Plate Discipline Series – Relief Update #2

(Photo by Lawrence Iles/Icon Sportswire)

Welcome back to my series on pitching metrics.  This week I will be returning to the topic of relief pitchers.  I haven’t looked at bullpens in over a month, so there’s a lot more data.  Also, the last time I looked at relievers was before incorporating StatCast data, so it could be interesting to see how that changed things.

Here are the new rankings:

Top 100 Qualified RP

Rank Name ERA Team Pitcher Score PD Score Predicted K% Actual K% K% Difference BB% xSLG SLG-xSLG
1 Josh Hader 1.22 Brewers 120.8% 121.7% 42.7% 53.7% -11.0% 11.2% 0.200 -0.049
2 Aroldis Chapman 1.26 Yankees 115.1% 113.2% 37.5% 44.3% -6.8% 11.5% 0.220 -0.024
3 Edwin Diaz 2.50 Mariners 113.5% 116.8% 39.4% 42.0% -2.6% 8.7% 0.265 -0.044
4 Sean Doolittle 1.57 Nationals 113.1% 119.1% 37.6% 38.5% -0.9% 2.9% 0.286 -0.064
5 Blake Treinen 0.87 Athletics 109.0% 115.1% 35.5% 29.0% 6.5% 6.5% 0.314 -0.062
6 Jose Leclerc 1.99 Rangers 108.4% 99.3% 33.0% 30.8% 2.2% 14.3% 0.216 -0.024
7 Dan Winkler 1.03 Braves 108.4% 101.2% 30.7% 37.0% -6.3% 7.0% 0.229 -0.029
8 Craig Kimbrel 2.48 Red Sox 107.8% 116.1% 38.7% 37.8% 0.9% 8.1% 0.337 0.039
9 Chris Devenski 1.75 Astros 106.8% 106.3% 32.6% 30.7% 1.9% 7.9% 0.285 0.026
10 Victor Arano 2.21 Phillies 104.5% 111.2% 34.8% 28.1% 6.6% 6.1% 0.348 -0.062
11 Carl Edwards Jr. 2.88 Cubs 104.3% 106.1% 35.4% 38.1% -2.7% 11.4% 0.317 -0.005
12 Adam Ottavino 0.95 Rockies 103.5% 88.9% 30.9% 45.5% -14.7% 10.1% 0.212 -0.074
13 Bruce Rondon 3.74 White Sox 102.5% 96.2% 31.3% 32.0% -0.8% 11.3% 0.275 0.035
14 Joe Jimenez 2.30 Tigers 102.4% 95.0% 30.6% 26.2% 4.4% 6.2% 0.268 0.026
15 Justin Anderson 3.38 Angels 102.2% 99.2% 35.0% 29.2% 5.8% 17.7% 0.299 -0.010
16 Reyes Moronta 1.76 Giants 101.1% 92.6% 30.2% 28.2% 2.0% 12.9% 0.270 -0.062
17 Dellin Betances 3.41 Yankees 100.1% 96.3% 31.5% 43.2% -11.7% 9.3% 0.307 0.007
18 Ryan Tepera 2.81 Blue Jays 99.8% 98.7% 29.8% 26.6% 3.2% 8.1% 0.328 0.083
19 Pedro Strop 1.95 Cubs 99.7% 106.1% 32.1% 22.9% 9.2% 8.3% 0.378 -0.105
20 Ryan Pressly 3.62 Twins 99.3% 109.3% 35.4% 32.4% 3.0% 9.2% 0.405 -0.005
21 Daniel Coulombe 4.50 Athletics 99.2% 99.7% 31.3% 29.1% 2.2% 9.3% 0.342 0.087
22 Brad Brach 3.96 Orioles 98.9% 103.1% 32.1% 22.7% 9.4% 12.6% 0.368 0.001
23 Jose Alvarado 3.10 Rays 98.6% 87.9% 26.9% 26.9% -0.1% 10.9% 0.271 -0.006
24 Bud Norris 3.38 Cardinals 98.0% 100.1% 29.6% 34.8% -5.3% 3.4% 0.361 -0.019
25 Tony Watson 2.10 Giants 97.8% 98.4% 28.3% 28.8% -0.6% 4.2% 0.352 -0.052
26 A.J. Minter 3.46 Braves 97.7% 100.3% 33.3% 25.4% 7.9% 11.4% 0.366 -0.012
27 Tony Cingrani 4.84 Dodgers 97.7% 91.4% 29.3% 39.6% -10.4% 6.6% 0.307 0.030
28 Brad Hand 1.83 Padres 97.4% 90.4% 28.4% 37.4% -9.0% 10.1% 0.304 -0.037
