June 25, 2010

Goalie Statistics for 5 years

So, here is a compilation of all the saves/goals/shots etc. each goalie faced over the last 5 years (inc. playoffs). I may be missing some games, but there is a lot of data here. The "Cred" column is just adjusting the shot quality neutral save percentage based on number of shots faced (regressing to the mean).

EG = Expected Goals
G = Actual Goals
SQN = shot quality neutral save percentage
= 1- 0.0926*G /EG
SV% = real save percentage
= 1 - G / S

Note: The expected goals are adjusted for site based biased shot information.
Few things of note
- Save percentages over 0.920 are not really sustainable (8 goalies in 2010).
- I didn't realize how good Hiller is.
- Raycroft is really bad (allowed almost 100 more goals than average)

1Henrik Lundqvist1017510108470.9170.9220.919
2Jonas Hiller41784023230.9230.9260.918
3Tomas Vokoun95508537530.9210.9180.915
4Jaroslav Halak36773482970.9190.9210.913
5Roberto Luongo112349959290.9170.9140.911
6Craig Anderson48574524050.9170.9170.911
7Timothy Thomas83887266840.9180.9130.910
8Dominik Hasek38993633320.9150.9150.909
9Cam Ward87398368130.9070.9100.907
10Cristobal Huet65495815590.9150.9110.907
11Chris Mason66526045790.9130.9110.907
12Martin Brodeur103548718610.9170.9090.906
13James Howard24642131950.9210.9150.906
14Dan Ellis31982892750.9140.9120.905
15J.S Giguere77676936850.9120.9080.905
16Pekka Rinne32032902760.9140.9120.905
17Ilja Bryzgalov78516656670.9150.9070.904
18Miikka Kiprusoff112449549720.9140.9060.904
19Dwayne Roloson85657697720.9100.9070.904
20Kari Lehtonen66795965950.9110.9080.904
21Manny Fernandez35573133040.9150.9100.904
22Nikolai Khabibulin66516296410.9040.9060.903
23Niklas Backstrom66625435490.9180.9060.903
24Ryan Miller105168628840.9160.9050.903
25Steve Mason34513213200.9070.9080.902
26Martin Biron72026236510.9100.9030.901
27Evgeni Nabokov91877948330.9090.9030.901
28Rick Dipietro59605395580.9060.9040.901
29Josh Harding22511941900.9160.9090.901
30Jason Labarbera31632872900.9080.9060.900
31Marty Turco91328118540.9060.9030.900
32M.A Fleury96168398870.9080.9020.900
33Carey Price45393954080.9100.9040.900
34Manny Legace41123793890.9050.9050.900
35Martin Gerber51694614860.9060.9020.899
36Ray Emery51144514780.9070.9020.899
37Pascal Leclaire43633944200.9040.9010.898
38Jonathan Quick33712983130.9070.9030.898
39Ty Conklin35123003160.9100.9020.898
40Alexander Auld52454735130.9020.9000.897
41Peter Budaj51704605020.9030.8990.896
42Mathieu Garon53144735180.9030.8990.896
43Brian Elliott23342102220.9050.9020.896
44Chris Osgood50584464850.9040.8990.896
45Jose Theodore69746357000.9000.8980.896
46Antero Niittymaki59135275780.9020.8980.896
47Joey Macdonald22202122230.9000.9020.896
48Brian Boucher25862452630.8980.9000.895
49Brent Johnson33752993310.9020.8980.894
50Johan Hedberg42993864300.9000.8970.894
51Curtis Sanford23522152340.9010.8990.894
52Vesa Toskala62175586320.8980.8950.893
53Scott Clemmensen23111952160.9070.8980.893
54Ed Belfour30262793090.8980.8970.893
55Olaf Kolzig54254765430.9000.8940.892
56Mike Smith38053123540.9070.8950.892
57David Aebischer24352202450.8990.8970.892
58Curtis Joseph37683413930.8960.8930.891
59Fredrik Norrena24102102440.8990.8920.889
60Patrick Lalime31162803270.8950.8920.889
61Mikael Tellqvist26362272700.8980.8900.887
62Andrew Raycroft45534065000.8900.8860.885
63Marc Denis27792473050.8900.8860.884
64John Grahame26752373010.8870.8820.882
65Johan Holmqvist24661992680.8910.8750.876


Olivier said...


That Halak kid doesn't look too bad either, uh?

I still haven't tabulated the whole stuff (I'm lazy now) but after reading David Staples interview with Jim Corsi, where Corsi said he used Scoring Chances Save % as an indicator, I made a quick look at Price and Halak's and again Jaro was way in front.

I'm curious to see how much Price and Halak will end up getting paid.

Scott Reynolds said...

Good stuff Javageek. One question (so far). When you say that the "Cred" column regresses these goalies to the mean based on the number of shots they've faced, what are you using for a mean? So far as I can tell, almost all of the goalies see their number go down, which seems a bit odd.

JavaGeek said...

For cred I am using 0.88 as the mean for a "marginal" goalie (a goalie at the lowest possible level for the NHL). Otherwise you end up increasing the percentage on goalies with small samples and very few shots (generally these are marginal goalies). It has only a slight effect on the high shot goalies though