,100 minutes, second line 1,000 minutes, third line 800 minutes and the fourth line 500 minutes. The top power play unit gets 300 minutes, the second unit 250 minutes, the third unit 100 minutes and the fourth unit 50 minutes. The top penalty killing pair gets 250 minutes, the second pair 175 minutes, the third pair 100 minutes and a fourth pair 50 minutes.

o Even handed, first defensive pair is assumed to play 1,400 minutes, second pair 1,200 minutes and the third pair 900 minutes. The top power play unit gets 300 minutes, the second unit 150 minutes and the third unit 50

minutes. The top penalty killing pair gets 300 minutes, the second pair 200 minutes and the third pair 100 minutes.

o The two press box forwards are each assumed to play 450 even handed minutes and the press box defenseman is assumed to play 600 minutes (of which 25 is power play and 25 is short handed) during the injuries, slumps and trips to the coach‟s doghouse of main roster players.

Below is my All Cap Roster. If you can find a more optimal one, share it with me.

All Cap Roster – 2011

Actual Projected Position Name Team CapCost MOI PC MOIEH MOISH MOIPP MOITOT PC LW1 Loui Eriksson DAL 4,266,667 1,625 99 1,100 0 250 1,350 78 C1 Sidney Crosby PIT 8,700,000 899 80 1,100 0 250 1,350 121 RW1 Martin St. Louis TBL 5,250,000 1,720 115 1,100 0 250 1,350 91 LW2 Daniel Sedin VAN 6,100,000 1,521 86 1,000 100 300 1,400 83 C2 Jonathan Toews CHI 6,300,000 1,661 116 1,000 50 300 1,350 96 RW2 Corey Perry ANA 5,325,000 1,830 99 1,000 100 300 1,400 80 LW3 Jamie Benn DAL 821,667 1,243 67 800 175 50 1,025 69 C3 Logan Couture SJS 1,241,667 1,408 76 800 0 100 900 48 RW3 Claude Giroux PHI 821,666 1,591 92 800 175 100 1,075 65 LW4 Alex Tanguay CGY 1,700,000 1,561 93 500 0 100 600 47 C4 Frans Nielsen NYI 525,000 1,261 60 500 250 50 800 53 RW4 Michael Grabner NYI 843,333 1,146 78 500 250 0 750 73 F5 Darren Helm DET 912,500 1,091 64 450 50 0 500 30 F5 Teddy Purcell TBL 750,000 1,142 60 450 0 50 500 27 F 44,207,500 19,700 1,185 11,100 1,150 2,100 14,350 964 D1 John Carlson WSH 845,833 1,857 90 1,400 300 50 1,750 90 D1 Alex Pietrangelo STL 3,166,666 1,738 90 1,400 100 150 1,650 84 D2 Brett Clark TBL 1,500,000 1,548 90 1,200 200 150 1,550 101 D2 Keith Yandle PHX 1,200,000 1,999 81 1,200 100 300 1,600 64 D3 Andy Greene NJD 737,500 1,834 73 900 300 50 1,250 57 D3 Mark Giordano CGY 891,667 1,898 69 900 200 300 1,400 57 D4 Jason Demers SJS 543,333 1,462 61 550 25 25 600 26 D 8,884,999 12,336 554 7,550 1,225 1,025 9,800 479 G1 Carey Price MTL 2,750,000 4,206 246 3,700 224 G2 James Reimer TOR 596,667 2,080 130 1,300 86 G 6,286 376 5,000 310 TEAM 55,789,166 2,116 1,753

Goal

Carey Price is my starting goalie at $2,750,000 (all „salary‟ data is the cap cost – the average annual paycheque over the contract). His projected PC goes down a little mainly on the basis of less ice time. James Reimer was hard not to choose for the backup

Copyright Alan Ryder, 2011 Hockey Analytics www.HockeyAnalytics.com 2011 NHL Review Page 82 position. He started the season deep in the Maple Leafs goaltending depth chart but got his chance midseason. His performance was at about the same level of Price but he got less ice time. Last season‟s starter for this team, Jimmy Howard, would remain a good choice with a $717,000 cap hit. Other strong candidates included Corey Crawford ($800,000 for 156 PC in 3,337 minutes) and Cory Schneider ($900,000 for 102 PC in just 1,372 minutes).

