Behindthenet Blog

Top Scorers on Rebounds, 2005-09

2009-09-15T17:45:00.000-07:00

The NHL statistical database has been consistent for the four seasons since the lockout (Missed Shots were excluded in the two seasons prior to it). Here are the rebound scoring leaders:


Player     Shot  G  SOG  MS
Parise     73   22  41   10
Svatos     49   20  23    6
E Staal    81   19  50   12
Frolov     53   18  28    7
Antropov   50   17  26    7
Jokinen    73   17  43   13
Gomez      47   16  23    8
Zubrus     47   16  18   13
Arnott     54   16  29    9
D. Roy     56   16  28   12
Vermette   63   16  36   11

The worst? Alexei Kovalev, with just one goal on 42 total rebounds...

New-and-Improved Statistical Reports

2009-09-12T14:36:00.000-07:00

I modified the 5-on-5 statistical reports for 2008-09 so that they're vastly easier to use. There are four reports:

Corsi Report
Quality of Competition Report
Goal-Scoring Report
Penalties Drawn/Taken Report

Let me know what you think!

Defensive Systems and their Impact on Shot Location

2009-08-28T17:48:00.000-07:00

As we saw a few weeks ago, Jacques Lemaire’s defensive system substantially limits the rate at which opponents take high-percentage shots against his teams. This effect has been persistent over the course of nearly a decade. This made me wonder what impact other coaches have on shots faced by their teams.

What the chart below shows is - for each coach in all years that he coached - the difference between league-wide save percentage and the save percentage each team expected given the shots they allowed.


Coach      +EXS% YRS
Lemaire     4.3  7
Hitchcock   3.4  5
B. Sutter   2.8  5
Mactavish   2.0  7
Julien      2.0  4
Trotz       1.7  7
Martin      1.3  6
Wilson      1.2  6
Ruff        0.9  7
Quinn       0.8  4
Tippett     0.3  6
Crawford   -0.8  6
Tortorella -1.0  6
Maurice    -1.0  4
Carlyle    -1.3  4
Gretzky    -1.5  4
Quenneville-1.7  6
A. Murray  -2.3  6
Babcock    -2.3  6
Laviolette -3.2  5
Hartley    -3.5  4

As you can see, Lemaire stands out, though it would be interesting to see how the shot location chart looks for Hitchcock's teams. Bob Hartley brings up the rear for coaches who coached four seasons or more - his poor performance may be entirely due to having Ilya Kovalchuk on the ice most of the game.

OHL 2003-04 Quality of Competition

2009-08-24T14:25:00.000-07:00

Following up on this table, here are 5v5 Quality of Competition percentiles for each of the players. (Quality of Competition is calculated using Willis' method with the following modifications - only 5v5 points are included, and all opponents are included, not just forwards.)

Rob Schremp appears to have been sheltered...


Player QoC  GP-G-A1-A2   +/-
Wolski   86  65-19-13-6   42/42
Schremp  41  63-12- 5-8   34/13
Bolland  83  65-14- 9-5   32/19
Bickel   32  56-14- 5-3   32/36
Garlock  95  51-8- 14-7   36/20
Berti    78  64-6- 11-7   38/35
Meidl    82  66-5-  7-7   33/29
Kennedy  85  62-11-11-4   38/36
Reddox   82  66-15-10-6   39/41
McGrath  96  67-10-11-9   45/43
Kell     69  62-7-  8-5   26/14
Pisellini67  67-4-  3-4   25/17
Haskins  78  61-5-  9-2   28/14
Kaleta   56  65-4-  4-4   18/34
Rizk     92  67-5-  6-4   21/33
Morrison 45  64-10- 7-7   38/31
Pitton   79  66-8-  3-4   25/36
Stewart   9  57-4-  4-2   14/23

New Puck Prospectus Article: Shot Quality and the Minnesota Wild

2009-08-19T12:16:00.000-07:00

Niklas Backstrom is a mystery to me - is he a great goalie? Or did Minnesota limit his exposure. The Wild's Chris Snow clearly feels that both are true. Depending on your angle, the numbers back up both opinions.

