Players outscoring their regular season pace

Unaffiliated

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I saw post a while ago re: sakic/forsberg, having something to do with comparing their points-per-game and goals-per-game paces in regular season and playoffs.

Anyway, I was wondering if the person who had posted that had a full list or something, because I seem to remember sakic and forsberg's better-than-regular-season paces being significant.


apologies for the ambiguity, but i read it a while ago and my recollection of it is a little spotty.
 

Teus

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Can't help you with the list, but Johan Franzén is an interesting one from recent years when it comes to regular season vs playoff stats. Quick calculations gave these career PPG averages:

Regular season - 0.63
Playoffs - 0.92

If you only look at his breakout season in 2007-08 and forward, the difference is even greater:

Regular season - 0.70
Playoffs - 1.15
 

seventieslord

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I know comparisons like this can be skewed by a player playing a high percentage of their playoff games at the start, middle, or end of their career, but nonetheless I would like to see a list of the best and worst ratios among active players with at least 300 regular season games and 30 playoff games: playoff PPG/regular season PPG.

I am thinking Franzen takes it (and his results will regress to the mean eventually) but I'd like to see someone actually check.
 

Canadiens1958

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Worthwhile

I know comparisons like this can be skewed by a player playing a high percentage of their playoff games at the start, middle, or end of their career, but nonetheless I would like to see a list of the best and worst ratios among active players with at least 300 regular season games and 30 playoff games: playoff PPG/regular season PPG.

I am thinking Franzen takes it (and his results will regress to the mean eventually) but I'd like to see someone actually check.

Worthwhile project but should be expanded to include line mates and team mates.

A player may out perform their season norms but the line may under perform as a unit. This is often the result of the opposition having the skill set to shut down the other two line mates but not the star or a specific player. From the standpoint of winning the net result is all that matters not the individual result.
 

Big Phil

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google it dude, it's called "looking something up"

http://hfboards.com/showthread.php?t=729233 found this

You're going to be one of those people on a message board huh?

Anyway, the first name that comes to mind for me is Daniel Briere. He has 0.80 ppg in the regular season compared to 1.01 in the playoffs. Quite a significant difference to the point where it is valid to suggest Briere steps up his game come crunch time
 

JackSlater

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Worthwhile project but should be expanded to include line mates and team mates.

A player may out perform their season norms but the line may under perform as a unit. This is often the result of the opposition having the skill set to shut down the other two line mates but not the star or a specific player. From the standpoint of winning the net result is all that matters not the individual result.

This issue may be present in a given series (although I do not really see the significance since the purpose relates to the individual) but over a large enough sample of games it is unlikely to have much impact.

This information would be pretty hard to use because of players playing differing amounts of playoff games in their peaks/primes and strength of their opponents... just like all playoff numbers I suppose.
 
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Canadiens1958

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Objective is Winning

The objective is winning the series not conforming to some statistical norm or abstract or a sample space.

The approach to playing against Gordie Howe in the playoffs as opposed to during the regular season when facing the post 1955 Detroit Red Wings was to neutralize the remaining players beyond Gordie Howe, Lindsay, Delvecchio and Kelly. When Lindsay and Kelly were traded Ulman was added.

Usually Howe played with Lindsay and either a rookie or a fringer, Or with Delvecchio and a fringer. Reduce the effectiveness of the lines third component and let Howe try to beat you on his own. Worked since post 1955 Detroit never won the cup yet in the majority of series Howe out performed his regular season.

Likewise Chicago with Hull and Mikita. Reduce the effectiveness of the other two linemates and the chances of beating Chicago improved significantly.

Same approach worked later with other greats.
 
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gifted88

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Feb 12, 2010
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You're going to be one of those people on a message board huh?

Anyway, the first name that comes to mind for me is Daniel Briere. He has 0.80 ppg in the regular season compared to 1.01 in the playoffs. Quite a significant difference to the point where it is valid to suggest Briere steps up his game come crunch time

:laugh: depends on the day...lol
 

TheMoreYouKnow

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Well, looking at career averages doesn't make a whole lot sense because if guy A played 15 seasons but only played in 7 playoffs right in his prime the PO average is going to look good pretty naturally. Messier is a good case where his career playoff PPG is significantly better than his regular season playoff PPG but then he played 7 seasons towards the end of his career during which his regular season PPG dropped considerably and his teams didn't make the playoffs. His overall regular season PPG is 1.07, his overall playoff PPG is 1.25. But his season career PPG between 82/83 and 96/97 is 1.31, his play-off career PPG between those years is 1.29. The 1983 playoffs being the first ones he played a significant number of games. Still obviously a great playoff player because it is a great feat to even maintain your scoring average in the playoffs as a star forward, but the initially impressive career difference disappears.

