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Tim Thomas vs Tuukka Rask

By on January 12th, 2012

There is a post over at Backhand Shelf today that lists 10 backup goalies that have out performed their #1 counterparts.  It is an interesting read but it may be a perfect example of how simple statistics don’t tell the whole story.

The first pair of goalies on the list are the Bruins Tukka Rask vs Tim Thomas.

Backup: Tuukka Rask (10-4-1, 1.59 GAA, .945 SV%)
Starter: Tim Thomas (17-7-0, 1.99 GAA, .938 SV%)

Now both goalies have exceptionally good numbers but on the surface you would probably conclude that Rask has superior numbers to Thomas and on the surface you would be correct.  But dig a little deeper and things may look a little different.

A few days ago I was wading through some statistics and made an interesting observation about the Bruins handling of these two goalies.  Specifically, Tukka Rask gets far easier starts than Tim Thomas.

Rask Thomas
Opp. Record 265-257-72 511-418-123
Opp. Points % 1.013 1.088
Opp. Points/82gms 83.1 89.2
Opp GFA 2.55 2.77
Opp Sh% 8.66% 9.29%

Thomas’s opponents have a better record, have a better goal scoring rate and have a better shooting percentage than Rask’s and generally speaking it isn’t very close.  Boston has the highest goals per game average in the NHL.  The next 6 teams are Philadelphia, Vancouver, Detroit, Toronto, Chicago and Ottawa.  Of Rask’s 14 starts he has 2 starts (14.3%) against those six teams, one against Toronto and one against Detroit.  Thomas has 25 starts, and 9 starts (36%) against those six teams (3 vs Toronto, 2 vs Ottawa, 2 vs Philadelphia, 1 vs Chicago and 1 vs Vancouver).

When you take Rask and Thomas’s individual numbers on the surface it appears that Rask has out performed Thomas but when you dig deeper and look at the quality of opposition it is far less clear that Rask has outperformed Thomas and in fact it may be the other way around.

(On a side note, the combined record of all of Boston’s opponents is just 776-675-195, the equivalent of an 87 point team so it seems they have had a fairly easy schedule thus far. )

 

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The Onus of Blame now falls on Burke’s shoulders

By on December 27th, 2011

So we found out over Christmas that Ron Wilson got his wish and got a new contract.  With that the onus of blame for any failures this Leaf team has now clearly falls on Brian Burke’s shoulders.  Specifically, I am talking about the Leafs horrid penalty kill.

Ron Wilson was one of, if not the, top paid coach in the NHL.  He is paid like one of the best coaches in the NHL and he was given a contract extension so clearly Brian Burke doesn’t believe Ron Wilson is the reason for the Leafs PK failures.

So, if Ron Wilson is not the problem it must be the players.  Clearly Burke believes the players are getting a good message from Ron Wilson so either the players have tuned Wilson out or they just don’t have the skill level to implement Ron Wilson’s PK plan.  If the players have tuned out Wilson you have two options, fire Ron Wilson or get new players who will listen.  Ron Wilson wasn’t fired and there is no indication that the players have tuned out Wilson or that Burke thinks a mass overhaul of the team is deemed necessary.  So, if it isn’t the coach and the players haven’t tuned out the coach then it must only be the talent level of the players.  These are Burke’s players so if they are a failure it is a problem created by Burke and Burke’s problem to fix.

This is Burke’s team now.  These are his players and his coach and everything to do with this team now has his stamp of approval.  Everything good, and bad, with this team is now Burke’s doing.  Burke talks confidence about this team and how it only needs tinkering but I don’t share that same optimism,  The team is clearly better and is a definite contender for a playoff spot but I wish I had more optimism that there is a viable path towards cup contender without major upgrades at several positions.

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The Leafs Offensively: Who is good and who is not.

By on December 16th, 2011

This will be the final part of my unplanned 3-part series on who is good and who is not on the current Leafs team.  The first was about the penalty kill and the second was defensively.  Today we look at the players offensively.

The Defensemen

Player Name GFA FenF20 Ozone%
DION PHANEUF 2.4 15.22 60.2%
KEITH AULIE 2.25 14.24 61.9%
JOHN-MICHAEL LILES 2.79 13.85 46.1%
CARL GUNNARSSON 2.1 13.42 56.1%
CODY FRANSON 2.37 13.2 47.2%
JAKE GARDINER 2.25 12.79 54.3%
LUKE SCHENN 2.49 12 47.3%
MIKE KOMISAREK 2.82 10.95 40.8%

Included in the table above are goals for average (goals for per 60 min.), fenwick for per 20 minutes and offensive zone faceoff percentage which gives an indication which players start most frequently in the offensive zone.  There really isn’t too much exciting going on here.  For the most part the defensemen’s FenF20 is driven by their Ozone%.  The r^2 between FenF20 and Ozone% is 0.60 so there is a pretty tight correlation.  The only deviation is Liles who generates more offense than his Ozone% indicates he should.  The r^2 is 0.80 if we don’t include Liles.  So offensively, it seems Liles is the only defenseman who is able to drive the play significantly more than any of the others.  Looks like he might be worth keeping around.  Let’s get his name on a contract extension.

