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-   -   2008-09 NHL Goals Above Replacement for Goalies (http://hfboards.hockeysfuture.com/showthread.php?t=634696)

 Chalupa Batman 04-21-2009 11:52 PM

2008-09 NHL Goals Above Replacement for Goalies

This is a little statistic I calculate each season - it's basically a linear transformation of save percentage (so if you don't like save percentage, you won't like this either, and I'm not going to argue with you about it here :D).

The statistics presented:
GD (Goal Differential) - how many goals better (or worse) a netminder is than a league-average NHL goaltender facing the same number of shots.

GARG (Goals Above Replacement Goaltender) - how many goals better (or worse) a netminder is than a replacement-level NHL goaltender facing the same number of shots. I define "replacement level" to be a save percentage 0.015 below league average (this is a bit of a SWAG). Replacement level goaltenders are plentiful and easily available.

SNW/SNL (Support-Neutral Wins and Losses) - if the goaltender had received "average" goal support, how many wins and losses would he have.

I sort this table by GARG, because there's a definite value in playing at a "league average" level for a decent period of time.

Links to the past three years of results here:

Note that I changed the methodology slightly as of 2007-08.

Not responsible for typos, although I'd love to have them pointed out.

2008-09 NHL GOALTENDERS:
NAME
GD
GARGSNWL
Thomas Tim
41.45
66.86
35-19
Backstrom Niklas
29.61
60.50
40-29
Vokoun Tomas
32.08
59.92
33-22
Lundqvist Henrik
15.47
45.57
38-32
Miller Ryan
17.12
43.71
32-26
Ward Cam
13.73
42.25
36-31
Roloson Dwayne
12.45
41.75
33-28
Luongo Roberto
16.99
40.12
30-23
Biron Martin
10.95
36.72
28-25
Mason Steve
11.48
36.35
32-28
Mason Chris
12.07
35.23
30-25
Fleury Marc-Andre
6.90
34.65
31-29
Rinne Pekka
12.12
33.64
26-22
Khabibulin Nikolai
12.93
30.81
23-17
Hiller Jonas
12.20
30.45
22-17
Anderson Craig
15.31
29.97
16-11
Smith Mike
9.08
28.31
22-19
Clemmensen Scott
9.95
27.02
21-18
Nabokov Evgeni
1.71
26.66
31-30
Lehtonen Kari
2.68
25.15
22-22
Bryzgalov Ilya
-5.28
24.63
31-32
Quick Jonathan
6.55
24.55
22-19
Halak Jaroslav
6.32
22.48
18-15
Auld Alex
3.11
20.23
21-20
Kiprusoff Miikka
-12.82
19.50
35-39
Brodeur Martin
6.43
19.48
17-14
Niittymaki Antero
3.42
17.62
15-14
Price Carey
-5.11
17.59
24-25
Huet Cristobal
0.14
16.45
20-19
Harding Josh
9.37
16.17
8-5
Conklin Ty
0.22
15.71
19-19
Gerber Martin
2.00
15.15
13-12
Danis Yann
1.11
15.10
15-15
Tellqvist Mikael
5.92
14.62
9-7
Fernandez Manny
1.16
13.02
14-13
Boucher Brian
4.38
12.83
11-10
LaBarbera Jason
0.58
11.69
12-12
MacDonald Joey
-12.80
10.96
21-25
Weekes Kevin
4.42
10.40
7-5
Theodore Jose
-13.92
9.66
25-29
Johnson Brent
-0.19
8.49
10-10
Budaj Peter
-14.67
8.30
24-30
Giguere Jean-Sebastien
-10.99
8.12
20-23
Turco Marty
-21.81
8.08
33-41
Elliott Brian
-5.37
6.42
13-14
Ellis Dan
-8.28
6.17
15-19
Garon Mathieu
-2.39
5.93
8-9
Valiquette Stephen
-0.61
5.71
6-6
Sanford Curtis
-1.15
5.57
7-8
LaCosta Dan
3.30
4.50
2-0
Ersberg Erik
-5.67
4.09
11-13
Lalime Patrick
-6.04
4.00
10-11
Varlamov Simeon
1.51
3.89
3-2
Leighton Michael
-3.78
3.82
7-8
Montoya Al
1.95
3.75
2-2
3.19
3.72
1-0
Sabourin Dany
-4.80
2.14
7-9
Drouin-Deslauriers Jeff
-2.47
2.06
3-4
Curry John
0.29
1.33
2-1
Kolzig Olaf
-2.66
1.01
3-4
Schwarz Marek
0.46
0.53
0-0
Holt Chris
0.27
0.32
0-0
Helenius Riku
0.18
0.21
0-0
Ramo Karri
-11.16
0.18
9-12
Climie Matt
-1.25
0.03
1-2
Bishop Ben
-1.79
-0.11
1-2
Neuvirth Michal
-1.70
-0.17
1-2
DiPietro Rick
-2.33
-0.24
2-2
Denis Marc
-0.36
-0.26
0-0
Mannino Peter
-2.07
-0.76
1-1
Howard Jimmy
-1.45
-1.03
0-1
McElhinney Curtis
-5.48
-1.28
3-5
Raycroft Andrew
-13.91
-1.37
12-16
Tordjman Josh
-2.35
-1.42
1-1
Niemi Antti
-2.62
-1.74
1-2
-2.98
-1.83
1-2
Krahn Brent
-2.18
-2.04
0-0
Schneider Cory
-5.24
-2.81
2-5
Norrena Fredrik
-4.88
-2.88
2-4
McKenna Mike
-9.02
-2.93
5-8
Pavelec Ondrej
-8.58
-4.07
4-6
Stephan Tobias
-8.05
-4.93
2-3
Toskala Vesa
-28.12
-5.35
20-30
Legace Manny
-16.13
-6.09
9-15
Hedberg Johan
-20.44
-7.31
11-17
Leclaire Pascal
-13.51
-8.65
4-7
Pogge Justin
-11.25
-8.65
2-4
Osgood Chris
-27.27
-9.15
17-26
Joseph Curtis
-15.15
-9.40
5-10

