# Examining Rebound Control

Earlier this week, Rob Pettapiece had an interesting article over at NHL Numbers on rebound control, where he looked at the percentage of shots a goaltender faced that resulted in a rebound (which he defined as a shot within the 3 seconds following another shot). In the article, he concluded that while some goalies do appear to be able to control rebounds better than others, the effect of rebound control wasn’t that large, and wasn’t one that persisted year over year. While I agree with Rob’s conclusions based on his data, I worry that looking at the % of saves that result in a rebound is really a combination of three factors: 1) the goalie’s ability to control his rebounds; 2) his teammates’ ability to clear away any rebounds he does give up; and 3) his opponents’ ability to drive the net and get a shot, given a rebound opportunity.

With that in mind, I decided to take a look at things from a different point of view, considering how many saves a goalie made where the puck was frozen in the next 3 seconds. Hopefully looking at it through this lens will allow us to eliminate most of the team/opponent effects and focus on a goalie’s ability to control what happens after he makes a save.

Using the Play by Play data from the 2010-2011 and 2011-2012 seasons, I compiled a list of all even strength shots on net and recorded whether or not there was a stoppage coded as either “Puck Frozen” or “Goalie Stopped” (if anyone knows the difference between these two codes, if there even is one, please let me know). I then calculated the % Frozen by dividing the total number of stoppages by the total number of saves made.

In total there were 110,271 Even Strength Saves in the sample, with 30,557 of those being frozen in the next 3 seconds, giving an average % Frozen of 27.7%. The table below has the top and bottom 10 goalies who faced at least 500 shots over the 2 year period in our sample.

 Top 10 Bottom 10 Goalie % Frozen Goalie % Frozen RINNE, PEKKA 36.40% HILLER, JONAS 24.94% BOUCHER, BRIAN 34.67% GARON, MATHIEU 24.56% HARDING, JOSH 34.64% MASON, STEVE 24.41% NEUVIRTH, MICHAL 32.70% GUSTAVSSON, JONAS 24.16% BACKSTROM, NIKLAS 32.36% MCELHINNEY, CURTIS 24.03% RAYCROFT, ANDREW 32.29% VARLAMOV, SEMYON 23.78% BERNIER, JONATHAN 31.79% THEODORE, JOSE 22.64% BOBROVSKY, SERGEI 31.21% FLEURY, MARC-ANDRE 22.01% MASON, CHRIS 30.90% BRODEUR, MARTIN 21.19% REIMER, JAMES 30.57% KHABIBULIN, NIKOLAI 21.18%

We do see a little overlap with Rob’s list, with Pekka Rinne once again way out in front, and with Michal Neuvirth and James Reimer appearing in the top 10 of both lists. On the bottom half we see some interesting names, with Marty Brodeur and Marc-Andre Fleury taking 2 of the bottom 3 spots. Jonas Hiller also makes an appearance in the lower group, but other than that there aren’t too many names that standout from the “Worst Of” list.

The question then is how much of this data is skill versus luck or randomness. The good news is that the % of saves frozen does seem to be a repeatable skill (at least over the two years in our sample). Between 2010-2011 and 2011-2012 the correlation for goalies who made at least 250 even strength saves was 0.69, and the split half correlation was 0.68 (when split on the game number) and 0.69 (when split on the play-by-play number).

 R R^2 2010-2011/2011-2012 0.687 0.473 Even-Odd Games 0.683 0.467 Even-Odd Plays 0.690 0.476

With that being said, the ability to freeze the puck doesn’t seem to be a huge determinant of team success (most people probably would have guessed that when they saw Andrew Raycroft in the top 10). The R^2 between Percent Frozen and Regulation/OT Wins is 0.0515, while for total points it’s slightly lower at 0.0508, and the correlation with even strength save percentage is very small (0.11).

I suspect that there are a few things at play here: First, while rebounds are undoubtedly more dangerous shots, they result in a shot attempt so rarely that they play a relatively smaller role in the overall results. Second, inevitably each frozen puck results in a defensive zone draw, putting the goalie at an immediate disadvantage, and potentially counteracting some of the benefit of preventing a rebound.

The other element that may have an effect is that some goalies could be better at safely deflecting shots away (i.e. into the corners) which would decrease their % Frozen but could be more of a contributor to overall team success. I suspect that may be the case for some of the bigger names on the lower end of the scale, and for some of the higher ranking goalies for Rebound % who were below average by % Frozen. I think that looking at some combination of the two metrics will likely give us a better sense as to a goalie’s “true” rebound control ability, if one does exist.

Tagged with: ,
Posted in Goaltending
###### 3 comments on “Examining Rebound Control”
1. Very interesting. (I’m a baseball guy by trade, so I would probably never have thought of another approach.)

As you say, the d-zone draw removes the advantage somewhat, but I agree there is definitely more of a teammate-independent approach here. In my study a goalie could do nothing, be saved by his defence, and get credit for not allowing a rebound.

In any event, a combination is usually the way to go with these things. These are the distributions of the important events in the four seconds following a save (I added 1 second for a slightly larger sample), from the past three years:

FAC 46%
SHOT (i.e., save) 24%
BLOCK 12%
MISS 10%
PENL 5%
GOAL 3%

So between the two of us we’ve covered 73% of what happens next. The distribution of penalties would be interesting — almost certainly skewed towards penalties drawn by the offence, but maybe certain types (obstruction of someone heading to the net?) are more likely.

2. […] NHL Numbers looking at Rinne’s skill in preventing rebounds, while I followed up his article with my own version of a rebound control statistic which came to similar conclusions. Both these pieces are now relatively old, however, and I’ve […]

3. […] looking at Rinne otherworldly skill in preventing rebounds, while I followed up his article with my own version of a rebound control statistic which came to similar conclusions. Both of these pieces are now relatively old, however, and I’ve […]