Starting Pitcher Metrics – Updated Rankings and Analysis

(Photo by Kevin Abele/Icon Sportswire)

Welcome back to my series on pitching metrics.  This week, I’m going back to my regular style of updates.  This includes updated rankings, analysis of several individual pitchers, and a new table: PD scores for just the past 30 days.  Last week, we discovered that the majority of strikeout outliers work themselves out in two moths of data, and so it can be helpful to look at smaller sample sizes.

Without further ado, here are the updated rankings:

 

TABLE A – QUALIFIED STARTERS

Rank Name ERA Pitcher Score Previous Score Score Change PD Score Predicted K% Actual K% K% Difference BB% xSLG SLG-xSLG 1 Max Scherzer 1.95 105.9% 101.4% 4.5% 111.7% 35.6% 39.4% -3.8% 5.6% 0.333 -0.025 2 Jacob deGrom 1.49 105.5% 104.3% 1.2% 103.0% 31.4% 33.9% -2.5% 7.3% 0.280 -0.017 3 Justin Verlander 1.24 98.9% 99.2% -0.3% 91.2% 26.8% 31.9% -5.1% 5.2% 0.289 -0.041 4 Noah Syndergaard 3.06 98.8% 98.8% 0.0% 99.1% 30.6% 28.3% 2.3% 4.8% 0.343 0.021 5 Chris Sale 3.00 98.8% 100.3% -1.5% 102.3% 32.1% 34.0% -2.0% 6.5% 0.365 -0.015 6 Patrick Corbin 2.87 96.4% 98.1% -1.7% 98.7% 29.8% 32.7% -3.0% 6.9% 0.372 -0.048 7 Gerrit Cole 2.20 95.4% 96.3% -0.9% 94.1% 29.8% 38.2% -8.4% 6.6% 0.356 -0.045 8 Aaron Nola 2.18 93.3% 93.4% -0.1% 85.3% 24.1% 24.9% -0.9% 6.1% 0.325 -0.055 9 Blake Snell 2.36 93.1% 91.0% 2.1% 91.1% 27.9% 29.5% -1.7% 7.7% 0.366 -0.042 10 Charlie Morton 2.84 91.5% 94.9% -3.4% 86.8% 26.8% 31.2% -4.5% 7.8% 0.359 0.019 11 Trevor Bauer 2.77 91.4% 89.8% 1.6% 90.5% 27.3% 29.6% -2.4% 8.5% 0.384 -0.054 12 Sean Newcomb 2.49 91.0% 92.0% -1.0% 77.3% 22.3% 24.2% -2.0% 11.7% 0.302 -0.019 13 James Paxton 2.95 90.6% 91.1% -0.6% 90.2% 26.5% 30.9% -4.5% 7.7% 0.394 -0.058 14 Lance McCullers Jr. 3.89 90.1% 92.0% -1.9% 88.7% 26.6% 25.5% 1.1% 9.6% 0.390 -0.038 15 Masahiro Tanaka 4.79 90.0% 90.3% -0.3% 98.5% 28.9% 23.4% 5.5% 6.5% 0.456 -0.005 16 Luis Severino 2.20 89.7% 87.8% 1.9% 88.1% 25.7% 30.5% -4.9% 6.3% 0.391 -0.109 17 Vince Velasquez 3.82 89.6% 88.2% 1.4% 82.8% 25.4% 29.2% -3.9% 8.1% 0.357 0.063 18 Jon Gray 5.68 89.6% 88.8% 0.8% 88.4% 27.4% 26.2% 1.2% 6.6% 0.395 0.058 19 Jose Berrios 3.86 89.2% 89.1% 0.1% 86.7% 23.8% 25.1% -1.3% 4.8% 0.388 -0.026 20 Kyle Gibson 3.54 88.6% 89.6% -1.0% 87.8% 26.4% 25.5% 0.9% 10.5% 0.404 -0.061 21 Carlos Carrasco 4.50 88.3% 89.1% -0.8% 92.8% 26.8% 23.4% 3.4% 6.1% 0.442 -0.031 22 Luis Castillo 5.64 87.3% 88.4% -1.1% 96.3% 30.2% 22.0% 8.2% 8.9% 0.478 -0.003 23 Alex