Team Canada won the cup. Team Canada went undefeated. They were the favourites going in, and they came out the winner. Not only did they win, but they went about it in dominant fashion. They rarely trailed and they controlled nearly every facet of the game.
It wouldn’t be surprising for many to hear that the team also dominated in the shots column… but they were not the most effective team in every aspect, which raises some interesting questions.
Last time, I showed how using data and video evidence can be combined to inform tactical offensive zone decisions. Today, I’m going to do the same thing in the neutral zone. Neutral zone play is something that has been a hot topic among analysts for many years, going back to this paper written by Eric Tulsky, Geoffrey Detweiler, Robert Spencer, and Corey Sznajder. Our own garik16 wrote a great piece covering neutral zone tracking. Jen Lute Costella’s work shows that scoring occurs sooner with a controlled entry than an uncontrolled entry.
However, for all the work that goes into zone entries, there have been few efforts to account for how predictable these metrics are. At the end of the day, what matters is how we can better predict future goal-scoring. Also, in looking at our passing data, what can we also learn about how actions are linked when entering the zone? Does simply getting into the offensive zone matter? Does it matter whether it’s controlled or not? Or, does what happen after you enter the zone matter exponentially more? Lastly, what decisions can we make to improve the team’s process using this data?
Player A is a sniper. Player B is a playmaker. Quick: If the two of them get a 2-on-1 break, what do you expect each of them to do? Odds are you would expect the playmaker to pass and the sniper to shoot. You may not know how good each of these players is, but the monikers give you a rough idea of this player’s relative strengths and how they generally try to succeed.
We have plenty of different names that explain a player’s general “role”. We use words like sniper, dangler, two-way player, and power forwards (even if we can’t agree on what that last one actually means). However, these names are usually limited to the offensive zone. We have no easy way to describe what a player does in the neutral zone.
Hockey analysts have repeatedly shown the value of neutral zone play. If a player performs well in the neutral zone, he or she is helping generate offense for their team and limiting the opponent’s chances. In addition, neutral zone play is repeatable, and the player is likely to continue to drive possession for their team. If you can identify players who thrive in the neutral zone, you are in a position to help your team improve.
But while neutral zone play is important, we still have a very limited understanding of it. Between the distance from the goal, the fluidity of play, and the relative scarcity of data, most people don’t know how players perform in the middle third of the ice. Furthermore, we don’t even have a complete idea of how to make those evaluations. When figuring out how good a player is in the neutral zone, should offense and defense be evaluated separately, or are overall results enough? What skills translate to strong neutral zone play? What playing styles?
Some day we will reach the point where we can comprehensively analyze which power plays are the best, which players drive that success, and most elusively, what roles to place players in to maximize a unit’s output, but statistically, our special teams cupboard is pretty bare. This season, as many of you know, I took on the long and arduous task of hockey tracking in the interest of trying to get us even one step closer to our objective: how can we better evaluate and predict power play success? So let’s dive right in. Continue reading
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)
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:
Related to what @Thats_Offside has said: Why should I care what a player’s zone entry rates are? Convince me, Twitter.
— Matt Cane (@Cane_Matt) November 27, 2015
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:
Long has it been argued that sustained zone time is a reliable way to not only prevent your opponents from scoring but as a way to produce offense of your own. The argument that is often made, or at least the one that’s often heard, is that the longer you are in the offensive zone the more likely it is that the defense will become fatigued and make a mistake that leaves someone open for a prime scoring opportunity.
So let’s test that theory by asking a more data driven question; does sustained zone time lead to an increase in shooting percentage?
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.
In my last post on neutral zone tracking, I went over repeatability of metrics using the data to measure performance in all three zones (Neutral, Offensive, Defensive). As I noted, the results didn’t quite measure up to Eric T’s initial hypothesis:
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Hockey Graphs 