Years ago the sabermetric community believed that once the ball left a hitters bat, from the perspective of a pitcher, there was a 30-percent chance it would go for a hit, plain and simple.

Since then, this position has wavered quite a bit. There have been too many instances where a pitcher has shown the ability, over a long period of time, to outperform his peripheral numbers.

I don’t mean to diminish the original work done on DIPs theory because, by and large, it’s true; a pitcher does have very little control over the ball once it leaves a hitter’s bat.

I’ve heard speculation, and the following two postulations come from Dave Cameron at FanGraphs, as to why some pitchers have been able to outperform their peripheral numbers and ERA estimators over a long period of time. But some elicit Googling by the author has been unable to reveal any definitive research that has been done on these hypotheses:

A pitcher is more likely to outperform his peripheral numbers (i.e. FIP), if they are able to show a skill to induce infield fly balls. Think about it. A pop-out to the infield is pretty much guaranteed to be an out (i.e. there is much higher than a 30% chance that this batted ball turns into an out). A pitcher’s ability to hold runners well and show an unordinary ability to pitch out of the stretch will make them more likely to outperform their peripherals.

For the purpose of this article, we’ll tackle the first hypothesis, and we may go back and look at the second hypothesis, which is really two ideas that are somewhat connected, in another article.

Does Infield Flyball Percentage (IFFB%) Matter?

What we care about is the long run trend; sure, there may be year to year variations in a player’s peripherals and ERA, but what we really want to know is if over a long period of time a player has outperformed his peripherals, how much of this has to do with IFFB% (infield flyball percentage) and how much of this has to do with other factors.

There is data on infield flyball percentage that dates back to 2002, which gives us a sample of 13 seasons.

I looked at all pitchers that had 1,000 innings pitched between 2002 and 2014 and looked at the correlation between their IFFB% and the difference between their ERA and FIP (E-F) (i.e. if a player had a positive differential, that means they underperformed their peripherals; if a player had a negative differential, that means their FIP suggests that they should have allowed more runs than they actually did).

What I found is that out of those players—135 to be exact—that threw 1,000 IP between 2002 and 2014, their IFFB% had a -.333r with the difference between their ERA and FIP, which is moderate negative relationship.

The graph below will help illustrate what this means.

In plain English: the higher a player’s IFFB%, the more he outperformed his FIP.

However, let’s put this into perspective. The correlation between IFFB% and the difference between a player’s ERA and FIP is enough to be noticeable and make an appreciable difference in a player’s ability to outperform their peripherals, but it is not an enormous effect. IFFB% has an 11% r2 wit E-F, which means that 89% is left to be explained by batted-ball variation, DIPs theory, noise, and any unknown unknowns or known unknowns, which depends on how you look at it.

Of the 135 pitchers that had 1000IP between 2002 and 2014 (chart below), the 20 pitchers that outperformed their ERA the most had an IFFB% of 11.49%, and the 20 pitchers that underperformed their ERA the most had a 9.45% IFFB%.