Wood 4.48 86.9% 87.8% -0.9% 87.2% 24.0% 22.6% 1.4% 4.9% 0.423 -0.030 24 Dylan Bundy 4.46 86.8% 86.8% 0.0% 100.1% 29.9% 28.3% 1.6% 6.8% 0.510 -0.016 25 Gio Gonzalez 2.27 86.7% 86.0% 0.7% 77.8% 22.2% 24.2% -2.0% 9.4% 0.362 -0.025 26 Corey Kluber 1.96 86.7% 85.6% 1.1% 82.6% 22.7% 27.5% -4.9% 2.9% 0.395 -0.067 27 Caleb Smith 4.03 86.2% 87.6% -1.4% 84.3% 24.4% 29.6% -5.2% 11.2% 0.413 -0.055 28 Mike Clevinger 3.36 86.1% 86.5% -0.4% 83.0% 23.6% 20.5% 3.1% 8.3% 0.405 -0.023 29 Jameson Taillon 3.97 85.8% 84.8% 1.0% 78.2% 20.1% 22.1% -2.0% 6.6% 0.377 -0.013 30 Tyler Skaggs 3.27 85.5% 85.1% 0.4% 82.9% 23.9% 25.1% -1.3% 7.9% 0.413 -0.031 31 Tyler Anderson 5.07 85.4% 86.5% -1.1% 83.2% 24.7% 20.4% 4.3% 9.6% 0.416 0.073 32 Rick Porcello 3.59 84.9% 85.4% -0.5% 75.2% 19.4% 22.3% -3.0% 5.0% 0.369 -0.007 33 Matt Boyd 3.23 84.8% 86.3% -1.5% 75.7% 21.8% 18.6% 3.2% 8.5% 0.374 -0.057 34 J.A. Happ 4.08 84.6% 86.4% -1.8% 81.4% 24.1% 30.0% -5.9% 6.9% 0.415 -0.038 35 Zack Greinke 3.44 84.5% 86.2% -1.7% 89.7% 25.4% 26.6% -1.3% 3.8% 0.471 -0.047 36 Tyson Ross 3.31 84.2% 85.2% -1.0% 79.0% 21.8% 24.0% -2.2% 8.8% 0.404 -0.054 37 Stephen Strasburg 3.20 84.2% 82.8% 1.4% 85.3% 24.7% 29.3% -4.6% 6.0% 0.446 -0.068 38 Nick Pivetta 3.48 84.0% 83.6% 0.4% 81.8% 23.3% 27.6% -4.4% 6.7% 0.425 -0.079 39 Kevin Gausman 4.63 83.7% 84.1% -0.4% 89.9% 26.6% 22.2% 4.4% 5.6% 0.483 -0.006 40 Mike Foltynewicz 2.22 83.4% 81.4% 2.0% 71.4% 20.8% 28.2% -7.4% 10.6% 0.364 -0.040 41 German Marquez 4.38 83.1% 80.6% 2.5% 72.4% 20.8% 21.8% -1.0% 9.5% 0.374 0.056 42 Chris Archer 4.24 83.0% 83.4% -0.4% 86.4% 26.4% 23.7% 2.7% 8.1% 0.469 -0.050 43 Tanner Roark 3.38 82.5% 82.9% -0.4% 76.5% 20.9% 21.2% -0.3% 8.3% 0.410 -0.062 44 Cole Hamels 3.63 82.4% 82.0% 0.4% 87.5% 25.6% 23.7% 1.9% 8.7% 0.484 -0.044 45 Clayton Richard 4.67 81.7% 81.4% 0.3% 77.0% 21.4% 19.4% 2.0% 7.9% 0.424 -0.008 46 Jakob Junis 3.62 81.5% 79.3% 2.2% 79.5% 21.4% 22.8% -1.4% 5.8% 0.443 -0.034 47 Miles Mikolas 2.49 81.3% 81.1% 0.2% 76.4% 18.5% 18.5% 0.0% 2.8% 0.425 -0.073 48 Dallas Keuchel 4.13 81.3% 82.8% -1.5% 73.9% 19.1% 18.6% 0.4% 6.5% 0.409 0.014 49 Michael Fulmer 4.73 80.8% 81.6% -0.8% 81.5% 22.1% 19.4% 2.7% 9.5% 0.466 -0.048 50 Kyle Freeland 3.48 80.8% 82.0% -1.2% 73.0% 19.3% 20.7% -1.4% 7.4% 0.410 -0.013 51 Jake Arrieta 2.66 80.5% 80.1% 0.4% 64.7% 14.7% 17.2% -2.5% 7.4% 0.358 -0.030 52 Luke Weaver 4.41 79.7% 82.1% -2.4% 73.3% 20.3% 21.5% -1.2% 7.6% 0.426 -0.052 53 Michael Wacha 2.41 79.3% 76.9% 2.4% 74.5% 22.1% 21.3% 0.8% 9.4% 0.439 -0.162 54 