Weekly SP Metrics Update – Season Mid-Point Edition

(Photo by Kevin Abele/Icon Sportswire)

 

Welcome back, everyone.  We’re now almost halfway through the MLB season, a great time to look back at some of the more surprising performances so far.  With that in mind, here are the newly updated mid-season rankings, starting with the qualified SP:

Rank Name Prev Diff Score IP ERA PD Score xK% K% xK%-K% BB% xSLG SLG-xSLG 1 Max Scherzer 1 0 103.4% 114.2 2.04 108.6% 34.3% 37.1% -2.8% 6.1% 0.345 -0.029 2 Jacob deGrom 2 0 103.0% 101.1 1.69 102.5% 30.8% 31.4% -0.7% 6.7% 0.310 -0.024 3 Chris Sale 3 0 103.0% 109.0 2.56 104.4% 32.4% 35.6% -3.2% 6.5% 0.323 -0.011 4 Patrick Corbin 5 +1 96.6% 100.0 3.24 101.5% 31.0% 32.5% -1.6% 6.8% 0.389 -0.057 5 Trevor Bauer 6 +1 95.9% 107.0 2.44 93.5% 28.3% 31.8% -3.6% 7.9% 0.345 -0.035 6 Justin Verlander 4 -2 95.5% 113.2 1.82 88.9% 25.8% 31.3% -5.5% 5.3% 0.319 -0.012 7 Charlie Morton 9 +2 94.7% 95.2 2.54 91.1% 28.3% 31.0% -2.8% 9.9% 0.345 -0.011 8 Aaron Nola 7 -1 92.9% 101.1 2.58 84.6% 23.8% 25.1% -1.4% 7.3% 0.326 -0.027 9 Jon Gray 12 +3 92.8% 88.0 5.52 92.2% 29.1% 28.6% 0.5% 6.9% 0.377 0.068 10 Gerrit Cole 8 -2 92.8% 105.2 2.56 91.6% 28.4% 36.3% -8.0% 8.2% 0.374 -0.056 12 Blake Snell 13 +1 92.1% 101.1 2.31 91.7% 29.1% 28.1% 1.0% 10.0% 0.383 -0.059 11 Luis Severino 10 -1 92.1% 111.2 2.10 90.7% 26.7% 30.4% -3.8% 6.0% 0.376 -0.083 13 Carlos Carrasco 15 +2 90.6% 91.1 4.24 94.4% 27.4% 25.6% 1.8% 5.9% 0.422 -0.031 14 Jose Berrios 19 +5 90.3% 103.0 3.15 89.2% 24.9% 26.9% -2.0% 4.9% 0.391 -0.043 15 Eduardo Rodriguez 14 -1 90.2% 81.2 3.86 85.4% 24.2% 26.1% -2.0% 7.4% 0.367 0.009 16 Lance McCullers Jr. 20 +4 90.0% 94.1 3.82 89.9% 27.2% 25.7% 1.5% 9.3% 0.399 -0.027 17 James Paxton 16 -1 89.6% 103.2 3.65 90.6% 26.7% 32.0% -5.4% 7.2% 0.410 -0.033 18 Sean Newcomb 11 -7 88.6% 87.0 2.59 77.0% 21.9% 23.9% -2.0% 10.8% 0.332 -0.027 19 Vince Velasquez 24 +5 87.9% 86.1 4.69 82.6% 25.0% 28.5% -3.5% 9.0% 0.379 0.046 20 Mike Clevinger 18 -2 87.8% 104.0 3.03 83.4% 23.6% 22.4% 1.2% 8.1% 0.386 -0.034 21 Tyler Anderson 29 +8 87.1% 85.2 4.62 85.2% 25.0% 21.1% 3.9% 8.2% 0.406 0.064 22 Tyler Skaggs 23 +1 87.1% 87.0 2.69 85.3% 24.3% 26.3% -2.0% 7.3% 0.407 -0.030 23 Kyle Gibson 22 -1 86.8% 88.2 3.25 83.3% 24.0% 23.3% 0.7% 10.6% 0.398 -0.058 24 Nick Pivetta 25 +1 86.8% 84.1 4.06 85.0% 24.9% 28.6% -3.8% 6.8% 0.410 -0.018 25 Corey Kluber 31 +6 86.8% 113.1 2.54 82.8% 22.4% 26.9% -4.5% 3.0% 0.395 -0.049 26 Dylan Bundy 28 +2 86.5% 96.0 3.75 94.5% 27.5% 27.0% 0.5% 7.3% 0.477 -0.037 27 Mike Foltynewicz 26 -1 86.4% 84.0 2.14 75.3% 21.9% 28.4% -6.6% 10.7% 0.350 -0.040 28 Alex Wood 27 -1 86.3% 80.2 4.13 86.5% 23.0% 22.3% 0.7% 4.8% 0.426 -0.037 29 Lance Lynn [UR] [N/A] 84.8% 78.2 4.81 78.5% 22.5% 22.8% -0.4% 13.2% 0.392 0.007 30 Jameson Taillon 30 0 84.7% 88.2 3.96 76.7% 20.3% 22.4% -2.1% 6.7% 0.382 0.007 31 Luis Castillo 33 +2 84.7% 83.2 5.70 92.7% 28.7% 22.4% 6.3% 8.8% 0.489 -0.004 32 Rick Porcello 35 +3 84.2% 99.1 3.44 74.0% 19.0% 22.7% -3.7% 5.3% 0.370 -0.025 33 Miles Mikolas 41 +8 84.1% 97.0 2.69 78.6% 18.7% 18.5% 0.2% 3.1% 0.402 -0.067 34 J.A. Happ 34 0 83.9% 97.0 3.62 76.5% 21.5% 27.0% -5.5% 6.9% 0.391 -0.035 35 Stephen Strasburg 40 +5 83.5% 80.2 3.46 85.1% 24.5% 29.1% -4.6% 5.8% 0.454 -0.055 36 Matt Boyd 37 +1 83.4% 82.1 4.15 74.0% 21.1% 19.9% 1.2% 9.5% 0.381 -0.023 37 Tyson Ross 36 -1 82.8% 95.0 3.32 77.0% 20.8% 22.7% -1.9% 8.8% 0.409 -0.045 38 Zack Greinke 46 +8 82.7% 96.0 3.66 86.4% 23.9% 26.0% -2.1% 4.9% 0.474 -0.039 39 Dallas Keuchel 44 +5 82.6% 97.0 3.90 74.2% 18.9% 18.5% 0.4% 6.0% 0.393 0.025 40 Clayton Richard 45 +5 82.5% 100.0 4.23 78.3% 21.9% 19.5% 2.4% 7.7% 0.422 -0.035 41 Sonny Gray 52 +11 82.2% 80.1 4.93 76.9% 22.4% 20.6% 1.8% 9.6% 0.417 -0.001 42 Zack Wheeler 47 +5 82.0% 