Most of my posts so far have talked about zone exits from the perspective of the team trying to breakout out of their defensive zone. Now, let’s flip the script and discuss the team on the forecheck. This team does not have possession of the puck, but they are in their offensive zone, which is an advantage. So, how can they regain control?Continue reading
From past posts, we have a general sense of the basics of zone exits: zone exits are important because they get you out of your zone and towards an opportunity to score. The key to a successful zone exit is maintaining possession, ideally by avoiding the temptation to dump the puck out.
But so far, we have only looked at zone exits league wide. Most fans care about one particular team more than the rest, but we haven’t looked at team-level results at all. So today, let’s see how each team has performed at zone exits over the past three seasons.Continue reading
If there’s anything you know from neutral zone analytics, it’s probably this: carry-in zone entries are better than dump-ins. In the linked piece, Eric Tulsky finds that “maintaining possession of the puck at the blue line (carrying or passing the puck across the line) means a team will generate more than twice as much offense as playing dump and chase”.
But what about zone exits? Is possession equally important there? Work by Jen Lute Costello suggests that it is, but her data was limited to one playoff series. Today, I’ll expand on her work to show that maintaining possession is crucial for successful zone exits, and breakouts should be structured with this in mind.Continue reading
Though it was completely tangential to @SteveBurtch’s line of thinking, his brief comments pondering the competitiveness between the middle of NHL lineups yesterday (which I can’t locate now, natch) got me thinking about whether the NHL and team management has gotten any more efficient or competitive overall the last decade. With 10 years in the books for complex Corsi data, and hockey’s seeming “Moneyball moment” fully here regardless of the quibbling on social and mainstream media, is the league getting any tighter?
This year’s NHL draft class is weak. I don’t follow junior prospects closely, but that’s what I’ve heard from more knowledgeable sources. It’s a fair claim; Nolan Patrick and Nico Hischier seem talented but not among the game-changing talents that have recently been drafted first overall.
However, it’s harder to judge the draft class past the very top. Scouting is hard, especially for hundreds of prospects across the world. It’s possible that while there is no clear star in the draft class, the rest of the draft is as strong as ever.
That would have big implications for draft strategy. The conventional wisdom is that teams may trade more picks this year because they believe the weak draft class makes the picks less valuable. But if the draft is typical after the first few picks, that would be a poor use of assets.
We don’t yet know how well this year’s draft class will do in the NHL. But, we can use historical data to ask questions that establish expectations: how well does each draft class typically perform, and how much does this vary by year?
Note: This is Part 2 of the series on coaching analysis. Part 1 is here.
In this post, I’ll do a brief review of each team’s coach history from the current Metropolitan Division. These graphs only show a team’s performance in 5v5 situations from 2005 to 2016. The vertical lines indicate when a season begins. The horizontal line shows the 50% mark, where a team would be if it had as many shots for as shots against. The bold line is a smoothed representation of the team’s shot percentage. The faded bands around the bold line indicate 95% confidence intervals. These intervals show the uncertainty around the smoothed estimation of the data.
Happy Max Corsi Productivity Day! We’ve reached the point in the season where Corsi best predicts future winning percentage. There’s plenty of more advanced ways to better predict how the rest of the season will go, but Corsi offers a simple baseline in a way that helps explain why it is so important. I’ll first explain what that means and why it matters, then take a look at how we can use it to predict basic shifts in the standings for the rest of the NHL season.
As a person who learns best by looking at visual representations of data, I have a couple of statistics that I check on a regular basis to hep me calibrate my interpretation of what’s happening around the NHL. I’m going to start sharing them in a regular series that I hope will give a quick overview of how teams are performing around the league. The goal is for this to be a high level view of the basic trends for all 30 teams that will draw attention to specific areas that might need to be explored further. The charts in this article are up to date through last night’s games. All data is via corsica.hockey.