Statistical analysis coming to hockey in the same type of wave that hit baseball years ago. To help you navigate these uncharted waters, we've put together a short primer of some of the key new developments, with an emphasis not so much on what they actually mean, but rather what they tell us about a particular player or team.
The most important thing to understand first is why we use advanced statistics at all. Since no one can watch every single game, for every single team, and in every single league, there needs to be a way to mine all that action for the key information that signals the need for a closer look. Not only are statistics helpful in that role of identifying players, teams or situations that have been overlooked by traditional analysis, they're also useful as a sober second thought. After all, sometimes our own experiences and biases can influence our judgment while watching certain players and teams, so it can be invaluable to have the objective facts as confirmation.
All that being said, there are limitations in the field of hockey analytics. Using too small a sample size, ignoring context, measuring something of no direct value to goals/wins and studying a question from only a single perspective are all common examples where statistics can steer you wrong. For maximum effectiveness not only should the following advanced statistics be use together with one another, but also together with traditional analysis (which is better known as “watching the game”).
What is the first thing that statistical hockey analysts look at when studying a particular player? Surprisingly, it's usually ice time. Though these are actually called advanced statistics, most of them are actually very basic. That's why that phrase is used far less frequently these days, in favour of such terms as non-traditional statistics, analytics or fancy stats instead.
Ice Time
A picture of how much ice time a player gets at even-strength, on the power play and killing penalties is a great place to start studying a player. Not only does it provide the proper context for all other statistics, but it's usually an accurate representation of a player's strengths and weaknesses. Consider the Special Teams Usage Chart for last year's Stanley Cup finalist Boston Bruins, for example (from Hockey Prospectus 2013-14).
corrective factor, even for players.