Plus-minus rating is a fundamentally flawed stat.

Goals-against average is misleading.

The dump-and-chase is not a fruitful offensive tactic (unless you’re the Los Angeles Kings).

The wrecking ball that is hockey analytics has taught us what not to care about. It has rerouted old-school trains of thought and moved the statistical needle forward.

When the common fan is hungry for a little extra insight, though, essays filled with line graphs and technical jargon sometimes can be a major turn off.

For all its good, advanced stats tend to complicate things, at least from afar. While the concepts behind the numbers aren’t all that “advanced” — Corsi, for instance, is very easy to comprehend — there’s no shortage of noise out there.

So, what really matters? Which modern stats should we be paying attention to in 2016?

Scenario A: Your favourite team acquires a forward you don’t know well.

“The first thing I would look at is time on ice,” says Matthew Coller, stats writer for ESPN Insider.

Paying attention to ice time distribution is not revolutionary. Inserting ice time into a statistical equation is, however, a relatively new practice.

As Coller points out, a 50-point forward who skates for 10 minutes a night is far more efficient than a 50-point forward who skates for 20. A more expressive number, then, is a forward’s Points Per 60 Minutes-played (P60) rating, because it adjusts for how often he sees the ice.

Under these conditions, Leon Draisaitl of the Edmonton Oilers is having an excellent season.

With 32 points in 33 games, the German centre was 37th on the league’s scoring list prior to Tuesday’s schedule, yet his even-strength P60 (2.82) paces all regular NHLers, according to War-On-Ice.com data.

The Oilers are getting plenty of offence from Draisaitl. Period.

It can be helpful to take the evaluation process a step further by cutting out secondary assists. By casting aside the runner-up assist, it’s easier to locate players who are having a direct impact on team success in the offensive zone.

“I don’t think there’s any point in keeping secondary assists,” says HockeyViz.com’s Micah Blake McCurdy, who is scheduled to deliver a presentation Saturday at a hockey analytics conference held at Carleton University. “There are some that are clearly on the back of good plays, but there are so many others that clearly are not and don’t actually add anything.”

First overall pick chances over past fortnight. pic.twitter.com/cfWQ74t1c2 — Micah Blake McCurdy (@IneffectiveMath) January 12, 2016

Scenario B: Your team acquires a defenceman you don’t know well.

To no one’s surprise, scoring takes a backseat here. Instead, Corsi is a logical entry point for picking apart unknown blueliners.

“At the end of the day, it’s encompassing multiple things,” says Domenic Galamini, stats consultant for the Ontario Hockey League’s Hamilton Bulldogs. “Winning board battles, recovering loose pucks, exiting the zone with control (of the puck), gaining the offensive zone with control — all of these things add up to a player’s Corsi differential.”

Still, an impressive Corsi rating doesn’t automatically make a defenceman good. Partners influence each other, both positively and negatively, in many facets of the game, often leading to similar metrics.

There’s two ways you can work through the pairing conundrum and emerge on the other side with a better grasp on the support system at work.

First, there are With Or Without You (WOWY) assessments, which, as the name implies, display a player’s stats while on the ice with another player as opposed to when the pair is separated.

It’s too soon to draw conclusions now, but expect Nashville Predators defenceman Barret Jackman’s puck-possession numbers to dip in the second half of the season. It’s no secret his former partner, newest Columbus Blue Jacket Seth Jones, was a first-pairing defender buried on the third pair in Nashville.

Another advanced stat used to compare defencemen — forwards, too — is Corsi For Percentage Relative (CF%Rel). It’s handy for identifying solid play-driving players on poor puck-possession teams.

Norris Trophy favourite Erik Karlsson is an excellent case study for CF%Rel.

His seasonal CF% is 51.67, according to War-On-Ice.com, meaning the Ottawa Senators control play more than half of the time Karlsson is on the ice at even-strength. The team is on the wrong side of the puck (43.58 CF%) when he’s not on the ice.

The 8.1 difference is Karlsson’s CF%Rel, a number which ranks first among defencemen who have played at least 300 5-on-5 minutes.

Seth Jones <-> Ryan Johansen pic.twitter.com/dcftZR5fQN — Domenic Galamini (@MimicoHero) January 6, 2016

Scenario C: Your favourite team should be winning but it isn’t.

On the surface, something just doesn’t add up with the 2015-16 Carolina Hurricanes.

They are a bottom-tier club sporting the fourth-best team CF% (53.3).

Not being able to put the puck in the net has buried them. One glance at what coach Bill Peters has to work with and — bam! — it all makes sense. Very limited scoring options.

Conversely, you could slap the label “riding the percentages” on a handful of NHL teams and about a dozen NHL players at any given time during a season. Luck is ever-present in this sport.

The New York Rangers, with a 9.8 even-strength team shooting percentage, have been lucky through the first half of the season. But, eventually, they won’t be so fortunate.

The Kings, on the other hand, are the envy of the NHL.

A league-high team CF% (56.2) — the by-product of smothering the opposition on a nightly basis — and a roster filled with finishers is a dangerous combination.

Corsi has been the cliche advanced stat since the inception of analytics. It’s a cliche for good reason, though, as shot attempts continue to hold great importance, especially at the team level.

“I think the biggest lesson that we have learned in analytics is that shot volume is the most important thing,” says McCurdy. “If you want to consistently win games, the best way to do it is to drive the puck up to the other end of the ice again, and again, and again.”

OK … but what about my favourite team’s goalie?

Must-know insight on advanced goalie stats: Nobody has cracked the code.

Aside from even-strength save percentage essentially replacing all-situation save percentage, consensus is difficult to find in this corner of the hockey analytics world.

Shot quality has been a debatable topic for years now. The position’s complexities don’t help the matter, either.

“There’s so much out of their control and that’s why it’s such a challenge,” Galamini says, before adding, “we have a long way to go when it comes to evaluating goaltenders. Hopefully, in the future when we have RFID tracking, we can track things like pre-shot movement that can shed some light on things that are under a goaltender’s control.”

Email: john.matisz@sunmedia.ca

Twitter: @MatiszJohn