An Expanded look at 5-year performance by NHL Centers

The other day I wrote an article looking at who the best two-way centers over the past 5 seasons and it generated a lot of interest and some requests to look at some more players. I am not going to go into too much analysis here but I have pulled together data for a number of additional centers which I hope will answer some of your questions. The majority of the players in these charts are new players but I have also included several players from the last post (Crosby, Datsyuk, Toews, Kopitar, Getzlaf, Sedin, and Bozak) to provide a

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Who are the best two-way centers in NHL over past 5 seasons?

Maybe the most important position in hockey is center, certainly more important than wing and probably more important than defense or goaltending. Even more important is having a real good two-way center capable of playing big minutes at both ends of the rink. Think about the recent Stanley Cup winners. In Chicago you have Jonathan Toews. In Los Angeles you have Anze Kopitar. In Boston you have Patrice Bergeron. Going further back you have Datsyuk in Detroit. These four guys are maybe the best two-way centermen in the league but I wanted to take a more analytical approach to answering that

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A look at free agent wingers Williams, Semin and Beleskey

I am sure this post will rattle some feathers in the Hockey Analytics community but hey, it won’t be the first time I have accomplished that. I have been looking through the list of potential free agents looking for players that are possibly under valued, possibly over valued, or otherwise interesting for one reason or another. There has been a fair bit of discussion around the three players that are the focus of this post. Justin Williams has been a favourite of the hockey analytics community posting outstanding Corsi numbers year after year. Alexander Semin, who was bought out by the

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TOI% Correlations with Rel Stats

Yesterday I looked at what statistics TOI% correlates with which will give us an indication of how coaches distribute ice time to their players. It has occurred to me that TOI% is really a “Rel” statistic in the sense that TOI% gets handed out to players based on how the players compare to the rest of the team and not the rest of the league. So, in comparing TOI% to overall stats such as GF%, CF%, Sh% I am not really comparing apples to oranges. TOI% is a statistic relative to the players teammates while those other stats are relative to

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What else does TOI% correlate with?

A few days ago I wrote a post looking at whether scoring chances and high danger scoring chances does a very good job at explaining variations in on-ice shooting percentages among NHL forwards. The short answer is that they do explain some of it (scoring chances better than high danger scoring chances) but is still a long way from being an ideal explanatory variable. We know that because I found that TOI% (the percentage of ice time the coach assigns to the player) had a far better correlation with shooting percentages. In this post I want to take a look

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Evaluating SCF and HSCF and our ability to quantify shot quality

This past season War on Ice introduced two new shot quality metrics – Scoring Chances (SC) and High Danger Scoring Chances (HSC) which are defined here.  Stephen Burtch has previously evaluated this scoring chances with respect to their ability to predict future goal scoring and goal differentials and found them to be a better predictor than traditional possession statistics. As a strong believer in shot quality I am not surprised by this conclusion but with this post I want to take a closer look at really how well these metrics are at measuring shot quality. The premise underlying this analysis is

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Persistence of Sv%RelTM and failure of statistical models in hockey analytics

Over the last several days I have tweeted several times (here, here and here) about my Sv%RelTM statistic which can be found on Puckalytics.com which generated some interest from my followers as well as some skeptics.   Seen Sv% rel team thrown out a few times in the past couple days–hoping to get a chance to dig into it more later this week, but an initial — Jason (@Jay32600) June 1, 2015 Obviously this is a miniture sample so I’m hoping to do multi year later this week, but I’m skeptical of the usefullness. — Jason (@Jay32600) June 1, 2015 The

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Is Hockey Analytics altering outcomes yet?

Hockey analytics is well behind analytics in other sports, particularly baseball, but we are now several years into what I will call modern (or current) hockey analytics which has largely focused on possession statistics such as Corsi and Fenwick. Last summer we even saw a number of teams publicly adopt analytics by picking up some prominent people from the public domain. Toronto, Edmonton, Carolina, Florida, and New Jersey to name a few. Results for those teams have clearly been mixed thus far but the greater question is whether hockey analytics, and possession analytics in particular, has had a greater impact on

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Is 4v4 overtime hockey a crap shoot we can or should ignore?

Since the Los Angeles Kings have been eliminated from the playoffs there has been a lot of discussion about why a team with such a good possession game failed to make the playoffs. This included my article from yesterday which generated a fair amount of discussion as well. A lot of the discussion can be summarized by the following tweet by Sunil Agnihotri referencing a comment by Walter Foddis. Nice summary by @Waltlaw69 on why the Kings missed the playoffs. You can imagine the flak he got on FB. pic.twitter.com/O7GVCdbh2p — Sunil Agnihotri (@sunilagni) April 13, 2015 The last paragraph

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Kings, Flames, Avalanche and Possession Analytics

The other day I posted the following twitter comment after the Flames defeated the Kings to gain a playoff position while simultaneously eliminating the reigning Stanley Cup Champion Los Angeles Kings from the playoffs. In the hockey analytics ledger be sure to add #Flames in playoffs and #Kings out to the “what possession analytics didn’t predict” column. — David Johnson (@hockeyanalysis) April 10, 2015 I posted this comment for two reasons. First because I think if you are being honest about evaluating possession analytics you have to consider the failures on an equal ground as the successes. I am certain

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