If you look at individual seasons vs that year's playoffs you may get a bit of a better snapshot or maybe a series of seasons. Esa Tikkanen between 1987/88 and 1990/91 was a 0.93 PPG player in the regular season but a 1.14 PPG player in the playoffs, scoring 75 points in 66 playoff games. Geoff Courtnall was a 0.86 PPG player in the regular season between 90/91 and 93/94 but a 1.02 PPG player in the playoffs.
 

matnor

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Oct 3, 2009
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I know comparisons like this can be skewed by a player playing a high percentage of their playoff games at the start, middle, or end of their career, but nonetheless I would like to see a list of the best and worst ratios among active players with at least 300 regular season games and 30 playoff games: playoff PPG/regular season PPG.

I am thinking Franzen takes it (and his results will regress to the mean eventually) but I'd like to see someone actually check.

TheMoreYouKnow made a very important point so I'm not sure how informative it is but here is the top-50 of active players (I took PostPts-PostPPG instead of PostPts/PostPPG since the latter will skew the results heavily in favor of players with a low regular-season pace):

| Name | GP | Pts | PPG | PostGP | PostPts | PostPPG | Difference
1. | Johan Franzen | 319 | 164 | 0.51 | 75 | 69 | 0.92 | 0.41
2. | Dennis Wideman | 378 | 165 | 0.44 | 30 | 22 | 0.73 | 0.30
3. | Fernando Pisani | 402 | 153 | 0.38 | 30 | 19 | 0.63 | 0.25
4. | Brent Seabrook | 392 | 144 | 0.37 | 39 | 23 | 0.59 | 0.22
5. | Daniel Briere | 666 | 526 | 0.79 | 86 | 87 | 1.01 | 0.22
6. | Maxime Talbot | 306 | 87 | 0.28 | 59 | 29 | 0.49 | 0.21
7. | Martin St. Louis | 772 | 679 | 0.88 | 45 | 48 | 1.07 | 0.19
8. | Robyn Regehr | 747 | 146 | 0.20 | 41 | 15 | 0.37 | 0.17
9. | Mattias Ohlund | 837 | 338 | 0.40 | 52 | 28 | 0.54 | 0.13
10. | Mikael Samuelsson | 540 | 261 | 0.48 | 81 | 50 | 0.62 | 0.13
11. | Travis Moen | 443 | 75 | 0.17 | 61 | 18 | 0.30 | 0.13
12. | Chris Pronger | 1104 | 661 | 0.60 | 170 | 120 | 0.71 | 0.11
13. | Eric Staal | 479 | 428 | 0.89 | 43 | 43 | 1.00 | 0.11
14. | Henrik Tallinder | 468 | 108 | 0.23 | 36 | 12 | 0.33 | 0.10
15. | Duncan Keith | 404 | 197 | 0.49 | 39 | 23 | 0.59 | 0.10
16. | Andrew Brunette | 950 | 660 | 0.69 | 43 | 34 | 0.79 | 0.10
17. | Samuel Pahlsson | 636 | 162 | 0.25 | 81 | 28 | 0.35 | 0.09
18. | Saku Koivu | 863 | 693 | 0.80 | 54 | 48 | 0.89 | 0.09
19. | Patrick Sharp | 419 | 245 | 0.58 | 51 | 34 | 0.67 | 0.08
20. | Raffi Torres | 432 | 182 | 0.42 | 30 | 15 | 0.50 | 0.08
21. | Brad Richards | 700 | 639 | 0.91 | 63 | 62 | 0.98 | 0.07
22. | Craig Rivet | 886 | 233 | 0.26 | 69 | 23 | 0.33 | 0.07
23. | Shawn Horcoff | 637 | 374 | 0.59 | 35 | 23 | 0.66 | 0.07
24. | Michal Rozsival | 637 | 226 | 0.35 | 33 | 14 | 0.42 | 0.07
25. | Tim Connolly | 559 | 353 | 0.63 | 30 | 21 | 0.70 | 0.07
26. | Stephane Robidas | 643 | 176 | 0.27 | 44 | 15 | 0.34 | 0.07
27. | Mike Richards | 372 | 283 | 0.76 | 52 | 43 | 0.83 | 0.07
28. | Ruslan Salei | 842 | 194 | 0.23 | 51 | 15 | 0.29 | 0.06
29. | Matt Bradley | 569 | 130 | 0.23 | 38 | 11 | 0.29 | 0.06
30. | Andrew Ference | 570 | 141 | 0.25 | 74 | 22 | 0.30 | 0.05
31. | Matt Cullen | 880 | 461 | 0.52 | 63 | 36 | 0.57 | 0.05
32. | Bryan McCabe | 1068 | 500 | 0.47 | 51 | 26 | 0.51 | 0.04
33. | Niklas Kronwall | 308 | 144 | 0.47 | 63 | 32 | 0.51 | 0.04
34. | Alex Kovalev | 1228 | 990 | 0.81 | 116 | 98 | 0.84 | 0.04
35. | Shane Hnidy | 547 | 71 | 0.13 | 37 | 6 | 0.16 | 0.03
36. | Adam Mair | 550 | 110 | 0.20 | 35 | 8 | 0.23 | 0.03
37. | Anton Volchenkov | 428 | 94 | 0.22 | 61 | 15 | 0.25 | 0.03
38. | Brian Rafalski | 770 | 467 | 0.61 | 154 | 97 | 0.63 | 0.02
39. | Christian Ehrhoff | 421 | 176 | 0.42 | 50 | 22 | 0.44 | 0.02
40. | Joffrey Lupul | 395 | 225 | 0.57 | 39 | 23 | 0.59 | 0.02
41. | Mark Eaton | 531 | 78 | 0.15 | 60 | 10 | 0.17 | 0.02
42. | J.P. Dumont | 752 | 504 | 0.67 | 48 | 33 | 0.69 | 0.02
43. | Jamal Mayers | 737 | 188 | 0.26 | 48 | 13 | 0.27 | 0.02
44. | Adrian Aucoin | 933 | 364 | 0.39 | 47 | 19 | 0.40 | 0.01
45. | Wade Redden | 994 | 450 | 0.45 | 101 | 47 | 0.47 | 0.01
46. | Rob Scuderi | 373 | 50 | 0.13 | 55 | 8 | 0.15 | 0.01
47. | Jarome Iginla | 1024 | 920 | 0.90 | 54 | 49 | 0.91 | 0.01
48. | Dan Boyle | 676 | 407 | 0.60 | 66 | 40 | 0.61 | 0.00
49. | Tomas Holmstrom | 879 | 469 | 0.53 | 164 | 88 | 0.54 | 0.00
50. | Jamie Langenbrunner | 965 | 606 | 0.63 | 137 | 86 | 0.63 | -0.00

