Metric-Based SP Rankings Update – I survived my road trip edition

(Photo by Juan DeLeon/Icon Sportswire)

Welcome back, everyone. First, I’d like to give a huge shout-out to Stephen Honovich for filling in last week!  Thanks again Stephen, awesome job.

Last week I was road-tripping down the California coast and I really must say….global warming is definitely real, y’all.  It never used to get that hot on the coast…

Anyways, I know what you’re here for.  Without further ado, here are the newly updated rankings:

Rank Name Prev Change Score IP ERA PD Score xK% K% xK%-K% BB% xSLG SLG-xSLG 1 Chris Sale 2 +1 104.6% 122.0 2.36 105.9% 33.0% 36.8% -3.8% 6.3% 0.311 -0.013 2 Jacob deGrom 3 +1 103.1% 115.1 1.79 104.0% 31.3% 31.2% 0.1% 6.4% 0.319 -0.022 3 Max Scherzer 1 -2 102.6% 127.2 2.33 107.6% 33.8% 35.4% -1.6% 6.4% 0.349 -0.016 4 Trevor Bauer 5 +1 96.7% 129.1 2.30 92.6% 28.2% 31.8% -3.7% 7.8% 0.328 -0.028 5 Justin Verlander 7 +2 96.7% 131.2 2.05 90.6% 26.6% 31.6% -5.1% 4.7% 0.315 -0.001 6 Patrick Corbin 4 -2 96.0% 116.1 3.09 100.7% 30.9% 31.3% -0.4% 7.3% 0.391 -0.058 7 Charlie Morton 6 -1 95.8% 108.0 2.83 91.5% 28.3% 31.5% -3.3% 9.6% 0.332 -0.005 8 Aaron Nola 8 0 95.1% 123.0 2.27 87.8% 24.9% 26.4% -1.5% 7.1% 0.317 -0.034 9 Lance McCullers Jr. 14 +5 93.5% 108.1 3.41 93.6% 28.9% 27.1% 1.8% 8.7% 0.377 -0.033 10 Blake Snell 9 -1 93.4% 116.0 2.09 92.3% 29.2% 28.8% 0.4% 9.6% 0.370 -0.048 11 Gerrit Cole 13 +2 92.5% 122.2 2.57 92.7% 28.7% 35.3% -6.6% 8.6% 0.385 -0.066 12 James Paxton 12 0 92.1% 118.2 3.49 93.6% 27.7% 32.4% -4.8% 6.9% 0.396 -0.036 13 Jon Gray 11 -2 92.0% 92.0 5.77 91.1% 28.8% 28.9% -0.1% 7.0% 0.380 0.075 14 Luis Severino 10 -4 91.1% 123.1 2.12 90.0% 26.1% 29.8% -3.8% 6.5% 0.386 -0.091 15 Carlos Carrasco 15 0 90.1% 96.2 4.28 94.7% 27.5% 25.9% 1.6% 5.5% 0.430 -0.026 16 Tyler Anderson 22 +6 89.3% 107.2 3.76 83.9% 24.7% 23.0% 1.7% 8.3% 0.369 0.046 17 Eduardo Rodriguez 25 +8 88.4% 99.1 3.62 83.8% 23.6% 24.7% -1.2% 7.5% 0.380 -0.010 18 Kyle Gibson 28 +10 88.2% 107.2 3.59 86.4% 25.3% 23.2% 2.1% 10.2% 0.400 -0.035 19 Jose Berrios 16 -3 88.1% 121.1 3.41 85.8% 23.9% 25.3% -1.5% 5.4% 0.397 -0.024 20 Tyler Skaggs 20 0 88.0% 92.0 2.64 85.6% 24.5% 26.4% -1.9% 7.1% 0.397 -0.029 21 Mike Clevinger 23 +2 87.3% 116.0 3.34 84.8% 24.4% 23.3% 1.1% 8.3% 0.401 -0.037 22 Sean Newcomb 17 -5 87.1% 99.1 3.44 76.9% 22.3% 23.0% -0.7% 11.8% 0.351 -0.006 23 Alex Wood 24 1 86.8% 99.2 3.88 87.1% 23.2% 21.5% 1.7% 4.4% 0.423 -0.030 24 Mike Foltynewicz 18 -6 86.4% 95.0 2.37 78.1% 23.1% 29.4% -6.4% 10.3% 0.369 -0.053 25 CC Sabathia 19 -6 86.3% 94.1 3.34 80.8% 22.1% 18.4% 3.7% 6.6% 0.388 0.028 26 Luis Castillo 26 0 86.3% 98.1 5.58 94.9% 29.0% 22.0% 7.0% 8.2% 0.482 -0.013 27 Corey Kluber 27 0 86.0% 126.1 2.49 82.2% 22.4% 25.6% -3.3% 3.1% 0.401 -0.055 28 Andrew Heaney [UR] [N/A] 85.9% 96.0 3.84 86.5% 25.3% 24.1% 1.2% 7.3% 0.431 -0.040 29 Zack Wheeler 31 +2 85.6% 99.2 4.42 82.5% 23.0% 23.1% -0.2% 8.9% 0.408 -0.048 30 Jameson Taillon 33 +3 85.5% 100.0 4.05 78.7% 21.2% 22.2% -1.0% 6.7% 0.385 0.006 31 Matt Boyd [UR] [N/A] 84.9% 98.1 4.76 76.0% 21.5% 21.1% 0.4% 8.7% 0.375 0.000 32 Dylan Bundy 29 -3 84.6% 99.1 4.08 93.2% 27.0% 26.3% 0.7% 7.2% 0.493 -0.042 33 Dallas Keuchel 39 +6 83.3% 116.1 3.95 73.6% 18.7% 17.8% 0.9% 6.4% 0.380 0.023 34 Zack Greinke 35 +1 83.3% 114.0 3.39 86.6% 23.9% 25.0% -1.2% 4.9% 0.467 -0.052 35 Miles Mikolas 36 +1 83.1% 115.1 2.65 75.1% 17.5% 17.6% -0.1% 3.9% 0.393 -0.070 36 J.A. Happ 34 -2 82.9% 105.1 4.44 76.7% 21.3% 26.3% -5.0% 7.8% 0.406 -0.018 37 Cole Hamels 37 0 82.7% 103.0 4.28 88.8% 25.8% 23.5% 2.3% 8.7% 0.489 -0.019 38 German Marquez 40 +2 82.7% 