This article is part of our The Z Files series.
I'm so old, I remember when we assumed every pitcher's BABIP (batting on balls in play) would regress to .300. It didn't matter if it was Pedro Martinez or Pedro Astacio, their BABIP should be .300.
Thankfully, we've come a long way since the advent of DIPS theory. To be fair, Voros McCracken's findings were revolutionary, and served as a foundation for a new generation of analysis.
The formula for BABIP is:
(Hits – HR)/(AB – HR- K +SF)
The original DIPS (defense-independent pitching statistics) theory noted how a large percentage of pitcher's BABIP clustered around .300. If an individual's mark was lower, he was deemed lucky, and his BABIP was expected to regress towards .300, either in-season or the following year. If it was above .300, the hurler was judged to be unlucky, with impending regression down to .300.
Over the years, it's become apparent that pitchers exert some influence on their BABIP; it isn't totally random. That said, the level of influence is often overblown which can produce flawed analysis. However, expecting everyone's BABIP to move towards league average is also egregious.
Thinking about it from a practical sense, what should affect BABIP? That is, what factors can a pitcher influence that would generate a low BABIP? The two that immediately come to mind are limiting hard contact and line drives.
Last time, I posed the question, "How Much Influence Does a Pitcher Exert?" Statcast's average exit velocity and HardHit% were reviewed, along with Baseball Info
I'm so old, I remember when we assumed every pitcher's BABIP (batting on balls in play) would regress to .300. It didn't matter if it was Pedro Martinez or Pedro Astacio, their BABIP should be .300.
Thankfully, we've come a long way since the advent of DIPS theory. To be fair, Voros McCracken's findings were revolutionary, and served as a foundation for a new generation of analysis.
The formula for BABIP is:
(Hits – HR)/(AB – HR- K +SF)
The original DIPS (defense-independent pitching statistics) theory noted how a large percentage of pitcher's BABIP clustered around .300. If an individual's mark was lower, he was deemed lucky, and his BABIP was expected to regress towards .300, either in-season or the following year. If it was above .300, the hurler was judged to be unlucky, with impending regression down to .300.
Over the years, it's become apparent that pitchers exert some influence on their BABIP; it isn't totally random. That said, the level of influence is often overblown which can produce flawed analysis. However, expecting everyone's BABIP to move towards league average is also egregious.
Thinking about it from a practical sense, what should affect BABIP? That is, what factors can a pitcher influence that would generate a low BABIP? The two that immediately come to mind are limiting hard contact and line drives.
Last time, I posed the question, "How Much Influence Does a Pitcher Exert?" Statcast's average exit velocity and HardHit% were reviewed, along with Baseball Info Solutions Hard%, Medium% and Soft%. The answer to that question is, "Not as much as you think." It is more than random, but there are other elements of pitching for which a pitcher exerts more control.
The chief area which a player can affect is groundballs and flyballs. The influence of line drives is the weakest of everything cited in this discussion.
Putting everything together, pitchers have limited influence over hard and soft contact, as well as the number of line drives they surrender. In other words, pitchers don't exert much control over two of the factors helping to maintain a low BABIP. Or at least not as much as many intuit.
On the other hand, pitchers have a great deal of influence over groundballs and flyballs. Furthermore, it is known the BABIP of grounders is higher than that of flies. As such, groundball pitchers should organically carry a higher BABIP than their flyball counterparts. Maybe we shouldn't be so quick to assume regression to the league mean.
Before going on, I am not taking credit for what follows. It was derived from independent thinking, but I am sure others do the same, or something similar. The notion is a pitcher's xBABIP (expected BABIP) can be computed solely based on their batted ball distribution.
xBABIP = (GB% x GB BABIP) + (LD% x LD BABIP) + (FB% x FB BABIP).
Using 2023 league averages, the component BABIP are
- Line Drive: 0.628
- Groundball: 0.248
- Flyball: 0.095
These numbers may be different from those cited elsewhere because these don't include homers. The overall BABIP for flyballs and line drives is higher. For simplicity's sake, bunts are included with grounders while popups are lumped with flyballs. If this were a study to be submitted to a SABR conference, I may have further distilled the components.