Defense

This is the cheapest defensive corps I have ever put together. The good news starts with the performances of Carlson and Clark. But it continues through returnees Yandle and Greene.

Based on ice time profiles I paired Carlson and Pietrangelo as the first even handed duo. Clark actually had the best even handed numbers but had the lowest ice time of this group of blueliners. With Yandle, I gave him second-pairing minutes.

I gave Greene third pairing even handed ice time but matched him with Carlson as the top penalty killing pair. Giordano got third pairing even handed ice time but second pairing (with Clark) PK time. Clark projects out as the best penalty killer based on his 2011 results, but his ice time profile suggests a second tier assignment.

Each of these players is comfortable on the power play. Giordano and Yandle produced best on the power play. So my algorithm gives them each 300 minutes of time with the man advantage. Next best were Clark and Pietrangelo.

The seventh defender is youthful Jason Demers, a well rounded defenseman (who, of course, works cheap). PC ranked him as the number two defenseman in San Jose.

At $3,167,000 Pietrangelo is the most expensive defender but his cost, $35,024 per PC point, is still below budget.

As the shopping was better this year, this team‟s defense cost less ($8.9 million versus $12.3 million in 2010 and $17.9 million in 2009) but is also projected to produce less (479 versus 513 PC points).

Forwards

All of this modeling assumes modest down time for injuries and Crosby missed half a season. Top line ice time on this team over a „full‟ season projects him to 1,100 even handed minutes. His relative strength is even handed play. So have the Crosby line seeded as the second power play unit. My model does not give any penalty killing time. His shootout success was much more limited than in the past and the model ranks him fourth on the shootout depth chart. Nevertheless he still projects out to be this team‟s most valuable skater at 121 PC. At $8,700,000 he is not cheap, but he is Crosby and plays up to his contract.

His wingers would be Eriksson and St. Louis. They are also top even handed players but tier two power play performers on this team. The entire first line is comprised of repeats from 2010. In fact, Eriksson has now been named to this team three years running, notwithstanding a near tripling of his cap hit in 2011.

The second best even handed players, Toews, Perry and Daniel Sedin, would also be the top power play unit. Sedin was the most productive power player in the league in 2011. While even handed, Toews would likely protect the team from the weak defense of his wingers and he projects out as the team‟s second most valuable skater (and second most expensive). Perry gets the biggest haircut in ice time (all players on this team are used to much more playing time than they would receive on such a team) so he won‟t score 50 goals for this team.

Overall the “top six” forwards are paid top six dollars. The third line is comprised of three very good, young, inexpensive players – Benn, Couture and Giroux. The two wingers would form the second penalty killing unit.

Frans Nielsen also repeats from 2010. His performance and cap hit make him very hard to exclude form such a team. He would be one of the team‟s top tie penalty killers and an potent weapon in the shootout. I picked Alex Tanguay for the fourth line for his solid overall performance and stellar shootout record (all for the low, low price of $1,700,000). Rookie Michael Grabner fit in too well not to be selected. He would join teammate Nielsen on the PK.

The press box forwards, Helm and Purcell, are both very solid, inexpensive players would provide PK and PP depth respectively.

All of these forwards can score. Nearly all could play the power play. Some of them may have to learn to play some defense for this team.

With these players the shootout depth chart would probably be topped by Tanguay, Toews and Nielsen. Crosby has historically been very effective in the shootout but was not in 2011.

The forwards cost $43.6 million in 2011, up a bit from last season ($42.5 million) but are projected to perform at much higher level (964 versus 860 PC points).

Overall

This team comes in about $900,000 under budget. The defensive spend is down from 2010 and that permitted the spend on the Carey Price contract. I considered Tim Thomas for the team, and it may have turned out to be a better team with him, but the inexpensive goaltending that I chose enables performance potential elsewhere. Looking backwards it is not hard to find inexpensive goaltenders (not so easy to do looking forward).

There are five contracts north of $5 million (of annual cap cost) – Crosby, St. Louis, Sedin, Toews and Perry. But these guys earned that kind of paycheck in 2011. Except for goaltenders, it is only extreme performance that can justify a contract north of $5

Copyright Alan Ryder, 2011 Hockey Analytics www.HockeyAnalytics.com 2011 NHL Review Page 84 million. In retrospect it is easy to find value in large contracts ... but it is not so easy to do looking forward.