29 Adam Cimber 2.60 Padres 97.1% 86.7% 25.3% 31.6% -6.3% 4.5% 0.283 0.048
30 Jacob Barnes 2.08 Brewers 97.0% 96.2% 30.9% 22.5% 8.4% 8.1% 0.348 -0.021
31 Sam Freeman 3.38 Braves 96.8% 87.8% 27.5% 25.9% 1.6% 14.8% 0.295 -0.014
32 Taylor Williams 2.13 Brewers 96.8% 96.5% 30.3% 33.7% -3.4% 11.5% 0.353 -0.061
33 Heath Hembree 3.94 Red Sox 96.4% 99.3% 30.5% 30.7% -0.2% 10.2% 0.377 0.023
34 Luis Garcia 4.74 Phillies 96.1% 98.1% 30.2% 22.3% 7.9% 5.8% 0.372 -0.039
35 Sammy Solis 3.52 Nationals 96.1% 92.3% 29.1% 30.5% -1.4% 11.6% 0.334 0.003
36 Steven Brault 3.47 Pirates 95.7% 91.2% 27.6% 31.0% -3.4% 13.0% 0.332 -0.003
37 Wade Davis 3.42 Rockies 95.6% 85.5% 25.5% 29.3% -3.9% 11.3% 0.295 0.053
38 Raisel Iglesias 2.33 Reds 95.5% 97.2% 30.3% 30.8% -0.5% 9.4% 0.375 -0.042
39 Kelvin Herrera 1.05 Royals 95.5% 99.6% 28.1% 23.2% 4.9% 2.1% 0.391 -0.108
40 Felipe Vazquez 4.21 Pirates 95.2% 91.4% 28.3% 24.1% 4.2% 10.3% 0.340 -0.032
41 Kyle Barraclough 1.23 Marlins 95.1% 79.8% 25.4% 26.1% -0.7% 13.0% 0.264 -0.076
42 Tyler Clippard 3.34 Blue Jays 95.1% 95.6% 30.0% 28.4% 1.6% 11.9% 0.369 0.053
43 Andrew Chafin 2.01 Diamondbacks 95.0% 94.6% 31.0% 24.7% 6.3% 12.4% 0.364 -0.080
44 Craig Stammen 2.30 Padres 94.9% 92.1% 26.1% 26.8% -0.8% 4.1% 0.349 -0.044
45 Zach Duke 3.13 Twins 94.8% 78.4% 22.6% 23.2% -0.6% 10.2% 0.258 0.035
46 Jose Alvarez 2.45 Angels 94.5% 85.8% 22.8% 26.9% -4.1% 5.0% 0.312 0.027
47 Kirby Yates 1.04 Padres 94.1% 91.2% 27.4% 29.5% -2.1% 7.6% 0.353 -0.136
48 Lou Trivino 1.82 Athletics 94.0% 94.6% 30.3% 26.2% 4.1% 12.6% 0.377 -0.074
49 Justin Wilson 2.28 Cubs 93.9% 82.6% 24.9% 33.3% -8.5% 18.0% 0.299 -0.015
50 Amir Garrett 2.21 Reds 93.8% 91.0% 28.7% 29.1% -0.4% 7.8% 0.356 -0.023
51 Will Harris 4.70 Astros 93.6% 97.1% 27.9% 26.5% 1.4% 6.1% 0.399 -0.019
52 Jared Hughes 1.02 Reds 93.5% 92.9% 27.8% 20.5% 7.3% 6.8% 0.372 -0.111
53 Dan Altavilla 2.61 Mariners 93.5% 85.5% 28.2% 27.1% 1.1% 17.7% 0.323 -0.044
54 Shane Carle 2.14 Braves 93.3% 101.0% 31.4% 17.9% 13.5% 7.5% 0.429 -0.093
55 Jeremy Jeffress 0.55 Brewers 93.2% 81.7% 25.1% 26.1% -1.0% 9.2% 0.302 -0.094
56 Richard Rodriguez 2.38 Pirates 93.1% 97.0% 29.3% 36.3% -7.1% 3.3% 0.406 -0.020
57 John Brebbia 3.38 Cardinals 92.9% 87.2% 26.6% 26.7% -0.2% 7.8% 0.342 0.007
58 Seung Hwan Oh 3.64 Blue Jays 92.9% 91.1% 26.3% 23.3% 3.0% 7.0% 0.369 0.028
59 Jake Diekman 3.09 Rangers 92.8% 87.5% 27.5% 27.1% 0.4% 15.0% 0.346 -0.054
60 Matt Barnes 2.43 Red Sox 92.4% 85.5% 26.0% 32.0% -6.1% 13.1% 0.338 -0.088
61 Daniel Hudson 4.98 Dodgers 92.1% 86.2% 26.0% 18.4% 7.6% 11.2% 0.347 0.044
62 Arodys Vizcaino 2.10 Braves 92.1% 92.9% 30.1% 26.9% 3.2% 10.6% 0.392 -0.088
63 Kenley Jansen 2.73 Dodgers 92.0% 91.5% 26.7% 25.8% 0.9% 5.8% 0.383 -0.056
64 Robert Gsellman 2.95 Mets 91.8% 81.1% 23.5% 23.2% 0.3% 10.4% 0.317 0.000