97.0 4.92 74.5% 21.3% 23.0% -1.7% 8.2% 0.394 0.060 39 Michael Fulmer 48 +9 82.7% 107.1 4.11 82.0% 22.2% 20.4% 1.8% 8.1% 0.444 -0.049 40 Zack Godley 51 +11 82.6% 98.1 4.85 83.0% 25.0% 22.3% 2.7% 11.5% 0.452 -0.035 41 Julio Teheran 54 +13 82.5% 99.1 4.26 82.2% 24.6% 22.2% 2.4% 11.6% 0.448 -0.031 42 Gio Gonzalez 38 -4 82.2% 95.2 3.76 75.7% 21.8% 21.5% 0.3% 11.2% 0.408 -0.010 43 Kevin Gausman 43 0 81.9% 107.1 4.11 84.5% 24.1% 20.8% 3.3% 5.7% 0.471 -0.006 44 Kyle Freeland 46 +2 81.5% 110.1 3.18 73.1% 19.1% 19.4% -0.4% 8.2% 0.401 -0.021 45 Tyler Mahle 45 0 81.3% 98.1 3.66 79.1% 22.5% 22.9% -0.5% 9.7% 0.444 -0.002 46 Rick Porcello 42 -4 81.1% 118.0 3.58 73.2% 18.3% 22.7% -4.4% 5.4% 0.406 -0.033 47 Marco Gonzales 50 +3 81.1% 106.1 3.64 78.4% 19.8% 21.6% -1.9% 5.1% 0.442 -0.038 48 Jake Odorizzi 52 +4 80.9% 96.2 4.28 81.6% 23.4% 24.2% -0.9% 10.5% 0.465 -0.008 49 Junior Guerra [UR] [N/A] 80.3% 93.2 2.79 74.2% 20.8% 23.5% -2.7% 9.4% 0.424 -0.062 50 Clayton Richard 41 -9 79.9% 118.0 4.50 74.9% 20.3% 17.7% 2.6% 8.4% 0.434 -0.035 51 Tyson Ross 49 -2 79.7% 102.0 4.41 75.3% 20.5% 21.2% -0.7% 9.2% 0.439 -0.026 52 Jose Urena 53 +1 79.7% 104.2 4.13 72.9% 18.3% 19.9% -1.7% 5.6% 0.423 -0.031 53 Jake Arrieta 55 +2 79.6% 96.0 3.47 67.9% 15.9% 17.3% -1.5% 7.5% 0.392 -0.015 54 Jhoulys Chacin 56 +2 78.9% 109.2 3.78 71.5% 20.1% 18.4% 1.7% 10.1% 0.424 -0.065 55 Luke Weaver 59 +4 78.1% 97.0 4.92 73.3% 20.6% 21.2% -0.7% 8.1% 0.447 -0.036 56 Kyle Hendricks 68 +12 77.9% 105.1 3.93 75.1% 20.0% 18.4% 1.6% 7.1% 0.462 -0.052 57 Steven Matz 58 +1 77.9% 89.2 3.31 63.8% 18.4% 21.4% -3.0% 9.3% 0.387 0.014 58 Sean Manaea 60 +2 77.3% 117.2 3.44 77.7% 20.1% 17.2% 2.9% 4.8% 0.488 -0.115 59 David Price 61 +2 77.2% 101.1 4.44 71.8% 18.6% 23.8% -5.3% 8.0% 0.449 -0.009 60 Jose Quintana 62 +2 76.8% 97.2 3.96 68.5% 18.1% 20.8% -2.7% 10.7% 0.433 -0.015 61 James Shields 71 +10 76.5% 118.2 4.47 74.8% 20.8% 16.9% 3.9% 9.0% 0.479 -0.088 62 Derek Holland 77 +15 76.1% 95.0 4.17 74.4% 21.2% 22.6% -1.5% 9.2% 0.481 -0.043 63 Chase Anderson 66 +3 76.1% 99.1 3.81 71.2% 19.0% 19.2% -0.2% 9.5% 0.460 -0.067 64 Tanner Roark 57 -7 75.9% 109.1 4.61 71.3% 18.8% 19.8% -1.1% 8.7% 0.463 -0.043 65 Chad Bettis 65 0 75.7% 95.1 5.10 71.0% 19.4% 16.9% 2.5% 9.3% 0.464 -0.010 66 Jakob Junis 69 +3 75.6% 101.2 5.13 75.5% 19.8% 20.9% -1.2% 6.4% 0.495 -0.008 67 Reynaldo Lopez 67 0 74.6% 105.0 3.77 67.3% 18.4% 16.6% 1.8% 10.4% 0.454 -0.065 68 Danny Duffy 76 +8 74.5% 106.2 4.89 75.9% 21.6% 20.0% 1.6% 10.6% 0.513 -0.066 69 Felix Hernandez 70 +1 74.4% 105.1 5.13 70.8% 18.0% 18.8% -0.8% 7.8% 0.480 -0.039 70 Mike Fiers 64 -6 74.2% 98.2 3.65 71.8% 18.5% 17.8% 0.7% 5.1% 0.490 -0.035 71 Trevor Williams 73 +2 73.5% 94.0 4.60 67.0% 16.8% 17.3% -0.5% 8.1% 0.466 -0.052 72 Jon Lester 75 +3 73.3% 106.1 2.45 68.8% 18.7% 18.6% 0.1% 8.7% 0.481 -0.121 73 Ivan Nova 74 +1 72.3% 98.0 4.50 74.0% 19.4% 18.2% 1.2% 4.1% 0.529 -0.029 74 Mike Minor 78 +4 72.2% 96.2 4.56 75.0% 20.3% 19.4% 0.8% 5.5% 0.537 -0.060 75 Sal Romano 79 +4 70.3% 102.1 5.28 64.9% 16.2% 16.4% -0.2% 8.9% 0.495 -0.020 76 Chris Stratton 82 +6 70.3% 96.2 4.93 67.8% 17.9% 17.6% 0.3% 8.7% 0.515 -0.062 77 Ian Kennedy 81 +4 69.9% 94.2 5.13 69.1% 17.4% 20.9% -3.5% 8.2% 0.529 -0.044 78 Mike Leake 83 +5 69.7% 115.2 4.36 70.5% 16.5% 14.5% 2.0% 5.5% 0.540 -0.083 79 Andrew Cashner 86 +7 69.5% 100.2 4.56 62.8% 15.7% 18.3% -2.6% 9.7% 0.492 -0.003 80 Lucas Giolito 84 +4 68.6% 97.0 6.59 62.9% 17.5% 12.9% 4.6% 12.9% 0.505 -0.040 81 Jason Hammel 80 -1 67.9% 102.1 6.16 72.6% 18.0% 14.0% 4.0% 6.6% 0.579 -0.085 82 Bartolo Colon 88 +6 63.8% 95.2 4.80 61.1% 11.8% 13.3% -1.5% 3.8% 0.557 -0.048

