Recently, an interesting article was published to the NHLNumbers website examining the behavior of skaters and their shooting tendencies, or how much they could be considered a “Puck Hog.” The article, written by Ben Wendorf, proposed an elegant way of measuring how frequently a player opts to shoot the puck.
Simply, the metric looks at the proportion of On-ice Fenwick (A’) that was represented by a specific player’s Fenwick shots (A). This number can be thought of as the Attempted Shot Ratio.
Ben found that this number did not correlate to things like shooting percent or quality of teammates, but that players showed the same tendency year after year. Thus, he concluded, “With high repeatability, and little connection to shooting talent, player development, or teammates, this seems much more like a behavioral activity.”
The article got me thinking about some of my own research that I did way back in the first month or so of writing this blog. I was messing around with players’ shots on goal versus missed shots, and determined what proportion of Fenwick shots were shots on goal (SOG/FEN), which I called Shooting Ratio. I had similar findings—that players could be productive even if they missed the net a lot, and the behavior was stable year after year. Something that stuck out to me during that research was the almost perfectly normal distribution of skaters’ ability to hit the net, so it was not much of a surprise to me when I checked with Ben and found that Attempted Shot Ratios also showed that perfect bell curve that we stat heads swoon over.
After mulling things over, I thought it would be insightful to combine Ben’s “Puck Hog” metric with my missed shot data to provide more of a two-dimensional look at player behavior. Or, simply,
How often do players choose to shoot, and how often do they hit the net?
I decided to look at just Minnesota Wild forward skaters from 2011-12 for this post, although I am working on a bigger dataset to look at more of a sample. I crunched all the numbers to determine players’ even-strength Attempted Shot Ratios (how often does the player take the shot when he’s on the ice) and Shooting Ratios (what proportion of those Fenwick shots are shots on goal) using the formulas listed above. All computations use 5v5 data.
After initially just comparing the 11-12 Wild players to each other, I realized that I would be better served using ‘population’ data that came out of Ben’s and my research. Specifically,
Attempted Shot Ratio: Mean = 0.244, SD = 0.05 (N = 2177 NHL forwards, 2007-2012)
Shooting Ratio: Mean = 0.737, SD = 0.074 (N = 492 NHL forwards > 10 GP, 2011-12)
The tables below list Minnesota forwards with their attempted shot ratio and shooting ratio. The z-scores associated with each are calculated using the population parameters listed above. Due to several players who wore the same number at different times, some numbers have been substituted for dummy numbers (Wellman, Taffe, Veilleux.)
|Almond, Cody (27)||.205||-.789||.778||.551|
|Bouchard, Pierre-Marc (96)||.265||.414||.803||.885|
|Brodziak, Kyle (21)||.266||.430||.712||-.338|
|Bulmer, Brett (19)||.233||-.229||.700||-.500|
|Christensen, Erik (26)||.205||-.787||.727||-.131|
|Clutterbuck, Cal (22)||.317||1.462||.686||-.684|
|Cullen, Matt (7)||.229||-.302||.872||1.083|
|Heatley, Dany (15)||.255||.221||.716||-.280|
|Johnson, Nick (25)||.281||.747||.817||1.083|
|Koivu, Mikko (9)||.218||-.513||.748||.144|
|Latendresse, Guillaume (48)||.314||1.391||.703||-.464|
|Mcintyre, David (34)||.214||-.594||.667||-.951|
|Mcmillan, Carson (45)||.215||-0.572||.571||-2.238|
|Ortmeyer, Jed (41)||.383||2.774||.645||-1.241|
|Palmer, Jarod (79)||.265||.426||.846||1.475|
|Palmieri, Nick (17)||.323||1.575||.747||.128|
|Peters, Warren (43)||.273||.581||.662||-1.010|
|Powe, Darroll (14)||.279||.700||.697||-.538|
|Rau, Chad (36)||.256||.248||.700||-0.500|
|Setoguchi, Devin (10)||.284||.796||.780||.578|
|Taffe, Jeff (97)||.286||.834||.750||.176|
|Veilleux, Stephane (98)||.228||-.326||.696||-.559|
|Wellman, Casey (95)||.309||1.302||.706||-.421|
|Zucker, Jason (16)||.345||2.017||.800||.851|
When charted, the z-scores can be informative because they fall into one of four quadrants on the chart. Attempted Shot Rate is on the X-axis, and Shooting Rate is on the Y-axis. For lack of better terminology, they are I – shooting inclined + accurate shot; II – shooting inclined + inaccurate shots; III – shooting averse + inaccurate shot; IV – shooting averse + accurate shot. (I really dislike using “accurate/inaccurate” here but I just don’t have a better pair of descriptors right now. If you have suggestions please share!)
*Click the chart to view the full-size version.
The first thing that jumps out to me is that the majority of players fall into quadrants I and II…so it’s a team full of puck hogs? Apparently so. Recall that the ASR data here are compared to the five-year population parameters, so the Wild have a lot of guys who choose to shoot the puck. I am trying to avoid value judgements here since a higher value ASR doesn’t necessarily represent “better hockey,” just a different playstyle. On the other hand, Sh Ratio is less subjective–making the goalie make a save is almost always better than missing the net. I know some times a player will shoot wide on purpose to try to make a play, but for now I am using the assumption that SOG > missed shot.
So the Wild had guys who were looking for shots but they had the fewest shots per game and goals per game. What to make of this? I wouldn’t necessarily expect a team-wide pattern to emerge when looking at this kind of plot, but it would seem to make sense that having more of a balance between shooters and set-up guys would produce more quality scoring chances. I would also think that a team distribution like this would indicate that the Wild players were predictable–the opponents probably figured out quickly that guys would be looking to shoot instead of making the extra pass, so perhaps that predictability suppressed their shot totals by making them easier to read. I’m just spitballing here, but if the Wild ranked high in a stat that measured blocked shots against, there might be something to this theory. But honestly at this stage in the research I’m still just digesting the numbers so again, if you have thoughts let’s hear them!
At the individual level, it is important to keep in mind that there isn’t really a “good play vs bad play” distinction here, it’s all just a measurement of behavior. Because we know that both ASR and ShR are normally distributed, it makes the indivudal results more interpretable, but a player who has a high attempted shot ratio isn’t necessarily doing his team any favors if he consistently misses the net more than his teammates. I do like the quadrant setup because it helps classify players. Matt Cullen doesn’t shoot much anymore, but when he does pull the trigger he hits the net more than any of his teammates. Mikko Koivu, known as a playmaker, prefers to make an extra pass rather than shoot, and is about average at hitting the net. Pierre-Marc Bouchard, another playmaker, actually shoots the puck more than I would have guessed, and is an accurate shot. Nick Johnson, despite having a strong tendency for the uncontrolled zone entry, pulls the trigger often and makes the goalie make a save. Dany Heatley is as close to zero on both scales as any player, which is probably a surprise to most of us. Cal Clutterbuck and Guillaume Latendresse have a strong tendency to shoot, but are somewhat wild.
In the end, it is my hope that this kind of multidimensional shooting analysis can be helpful in our understanding of players’ tendencies. This kind of stuff can’t be used in isolation, but rather it all works together to paint a picture and gives us a peek inside the head of the players we enjoy watching. The game of hockey is just a series of decisions, nearly all of which must be made at a speed where there is no time for conscious thought but instead are instinctual. I will be excited to continue this analysis to expand to different teams and different years. If you have questions or comments I would love to hear them. You can comment here on this page or though Twitter, @Hashtag_Hockey. Thanks for reading!