TOP 25 GOALS ABOVE REPLACEMENT GOALTENDER (since 1982-83):
NAMESEASONGARG
Joseph Curtis1992-93
92.73
Hasek Dominik1996-97
89.01
Hasek Dominik1997-98
88.82
Luongo Roberto2003-04
86.42
Vanbiesbrouck John1993-94
86.06
Hasek Dominik1998-99
83.94
Hasek Dominik1993-94
78.50
Lindbergh Pelle1984-85
77.77
Theodore Jose2001-02
76.87
Roy Patrick1991-92
75.70
Belfour Ed1990-91
75.25
Roy Patrick1993-94
75.03
Hasek Dominik1995-96
74.85
Joseph Curtis1991-92
74.34
Joseph Curtis1993-94
74.17
Hextall Ron1986-87
72.23
Kiprusoff Miikka2005-06
72.03
Luongo Roberto2005-06
71.11
Roy Patrick1989-90
71.02
Brodeur Martin2006-07
69.90
Hrudey Kelly1985-86
69.14
Belfour Ed1992-93
68.94
Luongo Roberto2006-07
68.42
Thomas Tim2008-09
66.86
Vokoun Tomas2005-06
66.64

TOP 25 GOAL DIFFERENTIALS (since 1982-83):
NAMESEASONGD
Joseph Curtis1992-93
59.70
Vanbiesbrouck John1993-94
57.38
Hasek Dominik1997-98
56.58
Hasek Dominik1996-97
56.35
Hasek Dominik1998-99
55.78
Hasek Dominik1993-94
55.22
Luongo Roberto2003-04
49.29
Lindbergh Pelle1984-85
48.83
Roy Patrick1991-92
48.61
Roy Patrick1989-90
48.16
Hrudey Kelly1985-86
47.32
Theodore Jose2001-02
47.29
Belfour Ed1990-91
47.00
Roy Patrick1993-94
45.69
Joseph Curtis1991-92
45.05
Froese Bob1985-86
44.82
Hasek Dominik1995-96
44.69
Hextall Ron1986-87
43.23
Peeters Pete1982-83
43.02
Kiprusoff Miikka2005-06
42.76
Melanson Rollie1982-83
41.53
Thomas Tim2008-09
41.45
Belfour Ed1992-93
40.74
Joseph Curtis1993-94
38.44
Hasek Dominik1994-95
37.69

 Chalupa Batman 04-21-2009 11:53 PM

TOP 25 CAREER GOALS ABOVE REPLACEMENT GOALTENDER (since 1982-83):
NAMEGARG
Roy Patrick
867.192
Hasek Dominik
711.925
Brodeur Martin
600.049
Joseph Curtis
563.412
Belfour Ed
537.863
Luongo Roberto
454.156
Hrudey Kelly
433.176
Burke Sean
429.945
Barrasso Tom
422.819
Richter Mike
383.666
Vokoun Tomas
342.143
Hebert Guy
328.695
Khabibulin Nikolai
328.678
Potvin Felix
328.433
Hextall Ron
326.289
Kolzig Olaf
310.292
Giguere Jean-Sebastien
278.369
Osgood Chris
271.717
Vernon Mike
255.237
Puppa Daren
248.985
Hackett Jeff
235.248
Nabokov Evgeni
234.792
Roloson Dwayne
227.020
Thibault Jocelyn
224.722
Theodore Jose
221.976

 otto84 04-22-2009 01:21 PM

Interesting stats indeed, but I'm just wondering how Garon ended up on that first list three different times.