And here is the bottom 50:

| Name | GP | Pts | PPG | PostGP | PostPts | PostPPG | Difference
1. | Nik Antropov | 603 | 371 | 0.62 | 35 | 8 | 0.23 | -0.39
2. | Steve Sullivan | 846 | 660 | 0.78 | 35 | 14 | 0.40 | -0.38
3. | Teemu Selanne | 1186 | 1260 | 1.06 | 105 | 72 | 0.69 | -0.38
4. | Antoine Vermette | 458 | 245 | 0.53 | 42 | 8 | 0.19 | -0.34
5. | Todd White | 635 | 379 | 0.60 | 43 | 11 | 0.26 | -0.34
6. | Radek Dvorak | 1052 | 534 | 0.51 | 39 | 7 | 0.18 | -0.33
7. | Mike Comrie | 568 | 359 | 0.63 | 32 | 10 | 0.31 | -0.32
8. | Joe Thornton | 915 | 931 | 1.02 | 91 | 65 | 0.71 | -0.30
9. | Erik Cole | 538 | 338 | 0.63 | 43 | 14 | 0.33 | -0.30
10. | Ray Whitney | 1072 | 869 | 0.81 | 83 | 43 | 0.52 | -0.29
11. | Pavel Datsyuk | 606 | 592 | 0.98 | 110 | 76 | 0.69 | -0.29
12. | Eric Belanger | 634 | 299 | 0.47 | 37 | 7 | 0.19 | -0.28
13. | Pavol Demitra | 847 | 768 | 0.91 | 94 | 59 | 0.63 | -0.28
14. | Alexei Ponikarovsky | 493 | 266 | 0.54 | 34 | 9 | 0.26 | -0.27
15. | Simon Gagne | 664 | 524 | 0.79 | 90 | 47 | 0.52 | -0.27
16. | Pavel Kubina | 822 | 348 | 0.42 | 38 | 6 | 0.16 | -0.27
17. | Jeff Carter | 381 | 277 | 0.73 | 41 | 19 | 0.46 | -0.26
18. | Keith Tkachuk | 1201 | 1065 | 0.89 | 89 | 56 | 0.63 | -0.26
19. | Shane Doan | 1047 | 678 | 0.65 | 35 | 14 | 0.40 | -0.25
20. | Milan Michalek | 383 | 248 | 0.65 | 40 | 16 | 0.40 | -0.25
21. | Alex Tanguay | 739 | 617 | 0.83 | 98 | 59 | 0.60 | -0.23
22. | Chuck Kobasew | 410 | 169 | 0.41 | 44 | 8 | 0.18 | -0.23
23. | Ales Hemsky | 443 | 353 | 0.80 | 30 | 17 | 0.57 | -0.23
24. | Patrick Eaves | 307 | 112 | 0.36 | 43 | 6 | 0.14 | -0.23
25. | Tomas Kaberle | 820 | 482 | 0.59 | 77 | 28 | 0.36 | -0.22
26. | Glen Metropolit | 407 | 159 | 0.39 | 30 | 5 | 0.17 | -0.22
27. | Andrei Markov | 616 | 363 | 0.59 | 49 | 18 | 0.37 | -0.22
28. | Jarret Stoll | 433 | 253 | 0.58 | 30 | 11 | 0.37 | -0.22
29. | Steve Ott | 410 | 149 | 0.36 | 34 | 5 | 0.15 | -0.22
30. | Scott Walker | 829 | 397 | 0.48 | 30 | 8 | 0.27 | -0.21
31. | Marc-Andre Bergeron | 399 | 194 | 0.49 | 43 | 12 | 0.28 | -0.21
32. | John-Michael Liles | 447 | 229 | 0.51 | 36 | 11 | 0.31 | -0.21
33. | Robert Lang | 989 | 703 | 0.71 | 91 | 46 | 0.51 | -0.21
34. | Joni Pitkanen | 411 | 221 | 0.54 | 39 | 13 | 0.33 | -0.20
35. | Derek Roy | 434 | 348 | 0.80 | 40 | 24 | 0.60 | -0.20
36. | Paul Gaustad | 342 | 133 | 0.39 | 31 | 6 | 0.19 | -0.20
37. | Darcy Tucker | 947 | 476 | 0.50 | 68 | 21 | 0.31 | -0.19
38. | Ryan Whitney | 354 | 199 | 0.56 | 38 | 14 | 0.37 | -0.19
39. | Jason Pominville | 386 | 306 | 0.79 | 40 | 24 | 0.60 | -0.19
40. | Steve Reinprecht | 634 | 372 | 0.59 | 50 | 20 | 0.40 | -0.19
41. | Brian Rolston | 1121 | 703 | 0.63 | 70 | 31 | 0.44 | -0.18
42. | Andrew Ladd | 321 | 149 | 0.46 | 53 | 15 | 0.28 | -0.18
43. | Marco Sturm | 855 | 466 | 0.55 | 52 | 19 | 0.37 | -0.18
44. | Craig Conroy | 991 | 540 | 0.54 | 81 | 30 | 0.37 | -0.17
45. | Jason Arnott | 1099 | 873 | 0.79 | 106 | 66 | 0.62 | -0.17
46. | Daniel Alfredsson | 1002 | 992 | 0.99 | 107 | 88 | 0.82 | -0.17
47. | Dean McAmmond | 996 | 448 | 0.45 | 46 | 13 | 0.28 | -0.17
48. | Marian Hossa | 832 | 770 | 0.93 | 120 | 91 | 0.76 | -0.17
49. | Niklas Hagman | 628 | 251 | 0.40 | 30 | 7 | 0.23 | -0.17
50. | Marc-Edouard Vlasic | 309 | 92 | 0.30 | 45 | 6 | 0.13 | -0.16
 