Let's plug in some numbers to get a feel for the range of BABIP, based solely on batted ball distribution. The LD% will be kept constant. Last season, it was 25.2 percent. Again, this is just for balls in play. It is higher than what will be shown elsewhere for the league average, but that denominator includes homers (mostly all flyballs, with some line drives, depending on the data source). The top line in bold blue is the league average, encompassing all pitchers who threw at least 50 innings.
GB% | FB% | LD% | BABIP |
---|---|---|---|
44.3 | 30.4 | 25.2 | 0.297 |
65 | 9.8 | 25.2 | 0.329 |
60 | 14.8 | 25.2 | 0.321 |
55 | 19.8 | 25.2 | 0.314 |
50 | 24.8 | 25.2 | 0.306 |
40 | 34.8 | 25.2 | 0.291 |
35 | 39.8 | 25.2 | 0.283 |
30 | 44.8 | 25.2 | 0.275 |
25 | 49.8 | 25.2 | 0.268 |
After the league average, the top two and bottom two are extremes. Most pitchers induce between 35 and 55 percent ground balls, generating an xBABIP range between .283 and .314. I can't count the number of times I saw a .283 BABIP and Pavlovian assumed it was lucky, or targeted a .314 BABIP, convinced it would drop.
Here is a sortable table displaying the BABIP and xBABIP of all pitchers who compiled at least 50 frames last season.
Pitcher | BABIP | xBABIP | Difference |
---|---|---|---|
A.J. Minter | 0.331 | 0.305 | 0.026 |
A.J. Puk | 0.319 | 0.266 | 0.053 |
Aaron Bummer | 0.340 | 0.308 | 0.032 |
Aaron Civale | 0.289 | 0.286 | 0.003 |
Aaron Nola | 0.286 | 0.302 | -0.016 |
Adam Ottavino | 0.255 | 0.271 | -0.016 |
Adam Wainwright | 0.359 | 0.311 | 0.048 |
Adbert Alzolay | 0.290 | 0.311 | -0.021 |
Adrian Houser | 0.320 | 0.282 | 0.038 |
Adrian Martinez | 0.315 | 0.324 | -0.009 |
Albert Abreu | 0.276 | 0.275 | 0.001 |
Alec Marsh | 0.321 | 0.302 | 0.019 |
Alek Manoah | 0.308 | 0.289 | 0.019 |
Alex Cobb | 0.319 | 0.318 | 0.001 |
Alex Faedo | 0.211 | 0.282 | -0.071 |
Alex Lange | 0.245 | 0.296 | -0.051 |
Alex Wood | 0.303 | 0.283 | 0.020 |
Alex Young | 0.279 | 0.289 | -0.010 |
Alexis Diaz | 0.270 | 0.271 | -0.001 |
Andre Jackson | 0.248 | 0.304 | -0.056 |
Andre Pallante | 0.320 | 0.298 | 0.022 |
Andres Machado | 0.304 | 0.307 | -0.003 |
Andrew Abbott | 0.302 | 0.281 | 0.021 |
Andrew Chafin | 0.310 | 0.312 | -0.002 |
Andrew Heaney | 0.302 | 0.280 | 0.022 |
Andrew Nardi | 0.290 | 0.285 | 0.005 |
Anthony DeSclafani | 0.303 | 0.314 | -0.011 |
Aroldis Chapman | 0.314 | 0.308 | 0.006 |
Austin Gomber | 0.314 | 0.295 | 0.019 |
Bailey Falter | 0.311 | 0.300 | 0.011 |
Bailey Ober | 0.276 | 0.264 | 0.012 |
Ben Lively | 0.297 | 0.314 | -0.017 |
Blake Snell | 0.256 | 0.310 | -0.054 |
Bobby Miller | 0.277 | 0.297 | -0.020 |
Brad Hand | 0.345 | 0.335 | 0.010 |