81.2 4.85 77.9% 21.1% 22.3% -1.2% 8.8% 0.426 -0.051 43 Cole Hamels 48 +5 81.9% 97.1 3.61 85.8% 24.8% 23.3% 1.5% 8.9% 0.480 -0.033 44 Kevin Gausman 32 -12 81.9% 94.1 4.20 84.4% 24.1% 21.7% 2.4% 6.2% 0.471 0.004 45 German Marquez 43 -2 81.8% 83.0 5.53 72.0% 20.5% 22.2% -1.8% 9.3% 0.389 0.091 46 Gio Gonzalez 39 -7 81.5% 85.2 3.68 75.9% 21.8% 22.0% -0.3% 10.5% 0.420 -0.015 47 Michael Fulmer 49 +2 81.4% 86.1 4.17 80.2% 21.6% 20.9% 0.7% 8.4% 0.449 -0.047 48 Zack Godley 51 +3 81.1% 88.1 4.58 81.3% 24.5% 22.0% 2.5% 11.4% 0.461 -0.039 49 Kyle Freeland 50 +1 80.7% 91.1 3.55 73.6% 19.3% 20.4% -1.1% 8.2% 0.415 -0.014 50 Jose Urena 56 +6 80.0% 94.0 4.40 74.3% 18.7% 19.4% -0.7% 5.4% 0.429 -0.040 51 Julio Teheran 53 +2 79.9% 81.2 4.52 78.4% 22.9% 21.4% 1.5% 11.4% 0.457 -0.021 52 Jake Odorizzi 57 +5 79.8% 79.2 4.97 82.9% 24.1% 22.7% 1.4% 10.2% 0.489 -0.004 53 David Price 58 +5 78.9% 93.1 3.66 70.5% 18.7% 23.3% -4.7% 8.6% 0.418 -0.034 54 Jake Arrieta 55 +1 78.8% 84.0 3.54 66.8% 15.5% 16.8% -1.3% 7.7% 0.394 -0.005 55 Tyler Mahle 70 +15 78.5% 86.0 3.98 75.9% 21.3% 22.0% -0.8% 9.8% 0.460 -0.005 56 Marco Gonzales 63 +7 78.4% 91.1 4.04 75.8% 18.7% 21.1% -2.5% 5.3% 0.460 -0.037 57 Jhoulys Chacin 54 -3 78.1% 92.0 3.82 70.9% 19.7% 18.1% 1.6% 10.2% 0.431 -0.059 58 Kyle Hendricks 65 +7 78.1% 89.1 3.73 73.6% 19.4% 18.9% 0.4% 7.4% 0.449 -0.045 59 Tanner Roark 60 +1 78.1% 92.1 4.09 73.4% 19.6% 20.5% -0.9% 8.6% 0.448 -0.051 60 Aaron Sanchez 62 +2 77.9% 79.2 4.52 76.6% 22.5% 18.7% 3.8% 12.6% 0.472 -0.085 61 Jose Quintana 59 -2 77.7% 80.1 4.26 69.8% 18.8% 22.0% -3.2% 10.7% 0.430 -0.015 62 Luke Weaver 64 +2 77.4% 84.1 4.59 72.6% 20.5% 21.0% -0.5% 8.7% 0.452 -0.052 63 Jakob Junis 61 -2 77.4% 96.1 4.67 76.9% 20.3% 21.8% -1.6% 6.5% 0.481 -0.009 64 Sean Manaea 68 +4 77.3% 100.2 3.40 78.5% 20.7% 18.5% 2.2% 4.7% 0.493 -0.127 65 James Shields 67 +2 77.0% 99.1 4.53 74.5% 20.5% 16.3% 4.2% 8.9% 0.470 -0.088 66 Marco Estrada 71 +5 77.0% 84.1 4.48 76.8% 21.0% 19.4% 1.6% 6.3% 0.486 -0.001 67 Chad Bettis 69 +2 76.6% 92.1 5.07 71.8% 19.6% 17.0% 2.6% 9.1% 0.457 0.003 68 Michael Wacha 72 +4 76.3% 84.1 3.20 72.9% 21.0% 20.0% 0.9% 10.1% 0.468 -0.124 69 Reynaldo Lopez 73 +4 75.8% 94.0 3.73 70.0% 19.2% 16.8% 2.4% 9.8% 0.456 -0.061 70 Ivan Nova 76 +6 75.7% 81.1 3.98 74.2% 19.1% 19.2% -0.1% 4.4% 0.486 -0.051 71 Steven Matz [UR] [N/A] 75.7% 78.0 3.69 61.8% 17.6% 21.4% -3.9% 9.2% 0.403 0.016 72 Trevor Williams 74 +2 74.8% 87.0 4.03 67.3% 16.9% 17.8% -0.9% 7.8% 0.451 -0.055 73 Felix Hernandez 77 +4 74.6% 95.1 5.10 70.7% 18.1% 19.2% -1.2% 8.4% 0.477 -0.046 74 Jon Lester 66 -8 74.5% 95.0 2.18 71.1% 19.6% 19.4% 0.1% 8.4% 0.481 -0.139 75 Derek Holland [UR] [N/A] 74.4% 85.0 4.24 71.8% 20.4% 22.1% -1.8% 9.2% 0.486 -0.043 76 Chase Anderson 75 -1 74.2% 82.1 4.37 68.0% 18.4% 18.8% -0.4% 10.1% 0.464 -0.056 77 Danny Duffy 79 +2 72.7% 88.2 5.18 73.9% 20.7% 19.3% 1.4% 11.2% 0.524 -0.059 78 Brandon McCarthy 78 0 72.6% 78.2 4.92 65.9% 15.7% 19.2% -3.5% 6.2% 0.471 0.027 79 Ian Kennedy 81 +2 71.1% 86.2 5.09 70.3% 17.7% 20.9% -3.2% 8.4% 0.521 -0.044 80 Chris Stratton 82 +2 70.1% 87.0 4.14 65.7% 17.4% 18.2% -0.8% 9.2% 0.503 -0.094 81 Sal Romano 84 +3 70.0% 85.0 5.40 63.2% 15.6% 16.5% -0.9% 9.6% 0.488 -0.021 82 Lucas Giolito [UR] [N/A] 69.7% 78.1 7.01 64.2% 18.3% 13.3% 5.0% 13.1% 0.498 -0.041 83 Jason Hammel 83 0 69.7% 94.1 5.34 72.9% 18.6% 14.6% 4.0% 7.1% 0.556 -0.107 84 Chad Kuhl 80 -4 69.0% 85.0 4.55 69.8% 20.5% 21.7% -1.2% 8.9% 0.546 -0.083 85 Andrew Cashner 85 0 68.8% 82.1 4.70 64.0% 16.5% 18.3% -1.9% 10.4% 0.509 0.002 86 Daniel Mengden 86 0 68.8% 90.2 4.47 68.5% 16.7% 14.5% 2.2% 5.0% 0.540 -0.097 87 Mike Leake 87 0 68.3% 100.2 4.11 68.5% 15.5% 14.4% 1.1% 5.5% 0.546 -0.113 88 Bartolo Colon 88 0 61.0% 82.2 4.90 58.5% 11.5% 13.9% -2.5% 3.8% 0.576 -0.062