For Reference (content continues below):

1.  “PD Score” is short for plate discipline score, a combined metric of strikeout ability weighted as:  3 points O-Swing%, 3 points Contact%, 3 points SwStr%, 1 point F-Strike%.
2.  “Score” is a combined metric weighted equally between PD Score and xSLG.
3.  For both luck indication columns (xK%-K% and SLG-xSLG) positive numbers indicate bad luck so far (likely to regress positively) while negative numbers indicate good luck so far (likely to regress negatively).  A higher SLG value is bad for pitchers, and I wanted it to be easy to remember: Positive Numbers = Good Outlook.
4.  IP, ERA, K%, BB%, and SLG are not included in the calculations, these are only included in the table for reference.
5.  For any newcomers, to understand the concepts behind these numbers I would recommend reading my introduction piece.
6.  Data is current through July 10, 2018

 

Two weeks ago, I wrote that the trio of Scherzer, Sale and DeGrom had clearly separated themselves from the pack, and formed their own ultra-elite tier at the top of this year’s rankings.  Their places have switched around a bit within that group, with Sale currently leading.  But overall that tier is still holding up, and there is still a sizable dropoff to the 4th ranked pitcher.

Otherwise in the top ten, there haven’t been many huge changes, with the exception of…

 

Lance McCullers Jr. (SP, Houston Astros)

McCullers was a big mover in the rankings the past two weeks, jumping a total of seven spots since my last update.  His last four starts have been simply phenomenal, posting a Contact% of just 61%, and a Swinging Strike rate over 18 in those four starts.  It doesn’t get a whole lot better than that.  On the flip side, two of those starts were against the Royals, who as of Wednesday rate as the worst offense in MLB, so a few grains of salt are required.  But dominating bad teams is exactly what good pitchers are supposed to do.

Everyone knows by now, McCullers has an amazing curveball.  For his career, it’s by far his best pitch.  But this year?  Actually his changeup is the better-performing pitch, pretty much any way you look at it – whiff rate, wRC+ allowed, or pitch value.

Another thing you may not know about McCullers is that for his career, he has demonstrated a significant reverse platoon split, i.e. he had been better vs. lefties than righties.  This year though, he has closed the gap in his platoon splits noticeably.  It’s a small sample to be trusting platoon splits, but I think the success can at least partially be explained by better location on his changeup.  In 2017, here were all of his changeup locations:

As you can see, all his changeup were basically thrown to the same location.  For lefties, that would be low & away, which is perfect.  But this chart includes the righties as well – and he is throwing to the exact same place for them.  Low & inside is simply a more hittable location, and batters had little reason to look anyplace else.  This could help explain why McCullers allowed an wRC+ of 195 on the changeup last year – it’s just too predictable being thrown in the same location every time.

Now here are his changeups this year:

As you can see, this season his changeups are dispersed across a much wider area at the bottom of the zone, not just one corner.  That indicates he’s becoming more comfortable throwing the changeup to righties, and keeping them guessing on the location much better than last year.  The movement readings on his changeup are very similar to last year, so the location seems likely to be a big factor in the huge disparity between results from year to year.

