The Red Wings’ season is four games in, which is just about the perfect time to take a little stock in the more odd numbers which have evolved in such a small bubble. As the season goes on, trends will tend to correct themselves and the more interesting stats will fade into place.

One such stat is Jakub Kindl’s plus/minus rating. The Red Wings have outscored their opponents 12-2 at 5-on-5 so far this season and Kindl has been on the ice for six of the goals for to zero of the goals against. His +6 rating on the season is tops for the team and second in the league only to the trio of Dion Phaneuf, Phil Kessel, and Tim Gleason

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Six games on the NHL schedule today after last night’s three games saw the Maple Leafs blank the Canadiens, the Flyers outlast the Bruins (and their pregame ceremony) and the Penguins defeat the Canucks in a shootout after a back-and-forth game in Vancouver.

We could joke about Matthew Lombardi’s pace to score 82 game-winners this season or Luongo’s likelihood to let in 120 soft goals, or we could take a look at today’s games and see what’s interesting from last season.

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We have a new stats category for shared ice time available under the Stats And Graphs portion of the top menu. Now you can view complete goalie stats by shared ice time, team strength, and game state.

One of the things this might help us do in the future is help discern something that has bothered advanced statisticians for some time: to help figure out how much a player can help drive his opponents’ shot quality. Let’s take a look at the three goalies who played behind Norris Trophy Finalist defensemen this season. While this is only a small part of a big puzzle, the information here can tell us something useful.

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One doesn’t have to take a giant leap of faith to make the claim that teams which spend more time in the lead tend to win more games. While it’s true that what really matters is which team is in the lead when the final horn sounds, there’s a leaguewide .89 correlation between time spent in the lead and final points earned last season. Alternately, the correlation between time spent trailing and points earned sits at a nice -.876.

However, if we look at a team’s goal differential in close game situations (leading by 1, trailing by 1, or tied) the correlation between goal differential and points jumps to .956. For comparison, the correlation between total goal differential and points is .929. Obviously a team with a good goal differential is going to score more points, but there is a definite difference between a team that can pile it on in blowouts and a team that can gut out the close wins.

Again, we’re shattering no new earth here.  A correlation difference this slight over an 82-game season won’t create a huge bit of difference between what you can see in the numbers and what you can see in the final standings.

Except it kinda does…

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In this post we are going to take a look at an old but ever relevant Wings question of whether Babcock is better advised to play Datsyuk and Zetterberg on the same line or separately.  This post is also an attempt to serve as a tutorial to using some of the statistical tools available exclusively at HockeyCSSI.com

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Lidstrom and Kronwall Graph

The bars are the shared ice time between Lidstrom and Kronwall.

The Line is a running total of Lidstrom’s plus/minus.

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As many of you are aware JJ and I have been working on a new NHL stats system. During the course of development I have made an effort to try to incorporate as much information as possible into the system.
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During the recent playoff series against San Jose:

• Datsyuk had 2:32:35 TOI. The Wings scored 12 goals and San Jose scored 4.
• Zetterberg had 2:33:56 TOI. The Wings scored 13 goals and San Jose scored 3.
• They spent 1:17:57 shared TOI. The Wings scored 10 goals and San Jose 0.

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