Shot Quality and the Minnesota Wild

I've written about this topic from various angles, here and here.

MLB Signing Bonuses

2009-08-18T20:00:00.000-07:00

I haven't found much reason to write about major league baseball recently, but this piece by Jayson Stark about the MLB draft really irks me:

Draft in desperate need of repair

Stephen Strasburg just signed for $15 million - not $50 million - and yet Stark quotes an AL exec: "That's still a gigantic amount of money. Don't kid yourself."

Except it's not. Not in baseball. Carl Pavano pitched 26 games over four seasons and made $38 million. Carlos Silva's in the second year of a 5-year, $60 million contract. His ERAs since he signed: 6.46 and 8.48. That puts the price of a pitcher who has proven himself incapable of getting hitters out or staying healthy at the major-league level is $10-$12 million per season. The Washington Nationals will control Stephen Strasburg for three major-league seasons for barely $16 million, a vast discount over his real value. Top picks bring great value - Justin Upton has cost the Arizona Diamondbacks just over $7 million, but his production will be worth $20 million by season's end.

And Stark wants you to know that he's not just shilling for management: "It's because players want it...big league players want those $15 million deals going to them, not to kids who have never played a professional baseball game."

Of course veteran players want more money - they got robbed of their signing bonuses and were paid at a discount for their first 3-6 seasons. Now they want as big a piece of the pie as possible. But that's not a good reason for Stark to want to squeeze amateur players. Would Stark want anybody to take a 50% or 75% discount in any other career? I think not.

New Puck Prospectus Post: The Dangers of Defensive Zone Faceoffs

2009-08-07T13:27:00.000-07:00

"What are the risks of losing a faceoff in the defensive zone in comparison to the neutral zone, and does a coach`s usage of players in faceoffs affect player performance?"

http://www.puckprospectus.com/article.php?articleid=239

Derrière le filet: Avec or Sans Saku

2009-08-06T10:48:00.000-07:00

"Après quinze ans à Montréal, l'ère Saku Koivu est officiellement terminée. Soit démonisé ou sanctifié, selon le jour de la semaine, il faisait partie des Canadiens toute ma vie d'adulte et a joué 792 parties pour eux, dix-neuvième pour tout les temps. Alors, quelle a été sa valeur à l'équipe?"

http://www.puckprospectus.com/article.php?articleid=238

Giveaways

2009-08-02T21:40:00.000-07:00

Not surprisingly, giveaways have a highly-negative defensive impact. The peak shot rate against following a giveaway is as high as during a 5-on-3:

Of course, not all defensive zone giveaways are the same. As you can see from the chart, the vast majority of giveaways occur behind the net and along the boards. It’s not clear whether scorers consistently record the location where the puckhandler gave the puck away, or where the opposing team picked up the turnover. However, since most turnovers occurred behind the goal, it is unlikely that we are substantially undercounting giveaways in the slot, for example, so the chart likely captures the actual distribution of giveaway locations.

The defensive cost of a giveaway has a slightly different profile. While giveaways behind the net or along the boards result in a shot against over the next 10 seconds of play about 25% of the time, giveaways in front of the goal are (not surprisingly) almost twice as likely to result in a shot.

Defenseman's Impact (cont'd...)

2009-08-01T09:31:00.000-07:00

I was initially only going to look at the performance of replacement level defensemen to see if their inclusion in the lineup had any additional negative impact relative to that of losing a #1 or #2 defenseman. But I ended up pulling the "With or Without You" data for every defenseman over the last four seasons who played between 10 and 70 games in a season. That ended up being 502 in all.

