Our team-by-team preseason tour gets underway with a look at the Seahawks and if we should expect more defensive regression ... In MLB, those who don’t do your Charlie Morton and Alex Cobb homework will be thrown a “curve”
It is time to begin what has become an annual adventure, a team-by-team pre-season tour across the NFL, though the first time at this new platform. The goal is to isolate one key issue per team that the shrewd handicapper can focus on, and the timing of doing it while training camps are open is intentional – there are some terrific pre-season publications available for you to read, but some of the material can also be a little stale as personnel changes take place.
There is also another aspect in which the notion of being stale comes into play, and that will be a big part of our trek – I will particularly focus on teams that bring carry-over statistics from 2016 that are of little relevance into the new season. I know that can be frustrating to many folks. Some have those nice clean data-bases of stats to work from, and while those of you are relatively low in number, the others have all of those publications filled with statistics that look so powerful and so convenient when laid out across various modes of print. You’ll need to muck them up if you want to win.
Many of those numbers are misleading, some so much so that they are utterly useless. There are also those that indeed mean something, but not what they may first appear to. That means time to get to work, and I will sort through what will be a reverse process from many of the usual modes – I am going to go from West to East, and inverse alphabetical order through the divisions.
We begin our 2017 tour in Seattle, the luck of the draw with the Seahawks being that we can get right into the notion of carefully clarifying some key statistics in order to properly carry them forward.
The 2017 Seattle defensive numbers are important, but only if you file them in the proper place
Until the closing quartet of the 2016 regular season, Pete Carroll had never coached a Seattle game without Earl Thomas on the field. Thomas has never played an NFL game under someone other than Carroll, arcs that have meshed in a unique way. What they have done well together now can be measured through an enhanced focus based on what happened when Thomas was not available, and there was such a striking difference that it becomes something that requires a deeper statistical dive.
Let’s begin with an overall look at the meshing of the Seahawks defense, starting with the season before Carroll and Thomas arrived, and the progression since then. I will use the weighted ratings from Football Outsiders, which will be the default here across much of the analysis this season.
Year Total D Pass D
2009 27 30
2010 32 29
2011 9 9
2012 7 3
2013 2 1
2014 1 2
2015 3 3
2016 9 13
The 2016 numbers, or course, require an * because of the Thomas injury vs. Carolina in Game #12. At the time the Seattle defense was on pace to rate among the NFL’s best once again, within the range of those stellar units of the previous three seasons. Then it went bad, very bad, the pass defense having a miserable closing stretch despite being served up with a gimmee on a Thursday night home vs. Jared Goff/Case Keenum and the Rams in Game #14.
The best source I have found in breaking down the particulars of Thomas-In and Thomas-Out is through the meticulous work of Warren Sharp. I will not steal from his thunder because most of you should be buying his pre-season annual, as well as the 2017 Football Outsider’s Almanac, but there were some excerpts in a recent piece in the Seattle Times that lays it out well.
My 2016 Seattle defensive ratings were filed away after the Seahawks whipped Carolina in Game #12. Yours should also. What happened after that does indeed have value because it helps to put Thomas in perspective – he has been a glue guy on a defense that has seen Richard Sherman and others gain more notoriety, and while there was more than just his impact involved in the closing stretch, his absence was the catalyst for the sharp performance decline.
What else happened that matters? The inability of the Seahawks to run the ball consistently, and work some play clock, forced their own defense to have to be on the field too long. Since this connects to the original take, let’s explore.
The Seattle ground game fell from #3 in effectiveness in 2015 to #23 last year on the FO charts. It naturally becomes more difficult to stay on the field without balance, and the Seahawks yards per possession took a significant hit, from 34.2 to 31.7. In terms of how that impacted the defense, Seattle fell from #1 in 2015 for fewest plays faced to #17 in 2016, the defense on the field for 73 additional snaps.
Note that a key to using the FO numbers is that it is about efficiency, and not accumulation, but while there is a direct negative in the latter the longer a unit is on the field, there is also an indirect connection to the former, because fatigue can impact efficiency. I believe it did.
Thomas looks ready to go as the Seahawks training camp begins, and there has been some added depth in the pass rush via Marcus Smith, and in the secondary through the draft (the lack of depth contributed to the late-season performance decline). That renders the overall 2016 Seattle defensive numbers as being most misleading given the potential of the current group, and your first step in setting a good Seahawks power rating is to properly filter through them.
Now let’s head over to the MLB diamonds …
Those who don’t do your Charlie Morton and Alex Cobb homework will be thrown a “curve”
When Morton and Cobb face off in Houston tonight there is a statistical issue comparable to what we will be dealing with across so many NFL case studies – you won’t get the proper feel for their bottom lines unless you delve into the particulars, and in this instance both pitchers will be throwing you, and opposing hitters, a curve.
There was a discussion of Morton’s 2017 emergence here last week, and his confidence should only grow based on the success he has had, and the fact that the team behind him will extend into October. Now time for Cobb, who brings more value than a 9-6/3.46 ordinarily would because some key market segments may be off a tick in their ratings, expecting him to fall back towards a FIP of 4.22 and xFIP of 4.47. But there is a plot twist here, and indeed like Morton that twist is a curve.
Cobb has finally worked his way back to full health after missing all of 2015, and most of 2016, and if you only looked at the bottom line you might suspect that he is basically the same guy now that he was in the past –
Why wouldn’t you sign off on that, it looks so easy? But it is a different pitcher putting up those numbers, and I believe it may also explain why his run prevention has profiled better than the advanced metrics say that it should. Cobb has worked around the rebuilding of his career by retooling his arsenal, in this case the use of his curveball. Let’s look at the usage before the injury cycle, and for 2017 –
Alex Cobb Curveball%
That is a significant increase, and it is his confidence in that offering, making him absolutely a pitcher, and not a thrower, that I believe helps to explain why he has out-performed some of the metrics. It is the ability to keep hitters off-balance that has made him effective at generating contact outs, in a season in which his K/9 if far below his previous standard (5.9 in 2017; vs. a career 7.3).
Why has it worked so well? Cobb has been able to throw his curve for strikes, both his BB/9 and BB% counts at career-bests. Let’s put the numbers into perspective. Cobb is #3 across MLB in terms of percentage of curveballs thrown, but look at the rather startling difference between how he has commanded his pitch, and the BB% of the others at the top of the usage charts -
Pitcher CB% BB%
McCullers 47.2 7.9
Pomeranz 35.9 9.1
Cobb 33.4 6.0
Quintana 29.5 8.7
Bauer 29.1 9.1
That gap in command matters – Cobb is around the plate far more than any of the other curveballers, and because of that I am not weighing his run prevention counts against FIP and other metrics as much as I do with other pitchers. I will make the case that throwing curves in or near the strike zone can lead to some soft contact outs from batters that are off-balance, which attaches a degree of merit to a .268 BABIP, instead of it being something that calls for regression.
Can we connect the dots tonight? I believe so, and there will be some #914 Astros/Rays First Half Under (8:10 Eastern) going into pocket, with 5 an easy find in the morning trading. I’ll call for both starters to stay on form, and make a couple of good passes through the lineup before the hitters are better able to get their timing down.
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