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Two Simple Metrics To Use To Find Pitching Regression Candidates

Michael Waterloo January 8, 2018 5:33PM EDT
Regression.

It’s a term we hear over the course of a 162-game season many, many times. Players like Aaron Judge and Rhys Hoskins were hitting home runs at an absurd, unsustainable pace, which meant they were due to regress. It’s the same way that Jason Vargas wasn’t going to carry over his 2.62 ERA from the first half of the season throughout the year, as his peripherals weren’t extremely different from his career.

But regression isn’t just a negative thing, though, even if it’s typically taken that way. Players can have positive regression, too, in which they rebound from a start that is out of the norm for them. Manny Machado last season is the perfect example of this.

Chris Sale’s FIP differential indicates that he pitched better than his ERA indicates. Credit: AP Photo/Michael Dwyer

As we turn our sights toward the 2018 season, let’s identify some pitchers that are due for regression – in one form or another – and we’ll tackle hitters next week.

ERA and FIP Differentials

One of the first signs I look for in regression for a pitcher is the difference between his ERA and his FIP. If his ERA is higher than his FIP, it tends to mean that his numbers should have been better than they were. If his ERA is lower than his FIP, it means that the pitcher had a lot of things go right for him throughout the year, and that negative regression should be expected.

Here are the qualified pitchers from the 2017 season, sorted by ERA, with their respective FIP and differential in the next columns:

# Name ERA FIP DIFFERENTIAL
1 Chris Sale 2.9 2.45 0.45
2 Corey Kluber 2.25 2.5 -0.25
3 Max Scherzer 2.51 2.9 -0.39
4 Luis Severino 2.98 3.07 -0.09
5 Stephen Strasburg 2.52 2.72 -0.2
6 Carlos Carrasco 3.29 3.1 0.19
7 Zack Greinke 3.2 3.31 -0.11
8 Jimmy Nelson 3.49 3.05 0.44
9 Clayton Kershaw 2.31 3.07 -0.76
10 Chris Archer 4.07 3.4 0.67
11 Jacob deGrom 3.53 3.5 0.03
12 Aaron Nola 3.54 3.27 0.27
13 Justin Verlander 3.36 3.84 -0.48
14 Jose Quintana 4.15 3.68 0.47
15 Jeff Samardzija 4.42 3.61 0.81
16 Yu Darvish 3.86 3.83 0.03
17 Michael Fulmer 3.83 3.67 0.16
18 Marcus Stroman 3.09 3.9 -0.81
19 Carlos Martinez 3.64 3.91 -0.27
20 Gio Gonzalez 2.96 3.93 -0.97
21 Michael Wacha 4.13 3.63 0.5
22 Trevor Bauer 4.19 3.88 0.31
23 Robbie Ray 2.89 3.72 -0.83
24 Drew Pomeranz 3.32 3.84 -0.52
25 Mike Leake 3.92 3.9 0.02
26 Gerrit Cole 4.26 4.08 0.18
27 Patrick Corbin 4.03 4.08 -0.05
28 Ervin Santana 3.28 4.46 -1.18
29 Sonny Gray 3.55 3.9 -0.35
30 Zach Davies 3.9 4.22 -0.32
31 Masahiro Tanaka 4.74 4.34 0.4
32 Jon Lester 4.33 4.1 0.23
33 Dylan Bundy 4.24 4.38 -0.14
34 Marco Estrada 4.98 4.61 0.37
35 Kevin Gausman 4.68 4.48 0.2
36 Jake Arrieta 3.53 4.16 -0.63
37 German Marquez 4.39 4.4 -0.01
38 Tanner Roark 4.67 4.13 0.54
39 Alex Cobb 3.66 4.16 -0.5
40 Jhoulys Chacin 3.89 4.26 -0.37
41 Clayton Richard 4.79 4.23 0.56
42 Jason Hammel 5.29 4.37 0.92
43 Rick Porcello 4.65 4.6 0.05
44 Dan Straily 4.26 4.58 -0.32
45 Ivan Nova 4.14 4.46 -0.32
46 Martin Perez 4.82 4.65 0.17
47 Andrew Cashner 3.4 4.61 -1.21
48 R.A. Dickey 4.26 4.72 -0.46
49 Jason Vargas 4.16 4.67 -0.51
50 Luis Perdomo 4.67 4.4 0.27
51 Lance Lynn 3.43 4.82 -1.39
52 Ty Blach 4.78 4.42 0.36
53 Julio Teheran 4.49 4.95 -0.46
54 Matt Moore 5.52 4.75 0.77
55 Ricky Nolasco 4.92 5.1 -0.18
56 John Lackey 4.59 5.3 -0.71
57 Jose Urena 3.82 5.2 -1.38
58 Jeremy Hellickson 5.43 5.77 -0.34