I looked at two quantities: Even-Strength Save Percentage For and Even-Strength Save Percentage Against, both when the player was in the lineup and when he was out. I then regressed against average TOI. What we get is essentially this, with the coefficients varying slightly depending on how I weight the data:

Opponent's Save Percentage Delta vs Avg TOI = -0.44 * (TOI - 15)
Own Team's Save Percentage Delta vs Avg TOI = +0.44 * (TOI - 15)

TOI isn't a perfect proxy for a defenseman's ability (or for a team's performance when he's in the lineup), so we end up with R^2 in the range of 0.3 to 0.5. Nonetheless, replacing a good defenseman with a bad one tends to decrease your team's shooting percentage and increase your opponent's.

Defenseman's impact on Offense

2009-07-29T22:46:00.000-07:00

I might as well re-run the previous post on the offensive end of the ice:


                       IN                        OUT
                  GP   G/GP  S+G/GP  SVPCT  GP   G/GP  S+G/GP  SVPCT  DELTA
N=28 Better +/-   1610 1.89  21.77   913.3  686  1.71  21.16   919.1   5.8
N=25 Worse +/-    1229 1.81  21.76   916.9  821  1.81  21.32   914.9   -2.0

Again, the "Better +/-" group had a significant impact on scoring when they were in the lineup: +14.5 goals per 82 games. The "Worse" group generated more shots on goal, but scored less often, resulting in no increase in scoring.

As a whole, here are the offensive and defensive contributions in and out of the lineup:


                       IN                         OUT
                  GP   G/GP  S+G/GP  SVPCT  GP    G/GP  S+G/GP  SVPCT  DELTA
Offense/GF        2839 1.86  21.77   914.9  1507  1.77  21.25   916.8   1.9
Defense/GA        2839 1.86  21.79   914.5  1507  1.95  21.97   911.0   3.5

So we get what we expect when the players are in the lineup: the expected record of a large number of teams is .500. When a top D-man is out of the lineup, both offensive and defensive shot volume and quality suffer to varying degrees, resulting in a .450 team in the aggregate. The difference between these two teams is approximately 8.66 points in the standings, or a little more than four wins. This seems like a reasonable estimate of the value of the average #1 or #2 defenseman.

If we look purely at the change in goals allowed due to not having one good defenseman in particular in the lineup, it accounts for approximately six goals per season. The difference in expected save percentage between the best and worst defensive teams using a simple shot quality model (see: http://www.behindthenet.ca/2008/5_on_5_goalie_shot_quality.php?sort=7&mingp=20) translates to approximately 20-25 goals per 82 games. If we assume that having neither a #1 or #2 defenseman on your team costs you twelve goals on shooting percentage alone, it seems unlikely that much more than half of this 20-25 goal difference is due to a weak defensive corps.

Do Defensemen influence Save Percentage?

2009-07-29T00:02:00.000-07:00

[Note: this methodology is similar to a previous analysis of replacement level: http://www.behindthenet.ca/blog/2008/04/replacement-level-how-many-wins-do.html. It is obvious that teams do worse when their top players are out of the lineup, but it's not clear what suffers.]

In order to answer this question, I made a list of defensemen over the last four seasons who averaged more than 22 minutes per game and played between 20 and 70 games in a given season. 22 minutes of TOI corresponds approximately to the 60th-best defenseman, which means that the group of subjects includes mostly 1st and 2nd defensemen.

I then counted up the number of even-strength goals and shots against when each defenseman was in the lineup and when he was not dressed. I further split the defensemen into those whose +/- was better than the team's overall +/- (on a per minute basis). Presumably the group with the "Better +/-" would have more of an impact on even-strength defensive zone play.

The results:

IN OUT
GP G/GP S+G/GP SVPCT GP G/GP S+G/GP SVPCT DELTA
N=28 Better +/- 1610 1.85 21.48 914.0 686 2.04 21.94 907.2 5.8
N=25 Worse +/- 1229 1.89 22.20 915.1 821 1.89 22.00 914.2 0.9

The assumption here is that during a given season, a player's aggregate group of teammates, including the goalie, will be basically unchanged whether he's in the lineup or not. Similarly, his team's aggregate group of opponents is assumed to be the same whether he's in the lineup or not.