Brady Singer | 0.330 | 0.308 | 0.022 |
Brandon Bielak | 0.312 | 0.298 | 0.014 |
Brandon Pfaadt | 0.316 | 0.292 | 0.024 |
Brandon Williamson | 0.280 | 0.298 | -0.018 |
Brandon Woodruff | 0.204 | 0.278 | -0.074 |
Braxton Garrett | 0.302 | 0.319 | -0.017 |
Brayan Bello | 0.307 | 0.291 | 0.016 |
Brennan Bernardino | 0.338 | 0.324 | 0.014 |
Brent Honeywell | 0.287 | 0.296 | -0.009 |
Brent Suter | 0.302 | 0.274 | 0.028 |
Brock Burke | 0.295 | 0.264 | 0.031 |
Brooks Raley | 0.288 | 0.269 | 0.019 |
Brusdar Graterol | 0.262 | 0.270 | -0.008 |
Bryan Abreu | 0.262 | 0.298 | -0.036 |
Bryan Hoeing | 0.275 | 0.297 | -0.022 |
Bryan Woo | 0.274 | 0.281 | -0.007 |
Bryce Elder | 0.275 | 0.305 | -0.030 |
Bryce Miller | 0.290 | 0.304 | -0.014 |
Bryse Wilson | 0.236 | 0.290 | -0.054 |
Buck Farmer | 0.244 | 0.264 | -0.020 |
Cal Quantrill | 0.300 | 0.309 | -0.009 |
Caleb Ferguson | 0.364 | 0.311 | 0.053 |
Camilo Doval | 0.308 | 0.282 | 0.026 |
Carlos Carrasco | 0.336 | 0.324 | 0.012 |
Carlos Estevez | 0.346 | 0.299 | 0.047 |
Carlos Hernandez | 0.287 | 0.307 | -0.020 |
Carlos Rodon | 0.287 | 0.285 | 0.002 |
Charlie Morton | 0.323 | 0.308 | 0.015 |
Chase Anderson | 0.292 | 0.288 | 0.004 |
Chase Silseth | 0.250 | 0.304 | -0.054 |
Chris Bassitt | 0.274 | 0.292 | -0.018 |
Chris Flexen | 0.333 | 0.318 | 0.015 |
Chris Martin | 0.301 | 0.337 | -0.036 |
Chris Sale | 0.291 | 0.284 | 0.007 |
Chris Stratton | 0.276 | 0.267 | 0.009 |
Cionel Perez | 0.323 | 0.293 | 0.030 |
Clarke Schmidt | 0.313 | 0.295 | 0.018 |
Clay Holmes | 0.301 | 0.306 | -0.005 |
Clayton Kershaw | 0.250 | 0.293 | -0.043 |
Cody Bradford | 0.285 | 0.288 | -0.003 |
Cole Irvin | 0.293 | 0.292 | 0.001 |
Cole Ragans | 0.275 | 0.295 | -0.020 |
Colin Holderman | 0.329 | 0.289 | 0.040 |
Colin Poche | 0.247 | 0.268 | -0.021 |
Colin Rea | 0.257 | 0.293 | -0.036 |
Collin McHugh | 0.348 | 0.324 | 0.024 |
Connor Seabold | 0.340 | 0.301 | 0.039 |
Corbin Burnes | 0.244 | 0.306 | -0.062 |
Corey Kluber | 0.301 | 0.285 | 0.016 |
Craig Kimbrel | 0.239 | 0.305 | -0.066 |
Cristian Javier | 0.273 | 0.270 | 0.003 |
Cristopher Sanchez | 0.273 | 0.295 | -0.022 |
Dakota Hudson | 0.305 | 0.312 | -0.007 |
Dane Dunning | 0.288 | 0.295 | -0.007 |
Daniel Lynch | 0.252 | 0.254 | -0.002 |
Danny Coulombe | 0.308 | 0.250 | 0.058 |
Dauri Moreta | 0.265 | 0.292 | -0.027 |
David Bednar | 0.299 | 0.261 | 0.038 |
David Peterson | 0.371 | 0.312 | 0.059 |
David Robertson | 0.297 | 0.272 | 0.025 |
Dean Kremer | 0.293 | 0.313 | -0.020 |
Derek Law | 0.278 | 0.305 | -0.027 |
Devin Williams | 0.198 | 0.315 | -0.117 |
Domingo German | 0.233 | 0.281 | -0.048 |
Dominic Leone | 0.255 | 0.294 | -0.039 |
Drew Smith | 0.301 | 0.267 | 0.034 |
