Using StatCast and BIS Batted Ball Data to Assess Expected Power Output

Major League front offices have had access to comprehensive StatCast data all season, data that describes essentially everything quantifiable about the movements of fielders, baserunners, batters and the baseball. Those of us in the public realm have only been privy to what’s released sparsely through MLB’s GameDay and At Bat applications. Baseball Savant, an invaluable resource for many things created by Daren Willman, has collected exit velocity and distance for most at bats, presenting it in the form of aggregate statistics for individual players. The data seems to be a little messy, as Jeff Sullivan found, but there’s enough of it that anomalies should be smoothed over enough to make critical conclusions.

At the same time, Baseball Info Solutions has been collecting data for contact quality and direction for every plate appearance since 2002, using manual data entry. Fangraphs recently shared this data on their site, providing information that should prove very useful in lieu of more detailed StatCast or Hitf/x outputs.

This article is my first foray into the new batted ball information and will present a fairly basic expression of expected isolated power. I looked at all hitters in 2015 with at least 65 at-bats of StatCast data and 100 plate appearances overall (all statistics through June 7th) and merged the datasets together to derive an appropriate regression. The good thing about isolated power is that it isn’t that dependent on things such as speed that are immeasurable with by this data. If I were to create a similar metric in the future to predict BABIP or more general measures of production, more datasets would need to be included to capture the additional significant player effects.

The model I came up with uses main effects for average fly ball velocity, average ground ball velocity, average distance, hard-hit percentage and pull percentage, and the interaction effects between average fly ball velocity and average feet, and average fly ball velocity and average ground ball velocity. Basically, it includes effects for each distinct element of contact quality. All together, we have a fair amount of quality data here, but as the season continues the model will need to be re-tuned to account for the new information.

expected isolated power



This chart shows a pretty tight fit. If you hit the ball hard, at the right angle and in the right direction, you’re liable to hit a lot for many extra bases. Some players stick out on the chart and I’ve highlighted them with labels. Bryce Harper has hit the ball very hard this year and has been rewarded. But he appears to be hitting above his means and doesn’t deserve to be running away with the sport’s ISO lead. Fifteen hitters have posted better expected isolated slugging percentages.

Taking this information at face value (as a legitimate metric that measures more talent and less noise than standard ISO), we could say that these players can be expected to perform closer to if not at their expected marks in the future. Players who have outperformed their expected isolated power have been lucky to generate so many extra bases given their contact quality, while players who have underperformed have been unlucky. Here is the full table, for reference.