The Forwards

Player Name GF20 FenF20 Ozone%
PHIL KESSEL 3.36 14.91 51.3%
MIKHAIL GRABOVSKI 2.79 14.67 57.6%
JOFFREY LUPUL 3.6 14.5 50.2%
NAZEM KADRI 3.54 14.13 48.1%
MIKE BROWN 1.2 14.13 49.5%
TYLER BOZAK 2.97 13.97 49.3%
NIKOLAI KULEMIN 2.46 13.68 53.4%
DAVID STECKEL 1.26 13.21 48.6%
CLARKE MACARTHUR 2.97 12.92 56.3%
MATT FRATTIN 2.07 12.64 49.5%
TIM CONNOLLY 2.43 12.63 46.1%
MATTHEW LOMBARDI 2.46 11.94 54.1%
PHILIPPE DUPUIS 0 11.65 50.0%
JOEY CRABB 2.34 11.57 56.1%
JOE COLBORNE 3.33 11.29 50.0%
JAY ROSEHILL 0 10.6 43.1%
COLBY ARMSTRONG 0.87 10.41 51.3%
COLTON ORR 3.21 9.65 22.2%

Unlike the defensemen there is very little correlation between the Ozone% and FenF20 (r^2=0.0395) which means there is no rhyme or reason to where these guys are starting on the ice.  Joey Crabb can’t seem to drive offense and yet has an Ozone% of 56.1%.  The best offensive line of Kessel-Lupul-Bozak start about 50% of the time in the defensive zone while our supposed defensive specialist Philippe Dupuis starts half the time in the offensive zone.  What’s that all about coach?  Aside from those oddities it is kind of what we’d expect.  Offense is driven by the Kessel and Grabovski lines.  Generally speaking, there aren’t too many surprises in regards to how the Leafs are performing offensively.  The only surprise might be Mike Brown rating so highly.  This is pretty abnormal for him so probably just small sample size issues going on.

 

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The Leafs Defensively: Who’s good and who’s not.

By on December 15th, 2011

Yesterday I took a look at the Leafs players on the PK to see who has seen good result and who has seen bad results when they have been on the ice.  Today I do the same thing but look at 5v5 situations from the defensive side of things to see if there is any consistency between 5v5 and the PK.

The Goalies

Player Name GAA SV%
JAMES REIMER 1.41 94.6%
JONAS GUSTAVSSON 2.58 91.3%
BEN SCRIVENS 2.82 90.6%

Interestingly, this is the exact opposite as we saw on the PK where Reimer had the worst save percentage and Scrivens had the highest.  We should have more confidence in these numbers so it is quite possible that Reimer’s poor results are primarily luck driven.  The question is, how much can he improve it?  Last year on the PK Reimer had an 85.6% save percentage which while is much better than this seasons 77.3% still is not good.  He ranked 34th of 40 goalies last season on the PK while he was 6th of 48 at 5v5.  Last year Reimer had a 93.3% 5v5 save percentage so he is actually better this season at 5v5.  Is it sustainable?  Time will tell.

The Defensemen

Player Name GAA FenA20
DION PHANEUF 2.40 12.11
CARL GUNNARSSON 2.25 12.24
CODY FRANSON 2.37 12.51
KEITH AULIE 4.50 12.74
MIKE KOMISAREK 2.34 13.38
JOHN-MICHAEL LILES 2.55 13.77
JAKE GARDINER 1.86 14.82
LUKE SCHENN 2.19 16.63

For those regular readers, I believe players can drive shooting percentages (especially) and suppress oppositions shooting percentages (less so) but we are below the threshold of where small sample size issues outweigh the benefits of doing a goal analysis over a fenwick/corsi analysis.  So, when ranking players defensively we should focus on fenwick (for now).

Ughhh.  While Schenn’s GAA isn’t the worst (it’s actually pretty good relative to his teammates) his fenwick against is awful.  Significantly worse than his teammates.  While Schenn has had a slight bias towards defensive zone faceoffs it isn’t enough so to justify this difference in fenwick against.  Liles, Franson and Komisarek had a higher percentage of defensive zone faceoffs and had better results.  Taking it to a league level, of the 166 defensemen with 250 minutes of 5v5 ice time this season Schenn ranks second last in fenwick against per 20 minutes.  Only Derek Morris of Phoenix is worse.  In the summer I wrote an article about how poor Schenn is defensively and there isn’t a lot in the numbers above to change my opinion any.