If we sort, we can see those pitchers who were the luckiest in 2017, which really, the first five come as no surprise:

51 Lance Lynn 3.43 4.82 -1.39
57 Jose Urena 3.82 5.2 -1.38
47 Andrew Cashner 3.4 4.61 -1.21
28 Ervin Santana 3.28 4.46 -1.18
20 Gio Gonzalez 2.96 3.93 -0.97
23 Robbie Ray 2.89 3.72 -0.83
18 Marcus Stroman 3.09 3.9 -0.81
9 Clayton Kershaw 2.31 3.07 -0.76
56 John Lackey 4.59 5.3 -0.71
36 Jake Arrieta 3.53 4.16 -0.63
24 Drew Pomeranz 3.32 3.84 -0.52
49 Jason Vargas 4.16 4.67 -0.51
39 Alex Cobb 3.66 4.16 -0.5
13 Justin Verlander 3.36 3.84 -0.48
48 R.A. Dickey 4.26 4.72 -0.46
53 Julio Teheran 4.49 4.95 -0.46
3 Max Scherzer 2.51 2.9 -0.39
40 Jhoulys Chacin 3.89 4.26 -0.37
29 Sonny Gray 3.55 3.9 -0.35
58 Jeremy Hellickson 5.43 5.77 -0.34
30 Zach Davies 3.9 4.22 -0.32
44 Dan Straily 4.26 4.58 -0.32
45 Ivan Nova 4.14 4.46 -0.32
19 Carlos Martinez 3.64 3.91 -0.27
2 Corey Kluber 2.25 2.5 -0.25
5 Stephen Strasburg 2.52 2.72 -0.2
55 Ricky Nolasco 4.92 5.1 -0.18
33 Dylan Bundy 4.24 4.38 -0.14
7 Zack Greinke 3.2 3.31 -0.11
4 Luis Severino 2.98 3.07 -0.09
27 Patrick Corbin 4.03 4.08 -0.05
37 German Marquez 4.39 4.4 -0.01
25 Mike Leake 3.92 3.9 0.02
11 Jacob deGrom 3.53 3.5 0.03
16 Yu Darvish 3.86 3.83 0.03
43 Rick Porcello 4.65 4.6 0.05
17 Michael Fulmer 3.83 3.67 0.16
46 Martin Perez 4.82 4.65 0.17
26 Gerrit Cole 4.26 4.08 0.18
6 Carlos Carrasco 3.29 3.1 0.19
35 Kevin Gausman 4.68 4.48 0.2
32 Jon Lester 4.33 4.1 0.23
12 Aaron Nola 3.54 3.27 0.27
50 Luis Perdomo 4.67 4.4 0.27
22 Trevor Bauer 4.19 3.88 0.31
52 Ty Blach 4.78 4.42 0.36
34 Marco Estrada 4.98 4.61 0.37
31 Masahiro Tanaka 4.74 4.34 0.4
8 Jimmy Nelson 3.49 3.05 0.44
1 Chris Sale 2.9 2.45 0.45
14 Jose Quintana 4.15 3.68 0.47
21 Michael Wacha 4.13 3.63 0.5
38 Tanner Roark 4.67 4.13 0.54
41 Clayton Richard 4.79 4.23 0.56
10 Chris Archer 4.07 3.4 0.67
54 Matt Moore 5.52 4.75 0.77
15 Jeff Samardzija 4.42 3.61 0.81
42 Jason Hammel 5.29 4.37 0.92

Any Fantasy advice you read last year told you to sell high or avoid using the top names on the above chart. Should they have finished the year – especially Lance Lynn and Gio Gonzalez – with the numbers they had? No, absolutely not. However, pitchers can outperform their peripherals and keep that up over not just a year, but a career. The most obvious example of this is Johnny Cueto, who has a 3.33 lifetime ERA and a 3.77 FIP.