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JackSlater

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The objective is winning the series not conforming to some statistical norm or abstract or a sample space.

The approach to playing against Gordie Howe in the playoffs as opposed to during the regular season when facing the post 1955 Detroit Red Wings was to neutralize the remaining players beyond Gordie Howe, Lindsay, Delvecchio and Kelly. When Lindsay and Kelly were traded Ulman was added.

Usually Howe played with Lindsay and either a rookie or a fringer, Or with Delvecchio and a fringer. Reduce the effectiveness of the lines third component and let Howe try to beat you on his own. Worked since post 1955 Detroit never won the cup yet in the majority of series Howe out performed his regular season.

I must admit that I never played on a team that used the "shut down the worst player and make the best player beat us" strategy, and I have not noticed it used often in the NHL in recent decades either. As far as Detroit not winning the Stanley Cup, that is likely more a function of the team as a whole being worse after 1955 (in addition to a Montreal dynasty) and not teams deciding to allow Howe to dominate them.

Likewise Chicago with Hull and Mikita. Reduce the effectiveness of the other two linemates and the chances of beating Chicago improved significantly.

Same approach worked later with other greats.

I can see a similar strategy being effective against Mikita, not shutting down his linemates necessarily but clogging passing lanes at least. Against Hull though as far as I can tell (reading/NHL classics) teams would try to use a player or two to shut him down individually, not his linemates. I don't recall Claude Provost checking Hull's linemates.
 
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Unaffiliated

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TheMoreYouKnow made a very important point so I'm not sure how informative it is but here is the top-50 of active players (I took Post-Pts-Post-PPG instead of Post-Pts/Post-PPG since the latter will skew the results heavily in favor of players with a low regular-season pace):

i'm not exactly sure what you mean here... could you elaborate a little? i'm probably being stupid.



and how did you compile that table? just using Excel, or?
 

matnor

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i'm not exactly sure what you mean here... could you elaborate a little? i'm probably being stupid.


and how did you compile that table? just using Excel, or?

I just mean how I calculated the difference between regular and playoff scoring. As an example, for Johan Franzén I took 0.92-0.51=0.41. What I could have done instead was to take the ratio measure: 0.92/0.51=1.80. While this gives you the percentage increase (in this case 80%) it would give (in my opinion) too large values when players have a very low regular season scoring pace.

As for how I compiled the table, I used the dataset from the hockey-databank (see http://sports.groups.yahoo.com/group/hockey-databank/). Then I used the dataset with Stata (which is the statistical software I mainly use) to create the tables.
 

Canadiens1958

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Targeting the Weak Link

Old adage that you are only as strong as your weakest link applies to hockey.

