Possession, Shooting Percentage and Outlier Teams

Shot quality as a talent at the team or player on-ice level has long been a topic of great debate and I outlined some of that debate in an article I wrote earlier in the week. For those who don’t believe that shot quality is a significant factor in performance put a lot of stock in possession metrics such as Fenwick or Corsi. These are shot attempt based metrics and as such ignore shot quality altogether. For those, like myself, who believe shot quality matters (at least for some teams and especially some players) I consider a possession based analysis a (potentially) incomplete analysis. Today I am going to put that debate aside and ask the question, is there any relationship between possession and shooting percentage?

To answer this question I took a look at CF% and CSh% (Corsi shooting percentage = GF/CF) for all 30 teams over the previous 3 seasons combined in 5v5close situations. When I plot these, here is what I get.


Ok, so while there seems to be some correlation it really isn’t all that significant. You might be inclined to end the investigation right here and conclude that there is no relationship but when you actually look at the data you will find that of the 10 best CSh% teams 8 of them are sub-50 CF% teams and of the 10 worst CSh% teams six are better than 50 CF% teams. The two top CSh% teams that have CF% above 50% are Chicago and Pittsburgh, two teams with elite level talent. The four bad CSh% teams that have a CF% below 50 are  Florida, Carolina, Minnesota and Buffalo. Of those teams, Florida, Carolina and Buffalo have combined for one playoff appearance in each of the past 3 seasons.

So, it appears that the teams that break the trend of good CSh% equals poor CF% and poor CSh% equals good CF% are the truly good or truly bad teams or, for better terminology, we could call them outlier teams. What if we attempted to remove the really good and really bad outlier teams from our analysis and focus on the teams that are more typical teams in terms of talent. To do this in an unbiased way I used GF% to rank teams and I removed the top 4 and bottom 4  GF% teams (8 total, or just over a quarter of the teams were removed). This is what the chart looks like now.


Now that looks better. R^2 has jumped from 0.09 to 0.47 and there is a clear negative relationship between possession and corsi shooting percentage. For the record the teams that were removed were Boston, Anaheim, Chicago, Pittsburgh, Calgary, Buffalo, Edmonton, and Florida.

For curiousity I took this one step further and removed the next two best (St. Louis, Detroit) and two worst (NY Islanders, Minnesota) teams and got the following chart.


Wow, R^2 jumps all the way to 0.77 which is a very strong correlation and indicates that for a large number of non-elite, non-terrible teams there is a strong negative correlation between possession and shooting percentage such that the difference between a 45% and a 55% possession team is 1.22% hit to CSh%. Considering last season the average team had about 2200 5v5close Corsi For events that would equate to a difference of about 27 goals. Considering the average NHL team had 90 5v5close goals last season, that is not an insignificant number.

How does the R^2 hold up for this season? Well, if we include all teams the R^2 is 0.00 or absolutely no correlation. If we delete the top 4 and bottom 4 GF% teams it improves to 0.097. If we drop the top 6 and bottom 6 it jumps to 0.26 and if we drop the top 7 and bottom 7 teams and just focus on the middle 16 the R^2 jumps up to 0.35. Now these correlations are not near as good as the 3-year analysis above but remember that our sample sizes are significantly smaller too (~43-45 games compared to 212 games). The general trend still continues. If we remove the really good and really bad outlier teams there appears to be a relatively strong negative relationship between possession and shooting percentage.

Now that we have identified a relationship, on thing we can do is look at how teams have changed from last season to this season. Let’s take the Edmonton Oilers as an example since they have improved their 5v5close CF% quite significantly this season but they are not an improved team. Let’s look at their numbers from last season and this season.

. CF% CSh%
2014-15 48.7 3.49
2013-14 43.4 4.38
Difference 5.3 -0.89

So, their 5v5 CSh% has improved from 43.4% to 48.7%. If we plug that 5.3% improvement into the regression equation above we would expect that their CSh% would drop 0.65% where it actually dropped 0.89%. Edmonton dropped from 11th in CSh% last season to 27th this season.

A couple of months ago I investigated the relationship between Corsi Against rates and save percentage and found that there does appear to be a relationship such that an increase in corsi against would result in a improved save percentage. This is completely consistent with the analysis above which one could infer that an increase in shot attempts correlates with a decrease in shooting percentage.

It is difficult to say whether these correlations are due to systems or talent but I have a couple theories.

