Further investigation into impact of zone starts

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Apr 192013

Tyler Dellow has a post at mc79hockey.com looking at zone starts and defensemen and if you read it the clear conclusion is that zone starts seem to matter quite a bit. In the third chart you can see that defensemen who get the most extreme defensive zone starts have an average corsi% of 44.7% while the average corsi% for defensemen with the most extreme offensive zone starts is 53.3%. This would seem to indicate that for defensemen zone starts can impact your corsi% anywhere from -5.3% to +3.3%. This is far more significant than I have estimated myself using a different methodology so I pondered that part of the reason for this is that when you start in the defensive zone you are playing with weaker quality of teammates than when you start in the offensive zone. My reasoning is that players that get used primarily in the defensive zone are often weak offensive players as if you are a good offensive player you will be given offensive opportunities. I wanted to explore this concept further and that is what I present to you here.

Unlike Tyler Dellow I used forwards in my analysis but it is unlikely that this will have a major impact in the analysis as forwards and defensemen are always on the ice together. One difference between my analysis and Tyler Dellow’s is I used data from stats.hockeyanalysis.com where as Tyler used stats from behindthenet.ca. Behindthenet.ca includes goalie pulled situations in their data and this has the potential to greatly emphasize the impact of zone starts. I feel it is important to eliminate this factor so I have it removed from the data. I also only used 2011-12 data but that shouldn’t have a major impact on the results.

So, my theory is that players who start in the defensive zone are weaker players overall. The challenge to this is that players who start with players that start frequently in the defensive zone likely start frequently in the defensive zone themselves and thus their stats are subject to zone start effects so if they have weak stats we don’t know whether they are due to the zone starts or because they are weak players. My solution was to look at the players zone start adjusted stats that I have on stats.hockeyanalysis.com. These stats ignore the first 10 seconds after a zone face off as it has been shown that the majority of the benefit/penalty of a zone face off has largely dissipated after 10 seconds. I understand that it may seem weird to use zone start adjusted data in a study that attempts to estimate the impact of zone starts but I don’t know what else to do.

I want to also point out that I will be using ZS adjusted FF% team mates when the team mates are not on the ice with the player and this may also mitigate the ZS impact on the teammates stats. My reasoning is, if a player has an extensive number of defensvie zone starts, it is quite possible that when his team mates are not playing with him their zone starts are more neutral or maybe even offensive zone biased. It if there ever was a way to get a non-zone start impacted FF% to use as a QoT metric this is probably the best we can do.

Ok, so what I did was compare a players 5v5 FF% (fenwick %) and zone start adjusted 5v5 TMFF% (zone start adjusted FF% of teammates when team mates are not playing with him) and came up with the following:


As you can see, TMFF% does seem to vary across zone start profiles as I had hypothesized though to a lesser extent than the players zone start influenced FF% which is to be expected. So, if we subtract TMFF% from FF% we get the following chart:


This chart indicates that the zone start impact on forwards once adjusted for quality of teammates (as best we can) ranges from -2.5% to +2.15% which is significantly lower than the -5.3% to +3.3% estimate that Tyler Dellow came up with for defensemen without adjusting for quality of teammates and using goalie pulled situations included in the data. That said, this is still more significant than my own estimates when I compared 5v5 data to 5v5 data with the first 10 seconds after a zone start ignored. When I did that I calculated the impact on H. Sedin’s FF% due to his heavy offensive zone starts to be +1.4% to his FF% and considered this an upper bound. To investigate this further I plotted the average difference between 5v5 FF% and my 5v5 zone start adjusted FF% and I get the following:


The above is an estimate of the average impact of zone starts using my zone start adjustment methodology which ignores the first 10 seconds after a zone face off. This is significantly lower than either of the previous 2 estimates as we can see in this summary table:

Methodology ZS Impact Estimate
T. Dellow’s estimate for defensemen -5.3% to +3.3%
My TM Adjusted estimate for forwards -2.5% to +2.15%
My 10 second after Zone FO adjustment for forwards -0.5% to +0.41%

I am pretty sure none of what I have said above will put an end to the impact of zone starts on a players statistics debate but at the very least I hope it sheds some light on some of the issues involved. For me personally, I have the most confidence in my zone start adjustment method which removes the 10 seconds after a zone face off. My reasoning is studies have shown that the effect of a zone face off is largely eliminated within the first 10 seconds (see here or here) and also because it is the only methodology that compares a player to himself under similar playing conditions (i.e. same season, almost identical QoT, QoC and situation profiles) eliminating most of the opportunity for confounding factors to influence the results. If this is the case, the impact of zone starts on a players stats is fairly small to the point of being almost negligible for the majority of players.


