2009 NHL Free Agency: Defenseman - Advanced Stats

Intro:

Many fans, journalists and even NHL General Managers still rely on statistics that have been around when your grandfather watched the NHL. Traditional stats like Goals-Assists-Points (aka "boxcar" stats) pre-date World World Two and more recent additions like Plus/Minus became official stats in the 1960s.

When the NHL began monitoring player ice time in the 1997-1998 season it opened the door to a whole new world of more refined data analysis. It is now possible to move beyond the "box car stats" and break apart the chaotic action on the ice and look for patterns. Every player receives his share of good and bad bounces, but in the long run a great NHL player like Nick Lidstrom will tend to cause more positive outcomes than negative outcomes.

One of the holy grails of analysis in baseball and hockey is understanding and predicting defense at the team and individual player level. If you are a NHL GM bidding for the services of Free Agent or weighing a trade offer it could be quite useful to see if advanced stats can give you some additional insight into the player. That is what I will attempt to do in this post on the UFA NHL Defensemen.

The Data:

This table below portray two basic patterns. 1) PLAYER USAGE: How much ice time did the coach give the player in comparison to other defensemen in the NHL; 2) PLAYER SCORING EFFICIENCY: How effective was that defensemen in terms of scoring points while on the ice in that situation.

All defensemen who played at least half a NHL season (41 GP) receive a percentile ranking. The large numbers indicate that they ranked near the very top of the NHL in that category, low numbers near the very bottom. A blank space means that they either failed to play 41 NHL Games or in the case of special teams, they failed to receive a minimum of half a minute of PP or SH ice time per game.

  • EST% = Even Strength Time On Ice Percentile Ranking
  • PPT% = Power Play Time On Ice Percentile Ranking
  • EST% = Short Handed Time On Ice Percentile Ranking
  • TT% = Total Combined Time On Ice Percentile Ranking
  • Off/Def = Ratio of Offensive (PP) ice time to defensive (SH) Ice Time
  • ESR% = Even Strength Scoring Rate Efficiency Percentile Ranking
  • PPR% = Power Play Scoring Rate Efficiency Percentile Ranking
  • TTR% = Total Combined Scoring Rate Efficiency Percentile Ranking

How Can I Use These Numbers?

The Off/Def ratio shows you whether coaches have used this defenseman in a primarly offensive or defensive role. The higher the number the more offensive the role and vice versa. If you're shopping for a defensive defenseman you probably want to start with players who have a low Off/Def ratio.

The ice time percentile ranking show precisely how this player has been used in the last two seasons. If you GM goes and signs Dmitri Kalinin (TT% rankings of 25% and 28%) and claims in the news conference that he just signed a "top four" guy--well you and I both know he's either a) ignorant of where Kalinin ranks among all NHL defenseman or b) trying to pull the wool over the eyes of the home fans. Another example, if your team is shopping for help on the PK and they sign a defense who gets very little PK ice time--you should be very afraid.

The scoring rate numbers also let you peer through the fog with a bit more clarity. The will show which defensemen generate comparatively more points at ES and PP. Some defensemen wrack up a ton of PP points simply because they receivd mounds of PP ice time--but in truth they are not all the efficient (Jay Bouwmeester for example). On the other hand there are D who are very efficient on the PP but you might not notice because their coaching staff doesn't give them all that many minutes (Johnny Oduya for example). Here's a very simple test, compare a defenseman's PPT% to his PPR% if the Rate percentile number is bigger, that player may explode with more PP points if given a larger role on the PP unit.

Stats

 