Name Team ERA FIP E-F IFFB% Ryan Franklin - - - 4.17 4.82 -0.65 12.60% Chris Young - - - 3.77 4.38 -0.61 15.20% Johnny Cueto Reds 3.27 3.87 -0.6 10.00% Tom Glavine - - - 3.87 4.4 -0.53 9.20% Jeremy Guthrie - - - 4.23 4.69 -0.47 9.70% Jarrod Washburn - - - 4.08 4.54 -0.46 11.50% Jered Weaver Angels 3.28 3.74 -0.45 13.00% Jamie Moyer - - - 4.3 4.71 -0.41 13.00% Bronson Arroyo - - - 4.08 4.48 -0.4 12.20% Carlos Zambrano - - - 3.62 4 -0.38 11.70% Ted Lilly - - - 4.01 4.36 -0.35 14.20% Barry Zito - - - 4.13 4.47 -0.34 12.90% Matt Cain Giants 3.39 3.72 -0.33 12.20% Tim Hudson - - - 3.42 3.74 -0.32 7.80% R.A. Dickey - - - 3.96 4.27 -0.32 10.70% Johan Santana - - - 3.02 3.32 -0.3 13.10% Jon Garland - - - 4.34 4.63 -0.29 10.50% Jeff Suppan - - - 4.56 4.85 -0.29 9.80% Woody Williams - - - 4.18 4.45 -0.28 12.30% Joe Saunders - - - 4.37 4.65 -0.27 8.10% Mark Buehrle - - - 3.85 4.1 -0.26 9.80% Clayton Kershaw Dodgers 2.48 2.73 -0.25 12.20% Paul Byrd - - - 4.32 4.56 -0.25 10.80% Jason Marquis - - - 4.64 4.88 -0.25 7.30% Brandon Webb Diamondbacks 3.27 3.5 -0.24 6.60% Randy Wolf - - - 4.15 4.38 -0.24 12.30% Bruce Chen - - - 4.67 4.91 -0.24 13.10% Kyle Kendrick Phillies 4.42 4.65 -0.23 9.20% Oliver Perez - - - 4.45 4.68 -0.23 11.10% Ramon Ortiz - - - 4.98 5.2 -0.22 11.30% Cole Hamels Phillies 3.27 3.48 -0.21 10.90% Trevor Cahill - - - 4.07 4.28 -0.21 6.50% Chris Carpenter - - - 3.18 3.37 -0.19 8.10% Tim Wakefield Red Sox 4.42 4.6 -0.19 14.70% Hiroki Kuroda - - - 3.45 3.61 -0.17 11.70% Bartolo Colon - - - 3.89 4.04 -0.16 10.90% Brett Myers - - - 4.25 4.41 -0.16 10.10% Kenny Rogers - - - 4.34 4.5 -0.16 9.40% Vicente Padilla - - - 4.32 4.48 -0.15 11.10% Miguel Batista - - - 4.39 4.51 -0.13 10.20% Adam Wainwright Cardinals 3.01 3.13 -0.12 9.90% Matt Garza - - - 3.81 3.93 -0.12 11.60% Jason Vargas - - - 4.2 4.33 -0.12 12.50% Ervin Santana - - - 4.17 4.26 -0.09 9.90% John Danks White Sox 4.28 4.37 -0.09 9.60% Felix Hernandez Mariners 3.07 3.15 -0.07 8.00% C.J. Wilson - - - 3.72 3.79 -0.07 7.00% Wandy Rodriguez - - - 4.06 4.12 -0.07 9.00% Roy Halladay - - - 3.17 3.23 -0.06 11.20% David Price - - - 3.21 3.27 -0.06 9.70% Roger Clemens - - - 3.23 3.28 -0.06 9.50% Jake Peavy - - - 3.53 3.6 -0.06 11.70% Doug Davis - - - 4.32 4.38 -0.06 10.40% Dontrelle Willis - - - 4.17 4.22 -0.05 10.30% Jamey Wright - - - 4.53 4.58 -0.05 8.40% Kip Wells - - - 4.6 4.65 -0.05 9.60% James Shields - - - 3.72 3.77 -0.04 8.70% Freddy Garcia - - - 4.34 4.38 -0.04 11.10% Kyle Lohse - - - 4.22 4.25 -0.03 10.60% Chad Billingsley Dodgers 3.65 3.67 -0.02 7.40% Yovani Gallardo Brewers 3.69 3.71 -0.02 7.60% Roy Oswalt - - - 3.4 3.41 0 11.50% Jon Lester - - - 3.58 3.58 0 12.10% Josh Fogg - - - 5.07 5.07 0 10.70% Gil Meche - - - 4.52 4.51 0.01 9.60% Gio Gonzalez - - - 3.59 3.57 