While the defensive difference with the "Worse +/-" defensemen out of the lineup was negligible, the teams of the "Better +/-" defensemen allowed 15.5 fewer goals per 82 games when they were playing. One-quarter of this change was due to reducing the volume of shots allowed, but the rest is due to better save percentage.

New Puck Prospectus post: Pulling the Goalie

2009-07-28T13:51:00.001-07:00

"at the end of the game, there is no value to having played it safe and having lost by only one goal. In the last two minutes of regulation time, scoring rates increase dramatically as the team that's down a goal pulls its goaltender for an extra attacker. We can see that the boldest teams pull their goalie with about 90 seconds to go in the game, and at around 40 seconds to go, the goaltender is almost certainly on the bench."

http://www.puckprospectus.com/article.php?articleid=232

Shooting Percentage Estimation Errors

2009-07-27T21:41:00.000-07:00

I recently found location data for missed shots going back four years, so I decided to compare shooting percentage estimates with and without missed shots. When missed shots are included, the high shooting percentage in the slot decreases substantially in size:
We can see where the estimate error is largest by subtracting the dataset that includes misses from the one that doesn't:

So by failing to include missed shots, we've substantially overestimated the shooting percentage in the high slot, 20 to 30 feet out from the goal. We can also express the error as a percentage:

This gives a different result - shots from the blue line are much less likely to go in than we would otherwise think. If we had location data for shots that get blocked (we only know where they were blocked, not where they were shot from), we'd probably find that we're making an even larger overestimate.

Do Fighters Ever Prosper?

2009-07-16T10:20:00.000-07:00

New column on Puck Prospectus:

http://www.puckprospectus.com/article.php?articleid=222

"I looked at every fight during the 2008-09 season where one player received was voted the winner by at least 50% of fans. Since many people vote that a fight was a draw, this picks out only the fights with a clear winner. I then looked at how many goals the winner's team scored and allowed over the next 10 minutes and over the rest of the game. I compared this goal differential with how an average NHL team did given the same initial score and time on the clock. That is, if a team was down 2-1 at the midway point of the 2nd period and won a fight, I compared their performance to all teams that were down 2-1 midway through the second."

Goaltender Pairs and 5v5 Rebounds

2009-07-14T19:04:00.000-07:00

Here are all of the 2008-09 Goaltending pairs where shot totals were roughly even. Draw your own conclusions...

Name	Team	SH	REB%<2	REB%<4	SPCT
Jonas Hiller	ANH	848	4.12	7.9	932
J. Giguere	ANH	881	3.51	5.78	913
Kari Lehtonen	ATL	1086	3.68	6.07	923
Johan Hedberg	ATL	621	3.54	6.11	909
Tim Thomas	BOS	1266	3.55	5.92	940
Manny Fernandez	BOS	619	4.68	6.78	927
N. Khabibulin	CHI	862	4.52	7.54	932
Cristobal Huet	CHI	760	3.94	5.92	917
Peter Budaj	COL	1154	4.59	6.06	906
Andrew Raycroft	COL	650	3.38	6.61	909
Ty Conklin	DET	779	3.97	7.7	920
Chris Osgood	DET	894	5.25	6.48	904
Tomas Vokoun	FLA	1463	4.98	8.2	935
Craig Anderson	FLA	726	4.26	6.74	928
Jonathan Quick	LA	875	3.08	5.71	923
Erik Ersberg	LA	471	3.18	5.09	912
Carey Price	MON	1115	3.76	5.91	921
Jaroslav Halak	MON	814	3.43	6.38	923
Scott Clemmensen	NJ	869	3.79	5.06	927
Martin Brodeur	NJ	629	5.08	6.67	934
Pekka Rinne	NSH	1173	4.17	6.64	927
Dan Ellis	NSH	678	4.27	6.48	918
Yann Danis	NYI	695	3.45	5.75	922
Joey MacDonald	NYI	1168	4.1	5.99	906
Alex Auld	OTT	829	4.22	6.75	920
Brian Elliott	OTT	601	3.49	5.65	920
Mike Smith	TB	883	3.85	5.77	929
Karri Ramo	TB	498	3.21	7.22	913