Phaneuf, Gunnarsson and Gardiner were the primary offensive zone players which explains in part why Phaneuf and Gunnarsson lead the list but also show that Gardiner still struggles defensively as is often the case with a rookie.  Hopefully, unlike Schenn, he’ll improve with experience.

The Forwards

Player Name GA20 FenA20
MIKE BROWN 1.62 10.36
COLBY ARMSTRONG 2.61 10.7
DAVID STECKEL 2.13 11.02
NAZEM KADRI 3.54 11.78
CLARKE MACARTHUR 2.76 11.79
PHILIPPE DUPUIS 0.81 11.83
JAY ROSEHILL 1.41 12.02
MIKHAIL GRABOVSKI 1.68 12.24
MATTHEW LOMBARDI 4.29 12.97
MATT FRATTIN 1.5 13.2
JOEY CRABB 2.64 13.32
TIM CONNOLLY 1.62 13.53
NIKOLAI KULEMIN 1.98 13.68
JOE COLBORNE 2.79 14.43
PHIL KESSEL 2.46 15.47
JOFFREY LUPUL 2.82 16.47
TYLER BOZAK 2.82 16.57
COLTON ORR 0 20.38

Kessel, Lupul, Bozak – score a lot of goals, give up a lot of goals.  The three of them have very high fenwick against relative to their teammates.  This isn’t unsual for offensive players (high risk, high reward), but the best players in the league find a way to accomplish both offense and defense (i.e. Datsyuk).  The second line of Grabovski, MacArthur and Kulemin seem much more defensively responsible, but surprisingly they have a higher percentage of offensive zone starts than the Kessel line so they should have better numbers, but maybe not to the extent they do.  Brown, Steckel and Dupuis do seem like pretty solid defensive players 5v5.  Those fenwick against numbers for those three are quite good relative to the rest of the team, and the rest of the league.

Overall the Leafs are a decent enough defensive team at 5v5.  Especially once you look past the Kessel-Lupul-Bozak line up front and Schenn (and to a lesser extent Gardiner) on defense.  For some strange reason though, that hasn’t translated very well to the PK.  Why they suck so bad on the PK is pretty dumbfounding.

 

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Leafs PK: Who’s good, who’s not.

By on December 14th, 2011

Considering the Leafs gave up another power play goal last night at a critical moment in the game (allowed Carolina to tie the game late) I thought I toss out some individual numbers for you to see who we can blame.  Now before we get to the numbers I need to caution you that these numbers are based on extremely small sample sizes so they need to be reviewed in that context.  These are also only 4v5 numbers so no 3v5 or 3v4 situations are included.

The Goalies

Goalie GA SA SV% GAA
SCRIVENS 3 28 89.3% 5.01
GUSTAVSSON 12 69 82.6% 8.55
REIMER 10 44 77.3% 11.49

Scrivens actually put up some pretty good penalty kill numbers.  Reimer and Gustavsson are pretty bad.  Of all NHL goalies with at least 25 minutes of 4v5 PK time Scrivens ranks 24th of 59 in save percentage while Gustavsson is 54th and Reimer 58th.  Only Curtis Sanford is worse.  Interestingly, Jason Labarbera of Phoenix has played 38 minutes of 4v5 PK time and has not given up a goal on 33 shots.  Martin Brodeur is almost as impressive having given up just 2 goals on 58 shots against in 91 minutes of 4v5 time.

The Defensemen

Player Name GA SA SV% GAA FenA20
GARDINER 5 41 87.8% 6.39 23.41
GUNNARSSON 11 68 83.8% 7.38 22.77
PHANEUF 11 65 83.1% 7.56 23.15
KOMISAREK 6 30 80.0% 9.81 25.09
SCHENN 10 50 80.0% 10.77 25.82
LILES 5 21 76.2% 11.97 23.92

Can we put an end to the “Luke Schenn is a much improved defensive player this season” talk?  And to some extent the same for Komisarek too?  At least on the penalty kill they have been bad.  If these limited sample sizes mean anything, we need more Gardiner, Gunnarsson and Phaneuf on the PK and less Komisarek, Schenn and Liles.  What is Liles doing on the PK anyway?

The Forwards

Player Name GA SA SV% GAA FenA20
DUPUIS 8 55 85.5% 6.69 22.05
KULEMIN 4 22 81.8% 7.8 21.42
LOMBARDI 4 26 84.6% 8.31 28.39
CRABB 4 23 82.6% 8.52 24.87
STECKEL 12 58 79.3% 8.61 20.58
CONNOLLY 6 37 83.8% 10.35 29.94
BROWN 6 22 72.7% 14.4 28.78
GRABOVSKI 5 18 72.2% 18.3 28.05

While Dupuis and Kulemin haven’t done much offensively this season they do seem to be the teams best penalty killers.  Steckel hasn’t been too bad either as he has a team low fenwick against per 20 minutes.  The rest, well not so good.  Grabovski?  Giving up goals at a rate of 18.3 goals per 60 minutes?  That’s nearly a goal every 3 minutes of PK time.