0.02 9.00% Ian Kennedy - - - 3.93 3.91 0.02 10.10% Roberto Hernandez - - - 4.6 4.57 0.02 8.40% Greg Maddux - - - 3.92 3.89 0.03 7.70% Gavin Floyd - - - 4.4 4.36 0.03 9.00% Livan Hernandez - - - 4.44 4.41 0.03 8.50% Dave Bush - - - 4.73 4.69 0.04 10.50% Rodrigo Lopez - - - 4.75 4.71 0.04 9.10% CC Sabathia - - - 3.57 3.52 0.06 10.00% Dan Haren - - - 3.77 3.71 0.06 10.30% Jake Westbrook - - - 4.23 4.17 0.06 6.90% Chris Capuano - - - 4.28 4.22 0.06 12.00% Cliff Lee - - - 3.52 3.45 0.07 11.10% Anibal Sanchez - - - 3.53 3.46 0.07 10.70% Kevin Correia - - - 4.59 4.52 0.07 8.20% Aaron Harang - - - 4.21 4.13 0.08 10.40% Paul Maholm - - - 4.3 4.22 0.08 7.40% Scott Feldman - - - 4.48 4.4 0.08 9.60% Jason Schmidt - - - 3.47 3.37 0.1 13.30% Justin Verlander Tigers 3.53 3.43 0.1 11.50% Andy Pettitte - - - 3.74 3.64 0.1 9.40% Odalis Perez - - - 4.29 4.19 0.1 9.50% Scott Kazmir - - - 4.07 3.96 0.11 10.40% Edinson Volquez - - - 4.44 4.32 0.11 7.60% Pedro Martinez - - - 3.32 3.19 0.12 11.00% Ben Sheets - - - 3.67 3.54 0.14 10.30% Josh Beckett - - - 3.91 3.77 0.14 11.60% Ubaldo Jimenez - - - 4 3.86 0.14 9.30% John Lackey - - - 4.03 3.89 0.14 9.40% Aaron Cook - - - 4.6 4.46 0.14 7.30% Brett Tomko - - - 4.77 4.6 0.16 11.70% Zack Greinke - - - 3.55 3.38 0.17 9.90% Erik Bedard - - - 3.99 3.82 0.17 10.40% Brad Penny - - - 4.32 4.16 0.17 9.30% Kevin Millwood - - - 4.21 4.04 0.18 9.80% Ryan Dempster - - - 4.25 4.08 0.18 9.80% Jason Jennings - - - 4.97 4.78 0.18 10.90% Max Scherzer - - - 3.58 3.39 0.19 9.50% Matt Morris - - - 4.43 4.24 0.19 8.20% Carlos Silva - - - 4.68 4.49 0.19 8.40% Randy Johnson - - - 3.61 3.42 0.2 10.00% Scott Baker - - - 4.25 4.04 0.2 12.50% David Wells - - - 4.26 4.04 0.21 10.20% A.J. Burnett - - - 4.02 3.8 0.22 9.00% Derek Lowe - - - 4.11 3.89 0.22 6.70% Javier Vazquez - - - 4.11 3.86 0.25 11.50% Joel Pineiro - - - 4.5 4.25 0.25 7.60% Jorge de la Rosa - - - 4.6 4.36 0.25 9.10% Carl Pavano - - - 4.35 4.09 0.26 8.70% Tim Lincecum Giants 3.59 3.31 0.27 7.30% Jose Contreras - - - 4.57 4.29 0.27 11.60% Nate Robertson - - - 5.01 4.75 0.27 8.60% Rick Porcello Tigers 4.3 4.03 0.28 9.20% Zach Duke - - - 4.46 4.17 0.28 7.30% Joe Blanton - - - 4.51 4.23 0.28 9.30% Mike Pelfrey - - - 4.56 4.24 0.31 9.40% Jason Hammel - - - 4.6 4.27 0.33 9.40% Justin Masterson - - - 4.24 3.89 0.36 7.50% Jeff Weaver - - - 4.77 4.39 0.38 11.10% Mike Mussina Yankees 4 3.61 0.4 10.50% Edwin Jackson - - - 4.63 4.23 0.41 9.00% Francisco Liriano - - - 4.07 3.61 0.46 8.50% Curt Schilling - - - 3.63 3.16 0.47 12.00% Mark Redman - - - 4.84 4.36 0.48 12.20% Mark Hendrickson - - - 5.03 4.51 0.51 10.90% Jeff Francis - - - 4.95 4.39 0.56 9.70% Sidney Ponson - - - 5.11 4.52 0.59 8.20% Jeremy Bonderman - - - 4.91 4.31 0.6 9.10% Ricky Nolasco - - - 4.48 3.82 0.66 8.20%