Mar 142013

I often see people using zone starts and/or quality of competition as a way to justify any players unexpectedly poor or unexpectedly good play. Player X has a bad goal or corsi ratio because he plays all the tough minutes (i.e. the defensive zone starts and against the oppositions best lines). I am pretty certain that quality of competition is vastly over emphasized (everyone plays against everyone to some extent) and is vastly overshadowed by individual skill and quality of teammates, and I think zone starts do as well.

Eric Tulsky at NHL Numbers.com posted a good review of the research into the zone start effects on corsi statistics and I recommend people give that a read. I want to look into the issue a little further though. Most of the attempts to identify the impact of zone starts on a players stats have been inferred by looking at the league-wide correlations or by actual counting of how many shots are taken after a zone face off. Both of these have their faults. As Eric Tulsky pointed out, taking a correlation of every players corsi with their zone start stats doesn’t take into account that it is the top line players that usually get the offensive zone starts and thus this likely over estimates the impact as these players do take more shots regardless of their zone start. Eric Tulsky also took the time to count the number of fenwick events that occur between an offensive zone face off and the time the puck leaves the offensive zone and estimated that to be 0.31. This would imply that every extra offensive zone start a player takes is worth 0.31 fenwick events. Of course, this doesn’t take into account that the best offensive players in the league typical get more  offensive zone starts but it also doesn’t consider what happens after the puck leaves the zone. If the puck leaves the zone under the opposing teams control there is probably a negative fenwick effect for the next several seconds of play reducing the 0.31 number further.

I want to get beyond these issues by taking a look at how zone starts affect individual players. I have previously argued that after 10 seconds of an offensive/defensive zone face off the majority of the benefit (or penalty) of an offensive (or defensive zone) face off has worn off. I wanted to take it a bit further to be sure that there is no residual effect and chose to conduct this analysis using a 45 second cut off. So, any time within 45 seconds of an offensive or defensive zone face off with no other stoppages in play will be eliminated in my face off adjusted data. This should eliminate pretty much every second of every shift that started with an offensive or defensive zone face off leaving just the play that occurred after a neutral zone face off or on the fly changes. I am going to call this ice time F45 ice time and it will represent ice time that is not in any way affected by zone starts. With this in mind, I will take a look at the differences between straight 5v5 stats and the F45 stats and the differences will give me an indication of how significant zone starts impact a players stats.

To do this I will look at both corsi for and corsi against stats on a per 20 minutes of ice time basis. It should be noted that corsi rates are about 7.5% higher during the f45 play (goal rates are ~15% higher!) so I will reduce the f45 corsi rates by 7.5% to account for this and conduct a fair comparison (previous zone start studies may have been impacted by this as well). Now, let’s take a look at eight players (Manny Malhotra, Dave Bolland, Brian Boyle, Jay McClement, Tanner Glass, Brandon Sutter, Adam Hall, and Taylor Pyatt) with an excess of defensive zone starts.

OZ% DZ% OZ%-DZ% FF20 FA20 FF%
Malhotra 12.2 54.6 -42.4 -3.09% 1.09% -1.0%
Bolland 19.8 40.5 -20.7 8.94% -5.25% 3.5%
B. Boyle 21.0 40.2 -19.2 2.87% 8.74% 0.3%
McClement 24.8 41.9 -17.1 -0.31% 1.34% -0.4%
Glass 20.5 37.1 -16.6 4.39% -6.00% 2.6%
Sutter 23.1 36.6 -13.5 -2.67% 2.32% -1.2%
Hall 20.7 33.9 -13.2 -4.06% 4.59% -2.2%
Pyatt 24.0 36.4 -12.4 0.38% -0.25% 0.2%
Average 20.8 40.2 -19.4 0.81% 0.82% 0.23%

The FF20 and FA20 columns show the % change in from 5v5 play to F45 play and the FF% column shows the 5v5 FF% – F45 FF%. The averages are a straight average, not weighted for ice time or zone starts. For players that have a significant defensive zone bias we would expect their F45 play to exhibit an increase in FF20 and a decrease in FA20 resulting in an increase in FF%. In bold are the circumstances where this in fact did happen. As you can see, this isn’t the majority of the time. It is actually kind of surprising that these heavily defensive zone start biased players didn’t see a significant and systematic improvement in their fenwick rates.

