The Globe & Mail’s James Mirtle recently explained how he become intrigued in advanced stats in hockey, particularly the debate over how they applied to the Toronto Maple Leafs this season. 

Mirtle’s piece reminded me of my own discovery of advanced stats, or “hockey analytics”, and how over time I also came to believe in their validity.

Do advanced stats like Corsi provide an accurate measure of performance?

Do advanced stats like Corsi provide an accurate measure of performance?

Around the turn of this decade I began hearing terms like “Corsi”, “Fenwick” and “PDO” kicking around the hockey blogosphere. Googling these terms, I discovered Corsi and Fenwick were  measurements of shot attempt differential, except that Fenwick doesn’t measure blocked shots, while PDO is the addition of shooting percentage and save percentage at even strength.

As I understand it, these stats measure puck-possession, the theory being that the team which controls the puck generates more scoring chances. Corsi and Fenwick are not only used to measure a team’s possession numbers but also to evaluate individual players.

I confess I was skeptical of these statistics, not really see how these measurements had any significant impact upon the NHL game. Like Mirtle, I didn’t really begin to pay attention to them until this season. What sparked my interest were comments made last summer by Maple Leafs forward Joffrey Lupul and Toronto Sun columnist Steve Simmons dismissing the validity of advanced stats (particularly Corsi). When analytics bloggers predicted the Leafs poor puck-possession could hamper their playoff hopes, the debate was on.

As Mirtle observed, early in the season the Leafs were among the top teams in the league despite their poor puck-possession numbers. That had critics like Simmons scoffing over the validity of Corsi.

The analytics crowd, however, stuck by their guns, claiming the Leafs couldn’t possibly maintain their then-torrid pace. They were ultimately proven right when the Leafs struggled with consistency over the course of the season before collapsing down the stretch and missing the playoffs. By season’s end they had the league’s second-worst Corsi numbers, ahead of only the woeful Buffalo Sabres.

Looking further, I was amazed to see that, of the 14 NHL teams which failed to make the playoffs, the Corsi numbers of all but four (Ottawa, New Jersey, Phoenix and Vancouver) were in the bottom half of the league.

What finally won me over on Corsi was the numbers for the 16 playoff teams following the first round of this year’s playoffs. Of the teams in the bottom eight for Corsi numbers, all but two (Montreal and Anaheim) were eliminated from the first round.

I now believe advanced stats are valuable tools for evaluating team or player performance. Bear in mind, of course, advanced stats aren’t infallible. While they shouldn’t be taken as unshakable gospel, neither should they be blithely dismissed. They belong in the equation for measuring performance.

For those of you interested in learning more about advanced stats, check out the following:

“Advanced Hockey Stats – An Introduction”.

“Frequently Asked Questions about Statistical Analysis in the NHL”. Arctic Ice Hockey.

“Fancy Stat Summer School” – Habs Eyes On The Prize.

For more information on advanced stats, check out the following sites: ExtraSkater.comBehind The Net, Hockey Abstract, Department of Hockey Analytics, NHL Numbers, Arctic Ice Hockey, and