Blasts: A Subset of Barrels

I’ve heard (read) a lot of hullabaloo about “not all barrels are equal.” Hullabaloo or not, it’s true; although barrels capture exit velocity (EV) and launch angle (LA) combinations that produce optimal wOBAcon (weighted on-base average on contact) results, the Statcast metric is defined broadly enough to include absolute blasts alongside somewhat-pedestrian hard hits within the same grouping.

The algorithm used to classify barrels is not publicly available (edit: an anonymous tipster alerted me that it, indeed, is available! I think I reverse-engineered it correctly just by sight…), but one can reverse-engineer it easily enough. Here’s a plot of all barrels since the start of the 2017 season.

Given the scatterplot, the formula is most likely as follows:

if EV < 97.5 mph, then barrel = no
if LA > 25.5° and LA < 30.5°, then barrel = yes
if LA < 25.5° and (25.5 – LA) < (EV – 97.5), then barrel = yes
if LA > 30.5° and ((LA – 30.5) * 2) < ((EV – 97.5) * 3), then barrel = yes
if EV > 97.5 mph but none of these apply, then barrel = no

“Not all barrels are equal” takes on its meaning once you convert the above scatterplot to a heatmap. I set the low end of the color legend artificially high to show the contrast between barrels that are relatively productive versus those that are massively productive:

The blue strip bordering a mostly red heatmap captures the contact qualities that range from [decent EV at optimal LA] to [excellent EV at suboptimal LA]. They’re good but not great.

To put words in its creators’ mouths, barrel rate is functional as a metric because it correlates well with many other measures of production, both descriptively and predictively. So, what happens when we shave off the blue fat? What if we pinch the base of the graphic above — instead of a base of launch angles from 25.5° to 30.5°, we condense it to just the midpoint, 28° — and increase the lowest EV threshold from 97.5 mph to 100 mph?

if EV < 100 mph, then blast = no
if LA < 28° and (28 – LA) < (EV – 100), then blast = yes
if LA > 28° and ((LA – 28) * 2) < ((EV – 100) * 3), then blast = yes
if EV > 100 mph but none of these apply, then blast = no

Turns out we nearly perfectly isolate the reddened portion of the heatmap. I call these orange dots “blasts,” for lack of a better word (although “long bombs away” was a serious contender). Because I don’t have a name for the blue area, but because I will need to refer to these other batted balls, I’ll call them “weak barrels.”

Some mildly interesting things happen by establishing blasts:

Statcast barrels are divided nearly perfectly 50-50 between blasts and weak barrels. Since the start of 2017, Statcast barrels have been 46% blasts, 54% weak barrels. It makes for a really nice league-wide benchmark; you know now that the average hitter’s barrels are likely to be half-blasts, half-weak, and any variations in talent deviate from there. I like the evenness of the split, at least.

The productive value of a blast is starkly different from that of a weak barrel. Since the start of 2017, barrels averaged a 1.416 wOBAcon, 58% home run rate, and .804 AVG. Now, blasts average a 1.744 wOBAcon, 82% HR/BBE, and .919 AVG while weak barrels average a 1.140 wOBAcon, 38% HR/BBE, and .707 AVG.

By narrowing Statcast barrels down to blasts, we neither substantively gain nor substantively lose descriptive or predictive power. Blasts predict themselves year-to-year (r2 = 0.66) just as well as barrels do (r2 = 0.66). Their relationships with wOBAcon, both descriptively (blast r2 = 0.59, barrel r2 = 0.62) and predictively (blast r2 = 0.41, barrel r2 = 0.42), are virtually indistinguishable. Ultimately, it’s largely a neutral/lateral move — which I’ll chalk up as a minor overall gain. (Barrels make up only 7% of all batted balls yet describe roughly 60% of the variance in wOBAcon; now just 3% of all batted balls can explain that variance. That’s really wild!)

A pessimist (me, admittedly) might ask, “Well, if we don’t gain anything [if you’re really pessimistic, you’ll nitpick the r2 and think we’ve lost something], what’s the point of another metric?” An optimist (me, but only in this instance) might respond, “Now we have two ways to measure excellent contact quality that, while, fundamentally different, can be used interchangeably. Moreover, it’s possible they’re most illuminating when used not just in place of each other but together.” Because wouldn’t you want to know if the majority of someone’s barrels were blasts (Luke Voit, Teoscar Hernández) or “weak” (Mookie Betts, Mike Moustakas)?