Now, as I said before I got into all these numbers, the sample sizes are really small so we can’t really draw and conclusions we can be confident about to a high degree so take them as conclusive evidence of anything, including anything I stated above.

 

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Leafs Still a Long Way from Being Good.

By on December 10th, 2011

The Leafs have played 29 games so far this season, or just over one third of their season.  For the most part it has been relatively good start to the season.  Kessel has led the league in goals and points for most of the season, Lupul has been close behind, and the team has generally been fairly comfortably in a playoff spot.  But in reality, the Leafs are a long way from being a contender.

The teams offense has been quite good.  They are scoring goals at about a 3 goals per game pace which ranks them 6th in the NHL.  For the most part I think this is sustainable, especially if they can get healthy and Grabovski and Kulemin can get back to scoring.  The problem is, the Leafs continue to stink defensively and there are no real signs of this getting any better any time soon.  Their goals against average is 3.16 which is 4th worst in the NHL and is worse than last seasons 2.94 gaa.  Only Columbus, Ottawa and Carolina are worse this season and that is not a recipe for success in the NHL.  Yes, not having James Reimer for much of the season is a factor, but the problem has not just been goaltending.

Defensively this team is awful.  It’s been awful for years and there is no evidence that it will be anything but awful in the future without significant changes being made.  The penalty kill is second worst in the league, it was 3rd worst last season, and dead last in both 2009-10 and 2008-09.  The roster is completely different.  The goalies have been changed more than once.  The one constant during those four years has been the coach.  I have given Ron Wilson the benefit of doubt long enough.  Despite the teams record, we have not seen this team make any progress in the one area this team has the most room (and need) to improve.  It is time to fire the coach.

Now it is not all the coach.  The players need to take responsibility too and so does the general manager.  But we need to start with replacing the coach with a good defensive minded coach.  Everyone quickly jumps on the Randy Carlyle bandwagon but I am not convinced he is the guy for the job.  Generally speaking Anaheim hasn’t had a great PK team the past several seasons, but I am open to the idea.  I am actually open to anyone who can bring a fresh look and new defensive awareness to the team.  Once we get the coach in place it will be up to the players to improve.  If they can’t, it’s time to ship some of them out and get some players in who can.

Now I don’t expect any coaching change, if there is one at all, to occur until January (unfortunately), but the Leafs currently sit 4 points out of 12th spot and most of the teams behind them have games in hand.  They are 1-3-1 in their past 5 games and if they go 1-3-1 in their next five they may be out of a playoff spot.  Since November 3rd they are  6-8-2 and that is no where near good enough.  They only reason they look good is their 9-3-1 start.  Come January they could be a few points out of a playoff position.  Let’s hope they don’t wait too long to make a change.

You may be asking, why this post and why now?  Well, it started on Monday when the Leafs were playing the Rangers.  The Leafs got off to a 3-0 start before giving up two goals to the Rangers in the second half of the second period.  Entering the third period I had zero confidence that this team could maintain the lead and I got to thinking that that isn’t a very good reflection on the team.  From that point on I decide I would not consider the Leafs a quality team until I had relatively good confidence that they can maintain a lead.  The Leafs did manage to hold on to the lead and won the game, but they were out shot 12-7 in the third period and generally out played.  It did nothing to change my lack of confidence in their ability to hold a lead.  They have played two games since the Rangers game, one a 3-2 OT loss to the mediocre Devils and the second a 4-2 loss to the struggling Washington Capitals.  They combined to give up 6 powerplay goals in those two games.  These games they could have, and maybe should have, won if they only knew how to kill penalties.  This just reaffirmed to me that until this team learns to play defense and learns how to kill penalties, I cannot consider it a good team.

(End of Rant.  Enjoy your weekend and don’t worry, I’ll guarantee you the Leafs won’t give up any more PP goals this weekend.)

 

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Can a Player Influence his Teammates Shooting Percentage?

By on December 9th, 2011

Gabe Desjardins of Arctic Ice Hockey asks the question about whether a player can influence his teammates shooting percentage.  To answer this question he took a look at the Pittsburgh Penguins shooting percentages with and without Mario Lemieux.  The conclusion:

I’d posit that Lemieux’s playmaking contribution is about as large as we’re going to consistently find – something on the order of 7-8% – and we can use it to bound the impact that a player can truly have on the quality of his teammates’ scoring chances.