65 Brad Boxberger 2.70 Diamondbacks 91.8% 75.4% 20.9% 32.7% -11.8% 10.2% 0.279 0.066
66 Chasen Shreve 4.35 Yankees 91.7% 99.3% 30.8% 30.9% -0.1% 11.7% 0.439 -0.024
67 Peter Moylan 3.32 Braves 91.7% 86.9% 24.6% 21.4% 3.2% 14.3% 0.357 0.033
68 Hector Rondon 1.50 Astros 91.5% 90.4% 26.4% 30.2% -3.9% 5.2% 0.382 -0.052
69 Ryan Madson 4.15 Nationals 91.5% 87.3% 26.0% 24.0% 2.0% 7.3% 0.362 -0.040
70 Joakim Soria 3.24 White Sox 91.3% 95.4% 28.4% 27.1% 1.3% 4.7% 0.419 -0.063
71 Scott Alexander 4.44 Dodgers 91.2% 79.4% 24.2% 16.4% 7.8% 13.5% 0.313 0.013
72 Jeurys Familia 2.48 Mets 90.9% 82.1% 25.3% 27.5% -2.3% 7.5% 0.335 0.014
73 Pedro Baez 3.23 Dodgers 90.8% 87.5% 27.6% 26.3% 1.3% 11.7% 0.373 0.024
74 Joe Kelly 2.70 Red Sox 90.7% 78.5% 24.1% 26.7% -2.6% 11.2% 0.314 -0.096
75 Hector Neris 5.01 Phillies 90.7% 106.7% 35.9% 28.9% 7.0% 9.6% 0.502 0.014
76 Tayron Guerrero 5.28 Marlins 90.6% 88.2% 29.2% 30.1% -0.9% 12.0% 0.380 0.036
77 Robbie Erlin 1.97 Padres 90.3% 78.7% 19.9% 21.7% -1.9% 1.7% 0.321 -0.048
78 Brandon Morrow 1.66 Cubs 90.2% 86.8% 26.7% 26.7% 0.0% 10.5% 0.376 -0.126
79 Sergio Romo 4.64 Rays 90.2% 93.7% 27.9% 26.6% 1.3% 7.5% 0.422 0.024
80 Drew Steckenrider 4.03 Marlins 90.0% 78.6% 23.7% 31.7% -8.0% 10.8% 0.324 -0.019
81 Alex Colome 4.08 – – – 89.5% 90.9% 27.3% 22.1% 5.2% 7.1% 0.412 -0.029
82 James Pazos 1.54 Mariners 89.5% 88.3% 24.0% 26.4% -2.5% 1.1% 0.395 -0.046
83 Ken Giles 4.76 Astros 89.4% 99.7% 30.0% 24.2% 5.8% 2.1% 0.473 -0.064
84 David Robertson 3.94 Yankees 89.3% 88.4% 28.9% 30.3% -1.4% 8.2% 0.398 -0.043
85 Chaz Roe 3.12 Rays 89.0% 83.6% 24.5% 28.9% -4.5% 8.7% 0.370 -0.029
86 Cody Allen 4.18 Indians 88.9% 87.1% 27.8% 27.4% 0.4% 9.4% 0.395 -0.007
87 Edgar Santana 3.58 Pirates 88.9% 92.5% 28.1% 20.9% 7.2% 3.6% 0.432 -0.083
88 Collin McHugh 1.20 Astros 88.6% 89.5% 26.3% 33.3% -7.0% 6.0% 0.415 -0.135
89 Steve Cishek 1.88 Cubs 88.6% 77.7% 22.6% 29.3% -6.8% 11.2% 0.337 -0.097
90 Juan Nicasio 5.34 Mariners 88.4% 90.2% 26.0% 31.4% -5.4% 1.7% 0.423 0.064
91 Yoshihisa Hirano 1.55 Diamondbacks 88.0% 85.6% 25.5% 25.0% 0.5% 8.3% 0.398 -0.115
92 Kyle Crick 3.27 Pirates 87.9% 73.6% 19.3% 21.0% -1.7% 13.0% 0.319 -0.017
93 Nick Vincent 4.09 Mariners 87.8% 94.8% 29.1% 23.7% 5.4% 6.2% 0.461 -0.061
94 Mychal Givens 4.36 Orioles 87.5% 74.7% 22.1% 27.4% -5.3% 12.3% 0.331 0.010
95 Wandy Peralta 4.66 Reds 87.4% 85.2% 25.4% 15.3% 10.1% 17.5% 0.403 -0.097
96 Trevor Hildenberger 2.41 Twins 87.3% 98.1% 28.3% 19.7% 8.6% 5.1% 0.490 -0.066
97 Chasen Bradford 1.75 Mariners 87.1% 85.4% 25.5% 19.8% 5.7% 5.9% 0.408 -0.075
98 Tyler Glasnow 4.89 Pirates 86.6% 79.5% 25.4% 29.4% -4.0% 11.8% 0.375 0.010
99 Edubray Ramos 0.75 Phillies 86.6% 78.5% 24.3% 28.7% -4.4% 10.6% 0.369 -0.068
100 Jordan Hicks 2.06 Cardinals 86.5% 68.6% 20.2% 19.7% 0.5% 13.4% 0.304 -0.119