It just so happens that the Top 5 names on this list had five of the seven lowest BABIPs against last year.

Coincidence? I think not.

The smart move, though, when you see differentials this high is to shop the pitcher because the likely outcome is that they regress in a bad way.

On the other side of the coin, let’s look at pitchers that weren’t as fortunate and experienced bad luck on the mound:

# Name ERA FIP DIFFERENTIAL
42 Jason Hammel 5.29 4.37 0.92
15 Jeff Samardzija 4.42 3.61 0.81
54 Matt Moore 5.52 4.75 0.77
10 Chris Archer 4.07 3.4 0.67
41 Clayton Richard 4.79 4.23 0.56
38 Tanner Roark 4.67 4.13 0.54
21 Michael Wacha 4.13 3.63 0.5
14 Jose Quintana 4.15 3.68 0.47
1 Chris Sale 2.9 2.45 0.45
8 Jimmy Nelson 3.49 3.05 0.44
31 Masahiro Tanaka 4.74 4.34 0.4
34 Marco Estrada 4.98 4.61 0.37
52 Ty Blach 4.78 4.42 0.36
22 Trevor Bauer 4.19 3.88 0.31
12 Aaron Nola 3.54 3.27 0.27
50 Luis Perdomo 4.67 4.4 0.27
32 Jon Lester 4.33 4.1 0.23
35 Kevin Gausman 4.68 4.48 0.2
6 Carlos Carrasco 3.29 3.1 0.19
26 Gerrit Cole 4.26 4.08 0.18
46 Martin Perez 4.82 4.65 0.17
17 Michael Fulmer 3.83 3.67 0.16
43 Rick Porcello 4.65 4.6 0.05
11 Jacob deGrom 3.53 3.5 0.03
16 Yu Darvish 3.86 3.83 0.03
25 Mike Leake 3.92 3.9 0.02
37 German Marquez 4.39 4.4 -0.01
27 Patrick Corbin 4.03 4.08 -0.05
4 Luis Severino 2.98 3.07 -0.09
7 Zack Greinke 3.2 3.31 -0.11
33 Dylan Bundy 4.24 4.38 -0.14
55 Ricky Nolasco 4.92 5.1 -0.18
5 Stephen Strasburg 2.52 2.72 -0.2
2 Corey Kluber 2.25 2.5 -0.25
19 Carlos Martinez 3.64 3.91 -0.27
30 Zach Davies 3.9 4.22 -0.32
44 Dan Straily 4.26 4.58 -0.32
45 Ivan Nova 4.14 4.46 -0.32
58 Jeremy Hellickson 5.43 5.77 -0.34
29 Sonny Gray 3.55 3.9 -0.35
40 Jhoulys Chacin 3.89 4.26 -0.37
3 Max Scherzer 2.51 2.9 -0.39
48 R.A. Dickey 4.26 4.72 -0.46
53 Julio Teheran 4.49 4.95 -0.46
13 Justin Verlander 3.36 3.84 -0.48
39 Alex Cobb 3.66 4.16 -0.5
49 Jason Vargas 4.16 4.67 -0.51
24 Drew Pomeranz 3.32 3.84 -0.52
36 Jake Arrieta 3.53 4.16 -0.63
56 John Lackey 4.59 5.3 -0.71
9 Clayton Kershaw 2.31 3.07 -0.76
18 Marcus Stroman 3.09 3.9 -0.81
23 Robbie Ray 2.89 3.72 -0.83
20 Gio Gonzalez 2.96 3.93 -0.97
28 Ervin Santana 3.28 4.46 -1.18
47 Andrew Cashner 3.4 4.61 -1.21
57 Jose Urena 3.82 5.2 -1.38
51 Lance Lynn 3.43 4.82 -1.39

What’s important about these types of exercises isn’t just the differential, it’s where the differential takes you. While we said Gonzalez was a sell-high player, and he had one of the Top 5 luckiest years in terms of ERA and FIP differential, if he pitched to his FIP, he would have been at a 3.93 ERA, which way below the 4.36 league average in 2017.