Jhoulys Chacin 3.39 79.1% 78.1% 1.0% 70.7% 19.4% 17.2% 2.2% 10.0% 0.417 -0.067 55 Jose Urena 4.60 78.6% 77.7% 0.9% 74.5% 19.2% 19.6% -0.4% 5.8% 0.448 -0.039 56 Jake Odorizzi 4.14 78.6% 79.5% -0.9% 82.0% 23.7% 22.6% 1.1% 9.6% 0.498 -0.002 57 James Shields 4.40 78.5% 77.3% 1.2% 75.7% 21.4% 16.3% 5.1% 9.3% 0.458 -0.108 58 Chad Bettis 4.02 78.4% 78.4% 0.0% 74.1% 20.2% 16.0% 4.2% 7.5% 0.448 -0.034 59 Kyle Hendricks 3.59 78.4% 76.8% 1.6% 76.8% 20.6% 19.3% 1.3% 5.7% 0.467 -0.047 60 Jon Lester 2.44 78.1% 76.4% 1.7% 76.3% 21.8% 21.2% 0.6% 8.7% 0.467 -0.106 61 David Price 4.08 78.0% 77.8% 0.2% 71.3% 19.1% 23.3% -4.3% 9.5% 0.435 -0.052 62 Zack Godley 5.12 78.0% 79.5% -1.5% 79.8% 23.8% 21.0% 2.8% 11.2% 0.492 -0.051 63 Julio Teheran 4.31 77.7% 84.3% -6.6% 77.2% 21.8% 18.9% 2.9% 11.1% 0.478 -0.022 64 Jose Quintana 4.30 77.7% 76.8% 0.9% 68.2% 18.2% 22.4% -4.2% 11.4% 0.419 0.007 65 Marco Gonzales 3.38 77.6% 76.7% 0.9% 71.6% 17.2% 21.4% -4.2% 6.2% 0.443 -0.047 66 Aaron Sanchez 4.48 77.4% 75.9% 1.5% 77.1% 22.3% 17.8% 4.5% 12.8% 0.482 -0.081 67 Reynaldo Lopez 3.42 76.7% 75.6% 1.1% 68.9% 19.4% 16.3% 3.1% 10.5% 0.436 -0.075 68 Tyler Mahle 4.38 75.6% 75.7% -0.1% 74.1% 20.9% 22.3% -1.4% 8.8% 0.486 -0.008 69 Sean Manaea 3.59 74.1% 76.6% -2.5% 76.4% 20.3% 17.6% 2.7% 5.5% 0.521 -0.142 70 Daniel Mengden 2.91 74.0% 73.4% 0.6% 71.4% 17.7% 16.2% 1.5% 2.7% 0.489 -0.129 71 Trevor Williams 3.84 73.5% 72.6% 0.9% 64.9% 15.9% 16.9% -1.1% 7.9% 0.453 -0.066 72 Brandon McCarthy 4.83 73.1% 72.8% 0.3% 62.3% 14.1% 18.8% -4.8% 6.9% 0.440 0.024 73 Marco Estrada 5.29 72.7% 71.2% 1.5% 74.2% 19.8% 17.3% 2.5% 6.1% 0.526 0.017 74 Felix Hernandez 5.33 72.6% 70.5% 2.1% 67.0% 16.7% 19.1% -2.5% 8.9% 0.479 -0.053 75 Derek Holland 4.91 71.1% [Unranked] [Unranked] 66.7% 18.0% 20.0% -2.0% 9.4% 0.497 -0.042 76 Ivan Nova 4.96 71.0% 71.0% 0.0% 73.7% 19.2% 17.6% 1.6% 3.8% 0.545 -0.059 77 Jason Hammel 5.17 70.8% 72.6% -1.8% 74.4% 19.0% 14.7% 4.3% 6.4% 0.552 -0.101 78 Chris Stratton 4.50 70.1% 69.1% 1.0% 66.2% 17.9% 20.2% -2.3% 10.3% 0.507 -0.074 79 Chad Kuhl 3.86 69.6% 69.6% 0.0% 69.1% 20.3% 22.0% -1.7% 8.7% 0.532 -0.080 80 Danny Duffy 5.81 68.9% 69.3% -0.4% 71.9% 19.3% 17.1% 2.2% 10.8% 0.560 -0.049 81 Lucas Giolito 7.08 68.5% 68.5% 0.0% 61.8% 17.5% 11.0% 6.5% 13.8% 0.499 -0.044 82 Mike Leake 4.71 68.2% 67.3% 0.9% 70.5% 16.1% 15.4% 0.7% 5.3% 0.560 -0.092 83 Andrew Cashner 5.02 67.6% 65.8% 1.8% 66.0% 16.8% 19.3% -2.5% 10.6% 0.539 -0.015 84 Homer Bailey 6.68 62.1% 62.1% 0.0% 64.2% 15.8% 13.0% 2.8% 8.2% 0.600 -0.036