A couple minor changes have been made in the table since last time:

1.  Added IP, by request
2.  Changed “Predicted K%” to “xK%” (to save space)
3.  Dropped the word “Pitcher” from Pitcher Score, now it’s just “Score” (also to save space)

For Reference:

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.

 

Halfway through the season, three pitchers have definitely separated themselves from the pack.  Max Scherzer, Jacob DeGrom and Chris Sale have been head & shoulders above the rest of MLB, their scores tightly bunched up around 103, while the 4th best pitcher is all the way down at 96.  Some other pitchers have better ERAs, but my early picks for the Cy Young as of right now would definitely be two of those three guys.  All three of them have been elite in both major components – strikeout ability and contact management.  These guys are well known as some of the best pitchers in MLB, so there really shouldn’t be any surprises.  But outside the top three, there are plenty to talk about.  Let’s start with one of the most difficult:

 

#9 Jon Gray (SP, Colorado Rockies)

Can we nickname him “the Enigma” already?  Most of the pitchers in my top 10 have pristine ERAs, because they are good pitchers.  And then, there’s Jon Gray.  His ERA currently sits at 5.52, which is not an ERA that one typically associates with good pitchers.  I honestly wouldn’t blame anyone for thinking I’m crazy to have him up so high on the list.  But it’s important to remember that these metrics are not subjective at all.  If a pitcher’s rank is way off from expected, we can usually learn something by trying to figure out WHY, rather than dismiss the model.  In Gray’s case, the explanation for why he is high on the list is an easy one.  He is simply missing the most bats in his career, by far.  He has made huge strides in his bat-missing ability, as demonstrated by his Contact% falling by ten percent since last year.  But the explanation for his ERA is not as simple.  One might assume it’s just his home park – he plays in Colorado, after all, widely recognized as the least pitcher-friendly park in MLB.