Since I have the numbers handy I figured I’d take a look at some more recent examples but instead of looking at straight shooting percentage I looked at corsi shooting percentage (since I had corsi data more available).  Corsi shooting percentage is simply goals for divided by corsi for.  I’d consider Joe Thornton one of the premiere playmaking centers in the league today so let’s take a look at how some players performed while playing with, and without, him.

CSH% With Thornton CSH% Without Boost
Marleau 4.93% 3.88% 27.02%
Setogutchi 5.09% 3.80% 33.82%
Heatley 5.59% 4.32% 29.50%

I included the past 4 years with Marleau, 3 years with Setogutchi and 2 years with Heatley.  That would indicate Thornton has an approximately 30% boost in corsi shooting percentage to his teammates.  Certainly far more than the 8% Gabe predicted as the upper bound.

Now, let’s take a look at another great player, Sidney Crosby.

CSH% With CSH% Without Boost
Malkin 7.30% 5.15% 41.89%
Dupuis 5.73% 4.06% 40.95%
Fleury 5.75% 4.22% 36.15%

All players are using 4 years of data.  I included Fleury in the list because it provides a good proxy of the Penguins shooting percentages when Crosby is on the ice vs when he is not.  This would seem to indicate that Crosby is worth a nearly 40% boost in his teams shooting percentage.  That’s significantly more than even Thornton and a massive amount more than Gabe’s estimated upper bound.  Maybe we should revise the upper bound to be 40%, not 8%.

For interest sake, here how much Crosby influenced his teammates corsi rates.

Boost in CF20
Malkin 21.15%
Dupuis 18.15%
Fleury 15.59%

While a ~20% boost is significant, it is at best only half the boost he provided to corsi shooting percentage.  Driving shooting percentage is a more significant reason why Crosby is so good offensively than driving corsi events.

 

Update:  Eric over at Broad St. Hockey has an interesting post looking at individual shooting percentages as opposed to on-ice shooting percentages as I did above.  Four of the players he looked at are H. Sedin, Crosby, Thornton and Datsyuk and for each he looked at a number of teammates with at least 30 shots with and without.  Taking it a step further I think it is necessary to average across players to get a better idea of what is happening.  If you do that, this is what you get:

With Without Boost
Sedin 11.19% 6.81% 64.28%
Crosby 9.14% 7.55% 21.17%
Thornton 9.69% 7.27% 33.19%
Datsyuk 9.36% 6.98% 34.09%

Wow, that might make Sedin the best playmaker in the league, by a significant margin.  Crosby doesn’t look quite as good as my “on-ice” analysis but that is because much of the reason why Crosby improves his linemates on-ice shooting percentage is because he is such a great shooter himself.

The point still stands, without considering shooting percentages we aren’t getting anywhere close to having a complete analysis of a players impact on the game.

 

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Thoughts on New Conference Format

By on December 6th, 2011

In general, I really like the new conference format.  Well, really, I didn’t like the previous conference format so I am glad that is gone.  First off, let me mention a few things that I don’t like about the current setup.

1.  Reduces chances of rivalries forming/developing.  Essentially under the current system if you make the playoffs you could meet any one of 14 other teams in the first round.  Rivalries are primarily built through competing for playoff spots and meeting in the playoffs.  Under the current system you are far less likely to meet the same team in the playoffs in back to back years and you are less likely to meet your natural geographical rivals in the playoffs (Toronto vs Montreal, Anaheim vs Los Angeles, Pittsburgh vs Philadelphia, etc.).  This, in my opinion, is bad for the NHL.

2.  Unbalanced schedule.  The current schedule isn’t quite as unbalanced as a few years back but it is still unbalanced and that means two teams competing for the same playoff position do so by playing different schedules with different strengths of difficulty.  This has generally favoured teams in weaker divisions, particularly the generally very weak southeast division.  Just look at the standings right now.  Four of the top eight and five of the top 10 teams are north east division teams while just one of the top eight teams is from the southeast and three of the bottom five teams are from the southeast.  With an unbalanced schedule that sees teams play a heavier within-division schedule, all the teams in the southeast have a much easier schedule than the teams in the northeast and yet those teams are competing for the same playoff spots.

The new conference set up fixes both of these problems.  The mini-conference playoff structure means a greater chance of rivalries developing and geographical rivals meeting in the playoffs.  Also, while the schedule is still unbalanced between conferences you are only competing for a playoff spot with your conference rivals who all more or less play an equal schedule.

Some people have raised some concerns though.  First and foremost they don’t like that some conferences have 7 teams and some have 8 meaning some teams have a 4 in 7 chance of making the playoffs and other teams have a 4 in 8 chance.  There is some validity to this, but fear not, I am certain Bettman and the owners have a plan to address this in the upcoming years.  Expansion to 32 teams making each conference having 8 teams.  Or, we could dream and they contract to 28 teams, but that is unlikely.