Now, let’s take a look at eight players (Henrik Sedin, Patrick Kane, Maian Gaborik, Justin Abdelkader, Kyle Wellwood, Tomas Vanek, John Tavares, Jason Arnott) who had a heavy offensive zone start bias.

OZ% DZ% OZ%-DZ% FF20 FA20 FF%
H. Sedin 49.3 16.2 33.1 -3.72% 1.81% -1.4%
P. Kane 41.4 20.3 21.1 5.94% 4.66% 0.3%
Gaborik 39.0 22.8 16.2 0.60% 2.32% -0.4%
Abdelkader 37.5 26.0 11.5 3.93% 3.49% 0.1%
K. Wellwood 36.9 27.6 9.3 4.54% -2.32% 1.7%
Vanek 36.2 27.2 9.0 -3.39% 1.06% -1.1%
Tavares 35.8 27.2 8.6 -2.39% 1.83% -1.0%
Arnott 36.4 28.0 8.4 -3.41% 1.81% -1.3%
Average 39.1 24.4 14.7 0.26% 1.83% -0.39%

For offensive zone start biased players we would expect to see their FF20 decrease, FA20 increase and FF% decrease when we remove their zone start bias. This is mostly true for FA10 (only Wellwood deviated from expectations) but less true for FF20 and FF% and overall the adjustments were relatively minor. Henrik Sedin had the greatest negative impact to his FF% but it only took him from a 55.2% fenwick player to a 53.8% fenwick player which is still pretty good. This could very well be an upper bound on the benefit of excessive offensive zone starts.

Eric Tulsky also presented a paper at the recent Sloan Sports Analytics Conference in which he suggested that a successful zone entry via carrying the puck in is worth upwards of 0.60 fenwick and upwards of 0.28 fenwick on a dump in. As pointed out earlier, Eric Tulsky counted o.31 fenwick between an offensive zone face off and the puck clearing the zone so and if the other team is clearing the zone with control of the puck, it is certainly possible that they will generate almost as many shots on their subsequent counter-rush essentially negating much of the benefit of the offensive zone start. Without studying zone exits and how frequently zone exists result in successful zone entries into opposing teams end we won’t know for sure, but the data shown above indicates that this might be the case.

The next question that might be worth exploring is, if there is no significant benefit to starting your offensive players in the offensive zone, is there a penalty? For example, might it be better for the Canucks to start the Sedin’s solely in the defensive and neutral zones on the theory that their talent with the puck will allow them to more frequently carry the puck into the offensive zone which, as Eric Tulsky showed, more frequently results in shots and goals. I am not certain of that but might be worthy of further investigation.  I suspect again any benefit/penalty of any zone start deployment will largely be overshadowed by the players individual ability and the quality of their line mates. The ability to win puck battles, control the puck and move it up the ice is the real driver of stats, not usage of the player.

All of this is to say that coaching strategy (at least player usage strategy) is probably not a significant factor in the statistical performance of the players or the outcomes of games and I suspect, as I previously found, the majority of the benefit of an offensive zone start is those situations where you win a face off, take a shot resulting in a goal or the goalie catching it or covering it for another face off.  If the play goes beyond that individual talent (puck retrieval for example) takes over and the opposition will get an opportunity to counter attack. This is why, as I previously determined, eliminating the first 10 seconds after a face off is sufficient for eliminating the majority of the effects of a zone start and even then, the effects are probably not as significant as we think they should be.


Using goalies to estimate zone start impact on corsi

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Nov 082012

Eric T. over at NHL Numbers had a post last week summarizing the current state of our statistical knowledge with respect to accounting for zone start differences.  If you haven’t read it definitely go read it because it is not only a good read but because it concludes that how the majority of people have been doing is is wrong.

