Is it time to appoint a new jester?

Toronto -with its high profile in the media combined with some questionable management- has consistently been the brunt of jokes over blogs, message boards and twitter from other fanbases.

Recently the Toronto Maple Leafs has made a bunch of savvy, low-risk, high-potential steps both in management and player personnel to improve their team. While they are still a distance away from being a contending team, the steps taken are not those that the online hockey community has grown to love about Toronto.

With this knowledge and the offseason nearly in our rearview mirror, it is time for Hockey-Graphs to ask its analytically inclined following:

All teams in poll came from an unofficial nomination survey I conducted on twitter.

Can NHL Teams Win With Two Mega Cap-Hits?

The new contracts of Kane and Toews mean an imminent death of the Blackhawks, says everyone
Photo from Matt Boulton via Wikimedia Commons

When Patrick Kane and Patrick Kane signed matching eight year extensions with $10.5 million annual cap-hits, many wondered out loud if a team can be successful with two players occupying $21 million in cap space together.

So I decided to take a look at the relationship between a team’s success, measured by total regular season and playoff wins, and how much of their total cap outlay is from their top two cap charges.

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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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Defensemen still have no substantial and sustainable control over save percentage

For quite some time there has been a debate going on: those who think you should add a defenseman’s effect on save percentage into player evaluations and those who think that adding such information causes more harm than good to the analysis. Note that this does not mean defensemen do not affect save percentage. That is an entirely different stance.

When it comes to evaluating a player statistically, you want the number to account for two things: effect and control. If a statistic does not help quantify how a player improves their team’s chance at winning, it is useless in measuring effect. If a statistic has too much white noise or other contributing factors that it would take too large of a sample to become significant to the player’s contribution, it is useless in measuring a player’s control over the effect.

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How repeatable is performance in the Offensive, Defensive and Neutral Zones?

A few years back, Eric Tulsky (and others at Broad Street Hockey) pioneered the start of neutral zone tracking, or rather the tracking by individuals of every entry each team makes from the neutral zone into the offensive zone during a hockey game.  The idea of this tracking was simple:  Neutral Zone play is obviously important to winning a hockey game, but NHL-tracked statistics contain practically no way to measure neutral zone success overall.   Zone Entry tracking remedied that, by giving us both individual and on-ice measures of neutral zone performance.

An overall measure of neutral zone performance that we can find with zone entry tracking is called “Neutral Zone Fenwick.”  By using the average amount of Fenwick events resulting from each type of zone entry (Carry-in or Dump-in), we can create an estimate of what we’d expect a player’s Fenwick % to be with them on the ice based on the team’s neutral zone play with them on the ice.  In essence, this is a measure of a player’s neutral zone performance, helpfully done in a format that we’re already pretty familiar with – like normal Fenwick%, 50%=break even, above 50% = good, below = bad.

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How Are Players Affected Financially By Buy-Outs?

photocred Wikimedia Commons

I compiled the data for all the players bought out by their teams since the 2005 lock-out (excluding this year’s buy-out class) and examined how much of the the money lost to the buy-out they made back over the years that were bought out. When players are bought-out, they get a portion of their previous contract, and are given an opportunity to re-enter the free agent market. Potentially, they could end up a net winner from the process.

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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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The Futility of Predicting Playoff Series Goaltending

Goaltending is a devilishly difficult thing to predict at the best of times. In smaller samples, even the most powerful forecasting tools fall victim to variance and luck. Playoff performances, and to a greater extent single series, represent such samples and we’re frustratingly inefficient at predicting them using traditional methods. I’m excluding more refined models such as @Garik16’s Marcels, which may very well do a better job of it. I compared regular season 5v5 Sv% over different intervals of time, both total and strictly on the road, for all playoff goalies over the past three seasons and how they matched up with playoff 5v5 Sv%. Here are the results:
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The Hartnell for Umberger + 4th Rounder Swap, and the Places a Bad Contract Puts You

File:Scott Hartnell 2010-10-30a.jpg

Photo by “Rhys A.” via Wikimedia Commons

I had a great question from a good friend of mine, a Flyers fan, after the fervor died down from yesterday’s Scott Hartnell for R.J. Umberger and 4th round pick swap. He asked me:

“From what I’m getting from the advanced stats guys, it appears that the Blue Jackets robbed the Flyers blind yesterday by getting Hartnell for Umberger (a guy they were going to compliance buyout anyhow).

Is Umberger really this bad?”

The short answer is that Umberger is not very good; his With-or-Without-Yous (or WOWYs; where you compare Corsi when a player is with and without a teammate on the ice) suggest that nobody plays better with him than others, outside of maybe Ryan Johansen. Now, some of that is due to zone starts, as Umberger has been saddled with a lot of time in his own zone. Even so, three years of possession in your end 55%+ of the time is a little too consistent in its futility. I’d expect at least one year there where that figure lowered to 51 or 52% if he was showing some defensive abilities. He’s still an average player in the faceoff dot, but his offensive contributions are shrinking, and at 32 it’s hard to see them recovering much. Blue Jackets beat reporter Aaron Portzline noted the Jackets were contemplating buying him out of his $4.6m/year cap hit contract, which was moving into modified no-trade clause (NTC; player can specify a list of teams he’d be willing to be traded to) years.

The longer answer is that yes, Umberger is not good, but this trade is much more complicated than a player-for-player, or player-for-player-and-a-pick swap. A trade presumably always looks good enough from both sides’ perspectives in order to happen, so what were the incentives for Ron Hextall? Jarmo Kekalainen?

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