This is where you say to yourself, “That doesn’t sound like a big difference.” But really, it is.

Out of the same sample, the median pitcher’s IFFB% was 9.9%, which shouldn’t be mistaken for the league average IFFB%, because these are all pitchers that pitched at least 1000IP over an extended period, so we have somewhat of a selection bias of talented pitchers, and the standard deviation of the population is 1.76%.

The 20 pitchers that outperformed their ERAs the most had an average IFFB% that was nearly one standard deviation above the median. This is more impressive when you also consider that IFFB% has a .35r year to year correlation, which suggests that it is a skill, unlike BABIP, for example, which is almost random on a year to year basis.

The Con: How to use IFFB% to your advantage

Now that you know that…

IFFB% does matter when it comes to a player’s ability to outperform their FIP. IFFB% is a skill.

…we can look at how to take advantage of the dogmatic sabermetrician in your league.

Below is a list of players that through 100IP in 2014, their ERAs, FIPs, ERAs minus FIPs, and their IFFB%.

Name ERA FIP E-F IFFB% Mat Latos 3.25 3.65 -0.4 16.30% Drew Smyly 3.24 3.77 -0.53 15.30% Jordan Zimmermann 2.66 2.68 -0.02 14.20% Danny Duffy 2.53 3.83 -1.3 14.10% Chris Young 3.65 5.02 -1.36 14.10% Tommy Milone 4.19 4.69 -0.5 14.10% David Buchanan 3.75 4.27 -0.52 14.00% Clayton Kershaw 1.77 1.81 -0.04 13.90% Jon Lester 2.46 2.8 -0.34 13.60% R.A. Dickey 3.71 4.32 -0.61 13.60% Kyle Gibson 4.47 3.8 0.67 13.60% Miguel Gonzalez 3.23 4.89 -1.67 13.50% Jake Arrieta 2.53 2.26 0.27 13.40% Zack Greinke 2.71 2.97 -0.26 13.20% Chris Archer 3.33 3.39 -0.06 13.10% Danny Salazar 4.25 3.52 0.73 13.10% Hiroki Kuroda 3.71 3.6 0.1 13.00% Yusmeiro Petit 3.69 2.78 0.91 12.90% Chris Sale 2.17 2.57 -0.4 12.70% Mark Buehrle 3.39 3.66 -0.28 12.70% John Lackey 3.82 3.78 0.04 12.70% Marco Estrada 4.36 4.88 -0.52 12.70% Travis Wood 5.03 4.38 0.65 12.70% Justin Masterson 5.88 4.5 1.38 12.20% Brad Peacock 4.72 4.99 -0.27 12.10% Yu Darvish 3.06 2.84 0.21 11.90% Kyle Kendrick 4.61 4.57 0.04 11.90% Josh Tomlin 4.76 4.01 0.75 