Another thing you might notice is his increasing usage of that changeup.  At this point in the season he’s thrown 10 fewer IP than last season, but has already thrown 66 more changeups.  The emergence of his changeup as a real weapon this year, thanks to better location and increased usage, seems like the big story so far.  His changeup now rates as top 5 in MLB in terms of pitch value (both overall and per 100 thrown) and is allowing an wRC+ of just nine.  As always with McCullers, the talent isn’t really the question so much as his health, which always needs to be considered as part of his overall value.  But it’s hard not to love how he’s pitching right now.

[Game Update] – the above was written prior to McCullers start on Wednesday.  As is tradition, as soon as I start praising someone, they go and throw a clunker.  Yesterday’s game was fairly bad but as long as he’s not injured or anything, it doesn’t change much.  Bad starts happen.

 

Kyle Gibson (SP, Minnesota Twins)

Like McCullers, Gibson has shot up the rankings recently thanks in part to some weakness in his schedule.  In particular, his completely dominant game vs. Baltimore on July 7th is responsible for a lot of his movement.  The Orioles are currently the second worst offense in MLB, barely better than the Royals.  In that game the Orioles only made contact with 55% of his pitches, which is really outstanding even against a bad team.

That all being said, Gibson has certainly been a different and much more valuable pitcher this year than previously.  The past two years, his full-season ERAs were over five, so he really wasn’t on a lot of radars coming into 2018, and no one would have expected to see him on any top 20 list.  He actually did pitch quite well towards the end of 2017, but those numbers disappear in his full-season line.  This came as the result of some adjustments to his slider he made late in the season, which Nick covered in his Fangraphs profile for Gibson this year.  This year, the slider has continued its success, with a contact rate under 50, which is really excellent. It’s also allowing an wRC+ of just 22 (compared to 98 last year).  So it seems that adjustment he made to his slider late last year has definitely stuck.

This brings me to an interesting phenomenon when it comes to plate discipline metrics.  In my very first piece, I looked at several pitchers entire careers trying to find guys who could consistently beat the metrics.  One pattern that emerged in that exercise was the fact that the pitchers we think of having “good stuff”, like Clayton Kershaw, were the only guys who showed that ability consistently.  And I think this is related to the ability to kick it up a notch when a strikeout is most needed, which is another way of saying they have a dominant “out pitch” (or several, in Kershaw’s case).  Again, just a reminder for context, even Kershaw only beats the metrics by about 4-5% – that’s why I use that as the “margin of error” when talking about expected strikeout rates.

To tie this idea back to Gibson, let’s look at his career numbers:

Season xK% K% xK%-K% 2013 18.15% 12.20% 5.95% 2014 18.90% 14.10% 4.80% 2015 21.00% 17.70% 3.30% 2016 21.25% 15.90% 5.35% 2017 21.50% 17.50% 4.00% 2018 25.10% 23.20% 1.90%

In five previous seasons before he developed the slider into the weapon it is today, he under-performed his K rate every single year, often quite substantially.  This year he has not only increased his actual strikeout rate by six percent, he’s also much closer to his plate-discipline-expected strikeout rate than ever before.  This seems to fit the idea that possessing a bonafide out pitch can at least partially explain why some pitchers are better at beating the metrics than others.

 

Moving on, here are the metrics for the non-qualified SP (10 IP minimum).  Scroll past the table for more analysis.