The second concern people have is that a 5th place team in one conference will be better than a 4th place team in another conference but the 5th place team misses the playoffs and the 4th place team makes the playoffs.  This too is a valid concern, but is more or less equivalent to the unbalanced schedule issues I pointed out above not to mention the 9th place team in the west has generally been better than the 8th place (and sometimes 7th and 6th place) team in the east for the past several years.  Nothing is perfect.

To me, the greater development of rivalries far outweighs any negatives with the new system.  Rivalries are what can turn casual fans into enthusiastic fans and anything that can be done to enhance rivalries.  I thought going to the conference playoff system was a mistake so I am glad they fixed that.

 

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Showing Shooting Percentage Matters (Yet Again)

By on November 22nd, 2011

I hate to keep beating the “Shooting Percentage Matters” drum but it really dumbfounds me why so many people choose to ignore it, or believe it is only a small part of the game and not worth considering and instead focus their attention on corsi/fenwick, and corsi/fenwick derived stats as their primary evaluation too.

It dumbfounds me that people don’t think players have an ability to control shooting percentage yet we all seem to agree that shooting percentage is affected by game score.  Rob Vollman wrote the following in a comment thread at arctic ice hockey.

<blockqote>The score can affect the stats because teams behave differently when chasing or protecting a lead…</blockquote)

He isn’t specifically referring to shooting percentage, but shooting percentage varies based on game score and I think most people accept that.  So, while people freely accept that teams can play differently depending on score, they seemingly choose not to believe that players can play different depending on their role, or skillset.  Or rather, it isn’t that they don’t believe players can play differently (for example they realize there are defensive specialists) they just choose not to accept that a players style of play (in addition to their talents, which often dictates their style of play) will affect their stats, including shooting percentage.  An example, which I brought up at The Puck Stops Here is Marian Gaborik vs Chris Drury.  Both Gaborik and Drury played the past 2 seasons on the NY Rangers but Gaborik played an offensive role and Drury generally played a more defensive/3rd line role.  As a result, here are their offensive stats at 5v5 over the past 2 seasons.

Gaborik Drury Gaborik’s Edge
Team Fenwick For per 20min WOI 13.8 12.8 +8%
Team Sh% For WOI 10.26% 6.18% +66%
Team Goals For per 20 min WOI 1.031 .575 +79%

Shooting percentage took what was a slight edge for Gaborik in terms of offensive fenwick for and turned it into a huge advantage in goals for.  Part of that is Gaborik and his line mates better skill level and part of it is their aggressive offensive style of play, but regardless of why, we need to take shooting percentage into account or else we will undervalue Gaborik at the offensive end of the rink and over value Drury.

It isn’t just Gaborik and Drury whose offense is significantly impacted by shooting percentage.  It happens all the time.  I took a look at all players that had 2000 5v5 even strength on-ice offensive fenwick events over the past 4 seasons.  From there I calculated their expected on-ice goals scored based on their ice time using league-wide average  on-ice fenwick for per 20 minutes (FF20) and league-wide average fenwick shooting percentage (FSH%).

I next calculated an expected goals based on the league-wide FF20 and the players FSH% as well as an expected goals based on the players FF20 and the league-wide average FSH%.  When we compare these expected goals to the expected goals based solely on the league-wide average we can get an idea of whether a players on-ice goal production is driven mostly by FF20 or FSH% or some combination of the two.

The following players had their on-ice 5v5 goal production influenced the most positively or most negatively due to their on-ice 5v5 FSH%.

Player Name %Increase from FSH%
MARIAN GABORIK 40.6%
SIDNEY CROSBY 36.3%
ALEX TANGUAY 33.1%
HENRIK SEDIN 32.8%
BOBBY RYAN 32.5%
EVGENI MALKIN 31.9%
DANIEL SEDIN 31.6%
ILYA KOVALCHUK 30.6%
NATHAN HORTON 29.6%
J.P. DUMONT 29.4%
… …
GREGORY CAMPBELL -12.4%
RYAN CALLAHAN -13.9%
RADEK DVORAK -15.6%
CHRIS DRURY -16.8%
SEAN BERGENHEIM -19.4%
SCOTT GOMEZ -19.7%
MARTIN HANZAL -21.5%
MIKE GRIER -21.5%
DANIEL WINNIK -24.5%
TRAVIS MOEN -32.1%

And the following players had their on-ice 5v5 goal production influenced the most positively or most negatively due to their on-ice 5v5 FF20.