Unfortunately for that narrative, it’s simply not the case.  His home/road splits, in terms of both ERA and FIP, are essentially identical.  Taking a closer look, it seems to me that Gray has been extremely unlucky in 2018.  His start against Texas on June 16th is a great example.  In that game, in five innings he allowed seven baserunners, including one home run.  He gave up six runs in that game (five earned) while striking out nine (40%).  That’s textbook sequencing luck, with the walk, multiple hits and the home run all coming in the same inning.  Three of the hits that led directly to the runs were groundballs.  Oh, and another groundball went for an error that also led to a run.  It’s pretty hard to blame Gray for that one – his mistakes were essentially one walk and one homer.  With good sequencing luck that’s just one earned run instead of five – a huge difference.  And there are several numbers that suggest this is a microcosm of his season so far, not an aberration.  For starters, he’s got positive values in both of my luck indication columns, which is more rare than you might think.  His BABIP is 40 points above his career number.  Lastly, his bullpen has been atrocious at preventing inherited runners from scoring.  His overall LOB% of 63% is low – but if you look at the rate limited to his 3rd time through the order, i.e. the times more likely to be the bullpen, that drops all the way to 47%, meaning those runners are scoring more often than not.  Terrible.

 

#14 Jose Berrios (SP, Minnesota Twins)

While it’s not a complete shock for someone as talented and hyped as Berrios to shoot up the rankings, at just 24 years old, it’s still surprising and impressive to me what he’s done so far this year.  While he did improve his ERA vastly between 2016 and 2017, his improvements in plate discipline metrics were much more modest, grading out roughly as average last season.  Don’t get me wrong, an “average” pitcher at age 23 is still impressive.  But this year, he’s truly broken out and taken things to the next level.  His metrics are improved across the board, suggesting a rise in his strikeout rate of about five points, which is exactly how much his strikeout rate did rise.  No red flags there.  On the flip side, he’s also improved his walk rate dramatically for two years running.  Those changes are backed up by significant improvements in his O-Swing% and F-Strike%, and so I also believe his now-excellent walk rate.

In 2017, Berrios’ main weakness was lefties.  His splits last year were fairly extreme, with a FIP of three against righties, but five against lefties.  This year he has basically no splits, putting up similarly great numbers against both righties and lefties.  But let’s not get too far ahead of ourselves – it’s too small of a sample size to conclude that his problems with lefties are a thing of the past.  I think it’s actually more likely that he will struggle against lefties again in the second half.  The reason I say that, is that his BABIP vs. lefties has dropped 70 points from last year, but the batted ball profile didn’t change barely at all.  So I think some good fortune has masked his weakness against lefties this year, rather than him figuring everything out.  In the end, the strikeout and walk improvements are very believable, but I suspect his contact management is likely to regress in the second half.  The future is very bright for Jose, but he’s not a capital-A Ace, quite yet.

 

#25 Corey Kluber (SP, Cleveland Indians)

Kluber has easily been the most contentious pitcher in my rankings all year.  Every week, someone asks – “Why is Kluber so low?  He’s easily top 3”.  And over the past couple years overall, that is true.  He is a fantastic pitcher.  But the simple fact is that he just hasn’t pitched the same this year as he did last year.  Specifically, he has not been missing bats at the same rate.  In the full season 2017 rankings (which can be found at the bottom of my introduction piece here) he ranked #1 overall.  So I want to be absolutely clear – the model is not biased against him whatsoever, he is just pitching differently.  And it’s not just a matter of early-season struggles either.  Kluber is known to start off the season poorly, and in 2017 he lived up to that reputation.  But by the end of June, those struggles were long in the rear view mirror.  Here is a snapshot of his plate discipline metrics, 1st half of 2017 vs 1st half of 2018:

Time Period Sw-Str% Contact% O-Swing% 1st Half 2017 15.1% 68.1% 35.8% 1st Half 2018 10.7% 77.3% 35.3%

His O-Swing% has remained elite, which makes sense because his walk rate has also remained elite this year.  But the other metrics point towards a drop in his strikeout rate of roughly ten points, which is a huge, huge difference.  And in fact, Kluber’s strikeout rate is down seven points this year.  The numbers say it’s likely to drop even further if he doesn’t change anything.  This is something that can go unnoticed when a pitcher is still performing very well.  But to me the data is pretty clear in that Kluber has been lucky this year to have such a pristine ERA.  If he keeps pitching like this, his second half could be very disappointing.  That BABIP is currently 55 points under his career, and his LOB of 85% is also high, to go along with negative numbers in both luck columns above.

There is one easily-identifiable thing Kluber could do to help regain his mojo.  Last year, a huge part of his success was increasing the slider usage from 20% up to 27%.  This is a story we’ve seen time and again – identify your best pitch, and throw it more often.  This year, his slider usage is back down closer to 20%.  That slider is still allowing an wRC+ of negative three, so I have to wonder – why not throw it more often?  It worked incredibly well for him last year, and as the saying goes – “If it ain’t broke, don’t fix it”.

 

#38 Zack Greinke (SP, Arizona D-Backs)

Greinke is another guy who generates a fair amount of discussion due to his low placement in the rankings.  He was in my top 10 last year, so #38 is a very noticeable dropoff.  Is it possible Greinke’s age is starting to catch up with him?  He is 34 after all.  His velocity is down a tick this year as well.  At first glance, maybe that could explain his declining metrics.  All three of the main metrics are trending the wrong direction for him this year, although they are more incremental changes than huge drops, which is something that would fit a small decline in velocity.  The metrics would suggest a drop in his strikeout rate of about 3% from last year.  His actual K% has dropped less than 1 percent, so he’s been a tiny bit fortunate in that area.  Overall though, we are still working within the margin of error; it’s not a big enough difference to mean much.  His actual strikeout rate of 26% is within the ballpark of what his metrics would suggest.  So what gives?