Overall, no two estimates are in direct agreement, but the analyses that are known to derive from looking directly at the outcomes immediately following a faceoff converge in the range of 0.25 to 0.4 Corsi shots per faceoff — one-third to one-half of the figure in widespread use. It is very likely that we have been overestimating the importance of faceoffs; they still represent a significant correction on shot differential, but perhaps not as large as has been previously assumed.

In the article Eric refers to my observation that eliminating the 10 seconds after a zone start effectively removes any effect that the zone start had on the game.  From there he combined my zone start adjusted data found at stats.hockeyanalysis.com with zone start data from behindthenet.ca and came up with an estimate that a zone start is worth 0.35 corsi.  He did this by subtracting the 10 second zone start adjusted corsi from standard 5v5 corsi and then running a regression against the extra offensive zone starts the player had.  In the comments I discussed some further analysis I did on this using my own data (i.e. not the stuff on behindthenet.ca) and came up with similar, though slightly different, numbers.  In any event I figured the content of that comment was worthy of its own post here.

So, when I did the correlation between extra offensive zone starts and difference between 5v5 and 5v5 10 second zone start adjusted corsi I got the following (using all players with >1000 minutes of ice time over last 5 seasons):

My calculations come up with a slope of 0.3043 which is a little below that of Eric’s calculations but since I don’t know the exact methodology he used that might explain the difference (i.e. not sure if Eric used complete 5 years of data, or individual seasons).

What is interesting is that when I explored things further, I noticed that the results varied across positions, but varied very little across talent levels.  Here are some more correlations for different positions and ice time restrictions.

Position Slope r^2
All Players >1000 min. 0.30 0.55
Skaters >1000 min. 0.28 0.52
Forwards >1000 min. 0.26 0.50
Defensemen >1000 min. 0.33 0.57
Goalies >1000 min. 0.44 0.73
Forwards >500 min. 0.26 0.50
Forwards >2500 min. 0.26 0.52
Forwards 500-2500 min. 0.26 0.39

Two observations:

1.  The slope for forwards is less than the slope for defensemen which is (quite a bit) less than the slope for goalies.

2.  There is no variation in slope no matter what restrictions we put on a forwards ice time.

There isn’t really much to say regarding the second observation except that it is nice to see consistency but the first observation is quite interesting.  Goalies, who have no impact on corsi, see the greatest zone start influences on corsi of any position.  It is a little odd but I think it addresses one of the concerns that Eric had pointed out in his article:

The next step would be to remove the last vestige of sampling bias from our analysis. The approaches that focus on the period immediately after the faceoff reduce the impact of teams’ tendency to use their best forwards in the offensive zone, but certainly do not remove it altogether.

I think that is exactly what we are witnessing here, but maybe more importantly teams put out their best defensive players and, maybe more importantly, their best face off guys for defensive zone face offs. If David Steckel, who is an excellent face off guy, is getting all the defensive zone face offs, it is naturally going to suppress the corsi events immediately after the defensive zone face off because he is going to win the draw more often than not.  There is probably more line matching done for the zone face offs than during regular play so the line matching suppresses some of the zone start impact.  It is more difficult to line match when changing lines on the fly so a good coach can more easily get favourable line matches. The result is normal 5v5 play offensive players might see a boost to their corsi (because they can exploit good matchups) and during offensive zone face offs they see their corsi suppressed because they will almost always be facing good defensive players and top face off guys.  Thus, the boost to corsi based on a zone start is not as extreme as should be for offensive players.  The opposite is true for defensive players.

Defensemen are less often line matched so we see their corsi boost due to an offensive zone face off a little higher than that of forwards, but it isn’t near as high as goalies because there are defensemen that are primarily used in offensive situations and others that are primarily used in defensive situations.

Goalies though, tell us the real effect because they are always on the ice and they are not subject to any line matching.  In the table above you will notice that goalies have a significantly higher slope and an impressively high r^2.  I feel I have to post the chart of the correlation because it really is a nice chart to look at.

I have looked at a lot of correlations and charts in hockey stats but very few of them are as nice with as high a correlation as the chart above.