I hope this provides another tool for the ol’ tool belt — one not necessarily superior to anything we already have but does measure something we maybe hadn’t measured quite this way before.

Blast% is now hosted on my Pitch Leaderboard, where you can sort by all of Statcast’s original definitions for BBEs (barrels, solid contact, flares/burners, and poor contact) as well as by blasts. Blasts are viewable for both hitters and pitchers!

If you’re too lazy to click through, you can view a table of barrels leaders here, with barrels split into blasts and weak barrels. Nearly 200 hitters recorded at least 100 BBE last year, presented below; by default, they’re sorted descending by overall barrel rate (Barrel%).

2020 Barrel% Leaders
Name BBE EV Max EV Blast% Weak Brl Barrel%
Fernando Tatis Jr. 164 95.9 113.4 9.1% 10.4% 19.5%
Teoscar Hernandez 128 93.3 115.9 12.5% 5.5% 18.0%
Juan Soto 123 92.2 113.3 11.4% 6.5% 17.9%
Brandon Lowe 137 89.8 111.4 9.5% 8.0% 17.5%
Bryce Harper 150 92.2 114.7 12.0% 5.3% 17.3%
Brandon Belt 113 90.7 109.1 7.1% 9.7% 16.8%
Eloy Jimenez 158 92.4 113.6 5.7% 10.8% 16.5%
Nicholas Castellanos 150 91.0 108.5 6.0% 10.0% 16.0%
Ronald Acuna 100 92.4 114.8 13.0% 3.0% 16.0%
Corey Seager 177 93.2 113.1 6.2% 9.6% 15.8%
Marcell Ozuna 169 93.0 115.6 10.1% 5.3% 15.4%
Mike Trout 147 93.7 112.9 10.9% 4.1% 15.0%
Nelson Cruz 127 91.6 114.4 11.0% 3.9% 15.0%
Wil Myers 142 91.0 109.2 7.7% 7.0% 14.8%
Rhys Hoskins 108 89.8 111.2 7.4% 7.4% 14.8%
Freddie Freeman 177 92.4 109.3 6.8% 7.9% 14.7%
Eugenio Suarez 132 89.1 111.4 8.3% 6.1% 14.4%
Mitch Moreland 104 88.2 110.1 4.8% 9.6% 14.4%
Jose Abreu 182 92.9 114.0 7.1% 7.1% 14.3%
Keston Hiura 134 87.4 110.2 9.0% 5.2% 14.2%
Joey Gallo 114 90.7 113.5 7.9% 6.1% 14.0%
Adam Duvall 137 88.1 114.2 8.8% 5.1% 13.9%
J.T. Realmuto 124 90.1 112.4 6.5% 7.3% 13.7%
Jesse Winker 104 92.1 113.0 6.7% 6.7% 13.5%
Colin Moran 127 91.9 112.0 7.1% 6.3% 13.4%
Dominic Smith 135 89.8 110.7 5.9% 7.4% 13.3%
Edwin Encarnacion 106 85.4 112.9 5.7% 7.5% 13.2%
Luke Voit 160 88.9 111.7 10.6% 2.5% 13.1%
Luis Robert 131 87.9 115.8 9.2% 3.8% 13.0%
Salvador Perez 115 90.8 110.4 6.1% 7.0% 13.0%
Franmil Reyes 147 92.4 114.7 6.8% 6.1% 12.9%
Pete Alonso 148 90.2 118.4 10.8% 2.0% 12.8%
Matt Olson 133 92.3 112.5 6.0% 6.8% 12.8%
George Springer 153 88.7 115.0 9.8% 2.6% 12.4%
Max Muncy 145 88.5 109.8 6.2% 6.2% 12.4%
Renato Nunez 130 86.4 110.3 6.2% 6.2% 12.3%
Rafael Devers 165 93.0 116.7 6.7% 5.5% 12.1%
Christian Yelich 124 94.0 112.0 7.3% 4.8% 12.1%
Kole Calhoun 144 89.4 109.0 3.5% 8.3% 11.8%
Lourdes Gurriel 162 90.8 109.5 4.3% 7.4% 11.7%