These players combined for 2,116 PC points, down from 2,287 PC in 2010. But the playing time of almost all of these players needs to be scaled back and this team projects out to 1,753 PC points (or 175 points in the standings). That would not happen for two big reasons:

 There are only 164 points (1640 PC points) up for grabs.

 Although winning is a linear (additive) function of individual performance over the normal range of team play, this team ain‟t normal. A really good team, such as this, faces an increased headwind in its winning percentage. But this team could be a 140 point team … and a Stanley Cup shoo-in.

Over the past few seasons I have had some fun forecasting the careers of Sidney Crosby and Alexander Ovechkin. I invited Evgeni Malkin into the process once but I have concluded that he is not in the same league as King Crosby and Alex the Great.

Unfortunately for everyone (and I mean everyone), Sid may no longer be “in the same league” either. Two hits, by David Steckel and Victor Hedman, halved his season and may have permanently altered his career trajectory. The projection of his future performance is now a much riskier proposition. Time will tell.

Ovechkin and Crosby entered the NHL in the same year (2006) and the Russian won round one, capturing the Calder Trophy as the NHL‟s top rookie. Crosby won the Art Ross and Hart Trophies in 2007 to claim round two. But Ovechkin trumped that in 2008 with an unprecedented sweep of the Ross, Richard, Hart and Pearson Trophies and stretched his lead in 2009 with repeat Richard, Hart and Pearson Trophies. In 2010 Crosby got his name on the Richard Trophy (he shared it with Stamkos) to continue the see-saw battle. In 2011 both players suffered a hardware outage. While Ovechkin looked less special, Crosby was on-plan for his own quadruple (Ross, Richard, Hart and Lindsay) until his concussion(s).

These players are such great talents and still so young. So the question just dangles – how good could they be over time?

The answer to this question is in career projections. This exercise is much like trying to forecast the weather over the long term – accuracy is very challenging. But the exercise is awfully interesting. The best approach to this is to find a group of similar players and study their performance over time. Below are the 18 players I selected for inclusion in the comparison group and their career summary scoring statistics.

To properly conduct that analysis it is necessary to pay attention to three large factors – age of entry into the NHL, experience and playing time. In the case of a teenage phenom this analysis is made easier as raw skill development, experience and playing time all tend to blossom in concert.

But the analysis is made more challenging by a very limited number of comparisons. The comparison group I formed is comprised of players who, like Crosby, were well

Copyright Alan Ryder, 2011 Hockey Analytics www.HockeyAnalytics.com 2011 NHL Review Page 86 established at an elite level of competition prior to the age Peer Group of 20. Over the history of the NHL, this is an awfully small Player GP G A Pts group of players. Wayne Gretzky 1,487 894 1,963 2,857 Mark Messier 1,602 658 1,146 1,804 Ovechkin was 20 years old Ron Francis 1,731 549 1,249 1,798 when he entered the NHL, Steve Yzerman 1,514 692 1,063 1,755 losing a year to the lockout. I Mario Lemieux 915 690 1,033 1,723 think it is fair to conclude that Joe Sakic 1,363 623 1,006 1,629 Jaromir Jagr 1,273 646 953 1,599 he could have played in the Dale Hawerchuk 1,188 518 891 1,409 league as a teenager and can Mike Gartner 1,510 735 652 1,387 be compared to this peer Brendan Shanahan 1,490 650 690 1,340 group. Denis Savard 1,196 473 865 1,338 Pierre Turgeon 1,294 515 812 1,327 To be a useful part of the Mats Sundin 1,305 555 766 1,321 analysis it is also necessary Dave Andrechuk 1,597 634 686 1,320 for a player to have a Pat Lafontaine 865 468 545 1,013 complete or nearly-so career Eric Lindros 760 372 493 865 (all of these players have now Jimmy Carson 626 275 286 561 retired). Furthermore the Sylvain Turgeon 669 269 225 494 game changes over time and it is desirable to keep the comparison group recent. To that end most of the comparable players were born in the 1960s.

It is clear from this list that Crosby and Ovechkin are in very good company. This group has averaged 1,244 games played, 568 goals, 851 assists and 1,419 points over their careers.