 

Keep in mind this is just a reflection of how well they are pitching, which is only half the battle when it comes to relief pitchers in fantasy baseball.  I’d recommend using a resource like Closer Monkey to help keep tabs on the ever-changing bullpen role situations, to complement this data.

 

#1 Josh Hader (SP, Milwaukee Brewers)

In my previous bullpen update, Hader had already made a name for himself by striking out over sixty (!!) percent of batters in April.  My model showed some serious regression incoming on that strikeout rate, but also that he was clearly elite as the #5 overall ranked reliever.  Now, over a month later, he has taken over the top overall spot.  This shouldn’t come as a huge surprise, as his breakout this year is well documented.  Part of this is his outstanding work limiting hard contact, with the league-best xSLG rate of just .200.  Some of the other top guys from the previous update have fallen off the pace slightly as well, to explain his upward movement.  But we need to recognize that Hader’s strikeout stuff has simply been the best in baseball.  The drop in his strikeout rate which I predicted very much has happened, dropping about 10 percent.  But when it’s the difference between sixty percent and fifty percent, does it really matter?  That is such a crazy good strikeout rate, that even with heavy regression baked in, he still rates as the top strikeout pitcher in MLB.  This is an important lesson in context – you don’t necessarily always want to sell the players with the largest discrepancies.  With a combination of league-best strikeout skills, and the lowest xSLG value, I won’t hesitate at all to proclaim that Hader has been the best qualified reliever in MLB so far.

 

#6 Jose LeClerc (RP, Texas Rangers)

Isn’t it fun when you don’t recognize a name in the top 10?   LeClerc is unlikely to be getting saves any time soon, but the numbers say he has easily been the best reliever in Texas this year.  The signs were there in last season’s numbers – his plate discipline metrics were quite good in 2017, but he was hit very hard.  This year, he has seemed to turn things around as far as contact management.  His xSLG is the second best in MLB, behind only Hader.  The strikeout stuff has remained solid.  His main weakness is clearly the walk rate, which is an ugly 14%.  That could easily come down, as most pitchers with a similar O-Swing% are more in the 10% range.  Or, you know, it might not, because walks are unpredictable.