Player Name %Increase from FF20
HENRIK ZETTERBERG 24.7%
ALEX OVECHKIN 21.7%
PAVEL DATSYUK 20.6%
TOMAS HOLMSTROM 19.9%
NICKLAS BACKSTROM 19.8%
ERIC STAAL 19.7%
RYANE CLOWE 18.8%
ALEXANDER SEMIN 18.3%
SCOTT GOMEZ 18.0%
ZACH PARISE 17.9%
… …
MARTY REASONER -6.5%
ANDREW COGLIANO -6.5%
ANTTI MIETTINEN -6.7%
KYLE BRODZIAK -7.3%
CHRIS KELLY -8.6%
ILYA KOVALCHUK -9.8%
JAY MCCLEMENT -10.4%
MICHAL HANDZUS -14.4%
JOHN MADDEN -14.5%
TRAVIS MOEN -15.6%

Some interesting notes:

  1.  The range in the influence of FSH% is significantly larger than the range of influence of FF20 indicating that shooting percentage is more important than shot generation in terms of scoring goals.
  2. The FSH% list is not random.  The list is stratified.  Offensive players at the top, non-offensive players at the bottom (plus Scott Gomez who gets offensive minutes, but sucks).  What you see above is not luck.  There is order to the list, not randomness.
  3. Speaking of Gomez, he sucks at on-ice FSH%, but has a very good FF20, though that is partly due to offensive zone start bias.
  4. Ilya Kovalchuk is the anti-Gomez.  He has a great FSH%, but is horrible at helping his team generate shots.
  5. The standard deviation of the FSH% influence is 14.5% while it is 8.3% for FF20 influence so it seems FSH% has a much greater influence on scoring goals than FF20.  This is not inconsistent with some of my observations in the past or observations of others.

So, what does all this mean?  Shooting percentage matters, and matters a lot and thus drawing conclusions based solely on a corsi analysis is flawed.  It isn’t that generating shots and opportunities isn’t important, but that being great at it doesn’t mean you are a great player (Gomez) and being bad at it doesn’t make you a bad player (Kovalchuk).  For this reason I really cringe when I see people making conclusions about players based on a corsi analysis.  A corsi analysis will only tell you how good he is at one aspect of the game, but is not very good at telling you the players overall value to his team.  My goal is, and always will be, to try and evaluate a players overall value and this is why I really dislike corsi analysis.  It completely ignores a significant, maybe the most significant, aspect of the game.  Furthermore, I believe that offensive ability and defensive ability should be evaluated separately, which many who do corsi analysis don’t do or only partially or subjectively do.

I really don’t know how many different ways I can show that shooting percentage matters a lot but there are still a lot of people who believe players can’t drive or suppress shooting percentage or believe that shooting percentage is a small part of the game that is dwarfed by the randomness/luck associated with it (which is only true if sample size is not sufficiently large).  The fact is corsi analysis alone will never give you a reliable (enough to make multi-million contract offers) evaluation of a players overall ability and effectiveness.  Shooting percentage matters, and matters a lot.  Ignore at your peril.

 

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Some Thoughts on Shot Quality

By on October 27th, 2011

There has been a fair bit of discussion going on regarding shot quality the past few weeks among the hockey stats nuts.  It started with this article about defense independent goalie rating (DIGR) in the wall street journal and several others have chimed in on the discussion so it is my turn.

Gabe Desjardins has a post today talking about his hatred of shot quality and how it really isn’t a significant factor and is dominated by luck and randomness.  Now, generally speaking when others use the shot quality they are mostly talking about thinks like shot distance/location, shot type, whether it was on a rebound, etc.  because that is all data that is relatively easily available or easily calculated.  When I talk shot quality I mean the overall difficulty of the shot including factors that aren’t measurable such as the circumstances (i.e. 2 on 1, one timer on a cross ice pass, goalie getting screened, etc.).  Unfortunately my definition means that shot quality isn’t easily calculated but more on that later.

In Gabe’s hatred post he dismisses pretty much everything related to shot quality in one get to the point paragraph.

 

Alan’s initial observation – the likelihood of a shot going in vs a shooter’s distance from the net – is a good one.  As are adjustments for shot type and rebounds.  But it turned out there wasn’t much else there.  Why?  The indispensable JLikens explained why – he put an upper bound on what we could hope to learn from “shot quality” and showed that save percentage was dominated by luck.  The similarly indispensable Vic Ferrari coined the stat “PDO” – simply the sum of shooting percentage and save percentage – and showed that it was almost entirely luck.  Vic also showed that individual shooting percentage also regressed very heavily toward a player’s career averages.  An exhaustive search of players whose shooting percentage vastly exceeded their expected shooting percentage given where they shot from turned up one winner: Ilya Kovalchuk…Who proceeded to shoot horribly for the worst-shooting team in recent memory last season.

