Perspective On Possession

The more ubiquitous metrics like Corsi and Fenwick become, the stronger their skeptics will argue against them. Though modern analytics have now permeated big-time media and drawn the attention of renowned hockey personalities, they continue to be met with resistance among the more stubborn fans. Somewhere between the polarization of statistics acceptance and complete groupthink is a happy place where opinions may differ but people are knowledgable enough to understand what they’re disagreeing about. I maintain that much of the resistance against advanced statistics is born from a lack of understanding, or a lack of desire to understand. I’ll use Ottawa’s Erik Condra as an example. Condra has been a net relative plus for on-ice possession at even strength for each of his four NHL seasons, yet is seen as expendable by the majority of Senators fans. I’ve heard on multiple occasions that any metric which puts Condra ahead of say, Kyle Turris, must be wrong. What’s getting lost in the shuffle here is that Corsi is not the be-all-end-all stat its doubters perceive it to be. Condra’s CF% REL is telling us he sees a greater share of the 5v5 shot attempts directed at his opponent’s net relative to what occurs when he’s off the ice than Kyle Turris does. Nothing more. This is unequivocal as long as you put trust in the league’s trackers.

There is an axiomatic truth regarding on-ice possession that is seldom spoken albeit intuitive enough not to have to be. Not all possession shares equal worth. The differences that exist between shot rates and shooting percentages while on the ice add or subtract importance to the minutes you play and in turn, the share of shot attempts you generate. At equal CF%, a first-line player’s minutes will hold more value than a fourth-liner’s due to the simple fact more goals are scored in those minutes. It is thus an oversimplification to compare Turris and Condra’s CF% ratings without proper context. A different way to look at possession is to examine the expected goal differential based on shooting percentages we can reasonable expect from the quality of the players on the ice. In other words, how rewarding are a player’s minutes at a set possession share?

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How Do Teams Use Their Top Defensemen

The following is a guest article written by Rob Vollman of Hockey Abstract and Hockey Prospectus fame. Enjoy!

Other than the goalie, a team’s top defensemen are arguably the most important players on the teams. Great ones like Nicklas Lidstrom, Scott Niedermayer and Chris Pronger can completely alter the outcome of an entire season almost single-handedly. Who were the top pairing defensemen this year, how will they used, and how effective were their teams when they were on the ice?
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Evaluating Defensemen using their effect on both team and opponent Corsi%

Courtesy of Wikimedia Commons

Eric Tulsky has previously shown that defensemen have very little control over their opponents on-ice shooting percentages, by demonstrating the extremely low repeatability in the statistic. Recently, Travis Yost expanded on this revolutionary information with showing that on-ice save percentage repeatability is even lower when reducing the impact of goaltender skill level differences; which makes sense when a defender with Ondrej Pavelec is going to have a higher probability of repeating a low save percentage, much like the opposite would be true with Tuukka Rask behind them. This leaves a defender’s influence on shot metrics as their primary impact in improving the team’s chance in winning the game. Tyler Dellow then pushed it one step further by stating the best method of evaluation then is using a defenseman’s impact on a team’s Corsi%.

But, there is one other primary factor: how a defender impacts the opposition. The two are not exactly one in the same, even though they are related:

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Does Shea Weber Deserve the Norris Trophy?

Allow me to preface this article with the following: Shea Weber is one of the best defensemen in the world and a guy the Nashville Predators should hold on to long-term. Trading him is not the answer for a variety of reasons, and if this club evolves into a contender during the Peter Laviolette era, Weber will certainly be a huge reason for that success.

Now that we got that out of the way, I want to take a detailed look at Weber’s performance this year to see if he truly deserves the Norris Trophy. You may have noticed Nashville has been campaigning hard for its captain, who has been snubbed for this award on several occasions.

Naturally, many fans and fellow writers have echoed the Preds’ sentiments, but a lot of folks—even some outside of Boston and Chicago—refuse to jump on this bandwagon.

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What’s the deal with Andrew MacDonald: Why do the statistics suggest he’s terrible?

Did you really think I was going to miss the opportunity to post the AMac with chains gif again? You thought wrong.

Islander Defenseman Andrew MacDonald is one of the hot names being bounced around during the trade deadline.  On one hand, this makes sense: He’s making basically nothing on his current contract, he’s one of the time on ice leaders in the NHL this year and has handled top level competition for a few years now.

On the other hand, his conventional fancystats show a well…..massive decline:

AMacThreeYear

Yikes.  That 2013-2014 number is downright terrible, dropping MacDonald into the bottom tier of defensemen.  And no zone starts and certainly not competition (see this article for an analysis of AMac vs various levels of competition) does not account for this.  If you believed the fancystats, AMac isn’t just not a top tier DMan, but not even a 2nd or 3rd pairing guy who could help any team at all.  Yet teams seem to believe he’s worth a high pick?  So what’s going on?  Is the conventional thought completely wrong here?

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The Skill of Avoiding Hits


The Elusive Austrian is a species that is apparently incredibly hard to hit on an NHL rink.

One of the most derided statistics tracked by the NHL is the “hit.” This is for good reason – outhitting the opposition generally has no correlation to winning hockey games, what correlation it has at all is basically negative (more hits = less winning, mainly due to more hits meaning you have the puck less), and of course, home trackers are known to massively over-count hits for home teams, with certain rinks being particularly bad.

But what about guys getting hit and avoiding getting hit? Just like Penalties, every play-by-play chart for each NHL game includes both the player doing the hitting and the guy who is being hit (like penalties taken and drawn). Extraskater now actually compiles hits against and hits +/- using these #s. Do these numbers mean anything?

Let’s see if we can answer 4 questions:
1.  Is avoiding getting hit a repeatable skill?
2. Is there a relationship between avoiding getting hit with increased scoring?
3. Is there a relationship between avoiding getting hit and winning the possession battle?
4. Do star players get hit more without an enforcer on the team?
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Overemphasizing Context – A mistake just as poor as explaining context in the first place.

AMac Context

The only context that can explain Andre MacDonald’s performance is if he’s actually wearing these chains under his uniform.

Eric Tulsky frequently points out on twitter that common critiques of analytics people (whether it be hockey or any other sports analytics) tend to act as if those involved with analytics are kind of stupid and have ignored the obvious.  For example, people tend to respond to arguments involving corsi and possession by bringing up the obvious subject of context – “Sure he has a bad corsi, but he gets tough minutes!”  And the general response of course is, yes we have, and we wouldn’t be making these assertions had we not done so.   Hockey Analytics has come up with a multitude of statistics to measure context – Behind The Net alone has 3 metrics for quality of competition and 3 metrics for quality of teammates, plus a measure of zone starts – HA has multiple different measures for the same thing and so does now Extra Skater (with Time on Ice QualComp and QualTeam).

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