To use this historical data one needs to adjust for changes in rates of scoring over time. To the right is a graph of the per-game scoring rates, by age, for this comparison group after adjusting scoring to the context of the 2011 season. This graph shows the significant growth of goal scoring and playmaking skills through the age of 23. Thereafter goal scoring tends to go into gradual decline. Playmaking tends to grow at about the same pace as goal scoring through the age of 23 but the growth continues on, peaking several years later. As point totals are dominated by assists, they tend to peak around the age of 27. Offensive skills are

Copyright Alan Ryder, 2011 Hockey Analytics www.HockeyAnalytics.com 2011 NHL Review Page 87 clearly in retreat over the age of 30, eroding quickly beyond the age of 37. Note that this analysis is of per game scoring rates. The forces of injury and retirement also reduce the average number of games played by attained age.

Adjusting scoring to the context of the current season is more complex work than you might think and moves the peer group expectations around from year to year. In 2011 scoring and playmaking were down a bit with the effect that the normalized career projections for Crosby and Ovechkin creep up a tad.

How do Crosby and Ovechkin compare to this group?

The table below shows that King Crosby has trumped the competition. Over his career (per game played, normalized to today‟s scoring environment) he has out-performed the peer group – 35% more goals, 55% more assists and 47% more points.

Age 18 19 20 21 22 23 Career Crosby Games Played 81 79 53 77 81 41 412 Goals 39 36 24 33 51 32 215 Assists 63 84 48 70 58 34 357 Points 102 120 72 103 109 66 572 Adjusted Peer Group * Games Played 70 72 75 72 72 72 433 Goals 21 24 30 30 31 35 171 Assists 30 36 43 44 45 49 247 Points 51 60 73 74 76 84 418 Ratio to Peers per GP Goals 159% 137% 114% 102% 146% 160% 135% Assists 180% 213% 159% 148% 115% 121% 155% Points 172% 183% 140% 130% 128% 137% 147% * adjusted to today’s scoring context

Breaking through 50 goals for the first time in 2010 (and on pace to do so again in 2011), Crosby certainly increased his goal scoring lead over the peer group (two years ago he was 25% ahead of the pack). But recently has Crosby traded goals for assists and his playmaking has regressed towards that of the peer group.

Earlier in his career Crosby looked more like a Wayne Gretzky than a Mario Lemieux. But, at this stage of his career, it is hard to know what Crosby wants to be. It feels like he has tried to put the Penguins on his back and carry them, like Mario.

Alexander the Great is clearly more of a sniper than is Crosby. The table below shows that Ovechkin‟s career performance, relative to the peer group, is different – 47% more goals, 6% more assists and 23% more points.

When you adjust for changes in scoring levels over time, Ovechkin‟s goal production in 2008 (age 22) was one of the ten best in NHL history. In 2010 he was very close to his career average goal pace but 2011 was a goal-scoring disappointment. Ovechkin seems

Copyright Alan Ryder, 2011 Hockey Analytics www.HockeyAnalytics.com 2011 NHL Review Page 88 to be trending in the general direction of the peer group, which became better playmakers over time.

Age 20 21 22 23 24 25 Career Ovechkin Games Played 81 82 82 79 72 79 475 Goals 52 46 65 56 50 32 301 Assists 54 46 47 54 59 53 313 Points 106 92 112 110 109 85 614 Adjusted Peer Group * Games Played 75 72 72 72 75 63 429 Goals 30 30 31 35 33 28 188 Assists 43 44 45 49 49 41 274 Points 73 74 76 84 82 69 462 Ratio to Peers per GP Goals 161% 134% 184% 145% 158% 91% 147% Assists 117% 91% 92% 100% 125% 103% 106% Points 135% 109% 129% 119% 138% 98% 123% * adjusted to today’s scoring context

I think it is important to note that Crosby is cursed by terrible teammates whereas Ovechkin in blessed. This situation is likely to average out over time and should affect their career trajectories.

Ovechkin is two years older than Crosby, a significant matter in career projections. He is now past the magic age of 23, when the performance of snipers tends to peak. While Ovie scored 50 goals four times in a five year career, the peer group analysis says that feat is becoming more challenging.

Although still very early in their careers it is evident that both of these youngsters are something quite special. Using their career-to-date performance and the lifetime trajectories of the peer group I have (boldly) forecast their careers (career to date statistics are highlighted) in the table below.