The strategy of targeting and reducing the effectiveness of the secondary or support players dates back to the start of hockey.

Classic example would be the 1971 upset of the Bruins by the Canadiens. Casual observers give credit to Ken Dryden as the only reason, those with a bit of knowledge point to the experienced talent that the Canadiens had. Both factors contributed but a quick look at the Bruins stats for the 1970-71 season:

http://www.hockey-reference.com/teams/BOS/1971.html

shows that the Canadiens systematically reduced the performance of the Bruins beyond Orr and Esposito. Orr had 12 pts in the 7 games which was on pace with his regular season. Esposito was slightly behind pace. The rest of the Bruins were well behind their usual offensive contributions. Cashman and Hodge, the Stanfield / Bucyk / McKenzie line all were well below their seasonal number. The third line Sanderson/Westfall plus a rotating LW wsa furher neutralized. Zero production from the LW. Not a coincidence.

The most recent example would be the just finished Canadiens Bruins series. Bruins won because they reduced the effectiveness of the Canadiens weakest forwards. Darche, Kostitsyn, Pouliot and Moen who contributed during the season were shut down effectively. The Canadiens did not reciprocate - unable to find a solution for Kelly and Peverley they lost.

Bill Russell at various times and in various publications clearly states that the reason why the Celtics had success against the Lakers was because they made sure that the Lakers production from the 4th and 5th man was reduced as much as possible. Easier to do than shutting down Wilt, Baylor and West.
 
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Unaffiliated

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I just mean how I calculated the difference between regular and playoff scoring. As an example, for Johan Franzén I took 0.92-0.51=0.41. What I could have done instead was to take the ratio measure: 0.92/0.51=1.80. While this gives you the percentage increase (in this case 80%) it would give (in my opinion) too large values when players have a very low regular season scoring pace.

As for how I compiled the table, I used the dataset from the hockey-databank (see http://sports.groups.yahoo.com/group/hockey-databank/). Then I used the dataset with Stata (which is the statistical software I mainly use) to create the tables.

ah, ok. makes perfect sense.

i was just confused because the hyphens in Post-Pts, Post-PPG, etc. are the same symbol as the subtraction sign.
 

JackSlater

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Old adage that you are only as strong as your weakest link applies to hockey.

The strategy of targeting and reducing the effectiveness of the secondary or support players dates back to the start of hockey.

Classic example would be the 1971 upset of the Bruins by the Canadiens. Casual observers give credit to Ken Dryden as the only reason, those with a bit of knowledge point to the experienced talent that the Canadiens had. Both factors contributed but a quick look at the Bruins stats for the 1970-71 season:

http://www.hockey-reference.com/teams/BOS/1971.html

shows that the Canadiens systematically reduced the performance of the Bruins beyond Orr and Esposito. Orr had 12 pts in the 7 games which was on pace with his regular season. Esposito was slightly behind pace. The rest of the Bruins were well behind their usual offensive contributions. Cashman and Hodge, the Stanfield / Bucyk / McKenzie line all were well below their seasonal number. The third line Sanderson/Westfall plus a rotating LW wsa furher neutralized. Zero production from the LW. Not a coincidence.

The most recent example would be the just finished Canadiens Bruins series. Bruins won because they reduced the effectiveness of the Canadiens weakest forwards. Darche, Kpstitsyn, Pouliot and Moen who contributed during the season were shut down effectively. The Canadiens did not reciprocate - unable to find a solution for Kelly and Peverley they lost.

What you are talking about here is certainly true, but reducing the effectiveness of players on other lines is different from what was brought up earlier.

Bill Russell at various times and in various publications clearly states that the reason why the Celtics had success against the Lakers was because they made sure that the Lakers production from the 4th and 5th man was reduced as much as possible. Easier to do than shutting down Wilt, Baylor and West.

Scoring in basketball and hockey is fundamentally different, so I don't know how appropriate the example is no matter how true. With regard to the 60s Celtics, it certainly didn't hurt that they generally had far superior depth compared to every other team other than Chamberlain's philadelphia teams.

Good job by matnor by the way.
 

Canadiens1958

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Hockey and the Buffalo Herd Theory

Bobby Orr supported all three of the Bruins lines from his defensive position and quarterbacked the PP. As such how the Canadiens defensed all situations pertains to the on going point.

Taking the PP first. The Bruins PP featured Stanfield on the point opposite Orr with Bucyk often playing the LW. Teams that overplayed Orr or did not cover the rebounds were vulnerable to goals from the left side . The Canadiens did not overplay to Orr's side and the Bruins did not get the easy PP goals.

For the three lines. Orr with the Esposito line. Basically the idea was to to keep Cashman and Hodge away from the scoring areas. Dryden's size caused Esposito to move back a few feet from his comfort zone.Combined this reduced the overall effectiveness of the line. The final key was preventing Orr's defensive partner from contributing with this and other lines.

