A Guide to Neutral Zone Tracking Part 2 of 2: How to track the Neutral Zone

A carry-in just waiting to be recorded by someone.

Okay so in our last post, we discussed why tracking the Neutral Zone is important.  We also briefly discussed what we track when tracking the neutral zone.  But in this post, I’m going to provide you with a detailed guide and the resources you will need to actually track the neutral zone yourself.

What You Need For Neutral Zone Tracking:

Neutral Zone tracking doesn’t require much.  At a minimum you only require:
1.  Access to NHL Games
2. Something to record Neutral Zone Entry #s (Usually a spreadsheet)
3. A place to compile your total #s (Usually another spreadsheet)

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A Guide to Neutral Zone Tracking Part 1 of 2: Why Neutral Zone Statistics Matter

nielsen

Frans Nielsen is incredibly good in the neutral zone.  But How important is that really?  And how can we tell that’s the case to begin with?

A while back, Hockey-Graph’s own Matt Cane wrote the following tweet:

Matt was referring to a statistic commonly found in “Neutral Zone Tracking,” which purports to measure the quality of individual and team play in the Neutral Zone.  Neutral Zone Tracking was pioneered by a bunch of guys at Broad Street Hockey (Eric Tulsky and Geoff Detweilier) back in 2011 and in the years since, a bunch of individuals have also began to do the same.  The work that’s been done on this area, on other sites as well as on this one suggests neutral zone tracking results in some extremely important data that we should be very interested in.

What is Neutral Zone Tracking:

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Hockey Graphs live video (Pod)cast #2: Tuesday 10/13 at 9PM EST!

The Hockey Graphs Live Video Cast has its second episode tomorrow night at 9PM!  We may be joined by additional members of the HG crew, and now we have an actual season – of more than one hockey league – to talk about!  On the agenda for this cast:

  1.  Interesting things that have happened in the first week of the season.
  2. RITHAC Recap
  3. The NWHL!
  4. 3 on 3 – Thoughts?

Hope you can join us! Again, the cast will be live at : http://www.youtube.com/user/wraithlead8/live

Hockey Graphs live video (Pod)cast #1: Talking about RITHAC and Manually Tracking Hockey Games!

For those who missed it, below is the archive from tonight’s Hockey Graphs Live Video Podcast #1, featuring Garik16, Ryan Stimson, Ben Wendorf, and DTMAboutHeart!  We talked about the upcoming Rochester Institute of Technology Hockey Analytics Conference (RITHAC), Neutral Zone and Pass Tracking, and how we go forward with deciding what to track and what to look at with such data.  Give us a listen and if you have any thoughts for what we should talk about next cast, please leave a comment!

Hockey Graphs live video (Pod)cast #1 : Tuesday 10/6/15 at 9PM EST!

This Tuesday at 9PM EST, we’ll be holding our first official Hockey Graphs live video podcast. This is a live event, so if you want to chat with some of the Hockey Graphs guys or ask some questions to us, you can do that and we’ll try and answer! (If you’re on mobile, you can chat via the youtube ap, apparently). And if you have some topics/questions you’d like us to discuss that you know of in advance, please feel free to leave a comment to this post and we’ll try to discuss in the actual live cast!

The stream will be featured here: http://www.youtube.com/user/wraithlead8/live

We did a preview stream for about an hour on Saturday, so you can see what that looked like below:

Hope to see you then!

Neutral Zone Score Effects: How does the game score affect play in the Neutral Zone?

This is the type of entry most likely to be made by a leading team – an odd man rush Carry-In against a d-man conceding the zone (the legendary Andrew MacDonald). Image courtesy of http://www.BroadStreetHockey.com

We know a decent amount about score effects in the game of hockey at this point. We know the obvious: teams play “conservatively” and shell up when leading and become more aggressive when trailing, resulting in the leading team taking less shots and the trailing team taking more.

Less obviously (at first glance anyhow), We also know that the leading team’s shooting % increases substantially when compared to when that same team is tied (Graph courtesy of new Hockey-Graphs writer Petbugs), while the trailing team’s shooting % either increases barely or stays the same as it does when tied.

As detailed earlier on this site this results in the trailing teams tending to score more than leading teams, especially in late.

But what we haven’t really detailed is some of the mechanics of “How” this happens. Some have suggested its because teams may change their systems with a lead or deficit. Others, such as Justin Bourne , have suggested the effect is mainly the result of psychological effects – no one wants to take the risky play when leading and possibly cause the opponent to get the tieing goal as a result of a risk, so players stop taking as many risks when leading even though the coach is preaching the same scheme. But little attention has been paid to seeing if any of these things are true, whether via a statistical analysis or via some systems breakdown.

So what I’m going to do in this post is attempt to break down how score effects change how the neutral zone is played. And by doing so, we can by extension, try to get a better picture of how the play in the other two zone is affected by score effects.