Goaltender Rebound Percentage Leaders

2009-07-14T06:16:00.000-07:00

In his work on Shot Quality, Alan Ryder noted that shooting percentage is extremely high on rebounds. That is, in the two seconds following another shot. The overall save percentages for 2008-09:

Overall	1-2 s	3 s	4 s
919	694	807	892

After four seconds, shooting percentages are in the low-to-mid 900s. So it is significant to look at what percentage of a goalie's shots are rebounds allowed less than 2, 3 and 4 seconds after a previous shot. Here are the league "leaders":

Goalie	PCT<2s	PCT<3s	PCT<4s
EVGENI NABOKOV	5.52	6	7.61
MIIKKA KIPRUSOFF	5.33	6.24	8.25
CAM WARD	5.31	6.38	7.09
CHRIS OSGOOD	5.25	5.59	6.48
MATHIEU GARON	5.19	5.73	6.55
MICHAEL LEIGHTON	5.16	6.25	7.06
MARTIN BRODEUR	5.08	5.72	6.67
TOMAS VOKOUN	4.98	6.63	8.2
MANNY FERNANDEZ	4.68	5.81	6.78
PETER BUDAJ	4.59	5.37	6.06

And at the other end:

Goalie	PCT<2s	PCT<3s	PCT<4s
CHRIS MASON	3.25	4.42	5.96
STEVE MASON	3.24	4.43	6.22
KARRI RAMO	3.21	5.22	7.22
ERIK ERSBERG	3.18	4.67	5.09
JONATHAN QUICK	3.08	3.77	5.71
JASON LABARBERA	3	4.6	5.61
RYAN MILLER	2.84	3.84	5.76
BRENT JOHNSON	2.69	3.92	4.9
MARTIN GERBER	2.6	3.9	4.72
JOSH HARDING	1.79	3.58	5.67

Variations on a Theme: Different Formulations of Quality of Competition

2009-07-12T21:53:00.001-07:00

One very nice innovation on Quality of Competition came from Jonathan Willis at Copper 'n Blue. In order to calculate Quality of Competition, you normally need 1) TOI totals for every player; and 2) head-to-head icetime totals for every player combination. This data is only available for the NHL, and it's only available for the last three years. What Willis did was to use goal events as a proxy for icetime. That is, in the absence of TOI, Willis assumed that the total number of goals a player was on the ice for was a reasonable proxy for the amount of time he spent matched up against specific opposing players.

That changes the Quality of Competition from:

QoC = sum[(Opponent Rating)*(Opponent TOI)]/TOI

Where Rating = (GFON/60 - GAON/60) - (GFOFF/60 - GAOFF/60) for each opponent.

To something like:

QoC = sum[(Opponent Rating#2)*(Opponent + and - per GP)]/(Opponent + and - per GP)

Where Rating#2 = (GFON/GP - GAON/GP) - (GFOFF/GP - GAOFF/GP)

Or something very similar - I don't think it matters very much whether you use GP or total events as a proxy for TOI.

At any rate, I generated Quality of Competition four different ways for the Edmonton Oilers. Rankings among regular players are below:


                    QC0 QC1  QC2 QC3
ETHANMOREAU          3   3    5   1
SHELDONSOURAY        2   2   12  12
STEVESTAIOS          9   8    3   5
JASONSTRUDWICK      20  20    8   6
LUBOMIRVISNOVSKY     8  10   17  17
SHAWNHORCOFF         1   1    2   4
ALESHEMSKY           5   7    7  19
ALESKOTALIK         17  17   16   7
DENISGREBESHKOV     11   9   13  14
FERNANDOPISANI       3   6    9  11
MARC-ANTOINEPOULIOT 17  18   15  15
ROBERTNILSSON       11  15    6  10
PATRICKO'SULLIVAN    9  11   11  13
DUSTINPENNER         5   4   10  20
LADISLAVSMID        16  14    4   3
ANDREWCOGLIANO      13  13    1   2
KYLEBRODZIAK        19  19   20   8
ZACHERYSTORTINI     21  21   19  18
TOMGILBERT           5   5   18  16
SAMGAGNER           13  16   14  21
LIAMREDDOX          13  12   21   9