Drew Smyly | 0.307 | 0.291 | 0.016 |
Drew VerHagen | 0.262 | 0.275 | -0.013 |
Dylan Cease | 0.331 | 0.306 | 0.025 |
Dylan Floro | 0.401 | 0.330 | 0.071 |
Eduardo Rodriguez | 0.275 | 0.309 | -0.034 |
Edward Cabrera | 0.285 | 0.268 | 0.017 |
Eli Morgan | 0.337 | 0.298 | 0.039 |
Elvis Peguero | 0.274 | 0.296 | -0.022 |
Emilio Pagan | 0.222 | 0.266 | -0.044 |
Emmanuel Clase | 0.296 | 0.296 | 0.000 |
Emmet Sheehan | 0.240 | 0.255 | -0.015 |
Enyel De Los Santos | 0.275 | 0.305 | -0.030 |
Erasmo Ramirez | 0.350 | 0.308 | 0.042 |
Erik Swanson | 0.280 | 0.251 | 0.029 |
Eury Perez | 0.264 | 0.270 | -0.006 |
Evan Phillips | 0.222 | 0.297 | -0.075 |
Felix Bautista | 0.274 | 0.260 | 0.014 |
Fernando Cruz | 0.317 | 0.294 | 0.023 |
Framber Valdez | 0.284 | 0.313 | -0.029 |
Freddy Peralta | 0.275 | 0.280 | -0.005 |
Gabe Speier | 0.305 | 0.303 | 0.002 |
Garrett Whitlock | 0.342 | 0.306 | 0.036 |
Gavin Williams | 0.270 | 0.310 | -0.040 |
Genesis Cabrera | 0.281 | 0.277 | 0.004 |
George Kirby | 0.293 | 0.285 | 0.008 |
George Soriano | 0.284 | 0.292 | -0.008 |
Gerrit Cole | 0.263 | 0.296 | -0.033 |
Giovanny Gallegos | 0.297 | 0.296 | 0.001 |
Graham Ashcraft | 0.293 | 0.308 | -0.015 |
Grayson Rodriguez | 0.323 | 0.313 | 0.010 |
Gregory Santos | 0.337 | 0.336 | 0.001 |
Gregory Soto | 0.265 | 0.274 | -0.009 |
Griffin Canning | 0.297 | 0.280 | 0.017 |
Griffin Jax | 0.299 | 0.292 | 0.007 |
Hayden Wesneski | 0.261 | 0.310 | -0.049 |
Hector Neris | 0.222 | 0.264 | -0.042 |
Hoby Milner | 0.254 | 0.291 | -0.037 |
Hogan Harris | 0.308 | 0.299 | 0.009 |
Huascar Brazoban | 0.318 | 0.306 | 0.012 |
Hunter Brown | 0.330 | 0.296 | 0.034 |
Hunter Greene | 0.342 | 0.278 | 0.064 |
Hunter Harvey | 0.253 | 0.282 | -0.029 |
Hyun Jin Ryu | 0.275 | 0.301 | -0.026 |
Ian Gibaut | 0.295 | 0.285 | 0.010 |
Ian Hamilton | 0.309 | 0.312 | -0.003 |
J.P. France | 0.290 | 0.298 | -0.008 |
Jack Flaherty | 0.357 | 0.318 | 0.039 |
Jacob Webb | 0.246 | 0.293 | -0.047 |
Jaime Barria | 0.286 | 0.292 | -0.006 |
Jake Bird | 0.333 | 0.302 | 0.031 |
Jake Diekman | 0.250 | 0.277 | -0.027 |
Jake Irvin | 0.281 | 0.280 | 0.001 |
Jakob Junis | 0.338 | 0.295 | 0.043 |
James Kaprielian | 0.324 | 0.279 | 0.045 |
James Paxton | 0.294 | 0.295 | -0.001 |
Jameson Taillon | 0.292 | 0.290 | 0.002 |
Jared Shuster | 0.277 | 0.277 | 0.000 |
Jason Adam | 0.239 | 0.263 | -0.024 |
Jason Foley | 0.310 | 0.319 | -0.009 |
Javier Assad | 0.269 | 0.292 | -0.023 |
Jeff Hoffman | 0.232 | 0.258 | -0.026 |
Jesse Scholtens | 0.313 | 0.297 | 0.016 |
Jesus Luzardo | 0.312 | 0.279 | 0.033 |
Jhoan Duran | 0.301 | 0.279 | 0.022 |
Jhony Brito | 0.268 | 0.274 | -0.006 |
Joan Adon | 0.333 | 0.313 | 0.020 |