11.90% Tanner Roark 2.85 3.47 -0.62 11.80% Hector Santiago 3.75 4.29 -0.54 11.80% Justin Verlander 4.54 3.74 0.8 11.40% Johnny Cueto 2.25 3.3 -1.05 11.30% Shelby Miller 3.74 4.54 -0.8 11.30% Corey Kluber 2.44 2.35 0.1 11.10% Scott Carroll 4.8 4.77 0.03 11.10% Collin McHugh 2.73 3.11 -0.37 10.90% Madison Bumgarner 2.98 3.05 -0.07 10.90% Wei-Yin Chen 3.54 3.89 -0.35 10.90% Jered Weaver 3.59 4.19 -0.61 10.90% Nick Tepesch 4.36 5.01 -0.65 10.90% Lance Lynn 2.74 3.35 -0.61 10.80% David Phelps 4.38 4.41 -0.03 10.80% Nick Martinez 4.55 4.94 -0.39 10.80% Josh Beckett 2.88 4.33 -1.46 10.70% Homer Bailey 3.71 3.93 -0.22 10.70% Jake Peavy 3.73 4.11 -0.38 10.70% Julio Teheran 2.89 3.49 -0.6 10.60% Jeff Samardzija 2.99 3.2 -0.21 10.60% James Shields 3.21 3.59 -0.38 10.60% Tyler Skaggs 4.3 3.55 0.75 10.60% Franklin Morales 5.37 5.42 -0.04 10.60% Dallas Keuchel 2.93 3.21 -0.29 10.50% Rick Porcello 3.43 3.67 -0.24 10.50% Phil Hughes 3.52 2.65 0.87 10.50% Matt Garza 3.64 3.54 0.1 10.50% Masahiro Tanaka 2.77 3.04 -0.27 10.30% Gerrit Cole 3.65 3.23 0.42 10.30% Garrett Richards 2.61 2.6 0.01 10.20% Alfredo Simon 3.44 4.33 -0.9 10.20% Dan Haren 4.02 4.09 -0.07 10.20% Ubaldo Jimenez 4.81 4.67 0.14 10.20% Roenis Elias 3.85 4.03 -0.18 10.10% Colby Lewis 5.18 4.46 0.71 10.10% Kevin Gausman 3.57 3.41 0.16 9.90% Jason Vargas 3.71 3.84 -0.13 9.90% Clay Buchholz 5.34 4.01 1.33 9.80% Wily Peralta 3.53 4.11 -0.58 9.60% Dillon Gee 4 4.52 -0.52 9.60% Roberto Hernandez 4.1 4.85 -0.75 9.60% Jake Odorizzi 4.13 3.75 0.37 9.60% Rubby de la Rosa 4.43 4.3 0.12 9.60% Zack Wheeler 3.54 3.55 -0.01 9.40% Chase Anderson 4.01 4.22 -0.2 9.30% Josh Collmenter 3.46 3.87 -0.41 9.20% Jorge de la Rosa 4.1 4.34 -0.24 9.20% Hector Noesi 4.75 4.83 -0.07 9.10% Bud Norris 3.65 4.22 -0.57 9.00% Scott Feldman 3.74 4.11 -0.37 8.90% Jordan Lyles 4.33 4.22 0.11 8.90% Scott Kazmir 3.55 3.35 0.19 8.80% Charlie Morton 3.72 3.72 -0.01 8.80% Ervin Santana 3.95 3.39 0.56 8.80% Tyson Ross 2.81 3.24 -0.44 8.70% Vance Worley 2.85 3.44 -0.59 8.70% Chris Tillman 3.34 4.01 -0.67 8.70% C.J. Wilson 4.51 4.31 0.2 8.70% Hisashi Iwakuma 3.52 3.25 0.27 8.60% Edwin Jackson 