Giancarlo Stanton0.3150.3-0.015
Joc Pederson0.3110.320.009
Steven Souza0.2930.22-0.073
Chris Davis0.2820.25-0.032
Brandon Moss0.2680.234-0.034
Todd Frazier0.2670.3110.044
Paul Goldschmidt0.260.3130.053
Brandon Belt0.2570.215-0.042
Ryan Howard0.2560.25-0.006
Pedro Alvarez0.2440.209-0.035
Freddie Freeman0.2430.221-0.022
Troy Tulowitzki0.240.191-0.049
Mark Teixeira0.2360.3280.092
Jay Bruce0.2350.196-0.039
Chris Carter0.2340.187-0.047
Bryce Harper0.230.380.15
Ryan Braun0.2270.2420.015
J.D. Martinez0.2270.194-0.033
Mike Trout0.2260.2780.052
Adrian Gonzalez0.2250.2660.041
Mark Trumbo0.2250.2260.001
Adam Lind0.2230.219-0.004
Colby Rasmus0.2230.2420.019
Alex Rodriguez0.2190.2420.023
Mike Napoli0.2190.196-0.023
Brian Dozier0.2180.2630.045
Starling Marte0.2180.217-0.001
Andrew McCutchen0.2150.208-0.007
Evan Gattis0.2150.2440.029
Anthony Rizzo0.2140.2760.062
Adam LaRoche0.2130.161-0.052
Josh Donaldson0.2130.2640.051
Khris Davis0.2120.196-0.016
Miguel Cabrera0.2110.2380.027
Curtis Granderson0.2110.156-0.055
Lucas Duda0.2090.220.011
Luis Valbuena0.2080.2140.006
Nelson Cruz0.2060.2840.078
Brett Lawrie0.2040.126-0.078
Jose Bautista0.2040.2790.075
Mitch Moreland0.2040.2040
Shin-Soo Choo0.2040.186-0.018
David Freese0.2030.191-0.012
Steve Pearce0.2010.15-0.051
Danny Espinosa0.2010.2030.002
Yoenis Cespedes0.20.20
Devon Travis0.1990.2330.034
Nolan Arenado0.1990.2720.073
Charlie Blackmon0.1990.158-0.041
Evan Longoria0.1960.141-0.055
Brandon Crawford0.1950.2030.008
David Peralta0.1950.2070.012
Joey Votto0.1940.2250.031
Brad Miller0.1920.179-0.013
Jason Castro0.1910.176-0.015
Jorge Soler0.190.138-0.052
Jose Abreu0.1880.1990.011
Marlon Byrd0.1870.230.043
Eric Hosmer0.1870.1880.001
George Springer0.1860.182-0.004
Carlos Santana0.1860.155-0.031
Gerardo Parra0.1840.157-0.027
Edwin Encarnacion0.1840.2190.035
Matt Adams0.1830.132-0.051
Andre Ethier0.1820.2120.03
Will Middlebrooks0.1810.178-0.003
Prince Fielder0.1810.1910.01
Albert Pujols0.180.2490.069
Michael Cuddyer0.180.141-0.039
Michael Morse0.180.078-0.102
Yasmani Grandal0.1790.16-0.019
Marcell Ozuna0.1780.101-0.077
Marwin Gonzalez0.1760.126-0.05
Logan Forsythe0.1750.1840.009
Jhonny Peralta0.1740.2030.029
Stephen Vogt0.1730.2540.081
Chris Coghlan0.1730.1940.021
Jimmy Paredes0.1710.1790.008
Matt Carpenter0.1710.2230.052
Adam Jones0.1710.1980.027
Josh Reddick0.170.2050.035
Brian McCann0.170.2180.048
A.J. Pierzynski0.1690.152-0.017
David Ortiz0.1690.156-0.013
Miguel Montero0.1680.1720.004
Kris Bryant0.1670.190.023
Seth Smith0.1650.2260.061
Wil Myers0.1640.2010.037
Christian Yelich0.1640.063-0.101
Neil Walker0.1640.132-0.032
Justin Turner0.1630.1890.026
Carlos Beltran0.1630.153-0.01
Marcus Semien0.1630.149-0.014
Logan Morrison0.1620.131-0.031
David DeJesus0.1620.16-0.002
Lorenzo Cain0.1620.126-0.036
Billy Butler0.1610.1-0.061
Eduardo Escobar0.1610.125-0.036
Kendrys Morales0.160.1760.016
Torii Hunter0.160.1710.011
Carlos Gomez0.1580.1790.021
Nick Castellanos0.1570.122-0.035
Carlos Gonzalez0.1560.137-0.019
Ian Desmond0.1550.141-0.014
Kyle Seager0.1550.1840.029
Matt Duffy0.1550.134-0.021
Mark Canha0.1550.1840.029
Hanley Ramirez0.1540.2140.06
Chase Headley0.1540.133-0.021
Chris Colabello0.1540.1740.02
Derek Norris0.1530.1810.028
Yangervis Solarte0.1530.104-0.049
Robinson Cano0.1520.081-0.071
Justin Upton0.1520.2150.063
Adrian Beltre0.150.150
Buster Posey0.150.1650.015
Salvador Perez0.150.1760.026
Caleb Joseph0.1490.138-0.011
A.J. Pollock0.1490.1730.024
Russell Martin0.1490.2150.066
Trevor Plouffe0.1490.1840.035
Dustin Ackley0.1480.134-0.014
Alex Gordon0.1470.1750.028
Wilmer Flores0.1470.1750.028
David Murphy0.1450.1470.002
Avisail Garcia0.1450.141-0.004
Jordy Mercer0.1450.073-0.072
Kolten Wong0.1450.1560.011
Matt Kemp0.1440.097-0.047
Dustin Pedroia0.1430.1480.005
Nick Hundley0.1430.1660.023
Daniel Murphy0.1420.131-0.011
Mookie Betts0.1410.133-0.008
Ryan Zimmerman0.140.140
Kevin Kiermaier0.1390.1750.036
Conor Gillaspie0.1380.127-0.011
Manny Machado0.1370.1870.05
Francisco Cervelli0.1370.074-0.063
Starlin Castro0.1350.087-0.048
Zack Cozart0.1350.1740.039
Kevin Pillar0.1330.122-0.011
Jake Marisnick0.1330.1480.015
Austin Jackson0.1320.114-0.018
Cody Asche0.130.094-0.036
Asdrubal Cabrera0.130.104-0.026
Kole Calhoun0.130.123-0.007
Yasmany Tomas0.1290.085-0.044
Alexei Ramirez0.1290.087-0.042
Yadier Molina0.1280.048-0.08
Victor Martinez0.1280.054-0.074
Ike Davis0.1260.1460.02
Josh Harrison0.1260.1320.006
Michael Brantley0.1260.1590.033
Odubel Herrera0.1260.117-0.009
Jeff Francoeur0.1250.1690.044
Aramis Ramirez0.1240.1660.042
Brett Gardner0.1230.160.037
Will Venable0.1220.1480.026
Jimmy Rollins0.1220.1350.013
Joe Panik0.1220.1410.019
Martin Prado0.120.087-0.033
Juan Uribe0.120.112-0.008
Rene Rivera0.120.08-0.04
Cory Spangenberg0.1190.113-0.006
J.T. Realmuto0.1180.1350.017
Kurt Suzuki0.1170.079-0.038
Mike Moustakas0.1170.1460.029
Ender Inciarte0.1150.093-0.022
Delmon Young0.1150.077-0.038
Gregory Polanco0.1150.109-0.006
Brock Holt0.1140.1160.002
Lonnie Chisenhall0.1130.1360.023
Jason Kipnis0.1130.180.067
Ryan Goins0.1130.09-0.023
Nick Ahmed0.1130.099-0.014
Jason Heyward0.1130.1320.019
Denard Span0.1130.1650.052
Jose Altuve0.1120.107-0.005
DJ LeMahieu0.1120.094-0.018
Johnny Giavotella0.1120.092-0.02
Matt Joyce0.1110.1380.027
Nick Markakis0.1110.067-0.044
Pablo Sandoval0.1110.1110
Leonys Martin0.1110.102-0.009
Andrelton Simmons0.110.1170.007
Xander Bogaerts0.1090.106-0.003
Jean Segura0.1080.1270.019
Adeiny Hechavarria0.1080.1210.013
Howie Kendrick0.1080.1440.036
Joe Mauer0.1070.101-0.006
Dexter Fowler0.1070.150.043
Stephen Drew0.1070.1680.061
Cameron Maybin0.1060.1320.026
Adam Eaton0.1060.1290.023
Brandon Phillips0.1060.079-0.027
Chase Utley0.1050.1190.014
James McCann0.1050.1260.021
Michael Bourn0.1040.058-0.046
Jose Reyes0.1030.087-0.016
Elvis Andrus0.1020.079-0.023
Erick Aybar0.0990.052-0.047
Juan Lagares0.0990.071-0.028
Jace Peterson0.0990.074-0.025
Melky Cabrera0.0980.032-0.066
Danny Santana0.0950.073-0.022
Jose Ramirez0.0930.06-0.033
Wilson Ramos0.0930.1170.024
Chris Owings0.0920.089-0.003
Matt Holliday0.0920.1130.021
Sam Fuld0.0920.0960.004
Ian Kinsler0.0890.0890
Jon Jay0.0890.016-0.073
Yunel Escobar0.0890.072-0.017
Omar Infante0.0880.087-0.001
Brandon Guyer0.0870.1070.02
Jacoby Ellsbury0.0840.047-0.037
Anthony Gose0.0830.110.027
Didi Gregorius0.080.073-0.007
James Loney0.0770.1010.024
Eric Sogard0.0760.039-0.037
Alcides Escobar0.0740.0910.017
Dee Gordon0.0740.068-0.006
Brayan Pena0.0730.053-0.02
Nori Aoki0.070.0840.014
Alexi Amarista0.0680.0740.006
Angel Pagan0.0670.0690.002
Freddy Galvis0.0650.041-0.024
Billy Hamilton0.060.0880.028
Ben Revere0.0590.0830.024
Carlos Ruiz0.0570.043-0.014
Alberto Callaspo0.0550.039-0.016
Jose Iglesias0.0530.0810.028
Billy Burns0.0510.1170.066
Ichiro Suzuki0.0070.0410.034