Joe Jimenez | 0.304 | 0.318 | -0.014 |
Joe Musgrove | 0.305 | 0.300 | 0.005 |
Joe Ryan | 0.305 | 0.275 | 0.030 |
Joel Payamps | 0.277 | 0.287 | -0.010 |
Joey Wentz | 0.329 | 0.288 | 0.041 |
Johan Oviedo | 0.281 | 0.301 | -0.020 |
Johnny Cueto | 0.236 | 0.294 | -0.058 |
Jon Gray | 0.299 | 0.304 | -0.005 |
Jordan Hicks | 0.323 | 0.304 | 0.019 |
Jordan Lyles | 0.256 | 0.278 | -0.022 |
Jordan Montgomery | 0.295 | 0.311 | -0.016 |
Jordan Romano | 0.296 | 0.289 | 0.007 |
Jordan Weems | 0.223 | 0.272 | -0.049 |
Jorge Lopez | 0.316 | 0.330 | -0.014 |
Jose Berrios | 0.290 | 0.308 | -0.018 |
Jose Cisnero | 0.342 | 0.293 | 0.049 |
Jose Cuas | 0.322 | 0.311 | 0.011 |
Jose Hernandez | 0.299 | 0.284 | 0.015 |
Jose Leclerc | 0.244 | 0.250 | -0.006 |
Jose Quintana | 0.307 | 0.305 | 0.002 |
Jose Urquidy | 0.281 | 0.287 | -0.006 |
Josh Fleming | 0.280 | 0.308 | -0.028 |
Josh Hader | 0.269 | 0.265 | 0.004 |
Josh Sborz | 0.287 | 0.289 | -0.002 |
Josh Winckowski | 0.331 | 0.300 | 0.031 |
Josiah Gray | 0.293 | 0.290 | 0.003 |
JP Sears | 0.280 | 0.267 | 0.013 |
Julian Merryweather | 0.313 | 0.285 | 0.028 |
Julio Teheran | 0.266 | 0.300 | -0.034 |
Julio Urias | 0.285 | 0.279 | 0.006 |
Justin Lawrence | 0.305 | 0.315 | -0.010 |
Justin Steele | 0.320 | 0.304 | 0.016 |
Justin Topa | 0.297 | 0.303 | -0.006 |
Justin Verlander | 0.265 | 0.281 | -0.016 |
Ken Waldichuk | 0.313 | 0.289 | 0.024 |
Kendall Graveman | 0.256 | 0.296 | -0.040 |
Kenta Maeda | 0.293 | 0.294 | -0.001 |
Kevin Gausman | 0.324 | 0.299 | 0.025 |
Kevin Ginkel | 0.244 | 0.289 | -0.045 |
Kevin Kelly | 0.264 | 0.305 | -0.041 |
Keynan Middleton | 0.278 | 0.279 | -0.001 |
Kirby Yates | 0.213 | 0.279 | -0.066 |
Kodai Senga | 0.279 | 0.285 | -0.006 |
Kutter Crawford | 0.269 | 0.258 | 0.011 |
Kyle Bradish | 0.271 | 0.313 | -0.042 |
Kyle Finnegan | 0.294 | 0.316 | -0.022 |
Kyle Freeland | 0.312 | 0.298 | 0.014 |
Kyle Gibson | 0.311 | 0.300 | 0.011 |
Kyle Hendricks | 0.284 | 0.295 | -0.011 |
Kyle Muller | 0.375 | 0.298 | 0.077 |
Kyle Nelson | 0.331 | 0.300 | 0.031 |
Lance Lynn | 0.292 | 0.290 | 0.002 |
Logan Allen | 0.317 | 0.295 | 0.022 |
Logan Gilbert | 0.275 | 0.291 | -0.016 |
Logan Webb | 0.303 | 0.305 | -0.002 |
Louie Varland | 0.284 | 0.278 | 0.006 |
Lucas Erceg | 0.357 | 0.300 | 0.057 |
Lucas Giolito | 0.275 | 0.280 | -0.005 |
Lucas Sims | 0.215 | 0.252 | -0.037 |
Luis Castillo | 0.268 | 0.290 | -0.022 |
Luis Garcia | 0.301 | 0.308 | -0.007 |
Luis Ortiz | 0.309 | 0.307 | 0.002 |
Luis Medina | 0.306 | 0.311 | -0.005 |
Luis Severino | 0.328 | 0.314 | 0.014 |
Luke Weaver | 0.331 | 0.321 | 0.010 |
MacKenzie Gore | 0.310 | 0.306 | 0.004 |
Marco Gonzales | 0.316 | 0.317 | -0.001 |