The first thing to observe is that the career of Ovechkin is disadvantaged by later entry into the NHL. Not only did he lose two seasons to Crosby but his older age of entry implies less upside. The projections say that Ovechkin has peaked.

Crosby

His career goal projection (659) is actually up from last year notwithstanding his concussion. The career assist forecast is down 47 this season, mainly due to injury but also due to his apparent strategy shift towards scoring that occurred in the past two seasons. Crosby‟s forecast for career points (1845) is down by 38 from last year (1883). This is mainly about the loss of a half season. The forecast would have been up otherwise.

Note that Sid was 23 years old last season. This is the magic peak year for offensive forwards.

Crosby Ovechkin Age G A Pts G A Pts 18 39 63 102 0 0 0 19 36 84 120 0 0 0 20 24 48 72 52 54 106 21 33 70 103 46 46 92 22 51 58 109 65 47 112 23 32 34 66 56 54 110 24 41 71 112 50 59 109 25 42 71 113 32 53 85 26 40 74 114 43 50 93 27 39 74 113 42 49 91 28 36 67 103 39 45 84 29 31 61 92 33 41 74 30 37 63 100 39 42 81 31 33 60 93 35 40 75 32 25 54 79 27 36 63 33 26 49 75 28 33 61 34 24 48 72 25 32 57 35 23 43 66 24 29 53 36 19 37 56 21 25 46 37 16 35 51 17 24 41 38 12 22 34 12 15 27 39 0 0 0 0 0 0 40 0 0 0 0 0 0 Totals 659 1186 1845 686 774 1460

How is he doing on games played? The peer group averaged 432 games played through the age of 23. Crosby has played 412, about 5% fewer. The model I use can only average out injuries. So far he is roughly on target.

The forecast, however, is now fraught with uncertainty. If Crosby can avoid the Eric Lindros career trajectory, the model‟s GP forecasts might be fine (it forecasts 72 GP next season). Before his concussion I would have said that he looked pretty durable. But his career is, today, looking like it has higher than average risk. In fact, it looks like he will miss a substantial part of the coming season.

Ignoring that very important consideration, with six years of data, the model is now stabilizing somewhat. The algorithm is forecasting 110 – 115 points for the next several years. I wouldn‟t be surprised to see him come in higher than that. There was a strong uptick in his offense in 2011 that gets only half credit because he missed so much playing time. And the model doesn‟t really know about Sid‟s lack of playmates and there may be some upside from this, some day. As it stands, his projected career assist total is behind that of only Wayne Gretzky (1,963), Ron Francis (1,249) and Mark Messier (1,193).

And his projected career points total is behind that of Gretzky (2,857), Messier (1,887) and Gordie Howe (1,850) – very good company indeed.

Ovechkin

This year he now projects out a bit under 700 career goals, down 46 from last year. His projection was hurt by netting a career worst 32 goals (17 short of the forecast of 49) and dialing back his future a bit. Ovechkin‟s playmaking performance in 2011 tracked expectations such that his career forecast (774) is up by just three over the 2010 model.

The goal-scoring stumble in 2011 is a setback. Last year he projected into the top five snipers of all time. Now he projects to 10th (remember, however, that he is playing in a low scoring environment) amongst all-time goal scorers. And 15th in all-time points. I think there is some upside in this projection as well. The forecast for goals for next season is 43.

Pay attention to these guys! Should these careers come to pass we would worship Crosby and Ovechkin as two of the finest players to ever lace on skates. But this would understate their relative achievements. They are disadvantaged by playing during one of the lowest scoring eras ever.

When you deflate the career performances of others to the current scoring context you come to the conclusion that

 Ovechkin projects to the second greatest goal scorer of all time. With 705 „normalized‟ goals (historical totals adjusted to the current scoring environment) only Gretzky has a higher total, and  Crosby projects to the second greatest playmaker and point scorer of all time. With 1,658 normalized assists and 2,362 normalized points only Gretzky has higher totals.

Or, to put it another way, just imagine what these numbers might have resembled during the free scoring 1980s (note that my assumption is that scoring levels remain at today‟s low levels). These projections are highly dependent on the size of goals and goaltenders going forward. The NHL‟s desire for more offense suggests that future scoring inflation could pump up these careers.