It seems that contact management has been Greinke’s main weakness in 2018.  His xSLG this year is nowhere near elite at .474, which is 40 points worse than league average, and 76 points worse than he did last year.  He went from above average in that respect, to well below average.  Looking a bit closer, it seems to me that something is off with his slider this year.  It doesn’t seem related to velocity, as the slider hasn’t really budged velocity-wise.  But hitters seem to be squaring it up MUCH better than previously in Greinke’s career.  His slider has a negative overall pitch value in 2018, something that has never happened in his career.  Actually it’s been the opposite – the slider has the best value of all his pitches, both overall and on a per-pitch basis.  For his career it has allowed an wRC+ of just 38.  This year, 105.  Having looked at quite a few slider pitch-splits this year, this definitely stands out to me as an anomaly.  I thought maybe he was tipping his pitches, but a glance at his release points doesn’t show anything out of the ordinary.  So my best theory is this:

Greinke’s slider location, 2017:

Greinke’s slider location, 2018:

He’s simply getting more of the plate than you want for a slider, with that entire dark red portion squarely within the zone.  That could definitely explain why hitters are able to square it up much better.  It’s the best theory I’ve got, at least.  The bright side is that pitch location is fixable.

Moving on, here is the data for the non-qualified SP (10 IP minimum):

Name Team Score IP ERA PD Score xK% K% xK%-K% BB% xSLG SLG-xSLG Freddy Peralta Brewers 106.7% 22.2 1.59 100.3% 31.9% 41.7% -9.8% 10.7% 0.246 -0.086 Matt Strahm Padres 104.8% 13.1 1.35 103.1% 31.1% 35.3% -4.2% 5.9% 0.290 -0.061 Noah Syndergaard Mets 98.8% 64.2 3.06 99.1% 30.6% 28.3% 2.3% 4.8% 0.343 0.021 Jonathan Loaisiga Yankees 98.6% 14.0 1.93 92.6% 26.9% 31.6% -4.7% 14.0% 0.303 -0.079 Shohei Ohtani Angels 96.9% 49.1 3.10 99.1% 34.0% 30.5% 3.5% 10.0% 0.368 -0.048 Domingo German Yankees 94.9% 49.0 5.88 102.1% 31.8% 27.1% 4.7% 6.8% 0.416 0.044 Ross Stripling Dodgers 92.6% 62.0 2.32 83.9% 22.4% 29.3% -6.9% 2.4% 0.325 0.066 Kenta Maeda Dodgers 91.2% 67.0 3.49 91.3% 27.5% 27.3% 0.2% 9.4% 0.392 -0.018 Jack Flaherty Cardinals 90.6% 57.2 2.50 85.1% 26.9% 29.4% -2.6% 6.9% 0.359 -0.034 John Gant Cardinals 90.0% 22.0 4.09 84.8% 24.9% 25.3% -0.4% 9.9% 0.365 -0.090 Johnny Cueto Giants 89.8% 32.0 0.84 76.2% 22.3% 22.2% 0.0% 5.1% 0.311 -0.105 Masahiro Tanaka Yankees 89.5% 72.2 4.58 98.1% 28.8% 24.8% 4.0% 6.5% 0.460 -0.019 Trevor Cahill Athletics 89.2% 48.2 2.77 92.2% 28.5% 25.0% 3.5% 5.9% 0.425 -0.072 Walker Buehler Dodgers 88.8% 51.1 2.63 72.4% 19.1% 26.7% -7.6% 5.5% 0.298 -0.025 Robbie Ray Diamondbacks 88.7% 27.2 4.88 92.1% 30.1% 36.3% -6.3% 13.7% 0.432 -0.013 Carlos Martinez Cardinals 88.2% 72.2 3.22 75.5% 20.9% 22.4% -1.6% 13.2% 0.328 -0.022 Brad Keller Royals 88.0% 25.2 2.45 76.9% 21.8% 16.0% 5.8% 10.4% 0.340 -0.063 CC Sabathia Yankees 87.7% 76.1 3.18 81.5% 22.1% 18.6% 3.5% 6.1% 0.374 0.025 Austin Bibens-Dirkx Rangers 87.5% 22.2 3.57 87.0% 22.7% 17.5% 5.2% 6.2% 0.413 -0.038 Jordan Montgomery Yankees 87.5% 27.1 3.62 79.9% 21.5% 19.8% 1.7% 10.3% 0.366 -0.010 Hyun-Jin Ryu Dodgers 87.1% 29.2 2.12 79.3% 24.8% 31.3% -6.5% 8.7% 0.367 -0.059 Shane Bieber Indians 87.0% 18.1 2.45 86.8% 26.5% 29.0% -2.5% 4.0% 0.419 0.033 Garrett Richards Angels 86.3% 68.1 3.42 84.0% 25.8% 26.8% -1.0% 11.0% 0.410 -0.050 Mike Montgomery Cubs 86.0% 35.2 2.02 83.7% 21.6% 18.0% 3.6% 6.5% 0.411 -0.130 Nick Kingham Pirates 85.4% 35.1 3.82 85.6% 25.0% 24.3% 0.7% 4.9% 0.432 -0.066 Andrew Heaney Angels 84.8% 78.2 3.43 