Marcus Stroman | 0.283 | 0.314 | -0.031 |
Mark Leiter | 0.270 | 0.315 | -0.045 |
Martin Perez | 0.295 | 0.296 | -0.001 |
Mason Englert | 0.307 | 0.296 | 0.011 |
Mason Thompson | 0.352 | 0.293 | 0.059 |
Matt Brash | 0.380 | 0.274 | 0.106 |
Matt Manning | 0.216 | 0.276 | -0.060 |
Matt Moore | 0.295 | 0.280 | 0.015 |
Matt Strahm | 0.275 | 0.290 | -0.015 |
Matthew Boyd | 0.302 | 0.283 | 0.019 |
Matthew Liberatore | 0.314 | 0.301 | 0.013 |
Max Fried | 0.310 | 0.291 | 0.019 |
Max Scherzer | 0.265 | 0.279 | -0.014 |
Merrill Kelly | 0.279 | 0.302 | -0.023 |
Michael Fulmer | 0.304 | 0.297 | 0.007 |
Michael Grove | 0.364 | 0.323 | 0.041 |
Michael King | 0.307 | 0.301 | 0.006 |
Michael Kopech | 0.265 | 0.264 | 0.001 |
Michael Lorenzen | 0.268 | 0.290 | -0.022 |
Michael Tonkin | 0.243 | 0.286 | -0.043 |
Michael Wacha | 0.266 | 0.287 | -0.021 |
Miguel Castro | 0.251 | 0.315 | -0.064 |
Mike Baumann | 0.266 | 0.286 | -0.020 |
Mike Clevinger | 0.282 | 0.273 | 0.009 |
Miles Mikolas | 0.309 | 0.303 | 0.006 |
Mitch Keller | 0.310 | 0.302 | 0.008 |
Nathan Eovaldi | 0.271 | 0.297 | -0.026 |
Nestor Cortes | 0.291 | 0.260 | 0.031 |
Nick Martinez | 0.294 | 0.291 | 0.003 |
Nick Pivetta | 0.269 | 0.301 | -0.032 |
Nick Sandlin | 0.195 | 0.256 | -0.061 |
Noah Syndergaard | 0.289 | 0.316 | -0.027 |
Osvaldo Bido | 0.329 | 0.323 | 0.006 |
Pablo Lopez | 0.313 | 0.293 | 0.020 |
Patrick Corbin | 0.311 | 0.302 | 0.009 |
Patrick Sandoval | 0.309 | 0.321 | -0.012 |
Paul Blackburn | 0.351 | 0.320 | 0.031 |
Paul Sewald | 0.284 | 0.258 | 0.026 |
Pedro Avila | 0.305 | 0.310 | -0.005 |
Peter Lambert | 0.296 | 0.280 | 0.016 |
Phil Bickford | 0.293 | 0.274 | 0.019 |
Phil Maton | 0.270 | 0.280 | -0.010 |
Pierce Johnson | 0.363 | 0.352 | 0.011 |
Quinn Priester | 0.297 | 0.309 | -0.012 |
Rafael Montero | 0.358 | 0.300 | 0.058 |
Raisel Iglesias | 0.312 | 0.289 | 0.023 |
Ranger Suarez | 0.327 | 0.318 | 0.009 |
Reese Olson | 0.255 | 0.308 | -0.053 |
Reid Detmers | 0.318 | 0.317 | 0.001 |
Reynaldo Lopez | 0.278 | 0.276 | 0.002 |
Rich Hill | 0.323 | 0.312 | 0.011 |
Roansy Contreras | 0.318 | 0.295 | 0.023 |
Robert Stephenson | 0.222 | 0.274 | -0.052 |
Ronel Blanco | 0.280 | 0.294 | -0.014 |
Ross Stripling | 0.310 | 0.326 | -0.016 |
Ryan Brasier | 0.248 | 0.293 | -0.045 |
Ryan Pressly | 0.272 | 0.293 | -0.021 |
Ryan Walker | 0.356 | 0.293 | 0.063 |
Ryan Weathers | 0.327 | 0.287 | 0.040 |
Ryan Yarbrough | 0.302 | 0.289 | 0.013 |
Ryne Nelson | 0.301 | 0.282 | 0.019 |
Ryne Stanek | 0.258 | 0.270 | -0.012 |
Sam Hentges | 0.347 | 0.322 | 0.025 |
Sam Moll | 0.281 | 0.278 | 0.003 |
Sandy Alcantara | 0.289 | 0.299 | -0.010 |
Scott Barlow | 0.326 | 0.324 | 0.002 |