The top five luckiest hitters by a straight spread are Bryce Harper, Mark Teixeira, Stephen Vogt, Nelson Cruz and Jose Bautista. They’re lucky but not bad: the average ISO of hitters in the sample is .152 while the average expected ISO of these five is .210. They’re still crushing the ball. Billy Burns, Russell Martin and Jason Kipnis populated the back spots of the top ten luckiest hitters and have below-average expected ISOs. They are players whose power production warrants concern going forward.

On the other side of the coin, two Marlins in Michael Morse and Christian Yelich are the only players to under-perform by over a tenth, while Marcell Ozuna has been the fifth most notable under-performer. A cursory glance doesn’t reveal any obvious patterns above over-performers or under-performers, and the Q-Q plot for the regression was normal.

Using new batted ball data to investigate expected peripherals seems like a worthy endeavour, something that Breaking Blue may explore further in future posts. An interesting idea would be to come up with expected measures for each fundamental peripheral (BABIP, ISO, K%, BB%) in order to produce an expected slash-line or composite stat such as wOBA.

(Title photo credit to Keith Allison,
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Author: Spencer Estey

Spencer has been a baseball fan since a young age and, being from Toronto, he has always been partial to the Blue Jays. He is a statistics major at the University of Waterloo and is intensely interested in the analytic aspect of the game. Spencer follows baseball by watching countless games each season, reading various advanced analysis sites, playing in deep dynasty fantasy leagues and discussing the game with fellow fans.

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