Name Team Score IP ERA PD Score xK% K% xK%-K% xSLG SLG-xSLG Matt Strahm Padres 104.8% 13.1 1.35 103.1% 31.1% 35.3% -4.2% 0.290 -0.061 Freddy Peralta Brewers 100.3% 33.2 2.14 95.2% 30.4% 36.2% -5.9% 0.298 -0.084 Noah Syndergaard Mets 98.8% 64.2 3.06 99.1% 30.6% 28.3% 2.3% 0.343 0.021 Ryne Stanek Rays 97.9% 16.2 1.08 101.9% 33.8% 32.8% 1.0% 0.374 -0.216 Shohei Ohtani Angels 96.9% 49.1 3.10 99.1% 34.0% 30.5% 3.5% 0.368 -0.048 Jonathan Loaisiga Yankees 95.4% 18.0 3.00 92.0% 26.4% 28.4% -2.1% 0.342 -0.009 Domingo German Yankees 95.3% 59.1 5.46 100.2% 30.9% 26.4% 4.5% 0.397 0.066 Felix Pena Angels 94.9% 19.2 2.75 95.8% 28.6% 30.1% -1.6% 0.373 -0.057 Yefry Ramirez Orioles 93.3% 13.1 5.40 96.4% 30.2% 23.0% 7.2% 0.399 0.035 Kenta Maeda Dodgers 93.0% 79.2 3.28 93.4% 28.4% 28.6% -0.2% 0.383 -0.020 Ross Stripling Dodgers 92.8% 74.0 2.55 84.9% 23.3% 29.1% -5.9% 0.329 0.070 Max Fried Braves 91.9% 14.2 3.07 83.7% 27.8% 29.5% -1.8% 0.333 -0.006 Jack Flaherty Cardinals 90.4% 70.0 3.34 85.5% 26.7% 28.4% -1.8% 0.364 0.000 Masahiro Tanaka Yankees 90.0% 77.0 4.68 98.0% 28.9% 24.7% 4.2% 0.453 -0.005 Robbie Ray Diamondbacks 89.1% 43.0 5.23 94.3% 29.5% 34.4% -4.9% 0.440 0.032 Trevor Cahill Athletics 89.1% 48.2 2.77 92.2% 28.5% 25.0% 3.5% 0.427 -0.074 Carlos Martinez Cardinals 89.0% 85.2 3.05 77.2% 21.3% 22.0% -0.8% 0.328 -0.022 Walker Buehler Dodgers 88.8% 51.1 2.63 72.4% 19.1% 26.7% -7.6% 0.298 -0.025 John Gant Cardinals 88.6% 33.1 4.32 84.0% 24.7% 21.4% 3.3% 0.379 -0.054 Vince Velasquez Phillies 88.0% 88.1 4.69 82.4% 25.1% 28.5% -3.5% 0.376 0.049 Joe Musgrove Pirates 87.9% 45.1 3.77 82.6% 21.6% 22.6% -1.0% 0.378 0.025 Jordan Montgomery Yankees 87.5% 27.1 3.62 79.9% 21.5% 19.8% 1.7% 0.366 -0.010 Johnny Cueto Giants 87.2% 37.0 1.95 76.8% 21.8% 19.7% 2.1% 0.349 -0.041 Hyun-Jin Ryu Dodgers 87.1% 29.2 2.12 79.3% 24.8% 31.3% -6.5% 0.367 -0.059 Clayton Kershaw Dodgers 86.1% 69.0 2.61 81.5% 22.5% 25.5% -3.0% 0.396 -0.037 Zach Eflin Phillies 85.7% 68.2 3.15 79.5% 22.1% 24.0% -1.9% 0.387 -0.011 Nick Pivetta Phillies 85.6% 88.2 4.67 84.9% 24.9% 27.4% -2.6% 0.425 0.006 Wilmer Font Rays 84.5% 21.0 1.71 70.7% 20.5% 22.0% -1.6% 0.345 -0.075 Garrett Richards Angels 84.3% 76.1 3.66 81.9% 25.1% 26.9% -1.8% 0.422 -0.040 Shane Bieber Indians 84.3% 36.1 3.47 85.3% 24.4% 23.1% 1.3% 0.445 0.014 Mike Montgomery Cubs 84.2% 45.2 2.76 79.1% 21.4% 17.0% 4.4% 0.405 -0.090 Austin Bibens-Dirkx Rangers 84.1% 34.0 3.71 82.2% 21.2% 17.9% 3.3% 0.427 -0.019 Seth Lugo Mets 83.9% 23.0 3.52 77.3% 21.6% 26.5% -4.9% 0.397 0.007 Chris Archer Rays 83.7% 79.2 4.41 86.8% 26.1% 23.3% 2.8% 0.462 -0.042 Stephen Strasburg Nationals 83.5% 80.2 3.46 85.1% 24.5% 29.1% -4.6% 0.454 -0.055 Ryan Borucki Blue Jays 83.5% 20.0 2.25 75.1% 19.0% 19.8% -0.9% 0.388 -0.068 Lance Lynn Twins 83.4% 86.1 5.21 77.4% 22.2% 21.5% 0.6% 0.404 0.003 Caleb Smith Marlins 83.3% 77.1 4.19 82.9% 24.3% 27.0% -2.7% 0.442 -0.054 Anibal Sanchez Braves 83.3% 56.2 2.86 74.9% 19.6% 23.8% -4.2% 0.389 -0.021 Nathan Eovaldi Rays 83.2% 48.1 3.35 81.1% 20.3% 24.3% -4.0% 0.432 -0.045 Sam Gaviglio Blue Jays 83.1% 47.2 3.97 81.0% 21.9% 22.3% -0.4% 0.432 0.005 Madison Bumgarner Giants 83.1% 43.2 3.09 75.9% 19.6% 19.6% 0.0% 0.398 -0.018 Nick Kingham Pirates 82.9% 44.1 4.26 86.7% 25.6% 22.2% 3.4% 0.473 -0.039 Yu Darvish Cubs 82.7% 40.0 4.95 78.2% 24.1% 27.2% -3.2% 0.418 0.007 Jordan Zimmermann Tigers 82.7% 56.1 3.51 81.0% 21.4% 24.8% -3.5% 