LeClerc is a two-pitch guy, fairly standard for a reliever.  He throws a 4-seam fastball and a splitter, each roughly half the time.  The fastball is average, but the splitter has been an extremely effective pitch for him.  That splitter has a contact rate under 50%, and batters are putting an wRC+ of -2 against it.

Unfortunately, he isn’t even listed on the Closer Monkey depth chart, so it seems incredibly unlikely that he will get any save chances.  This season looks to be pretty disappointing for Ranger fans, but at least there may be a bright spot or two.  At age 24, LeClerc should be working himself into the “closer of the future” discussion.

 

#12 Adam Ottavino (RP, Colorado Rockies)

Ottavino has similarities to both guys mentioned above.  Like Hader, he’s clearly been over-performing, but has also been quite good.  Like LeClerc, he is pitching the best on his team’s bullpen, but is unlikely to be getting saves.  He’s currently injured, but due back very soon.  He seems like someone worth keeping an eye on.

Judging by ERA, FIP, and SIERA, Ottavino has been a top 5 reliever in MLB so far on the strength of his 45% strikeout rate.  But really, the metrics see him more as top-15.  The discrepancy in his strikeout rate is by far the largest in MLB.  To illustrate, that 45% is the 2nd best in all of MLB, but in comparison his predicted strikeout rate (30%) would only rank 23rd in MLB.  That’s a pretty huge difference.  He also owes a lot of success to suppressing contact at an elite level.  He’s gotten a bit lucky on his SLG, as reported by StatCast, which seems unlikely to continue especially pitching in Coors.

Taken all together, it’s an interesting case.  These numbers clearly say “sell high” – but that would assume he had value in the first place.  As an injured middle reliever, that’s just not really the case.  But I will certainly be keeping an eye on him once he is back.  If he comes back clean and continues pitching at a top-15 level, he’d probably be next in line should anything happen to Wade Davis, and would make a pretty decent closer even with quite a bit of regression.

 

#16 Reyes Moronta (RP, San Francisco Giants)

As a Giants fan, it’s nice to see some names moving up the list.  In my previous update, their bullpen unit overall graded out quite poorly.  Moronta, a rookie, has been their best (qualified) reliever so far by the metrics.  He owes his success equally to both sides of things – looking solidly above average at strikeout skill as well as contact management.  Walks are his weakness, but like LeClerc, I feel his walk rate is more likely to fall than rise based on his O-Swing%.

Moronta gets it done with the typical fastball-slider combination often seen in relievers.  They both seem like strong offerings, with even the fastball generating a very low wRC+ allowed of just 53.  That is quite good for a fastball, which typically generate results closer to 100 (league average).  Fastballs often serve to set up the other, deadlier pitches, so by themselves the fastball numbers tend to look relatively pedestrian.  In Moronta’s case the fastball looks good, but the general pattern holds true as the slider is even better.  The slider allows an wRC+ of just 11, and carries a 46% strikeout rate compared to 17% on the fastball.  He seems to be consistently executing the strategy of setting batters up with the fastball, and finishing them with the slide piece.

Like a lot of the other guys I’ve talked about, Moronta is very unlikely to be seeing any save chances this year.  But at age 25, it’s possible he could be a valuable piece of this bullpen unit for years to come.

 