QC0 is Quality of Competition as calculated on my site. QC1 is the same TOI-based calculation, but it includes only the off-ice stats for games the player played in (for simplicity of calculation, QC0 includes all of a team's games.) QC2 assumes total TOI is known, but uses goal events (+ and -) as a proxy for head-to-head icetime. QC3 is the same as QC2, but uses games played as a proxy for TOI.

Some results are similar: everybody loves Horcoff and Moreau; everybody hates Stortini. But there are some substantial differences between these systems too. The TOI based ones favor Sheldon Souray, Dustin Penner and Tom Gilbert, while the proxy systems like Jason Strudwick, Ladislav Smid and Andrew Cogliano.

So my question is - given that I see maybe one Oilers game per season - which system seems to be closest to the right answer? Is the difference tolerable?

Leveraged Icetime Leaders

2009-07-11T15:50:00.000-07:00

I'll introduce the details behind leverage later, but for now I'll just give a short explanation. I'm going to define the leverage of a game state - that is, goal differential and time remaining in the game - as the value in Wins of scoring an additional goal minus the cost in Wins of allowing an additional goal. A simple example:

A game is tied at 19:59 of the third period. If your team scores, it will get two points in the standings = 1 Win. If your team is scored on, it will get no points. So the leverage in this situation is 1 Win, which is the highest possible leverage. Using historical data, we can calculate the leverage for every game state.

The average leverage during 2008-09 was 0.329. The top 25 players in leverage (defined as sum(leverage*shift length)/total toi) are shown below, minimum 600 minutes TOI:


Player          Pos     Lev.    %TOI
ANTTIPIHLSTROM  LW      0.3616  12.3
ANDREWFERENCE   D       0.3607  20.3
BRANDONCROMBEEN RW      0.3604  20.9
SAMUELPAHLSSON  C       0.3604  23.8
JEFFWOYWITKA    D       0.3596  24.1
MIKEWEAVER      D       0.3595  20.1
BRADWINCHESTER  RW      0.3587  15.8
BARRETJACKMAN   D       0.3576  38.3
ROBNIEDERMAYER  C       0.3567  24.6
JAYMCCLEMENT    C       0.3563  27.3
MILANMICHALEK   RW      0.3560  28.5
MANNYMALHOTRA   C       0.3551  27.8
TRAVISMOEN      LW      0.3551  25.0
ZDENOCHARA      D       0.3551  41.7
MIKEGREEN       D       0.3537  34.8
JANHEJDA        D       0.3536  36.6
JAYMCKEE        D       0.3529  23.9
TIMGLEASON      D       0.3519  29.0
SCOTTGOMEZ      C       0.3518  31.9
P. J.AXELSSON   C       0.3517  24.6
BLAIRBETTS      C       0.3516  17.0
JERREDSMITHSON  C       0.3512  23.0
DAVIDBACKES     RW      0.3510  29.2
JOELWARD        RW      0.3508  25.4
BRETTFESTERLING D       0.3508  13.5

We've already identified many of these players as ones who get tough icetime, either by Quality of Competition metrics or through their percentage of "late-and-close" icetime. But some, like Mike Green, didn't make either of those lists despite being on the ice in a lot of tough situations. Not every method is perfect!