TABLE B – NON-QUALIFIED STARTERS (minimum 10 IP)

Name IP ERA Pitcher Score PD Score Predicted K% Actual K% K% Difference xSLG SLG-xSLG Mike Montgomery 11.2 0.8 99.7% 94.4% 24.8% 22.0% 2.8% 0.300 -0.125 Shohei Ohtani 49.1 3.1 97.3% 99.1% 34.0% 30.5% 3.5% 0.363 -0.044 Ross Stripling 38.0 1.9 96.0% 83.5% 22.9% 32.2% -9.3% 0.277 0.065 Kenta Maeda 51.1 3.7 95.0% 94.9% 28.7% 30.3% -1.7% 0.366 0.037 Domingo German 27.0 6.3 90.8% 92.3% 28.3% 22.4% 5.9% 0.405 -0.015 Johnny Cueto 32.0 0.8 89.8% 76.2% 22.3% 22.2% 0.0% 0.311 -0.105 Eduardo Rodriguez 66.0 3.7 89.8% 84.7% 24.4% 27.6% -3.3% 0.368 -0.009 Trevor Cahill 48.2 2.8 89.2% 92.2% 28.5% 25.0% 3.5% 0.425 -0.072 John Gant 15.0 6.0 89.2% 90.3% 26.8% 29.2% -2.4% 0.413 -0.057 Carlos Martinez 54.0 1.8 88.9% 72.8% 19.5% 22.8% -3.3% 0.300 -0.055 Robbie Ray 27.2 4.9 88.7% 92.1% 30.1% 36.3% -6.3% 0.432 -0.013 Walker Buehler 46.0 2.7 88.4% 72.5% 19.7% 27.2% -7.6% 0.305 -0.021 Andrew Heaney 60.2 3.1 88.2% 86.1% 24.9% 23.6% 1.3% 0.398 -0.057 Garrett Richards 61.0 3.3 88.0% 83.8% 26.1% 26.9% -0.8% 0.385 -0.050 Joe Musgrove 19.0 1.9 87.7% 77.9% 20.8% 21.8% -1.0% 0.350 0.025 Jordan Montgomery 27.1 3.6 87.5% 79.9% 21.5% 19.8% 1.7% 0.366 -0.010 Hyun-Jin Ryu 29.2 2.1 87.1% 79.3% 24.8% 31.3% -6.5% 0.367 -0.059 Nathan Eovaldi 11.0 3.3 86.9% 73.3% 17.1% 20.0% -3.0% 0.330 -0.093 Jaime Barria 36.1 2.5 86.1% 90.1% 24.8% 20.4% 4.4% 0.452 -0.111 Jack Flaherty 39.1 3.2 85.9% 79.6% 23.6% 26.1% -2.5% 0.385 -0.038 CC Sabathia 57.2 3.6 85.6% 78.7% 20.9% 18.0% 2.9% 0.384 0.035 Frankie Montas 14.0 0.6 84.5% 60.4% 14.9% 17.0% -2.2% 0.276 -0.026 Clayton Kershaw 49.0 2.8 84.0% 82.2% 23.1% 26.5% -3.5% 0.428 -0.036 Nick Kingham 29.0 4.0 83.8% 83.0% 24.5% 25.4% -0.9% 0.436 -0.043 Austin Bibens-Dirkx 11.0 6.6 83.5% 93.1% 25.6% 20.8% 4.8% 0.508 -0.018 Fernando Romero 36.1 4.0 83.4% 82.6% 25.0% 21.5% 3.5% 0.439 -0.059 Blaine Hardy 28.1 3.8 83.2% 71.7% 18.2% 15.4% 2.8% 0.368 0.001 Jason Vargas 30.1 7.7 82.8% 84.7% 23.5% 18.8% 4.7% 0.461 0.070 Yu Darvish 40.0 5.0 82.7% 78.2% 24.1% 27.2% -3.2% 0.418 0.007 Dylan Covey 22.1 2.8 82.7% 67.3% 17.7% 21.2% -3.5% 0.346 -0.065 Anibal Sanchez 22.0 2.5 81.7% 76.2% 18.2% 21.4% -3.3% 0.418 -0.005 Michael Soroka 14.2 3.7 81.6% 87.8% 25.4% 21.7% 3.7% 0.498 -0.054 Wade LeBlanc 35.1 2.3 81.5% 77.1% 18.0% 18.2% -0.2% 0.427 -0.102 Nick Tropeano 49.2 4.4 81.4% 85.0% 26.0% 20.5% 5.5% 0.481 -0.019 Jordan Lyles 34.0 5.3 81.2% 76.2% 19.7% 21.8% -2.1% 0.425 0.064 Zack Wheeler 63.0 4.6 80.9% 76.7% 20.6% 22.4% -1.8% 0.432 -0.028 Sam Gaviglio 24.1 2.6 80.2% 84.3% 21.8% 20.8% 0.9% 0.492 -0.007 Jeremy Hellickson 43.1 2.3 80.0% 77.3% 20.5% 20.7% -0.3% 0.448 -0.087 Joey Lucchesi 47.1 3.2 80.0% 78.4% 23.6% 24.9% -1.4% 0.456 -0.033 Hector Velazquez 10.2 2.5 80.0% 91.4% 23.4% 22.7% 0.6% 0.543 -0.091 Ryan Yarbrough 14.2 4.9 79.0% 60.9% 15.1% 20.3% -5.3% 0.352 0.041 Lance Lynn 56.0 5.5 78.7% 73.5% 20.2% 21.3% -1.2% 0.441 -0.012 Junior Guerra 60.1 2.8 78.6% 73.5% 20.8% 22.7% -2.0% 0.442 -0.093 Sonny Gray 63.2 4.8 78.5% 72.6% 21.3% 20.4% 0.9% 0.437 -0.008 Yonny Chirinos 22.2 4.4 78.3% 75.9% 20.1% 21.0% -0.9% 0.462 -0.043 David Hess 23.1 3.5 78.0% 75.7% 18.4% 12.6% 5.8% 0.465 0.007 Wei-Yin Chen 35.1 5.9 77.6% 67.5% 17.1% 16.3% 0.8% 0.416 0.122 Brent Suter 56.2 4.8 77.4% 77.2% 20.1% 19.7% 0.4% 0.483 -0.014 Clay Buchholz 24.0 1.9 77.2% 77.5% 20.6% 22.8% -2.2% 0.487 -0.195 Jordan Zimmermann 31.1 4.9 76.3% 78.0% 20.6% 23.7% -3.2% 0.503 -0.047 Steven