Kyle Lewis 137 88.3 110.9 5.8% 5.8% 11.7%
Ryan Braun 103 89.8 110.2 4.9% 6.8% 11.7%
Evan Longoria 157 91.7 111.5 5.1% 6.4% 11.5%
Chris Taylor 131 87.7 109.6 4.6% 6.9% 11.5%
Dansby Swanson 167 89.0 109.3 4.2% 7.2% 11.4%
Randal Grichuk 169 88.9 110.9 4.1% 7.1% 11.2%
Kyle Schwarber 125 92.8 114.9 8.8% 2.4% 11.2%
Justin Turner 125 90.3 107.8 3.2% 8.0% 11.2%
Travis d’Arnaud 116 93.4 109.7 6.0% 5.2% 11.2%
Ryan McMahon 107 90.1 109.7 4.7% 6.5% 11.2%
Trent Grisham 153 88.3 111.9 7.2% 3.9% 11.1%
Manny Machado 191 90.2 115.7 6.3% 4.7% 11.0%
J.D. Martinez 154 89.5 110.7 3.9% 7.1% 11.0%
Michael Conforto 145 88.4 114.4 4.1% 6.9% 11.0%
Mike Yastrzemski 137 88.2 105.6 6.6% 4.4% 10.9%
Paul Goldschmidt 149 89.2 111.3 3.4% 7.4% 10.7%
Alex Dickerson 122 91.0 114.6 4.9% 5.7% 10.7%
Shohei Ohtani 103 89.1 111.9 5.8% 4.9% 10.7%
A.J. Pollock 153 89.6 110.0 4.6% 5.9% 10.5%
Jake Cronenworth 143 89.8 110.1 3.5% 7.0% 10.5%
Willson Contreras 134 89.8 114.1 5.2% 5.2% 10.4%
Jeimer Candelario 136 90.2 110.8 3.7% 6.6% 10.3%
Ian Happ 136 91.1 109.1 5.1% 5.1% 10.3%
Anthony Santander 126 88.4 113.2 3.2% 7.1% 10.3%
Alec Bohm 126 90.2 109.6 3.2% 7.1% 10.3%
Eric Hosmer 117 90.8 112.0 6.0% 4.3% 10.3%
Jose Ramirez 177 88.7 114.3 4.5% 5.6% 10.2%
Kyle Seager 176 89.1 108.7 2.3% 8.0% 10.2%
Bryan Reynolds 128 87.5 110.7 4.7% 5.5% 10.2%
Tim Anderson 159 87.2 108.8 5.7% 4.4% 10.1%
Austin Riley 140 91.0 111.0 6.4% 3.6% 10.0%
Willy Adames 111 88.8 109.1 4.5% 5.4% 9.9%
Miguel Cabrera 155 93.2 112.2 5.2% 4.5% 9.7%
Brian Anderson 135 87.5 109.5 4.4% 5.2% 9.6%
Mike Moustakas 105 88.8 111.7 1.9% 7.6% 9.5%
Cody Bellinger 171 89.3 110.6 4.1% 5.3% 9.4%
Ramon Laureano 128 87.7 111.3 4.7% 4.7% 9.4%
Brandon Crawford 127 88.7 109.8 1.6% 7.9% 9.4%
Yoshitomo Tsutsugo 108 90.2 108.9 4.6% 4.6% 9.3%
Trea Turner 196 90.4 111.2 4.6% 4.6% 9.2%
Joey Votto 142 87.4 113.2 4.9% 4.2% 9.2%
Kyle Tucker 164 91.1 110.9 3.7% 5.5% 9.1%
J.D. Davis 135 90.1 111.2 4.4% 4.4% 8.9%
Vladimir Guerrero Jr. 183 92.5 116.1 3.3% 5.5% 8.7%
Trevor Story 172 90.0 109.0 4.1% 4.7% 8.7%
Ty France 104 85.7 108.2 3.8% 4.8% 8.7%
Xander Bogaerts 163 89.0 112.5 5.5% 3.1% 8.6%
Josh Bell 140 91.7 114.2 4.3% 4.3% 8.6%
Rio Ruiz 139 88.3 109.0 0.7% 7.9% 8.6%
Pat Valaika 105 88.6 108.2 3.8% 4.8% 8.6%
Justin Upton 105 91.7 111.5 3.8% 4.8% 8.6%
Andrew McCutchen 170 89.8 109.9 3.5% 4.7% 8.2%
Hunter Dozier 110 86.4 110.3 3.6% 4.5% 8.2%
Javier Baez 149 89.4 116.0 4.7% 3.4% 8.1%
Garrett Hampson 111 86.3 105.6 2.7% 5.4% 8.1%
Travis Shaw 114 90.9 112.8 5.3% 2.6% 7.9%
Anthony Rizzo 167 87.8 114.5 3.0% 4.8% 7.8%
Austin Nola 129 89.7 110.1 2.3% 5.4% 7.8%