Keep that in mind when you see names like Matt Moore and Jason Hammel at the top of the “unlucky” pitchers. If they would have pitched to what they should have pitched to, they still would have been worse than league average.

But the pitcher that stands out to me the most is Jeff Samardzija. His price is more than affordable (132 and 156 in two mocks that I’ve done so far with Fantasy experts), as his ERA will stand out. There’s something to say for a guy that consistently throws 200-plus innings. I’m buying him where I can this year.

Strikeouts

We love the strikeout in Fantasy. It’s the most valuable out, as you don’t have to depend on a fielder to make a play on the ball. It’s just the pitcher, the catcher and the batter … and of course, we can’t forget the #umpshow. Taking strikeouts further, we like pitchers who have a high swinging strike rate (SwStr%), that just dominates hitters and take it out of the hands of the umps.

Alex Chamberlain wrote a good piece over at FanGraphs taking a closer look at Luke Weaver. Chamberlain tells Fantasy owners to have some pause with Weaver, as he explores his below-average SwStr% and his above-average K%. They do, as Chamberlain explains, correlate with one another.

Similar to the above exercise, I wanted to see which pitchers with at least 100 innings pitched were on the leaderboards for top SwStr% and K%, and to see which ones may be misleading.

I broke it down by looking at pitchers with a SwStrk% of 10 percent or higher, and then pitchers with a K% of 21 percent or higher.

Name SwStr% Name K%
Danny Salazar 16.4 % Chris Sale 36.2 %
Corey Kluber 15.6 % Max Scherzer 34.4 %
Max Scherzer 15.5 % Corey Kluber 34.1 %
Masahiro Tanaka 15.1 % Danny Salazar 33.0 %
Chris Sale 14.9 % Robbie Ray 32.8 %
Robbie Ray 14.2 % Rich Hill 30.1 %
Clayton Kershaw 14.1 % Clayton Kershaw 29.8 %
Chris Archer 13.4 % Brad Peacock 29.5 %
Carlos Carrasco 13.4 % Luis Severino 29.4 %
Zack Godley 13.3 % Chris Archer 29.2 %
Jacob deGrom 13.3 % Stephen Strasburg 29.1 %
Stephen Strasburg 13.0 % Jacob deGrom 28.9 %
Luis Severino 13.0 % Dinelson Lamet 28.7 %
Kenta Maeda 12.5 % Carlos Carrasco 28.3 %
James Paxton 12.5 % James Paxton 28.3 %
Mike Clevinger 12.5 % Jimmy Nelson 27.3 %
Zack Greinke 12.4 % Mike Clevinger 27.3 %
Yu Darvish 12.3 % Yu Darvish 27.3 %
Jordan Montgomery 12.2 % Zack Greinke 26.8 %
Dan Straily 12.2 % Aaron Nola 26.6 %
Lance McCullers 12.0 % Charlie Morton 26.4 %
Sonny Gray 11.9 % Zack Godley 26.3 %
Brad Peacock 11.8 % Jose Quintana 26.2 %
Dinelson Lamet 11.8 % Trevor Bauer 26.2 %
Alex Wood 11.8 % Justin Verlander 25.8 %
Eduardo Rodriguez 11.7 % Masahiro Tanaka 25.8 %
Joe Musgrove 11.7 % Lance McCullers 25.8 %
Rich Hill 11.5 % Eduardo Rodriguez 25.8 %
Dylan Bundy 11.4 % Carlos Martinez 25.3 %
Jimmy Nelson 11.4 % Kenta Maeda 25.1 %
Danny Duffy 11.4 % Alex Wood 24.6 %
Sean Manaea 11.4 % Jon Gray 24.3 %
Jake Odorizzi 11.2 % Jeff Samardzija 24.2 %
Sean Newcomb 11.2 % Nick Pivetta 24.0 %
Jaime Garcia 11.2 % Sean Newcomb 23.7 %
Patrick Corbin 11.1 % Jon Lester 23.6 %
Ricky Nolasco 11.0 % Drew Pomeranz 23.5 %
Jon Lester 11.0 % Chase Anderson 23.4 %
Hyun-Jin Ryu 11.0 % Gerrit Cole 23.1 %
Kevin Gausman 10.9 % Jake Arrieta 23.1 %
Dallas Keuchel 10.9 % Gio Gonzalez 22.7 %
Charlie Morton 10.9 % J.A. Happ 22.7 %
Marco Estrada 10.9 % Sonny Gray 22.6 %
Blake Snell 10.8 % Jose Berrios 22.6 %
Aaron Nola 10.8 % Michael Wacha 22.5 %
Ariel Miranda 10.8 % Madison Bumgarner 22.4 %
Tim Adleman 10.8 % Jordan Montgomery 22.2 %
Justin Verlander 10.7 % Dan Straily 22.1 %
Johnny Cueto 10.6 % Kevin Gausman 21.9 %
Carlos Martinez 10.6 % Marco Estrada 21.8 %
John Lackey 10.4 % Dylan Bundy 21.8 %
Madison Bumgarner 10.3 % Blake Snell 21.8 %
James Shields 10.2 % Mike Fiers 21.8 %
Chase Anderson 10.2 % Kyle Hendricks 21.6 %
Rafael Montero 10.2 % Anibal Sanchez 21.6 %
Erasmo Ramirez 10.2 % Patrick Corbin 21.6 %
Ervin Santana 10.1 % Ubaldo Jimenez 21.5 %
Tanner Roark 10.1 % Hyun-Jin Ryu 21.4 %
Kyle Gibson 10.0 % Dallas Keuchel 21.4 %
Jeff Samardzija 10.0 % Tanner Roark 21.4 %
Marcus Stroman 10.0 % Danny Duffy 21.4 %
Matt Boyd 10.0 % Taijuan Walker 21.4 %
Jameson Taillon 21.3 %
Joe Musgrove 21.2 %
Jake Odorizzi 21.0 %
Johnny Cueto 21.0 %
German Marquez 21.0 %