Matz 52.2 3.4 76.0% 62.3% 18.3% 21.7% -3.4% 0.402 -0.001 Jaime Garcia 47.1 6.1 76.0% 72.2% 20.2% 20.5% -0.4% 0.468 0.061 Matt Moore 52.0 7.6 75.7% 76.6% 20.7% 15.7% 5.0% 0.501 0.040 Trevor Richards 23.2 4.9 75.7% 70.9% 19.7% 22.4% -2.7% 0.463 -0.019 Francisco Liriano 57.2 3.9 75.7% 80.7% 24.3% 19.2% 5.1% 0.529 -0.156 Zach Eflin 33.2 3.7 75.5% 69.8% 20.3% 21.5% -1.3% 0.459 -0.032 Tyler Chatwood 53.2 4.0 75.3% 62.4% 17.6% 19.2% -1.6% 0.412 -0.080 Chase Anderson 65.0 4.6 74.8% 68.5% 18.2% 15.9% 2.3% 0.459 -0.018 Luis Perdomo 14.0 8.4 74.4% 68.5% 21.2% 22.1% -0.9% 0.465 0.058 Andrew Triggs 41.1 5.2 73.0% 75.9% 21.4% 23.6% -2.3% 0.533 -0.120 Adam Wainwright 18.0 4.0 72.9% 55.9% 14.0% 17.1% -3.1% 0.400 0.035 Mike Fiers 60.1 4.3 72.6% 71.7% 18.3% 16.1% 2.2% 0.510 -0.004 Zach Davies 43.0 5.2 72.3% 69.1% 18.7% 16.3% 2.4% 0.497 -0.003 Drew Pomeranz 37.0 6.8 72.1% 65.2% 16.7% 20.8% -4.2% 0.473 0.070 Mike Minor 59.1 5.8 71.7% 77.9% 21.4% 20.1% 1.3% 0.563 -0.020 Marcus Stroman 37.1 7.7 71.2% 72.9% 21.2% 18.2% 3.0% 0.537 -0.082 Ty Blach 60.2 4.9 70.9% 60.7% 14.7% 11.1% 3.6% 0.460 -0.047 Matt Harvey 45.1 5.2 70.4% 63.7% 16.2% 18.2% -2.0% 0.486 0.006 Jake Faria 47.2 5.5 70.4% 68.1% 19.0% 18.2% 0.7% 0.516 -0.093 Dillon Peters 24.2 5.8 70.0% 62.0% 16.3% 14.4% 1.9% 0.480 -0.011 Jeff Samardzija 35.2 6.6 69.9% 68.8% 17.7% 15.7% 2.0% 0.527 -0.084 Andrew Suarez 43.2 4.7 69.9% 66.2% 15.8% 23.5% -7.8% 0.510 -0.040 Elieser Hernandez 18.0 4.5 69.2% 70.2% 21.0% 12.5% 8.5% 0.546 0.042 Eric Skoglund 49.2 6.7 69.1% 70.3% 17.3% 18.0% -0.7% 0.548 -0.018 Adam Plutko 18.1 3.9 68.9% 70.6% 16.9% 16.7% 0.2% 0.552 -0.014 Brandon Woodruff 11.2 8.5 68.7% 68.9% 21.2% 17.5% 3.7% 0.543 -0.064 Matt Wisler 17.1 3.6 68.7% 73.6% 20.7% 18.6% 2.1% 0.575 -0.160 Brandon Finnegan 20.2 7.4 68.0% 63.0% 16.0% 13.6% 2.4% 0.513 0.040 Dan Straily 36.0 3.5 67.6% 72.5% 20.2% 17.3% 2.9% 0.582 -0.177 Ben Lively 23.2 6.9 67.2% 62.8% 17.9% 19.1% -1.3% 0.522 0.023 Kendall Graveman 34.1 7.6 67.0% 67.6% 17.1% 17.1% 0.0% 0.557 -0.015 Doug Fister 61.0 4.1 67.0% 56.8% 12.1% 14.2% -2.2% 0.486 -0.035 Ian Kennedy 65.2 5.8 67.0% 70.5% 17.1% 20.5% -3.4% 0.577 -0.051 Alex Cobb 52.1 6.2 66.2% 58.5% 13.6% 13.5% 0.1% 0.507 0.063 Eric Lauer 34.1 6.8 65.9% 55.2% 13.6% 19.1% -5.5% 0.489 0.076 Sal Romano 65.0 6.2 65.9% 57.6% 13.5% 16.2% -2.7% 0.506 -0.010 Daniel Gossett 24.1 5.2 64.9% 66.2% 15.5% 11.8% 3.7% 0.576 -0.081 Brett Anderson 15.1 7.6 64.9% 67.1% 18.0% 11.1% 6.9% 0.582 0.009 Joe Biagini 18.2 7.7 64.9% 65.9% 16.7% 14.4% 2.3% 0.574 -0.080 Steven Brault 26.0 5.5 63.8% 69.2% 20.0% 13.4% 6.6% 0.611 -0.213 Taijuan Walker 13.0 3.5 62.7% 57.6% 15.1% 16.1% -1.1% 0.548 -0.156 Bartolo Colon 66.1 4.3 62.4% 58.8% 11.7% 14.3% -2.6% 0.560 -0.068 Jarlin Garcia 33.0 3.6 61.0% 65.1% 18.0% 16.7% 1.3% 0.620 -0.222 Matt Koch 53.0 3.9 59.9% 62.6% 14.6% 12.9% 1.7% 0.619 -0.149 Hector Santiago 32.1 6.1 59.8% 62.0% 16.5% 15.9% 0.6% 0.616 -0.037 Bryan Mitchell 32.0 6.5 59.3% 47.1% 11.8% 10.4% 1.4% 0.523 -0.027 Rich Hill 24.2 6.2 58.1% 59.4% 16.3% 21.7% -5.5% 0.621 -0.055 Ryan Carpenter 12.0 6.8 57.4% 58.5% 14.9% 10.7% 4.2% 0.624 -0.047 Miguel Gonzalez 12.1 12.4 56.8% 66.3% 15.5% 7.6% 7.9% 0.684 0.099 Josh Tomlin 30.0 8.1 55.9% 73.8% 19.1% 12.9% 6.2% 0.746 -0.019 Carson Fulmer 31.0 8.1 55.3% 56.5% 14.6% 16.6% -2.1% 0.640 -0.136 Martin Perez 22.1 9.7 55.1% 51.8% 11.6% 10.9% 0.6% 0.610 0.060 Chris Tillman 26.2 10.5 51.6% 49.4% 11.9% 9.5% 2.4% 0.641 0.011

