Practical Concerns: Meatballs & The Art Of Deployment


Last week, I dug up some old stats and posed this question to our Twitter followers and to a few people I know working in pro hockey.

Some interesting lessons were learned.

Information Underload

Marc Bergevin once said that it is difficult for fans to fully understand the decision-making process of NHL general managers and coaches because they don’t have access to all the information.

Most people I’ve talked to with at least a working knowledge of analytics were able to give very sensible suggestions on which three defense pairings to form given the available players, despite having no idea of who these players are and with only their 5vs5 With or Without You possession stats at their disposal.

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A New Way To Measure Deployment – Expected Faceoff Goal Differential

Zone starts are not that great of a metric. Although certain players do tend to be put out almost exclusively for offensive or defensive purposes, the reality is that for most players’ zone starts have a relatively small effect on a player’s performance. And yet, many hockey writers still frequently qualify a player’s performance based on observations like “they played sheltered minutes” or “they take the tough draws in the defensive zone”. Part of the problem is that we’ve never really developed a good way of quantifying a player’s deployment. With many current metrics, such as both traditional and true zone starts, it’s difficult to express their effect except in a relative sense (i.e. by comparing zone starts between players). So when a pundit says that a player had 48% of his on-ice faceoffs in the offensive zone, it’s difficult to communicate to most people what that really means.

Going beyond that, even if we know that 48% would make a player one of the most sheltered skaters in the league, the question that we should ask is so what? Simply knowing that a player played tough minutes doesn’t give us any information that’s useful to adjust a player’s observed results, which is really the reason that we care about zone starts. We know that if you start your shifts predominantly in the defensive zone, you’ll likely see worse results, but zone start percentages don’t tell us how much worse they should be. Traditional deployment metrics are too blunt of a tool – they provide a measurement, but not one that gives any context to the performance numbers that we really care about.

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