 Chalupa Batman 04-22-2009 01:42 PM

Good catch! Thanks to the powers of modern technology, I had to manually combine Garon's (and Gerber's, Tellqvist's and LaBarbera's) statistics to create an aggregate total of his 2008-09 performance. I then forgot to delete the rows corresponding to their individual team performances.

Thanks! :handclap:

 Czech Your Math 07-13-2012 12:18 AM

Nice work, this is an interesting study. I like how it's translated into a metric of value which allows direct comparison between the goalies in terms of total value. I also like the general design/methodology of the metric.

If I understand correctly, your metric rests on a couple of fundamental assumptions:

- that save % better measures the quality of goaltending than the more direct GAA (of course various factors influence each)

- that the replacement level of goalies is a constant .015 below league average of save %

If you already have the data in a format that allows you to make additional calculations relatively quickly, you might want to try some alternative approaches and see how the results compare.

Have you considered using the more direct GAA? I'm not familiar with much work on goalies, so I wouldn't be surprised if that had already been done, or you have other reason to believe your approach superior to that one.

Whether you use save % or GAA, you might also consider different ways of determining replacement level goaltending. For instance, you could approach it as follows:

- Sort the top 2N (where N is # teams in league) goalies in NHL in terms of games played. Assume the top 1N (in terms of games, or alternatively in terms of either save % or GAA) of those 2N are the "starters" and that the remainder are "backups." Use either the mean or median goalie among goalies 1N+1 to 2N as the replacement level. An alternative to selecting the top 1N goalies is to simply use the "actual" starters and then use the same basic method from there.

- Sort all the goalies in terms of games played or GAA/save% (if use either of latter two, could use min. games or top ~2.5N goalies in games). If sorted by save % or GAA, use the 2N+1 goalie as replacement level. If sorted by games, use a weighted average of GAA/save% for all goalies > 2N in games.

- Sort the top 2N goalies in one of the above ways, and calculate a standard deviation of GAA/save% among those goalies. Then calculate replacement level as X standard deviations below the mean of those 2N goalies.

I'm not saying any of these will necessarily yield better results, but I think they at least some are worth considering. Besides being arbitrary, a fixed number may be more or less accurate as the depth of goaltending and/or league parity vary. I know it's difficult to determine replacement level, but the approaches I outlined above rest on logic of different sorts that might be accepted over a SWAG (however accurate that may be).

 TheHudlinator 07-13-2012 12:28 AM

Are you sure that Kipper is -12 at GD? Seems crazy that he is behind almost all goalies.

 GuineaPig 07-13-2012 06:03 AM

A suggestion, maybe? Don't know if it's a good idea because of the small sample size. But pro-rating the '94-95 season might be a decent idea for the individual season stats.

 Chris Hansen 07-13-2012 01:56 PM

Cool stats - not surprised to see Huet's numbers. Still baffled as to why his NHL numbers floundered so suddenly. Thanks for posting.

 Czech Your Math 07-17-2012 11:40 PM

Does anyone have any views on these methods of determining replacement level goalies? This assumes that GAA and/or Save % are used as the primary basis of the metric for goaltender value.

A) Sort the top 2N (where N is # teams in league) goalies in NHL in terms of games played. Assume the top 1N (in terms of games, or alternatively in terms of either save % or GAA) of those 2N are the "starters" and that the remainder are "backups." Use either the mean or median goalie among goalies 1N+1 to 2N as the replacement level. An alternative to selecting the top 1N goalies is to simply use the "actual" starters and then use the same basic method from there.

B) Sort all the goalies in terms of games played or GAA/save% (if use either of latter two, could use min. games or top ~2.5N goalies in games). If sorted by save % or GAA, use the 2N+1 goalie as replacement level. If sorted by games, use a weighted average of GAA/save% for all goalies > 2N in games.

C) Sort all the goalies by GAA/Sv% (with min. games) and use the 1N+1 goalie as replacement level.

The basis of "A" is that a goalie with the mean/median level of the back-ups should be available by trade for a relatively reasonable amount. The basis of "B" is that goalies not considered starter/backup quality should be available for very little. The basis of "C" is that a goalie who's not of starter quality should be considered replacement level.

 Chalupa Batman 07-17-2012 11:47 PM

When I did this, I did something that was a combination science/art - I looked at each NHL team, and considered who the top two goaltenders were for each team at the start of the season.

Then, I compared their aggregated statistics with those of all other goalies (goalies called up from the minors either due to poor play or injury).