Here's the bottom 25:


Player          Pos     Lev.    %TOI
THOMASPOCK      D       0.2818  15.2
BORISVALABIK    D       0.2899  15.5
CHRISBUTLER     D       0.2920  15.8
PHILIPPEBOUCHER D       0.2951  16.6
MICHAELRUPP     LW      0.2974  12.8
ZACHBOGOSIAN    D       0.2989  16.9
JEFFFINGER      D       0.2991  27.1
RICHPEVERLEY    C       0.2995  21.2
ANDYGREENE      D       0.3001  16.1
JOHNMITCHELL    C       0.3002  21.1
NATHANOYSTRICK  D       0.3003  16.8
KYLETURRIS      C       0.3008  16.5
DOUGWEIGHT      C       0.3009  19.4
BOBBYHOLIK      C       0.3009  12.8
KEITHYANDLE     D       0.3010  23.0
BRIANROLSTON    C       0.3011  19.5
NICLASHAVELID   D       0.3011  32.4
ARRONASHAM      RW      0.3016  13.6
JORDANLEOPOLD   D       0.3018  31.4
TIMCONNOLLY     C       0.3018  18.3
ILYAKOVALCHUK   RW      0.3019  34.5
DAVIDHALE       D       0.3023  14.7
OLLIJOKINEN     C       0.3023  28.9
NIKOLAIKULEMIN  LW      0.3024  20.3
NIKLASHAGMAN    LW      0.3025  22.2

Clearly some of these players, including the large number of Toronto and Atlanta players, make this list because their teams were so bad that there weren't any high-leverage situations to play in at all. This method is probably not very useful at the bottom end, but hopefully it gives some insight into who got the toughest minutes on the best teams.

Hockeyfights.com Top Ten Fights of 2008-09

2009-07-11T14:58:00.000-07:00

As voted by the fans. I still don't know why this list doesn't appear on the front page of Hockeyfights.com, but I will happily provide it periodically as a "public service":

Rating	Description	Winner	Video
9.2	Nov 26, 2008 - Carcillo v Dorsett	Draw	Video
8.9	Oct 14, 2008 - Cote v Godard	Godard	Video
8.8	Oct 30, 2008 - Boulton v Orr	Orr	Video
8.5	March 3, 2009 - Downey v Janssen	Draw	Video
8.4	Jan 10, 2009 - Weller v Boll	Weller	Video
8.3	Mar 19, 2009 - Staubitz v Tootoo	Staubitz	Video
8.3	Dec 22, 2008 - Carcillo v Strudwick	Strudwick	Video
8.3	Nov 22, 2008 - Brashear v Shelley	Brashear	Video
8.1	Nov 4, 2008 - Murray v Nystrom	Murray	Video
8.0	Mar 10, 2009 - Brashear v Belak	Belak	Video

WSJ Article: NHL Teams Hunt for Talent in a Frenzied Bazaar

2009-07-09T10:44:00.000-07:00

It's tough to fit into their 250-word limit:

http://online.wsj.com/article/SB10001424052970204261704574276204110346362.html

KHL->NHL Equivalency with TOI

2009-07-09T00:16:00.000-07:00

The value of keeping better statistics has finally moved past the NHL, with the top Finnish, Swedish and Russian leagues tracking and publishing ice time figures for every player. There's very little player movement between the NHL and Finland, but there's enough to generate an NHL Equivalency for the other two leagues that accounts for playing time differences.

Here are the Russian (KHL) and Swedish summaries:


     N  TOI OTH TOI NHL % TOI OTH/82 NHL/82 SAME TOI
KHL  23   18.0    14.5   80.8   45     24     30     
SEL  15   17.9    14.0   77.8   38     22     28

This gives equivalencies of 0.57 for the SEL and 0.54 for the KHL. Adjusting for icetime differences, the NHLEs are 0.78 (SEL) and 0.67 (KHL). The Russian figures are surprisingly low - in the past, the top Russian league was better than the SEL, and approached the caliber of the NHL in some cases.

Puck Prospectus: Analyzing The Sharks' Defense

2009-07-07T13:38:00.001-07:00

http://www.puckprospectus.com/article.php?articleid=216

"One of the downsides of writing about hockey statistics is not necessarily getting to watch all that much hockey. So I decided to watch video of every even-strength goal the San Jose Sharks gave up during the regular season this year."