6.33 4.45 1.88 8.60% David Price 3.26 2.78 0.48 8.50% Kyle Lohse 3.54 3.95 -0.41 8.50% Vidal Nuno 4.56 4.51 0.05 8.50% Drew Hutchison 4.48 3.85 0.64 8.40% Yordano Ventura 3.2 3.6 -0.41 8.30% Marcus Stroman 3.65 2.84 0.81 8.30% Cole Hamels 2.46 3.07 -0.61 8.20% Michael Wacha 3.2 3.17 0.03 8.20% Jose Quintana 3.32 2.81 0.51 8.20% Brett Oberholtzer 4.39 3.56 0.83 8.20% Jarred Cosart 3.69 3.77 -0.08 8.00% Jesse Chavez 3.45 3.89 -0.44 7.90% Gio Gonzalez 3.57 3.03 0.55 7.90% John Danks 4.74 4.76 -0.02 7.90% Jacob deGrom 2.69 2.67 0.02 7.80% Jason Hammel 3.47 3.92 -0.45 7.80% Jeff Locke 3.91 4.37 -0.46 7.60% Bartolo Colon 4.09 3.57 0.52 7.60% Edinson Volquez 3.04 4.15 -1.11 7.50% Sonny Gray 3.08 3.46 -0.38 7.50% Jon Niese 3.4 3.67 -0.27 7.50% Tyler Matzek 4.05 3.78 0.28 7.40% Jeremy Guthrie 4.13 4.32 -0.19 7.40% Doug Fister 2.41 3.93 -1.52 7.30% Ian Kennedy 3.63 3.21 0.42 7.30% Ryan Vogelsong 4 3.85 0.14 7.30% Francisco Liriano 3.38 3.59 -0.21 7.10% Trevor Bauer 4.18 4.01 0.16 7.10% Anibal Sanchez 3.43 2.71 0.72 7.00% Stephen Strasburg 3.14 2.94 0.2 6.80% Tim Hudson 3.57 3.54 0.02 6.80% Aaron Harang 3.57 3.57 0 6.80% Ricky Nolasco 5.38 4.3 1.08 6.80% Hyun-Jin Ryu 3.38 2.62 0.76 6.70% Eric Stults 4.3 4.63 -0.33 6.70% Nathan Eovaldi 4.37 3.37 1 6.60% Brandon McCarthy 4.05 3.55 0.5 6.50% Adam Wainwright 2.38 2.88 -0.5 6.30% Alex Wood 2.78 3.25 -0.48 6.30% Max Scherzer 3.15 2.85 0.3 6.30% J.A. Happ 4.22 4.27 -0.05 6.30% Samuel Deduno 4.47 4.31 0.16 6.30% Alex Cobb 2.87 3.23 -0.36 6.20% Kevin Correia 5.44 4.67 0.76 6.20% Henderson Alvarez 2.65 3.58 -0.93 6.10% Tom Koehler 3.81 3.84 -0.03 6.00% Tim Lincecum 4.74 4.31 0.43 5.80% Felix Hernandez 2.14 2.56 -0.42 5.70% Mike Leake 3.7 3.88 -0.18 5.70% A.J. Burnett 4.59 4.14 0.45 5.60% Trevor Cahill 5.61 3.89 1.72 5.60% Yovani Gallardo 3.51 3.94 -0.43 5.20% Jacob Turner 6.13 4.16 1.97 5.20% Andrew Cashner 2.55 3.09 -0.54 5.10% Jerome Williams 4.77 4.16 0.62 5.00% Matt Shoemaker 3.04 3.26 -0.22 4.70% Mike Minor 4.77 4.39 0.38 4.30% Carlos Carrasco 2.55 2.44 0.11 4.10% T.J. House 3.35 3.69 -0.34 3.60% Wade Miley 4.34 3.98 0.36 3.60% Brad Hand 4.38 4.2 0.17 2.70%