TABLE C – RECENT PD METRICS (Last 30 Days – Qualified Starters)

Rank Name PD Score O-Swing% Contact% SwStr% F-Strike% 1 Max Scherzer 118.0% 41.9% 66.6% 18.8% 74.6% 2 Jacob deGrom 106.4% 39.3% 69.1% 16.1% 65.0% 3 Kevin Gausman 103.5% 38.6% 69.7% 15.7% 59.5% 4 Masahiro Tanaka 96.7% 34.9% 71.3% 14.1% 65.2% 5 Chris Sale 96.3% 30.7% 68.4% 14.4% 62.0% 6 Luis Castillo 95.7% 33.7% 70.1% 14.4% 54.1% 7 Dylan Bundy 95.0% 34.7% 72.9% 13.8% 69.0% 8 Trevor Bauer 94.1% 31.8% 70.1% 13.8% 60.7% 9 Aaron Nola 93.7% 32.2% 70.8% 13.4% 65.6% 10 Jose Berrios 93.6% 38.6% 74.2% 12.6% 64.4% 11 Vince Velasquez 92.3% 29.6% 69.6% 13.9% 56.4% 12 Jon Gray 92.1% 28.5% 69.2% 13.2% 66.4% 13 Carlos Carrasco 90.7% 35.0% 74.3% 12.5% 65.9% 14 Ross Stripling 90.5% 33.1% 74.8% 12.4% 78.3% 15 Blake Snell 90.2% 35.4% 73.6% 12.4% 58.1% 16 Patrick Corbin 88.7% 33.8% 73.5% 11.6% 65.5% 17 Kyle Hendricks 88.1% 38.7% 76.7% 10.9% 66.2% 18 Luis Severino 87.8% 31.1% 74.8% 12.4% 71.3% 19 Kyle Gibson 87.7% 32.2% 72.8% 11.9% 59.8% 20 James Paxton 86.7% 37.4% 78.2% 11.5% 66.0% 21 Tyler Skaggs 86.6% 33.1% 73.6% 11.6% 57.1% 22 Zack Greinke 86.2% 34.5% 75.9% 11.1% 67.5% 23 Jameson Taillon 86.1% 37.4% 78.3% 11.2% 66.4% 24 Andrew Heaney 85.5% 30.8% 75.0% 11.7% 68.6% 25 Charlie Morton 84.8% 30.3% 74.0% 11.7% 60.9% 26 Nick Pivetta 84.7% 31.3% 74.8% 11.9% 57.8% 27 Michael Fulmer 84.6% 37.5% 78.1% 10.8% 60.7% 28 Brent Suter 84.1% 31.5% 76.3% 11.5% 67.0% 29 Jakob Junis 83.6% 31.4% 74.9% 11.0% 62.0% 30 Fernando Romero 82.9% 30.1% 74.5% 11.7% 53.3% 31 Clayton Richard 82.8% 33.5% 77.4% 10.9% 63.5% 32 Mike Clevinger 82.4% 33.0% 77.3% 10.7% 65.4% 33 James Shields 82.3% 33.7% 77.7% 10.7% 64.0% 34 Stephen Strasburg 82.3% 30.1% 75.8% 11.1% 64.8% 35 Corey Kluber 82.1% 35.4% 78.2% 10.7% 57.5% 36 Justin Verlander 82.0% 32.9% 77.8% 10.9% 64.3% 37 Jhoulys Chacin 81.7% 29.1% 74.6% 10.9% 61.1% 38 CC Sabathia 81.6% 33.7% 77.4% 10.7% 58.1% 39 Aaron Sanchez 81.1% 31.8% 76.5% 10.6% 60.0% 40 Walker Buehler 79.9% 32.6% 79.3% 10.7% 64.5% 41 Junior Guerra 79.8% 29.0% 76.2% 11.1% 57.8% 42 Gerrit Cole 79.7% 26.9% 75.5% 11.5% 58.3% 43 Michael Wacha 79.4% 30.8% 76.8% 10.7% 54.8% 44 Luke Weaver 79.1% 33.6% 79.0% 9.9% 62.7% 45 Chad Bettis 78.7% 28.8% 77.8% 10.0% 74.8% 46 J.A. Happ 78.6% 29.4% 76.5% 10.4% 58.8% 47 Wade LeBlanc 78.5% 39.8% 82.0% 8.5% 63.9% 48 Zack Wheeler 77.9% 32.0% 79.2% 10.0% 63.2% 49 Jon Lester 77.6% 25.1% 75.1% 11.0% 57.7% 50 Lance McCullers Jr. 77.5% 29.1% 77.2% 10.4% 57.9% 51 Eduardo Rodriguez 77.3% 32.1% 79.8% 9.8% 64.7% 52 Dallas Keuchel 77.3% 34.3% 79.6% 9.2% 60.1% 53 Tyson Ross 77.2% 34.2% 79.3% 9.4% 56.1% 54 Chris Archer 76.3% 27.2% 76.0% 10.4% 52.4% 55 Gio Gonzalez 76.2% 30.5% 77.3% 9.9% 50.0% 56 Jordan Lyles 76.2% 31.0% 80.2% 9.3% 72.1% 57 Miles Mikolas 75.7% 30.6% 81.2% 9.5% 74.6% 58 German Marquez 74.9% 24.2% 76.2% 10.5% 58.5% 59 Zack Godley 74.8% 27.7% 77.2% 9.5% 59.1% 60 David Price 74.5% 27.4% 78.4% 9.8% 62.1% 61 Rick Porcello 74.3% 30.1% 79.8% 9.3% 62.3% 62 Marco Estrada 73.5% 32.6% 82.5% 8.9% 67.0% 63 Tanner Roark 72.4% 27.8% 79.6% 9.2% 62.2% 64 Mike Leake 72.2% 38.9% 86.3% 7.2% 71.8% 65 Sean Newcomb 71.6% 30.9% 80.0% 8.9% 48.5% 66 Zach Eflin 71.4% 24.1% 78.5% 9.9% 58.9% 67 Dan Straily 71.2% 28.4% 80.6% 9.1% 59.0% 68 Trevor Williams 71.1% 34.3% 83.3% 7.9% 61.2% 69 Chad Kuhl 71.0% 24.6% 78.5% 9.4% 60.3% 70 Andrew Cashner 70.7% 33.0% 82.5% 8.0% 58.6% 71 Danny Duffy 70.5% 29.0% 81.5% 8.8% 61.4% 72 Tyler Anderson 70.5% 26.7% 81.0% 9.2% 64.2% 73 Jose Urena 70.2% 32.5% 82.6% 8.2% 56.4% 74 Reynaldo Lopez 69.4% 25.2% 81.5% 9.4% 65.7% 75 Daniel Mengden 69.1% 32.0% 84.5% 7.8% 68.4% 76 Mike Fiers 69.1% 28.0% 82.1% 8.0% 70.6% 77 Jose Quintana 69.0% 28.0% 81.3% 8.0% 65.6% 78 Derek Holland 68.9% 26.4% 80.7% 9.0% 56.8% 79 Jason Hammel 68.5% 27.7% 81.6% 8.3% 61.9% 80 Mike Foltynewicz 67.5% 24.7% 79.5% 8.1% 60.5% 81 Marco Gonzales 67.5% 33.6% 84.8% 6.9% 63.8% 82 Jake Arrieta 66.3% 32.6% 85.6% 7.0% 64.7% 83 Felix Hernandez 66.2% 29.5% 84.1% 7.2% 67.9% 84 Kyle Freeland 66.0% 28.6% 83.6% 7.2% 67.9% 85 Sean Manaea 65.9% 30.4% 84.2% 7.5% 58.9% 86 Julio Teheran 63.9% 25.6% 82.7% 7.1% 65.5% 87 Matt Koch 63.0% 29.4% 86.1% 6.9% 64.5% 88 Alex Cobb 62.9% 27.6% 84.3% 7.2% 58.3% 89 Bartolo Colon 59.3% 32.7% 88.5% 5.2% 61.5% 90 Lucas Giolito 56.4% 22.5% 84.4% 6.4% 53.7% 91 Doug Fister 55.7% 31.5% 89.8% 4.4% 63.2%

