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Around SBN: Explaining Jeremy Lin's Early, Surprising Success

And Now For Something Completely Different (TOPHS) on Free Agent Centers


John has provided a large number of posts focusing on the different aspects of the available Free Agent Centers. This is sort of a corollary to his face-off discussion found here. Face-off wins help the team *get* the puck. But how about *keeping* the puck? The NFL tracks turnover ratios. That stat may exist somewhere for the NHL, but I've never seen it. I wanted to see what the FA Centers looked like with respect to their turnover ratios. For comparison's sake, I included Kovalchuk and Clarkson in the mix, since the Devils would obviously be interested in signing either of them. Details after the jump. Oh yeah, viewing wide will probably work better.

Star-divide

Unfortunately, part of the problem with looking at turnover ratios is that the players who handle the puck a lot would tend to turn over the puck a lot. One of the stats nhl.com tracks is total number of shifts. Now, I know players' shift lengths are quite varied, but I felt normalizing their turnover ratios per shift (well, actually one hundred shifts to make the numbers seem more reasonable) would be reasonable.

So what I did was rank the free agent centers that John compared based on their Takeaways minus their number of Giveaways, then divided that by their total number of shifts and multiplied it all by 100. Viola, TurnOvers Per Hundred Shifts (TOPHS). What this stat really measures though is their net turnover ratio for every hundred shifts, i.e every 100 shifts the player would have netted X number of turnovers. Positive numbers mean the player would have taken the puck away this many more times than given it away. Negative numbers mean the player would have given the puck away this many more times than taken it away. Finally, for some comparison against thee best and worst, I included the top 10 forwards and bottom ten. Players had to have played in 20 games to be counted. I figured since it was normalized based on number of shifts, Time On Ice limits wouldn't matter. So without further ado:

