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WOWY Is Worthless: Part 2

WOWY is worthless. It's things we know from Corsi plus a big dose of statistical noise. In Part 2, I use WOWG (With or Without Goalie) to look at WOWY.

Cracknell with Halak: 16% better!
Cracknell with Halak: 16% better!
Sergei Belski-USA TODAY Sports

Before I get into the comparison of WOWY to WOWG, let me first review WOWY a little. In part 1, I defined WDiff as (Corsi With) – (Corsi Without). Across the league, there are 24,875 valid WOWY pairs. In part 2 and part 3, for convenience I'm going to use Corsi%, so I threw out any pair that had either 0 events With or 0 events Without. Since small sample sizes are a problem, I also looked at the pairs that had at least 100 events With and 100 events Without (called "100/100") , the pairs that had 200 events With and 200 events Without ( "200/200"), the pairs that had 300 events With and 300 events Without ( "300/300"), and the pairs that had 600 events With and 600 events Without ( "600/600"). Looking at the range of observed WDiff we see

group

mean

sd

0%

2.5%

50%

97.5%

100%

n

All

-1.1

16.6

-100.0

-44.5

-0.6

43.2

100.0

24875

100/100

0.0

5.5

-23.7

-10.9

0.0

10.7

19.9

10623

200/200

0.3

4.8

-22.1

-9.1

0.3

9.8

19.6

6947

300/300

0.4

4.5

-16.4

-8.4

0.4

9.4

19.0

4893

600/600

1.0

4.0

-11.7

-6.7

1.1

9.3

15.1

1335

Going from all pairs to 100/100 things narrow down a lot. Going on to 600/600 narrows things only a little more.

WOWG

So I went through the 2013-14 season and computed WOWY for every skater with each of their team's goaltenders (WOWG). Goaltenders have no effect on Corsi production rates so they serve as a form of placebo (I see some of you with your hands raised. I will answer your question in a minute). So what does the distribution of WOWG WDiff look like? Once again I looked at all pairs, 100/100, 200/200, 300/300, and 600/600.

group

mean

sd

0%

2.5%

50%

97.5%

100%

n

all

-19.0

40.8

-100.0

-100.0

-1.6

19.4

100.0

3537

100/100

0.0

4.6

-17.1

-9.0

-0.1

9.3

17.1

1772

200/200

-0.1

3.9

-12.1

-7.6

-0.2

7.6

13.8

1377

300/300

-0.1

3.6

-11.2

-7.1

-0.2

7.1

12.0

1120

600/600

-0.1

3.0

-10.1

-6.1

-0.1

5.9

8.5

414

Comparing the 100/100 groups, the standard deviation of WOWG is 84% of the standard deviation of WOWY. For 600/600, it's 75%.

In the 300/300 group we see goalies with "effects" of -11% and +12%. There are only 47 WOWY pairs above 11% and many of those include pairs like Player/Patrice Bergeron, Player/Sidney Crosby, and Player/Daniel Sedin. Interestingly, Player/Mark Giordano appears 4 times and Player/TJ Brodie 3. On the low end, only 28 WOWY pairs are below -11%, and many involve Player/Manny Malhotra, Player/Tanner Glass, Player/Andrew MacDonald, and Player/Max Lapierre. You don't need WOWY to know that Patrice Bergeron is going to make people better or that Manny Malhotra is going to make people worse.

Lack of persistence

If we look at the players who aren't paired up with stars who had a WDiff above 11%, do any of the pairs show persistence from season to season?

Player

With

2013-14 WDiff

2012-13 WDiff

64 MIKAEL GRANLUND

29 JASON POMINVILLE

19.0

-27.4

27 CRAIG ADAMS

3 OLLI MAATTA

14.3

NA

42 TYLER BOZAK

21 JAMES VAN RIEMSDYK

13.9

-0.6

44 MORGAN RIELLY

51 JAKE GARDINER

13.4

NA

55 MARK LETESTU

21 JAMES WISNIEWSKI

13.1

6.1

44 NATE THOMPSON

77 VICTOR HEDMAN

12.9

-4.6

40 TROY BODIE

12 MASON RAYMOND

12.8

NA

5 JASON GARRISON

14 ALEXANDRE BURROWS

12.3

8.2

16 ELIAS LINDHOLM

11 JORDAN STAAL

12.1

NA

55 ED JOVANOVSKI

44 ERIK GUDBRANSON

12.1

-28.8

44 BROOKS ORPIK

36 JUSSI JOKINEN

12.0

-6.2

47 TOREY KRUG

63 BRAD MARCHAND

11.9

NA

28 JARRET STOLL

6 JAKE MUZZIN

11.9

-4.5

4 ROB SCUDERI

2 MATT NISKANEN

11.8

NA

48 TOMAS HERTL

88 BRENT BURNS

11.7

NA

84 MIKHAIL GRABOVSKI

81 DMITRY ORLOV

11.5

NA

5 MARK STUART

18 BRYAN LITTLE

11.4

-2.4

74 ALEXEI EMELIN

11 BRENDAN GALLAGHER

11.4

4.1

81 DMITRY ORLOV

52 MIKE GREEN

11.3

-24.9

59 ROMAN JOSI

57 GABRIEL BOURQUE

11.2

-5.1

33 HENRIK SEDIN

18 RYAN STANTON

11.1

NA

6 BEN LOVEJOY

10 COREY PERRY

11.1

5.9

23 VILLE LEINO

57 TYLER MYERS

11.1

1.6

You don't need to look beyond the first line of the table to see the problem.

Are Goaltenders really placebo?

Yes. Presumably, if a goalie is going to have an effect on Corsi, he's a good puck handler. Two of the best puck handling goalies are Martin Brodeur and Mike Smith. In the 300/300 data, Brodeur's average WDiff is -0.9%. Smith is near the bottom of the list at -3.0%. The goaltender with the biggest impact in this group is Anders Lindback with a WDiff of +4.7% Please don't tell me you think Lindback is a good puck handler.

Goaltenders have no effect on Corsi production but the overall distribution of WOWG WDiff is similar to the distribution of WOWY WDiff.  There are a number of skater-goalie WOWG pairs where the goaltender appears to have a substantial effect on the player. That's not effect. That is simply randomness.

I suppose some people still don't feel like goalies are placebos. So, in part 3, I bring you a new and improved placebo, now with even less active ingredient!