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Analyzing the Neutral Zone (and beyond!): A Call for Volunteers.

Over here at Hockey-Graphs, I’ve been taking a look at Neutral Zone Tracking and what the results of such tracking can tell us about the modern game of Hockey. My last post, for example, looked at what such tracking told us about play in the offensive, defensive, and neutral zones, and to what extent was performance in each of those zones skill or randomness at the team and individual levels. Before next season begins, I have two more posts planned: one doing further research into repeatability of various neutral zone metrics and another looking at how score effects affect neutral zone play.

The biggest weapon I’ve been using recently to do such research has been Corey Sznajder’s (aka @ShutdownLine) All Three Zones Project (the genesis of which can be found HERE).   Through Corey’s work, we have a nearly complete dataset with Neutral Zone Data for the 2013-14 season, for EVERY team in the league.  The dataset also includes to a lesser extent zone exit and zone entry defense data.  Even more, Corey is actually really close to finally finishing the tracking this summer and we’ll have a complete data set very soon.  This is an incredible resource for new hockey knowledge, and it’s available for anyone , as long as you make a $15 contribution to Corey’s GoFundMe Page, which can be found here.   I think this is an incredibly worthwhile use of funds if you can afford it, and many people have indeed actually already given.

What many people haven’t done is actually taken the data and DONE anything with it.  Again, this data set was released about a year ago now, and yet very few individuals have been doing work with it at all.  This is a bit of a disappointment.  If you include the passing tracking project of Ryan Stimson (Data available here, here, and here), we now have two large datasets filled with information that could help us better understand the game of hockey.

So what I’m asking is this for volunteers to try and actually try and do some work with the data.  There are a lot of questions we can try to answer!

For example, one question someone posed to me on twitter is:

What really is the risk of a D-Man attempting to jump up through the neutral zone and carry the puck-in?  

Now we can’t answer that question fully from the data – a D Man who tries to carry the puck through the NZ and turns the puck over at the red line is making a bad play that our data can’t capture – but we can take a shot by looking at the effects on shots against of carry-ins and carry-in failures by defensemen.  And this is just one question that we can possibly look at.

Please email me at my email address (garik16 AT Gmail) if you’re interested in looking at the data, or leave comments here in the comment section.  Alternatively, if you have other questions you might like answered, please leave them in the comments as well.  Together we can hopefully learn a lot more about the game of hockey.

Individual Skill, Coaching/Systems, or Randomness: What is driving open play results in the Offensive, Defensive and Neutral zones?

Can a team lose the neutral zone and still drive possession in the other zones to win the possession battle? Todd McLellan thinks so.

These days, when we talk about possession, we’re typically talking about a player’s corsi/fenwick/shot numbers overall, or we break them down into shots for and against.  The thing about doing this is that while it gives you a decent picture of what overall is happening while a player or team is on the ice, it doesn’t really give you a specific picture – does a player have a good corsi because he’s an elite offensive zone player or is it his performance in neutral and defensive zone causing this?  Even separating into shots for and against doesn’t narrow this down – for instance, a player can suppress shots by being in the neutral (or hell, even offensive zones), which doesn’t say anything about him necessarily in the defensive zone.

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2015 Midseason Goalie Projections using Hockey Marcels

Last Year, I unveiled a hockey version of the baseball Marcels forecasting system in an attempt to forecast the future performance of goalies.  The idea behind Marcels is simple: we take the last few years of a player’s performance and then weight more recent numbers higher than older numbers.  In addition, we regress the player’s #s to the mean (with a player who has a larger sample being regressed less than one with a smaller sample) and, if we’re projecting for the future, we adjust the overall #s for aging.  Again, this is a very very basic projecting system, but its’ been proven to be incredibly well founded for baseball, and probably for hockey as well.

So let’s take a look at how things have changed now that we have data from the most recent season.  We now have a few goalies with enough data to run Marcels on that we didn’t previously (although barely in most cases) and a few goalies have had large turns in one way or another in their career, which changes the projections.

Again, as a reminder, here is our methodology:
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The Defensive Shell is a good idea in theory. Unfortunately, it doesn’t work.

The results of score effects are pretty basic hockey analytics knowledge at this point.  Teams down in goals tend to take more shots, while teams up tend to take less, with the effect becoming larger as the game goes on.

We often explain this effect by saying teams go into a “defensive shell”, playing extremely conservative on offense to avoid easy opponent scoring opportunities, at the cost of more time in the team’s defensive zone.  It is of course, not a one team effect either – we often emphasize that the other team is taking greater risks as well to try and score, which is why the shots taken by the team with the lead go in at a higher rate than normal.    That said, it’s pretty much accepted that going into a shell would be a losing strategy for a team to attempt over a whole game, which is why teams don’t attempt this strategy for a full game. Continue reading