So, what Gabe is suggesting is that players have little or no ability to generate goals aside from their ability to generate shots.  Those who follow me know that I disagree.  The problem with a lot of shot quality and shooting percentage studies is that sample sizes aren’t sufficient to draw conclusions at a high confidence level.  Ilya Kovalchuk may be the only one that we can say is a better shooter than the average NHLer with a high degree of confidence, but it doesn’t mean he is the only one who is an above average shooter.  It’s just that we can’t say that about the others at a statistically significant degree of confidence.

Part of the problem is that goals are very rare events.  A 30 goal scorer is a pretty good player but 30 events is an extremely small sample size to draw any conclusions over.  Making matters worse, of the hundreds of players in the NHL only a small portion of them reach the 30 goal plateau.  The majority would be in the 10-30 goal range and I don’t care how you do your study, you won’t be able to say much of anything at a high confidence level about a 15 goal scorer.

The thing is though, just because you cannot say something at a high confidence level doesn’t mean it doesn’t exist.  What we need to do is find ways of increasing the sample size to increase our confidence levels.  One way I have done that is to use 4 years of day and instead of using individual shooting percentage I use on-ice shooting percentage (this is useful in identifying players who might be good passers and have the ability to improve their linemates shooting percentage).  Just take the list of forwards sorted by on-ice 5v5 shooting percentage over the past 4 seasons.  The top of that list is dominated by players we know to be good offensive players and the bottom of the list is dominated by third line defensive role players.  If shooting percentage were indeed random we would expect some Moen and Pahlsson types to be intermingled with the Sedin’s and Crosby’s, but generally speaking they are not.

A year ago Tom Awad did a series of posts at Hockey Prospectus on “What Makes Good Players Good.”  In the first post of that series he grouped forwards according to their even strength ice time.  Coaches are going to play the good players more than the not so good players so this seems like a pretty legitimate way of stratifying the players.  Tom came up with four tiers with the first tier of players being identified as the good players.  The first tier of players contained 83 players.  It will be much easier to draw conclusions at a high confidence level about a group of 83 players than we can about single players.  Tom’s conclusions are the following:

The unmistakable conclusions from this table? Outshooting, out-qualitying and out-finishing all contribute to why Good Players dominate their opponents. Shot Quality only represents a small fraction of this advantage; outshooting and outfinishing are the largest contributors to good players’ +/-. This means that judging players uniquely by Corsi or Delta will be flawed: some good players are good puck controllers but poor finishers (Ryan Clowe, Scott Gomez), while others are good finishers but poor puck controllers (Ilya Kovalchuk, Nathan Horton). Needless to say, some will excel at both (Alexander Ovechkin, Daniel Sedin, Corey Perry). This is not to bash Corsi and Delta: puck possession remains a fundamental skill for winning hockey games. It’s just not the only skill.

In that paragraph “shot quality” and “out-qualitying” is used to reference a shot quality model that incorporates things like shot location, out-finishing is essentially shooting percentage, and outshooting is self-explanatory.  Tom’s conclusion is that the ability to generate shots from more difficult locations is a minor factor in being a better player but both being able to take more shots and being able to capitalize on those shots is of far greater importance.

In the final table in his post he identifies the variation in +/- due to the three factors.  This is a very telling table because it tells it gives us an indication of how much each factors into scoring goals.  The following is the difference in +/- between the top tier of players and the bottom tier of players:

  • +/- due to Finishing:  0.42
  • +/- due to shot quality:  0.08
  • +/- due to out shooting:  0.30

In percentages, finishing ability accounted for 52.5% of the difference, out shooting 37.5% of the difference and shot quality 10% of the difference.  Just because we can’t identify individual player shooting ability at a high confidence level doesn’t mean it doesn’t exist.

If we use the above as a guide, it is fair to suggest that scoring goals is ~40% shot generation and ~60% the ability to capitalize on those shots (either through shot location or better shooting percentages from those locations).  Shooting percentage matters and matters a lot.  It’s just a talent that is difficult to identify.

A while back I showed that goal rates are better than corsi rates in evaluating players.  In that study I showed that with just 1 season of data goal for rates will predict future goal for rates just as good as fenwick for rates can predict future goal for rates and with 2 years of data goal for rates significantly surpass fenwick for rates in terms of predictability.  I also showed that defensively, fenwick against rates are very poor predictors of future goal against rates (to the point of uselessness) while goals against rates were far better predictors of future goal against rates, even at the single season level.

The Conclusion:  There simply is no reliable way of evaluating a player statistically at even a marginally high confidence level using just a single year of data.  Our choices are either performing a Corsi analysis and doing a good job at predicting 40% of the game or performing a goal based analysis and doing a poor job at predicting 100% of the game.  Either way we end up with a fairly unreliable player evaluation.  Using more data won’t improve a corsi based analysis because sample sizes aren’t the problem, but using more data can significantly improve a goal based analysis.  This is why I cringe when I see people performing a corsi based evaluation of players.  It’s just not, and never will be, a good way of evaluating players.