1
Photo Credit: © Stan Szeto-USA TODAY Sports

Pilot’s Logbook: Paul Postma

The Winnipeg Jets’ 2016-2017 disappointing season finally ended. While the extent of disappointment may be subjective from individual-to-individual dependent on expectations, fans without a single franchise playoff win prefer their seasons to carry some post-season excitement.

So, what went wrong? What went well? How do the Jets measure up against their competition? Which areas actually require improvement relative to others?

If your car breaks down, you need to know what is wrong with it prior to dropping cash to fix it. With that in mind, we continue our in-depth investigation on the Jets’ performance breaking down the team player-by-player from worst-to-best according to statistical impact, with some adjustments made by my own, personal analysis.

Up next: Paul Postma.

Basic Statistics

GP G A P +/- PIM PPG PPP SHG SHP GWG OTG S S%
65 1 13 14 +3 15 0 0 0 0 0 0 50 2.0

Paul Postma put up 14 points in 65 games as a third pairing defender with no power play ice time and only converting on two per cent of shots. That’s pretty impressive!

How did Postma pull that off? Post scored about one and a quarter points for every hour of five-on-five ice time. His point pace was the seventh highest in the NHL for defenders with at least 500 minutes played. The six ahead were Brent Burns, Dougie Hamilton, Erik Karlsson, Brady Skjei, Andrei Markov, and Jacob Trouba. That’s it.

Goals Above Replacement

Goals Above Replacement data courtesy of @DTMAboutHeart.

Goals Above Replacement (GAR) combines multiple statistics in terms of one currency, allowing one to estimate a player’s overall impact. It is imperfect, as it combines many imperfect statistics, but it is also a severely useful tool.

Postma is an underrated and under appreciated defender.

Paul Postma dressed for about 700 minutes with the Jets, almost exclusively even strength. Despite ranking 181st in the NHL for defender ice time, Postma ranked 128th in terms of results, just seven ranks behind Tobias Enstrom. His value predominately comes from his offensive impact, although he does have some defensive value, although below league average.

Advanced Metrics

TOI CF% REL CF% XGF% REL.XGF% G60 A60 P60
683 48.1 -1.96 48.4 -1.96 0.09 1.14 1.23

While Postma’s scoring was elite level impressive, his two-way numbers are not as flattering on a purely surface level investigation. However, Postma spent 523 of his 683 five-on-five minutes with either Mark Stuart or Ben Chiarot, who are notably worse performers. In both cases, Postma was notably superior performer away and they improved (Chiarot) or stagnated (Stuart) when with Postma.

I thought the above graphs were quite interesting. The left shows the Jets’ shots allowed with Postma on the ice, while the right is without Postma. In the right graph, we see the Jets are far better at preventing shots against up close on the right side. This makes sense with the Jets best players (Byfuglien and Trouba) being the alternative right shot defenders. Where the Jets perform worse predominately comes from the left side of the ice, which would more-often-than-not be the domain responsibility of the left-shot defender. Almost all of the minutes in the left graph for left-shot defenders would be Chiarot and Stuart, while most of the minutes on the right graph would be Morrissey and Enstrom.

This just further adds evidence, in addition to Stuart’s and Chiarot’s performance with and without Postma, that Chiarot and Stuart were pulling down Postma.

Postma did have some small time of relief away from the other two, where he played 72 minutes with Toby Enstrom, putting up a 58 per cent Corsi.

Microstatistics

Visual is for minutes played in 2015-16 and 2016-17 combined.

Microstatistics provide a window into the actions that players take that create the results they do in the previous sections. They allow us to see why Postma performs in the manner he does.

The graphic is a bit behind the raw data tracked, and so it only represents about 283 minutes for Postma, with the bulk being last season. It does have validity in suggesting the type of player Postma is offensively, and it suggests Postma is stylistically very similar to Tyler Myers. Both are defenders where their primary value comes from shot volume. They may not pass often, but when they do they are very often to a player in position to shoot.

Looking into the larger raw datasets we have tracked for the past season (almost the full year and all of Postma’s games), Postma fared similar to the Jets depth defenders like Stuart, Chiarot, and Melchiori in percentage of defensive zone touches being exit attempts, but was far superior in terms of the percentage of exits being with control of the puck. Postma leaned heavily on passing for zone exits, and could probably improve his exit numbers by skating it out more often.

It was the other end of the ice where Postma really started to shine. In terms of entry efficiency, Postma performed similarly to Dustin Byfuglien (who was second only to Jacob Trouba for the Jets regular defenders) in terms of percentage of entry attempts being successful carry-ins. Postma converted those entries into successful passes with even higher efficiency than Byfuglien or Trouba, which gave the Jets their highest shots per carry-in for all defenders.

Defensively, Postma sat around average around the board in defending against zone entries. I wonder how much of the Jets rankings in this area is random or situational, however, with the Jets seemingly giving up the blue-line systematically.

Please support Corey Sznajder (@ShutDownLine) for his contributions in manually tracking microstatistics. He has a Patreon page where you can make a donation for his tireless work supporting the community. Also, give Ryan Stimson (@RK_Stimp) a follow.

Final Thoughts

Postma is a flawed defender, but that’s what makes a third-pairing defender a skater you place on your third pair. You would be hard pressed to find a plethora of superior third-pairing defenders, especially at Postma’s salary.

Often on Jets Nation I simply analyze, but in these Pilot’s Logbook breakdowns I’ve gone further in discussing the philosophy and purpose behind analytical thinking. The whole point of statistical analysis in hockey is to better analyze players, but  not simply to know who is best. Analysis allows one to take advantage of market inefficiencies.

One large market inefficiency is human susceptibility to the big mistake. Paul Postma can make some very large and visible mistakes that causes fans to dislike and also coaches to mistrust. However, statistical analysis helps us understand that despite these mistakes, Postma stands as the superior depth option over “safer” players like Chiarot and Stuart.

Postma produces more value than the Jets depth defenders, despite many placing him at a similar or even lower tier. In addition, both the perceived value and compensation level gaps are far larger between players like Myers and Postma relative to the true performance value. While Postma may or may not actually be superior to Myers, the undervaluing of Postma allows for him to derive the team better bang for buck while playing on the team versus Myers who derives more bang for buck in the trade markets.

Thinking this way is how a small market Oakland A’s was able to slay the MLB in terms of wins per dollar for season after season. They never won the championships, but they came closer than they ever would have without. Thinking this way should motivate the Jets to do the same.

All numbers courtesy of Corsica.hockey, @ShutdownLine, or @DTMAboutHeart unless otherwise noted. Please follow them all.
This series was intended to be a Monday/Wednesday/Friday post, but with unforeseen circumstances, I will be accelerating posts and changing the schedule to be Monday-Friday posts for the duration of the series.


More Pilot’s Logbook Series