TEAM BULLPEN RANKINGS

Rank Team ERA Pitcher Score PD Score Predicted K% Actual K% K% Difference BB% xSLG SLG-xSLG
1 Yankees 2.97 93.8% 96.4% 30.6% 32.7% -2.2% 9.5% 0.392 -0.059
2 Brewers 2.68 92.2% 89.2% 27.6% 28.4% -0.8% 9.7% 0.365 -0.022
3 Astros 2.94 91.6% 91.5% 27.1% 28.8% -1.8% 6.5% 0.389 -0.033
4 Mariners 3.63 91.6% 92.7% 28.2% 27.4% 0.8% 7.8% 0.397 -0.027
5 Braves 3.88 91.4% 90.4% 28.0% 24.3% 3.7% 11.7% 0.384 -0.016
6 Cubs 2.69 91.3% 85.6% 25.3% 25.1% 0.2% 11.6% 0.353 -0.058
7 Red Sox 3.02 90.3% 86.2% 25.3% 26.6% -1.4% 9.2% 0.371 -0.021
8 Dodgers 3.97 89.0% 84.7% 25.1% 23.2% 1.9% 9.1% 0.378 0.015
9 Phillies 3.91 89.0% 88.4% 26.8% 24.4% 2.4% 9.0% 0.403 -0.022
10 Padres 3.22 87.7% 84.9% 25.0% 24.9% 0.1% 8.0% 0.396 -0.045
11 Athletics 3.47 86.3% 86.7% 25.7% 21.7% 4.0% 9.0% 0.428 -0.031
12 Blue Jays 3.97 85.6% 82.9% 23.9% 22.6% 1.3% 8.9% 0.412 0.019
13 Giants 3.88 85.6% 82.3% 24.2% 22.3% 1.9% 8.8% 0.408 -0.030
14 Orioles 4.32 85.2% 82.8% 24.2% 20.5% 3.7% 10.9% 0.416 -0.013
15 Rangers 3.73 84.7% 81.8% 23.4% 20.9% 2.5% 8.0% 0.416 -0.029
16 White Sox 3.85 84.0% 81.1% 24.4% 23.5% 0.9% 9.8% 0.420 -0.015
17 Nationals 3.74 83.9% 80.4% 23.7% 24.8% -1.1% 8.1% 0.417 -0.025
18 Rays 3.81 83.9% 80.4% 22.5% 22.0% 0.5% 8.2% 0.417 -0.045
19 Reds 3.97 83.6% 81.1% 23.4% 21.3% 2.1% 10.3% 0.426 -0.036
20 Pirates 4.60 83.5% 81.4% 24.3% 24.2% 0.1% 9.6% 0.429 -0.022
21 Angels 3.62 83.2% 78.4% 22.8% 23.9% -1.2% 9.8% 0.413 -0.002
22 Twins 4.08 83.0% 85.9% 25.0% 23.0% 2.0% 7.8% 0.466 -0.034
23 Rockies 5.22 82.7% 78.9% 23.4% 22.9% 0.5% 10.2% 0.423 0.008
24 Tigers 4.51 82.7% 80.1% 23.4% 20.9% 2.5% 9.8% 0.432 -0.013
25 Diamondbacks 2.55 82.3% 77.2% 21.3% 21.6% -0.4% 8.2% 0.417 -0.077
26 Cardinals 4.47 81.9% 77.6% 22.5% 21.9% 0.5% 10.1% 0.426 -0.004
27 Indians 5.61 81.7% 83.4% 24.2% 22.9% 1.3% 8.0% 0.467 0.019
28 Mets 4.51 81.6% 77.0% 22.6% 23.1% -0.6% 9.9% 0.425 0.005
29 Marlins 5.22 78.3% 74.1% 21.3% 21.3% -0.1% 10.5% 0.450 -0.017
30 Royals 5.55 76.2% 74.0% 20.2% 18.0% 2.2% 9.3% 0.477 -0.010

 

First of all, you should notice that the K% discrepancies are much, much smaller than for individual pitchers.  This is exactly what we should expect if this whole theory has any merit.  Bullpens collectively have just thrown a lot more innings, and include many different pitchers.  With more data points the outliers have simply had more chances to work themselves out.  In fact all bullpens are over 200 IP now, so these numbers represent more than a full starter’s season for each team.

The next thing I noticed was just how SLG-xSLG seems negative almost across the board.  In fact, the SLG-xSLG number MLB-wide is currently -22.  My best guess to explain this is simply the calendar year.  We’ve only played the two coldest months of the year, with the warmest months to come.  Baseballs travel further in warm air, which is less dense.  So it makes a lot of sense that SLG would be reduced in the coldest months relative to StatCast predicted outputs, which presumably are averaged across the whole season.  I suspect we’ll see some large positive values in this column come July/August.  That summer correction could be harsher on teams with the largest discrepancies here, like the Yankees, D-Backs and Cubs.