0.437 -0.057 Dereck Rodriguez Giants 82.4% 40.1 3.12 73.0% 19.3% 17.8% 1.5% 0.388 0.018 Paul Blackburn Athletics 81.9% 27.2 7.16 73.5% 18.0% 16.0% 2.0% 0.398 0.052 Brent Suter Brewers 81.2% 86.2 4.67 79.6% 21.2% 19.9% 1.3% 0.448 -0.009 Fernando Romero Twins 81.0% 51.1 4.38 79.0% 22.8% 19.6% 3.2% 0.446 -0.037 Sonny Gray Yankees 81.0% 84.2 5.85 76.6% 22.2% 20.0% 2.2% 0.431 0.017 Edwin Jackson Athletics 80.9% 18.1 2.45 70.7% 18.3% 21.6% -3.3% 0.393 -0.055 Caleb Ferguson Dodgers 80.8% 10.2 7.59 78.9% 26.7% 25.0% 1.7% 0.449 -0.049 Brad Keller Royals 80.5% 38.1 2.82 69.0% 18.2% 13.9% 4.3% 0.387 -0.096 Nick Tropeano Angels 79.8% 54.0 4.83 83.7% 25.5% 19.6% 5.9% 0.494 -0.019 Michael Soroka Braves 79.8% 25.2 3.51 78.7% 22.0% 18.6% 3.4% 0.461 -0.048 Joey Lucchesi Padres 79.7% 63.1 3.27 75.7% 22.7% 25.0% -2.4% 0.442 -0.051 Marcus Stroman Blue Jays 79.1% 61.0 5.90 74.7% 21.2% 17.8% 3.4% 0.443 -0.032 Jordan Lyles Padres 78.8% 47.0 4.79 72.6% 17.9% 19.9% -2.1% 0.433 0.051 Chris Bassitt Athletics 78.8% 27.0 3.00 64.2% 14.8% 20.0% -5.2% 0.377 -0.078 Yonny Chirinos Rays 78.3% 22.2 4.37 75.9% 20.1% 21.0% -0.9% 0.462 -0.043 Blaine Hardy Tigers 78.1% 43.2 3.71 70.1% 17.1% 16.6% 0.5% 0.426 0.005 Jason Vargas Mets 77.9% 37.2 8.60 82.2% 22.9% 17.8% 5.1% 0.509 0.104 Aaron Sanchez Blue Jays 77.9% 79.2 4.52 76.6% 22.5% 18.7% 3.8% 0.472 -0.085 Wei-Yin Chen Marlins 77.9% 66.0 6.14 68.9% 17.2% 16.5% 0.7% 0.421 0.071 Matt Andriese Rays 77.9% 11.1 3.18 75.0% 19.7% 19.2% 0.5% 0.462 -0.121 Francisco Liriano Tigers 77.7% 76.0 4.74 81.6% 24.4% 18.7% 5.7% 0.508 -0.093 Tyler Chatwood Cubs 77.6% 79.0 5.01 67.1% 19.5% 20.0% -0.5% 0.413 -0.054 Ryan Yarbrough Rays 77.5% 23.2 5.32 68.3% 16.8% 19.4% -2.7% 0.422 -0.003 Wade LeBlanc Mariners 77.3% 71.1 3.15 77.9% 19.0% 17.9% 1.1% 0.489 -0.088 Carlos Rodon White Sox 77.2% 35.2 4.29 69.3% 18.1% 18.2% -0.1% 0.433 -0.018 Trevor Richards Marlins 77.0% 56.2 5.24 70.4% 18.4% 20.8% -2.5% 0.442 -0.006 Pablo Lopez Marlins 76.6% 17.0 6.35 85.0% 20.6% 19.4% 1.2% 0.545 -0.083 Hector Velazquez Red Sox 76.6% 13.2 2.63 86.6% 22.2% 21.1% 1.1% 0.556 -0.084 Jeremy Hellickson Nationals 76.4% 57.0 3.47 72.9% 18.9% 18.8% 0.1% 0.468 -0.059 Michael Wacha Cardinals 76.3% 84.1 3.20 72.9% 21.0% 20.0% 0.9% 0.468 -0.124 Jaime Barria Angels 76.2% 61.0 3.39 81.7% 23.3% 18.7% 4.6% 0.529 -0.105 Marco Estrada Blue Jays 75.4% 89.2 4.72 75.8% 20.6% 18.6% 2.0% 0.500 -0.004 Eric Lauer Padres 75.2% 75.2 4.40 67.5% 18.0% 18.7% -0.7% 0.448 0.027 Anthony DeSclafani Reds 74.9% 40.2 4.43 68.2% 17.4% 19.1% -1.7% 0.456 0.021 Clay Buchholz Diamondbacks 74.9% 38.2 2.56 74.6% 18.9% 20.3% -1.4% 0.499 -0.126 Andrew Suarez Giants 74.8% 84.0 3.75 66.5% 16.2% 22.5% -6.3% 0.446 -0.030 Luis Perdomo Padres 74.4% 26.2 7.09 64.0% 16.9% 14.8% 2.1% 0.435 0.047 Matt Harvey – – – 74.2% 80.1 4.37 66.6% 17.3% 17.9% -0.6% 0.455 -0.029 Frankie Montas Athletics 74.1% 48.1 3.35 64.7% 16.5% 14.6% 1.9% 0.443 -0.029 Matt Moore Rangers 74.1% 55.0 8.02 75.2% 20.1% 14.7% 5.4% 0.513 0.056 Andrew Triggs Athletics 73.0% 41.1 5.23 75.9% 21.4% 23.6% -2.3% 0.533 -0.120 Adam Wainwright Cardinals 72.9% 18.0 4.00 55.9% 14.0% 17.1% -3.1% 0.400 0.035 David Hess Orioles 72.7% 47.0 5.94 69.3% 16.7% 12.4% 4.3% 0.492 0.016 Steven Wright Red Sox 72.7% 24.0 4.13 67.0% 19.0% 16.8% 2.2% 0.478 -0.122 Brandon McCarthy Braves 72.6% 78.2 4.92 65.9% 15.7% 19.2% -3.5% 0.471 0.027 Zach Davies Brewers 72.3% 