82.3% 23.3% 22.5% 0.7% 6.6% 0.418 -0.037 Clayton Kershaw Dodgers 83.9% 52.0 2.94 81.2% 22.5% 26.6% -4.1% 5.6% 0.422 -0.021 Seth Lugo Mets 83.9% 23.0 3.52 77.3% 21.6% 26.5% -4.9% 5.9% 0.397 -0.003 Sam Gaviglio Blue Jays 83.6% 36.1 4.21 79.9% 20.8% 22.1% -1.3% 6.5% 0.418 0.019 Joe Musgrove Pirates 83.5% 33.1 4.59 76.5% 20.4% 21.0% -0.7% 6.1% 0.396 0.026 Ryne Stanek Rays 83.5% 10.0 1.80 87.0% 26.6% 26.3% 0.3% 10.5% 0.466 -0.290 Caleb Smith Marlins 83.3% 77.1 4.19 82.9% 24.3% 27.0% -2.7% 10.1% 0.442 -0.054 Anibal Sanchez Braves 83.1% 44.0 2.86 76.8% 19.9% 23.7% -3.8% 7.3% 0.404 -0.008 Chris Archer Rays 83.0% 76.1 4.24 86.4% 26.4% 23.7% 2.7% 8.1% 0.469 -0.050 Zach Eflin Phillies 83.0% 49.2 3.44 76.1% 21.4% 24.6% -3.3% 5.8% 0.400 -0.012 Yu Darvish Cubs 82.7% 40.0 4.95 78.2% 24.1% 27.2% -3.2% 11.7% 0.418 0.007 Dereck Rodriguez Giants 81.2% 27.1 3.95 76.7% 20.9% 20.2% 0.6% 5.0% 0.429 -0.016 Fernando Romero Twins 81.0% 51.1 4.38 79.0% 22.8% 19.6% 3.2% 8.5% 0.446 -0.037 Brent Suter Brewers 81.0% 75.2 4.28 79.7% 21.2% 19.4% 1.8% 5.1% 0.451 -0.018 Caleb Ferguson Dodgers 80.9% 10.2 7.59 78.9% 26.7% 25.0% 1.7% 12.5% 0.447 -0.047 Junior Guerra Brewers 80.6% 76.2 2.82 75.5% 21.8% 23.3% -1.6% 9.5% 0.428 -0.081 Wilmer Font Rays 80.6% 16.0 1.69 67.9% 19.8% 23.4% -3.7% 9.4% 0.378 -0.068 Carlos Rodon White Sox 80.3% 24.1 3.70 75.5% 19.7% 18.5% 1.2% 6.8% 0.433 -0.063 Jeremy Hellickson Nationals 80.0% 43.1 2.28 77.3% 20.5% 20.7% -0.3% 3.7% 0.448 -0.087 Hector Velazquez Red Sox 80.0% 10.2 2.53 91.4% 23.4% 22.7% 0.6% 4.6% 0.543 -0.091 Nick Tropeano Angels 79.8% 54.0 4.83 83.7% 25.5% 19.6% 5.9% 8.9% 0.494 -0.019 Michael Soroka Braves 79.8% 25.2 3.51 78.7% 22.0% 18.6% 3.4% 6.2% 0.461 -0.048 Wade LeBlanc Mariners 79.0% 52.2 2.91 79.5% 19.3% 19.7% -0.4% 5.6% 0.476 -0.088 Jordan Lyles Padres 78.8% 47.0 4.79 72.6% 17.9% 19.9% -2.1% 5.5% 0.433 0.051 Yonny Chirinos Rays 78.3% 22.2 4.37 75.9% 20.1% 21.0% -0.9% 8.0% 0.462 -0.043 Ryan Yarbrough Rays 78.3% 20.2 5.23 70.7% 18.4% 19.1% -0.7% 6.7% 0.427 -0.002 Trevor Richards Marlins 78.3% 44.0 4.91 71.4% 19.2% 20.9% -1.8% 10.5% 0.432 -0.014 Tyler Chatwood Cubs 78.3% 68.1 3.95 65.8% 19.1% 20.3% -1.3% 20.0% 0.395 -0.064 Blaine Hardy Tigers 78.2% 43.2 3.71 70.2% 17.1% 16.6% 0.5% 5.5% 0.426 0.005 Jason Vargas Mets 77.9% 37.2 8.60 82.2% 22.9% 17.8% 5.1% 7.8% 0.509 0.104 Dylan Covey White Sox 77.9% 44.1 3.45 64.9% 16.3% 18.7% -2.4% 10.4% 0.394 -0.072 Joey Lucchesi Padres 77.6% 53.0 3.57 75.9% 22.8% 25.1% -2.3% 8.7% 0.471 -0.037 Paul Blackburn Athletics 77.1% 17.1 8.83 72.3% 17.4% 14.3% 3.1% 5.2% 0.454 0.053 Chris Bassitt Athletics 77.1% 16.1 3.86 69.3% 14.6% 17.8% -3.3% 4.1% 0.434 -0.125 Jordan Zimmermann Tigers 77.0% 41.1 4.35 76.5% 19.9% 22.5% -2.7% 5.8% 0.483 -0.073 Madison Bumgarner Giants 76.8% 25.1 3.20 67.2% 16.2% 16.2% 0.0% 6.7% 0.424 0.008 Jaime Barria Angels 76.7% 50.1 3.40 84.6% 24.2% 20.1% 4.1% 6.7% 0.541 -0.112 Nathan Eovaldi Rays 76.6% 35.1 4.08 74.5% 17.9% 22.4% -4.6% 3.7% 0.476 -0.051 Wei-Yin Chen Marlins 75.9% 49.2 6.70 67.9% 17.0% 15.6% 1.4% 10.4% 0.440 0.095 Francisco Liriano Tigers 75.5% 61.2 3.94 79.4% 23.8% 19.1% 4.7% 12.7% 0.523 -0.157 Frankie Montas Athletics 75.4% 36.2 3.68 62.0% 15.5% 13.9% 1.6% 8.2% 0.408 0.000 Clay Buchholz Diamondbacks 74.9% 38.2 2.56 74.6% 18.9% 20.3% -1.4% 4.6% 0.499 -0.126 Marcus Stroman Blue Jays 74.8% 42.1 6.80 73.1% 21.0% 18.8% 2.2% 9.6% 0.490 -0.053 Yovani Gallardo Rangers 74.5% 10.1 7.84 58.9% 12.6% 14.9% -2.4% 10.6% 0.399 0.125 Mike Fiers Tigers 74.4% 77.2 4.29 71.3% 18.3% 17.3% 1.0% 5.4% 0.483 0.015 Luis Perdomo Padres 74.4% 14.0 8.36 68.5% 21.2% 22.1% -0.9% 11.7% 0.465 0.058 Matt Moore Rangers 74.1% 55.0 8.02 75.2% 20.1% 14.7% 5.4% 