Mookie Betts 182 90.7 108.5 0.5% 7.1% 7.7%
Brandon Nimmo 143 87.2 106.9 4.2% 3.5% 7.7%
Mark Canha 142 89.7 108.9 2.8% 4.9% 7.7%
Jackie Bradley Jr. 144 88.3 112.4 2.8% 4.9% 7.6%
Yasmani Grandal 105 90.3 110.5 3.8% 3.8% 7.6%
Paul DeJong 106 89.2 105.5 1.9% 5.7% 7.5%
Robinson Cano 148 90.4 113.5 4.1% 3.4% 7.4%
Pedro Severino 121 87.6 111.2 3.3% 4.1% 7.4%
Adalberto Mondesi 151 90.6 111.0 3.3% 4.0% 7.3%
Enrique Hernandez 109 88.5 110.2 3.7% 3.7% 7.3%
Jesus Aguilar 152 89.3 109.9 3.9% 3.3% 7.2%
Wilson Ramos 112 89.0 110.1 4.5% 2.7% 7.1%
Aaron Hicks 131 87.9 109.5 4.6% 2.3% 6.9%
Giovanny Urshela 130 91.4 111.0 1.5% 5.4% 6.9%
Carlos Santana 164 87.9 111.5 3.7% 3.0% 6.7%
Erik Gonzalez 134 88.5 111.4 2.2% 4.5% 6.7%
Asdrubal Cabrera 151 89.7 107.0 2.0% 4.6% 6.6%
Stephen Piscotty 108 88.1 111.1 3.7% 2.8% 6.5%
Starling Marte 188 87.1 110.6 3.7% 2.7% 6.4%
Christian Walker 171 90.4 110.4 3.5% 2.9% 6.4%
Alex Verdugo 157 87.0 109.5 1.3% 5.1% 6.4%
Anthony Rendon 158 90.1 109.1 2.5% 3.8% 6.3%
Eddie Rosario 178 87.5 105.0 2.2% 3.9% 6.2%
Yoan Moncada 130 87.8 109.9 3.8% 2.3% 6.2%
Wilmer Flores 163 87.9 107.8 3.1% 3.1% 6.1%
Jean Segura 148 87.7 109.4 2.7% 3.4% 6.1%
Carlos Correa 153 88.6 109.0 2.6% 3.3% 5.9%
Maikel Franco 189 86.7 112.5 2.1% 3.7% 5.8%
Corey Dickerson 159 85.7 108.8 2.5% 3.1% 5.7%
Francisco Lindor 197 89.9 111.4 2.5% 3.0% 5.6%
Orlando Arcia 142 89.0 108.7 1.4% 4.2% 5.6%
Jonathan Schoop 125 87.2 114.4 4.0% 1.6% 5.6%
Eduardo Escobar 164 88.6 106.7 1.8% 3.7% 5.5%
Robbie Grossman 128 89.0 108.1 0.8% 4.7% 5.5%
Albert Pujols 128 88.6 108.8 1.6% 3.9% 5.5%
Kevin Pillar 167 87.0 108.0 1.2% 4.2% 5.4%
Nolan Arenado 166 87.8 108.9 3.0% 2.4% 5.4%
Nick Ahmed 153 87.7 107.7 1.3% 3.9% 5.2%
Todd Frazier 115 87.8 108.1 1.7% 3.5% 5.2%
Whit Merrifield 216 86.1 105.8 0.5% 4.6% 5.1%
Marwin Gonzalez 138 89.2 106.0 3.6% 1.4% 5.1%
Max Kepler 136 88.5 110.3 2.9% 2.2% 5.1%
Marcus Semien 161 86.2 108.0 1.9% 3.1% 5.0%
David Peralta 160 89.2 113.8 1.9% 3.1% 5.0%
Cavan Biggio 159 87.4 103.6 0.6% 4.4% 5.0%
Charlie Blackmon 182 86.9 109.7 1.6% 3.3% 4.9%
Michael Brantley 142 88.5 105.3 0.0% 4.9% 4.9%
Daniel Murphy 103 85.1 109.6 1.0% 3.9% 4.9%
Tommy La Stella 187 88.0 108.8 0.5% 4.3% 4.8%
Josh Reddick 147 85.9 106.7 1.4% 3.4% 4.8%
Luis Garcia 105 83.5 111.1 1.9% 2.9% 4.8%
Nick Solak 171 89.9 111.7 1.8% 2.9% 4.7%
Adam Eaton 128 87.8 109.8 3.1% 1.6% 4.7%
Jose Altuve 153 86.7 106.9 1.3% 3.3% 4.6%
Donovan Solano 152 88.5 108.1 0.7% 3.9% 4.6%
Christian Vazquez 130 88.4 108.8 2.3% 2.3% 4.6%
Jason Heyward 112 87.6 108.1 3.6% 0.9% 4.5%
Freddy Galvis 111 87.0 107.7 0.9% 3.6% 4.5%