43.0 5.23 69.1% 18.7% 16.3% 2.4% 0.497 -0.003 Brandon Woodruff Brewers 72.2% 15.2 6.32 65.8% 19.2% 18.1% 1.1% 0.476 -0.083 Drew Pomeranz Red Sox 72.1% 37.0 6.81 65.2% 16.7% 20.8% -4.2% 0.473 0.070 Dylan Covey White Sox 72.1% 55.1 5.69 63.4% 16.2% 16.9% -0.7% 0.462 -0.056 Dan Straily Marlins 71.6% 65.1 4.55 74.9% 21.3% 18.7% 2.6% 0.544 -0.105 Jeff Samardzija Giants 71.0% 40.2 6.42 69.2% 18.0% 15.3% 2.7% 0.514 -0.079 Jaime Garcia Blue Jays 71.0% 61.1 6.16 68.1% 19.0% 19.9% -1.0% 0.508 0.004 Ty Blach Giants 70.9% 60.2 4.90 60.7% 14.7% 11.1% 3.6% 0.460 -0.047 Rich Hill Dodgers 70.7% 54.1 4.64 68.9% 17.4% 24.4% -7.1% 0.517 -0.045 Jake Faria Rays 70.4% 47.2 5.48 68.1% 19.0% 18.2% 0.7% 0.516 -0.093 Dillon Peters Marlins 70.0% 24.2 5.84 62.0% 16.3% 14.4% 1.9% 0.480 -0.011 Jefry Rodriguez Nationals 69.7% 14.0 9.64 77.6% 20.0% 18.8% 1.2% 0.588 0.055 Elieser Hernandez Marlins 69.6% 22.0 4.50 71.6% 21.2% 18.7% 2.5% 0.549 0.011 Corey Oswalt Mets 69.6% 12.2 7.82 64.0% 13.5% 18.2% -4.8% 0.499 -0.030 Chad Kuhl Pirates 69.0% 85.0 4.55 69.8% 20.5% 21.7% -1.2% 0.546 -0.083 Eric Skoglund Royals 68.8% 49.2 6.70 70.3% 17.3% 18.0% -0.7% 0.551 -0.021 Daniel Mengden Athletics 68.8% 90.2 4.47 68.5% 16.7% 14.5% 2.2% 0.540 -0.097 Alex Cobb Orioles 68.7% 86.1 6.67 64.9% 15.5% 15.2% 0.3% 0.516 0.036 Matt Wisler Braves 68.7% 17.1 3.63 73.6% 20.7% 18.6% 2.1% 0.575 -0.160 Adam Plutko Indians 68.2% 34.2 4.67 71.6% 17.3% 16.9% 0.4% 0.568 -0.034 Brandon Finnegan Reds 68.0% 20.2 7.40 63.0% 16.0% 13.6% 2.4% 0.513 0.040 Yovani Gallardo Rangers 67.9% 28.0 6.75 59.7% 13.2% 15.0% -1.8% 0.493 -0.011 Erick Fedde Nationals 67.4% 28.0 5.79 68.7% 17.9% 15.7% 2.2% 0.559 -0.009 Ben Lively Phillies 67.2% 23.2 6.85 62.8% 17.9% 19.1% -1.3% 0.522 0.023 Kendall Graveman Athletics 67.0% 34.1 7.60 67.6% 17.1% 17.1% 0.0% 0.557 -0.015 John Lamb Angels 66.7% 10.0 7.20 72.3% 17.8% 22.0% -4.3% 0.593 0.124 Doug Fister Rangers 66.4% 66.0 4.50 55.9% 11.8% 13.8% -2.0% 0.487 -0.031 Brian Johnson Red Sox 66.0% 14.2 2.45 53.4% 11.7% 14.1% -2.4% 0.476 -0.069 Brett Anderson Athletics 66.0% 20.1 5.75 63.5% 16.4% 11.8% 4.6% 0.544 -0.038 Shelby Miller Diamondbacks 65.3% 14.0 9.00 67.5% 17.6% 26.9% -9.3% 0.579 0.044 Antonio Senzatela Rockies 65.2% 13.0 4.15 58.2% 13.9% 11.8% 2.1% 0.519 -0.215 Daniel Gossett Athletics 64.9% 24.1 5.18 66.2% 15.5% 11.8% 3.7% 0.576 -0.081 Joe Biagini Blue Jays 64.9% 18.2 7.71 65.9% 16.7% 14.4% 2.3% 0.574 -0.080 Steven Brault Pirates 63.8% 26.0 5.54 69.2% 20.0% 13.4% 6.6% 0.611 -0.213 Taijuan Walker Diamondbacks 62.7% 13.0 3.46 57.6% 15.1% 16.1% -1.1% 0.548 -0.156 Homer Bailey Reds 62.1% 62.0 6.68 64.2% 15.8% 13.0% 2.8% 0.600 -0.036 Hector Santiago White Sox 61.1% 32.1 6.12 62.0% 16.5% 15.9% 0.6% 0.598 -0.027 Jarlin Garcia Marlins 61.0% 33.0 3.55 65.1% 18.0% 16.7% 1.3% 0.620 -0.222 Bryan Mitchell Padres 59.3% 32.0 6.47 47.1% 11.8% 10.4% 1.4% 0.523 -0.027 Ryan Carpenter Tigers 57.4% 12.0 6.75 58.5% 14.9% 10.7% 4.2% 0.624 -0.047 Matt Koch Diamondbacks 56.9% 69.2 4.52 60.7% 13.5% 12.1% 1.4% 0.646 -0.140 Miguel Gonzalez White Sox 56.8% 12.1 12.41 66.3% 15.5% 7.6% 7.9% 0.684 0.099 Josh Tomlin Indians 55.9% 30.0 8.10 73.8% 19.1% 12.9% 6.2% 0.746 -0.019 Martin Perez Rangers 55.1% 22.1 9.67 51.8% 11.6% 10.9% 0.6% 0.610 0.060 Carson Fulmer White Sox 55.0% 31.0 8.13 56.5% 14.6% 16.6% -2.1% 0.643 -0.139 Chris Tillman Orioles 51.6% 26.2 10.46 49.4% 11.9% 9.5% 2.4% 0.641 0.011