Rank

Player

Team

GP

GvA

TkA

TAR

TO/G

FOW

FOL

Tot

FO%

TOI/G

Shifts

TO/100S

1

Sean Bergenheim

NYI

63

16

57

41

0.651

5

12

17

29.4

14:03

1,217

3.369

2

Eric Fehr

WSH

69

9

39

30

0.435

1

1

2

50

12:07

1,010

2.970

3

Marty Reasoner

ATL

80

12

51

39

0.488

512

494

1006

50.9

12:30

1,340

2.910

4

Pavel Datsyuk

DET

80

73

132

59

0.738

590

480

1070

55.1

20:20

2,056

2.870

5

Enver Lisin

NYR

57

3

25

22

0.386

2

1

3

66.7

11:10

829

2.654

6

Colby Armstrong

ATL

79

22

61

39

0.494

10

10

20

50

14:47

1,473

2.648

7

Ryan Kesler

VAN

82

28

83

55

0.671

772

629

1401

55.1

19:37

2,078

2.647

8

Bryan Little

ATL

79

15

51

36

0.456

68

86

154

44.2

15:45

1,374

2.620

9

Michael Grabner

VAN

20

3

13

10

0.5

1

1

2

50

13:54

399

2.506

10

Peter Regin

OTT

75

19

50

31

0.413

240

298

538

44.6

12:53

1,237

2.506

18

Jim Slater

ATL

61

13

35

22

0.361

254

177

431

58.9

12:12

997

2.207

51

Rickard Wallin

TOR

60

14

31

17

0.283

225

281

506

44.5

12:38

1,014

1.677

52

Richard Park

NYI

81

31

61

30

0.37

536

504

1040

51.5

15:45

1,794

1.672

53

Dominic Moore

FLA, MTL

69

12

36

24

0.348

365

298

663

55

14:50

1,445

1.661

73

Vinny Prospal

NYR

75

20

44

24

0.32

327

312

639

51.2

20:06

1,819

1.319

100

John Madden

CHI

79

25

43

18

0.228

613

543

1156

53

15:24

1,798

1.001

101

Brendan Morrison

WSH

74

32

45

13

0.176

501

477

978

51.2

15:44

1,315

0.989

102

Eric Belanger

MIN, WSH

77

23

40

17

0.221

521

403

924

56.4

15:30

1,729

0.983

103

Matt Cullen

CAR, OTT

81

35

54

19

0.235

572

549

1121

51

18:45

1,946

0.976

130

Scott Nichol

SJS

79

17

30

13

0.165

504

328

832

60.6

13:03

1,595

0.815

208

Glen Metropolit

MTL

69

13

18

5

0.072

327

334

661

49.5

13:33

1,274

0.392

209

Jeff Halpern

TBL, LAK

71

21

27

6

0.085

294

276

570

51.6

14:31

1,557

0.385

235

Rob Niedermayer

NJD

71

19

22

3

0.042

478

467

945

50.6

16:48

1,710

0.175

246

Manny Malhotra

SJS

71

28

30

2

0.028

415

249

664

62.5

15:37

1,626

0.123

254

Dean McAmmond

NJD

62

31

32

1

0.016

253

303

556

45.5

12:51

1,182

0.085

264

Kyle Wellwood

VAN

75

30

30

0

0

390

335

725

53.8

13:51

1,395

0.000

331

Craig Conroy

CGY

63

32

26

-6

-0.1

453

426

879

51.5

13:33

1,377

-0.436

344

Tomas Plekanec

MTL

82

58

46

-12

-0.15

791

824

1615

49

19:57

2,226

-0.539

350

Saku Koivu

ANA

71

42

31

-11

-0.15

571

539

1110

51.4

18:34

1,797

-0.612

355

David Clarkson

NJD

46

17

11

-6

-0.13

6

14

20

30

14:26

876

-0.685

361

Patrick Marleau

SJS

82

69

53

-16

-0.2

316

299

615

51.4

21:12

2,225

-0.719

386

Matthew Lombardi

PHX

78

36

20

-16

-0.21

452

458

910

49.7

17:56

1,663

-0.962

409

Robert Lang

PHX

64

24

9

-15

-0.23

375

359

734

51.1

15:04

1,214

-1.236

414

Olli Jokinen

CGY, NYR

82

63

39

-24

-0.29

480

493

973

49.3

17:51

1,799

-1.334

433

Teemu Selanne

ANA

54

39

17

-22

-0.41

62

69

131

47.3

17:19

1,156

-1.903

434

Steve MacIntyre

EDM, FLA

22

3

1

-2

-0.09

0

0

0

0

2:52

105

-1.905

435

Andrew Peters

NJD

29

5

0

-5

-0.17

2

2

4

50

5:11

254

-1.969

436

Ethan Moreau

EDM

76

44

14

-30

-0.39

7

10

17

41.2

14:24

1,462

-2.052

437

Raitis Ivanans

LAK

61

10

0

-10

-0.16

0

0

0

0

4:53

453

-2.208

438

Pierre-Luc Letourneau-Leblond

NJD

27

6

0

-6

-0.22

1

1

2

50

5:31

254

-2.362

439

Alexei Kovalev

OTT

77

71

34

-37

-0.48

1

2

3

33.3

18:09

1,487

-2.488

440

Ilya Kovalchuk

ATL, NJD

76

73

34

-39

-0.51

7

23

30

23.3

22:02

1,563

-2.495

441

Jordin Tootoo

NSH

51

34

13

-21

-0.41

2

6

8

25

10:50

745

-2.819

442

David Koci

COL

43

7

0

-7

-0.16

0

0

0

0

3:03

217

-3.226

 

I included face-off data in the table to see that data side-by-side. A couple "no, duhs" in the data, like Pavel Datsyuk being near the top and Andrew Peters near the bottom. But also a couple surprises. Even based on an equal hundred shifts, the top TOI players are *mostly* near the bottom of the list. Vinny Prospal is the top ranked high TOI center. Richard Park the highest second level and Jim Slater the top third tier center. Not to mention Ilya Kovalchuk near the bottom of the list (and he IS dead last in un-normalized overall turnover ratio, TAR in my table). My data in Excel had similar colored highlights as John's, but for whatever reason I couldn't copy that info in here. Does this change anybody's perspective on any player(s)? I'll be looking at the most commonly mentioned Free Agent Defensemen in the next day or so. Enjoy.

All FanPosts and FanShots are the respective work of the author and not representative of the writers or other users of In Lou We Trust.

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Very cool...

I’ve had a little man-crush on Matt Lombardi from all of John’s articles and this does change my opinion on him slightly at a -0.962 TOPHS. It’s a good stat and calculation yet there one little problem: Different arenas tend to differ on what’s a takeaway and what’s a giveaway. It’s the 2 stats that have the most human influence IMO (maybe scoring changes too?). Either way though, your stats are for a whole season, so it’s pretty accurate. Players with a better ranking most likely handle the puck better than guys at the bottom (sorry Kovy).

by Matthew Ventolo on Jun 3, 2010 9:52 PM EDT reply actions  

It’s the 2 stats that have the most human influence IMO (maybe scoring changes too?).

Add “Hits” to that list.