With the Stanfield and Sanderson line the key was preventing the the rebound or easy goal that arose when players would leave their check tor zone to help cover Bobby Orr. This was done successfully.

The basics of playing defense against any line derive from the same theory. The example from the Canadiens / Bruins series just finished being a case in point. Further reduce the effectiveness of the weakest link and you gain a net advantage.

The Bobby Hull example that someone tried to introduce earlier is a prime example of a superficial analysis when credit is given to Claude Provost.

Bobby Hull's performance against the Canadiens and Leafs paled when compared to the other teams because both teams had centers- mainly Henri Richard and Dave Keon that were very quick and efficient forecheckers who would delay the transition game out of the Chicago zone from reaching Hull or the other two forwards be they Hay/Balfour or Esposito/Maki in an efficient fashion. When the puck did reach Hull on a rush or in the zone additional attention was given his linemates.

Like the Buffalo Herd Theory:

http://incolor.inetnebr.com/mjboesen/Literature/Buffalo_Theory.HTML

The elite players may move faster or produce more but eventually the herd loses.

Conversely when subs or lesser players are ignored or paid little attention teams lose. Examples would be Marcel Bonin in 1959, Jim Pappin in 1967, Bob Nystrom, Yvon Lambert, down to Chris Higgins last night.
 
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matnor

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This -- really awesome post.

Would it be too much to ask to run data on significant playoff people? :)
(e.g. gretz mario sakic etc.)

Sure, to get some significant names, here is a list of all players with at least 150 playoff games. As can be seen, this list is quite misleading for the reason mentioned previously. Messier spent most of his playoff games in his prime, while Trottier had the two cup runs as a role player with the Pens that really lowers his number.