 

 

Matt Strahm (P, San Diego Padres)

Strahm has been high on this list ever since I started splitting out the non-qualified SP to a separate table, but I have been hesitant to write about him so far.  The reason for his high ranking is due to his small sample size and peculiar role.  Basically he is a reliever, but has “opened” a handful of starts, which is a new phenomenon in MLB this year.  For the uninitiated, an “opener” is a reliever who pitches the first couple innings of the game, typically in lieu of a 5th starter.  Technically that still counts as “starting” those games, even if he only pitches 2-3 innings.  Strahm has also changed roles a couple times, bouncing back between opening and a more typical middle relief role.  He’s pitched over 30 innings total, but only 13 as a “starter”.  The table above only includes his innings as a starter, but over his complete body of work, he grades out much, much lower.  For whatever reason he has been much more effective in that “opener” role (FIP as a reliever = 5).  So that is certainly one reason to pump the brakes a bit upon seeing that score of 104.

Even if we were to discard his work as a reliever and focus on those 13 starting innings (which we shouldn’t) I still wonder how the “opener” role affects the mindset of a pitcher compared to a regular starter.  If a guy in this role knows he only has to pitch a couple innings, are they still in the reliever mindset of throwing the ball as hard as possible?  A score of 104 for a reliever wouldn’t be that special, because relievers just have better strikeout stuff thanks to their limited workload (I adjust the score thresholds for relievers by 10 points).  So it’s likely that if the Padres did decide to stretch him out and make him a full starter, those numbers wouldn’t translate directly; we wouldn’t expect him to continue pitching that well.

Secondly, the whole “opener” thing just seems to be bad for fantasy baseball.  Being guaranteed to pitch less than five innings means wins and quality starts are impossible, and these are still very important in fantasy.  This is even worse than a middle reliever – at least those guys have a chance at nabbing a win or save here or there.  Really all he can do for your team is help with ratios and strikeouts.  On the “bright” side the last time he opened was a couple weeks ago now, having moved back to a normal bullpen role.  In either role, he’s probably not someone you want on your fantasy team, despite the high score here.

Note – basically the same logic applies to Ryne Stanek, who has taken the “opener” role from Sergio Romo in Tampa.

 

Freddy Peralta (SP, Milwaukee Brewers)

Here is a bit more straightforward one.  Peralta has worked his way to the top of the non-qualified rankings in more typical fashion; there are no role shenanigans here.  Peralta is a 22-year-old Rookie who has pitched six starts in the data, plus one Wednesday that was not included.   There are is a lot to like in the data for those six starts.  For one, he has consistently missed bats.  Even the worst of those six starts was above average in that regard, and his PD metrics look fantastic overall.  Yes, he is over-performing his K rate a bit, but even if that were to drop the full amount, 30% would still be excellent.  He has also done very well in managing contact – his xSLG near .300 is in the neighborhood of the league leaders.

There is unfortunately one big problem with Freddy Peralta, and that is right now he seems like a two pitch guy.  He basically uses his fastball 80 percent of the time, with the curveball making up the other 20%.  He does technically have a changeup, but only throws it 3% of the time, which doesn’t really count.  Two-pitch guys tend to have bad platoon splits, and hence can be a dicey proposition for starting pitchers.  It’s not uncommon for these guys to end up in the bullpen.  Even with his dominant numbers so far, he does show those concerning platoon splits.  His FIP against lefties is three times higher than against righties (3 vs 1).  He’s also managed to put up a .215 BABIP so far, which has to regress.  Going forward I see him as a great streamer pick vs. right-handed lineups, but likely not much more than that.

[Game Update] The above was written prior to Wednesday’s game.  Yesterday he was knocked around a bit by the Marlins, including giving up a HR to a lefty, while failing to miss bats at all compared to the previous six starts.  It looks like the shine is starting to wear off already.

 

Clayton Kershaw (SP, Los Angeles Dodgers)

This is looking like the year where Kershaw finally gives up his mantle as the best pitcher on the planet.  At least, if he keeps pitching like he has so far, he won’t be anywhere near the league leaders at the end of the season.  Part of it could certainly be the injuries he’s dealt with – his velocity right now is the worst in his career.  He’s been able to hold things together somehow, posting an ERA of just 2.6.  But as a Kershaw owner myself, I am very concerned.  His plate discipline metrics are way, way down.  For the past four years, his swinging strike rate has never dipped below 14%.  This year it is just 10.9%, hardly even above average.  His contact management hasn’t been elite either – the xSLG mark of .400 is only a bit above average as well.  Basically he has not been Clayton Kershaw this year.

Of course it’s very possible that he recovers from his injuries and he starts pitching like Clayton Kershaw again.  But I’m not super hopeful at the moment.  Since he returned from injury, he’s compiled four starts and they just aren’t very encouraging.  They were against fairly weak teams (3 of the 4) but he didn’t dominate those bad teams at all.  Some of the lines he produced were good, but even against the Padres he only managed a swinging strike rate of 9%.

On the flip side, he is Clayton Kershaw.  If anyone is capable of turning things around, it’s him.  I absolutely wouldn’t write him off yet.  But there’s no denying I see a selling opportunity here, if any of your league-mates assume he is 100% based on that ERA.