Neutral Zone Playing Styles

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.

Identifying neutral zone roles can serve useful purposes. General Managers can try to bolster their roster by ensuring they have the best possible mix of playing styles. Coaches can identify player tendencies and respond to deficiencies. Fans can find neutral zone play more understandable and interesting.

In this post, I try to distinguish neutral zone roles that meet two criteria: First they should provide some quick insight into what to expect of a particular player in the neutral zone. Second, the roles should not closely correlate with overall neutral zone play; if the roles just mean “good” and “bad”, there’s no need for them in the first place.

To do this, I first discuss some of the statistics we have that can shed light on neutral zone playing style. This includes individual entry share and how it may begin to quantify line chemistry. Finally, I introduce five neutral zone “roles” that serve as a shorthand to understand how a given player typically performs in the neutral zone.

Individual Entry Share and Team Chemistry

One avenue to understanding neutral zone playing style is carry-in %, which measures how many of a player’s entries are carry-ins with possession. Carry-in % is a reflection of the player’s tendencies and also a measure of results since carry-ins tend to lead to more shots on net than dump-ins.

Another avenue to measure style is individual entry share. Individual entry share (iES, also called burden) takes advantage of the fact that most neutral zone tracking includes both the player who completed the zone entry and his or her on-ice teammates. Using this, we can calculate the proportion of on-ice team entries where the skater made the play with the puck. A high iES player is a player who gets the puck into the offensive zone himself, no matter how he does it. This is not to say that players with low iES are bad in the neutral zone: they may provide strong defensive play, earlier passes, or savvy positional play to make the entry possible, they just don’t get the puck into the zone themselves.

iES is particularly tantalizing because it may be a proxy for measuring which players “like to have the puck on their stick”. It’s commonly observed that some players are more comfortable stick-handling and making plays, while others prefer to lurk without the puck until an opportune moment. This observation is reasonable and potentially valuable in figuring out which players are best suited to play with one another. However, short of public and verifiable microstats, we do not have a great way to study this idea quantitatively. iES measures who has the puck at the moment of zone entry, which is a window into possession tendencies.

For example, look at this year’s Stanley Cup Champions, the Pittsburgh Penguins. One of the team’s key personnel changes was moving Phil Kessel from a line centered by Evgeni Malkin to one with Nick Bonino. The switch created the dominant HBK line of Hagelin, Bonino, and Kessel. One explanation for the Kessel resurgence on this line was that he and Malkin clashed because both like to carry the puck, whereas Bonino was more adept at deferring to Kessel’s play-driving ability.

iES backs this up this theory. Based on Corey Sznajder’s tracking of the 2013-2014 season, we know that in that year, Kessel had an iES of 33%, while Malkin had 35% and Bonino had 20%. As shown below, Malkin and Kessel’s iESs were both much higher than league average, whereas Bonino’s is much lower. Looking at iES could help other teams determine which wingers might perform best with which centers. Obviously, iES has significant limitations, the largest of which being that it is incredibly dependent on the actions of teammates. In this case, Kessel, Malkin, and Bonino all played for different teams when the data was collected, and it gives us insight into how they eventually played together.

iES Standard Deviations

Neutral Zone Roles

Now that we have both carry-in % and iES, how can we use them to assign players with a role? The first step is to plot them in a 2×2 and see the distribution:

Neutral Zone 2x2

This graph shows all forwards who played at least 250 minutes in 2013-2014. While there is a slight positive relationship, there are plenty of players who fall into each of the 4 quadrants divided by the mean of each statistic. I’ve also added 4 names, one in each corner, marking different roles:

  • Drivers: These players “drive” play in the neutral zone. They frequently possess the puck during entries and carry it in.
  • Passengers: The opposite of drivers, these players rely on their teammates to conduct zone entries. When they do enter the zone, they tend to dump it in.
  • Opportunists: These players don’t enter the zone often, but when they do, they do it well. They have high carry-in rates but do not enter the zone as often as their teammates.
  • Dump Trucks: As the name implies, these players dump the puck in and dump it often. They are tasked with getting the puck into the zone, and they do so by giving up posession.

These roles are not just proxies for good or bad play. A driver’s impact could be negated by terrible defensive play. A dump truck may or may not create a huge volume of entries that his team would not otherwise have. A passenger may produce great results for his team through strong passing and positional play that does not appear in this data.

Below are density curves for the 5v5 Entry For % of players in each role. This shows how well players of that type do at giving their team a majority of entries. Here, we see that the curves are similar and none are dramatically skewed; each role includes both good and bad neutral zone players.

Neutral Zone Role Density Curve

Individual Players and Neutral Zone Roles

Below, you can find a link to an interactive plot with every eligible player based on the 2013-2014 season. These roles are determined based on how the player compares to the league average for either forwards or defensemen, just like in the scatterplot above. I’ve also added a “balanced” label for players who perform near the league average in both stats. You can picture this as a diamond centered on the middle of the scatterplot. (Mathematically, I converted each player’s stats into a z-score that showed how far they fall from the mean in units of standard deviation. Players whose z-scores summed up to less than 1 were labeled “balanced”.)

Use the interactive Tableau here


Finally, there are also some interesting players whose names appear as the most extreme cases of each role. These are the players who appear in the four corners of the scatterplot and have neutral zone tendencies far from league average. I’ve listed those players below, along with some others I found intriguing. Again, not all drivers are good, nor are all passengers bad. We have other ways to measure that, but this helps show what methods the player is using to get to that result.

Role Extreme Examples

While these lists don’t provide definitive proof of anything, we can make some initial observations and begin asking questions for further study.

  • The drivers list includes some indisputably great players (including both Kessel and Malkin), who are used to driving their team’s performance in other areas. It also has players like Leddy, Barrie, and Yandle, who generally have a better reputation among the analytics community than elsewhere. Perhaps their neutral zone play is one area that drives results but is overlooked by the eye test
  • In contrast to the drivers list, some of the most extreme passengers are generally bad players or “defensive defensemen” who make limited contributions. Despite my earlier notes about good and bad players appearing in each group, there definitely are some clear trends in ability at the extremes.
  • The “dump trucks” include, with some exceptions, players I would generally categorize as depth players. These players are serving a key function for their lines, suggested they may make a particular contribution to their team’s neutral zone play.


Perhaps the biggest question in neutral zone playing styles is the importance of coaching and systems compared to individual player’s natural talent and preferences. How much is the decision to carry or dump the puck influenced by instructions from the bench? Opportunists are able to carry in the puck, but could they continue to do so at a high rate if they were asked to try it more often? Could dump trucks – who are used to carrying the puck a lot – see better results if pushed to carry the puck in, or have their coaches correctly identified that they lack the ability to do so? There remains much to be understood about how to maximize these decisions for a team’s overall neutral zone performance.

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