  1. Good possession teams play in the offensive zone more frequently and the defensive zone less frequently. This could result in a shot type bias away from higher quality “rush shots” and towards lower quality zone play shots.
  2.  It could be related to style of play and passing. It has been shown that shots after passes are more likely to result in goals and lateral movement, especially passes, across the “Royal Road” down the center of the ice also result in more goals. My theory is passing, and in particular passing through the center of the ice, while more likely to result in a goal is also more likely to result in a turnover. Thus teams that take riskier, longer passes especially lateral passes are more likely to see plays result in a goal if successful or a turnover (and no shot from that possession) if unsuccessful. Conversely a more conservative passing team with fewer cross-ice passes through traffic would have fewer possession not result in shots but in turn not get rewarded with high quality shots that result from those risky cross-ice plays.

In conclusion, if you have exceptional talent such as Pittsburgh with Crosby and Malkin or Chicago with Kane and Toews  or exceptional depth like Boston or Detroit you might be able to be a good possession and a good shooting percentage team but if you are not one of the truly elite teams in the league it seems you likely have to choose one or the other. Unless of course you are Buffalo and you are terrible at both.


Update: Tyler Dellow, in one of his few hockey related tweets since being hired from the Oilers, tweeted the following:

Tyler is right. Things fall apart for earlier seasons. Let’s look at this in more detail by looking at R^2 between CF% and CSh% for individual seasons for all teams, middle 26, 22, and 18 GF% teams. Here is what we have:


All of the above relationships are negative relationships meaning improved CF% led to decreased CSh% so it is very difficult to argue that this relationship isn’t real. More shots tends to mean lower shot quality.

Additionally, for 5 of the 7 seasons the middle 22 are better than the middle 26 which is better than all 30 teams (only 2007-08 and 2010-11 do not fit) and of those 5 seasons, four of them also have the middle 18 teams being better than the middle 22 (only 2011-12 is worse). This implies that there may be a few truly elite teams that can post a good CF% and a good CSh% and a few truly terrible teams that put up bad CF% and bad CSh% but for the mass of teams in the middle the trend holds.

Finally, the strongest relationships have occurred during the previous few seasons after removing the outlier teams from the sample and from above 2014-15 appears to following that trend as well. It is difficult to say why this is but it is an interesting observation. One has to wonder if it has anything to do with teams becoming more aware of and putting more focus on possession which in turn is strengthening the negative correlation with shooting percentage.



  • D Graffius

    I was playing around with the data as well, since I was intrigued by some of the comments it received on twitter. I was curious as to why you were using the differential percentages, since we are talking about shooting percent, a specifically offensive metric. Since we really don’t need to know the Against in this instance I wanted to look at just the For half of the equation, so I looked at GF60 rather than GF% to identify the oultiers.

    Using your initial premise, 5-on-5 Close from the previous 3 seasons comparing CF% to CSh%, if we instead remove the top and bottom 4 GF60 teams the correlation improves to .4854. We even see an improvement when negating the top and bottom 5 (I like 5, because 66.7% of the league should fall within 1 standard deviation of the midpoint, so the middle 20 can all be viewed as “average”), using GF% we get a .5038 while using GF60 we get a .5527. However, we don’t get the same massive improvement you did when we dropped the top and bottom 6, so obviously something about GF% was better for that final entry.

    Also on the same line of thought, I wondered why we were looking at CF% rather than Corsi For. So I looked at raw CF vs CSh% and for all 30 teams our correlation jumped to .1437, while eliminating the top and bottom 4 GF60 teams improved to a .5930 (it is a .4721 if you sort by GF% rather than GF60). Taken a step further and removing the top and bottom 5, leaving us with the 20 average teams within one standard deviation of the midpoint, was a massive .8247 (.4678 when sorting by GF%) and eliminating top/bottom 6 gives us a .8566 (.6151 using GF%).

    So all in all it is a pretty clear indication that for the average team more shot attempts do indeed mean a lower Sh% (and conversely one can assume this also suggests that more shot attempts against tend to mean increased Sv%, since Sv% is inversely proportional to Sh%).

    And lastly I suppose I was curious to see how that worked when comparing Sh% rather than CSh% (since that was one of the comments on twitter). So sorting by GF60 and removing the top/bottom 4 teams we still have a decent .4186 correlation between raw Corsi and Sh% (.6717 when eliminating top/bottom 5 and .7132 when eliminating top/bottom 6). As you pointed out, its not quite as high, but it still follow the same trend and suggests there is an inverse relationship between the number of shot attempts and the team’s Sh%.

    • Sebmono

      I looked at something similar to what you did and saw similar results from the Corsi For perspective but the relationship seemed to disappear when I looked at Corsi Against (one would expect it to be the same relationship). I think the important take away is not so much that for most teams shooting more correlates to shooting with less quality, but that teams have far more control over the quality of the shots they take as opposed to the quality of the shots taken against them. This would mean that the most important defensive skill at a team level would be shot suppression and not trying to “take away high quality chances”.

      Please check my comment in his later post from the 20th.