 

PLAYER ANALYSIS

Max Scherzer (SP, Washington Nationals)

The last two weeks, Jacob deGrom held the top spot in my rankings, but he’s now been usurped again by Mad Max.  No offense to Kershaw or anyone else, but Scherzer is seriously making the case for himself as the best pitcher in baseball, and he’s doing it the most reliable way – by straight up missing bats.  His Contact% and Swinging Strike rate are both tops among qualified starters, and it’s not even particularly close.  He’s simply been unhittable this year, even moreso than previous years.  His Swinging Strike rate of 18% is the best of his career, by far.  So yes, that 40% K rate is actually very believable.

Looking at his individual pitch data, I wasn’t really expecting to find much to talk about, but to my surprise, Scherzer has a bad pitch! Here is the breakdown of his arsenal this year:

Pitch Type Usage Sw-Str% Contact% wRC+ Allowed Fourseam (FA) 49.8% 15.8% 68.4% 29 Slider (SL) 15.4% 28.3% 50.4% 27 Changeup (CH) 15.1% 18.7% 63.2% 47 Cutter (FC) 12.0% 18.2% 72.0% 133 Curveball (CU) 6.9% 7.4% 80.0% 262

One of them clearly stands out as being far less effective.  And it’s not just a small sample outlier either – his curveball has a negative pitch value over his whole career.  It’s not the biggest deal, considering he’s only throwing it seven percent of the time.  But I do wonder, given how outstanding his other options are, why he feels the need to keep throwing that occasional curve.  Not that it really matters when you’re on track to win the Cy Young…

 

Patrick Corbin (SP, Arizona D-Backs)

I apologize if you are tired of reading about Corbin, but given his continuously high rankings I feel compelled to keep discussing him.  Most of you should be aware of the story about his velocity taking a worrisome downward spike towards the end of April.  But with seven starts under his belt now with that reduced velocity, it seems pretty clear that he’s still very effective.  His metrics from the period with reduced velocity still suggest a strikeout rate in the 25-30 percent range, which is quite good for a strong contact manager.  In fact, over the past 30 days his PD score is still top 20 in MLB of qualified starters, with a B+ grade.  His overall score does show small drops the past few weeks – but this is more a statement about just how good he was earlier, rather than him being bad now.  Basically, he’s not the super-dominant pitcher who started the season, but he is still pretty good.

Other than velocity, the other story with Corbin has been his slider usage.  Corbin’s slider is by far his best weapon, with a whiff rate near 30%, so it’s important that he throws it frequently.  But it’s possible to go too far in that direction, since even a very good pitch needs other pitches to make it effective.  In Corbin’s start on May 30th against the Reds, he threw the slider over 50% of the time, his highest rate this year.  He struck out 10 batters in that game, but also gave up two homers and six runs.  That hard contact could be an indication that hitters were sitting on the slider.  In his next start, it was back down to 32% and with it he returned to his successful ways.  It may be an oversimplification, but I found that interesting.

 

Jon Gray (SP, Colorado Rockies)

Scanning down the list by ERA, Gray easily stands out as a highly ranked pitcher with a very ugly ERA.  The last time I talked about him, in early May, he seemed ready to put his early-season struggles behind him, raising his PD score from the C level up to B.  Since then, he has appeared to continue struggling, by his ERA.  His current mark of 5.4 is certainly not what owners were hoping for.  But there are some good signs to be found in his numbers.  His PD score has actually increased since then, up to B+, in the top 20, fully supporting his excellent strikeout rate.  In other words, his fantastic FIP for May (2.8) is quite believable.  Interestingly, his full season metric line above looks remarkably similar to Luis Severino’s, whose ERA is less than half of Gray’s.

As you may have guessed, Coors field is a big part of the problem.  Gray’s home ERA this year is 6.5.  But there seems to be a fair amount of bad luck affecting Gray as well.  Particularly at home, his BABIP of .404 is much higher than his career average at home of .340.  This seems unlikely to continue.  He’s also sporting a low LOB% of just 63%.  With positive values (though small) in both of my “luck indicator” columns (K% difference and SLG-xSLG), that makes him four for four in the bad luck department, so I believe this makes him a fairly solid “buy low” candidate.  Coors field is likely to scare off owners, and he can probably be had cheaply with that ERA.  There is one note of caution for head-to-head leagues – the Rockies are at home most of the final month of the season, including the full last week.  So he may not be very helpful come playoff time.