That’s … a lot of names. First, let’s take a look at the pitchers who appear just once on the spreadsheet.

SwStr% only

  • Sean Manaea
  • Jaime Garcia
  • Ricky Nolasco
  • Ariel Miranda
  • Tim Adleman
  • John Lackey
  • James Shields
    Rafael Montero
  • Erasmo Ramirez
  • Ervin Santana
  • Kyle Gibson
  • Marcus Stroman
  • Matt Boyd

K% only

  • Jose Quintana
  • Trevor Bauer
  • Jon Gray
  • Nick Pivetta
  • Drew Pomeranz
  • Gerrit Cole
  • Jake Arrieta
  • Gio Gonzalez
  • J.A. Happ
  • Jose Berrios
  • Michael Wacha
  • Mike Fiers
  • Kyle Hendricks
  • Anibal Sanchez
  • Ubaldo Jimenez
  • Taijuan Walker
  • Jameson Taillon
  • German Marquez

So, what does this mean? That means that those 18 names that appear in K% only have some question marks with their strikeouts last year, as they fail to appear in the Top 63 pitchers with at least 100 innings pitched in SwStr%. While those that appear just on the SwStrk% but not on the K% list should have had more strikeouts than they ended up with for the year.

Here are some notables from those that fit both criteria and the differences that caught my eye.

Difference in spot where K% is > SwStr%

  • Chase Anderson 16 spots
  • Carlos Martinez 21 spots
  • Charlie Morton 21 spots
  • Rich Hill 22 spots
  • Justin Verlander 23 spots
  • Aaron Nola 25 spots

Difference in spot where SwStr% is > K%

  • Sonny Gray 21 spots
  • Masahiro Tanaka 22 spots
  • Dylan Bundy 22 spots
  • Dan Straily 28 spots
  • Jordan Montgomery 28 spots
  • Danny Duffy 30 spots
  • Jake Odorizzi 32 spots
  • Joe Musgrove 37 spots

Play Fantasy Football, CFL Style! Visit the Canadian Football League’s Fantasy page for info on how to get in the game for 2018! RotoExperts.com provides winning tips and insights for the 2018 season. . 

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