Scott McGough | 0.272 | 0.306 | -0.034 |
Sean Manaea | 0.293 | 0.307 | -0.014 |
Seranthony Dominguez | 0.291 | 0.292 | -0.001 |
Seth Lugo | 0.298 | 0.313 | -0.015 |
Shane Bieber | 0.295 | 0.313 | -0.018 |
Shane McClanahan | 0.274 | 0.296 | -0.022 |
Shawn Armstrong | 0.250 | 0.293 | -0.043 |
Shintaro Fujinami | 0.300 | 0.298 | 0.002 |
Shohei Ohtani | 0.240 | 0.286 | -0.046 |
Sonny Gray | 0.295 | 0.313 | -0.018 |
Spencer Strider | 0.316 | 0.295 | 0.021 |
Steven Matz | 0.320 | 0.299 | 0.021 |
Steven Okert | 0.299 | 0.299 | 0.000 |
Steven Wilson | 0.224 | 0.243 | -0.019 |
Taijuan Walker | 0.273 | 0.296 | -0.023 |
Taj Bradley | 0.312 | 0.311 | 0.001 |
Tanner Banks | 0.282 | 0.293 | -0.011 |
Tanner Bibee | 0.287 | 0.295 | -0.008 |
Tanner Houck | 0.299 | 0.296 | 0.003 |
Tanner Scott | 0.291 | 0.313 | -0.022 |
Tarik Skubal | 0.289 | 0.284 | 0.005 |
Taylor Clarke | 0.369 | 0.283 | 0.086 |
Taylor Rogers | 0.282 | 0.269 | 0.013 |
Tim Mayza | 0.331 | 0.312 | 0.019 |
Tom Cosgrove | 0.211 | 0.244 | -0.033 |
Tommy Henry | 0.278 | 0.286 | -0.008 |
Tony Gonsolin | 0.235 | 0.290 | -0.055 |
Touki Toussaint | 0.266 | 0.313 | -0.047 |
Trevor Gott | 0.345 | 0.302 | 0.043 |
Trevor Richards | 0.313 | 0.281 | 0.032 |
Trevor Stephan | 0.318 | 0.288 | 0.030 |
Trevor Williams | 0.316 | 0.298 | 0.018 |
Tristan Beck | 0.290 | 0.284 | 0.006 |
Tucker Davidson | 0.367 | 0.294 | 0.073 |
Ty Blach | 0.346 | 0.323 | 0.023 |
Tyler Anderson | 0.302 | 0.295 | 0.007 |
Tyler Glasnow | 0.294 | 0.294 | 0.000 |
Tyler Holton | 0.213 | 0.305 | -0.092 |
Tyler Rogers | 0.274 | 0.275 | -0.001 |
Tyler Wells | 0.200 | 0.258 | -0.058 |
Tylor Megill | 0.325 | 0.300 | 0.025 |
Wade Miley | 0.236 | 0.272 | -0.036 |
Wandy Peralta | 0.220 | 0.283 | -0.063 |
Will Smith | 0.262 | 0.290 | -0.028 |
Xzavion Curry | 0.295 | 0.288 | 0.007 |
Yennier Cano | 0.284 | 0.316 | -0.032 |
Yimi Garcia | 0.345 | 0.305 | 0.040 |
Yonny Chirinos | 0.286 | 0.316 | -0.030 |
Yu Darvish | 0.319 | 0.310 | 0.009 |
Yusei Kikuchi | 0.315 | 0.307 | 0.008 |
Zac Gallen | 0.301 | 0.311 | -0.010 |
Zach Davies | 0.348 | 0.308 | 0.040 |
Zach Eflin | 0.296 | 0.284 | 0.012 |
Zack Greinke | 0.300 | 0.304 | -0.004 |
Zack Littell | 0.295 | 0.292 | 0.003 |
Zack Thompson | 0.341 | 0.307 | 0.034 |
Zack Wheeler | 0.292 | 0.290 | 0.002 |
This is a lot of data to digest, but keep in mind it's backwards looking, or as the kids say, it's descriptive, not predictive. Not to mention, the assumption is the individual has no control over the authority of contact, or the number of line drives. It was never stated the pitcher has zero control, only that it's limited, at least compared to how able they are to induce grounders and flies.