| Name| GP| Pts| PPG | PostGP | PostPts | PostPPG | Difference
1. | Mark Messier | 1756 | 1887 | 1.07 | 236 | 295 | 1.25 | 0.18
2. | Chris Pronger | 1104 | 661 | 0.60 | 170 | 120 | 0.71 | 0.11
3. | Doug Gilmour | 1474 | 1414 | 0.96 | 182 | 188 | 1.03 | 0.07
4. | Jari Kurri | 1251 | 1398 | 1.12 | 200 | 233 | 1.16 | 0.05
5. | Claude Lemieux | 1215 | 786 | 0.65 | 234 | 157 | 0.67 | 0.02
6. | Brian Rafalski | 770 | 467 | 0.61 | 154 | 97 | 0.63 | 0.02
7. | Charlie Huddy | 1017 | 453 | 0.45 | 183 | 85 | 0.46 | 0.02
8. | Sergei Fedorov | 1248 | 1179 | 0.94 | 183 | 176 | 0.96 | 0.02
9. | Al MacInnis | 1416 | 1274 | 0.90 | 177 | 160 | 0.90 | 0.00
10. | Tomas Holmstrom | 879 | 469 | 0.53 | 164 | 88 | 0.54 | 0.00
11. | Jean Beliveau | 1125 | 1219 | 1.08 | 162 | 176 | 1.09 | 0.00
12. | Sergei Zubov | 1068 | 771 | 0.72 | 164 | 117 | 0.71 | -0.01
13. | Esa Tikkanen | 877 | 630 | 0.72 | 186 | 132 | 0.71 | -0.01
14. | Gordie Roberts | 1097 | 420 | 0.38 | 153 | 57 | 0.37 | -0.01
15. | Ken Daneyko | 1283 | 178 | 0.14 | 175 | 22 | 0.13 | -0.01
16. | Brian Skrudland | 881 | 343 | 0.39 | 164 | 61 | 0.37 | -0.02
17. | Craig Ludwig | 1256 | 222 | 0.18 | 177 | 28 | 0.16 | -0.02
18. | Glenn Anderson | 1129 | 1099 | 0.97 | 225 | 214 | 0.95 | -0.02
19. | Adam Foote | 1107 | 300 | 0.27 | 170 | 42 | 0.25 | -0.02
20. | Eric Desjardins | 1143 | 575 | 0.50 | 168 | 80 | 0.48 | -0.03
21. | Gordie Howe | 1767 | 1850 | 1.05 | 157 | 160 | 1.02 | -0.03
22. | Brad Park | 1113 | 896 | 0.81 | 161 | 125 | 0.78 | -0.03
23. | Bob Gainey | 1160 | 501 | 0.43 | 182 | 73 | 0.40 | -0.03
24. | Darryl Sydor | 1291 | 507 | 0.39 | 155 | 56 | 0.36 | -0.03
25. | Nicklas Lidstrom | 1412 | 1046 | 0.74 | 247 | 175 | 0.71 | -0.03
26. | Chris Chelios | 1651 | 948 | 0.57 | 266 | 144 | 0.54 | -0.03
27. | Bob Nystrom | 900 | 513 | 0.57 | 157 | 83 | 0.53 | -0.04
28. | Larry Murphy | 1615 | 1216 | 0.75 | 215 | 152 | 0.71 | -0.05
29. | Scott Stevens | 1635 | 908 | 0.56 | 233 | 118 | 0.51 | -0.05
30. | Igor Larionov | 921 | 644 | 0.70 | 150 | 97 | 0.65 | -0.05
31. | Jamie Macoun | 1128 | 358 | 0.32 | 159 | 42 | 0.26 | -0.05
32. | Larry Robinson | 1384 | 958 | 0.69 | 227 | 144 | 0.63 | -0.06
33. | Kirk Maltby | 1072 | 260 | 0.24 | 169 | 31 | 0.18 | -0.06
34. | Glen Wesley | 1457 | 537 | 0.37 | 169 | 52 | 0.31 | -0.06
35. | Brian Propp | 1016 | 1004 | 0.99 | 160 | 148 | 0.93 | -0.06
36. | Geoff Courtnall | 1048 | 799 | 0.76 | 156 | 109 | 0.70 | -0.06
37. | Red Kelly | 1316 | 823 | 0.63 | 164 | 92 | 0.56 | -0.06
38. | Mike Keane | 1161 | 470 | 0.40 | 220 | 74 | 0.34 | -0.07
39. | Jean-Guy Talbot | 1056 | 285 | 0.27 | 150 | 30 | 0.20 | -0.07
40. | Kevin Lowe | 1254 | 431 | 0.34 | 214 | 58 | 0.27 | -0.07
41. | Paul Coffey | 1409 | 1531 | 1.09 | 194 | 196 | 1.01 | -0.08
42. | Stephane Yelle | 991 | 265 | 0.27 | 171 | 32 | 0.19 | -0.08
43. | Jimmy Roberts | 1006 | 320 | 0.32 | 153 | 36 | 0.24 | -0.08
44. | Denis Savard | 1196 | 1338 | 1.12 | 169 | 175 | 1.04 | -0.08
45. | Stan Mikita | 1394 | 1467 | 1.05 | 155 | 150 | 0.97 | -0.08
46. | Wayne Gretzky | 1487 | 2857 | 1.92 | 208 | 382 | 1.84 | -0.08
47. | Dale Hunter | 1407 | 1020 | 0.72 | 186 | 118 | 0.63 | -0.09
48. | Bobby Smith | 1077 | 1036 | 0.96 | 184 | 160 | 0.87 | -0.09
49. | Joe Sakic | 1378 | 1641 | 1.19 | 172 | 188 | 1.09 | -0.10
50. | Mike Modano | 1459 | 1359 | 0.93 | 174 | 145 | 0.83 | -0.10
51. | Darren McCarty | 758 | 288 | 0.38 | 174 | 49 | 0.28 | -0.10
52. | Rod Brind'Amour | 1484 | 1184 | 0.80 | 159 | 111 | 0.70 | -0.10
53. | Jeremy Roenick | 1363 | 1216 | 0.89 | 154 | 122 | 0.79 | -0.10
54. | Guy Carbonneau | 1318 | 663 | 0.50 | 231 | 93 | 0.40 | -0.10
55. | Scott Niedermayer | 1263 | 740 | 0.59 | 202 | 98 | 0.49 | -0.10
56. | Adam Oates | 1337 | 1420 | 1.06 | 163 | 156 | 0.96 | -0.11
57. | Denis Potvin | 1060 | 1052 | 0.99 | 185 | 164 | 0.89 | -0.11
58. | Duane Sutter | 731 | 342 | 0.47 | 161 | 58 | 0.36 | -0.11
59. | Kris Draper | 1110 | 353 | 0.32 | 214 | 45 | 0.21 | -0.11
60. | Henri Richard | 1256 | 1046 | 0.83 | 180 | 129 | 0.72 | -0.12
61. | Peter Forsberg | 706 | 885 | 1.25 | 151 | 171 | 1.13 | -0.12
62. | Mark Recchi | 1571 | 1485 | 0.95 | 164 | 133 | 0.81 | -0.13
63. | Raymond Bourque | 1612 | 1579 | 0.98 | 214 | 180 | 0.84 | -0.14
64. | Craig MacTavish | 1093 | 480 | 0.44 | 193 | 58 | 0.30 | -0.14
65. | Steve Thomas | 1235 | 933 | 0.76 | 174 | 107 | 0.61 | -0.14
66. | John Tonelli | 1028 | 836 | 0.81 | 172 | 115 | 0.67 | -0.14
67. | Clark Gillies | 958 | 697 | 0.73 | 164 | 94 | 0.57 | -0.15
68. | Brett Hull | 1269 | 1391 | 1.10 | 202 | 190 | 0.94 | -0.16
69. | Brendan Shanahan | 1524 | 1354 | 0.89 | 184 | 134 | 0.73 | -0.16
70. | Joe Nieuwendyk | 1257 | 1126 | 0.90 | 158 | 116 | 0.73 | -0.16
71. | Luc Robitaille | 1431 | 1394 | 0.97 | 159 | 127 | 0.80 | -0.18
72. | Jaromir Jagr | 1273 | 1599 | 1.26 | 169 | 181 | 1.07 | -0.19
73. | Ron Francis | 1731 | 1798 | 1.04 | 171 | 143 | 0.84 | -0.20
74. | Steve Yzerman | 1514 | 1755 | 1.16 | 196 | 185 | 0.94 | -0.22
75. | Dave Andreychuk | 1639 | 1338 | 0.82 | 162 | 97 | 0.60 | -0.22
76. | John LeClair | 967 | 819 | 0.85 | 154 | 89 | 0.58 | -0.27
77. | Bryan Trottier | 1279 | 1425 | 1.11 | 221 | 184 | 0.83 | -0.28

