This is the second post in a (likely) 3 part series going through the data/methods/results which I presented at the Pittsburgh Hockey Analytics Workshop. Part I, which covers whether defencemen play worse on their off-hand, is available here. If you’re interested in seeing the slides or hearing the presentation (or the other presentations, which I highly recommend), they’re available on the WaR on Ice website here.
As anyone who has ever dug into the data around defensive zone play knows, evaluating an individual player’s contribution in his own end is a difficult task. Most defensive metrics that we have today show far less year-over-year repeatability than offensive metrics, suggesting that they’re more likely measuring team or system effects than individual abilities. For defencemen, who tend to drive offensive play much less than forwards, this presents a particularly tricky challenge, as if we are unable to isolate their ability to defend their net from the opposition we aren’t left with much to judge them on.
Part of this challenge is just the nature of the data that’s recorded: when a player takes a shot attempt we note who took the shot, and for goals we also note the players that assisted as well. Both of these data points, while far from perfect, give us a better ability to differentiate the players who are driving the bus in the offensive zone from the skaters that are simply along for the ride. At the other end of the rink though we don’t have the same luxury: we know who took a shot against, but no one collects information on which defender was closest to the shooter, or who was (in theory at least) responsible for defending him. In an ideal world we’d have dozens of scorers or assistant coaches writing this data down, or better yet we’d have an intricate series of cameras available to track all of this information automatically (we can dream, right?), but even if this data is or will be collected it’s unlikely to ever make it into the public sphere.
While I may be painting a bleak picture here, the situation isn’t completely hopeless. The NHL’s game files do contain information on the location that each shot was taken from, and (with a bit of effort), we can leverage this data to get a better sense of an individual defenceman’s efforts at his own end of the rink. This is important after all, because if a GM is thinking about adding a shutdown defenceman at the trade deadline to make a playoff push, we want to know whether he’s actually preventing shots himself or whether his partner is doing the heavy lifting. While we can use our current metrics figure out whether a player generally allows more or fewer shots when he’s on the ice, we can’t really get a sense as to whether it’s due to his own efforts or not at first glance. And it’s with that thought in mind that I’m going to present an initial attempt at modelling a defenceman’s individual shot prevention ability in his own zone.
puck++ 