 

Blake Snell (SP, Tampa Bay Rays)

Snell is the classic breakout story of 2018, turning himself into a top 10 starter at age 25, so I think he presents a great opportunity to see if the metrics could have predicted this.  Spoiler alert:  kinda.  With the PD metrics, I typically like to check two things: whether they support the strikeout rate, and whether they are better or worse than previous years.  To find a breakout, ideally you’re looking for someone whose metrics have improved, but not the overall results, and is the right age where they are likely to be improving generally.  We’re looking for a confluence of two events:  1) a young pitcher likely to get better, and 2) positive corrections in the stats due to previously poor luck.  When both of these things line up, that’s how breakouts happen.

Between 2016 and 2017, Snell’s PD metrics were essentially unchanged.  So he wouldn’t have passed the “metrics improving” test.  But on the other side, the metrics did suggest some poor luck in 2017.  Despite putting up nearly identical metrics, his strikeout rate fell significantly in 2017, so he was under-performing there.  So there was certainly some signs of a breakout incoming, though maybe not as clear as we would have hoped.  However, given his age and prospect pedigree, it would have been logical to assume some improvements this year, and combined with poor luck in the previous year, this could have been enough for some savvy folks to see it coming.

 

Dylan Bundy (SP, Baltimore Orioles)

Bundy seems to have fully recovered now from his disastrous start a month ago.  Since then, he’s put up a 2.5 ERA to go along with his 29% strikeout rate. Hopefully you’ve been reading my columns where I had rated him a “BUY” more than once.  We are now seeing the fruits of that investment.  Yes, there will continue to be some blowup games, as he is not the greatest contact manager and plays in a tough park/division.  But a 30% strikeout true talent level is too good to pass up – his predicted K% is sixth best in all of MLB.  His recent success has been buoyed by some good luck in terms of low BABIP and high LOB rates – but for the overall season, both numbers are very much in line with his career.  So you could say this good luck recently was more of a correction to earlier bad luck, than anything else.

Like Snell, Bundy presents an interesting opportunity to see if the metrics could have predicted his breakout.  And in Bundy’s case, it should have been even more obvious than Snell.  Between 2016 and 2017, Bundy showed real improvements in his PD metrics, across the board of the three most important ones (Contact%, SwStr, and O-Swing%).  However despite these improvements, his strikeout rate barely budged at all, indicating some poor luck in 2017.  He’s also 25 years old, the same as Snell, and was previously a hot prospect as well.  He’s just been in the league longer, and not fantastic, so people forgot he was a formerly elite prospect.  But “bad luck in previous year + right age & prospect status” seems like a decent recipe for predicting breakouts.

 

Trevor Bauer (SP, Cleveland Indians)

Speaking of breakouts, Bauer has been simply amazing this year.  At 27 years old and with four full MLB seasons under his belt, he’s a different story from Snell and Bundy.  But he is breaking out all the same, currently rated as 12th best in MLB by my rankings.  This is what his plate discipline metrics look like for his career:

Year IP ERA Contact% SwStr% O-Swing% F-Strike% 2014 153.0 4.2 80.0% 9.0% 31.5% 56.4% 2015 176.0 4.6 78.3% 9.6% 28.8% 59.1% 2016 190.0 4.3 79.1% 9.0% 26.3% 59.9% 2017 176.1 4.2 77.8% 9.2% 27.4% 56.9% 2018 78.0 2.8 72.1% 12.7% 29.9% 62.2%

So for four straight years, there weren’t really any major changes at all in his profile.  But this year, seemingly out of nowhere, everything is just much better.  Along with those improvements, his strikeout rate is way up, as to be expected, and this explains the majority of his success.  But where did this come from?

To explain, I’d recommend reading Nick’s profile of Bauer for 2018 on his FanGraphs page.  Essentially, in mid-2017 he stared cutting back on his cutter, and started throwing more sliders instead.  It turns out his slider is much better pitch.  His slider usage increased gradually throughout the second half of 2017, up to about 15% where it sits for 2018.  In graph form, here is his slider usage vs. cutters, along with his ERA the past two years:

 

 

It’s interesting just how closely his ERA line follows his cutter usage.  I have to say it looks like Nick really hit the nail on the head here.  But because that change was gradual, and late in the season, it didn’t show up in his full season metrics.  He was also fairly bad in the first half of 2017, dragging down his overall numbers.  So this is a good lesson in how full season plate discipline metrics can fail to tell the complete story, and sometimes you need to dive deeper.

 

Ross Stripling (SP, Los Angeles Dodgers)

I’d be remiss not to mention Stripling, who is surprising a lot of people this year by transforming into the Ace of the Dodgers staff.  For the past couple of my updates, he has held the distinction of holding the largest discrepancy between his predicted K% and actual results, indicating some serious good luck on the strikeout side.  Last week the gap between those two numbers was over 12%.  But in two starts last week, he closed the gap significantly down to 9%.  And he did it in a very interesting way.

If you remember from last week, in general these gaps are getting closed more by the strikeout rates moving than the metrics moving, about 75% to 25%.  But it would appear that Stripling has been going against the grain.  In just those two starts, his metrics were so excellent that his predicted K% rose by five percent, up to a now respectable 23%.  His gap is still the largest in MLB, but you have to be encouraged by those last few starts.  I’m certainly less pessimistic on his outlook than I was a week ago.  But in the end, it would probably be a mistake to assume he will continue closing his gap in this manner.  Since he looks like just an average strikeout pitcher overall, and is relying much more on managing contact, which is less reliable, I would still absolutely consider selling.