The Toronto Maple Leafs were the first team to pull the trick last week.

Wednesday in Detroit, the Leafs were heavily outplayed, right from the drop of the puck. They were outshot 38 to 14 at even strength. They had a possession rating of a little under 26 per cent, making it the third most lopsided game out of 447 in the NHL this season.

And yet they won.

Two nights later, Montreal did something similar, beating the defending Stanley Cup champion Los Angeles Kings 6-2 despite the fact they were outshot 46-20.

Their possession on the night? Only 37 per cent, their second worst showing of the year.

These are the kind of results that drive the critics of analytics crazy. How can a stat be useful and yet defied so regularly in games? Shouldn't it always be "right?"

It's widely known that hockey is significantly behind sports like baseball, football and basketball in terms of using analytics. And one of the biggest reasons for that is hockey is so much harder to distil down to one number or series of events.

For one, there are far fewer scoring plays in hockey than other sports (think goals versus touchdowns etc.). Fewer scoring plays means more chance is involved, both at the end of a game and the end of season.

Ultimately, that means winning in hockey is more heavily influenced by luck (or randomness) than other sports.

The other big difference between hockey is there is a goaltender – the single biggest wild card in any game, as evidence by James Reimer and Carey Price stealing the show last week.

All that makes hockey harder to measure and quantify. A unique sport, however, requires unique numbers to define what's happening.

Which is where possession comes in.

Gabriel Desjardins, an engineer in Silicon Valley who is one of the pioneers of hockey's analytics movements and has worked for multiple NHL teams, once calculated that puck possession at even strength was responsible for 37 per cent of an NHL team's record in a season.

The combined effect of luck and goaltending, meanwhile, is roughly 43 per cent.

That may seem to minimize how valuable possession stats like Corsi and Fenwick are for analysis, but if you take out the luck factor and goaltending, those numbers make up 65 per cent of what remains.

And that's before special teams – about 20 per cent of games – are even considered.

That's how important simply having the puck more than the other team is.

The main aspect of possession stats that makes them so valuable, however, is they're quite predictive of future success. A team that is good at controlling play in the first 20 or 30 games of the season usually excels in that area over the long term, which is not always the case with other aspects of play.

It's a stable attribute, in other words, and that helps it forecast (better than other stats) how a team will do over the remainder of the season and into the playoffs.

In fact, TSN's Travis Yost has shown that score-adjusted possession over the final 20 games of the regular season has correctly predicted the winner of playoff series 70 per cent of the time in the last eight seasons.

Last season, it was 12-3, and the best possession team in hockey (the Kings) again won the Cup.

For a stat that only accounts for a little more than one- third of winning – and omits goaltending entirely – that's an impressive track record.

Is there room for improvement in hockey analytics? Absolutely, and that will likely come once optical cameras are tracking games beginning in 2015 or 2016 and generating more data.

But Corsi and similar analytics remain important foundation stats that give simple, strong insight into an often difficult-to-measure game.

They may not always be right night-to-night because (a) they aren't attempting to be and (b) that's not likely possible. But don't bet against them over the long haul.

'The trough of disillusionment'

Desjardins calls the period where hockey's analytics are at – and the fact they're so highly controversial – "the trough of disillusionment."

It's a term used in the tech sector and comes from Gartner's Hype Cycle that gauges the adoption and application of new technology.

Or, in this case, analytics.

"The timeline that people expect change is very short," Desjardins said, referencing how previously weak franchises like Edmonton, Toronto and New Jersey made big investments in analytics in the summer. "When there's no immediate, obvious benefit, you have disillusionment."

The fact NHL teams are so secretive about what they're doing with data also doesn't help. It's difficult to know which actions they're taking as a result of using these new ideas and whether or not they're listening to their new analysts. It's therefore sometimes hard to draw conclusions as to whether they're working or not.