Player  Year EST% PPT% SHT% TT% Off/Def ESR% PPR% TTR%
Pardy 2009 15% 7% 8% 0.96 49% 33%
Aucoin 2008 36% 83% 25% 61% 1.16 69% 67% 85%
Aucoin 2009 33% 87% 69% 72% 1.07 83% 20% 70%
Semenov 2008 1.01
Semenov 2009 5% 7% 4% 0.95 54% 45%
Alberts 2008 0.89
Alberts 2009 9% 50% 13% 0.85 43% 29%
Bell 2008 1.06
Bell 2009 27% 59% 28% 1.20 15% 87% 81%
Hedican 2008 67% 5% 30% 46% 0.92 77% 12% 52%
Hedican 2009 26% 10% 11% 18% 0.98 4% 37% 11%
Chelios 2008 8% 91% 21% 0.78 71% 37%
Chelios 2009 0.87
Murphy 2008 2% 80% 10% 1.36 40% 68% 91%
Murphy 2009 1.24
Tjarnqvist 2009 0.94
Sydor 2008 23% 36% 17% 28% 1.05 30% 13% 34%
Sydor 2009 30% 23% 30% 33% 0.98 39% 13% 34%
Gauthier 2009 4% 59% 6% 0.82 3% 1%
Seidenberg 2008 29% 46% 27% 41% 1.04 57% 61% 69%
Seidenberg 2009 66% 52% 55% 73% 1.01 79% 55% 71%
Morris 2008 63% 31% 75% 72% 0.94 25% 93% 54%
Morris 2009 57% 37% 35% 57% 1.01 32% 16% 43%
Kalinin 2008 22% 29% 13% 25% 1.05 21% 24% 35%
Kalinin 2009 31% 14% 25% 28% 0.97 61% 21% 46%
Kuba 2008 92% 69% 72% 92% 1.02 73% 35% 68%
Kuba 2009 49% 92% 53% 83% 1.11 51% 81% 85%
Bouillon 2008 30% 55% 26% 0.85 20% 10%
Bouillon 2009 21% 34% 18% 0.89 31% 28%
Beauchemin 2008 96% 54% 93% 95% 0.94 28% 23% 35%
Beauchemin 2009 0.89
De Vries 2008 55% 56% 42% 0.86 61% 38%
De Vries 2009 8% 32% 8% 0.88 4% 3%
Zanon 2008 24% 94% 36% 0.78 6% 4%
Zanon 2009 64% 94% 56% 0.82 11% 7%
Gill 2008 47% 97% 52% 0.78 93% 58%
Gill 2009 30% 77% 30% 0.82 38% 21%
Cullimore 2008 48% 45% 31% 0.87 65% 41%
Cullimore 2009 32% 30% 23% 0.89 20% 20%
Bouwmeester 2008 99% 67% 93% 99% 0.98 74% 50% 67%
Bouwmeester 2009 98% 87% 84% 99% 1.04 67% 54% 71%
McKee 2008 36% 61% 30% 0.84 36% 22%
McKee 2009 16% 80% 26% 0.81 11% 8%
Woywitka 2008 0.97
Woywitka 2009 42% 42% 36% 1.13 26% 44% 57%
Oduya 2008 49% 26% 18% 43% 1.04 81% 56% 74%
Oduya 2009 70% 11% 65% 56% 0.90 81% 67% 62%
Boychuk 2008 1.13
Boychuk 2009 1.02
Leopold 2008 20% 17% 3% 14% 1.05 93% 28% 75%
Leopold 2009 35% 35% 18% 36% 1.06 75% 8% 59%
Skrastins 2008 53% 54% 37% 0.86 8% 5%
Skrastins 2009 72% 78% 53% 0.85 54% 32%
Klee 2008 78% 52% 53% 0.88 18% 16%
Klee 2009 11% 31% 11% 0.89 43% 26%
Huskins 2008 28% 16% 15% 0.95 87% 63%
Huskins 2009 0.91
Foster 2008 13% 48% 2% 16% 1.14 60% 80% 81%
Foster 2009 1.08
Bergeron 2008 9% 79% 26% 1.28 11% 76% 80%
Bergeron 2009 10% 64% 23% 1.23 73% 74% 91%
Malik 2008 62% 53% 45% 0.87 77% 48%
Malik 2009 39% 10% 60% 40% 0.89 13% 0% 6%
Skoula 2008 81% 59% 56% 0.88 22% 15%
Skoula 2009 69% 58% 45% 0.88 35% 26%
Schneider 2008 69% 84% 12% 75% 1.18 95% 64% 94%
Schneider 2009 51% 74% 10% 58% 1.15 47% 71% 82%
Walker 2008 17% 30% 14% 0.88 3% 2%
Walker 2009 22% 41% 20% 0.87 61% 44%
Ohlund 2008 84% 66% 53% 87% 1.04 73% 63% 77%
Ohlund 2009 60% 44% 56% 66% 0.99 45% 29% 52%
Komisarek 2008 82% 77% 64% 0.85 60% 39%
Komisarek 2009 68% 83% 54% 0.84 16% 15%
Oystrick 2009 20% 3% 8% 12% 0.98 66% 62% 55%
Boynton 2008 28% 43% 22% 0.87 41% 28%
Boynton 2009 13% 25% 19% 19% 1.01 93% 15% 69%
Schultz 2008 70% 78% 54% 0.84 49% 30%
Schultz 2009 71% 81% 52% 0.84 7% 8%
Tollefsen 2008 1% 26% 1% 0.85 10% 12%
Tollefsen 2009 0.95
Vaananen 2009 31% 71% 31% 0.83 55% 40%
Brisebois 2008 21% 46% 20% 1.15 14% 72% 62%
Brisebois 2009 7% 51% 13% 1.20 69% 29% 66%
Mara 2008 21% 40% 24% 30% 1.04 66% 40% 64%
Mara 2009 23% 49% 33% 38% 1.04 18% 49% 56%
Boucher 2008 1.00
Boucher 2009 43% 38% 34% 46% 1.02 22% 18% 31%
Scuderi 2008 43% 74% 39% 0.83 6% 5%
Scuderi 2009 36% 93% 41% 0.80 60% 29%
Niedermayer 2008 64% 76% 83% 88% 1.02 48% 94% 84%
Niedermayer 2009 94% 83% 99% 98% 0.97 77% 93% 92%
O'Donnell 2008 16% 87% 24% 0.79 8% 11%
O'Donnell 2009 53% 96% 52% 0.81 20% 11%
Zubov 2008 85% 94% 65% 96% 1.10 96% 81% 97%
Zubov 2009 1.17
Hnidy 2008 9% 10% 6% 0.93 17% 20%
Hnidy 2009 16% 2% 11% 11% 0.96 52% 14% 36%
Eminger 2008 0.98
Eminger 2009 65% 32% 51% 67% 0.98 44% 79% 63%
Montador 2008 1% 22% 1% 1.11 98% 69% 94%
Montador 2009 14% 13% 20% 15% 0.98 90% 5% 62%
Numminen 2008 0.98
Numminen 2009 23% 29% 16% 26% 1.04 69% 52% 64%
Koistinen 2008 12% 70% 19% 1.26 40% 70% 82%
Koistinen 2009 1.23

 

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