Stuart logged huge minutes on the penalty kill and essentially none on the power play. He ended the season with the 6th-best plus/minus, with a +5 rating. Mark Stuart carried the Jets’ team-worst goal differential of the 13 defenders when looking at even strength (-3), power play (+0), and penalty kill (-19). One example I like to use is Mark Stuart of the Winnipeg Jets for the 2014-2015 season: It is simply because it seemed right to the first person who made the rules for the number, and then tradition has kept it that way. There is no science or evidence-backed reasoning to the meaningfulness of using some goals and not others. There is a tendency for penalty killers to play in the lead situation, and power play unit skaters to go out with the trailing situation, so these two factors in general skew in the same direction for skaters.Ī handful of short handed and empty net goals may not seem like much, until you realize that the standard deviation in even strength goal differential is only about nine goals. Players who are playing from behind and have their own goalie pulled are the opposite. This means that players who typically play with the lead and the opposition’s goaltender pulled are more likely to garner pluses than minuses over the long run. The skew is increased further by empty nets. Pulling the goalie is a desperation tactic, that increases the chance of scoring while also increasing the chance of a goal against even more. It also means that a penalty killer can only improve their rating with tallies in the plus column (or stay even). The longer they spend in those situations, the greater the likely skew, regardless of how effective they are in their respective special teams deployment. Including only shorthanded goals means that the power play can only hurt a skater’s rating (or stay even). This causes some very odd skewing in plus/minus to particular player types. The plus/minus statistic includes all even strength goals, all goals with either goaltender pulled (as hockey views goalie pulled as even strength), and short handed goals. The number is not exclusive to 5v5, or even strength. This is sometimes news to those that use plus/minus as a stat. #Canucks score on themselves on a delayed penalty. Plus/Minus arbitrarily chooses to exclude some goals and not others Goals are rare, and with any rare statistical event it becomes easy for the sample to be skewed by outliers and not be indicative of the “true-talent level” or population. There are also more confounding variables added with the highly unstable impact that is goaltending performance on both ends while a player is on the ice.Ĭombining a rare event with highly variable confounding variables and you get a number that takes a very long while to settle. With outscoring, this often means multiple seasons. We’re not even limited in shot quantity only in the toolbox anymore either, as shot metrics can now account for shot quality, like with the expected goal (xG) model seen above. What is most likely to happen in the future is a better measure of who they truly are rather than what happened before. Noting who outscored who doesn’t really matter if they do not continue outscoring. The purpose of analysis is to maximize the probability of future outscoring, and to do this requires looking at those metrics that suggest success is most likely in the future. This uncertainty means we can’t rely on goals for predictivity. I wanted to get the obvious one for a hockey stats guy to argue out of the way first.ĭon’t get me wrong, goals are the end objective, and in the very long run it should be worth at least a look, but we also know that sometimes players get lucky bounces, or that goaltenders steal games. Predicting future 5v5 outscoring by DTM About Heart and Asmean Shot based metrics are typically better than goals While I do feel that way, it is only one of a few reasons that that plus/minus fails in being useful. Now, some people may read that and think I’m simply saying this because I value shot metrics over goal metrics in player evaluations. It could even be in contention for just the worst statistic in sport. Hockey’s plus/minus may be the worst statistic in hockey, although there is some debate with goalie statistics not based off of save percentage (like GAA or Win% that just adds a team component to a goalie’s save percentage). Every once-in-a-while I will rant on the concepts and ideas behind what numbers suggest in a series called Behind the Numbers, as a tip of the hat to the website that brought me into hockey analytics: Behind the Net.
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