9.3% 0.513 0.056 Erick Fedde Nationals 73.6% 22.0 5.32 72.9% 19.6% 17.4% 2.2% 6.5% 0.505 -0.011 Andrew Triggs Athletics 73.0% 41.1 5.23 75.9% 21.4% 23.6% -2.3% 9.9% 0.533 -0.120 Adam Wainwright Cardinals 72.9% 18.0 4.00 55.9% 14.0% 17.1% -3.1% 15.9% 0.400 0.035 Steven Wright Red Sox 72.7% 24.0 4.13 67.0% 19.0% 16.8% 2.2% 9.9% 0.478 -0.122 Zach Davies Brewers 72.3% 43.0 5.23 69.1% 18.7% 16.3% 2.4% 9.0% 0.497 -0.003 Brandon Woodruff Brewers 72.2% 15.2 6.32 65.8% 19.2% 18.1% 1.1% 12.5% 0.476 -0.083 Mike Minor Rangers 72.2% 78.1 5.06 75.6% 20.4% 19.6% 0.8% 5.7% 0.542 -0.045 Eric Lauer Padres 72.2% 57.0 5.05 61.8% 15.8% 19.3% -3.6% 10.2% 0.450 0.041 Drew Pomeranz Red Sox 72.1% 37.0 6.81 65.2% 16.7% 20.8% -4.2% 12.1% 0.473 0.070 Andrew Suarez Giants 71.7% 65.0 4.43 65.8% 15.7% 23.0% -7.3% 4.9% 0.482 -0.037 David Hess Orioles 71.3% 41.1 5.44 68.6% 16.4% 13.3% 3.1% 9.4% 0.507 -0.007 Matt Harvey – – – 71.3% 69.0 4.83 64.5% 16.5% 17.4% -0.9% 5.5% 0.480 -0.031 Jaime Garcia Blue Jays 71.0% 61.1 6.16 68.1% 19.0% 19.9% -1.0% 11.0% 0.508 0.004 Ty Blach Giants 70.9% 60.2 4.90 60.7% 14.7% 11.1% 3.6% 8.5% 0.460 -0.047 Jake Faria Rays 70.4% 47.2 5.48 68.1% 19.0% 18.2% 0.7% 10.8% 0.516 -0.093 Dillon Peters Marlins 70.0% 24.2 5.84 62.0% 16.3% 14.4% 1.9% 11.7% 0.480 -0.011 Jeff Samardzija Giants 69.9% 35.2 6.56 68.8% 17.7% 15.7% 2.0% 13.9% 0.527 -0.084 Elieser Hernandez Marlins 69.6% 22.0 4.50 71.6% 21.2% 18.7% 2.5% 5.5% 0.549 0.011 Anthony DeSclafani Reds 69.5% 22.0 4.09 59.6% 14.5% 19.6% -5.2% 8.7% 0.470 0.030 Eric Skoglund Royals 69.1% 49.2 6.70 70.3% 17.3% 18.0% -0.7% 6.5% 0.548 -0.018 Alex Cobb Orioles 68.8% 70.0 6.56 63.9% 15.2% 15.5% -0.3% 5.7% 0.508 0.055 Matt Wisler Braves 68.7% 17.1 3.63 73.6% 20.7% 18.6% 2.1% 7.1% 0.575 -0.160 Dan Straily Marlins 68.6% 52.1 4.82 76.3% 21.8% 19.6% 2.2% 10.9% 0.594 -0.122 Brandon Finnegan Reds 68.0% 20.2 7.40 63.0% 16.0% 13.6% 2.4% 14.6% 0.513 0.040 Ben Lively Phillies 67.2% 23.2 6.85 62.8% 17.9% 19.1% -1.3% 8.7% 0.522 0.023 Kendall Graveman Athletics 67.0% 34.1 7.60 67.6% 17.1% 17.1% 0.0% 8.2% 0.557 -0.015 Adam Plutko Indians 66.8% 29.0 4.66 70.3% 16.6% 17.5% -0.9% 6.7% 0.578 -0.042 John Lamb Angels 66.7% 10.0 7.20 72.3% 17.8% 22.0% -4.3% 8.0% 0.593 0.124 Doug Fister Rangers 66.4% 66.0 4.50 55.9% 11.8% 13.8% -2.0% 6.6% 0.487 -0.031 Rich Hill Dodgers 65.0% 35.2 5.30 61.8% 15.6% 22.2% -6.6% 9.9% 0.546 -0.046 Daniel Gossett Athletics 64.9% 24.1 5.18 66.2% 15.5% 11.8% 3.7% 7.8% 0.576 -0.081 Brett Anderson Athletics 64.9% 15.1 7.63 67.1% 18.0% 11.1% 6.9% 8.3% 0.582 0.009 Joe Biagini Blue Jays 64.9% 18.2 7.71 65.9% 16.7% 14.4% 2.3% 10.0% 0.574 -0.080 Steven Brault Pirates 63.8% 26.0 5.54 69.2% 20.0% 13.4% 6.6% 12.5% 0.611 -0.213 Taijuan Walker Diamondbacks 62.7% 13.0 3.46 57.6% 15.1% 16.1% -1.1% 8.9% 0.548 -0.156 Homer Bailey Reds 62.1% 62.0 6.68 64.2% 15.8% 13.0% 2.8% 8.2% 0.600 -0.036 Hector Santiago White Sox 61.1% 32.1 6.12 62.0% 16.5% 15.9% 0.6% 15.2% 0.598 -0.027 Jarlin Garcia Marlins 61.0% 33.0 3.55 65.1% 18.0% 16.7% 1.3% 9.9% 0.620 -0.222 Bryan Mitchell Padres 59.3% 32.0 6.47 47.1% 11.8% 10.4% 1.4% 16.9% 0.523 -0.027 Ryan Carpenter Tigers 57.4% 12.0 6.75 58.5% 14.9% 10.7% 4.2% 3.6% 0.624 -0.047 Matt Koch Diamondbacks 56.9% 69.2 4.52 60.7% 13.5% 12.1% 1.4% 5.9% 0.646 -0.140 Miguel Gonzalez White Sox 56.8% 12.1 12.41 66.3% 15.5% 7.6% 7.9% 9.1% 0.684 0.099 Josh Tomlin Indians 55.9% 30.0 8.10 73.8% 19.1% 12.9% 6.2% 3.6% 0.746 -0.019 Carson Fulmer White Sox 55.3% 31.0 8.13 56.5% 14.6% 16.6% -2.1% 15.3% 0.640 -0.136 Martin Perez Rangers 55.1% 22.1 9.67 51.8% 11.6% 10.9% 0.6% 10.1% 0.610 0.060 Chris Tillman Orioles 51.6% 26.2 10.46 49.4% 11.9% 9.5% 2.4% 12.4% 0.641 0.011