The next step is incorporating xBABIP into formulaic projections. This obviously entails projecting batted ball distribution. Data presented last time (and linked above) illustrates that groundball and flyball rates correlate well from year to year. One approach could be to use a weighted average for groundball and flyball rate, similar to that utilized for other statistics. The line drive rate can be what's remaining after the others are computed.
This also requires projecting the component BABIP. Using the previous season's levels could suffice, as could a weighted average of a few previous seasons. For the purpose of projections, the precision isn't important since everyone gets the same treatment, so when they are compared on a relative basis, if everyone is a little too high, or a little too low, the rankings for drafting will be the same.
Some may find the above flawed, since pitchers exhibit little control over line drives. Perhaps the line drive rate should be the projected league average for everyone, then the ground ball and fly ball rates are derived from a projected GB/FB ratio.
An argument can be tendered for either method, especially when considered in light of the following: pitchers do exert some measure of influence. Determining how much is going to be subjective, just as it is with other statistics. A good projection system should allow for overriding, especially if it's a level of regression. As a simple example, if a pitcher yields 20 homers, but his xHR is 24, plugging anything between 20 and 24 into the little black box can be justified. If the prognosticator has a reason the pitcher should have surrendered 24 homers, plugging 24 in is defensible. Personally, I set regressions of this nature to 50 percent, then season to taste.
A more complex version of xBABIP can regress everything, including the pitcher's component BABIP, to league norm. This helps account for the pitcher's ability to influence their own numbers. In the case of xBABIP, my starting point will probably be a stronger regression to league mean for all of the involved factors.
The objective of this presentation is not to spur everyone to fire up Excel and crunch xBABIP for 750 pitchers expect to appear in MLB this season. By all means, if you so desire, go for it. The primary goal is to illustrate BABIP has a wider acceptable range than many assume. You don't need to set up formulas. After checking out a pitcher's BABIP, look at their batted ball distribution. Maybe you shouldn't hang onto a perceived unlucky guy or fade an assumed lucky one. Just don't give the pitcher too much credit (or blame) for the delta from expected.