Generating Offense and Shots per Entry


Suppose the hockey gods gave you a choice: Your team could get 10 zone entries and take 1 shot each time, or it could have a single zone entry and take 10 shots. (Since these are the hockey gods, assume the team is allowed to score multiple goals on the one entry.) Which would you pick? It is possible that the single ‘high-shot entry’ would tire the defense and lead to better opportunities than attacking a fresh defense 10 times. If that’s the case, how many 1-shot entries would be equally valuable as the entry with 10 shots?

Hockey observers are coming to see the importance of both shot volume and zone entries, but there are still significant gaps in understanding how they relate and how offense is generated. For example, little attention has been paid to the distribution of shots within zone entries. We have very limited quantitative knowledge of the value of ‘high-shot entries’ compared to low ones.

In this post, I look at the frequency of achieving different numbers of shots on a single entry and the success rate of these entries. This is made possible by Corey Sznajder’s All Three Zones project, which you can and should support here. I look at two main questions: In Part 1, I examine how common it is to achieve each number of shots on an individual entry and which of these entries generate goals. In Part 2, I use this information to examine what exactly makes carry-ins more valuable than dump-ins.


For this work, I looked at every regulation 5v5 entry in the All Three Zones project that could be clearly classified as either a carry-in or a dump-in. This gave me a dataset of 29,264 carry-ins and 57,693 dump-ins, which led to 2,965 and 1,364 goals, respectively.

If the next entry/faceoff after an entry was an offensive zone faceoff, I gave the initial entry credit for shots and goals that followed the faceoff. Unfortunately, this does not distinguish between icings and stoppages where the defending team is able to change skaters, but this limitation seemed preferable to ignoring all shots that were preceded by a faceoff. Finally, all references to “shots” in this post refer to Fenwick For, as that is the measure tracked in All Three Zones. Fenwick includes both shots on goal and missed shots but, unlike corsi, excludes blocked shots.

The spreadsheet with the main calculations and charts are available here. In addition, if you reach out to me and show you purchased the All Three Zones dataset, I’m happy to share the full spreadsheet in which I cleaned and analyzed the raw numbers.

Part 1: How many licks does it take to get to the center of the net?

How common are ‘high-shot entries’ in which the offense is able to take multiple shots before the puck is cleared out of the zone? And how important are they for scoring goals?

First, it is important to recognize that entering the zone does not guarantee offensive opportunities. 61% of all entries are cleared out of the zone without a shot. Another 30% achieve only 1 shot. Considering these odds, any entry that includes at least one shot should be considered at least somewhat successful.

The distribution of goals follows a similar pattern: most offense comes from low-shot entries. Almost two-thirds of goals were scored on the first shot following a zone entry, and another quarter were scored on the second.

Chart 1

I initially expected that high-shot entries would be responsible for more goals because while they are rarer, they would have higher shot quality. Indeed, shooting percentage increases with each additional shot taken. This makes sense since any shot taken after the first could be a rebound, which has a better chance of scoring. Shooting percentage continues to increase with each additional shot after the second, which suggests that players get better shots as defensemen get tired. (Alternatively, it’s possible that players who have the skill to take multiple shots in a shift are also the players with an above average shooting percentage.)

However, while shooting percentage increases from 5% to about 13% as more shots are taken, this increase is far less important than the volume of low-shot entries.

Chart 2

In sum, we see that almost all entries lead to no shots or just one shot. When a team does get a lot of shots on a single entry, each additional shot has a higher chance of becoming a goal. An individual high-shot entry is more likely to end in a goal than a low-shot entry, but low-shot entries are so much more common that they are responsible for most goals.

The data also answers the questions posed in the introduction. Entering the zone and taking 1 shot has an expected value of 0.05 goals. If we pretend that multiple goals could be scored on a single entry, then the 10-shot single entry would have an expected value of 1.06 goals. The 1 extremely long entry is therefore worth a little more than 21 1-shot entries. However, 1-shot entries are for more than 21 times more common than an entry with 10 shots.

Part 2: You Miss 100% of the Shots You Don’t Take (Because You Dumped the Puck)

One key insight from hockey analytics has been the importance of carrying the puck into the offensive zone instead of dumping it in. The All Three Zones data supports this assertion: in the data I examined, 4.4% of all carry-ins led to goals compared to just 1.8% of dump-ins. More specifically, this data lets us explore how a carry-in creates more offense than a dump-in.

There are several different ways that carrying the puck could translate into higher offensive output:

  • Case 1: Carrying in leads to more high-shot entries, where higher shot quality makes goals more likely
  • Case 2: Carrying in allows the player to get into a better scoring situation, improving shot quality regardless of shots per entry
  • Case 3: Carrying in increases the likelihood that the player will get at least one shot off.

The data does not support cases 1 and 2. Carry-ins are no more likely than dump-ins to lead to high-shot entries. Furthermore, shooting percentage for each shot in the entry is nearly identical between entry types. The first shot after a carry-in has a slightly higher shooting percentage than the first shot after a dump in (I suspect because the carries include shots on the rush), but the difference is not large enough to explain why carries produce so many more goals than dumps.

Chart 3Chart 4

Instead, the truth is case 3: carrying in the puck makes it significantly more likely that the offense will produce at least one shot. The defense successfully clears dump-ins without allowing a shot three-quarters of the time. In contrast, they do so for carry-ins just 44% of the time. These additional opportunities for one shot are a huge source of additional offense after a carry-in.

Chart 5

These findings match the general analytical criticism of dump-ins: by voluntarily giving up possession, the offense gives the defense the chance to neutralize a potentially dangerous situation.


These findings add some additional context to our understanding of zone entries and offensive production. First, long shifts with multiple shots in a single entry are responsible for very little goal production. Second, carry-ins are more valuable than dump-ins because they are much more likely to lead to at least one shot before the zone exit.

There is a bunch of additional work that could be done to build on this. First, this data could be split up to see if effects vary by team. Second, we could incorporate additional data such as score effects or special teams. Finally, it would be beneficial to try to incorporate different types of shots, such as rebounds and rushes.


4 thoughts on “Generating Offense and Shots per Entry

    • Not that I’m aware of, but it’s definitely an area worth of further exploration. One possible method is to count any shot within the first 3 seconds after entering the zone (or some other cutoff) is a rush shot, but that won’t necessarily differentiate between even- and odd-man rushes.


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