Notice that the players that have the highest IFFB%s (the default sort for this graph) also have a large difference between their ERA and FIP. These players, if they have shown a track record to have a high IFFB% over the course of their career, should be expected to outperform their FIP again. However, they may not outperform it by as much as they did last year, because, remember, IFFB% only explains part of the difference in a player’s ERA and FIP, not all of it.

To give a better indication of the players that have shown an ability to induce infield fly balls, here is a a list of players that have thrown 1,000 inning in their career and pitched last year (i.e. the active infield fly ball leaders):

Name ERA FIP E-F IFFB% Chris Young 3.77 4.38 -0.61 15.20% Bruce Chen 4.58 4.91 -0.32 13.10% Jered Weaver 3.28 3.74 -0.45 13.00% Jason Vargas 4.2 4.33 -0.12 12.50% Scott Baker 4.25 4.04 0.2 12.50% Randy Wolf 4.21 4.37 -0.16 12.30% Clayton Kershaw 2.48 2.73 -0.25 12.20% Matt Cain 3.39 3.72 -0.33 12.20% Bronson Arroyo 4.19 4.53 -0.34 12.20% Jon Lester 3.58 3.58 0 12.10% Chris Capuano 4.28 4.22 0.06 12.00% Hiroki Kuroda 3.45 3.61 -0.17 11.70% Jake Peavy 3.53 3.6 -0.06 11.70% Matt Garza 3.81 3.93 -0.12 11.60% Josh Beckett 3.88 3.78 0.1 11.60% Justin Verlander 3.53 3.43 0.1 11.50% Cliff Lee 3.52 3.45 0.07 11.10% LaTroy Hawkins 4.33 4.2 0.13 11.10% Oliver Perez 4.45 4.68 -0.23 11.10% Cole Hamels 3.27 3.48 -0.21 10.90% Bartolo Colon 3.95 4.06 -0.11 10.90% Anibal Sanchez 3.53 3.46 0.07 10.70% R.A. Dickey 3.98 4.3 -0.32 10.70% Kyle Lohse 4.28 4.28 -0.01 10.60% Erik Bedard 3.99 3.82 0.17 10.40% Scott Kazmir 4.07 3.96 0.11 10.40% Aaron Harang 4.21 4.13 0.08 10.40% Dan Haren 3.77 3.71 0.06 10.30% Ian Kennedy 3.93 3.91 0.02 10.10% Johnny Cueto 3.27 3.87 -0.6 10.00% CC Sabathia 3.63 3.56 0.06 10.00% Adam Wainwright 3.01 3.13 -0.12 9.90% Zack Greinke 3.55 3.38 0.17 9.90% Ervin Santana 4.17 4.26 -0.09 9.90% Mark Buehrle 3.81 4.1 -0.29 9.80% David Price 3.21 3.27 -0.06 9.70% Jeremy Guthrie 4.23 4.69 -0.47 9.70% Jeff Francis 4.95 4.39 0.56 9.70% John Danks 4.28 4.37 -0.09 9.60% Scott Feldman 4.48 4.4 0.08 9.60% Max Scherzer 3.58 3.39 0.19 9.50% John Lackey 4.03 3.89 0.14 9.40% Mike Pelfrey 4.56 4.24 0.31 9.40% Jason Hammel 4.6 4.27 0.33 9.40% Ubaldo Jimenez 4 3.86 0.14 9.30% Brad Penny 4.29 4.12 0.17 9.30% Rick Porcello 4.3 4.03 0.28 9.20% Kyle Kendrick 4.42 4.65 -0.23 9.20% Jorge de la Rosa 4.6 4.36 0.25 9.10% Gio Gonzalez 3.59 3.57 0.02 9.00% A.J. Burnett 4.04 3.9 0.14 9.00% Wandy Rodriguez 4.06 4.12 -0.07 9.00% Gavin Floyd 4.4 4.36 0.03 9.00% Edwin Jackson 4.63 4.23 0.41 9.00% James Shields 3.72 3.77 -0.04 8.70% Francisco Liriano 4.07 3.61 0.46 8.50% Roberto Hernandez 4.6 4.57 0.02 8.40% Jamey Wright 4.81 4.87 -0.07 8.40% Ricky Nolasco 4.48 3.82 0.66 8.20% Kevin Correia 4.59 4.52 0.07 8.20% Joe Saunders 4.37 4.65 -0.27 8.10% Felix Hernandez 3.07 3.15 -0.07 8.00% Tim Hudson 3.45 3.75 -0.3 7.80% Yovani Gallardo 3.69 3.71 -0.02 7.60% Edinson Volquez 4.44 4.32 0.11 7.60% Justin Masterson 4.24 3.89 0.36 7.50% Paul Maholm 4.3 4.22 0.08 7.40% Tim Lincecum 3.59 3.31 0.27 7.30% Zach Duke 4.46 4.17 0.28 7.30% C.J. Wilson 3.72 3.79 -0.07 7.00% Trevor Cahill 4.07 4.28 -0.21 6.50%

This is where you go to the dogmatic sabermetrician in your league and make an offer for one of their pitchers; you relate to him from his perspective and say, “you can’t expect ‘_________’ to outperform his FIP by as much as he did last year”; you give him value that is equivalent to the pitcher’s 2015 projected value, and you profit, because you know full well that ‘__________’ will outperform their FIP again because of their IFFB%.

To close, I’ll use an example I’ve used before. In Boomerang: Travels in the New Third World, Michael Lewis interviews Kyle Bass, a hedge fund manager who, at some point in the aughts if memory serves correct, bought a million dollars worth of nickels because “the value of the metal in nickels was [is] worth six point eight cents” (Lewis xvii). The same goes for Fantasy Baseball. As long as you can get more back in a trade than you gave up, you can continue to make a profit, and your knowledge of IFFB% can help you successfully do this.

Feature image of Drew Smyly is courtesy of Keith Allsion