 

Madison Bumgarner (SP, San Francisco Giants)

For the second season in a row, injuries to the Giants’ ace have put a damper on their playoff hopes.  Now that he’s returned and pitched a handful of games, there are a lot of eyes on him.  Everyone wants to know – is he the same pitcher?  Last year he wasn’t, and then he got injured again.  And at first glance, the metrics are certainly not great.  That 16% expected K-rate is way, way down from his career rate of 24%.  But there are also reasons to be hopeful.  For starters, he pitched yesterday which is not included in the data.  In that game he struck out eight, with a Contact% of 77%.  This was against the Rockies, one of the worst offense away from Coors, so take it with a grain of salt – but at least his metrics as well as strikeout rate are moving in the right direction.  His actual K% rose by three percent from that one game.

Looking at his pitch-splits, something seems off with his curveball.  Bumgarner’s curve has long been his best pitch, generating a 16% whiff rate and allowing a wRC+ of just 43 for his career.  This year, the results are still outstanding with an wRC+ of negative 24.  But instead of missing bats, it’s generating weak contact.  The whiff rate is down to just 8.5%, but the LD% is also super low at just 7%.  Actually, batters have only got a single hit off Bumgarner’s 82 curveballs thrown.  This was a home run, leaving his BABIP for curveballs at precisely .000.  And overall his BABIP of .226 is certainly a red flag.  But at the same time, there doesn’t seem to be anything wrong with his movement numbers, velocity, or release points for the curveball.  So I want to believe the whiffs and strikeouts are coming back, and could help counteract any potential regression coming from BABIP.  His velocity is also trending upward so far, an indication that he’s rebuilding his strength after the injury.  I’ll be keeping a close eye on him, the jury is still out – but there are some hopeful signs pointing towards a return to form.

 

Walker Buehler (SP, Los Angeles Dodgers)

For the first couple months of the season, Buehler stood out as having the largest difference between expected K% and actual K% of anyone in the league.  The difference was about 15% (15 vs. 30) as of mid-May, where I rated him a solid “SELL”.  Since then, the results have still been pretty positive for the most part.  Overall he’s continued to pitch well, with his ERA as well as FIP/SIERA looking very nice.  He has also missed more bats since then, increasing his expected K% from about 16 up to the current level of 19%, which is at least average-ish.  At the same time, his actual K% has dropped about 3.5%.  So his gap is certainly closing, as we should expect, but in his case it’s coming about equally from both sides, rather than predominantly the K% moving.  In past analysis, we found the gap closure is typically attributed about 75% to the strikeout rate changing, not the metrics, so he is bucking the trend a bit.

Since that update, he has undoubtedly done better than I expected, as reflected by his overall score rising to 88.  But I think I still have to rate him as a “SELL”.  Even with the significant gap closure, he still sports one of the largest K% discrepancies.  But mainly his schedule has just been incredibly fortunate.  Six of his nine starts have come against the Padres, Marlins and Rockies, which are three of the most inept offenses in the game.  His tougher matchups, the Giants and Reds, have been at home.  Truly he’s only had one bad matchup all season – against the Rockies in Coors, where he only struck out two and gave up 4 ER.  Between that, the K% discrepancy, and potential innings limits, I think that is enough to take advantage of his current stat line and cash in the chips.