Joe Thornton's giveaways: bad for the Sharks?

2009-07-03T09:38:00.000-07:00

Joe Thornton made one particularly egregious giveaway this season. Unfortunately, it was at 14:04 of the 3rd period in Game 4 of the first round of the playoffs, making the score 3-0 Ducks and dashing the Sharks' hopes of evening up the series.

Here's the footage:
http://www.nhl.tv/team/console.jsp?hlg=20082009,3,154&event=ANA623

Ugly...

So I set out to figure out how often Thornton made giveaways like that:

http://www.puckprospectus.com/article.php?articleid=202

"Thornton, though? He spends most of his time skating slowly, fighting for the puck behind the opposing team's net, out-muscling guys along the boards, pushing defensemen out of the way as he carries the puck between them. He's a finesse player, no doubt, but he plays a strength game, and it can at times look almost effortless. Unfortunately, with all that puck possession comes a lot of giveaways. Thornton, because he skates slowly, is never in position to recover his giveaways, which leads to a lot of plays where an opposing player's streaking down the ice, while Thornton is stuck in the offensive zone.

At least it seems that way to many observers, and I've been frequently asked to figure out how many goals Joe Thornton's giveaways cost the Sharks."

Swedish Elite League NHLE with TOI

2009-06-28T12:03:00.000-07:00

My attempts to analyze NHL Equivalencies have always been hampered by the question of usage. The NHL has published player ice time (TOI) data for over ten years, but other leagues have been slower to publish the data, either because they didn't track it officially or because they released only a very limited number of statistics to the public.

The Swedish Elite League has now published TOI for two seasons, which allows me to include ice time in the equivalencies. There aren't a huge number of players who've played significant time in both leagues the last two seasons, and because we only have one past season of SEL data, most of the players in question went from the NHL to the SEL, which is not the preferred direction for an equivalency study.

Here's the list:


                    Dir TOI SEL TOI NHL % TOI SEL/82 NHL/82 +22% TOI
Joe DiPenta         SEL   18.4    10.6   57.9   10     18     23
Kris Beech          SEL   18.5    11.5   62.1   62     36     46
Mathias Tjarnqvist  SEL   21.2    13.7   64.3   43     12     15
Ossi Vaananen       SEL   21.2    14.3   67.6   27      9     11
Jaroslav Hlinka     SEL   19.5    13.9   71.3   84     36     47
Petr Tenkrat        SEL   17.0    12.5   73.6   43     18     23
Ronald Petrovicky   SEL   10.5     8.3   79.1    9     16     20
Jan Hlavac          SEL   19.1    15.2   79.3   73     36     46
Josef Melichar      SEL   19.3    18.8   97.6   13     14     18
Michael Holmqvist   SEL   12.7    14.0  109.7   26     17     22
Patric Hornqvist    NHL   17.8    11.4   64.0   46     21     26
Josef Melichar      NHL   19.3    13.8   71.4   13     19     24
Ossi Vaananen       NHL   21.2    17.9   84.5   27     18     24
Fabian Brunnstrom   NHL   12.9    11.6   89.9   56     43     56
Jonas Frogren       NHL   17.3    13.4   77.5    2     14     18
       
                          17.9    14.0   77.8   38     22     28

Players retained approximately 78% of their ice time when they went from the SEL to the NHL, and 57% of their per-game scoring. However, if we compare scoring on a per-minute basis, giving each player 22.2% more ice time, they retain 72% of their scoring. In other words, given equal ice time, we would expect them to score 26% more than they do*. But it's not true for everyone. Victor Hedman played over 21 minutes already as an 18-year-old in Sweden, so it's difficult to imagine him playing much more than that as a rookie in the NHL. Obviously we expect huge skills growth for teenagers, but a 40-point season would be a tremendous achievement for Hedman in Tampa Bay.

*In a previous analysis, I found that when we adjusted AHL players for PP scoring, their NHL Equivalency was 32% higher than if we ignored usage. The usage factor in the SEL and AHL seems to be similar.