 

NEW YORK YANKEES

In my first bullpen update the Yankees ranked first overall, and over a month later they still hold onto that spot.  But there appears to be less of a margin separating them from the rest of the pack now.   It seems that incorporating contact management has brought them back down to Earth.  This makes sense, considering their reputation is all about the strikeouts.  And on that front, they still do lead the league by several points.  On the contact management side, they are still good, ranking in the top 1/3rd of teams, but not elite.

Of the individuals pitchers, Chad Green and Dellin Betances both seem worth discussing further, as they are showing some cracks in the veneer.  Betances has been over-performing on strikeouts very significantly, with a -12% difference.  While a pitcher score of 100 is still very good, it’s not as dominant as his reputation suggests.  Green also managed to establish himself as a premiere reliever last year on the strength of a 40% K rate.  The metrics, however, pointed more towards a 30% rate, which is much more in line with what he’s doing this year.  So how does he have an ERA of 1.9 with just an average Pitcher Score?  I think it could have a lot to do with that -150 SLG-xSLG value.

Overall the Yankees unit still looks pretty solid. But I do wonder if the warmer summer months coming up will be harsher on them than most other teams.

 

TORONTO BLUE JAYS

Most teams haven’t really moved around the list a whole lot, but the Blue Jays fell all the way from #2 to #12.  By xSLG, the Blue Jays rate almost exactly average, so that’s certainly a part of the fall from grace.  But it also probably has a lot to do with losing their best reliever to administrative leave as he awaits trial for assault.  Osuna was the anchor on that bullpen, compiling more WAR than the 2nd place guy (Tepera) in less than half of the innings.  With him gone, they haven’t had any dominant relief pitching.  Tepera and Clippard have been very good, and the rest of the unit above average as well, but bullpens need some truly dominant guys if they want to stay atop the rankings in today’s MLB.

 

DETROIT TIGERS

Like the Blue Jays, the Tigers have fallen precipitously down the list, all the way from #10 down to #24.  Unlike the Blue Jays, the reason seems to be more related to incorporating contact management.  The Tigers have the 5th worst xSLG mark in MLB at .432.  This seems like a pretty straightforward case of “they were never that great to begin with…come on, it’s the Tigers”.  But actually, something is going on with their strikeouts as well as the contact management.  Their PD score has dropped over 5 points as a unit since the last update, which is just measuring strikeout ability.

Looking into this a bit further, it seems mostly due to two factors.  First, Buck Farmer fell back down to Earth after a blistering start, with his PD score falling from 102 to 88 since the last update.  Secondly, Drew VerHagen who had been racking up a lot of strikeouts in April was demoted to AAA due to giving up a lot of hard contact.  The Tigers do have one dominant reliever in Joe Jimenez, but the rest of the group looks pretty bad.

 

SAN FRANCISCO GIANTS

Time for some good news.  The Giants have risen the most of any team, jumping from #26 all the way up to #13.  Part of this is certainly related to the emergence of Reyes Moronta, whom I covered above.  Incorporating the StatCast data also helped the Giants, as they have an average xSLG mark.  Another factor in their rise has been the very successful returns of Will Smith and Marc Melancon from their injuries.  Both of those guys have been putting up sterling metrics since their return, albeit in small samples.

Hunter Strickland continues to be a solid closer, and a guy you can (kinda) trust despite the low grades, which I explained last time.  Tony Watson has been quietly excellent as well.  Between him & Smith on the left, and Strickland, Moronta and Melancon from the right, that gives them five pretty solid options.  The rest of the unit isn’t terrible either.  If Smith and Melancon stay healthy, this could actually be a strength for the Giants.

Chaz Steinberg http://reddit.com/u/chazzy_cat

Third generation Giants fan, begrudging Kershaw admirer, and lover of Taco Bell

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Comments


Chaz Steinberg

Reed is down around #150. His strikeout stuff has fallen off this year, and the metrics are in line with that (PD score of 80). He’s also putting up a terrible xSLG mark (bottom 10 of qualifed RP).

Chaz Steinberg

Bradley is down in the same area as Reed, ranked #141. Honestly his metrics look pretty bad so far this year relative to expectations. His strikeout rate has fallen 4% since last year, but even still he is over-performing substantially with a “K% difference” of -8%. Batters are just making a lot more contact against him. It’s possible he’s doing this on purpose – pitching to contact more, now that they’ve installed the humidor at Chase. And indeed checking the splits, his road SLG is much much closer to his xSLG than his home SLG.

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