Didi Gregorius 190 83.8 104.7 1.1% 3.2% 4.2%
Manuel Margot 121 89.0 108.2 0.8% 3.3% 4.1%
Cesar Hernandez 177 89.1 108.2 2.3% 1.7% 4.0%
Adam Frazier 175 85.5 107.5 1.7% 2.3% 4.0%
Mauricio Dubon 124 86.2 106.3 1.6% 2.4% 4.0%
Alex Bregman 128 88.9 105.6 0.8% 3.1% 3.9%
Luis Arraez 102 87.5 103.7 0.0% 3.9% 3.9%
Tommy Edman 158 86.7 109.0 0.6% 3.2% 3.8%
Victor Reyes 157 90.0 108.6 2.5% 1.3% 3.8%
Avisail Garcia 132 87.4 113.3 3.0% 0.8% 3.8%
Yulieski Gurriel 189 89.3 107.1 1.1% 2.6% 3.7%
Ketel Marte 163 89.0 115.9 0.0% 3.7% 3.7%
Joey Wendle 134 86.7 104.9 1.5% 2.2% 3.7%
Amed Rosario 109 86.5 107.8 1.8% 1.8% 3.7%
Gleyber Torres 108 88.6 110.2 2.8% 0.9% 3.7%
Jurickson Profar 155 87.2 107.7 1.9% 1.3% 3.2%
Jose Iglesias 126 86.2 110.2 1.6% 1.6% 3.2%
Alex Gordon 126 82.8 112.3 2.4% 0.8% 3.2%
DJ LeMahieu 175 91.3 109.5 1.1% 1.7% 2.9%
Jorge Polanco 177 86.6 109.2 0.6% 2.3% 2.8%
Tim Lopes 109 87.2 109.1 0.0% 2.8% 2.8%
Cedric Mullins 107 88.6 110.2 2.8% 0.0% 2.8%
Jeff McNeil 162 86.6 106.2 1.2% 1.2% 2.5%
Yadier Molina 126 84.7 104.2 0.8% 1.6% 2.4%
Isiah Kiner-Falefa 180 87.2 106.2 0.0% 2.2% 2.2%
Raimel Tapia 150 85.3 107.2 1.3% 0.7% 2.0%
Nick Markakis 107 89.0 106.1 0.0% 1.9% 1.9%
J.P. Crawford 167 85.8 110.1 1.2% 0.6% 1.8%
Victor Robles 117 81.9 109.2 0.9% 0.9% 1.7%
Jonathan Villar 134 86.7 111.1 1.5% 0.0% 1.5%
Nicky Lopez 131 84.9 104.6 0.0% 1.5% 1.5%
Hanser Alberto 188 82.7 103.8 0.0% 1.1% 1.1%
Miguel Rojas 107 87.3 107.0 0.9% 0.0% 0.9%
Shogo Akiyama 121 85.1 104.0 0.0% 0.8% 0.8%
Kevin Newman 138 85.5 104.7 0.0% 0.7% 0.7%
Kolten Wong 154 86.5 103.7 0.0% 0.6% 0.6%
David Fletcher 185 84.7 107.0 0.0% 0.5% 0.5%
Andrelton Simmons 102 86.8 105.8 0.0% 0.0% 0.0%
SOURCE: Statcast/Pitch Leaderboard
Barrel% = barrels per BBE
Click headers to sort!

Justin Choi recently wrote about Nick Castellanos‘ barrels issue here; the distinction between blasts and weak barrels further supports that narrative.

Thanks to Tango and the Statcast team for doing all the hard work and developing the “barrel” taxonomy in the first place. Apologies to anyone who I may have inadvertently mimicked or copied in my work here; surely someone has had this very train of thought before.





Currently investigating the relationship between pitcher effectiveness and beard density. Two-time FSWA award winner, including 2018 Baseball Writer of the Year, and 8-time award finalist. Previously featured in Lindy's Sports' Fantasy Baseball magazine (2018, 2019). Tout Wars competitor. Biased toward a nicely rolled baseball pant.

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Tatis Jr rocks