I arrived at about a save percentage difference of about 0.015 for each of the three seasons I tested, and that passed my sniff test, so I went with it. I'd like to do something more rigorous sometime once I have the time.

 Czech Your Math 07-18-2012 12:16 AM

Quote:
 Originally Posted by Taco MacArthur (Post 52653759) When I did this, I did something that was a combination science/art - I looked at each NHL team, and considered who the top two goaltenders were for each team at the start of the season. Then, I compared their aggregated statistics with those of all other goalies (goalies called up from the minors either due to poor play or injury). I arrived at about a save percentage difference of about 0.015 for each of the three seasons I tested, and that passed my sniff test, so I went with it. I'd like to do something more rigorous sometime once I have the time.
That seems reasonable, and similar to the methods which I've considered (you chose "B" it sound like). In the thread for your study, you said it was a "SWAG" (wild guess), but it seems you actually did some research and made a very educated guess in choosing (league avg. SV% - .015) for replacement level. From what I know, as we go back in time, the parity was lower, total league talent was lower, and SV% differed from more recent levels, so I wonder if the differential varied significantly in past decades?

I hope you didn't view my feedback on your study as negative, as it certainly was not intended that way. You did some nice work there.

Is SV% considered more reliable than GAA due to less influence from team/external factors? I haven't looked at goalies too closely, so just wondering what the consensus is.

 Strong Island 07-27-2012 06:57 PM

Quote:
 Originally Posted by Czech Your Math (Post 52654477) Is SV% considered more reliable than GAA due to less influence from team/external factors? I haven't looked at goalies too closely, so just wondering what the consensus is.
SV% is better than GAA. Even strength SV% is even better than regular SV% too.

 Czech Your Math 07-27-2012 07:30 PM

Quote:
 Originally Posted by Strong Island (Post 53042323) SV% is better than GAA. Even strength SV% is even better than regular SV% too.
Where do you find ES SV% and how far back is it available?

Here's some replacement levels I calculated for goalies for the last 28 seasons. "Med 2N" is the top 2N goalies in games played (N= number of teams) are sorted by GAA or SV%. The median of the 1N+1 to 2N goalies is taken as replacement level (middle of the road backup). For instance, in a 30 team league, take the top 60 in GP, sort them by the relevant metric (GAA/SV%), then average goalies #45 & #46 in that metric. "Med N+1" sorts the top 2N goalies in games and uses N+1. "Avg." is the league average. "GVT" is 4% more goals allowed than league average.

 YEAR Med N+1 Med 2N Avg. GVT 2012 91.3% 90.4% 91.4% 91.1% 2011 91.4% 90.7% 91.3% 91.0% 2010 90.9% 90.4% 91.1% 90.7% 2009 91.0% 90.0% 90.8% 90.4% 2008 90.8% 90.0% 90.9% 90.5% 2007 90.5% 89.3% 90.5% 90.1% 2006 90.0% 89.3% 90.1% 89.7% 2004 91.0% 90.5% 91.1% 90.7% 2003 90.8% 89.7% 90.9% 90.5% 2002 90.6% 90.1% 90.8% 90.4% 2001 90.1% 89.3% 90.3% 89.9% 2000 90.5% 89.7% 90.4% 90.0% 1999 90.6% 89.8% 90.8% 90.4% 1998 90.5% 90.0% 90.6% 90.2% 1997 90.3% 89.7% 90.5% 90.1% 1996 90.0% 88.7% 89.8% 89.4% 1995 90.2% 89.0% 90.1% 89.7% 1994 89.3% 88.3% 89.5% 89.1% 1993 88.6% 87.8% 88.5% 88.0% 1992 88.6% 88.1% 88.8% 88.4% 1991 88.9% 87.8% 88.6% 88.1% 1990 88.0% 87.0% 88.1% 87.6% 1989 88.0% 87.1% 87.9% 87.4% 1988 87.8% 86.8% 88.0% 87.5% 1987 88.1% 87.4% 88.0% 87.5% 1986 87.5% 86.1% 87.4% 86.9% 1985 87.7% 86.3% 87.5% 87.0% 1984 87.1% 86.3% 87.3% 86.8%

 Chalupa Batman 12-19-2012 11:44 AM

For what it's worth, I now have goal differentials (and goals above replacement) up, for all NHL seasons starting in the early 1950s (regular and postseason), for all WHA regular seasons, and for other recent seasons.

By goaltender (for instance, http://hockeygoalies.org/bio/roy.html )

Or by NHL team (for instance, http://hockeygoalies.org/bio/nhl/montreal.html )

Will be adding more data as time allow, but this may allow for good comparisons. (I'd also like to add sort capability at some point).

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