I believe that this is telling us that an offensive zone start is worth 0.44 corsi, but only when a player is playing against similarly defensively capable players as he would during regular 5v5 play which I speculate above is not necessarily (or likely) the case.  The 0.44 adjustment really only applies to an idealistic situation that doesn’t normally occur for any players other than goalies.  So where does that leave us?  Should we use a zone start adjustment of 0.44 corsi for all players, or should we use something like 0.33 for defensemen and 0.26 for forwards?  The answer isn’t so simple.  One could argue that we should apply 0.44 to all players and then make some sort of QoC adjustment and that would make some sense.  But if we are not intending to apply a QoC adjustment, does that mean we should use 0.33 and 0.26?  Maybe, but that is a little inconsistent because it would mean you are using a QoC adjustment only for the zone start adjustment of a players stats, and not for all his stats.  The answer for me is what I have been doing the past little while and not even attempt to adjust a players stats based on zone starts differences and rather simply just ignore the the portion of play that is subject to being influenced by zone starts – the 10 seconds after a zone start face off.  To me it seems like the simplest and easiest thing to do.


Adjusting for Zone Starts

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Jan 232012

One of the biggest omissions in my player rankings is making adjustments for zone start differences.  We know that Manny Malhotra has a significant bias towards starting his shifts in the defensive zone and that his teammates Daniel and Henrik Sedin have a significant bias towards starting their shifts in the offensive zone.  The result is Malhotra will unfairly be penalized for giving up more shots and goals against simply because he starts more often in the defensive zone and the Sedins have a huge advantage in generating shots and goals because of how often they start their shifts in the offensive zone.  The question is, how much of an effect does it have and how do we adjust for it?

Over the past couple of weeks I have been pondering these questions and I thought of two potential solutions to the problem.  The first solution is to find some sort of adjustment factor based on zone start statistics.  I briefly pondered a few ideas but wondered if a uniform adjustment factor can be fairly applied to all players who have varying skills and talents.  I decided that I would take a look at my second idea first.

My second adjustment idea is really a simple idea and really isn’t an adjustment at all.  The idea is to just ignore any play that occurs during some stretch of time after an offensive/defensive zone face off.  After some length of time, any advantage (or disadvantage) one might get from starting in the offensive (or defensive) zone would be nullified.  Worst case scenario is we have to eliminate ~45 seconds after every offensive or defensive zone face off which would essentially nullify the whole shift.

So, with that in mind I took a look at 3 year (2008-09, 2009-10 and 2010-11) 5v5 statistics and did a comparison of four different lengths of time to ignore after an offensive/defensive zone faceoff – 0, 10, 20 and 30 seconds.  To evaluate what is going on I looked at each players fenwick for and against per 20 minutes and calculated the correlation between each time after faceoff adjustment.  Here is what I found:

FenF/20 FenA/20
5v5 vs F10 0.8639 0.8451
F10 vs F20 0.9882 0.9866
F20 vs F30 0.9870 0.9883
5v5 vs F20 0.8718 0.8368

5v5 is no zone start adjustment, F10 is ignoring 10 seconds after an offensive/defensive zone faceoff, f20 is ignoring 20 seconds after and f30 is ignoring 30 seconds after.  The numbers are r^2 for fenwick for per 20 minutes and fenwick against per 20 minutes.

As you can see, there is a somewhat sizeable difference between 5v5 and the F10 adjustment but there is very little difference between the F10 and F20 or F20 and F30 and there isn’t really any difference between 5v5 vs F10 and 5v5 vs F20.  All of this tells me that any advantage (or disadvantage) a player gains because of their zone stars occurs during the first 10 seconds after an offensive or defensive face off.  After that, only the players talent matters and there is no benefit to removing more data from our analysis.

Wanting to confirm this works for a single season of data I decide to take a look at Manny Malhotra and Henrik Sedin’s stats from last season.

Malhotra FenA/20 Sedin FenF/20
5v5 14.16 15.39
F10 12.49 13.31
F20 12.44 13.66
F30 12.24 13.71

This confirms what we witnessed with the correlations using 3 years of data.  By ignoring the first 10 seconds after an offensive/defensive zone faceoff we can eliminate any benefit/penalty a player may get because of his zone starts.  When I finally get around to updating my stats site I intend to include F10 data as well and I think this is a simple enough solution to abandon any attempts at any other zone start adjustment technique.