"There are three kinds of lies: lies, damned lies, and statistics." -Mark Twain (?)

by elesias on Jun 3, 2010 10:08 PM EDT up reply actions  

Well in Kovy’s defense he takes chances he is a high risk high reward player. Ive seen game tape of alot of the other guys and they are much more conservative with the puck. That don’t mean I wouldn’t like to see Kovy be a little more careful. But he is who he is.

by KingHellfire on Jun 3, 2010 11:41 PM EDT up reply actions  

There's no denying that

He does work hard when he has the puck. Some people go a little too far and call it being “fancy”. He was one of the hardest working Devils if not the hardest during the playoffs. But like you said, he’s a high risk player. He gave the puck away a good amount of times at the point during the PP, which would count as a giveaway. Did he skate his heart out to get back and play defense. You betcha. But this stat doesn’t realize that aspect.

To give you a sense of other “superstars” in the league, here’s their respected TOPHS.

Crosby 1.79
Ovechkin 0.70
Malkin -0.36
H. Sedin -0.1
Parise -1.13

Kovie at -2.45. So maybe this stat judges “risk” for a player. Do the Devils want a high risk player long term?

by Matthew Ventolo on Jun 4, 2010 12:09 AM EDT up reply actions  

I like your idea about risk, but some corrections – Crosby is 1.79, and the rest of your +/ are reversed as well, Ovie -.70, Malkin +.36, Sedin +.1 and I have Parise at +.93 (112th overall), so I’m not sure about your number…

Other Devils of note:
Pandolfo, 90th, 1.12
Zajac, 98th, 1.04
Bergfors, 147th, .69
Rolston, 157th, .64
Zubrus, 309, -.26
Langenbrunner, 311th, -.29
Clarkson, 355th, -.68
Elias, 422nd, -1.58

Go Jets
Go Devils

by FrankG929 on Jun 4, 2010 7:51 AM EDT up reply actions  

haha..whoops

I just copy and pasted the stats from NHL to excel and did the A cells minus B (rookie mistake) and did them as quickly as possible. Sorry. Thanks for the corrections. What’s good is they are all still in that +2.0 to -2.0 interval just switched..haha.

by Matthew Ventolo on Jun 4, 2010 11:19 AM EDT up reply actions  

I love the effort
It’s a good stat and calculation yet there one little problem: Different arenas tend to differ on what’s a takeaway and what’s a giveaway. It’s the 2 stats that have the most human influence IMO (maybe scoring changes too?).

It’s worse than that. There’s a possibility there’s a rink bias for even shots. Tom Awad discussed this last December (and makes a case that Brodeur is actually BETTER than what the stats show) Yes, shots. I thought recording shots was straight forward – either the goalie makes a save, it goes in, or it’s not a shot on net. Yet here’s evidence contrary to that.

Yes, I know that completely undercuts some of the stats I’ve used; but unfortunately, the official numbers are what they are. Again, I love the effort, the problem doesn’t lie with you – it’s the base number of the league that’s the problem. Yet, until someone can come up with a provable way to account for rink bias, the stats I use and this stat you formed aren’t going to be end-all be-all stats. And that sucks because the general method is a quick way to count RTSS stats.

Devils in my heart! Devils in my mind! Devils in my eyes! Devils until I die!
In Lou We Trust - The New Jersey Devils SBN Blog

by John Fischer on Jun 4, 2010 12:08 AM EDT up reply actions  

true,

But as njdNYG’cuse pointed out, that variance is lessened over the course of the season, because, unbalanced schedule in mind, everybody plays everywhere and hopefully, at least within one arena over the course of the season, there is some consistency.

Go Jets
Go Devils

by FrankG929 on Jun 4, 2010 7:54 AM EDT up reply actions  

Not entirely true…

Every team plays every team during a season, but the majority of out of conference teams are only played once. Playing 3 times in a divisional rivals’ buildings, 2 times in the rest of the conferences’ buildings, and once in 50% of the opposing conferences’ buildings (which, additionally, will probably be a different list than the other teams from your own division – making comparisons ineffective) could, depending on just how bad the bias is, add up significantly.

It is lessened over the course of the season, and if the teams alternate playing home and away with the out of conference teams, then every two seasons should give an even more accurate picture… but regardless, arena bias is prevalent and even with an “averaging out” effect, the numbers have to be taken with a grain of salt when using them to calculate statistics in which a .01 difference between players means something.

"There are three kinds of lies: lies, damned lies, and statistics." -Mark Twain (?)

by elesias on Jun 4, 2010 8:16 AM EDT up reply actions  

Very interesting stats. Amazing where Eric Fehr, the Caps third line Right Winger, falls on that list. #2!

Rocking the Red since 1975

by CapsFan75 on Jun 6, 2010 7:55 PM EDT reply actions  

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