Oh, and Mario has a PPG of 1.88 and a postPPG of 1.61 for a difference of -0.28 (rounded) in 107 playoff games.
 

JackSlater

Registered User
Apr 27, 2010
18,074
12,728
Bobby Orr supported all three of the Bruins lines from his defensive position and quarterbacked the PP. As such how the Canadiens defensed all situations pertains to the on going point.

Taking the PP first. The Bruins PP featured Stanfield on the point opposite Orr with Bucyk often playing the LW. Teams that overplayed Orr or did not cover the rebounds were vulnerable to goals from the left side . The Canadiens did not overplay to Orr's side and the Bruins did not get the easy PP goals.

For the three lines. Orr with the Esposito line. Basically the idea was to to keep Cashman and Hodge away from the scoring areas. Dryden's size caused Esposito to move back a few feet from his comfort zone.Combined this reduced the overall effectiveness of the line. The final key was preventing Orr's defensive partner from contributing with this and other lines.

With the Stanfield and Sanderson line the key was preventing the the rebound or easy goal that arose when players would leave their check tor zone to help cover Bobby Orr. This was done successfully.

The basics of playing defense against any line derive from the same theory. The example from the Canadiens / Bruins series just finished being a case in point. Further reduce the effectiveness of the weakest link and you gain a net advantage.

Orr may be a special case in that he played so much and was a defencemen and thus did not have a regular set of forward partners, but the point remains that shutting down the lesser lines has little to do with the scoring of the players on the other lines. Targeting the secondary support players on a team is different than targeting the weakest player on a line.

The Bobby Hull example that someone tried to introduce earlier is a prime example of a superficial analysis when credit is given to Claude Provost.

Bobby Hull's performance against the Canadiens and Leafs paled when compared to the other teams because both teams had centers- mainly Henri Richard and Dave Keon that were very quick and efficient forecheckers who would delay the transition game out of the Chicago zone from reaching Hull or the other two forwards be they Hay/Balfour or Esposito/Maki in an efficient fashion. When the puck did reach Hull on a rush or in the zone additional attention was given his linemates.

Yes, elite defensive centres do tend to deflate the points of the opposition. The impact on the transition game that you are describing impacts all of the forwards, not just the weakest link. Once Chicago entered the zone Montreal's strongest defensive winger in Provost checked Hull for the most part. This is not the plan of a team which wants to shut down the weakest link and let Hull try and beat them. You yourself are saying that Hull's performances paled in comparion to his other performances when playing these teams, and yet you are trying to say that these teams were trying to let him beat them by focusing on the other players, thereby increasing his scoring.

Like the Buffalo Herd Theory:

http://incolor.inetnebr.com/mjboesen/Literature/Buffalo_Theory.HTML

The elite players may move faster or produce more but eventually the herd loses.

Conversely when subs or lesser players are ignored or paid little attention teams lose. Examples would be Marcel Bonin in 1959, Jim Pappin in 1967, Bob Nystrom, Yvon Lambert, down to Chris Higgins last night.

... do not know if you are being serious here.
 

Unaffiliated

Registered User
Aug 26, 2010
11,082
20
Richmond, B.C.
Sure, to get some significant names, here is a list of all players with at least 150 playoff games. As can be seen, this list is quite misleading for the reason mentioned previously. Messier spent most of his playoff games in his prime, while Trottier had the two cup runs as a role player with the Pens that really lowers his number.

[omitted table in quote]

Oh, and Mario has a PPG of 1.88 and a postPPG of 1.61 for a difference of -0.28 (rounded) in 107 playoff games.


Yea, definitely flawed in areas.



Maybe if regular season points were only counted in the years that the team made the playoffs? That might be a lot less straightforward in implementation, though. Either way, still a solid post :)
 

Canadiens1958

Registered User
Nov 30, 2007
20,020
2,779
Lake Memphremagog, QC.
Sophistry IV

Note to Jack Slater,

Trying to figure out how the Canadiens and Leafs played Bobby Hull with your various vapid suppositions, failed inferences precludes you from understanding the explanations past or future so I will stop trying since it is not worth the keystrokes..

If you were not around - a fact that you admitted, for the 1974-75 season to appreciate the Hart that Bobby Clarke won then you obviously were not around to see and appreciate how the Leafs and Canadiens defended against Bobby Hull.

Trying your various attempts at sophistry simply will not work.
 

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