How Well Have Hitters Been Hitting, Objectively? | Expected wOBA and Slash Lines

(Title photo courtesy of Dave R, https://www.flickr.com/photos/daver6/)

This is the culmination of Breaking Blue’s mini-series on expected hitter peripherals. The idea of the series is to take a look at how hitters have been performing at each of the fundamental skills, from the perspective of the advanced new data that is available.

Through StatCast (as collected by BaseballSavant), we have information on how hard players are hitting the ball, in terms of exit velocity on both ground balls and fly balls, and distances. Through the batted ball information on Fangraphs that is provided by Baseball Info Solutions, we also have directional data in the form of the rates at which batters hit the ball to the pull, middle and opposite fields, as well as quality of contact. Pitchf/x has for years provided an easy source for metrics such as swinging strike, contact, and chase rates. We have a wide array of very granular statistics which with to do research. The four main rates that govern offensive production are strikeout rate, walk rate, isolated power and batting average on balls in play. There is almost a perfect relationship between the overall package of a hitter as expressed in a stat like wOBA, and these four stats. Productive hitters come in all different shapes and sizes, but they produce at the plate through avenues specified by these rates.

The ‘xSeries’ is designed to provide a window into a player’s season that is free from many sources of bias and luck. Players often carry batting lines that bloat or under-represent the actions they’ve made in the batter’s box to help their team. By regressing for the important rates using talent-based metrics, we can know with much more accuracy how they have actually hit, objectively. The results we’ll get are not meant to be projections or attempts at illustrating true talent. However, they in many cases will represent a player’s talent level fairly and will be meaningful when looking ahead. As said in previous articles, these numbers are meant to be one tool of many when evaluating a player’s outlook.

This article in particular will present our expected weighted on-base average (wOBA) as well as expected batting average, on-base percentage and slugging percentage. The latter three numbers make up the oft-referenced triple slash line.

The frameworks for the previous expected peripherals were for the most part considered, with some tweaking. Here’s a summary of the statistics used:

Average fly ball/line drive exit velocity. How hard the hitter’s average fly ball or line drive is struck. (Used in xISO and xBABIP)

– FB%. Percentage of balls in play that are fly balls. (xISO, xBABIP)

– IFFB%. Percentage of fly balls that are infield flies. (xBABIP)

– GB%. Percentage of balls in play that are ground balls. (xBABIP)

 Speed score. Created by Bill James, represents a player’s baserunning speed. (xISO, xBABIP)

– Hard%. Percentage of batted balls judged to be the result of hard contact. (xBABIP)

– Pull%. Percentage of batted balls hit to pull field. (xBABIP)

– Swing%. Percentage of pitches swung at. (xK)

– Contact%. Percentage of swings that result in contact. (xK)

Zone%. Percentage of pitches to batter that are in the strike zone. Pitchers generally throw fewer pitches in the zone to better hitters, so Zone% is relevant to a hitter’s plate discipline talent. (xBB)

– ZContact%. Contact rate on pitches in the strike zone. (xBB)

– OSwing%. Swing rate on pitches outside the strike zone. (xBB)

Here are some notes on methodology:

– Less inputs were used for BABIP in order to more closely represent talent. I wanted a regression that relies on only main effects of intuitive statistics. The previous xBABIP formula was good but we have to be careful with StatCast data since it’s limited. The statistics used in the xBABIP here should stabilize quickly and be much less prone to over-fitting.

– Expected strikeout and walk rates were made much more simple at no loss to fit. They are extremely intuitive and tell most of the story of how strikeouts and walks happen. Strikeouts are a product of swinging at pitches, and not making contact on swings.

– Not every event (i.e., sacrifices, hit-by-pitches) is represented in the peripherals used, so some additional manipulation was needed. wOBA was created using expected wOBAcon (wOBA on contact), walk and strikeout rates. Expected home run rate (needed for batting average since home runs don’t count towards BABIP) was created using expected isolated power.

– These numbers are not park-adjusted, so they represent neutral-context expected production. You can adjust them on your own using Fangraphs park factors. The peripherals were not significantly influenced by park since most of the stats considered are park-independent (i.e., Pull% and Swing%). However, future versions of the peripherals may make the necessary marginal adjustments.

– Hitters with 180 PA were considered here. Data is as of the morning of June 28th.

Name
xwOBA
xAVG
xOBP
xSLG
Giancarlo Stanton0.4070.2710.3490.617
Paul Goldschmidt0.4040.3040.3930.551
Brandon Belt0.3990.3160.4060.518
Mike Trout0.3950.3060.3810.548
Anthony Rizzo0.3920.3040.3880.527
Miguel Cabrera0.3890.3120.3780.541
Freddie Freeman0.3810.3010.3830.505
Bryce Harper0.3780.2740.3660.51
Andrew McCutchen0.3780.2750.3610.52
Todd Frazier0.3730.280.3440.536
Matt Carpenter0.3730.2930.390.464
Manny Machado0.3720.290.3660.504
Josh Donaldson0.3710.2750.3550.511
Lucas Duda0.370.2810.3660.492
Curtis Granderson0.370.2770.3710.482
Ryan Braun0.370.3110.3660.505
Jason Kipnis0.3680.3230.3860.472
Josh Reddick0.3660.2830.3640.486
Joey Votto0.3640.2730.3760.456
Jose Bautista0.3640.2480.340.505
Rajai Davis0.3630.3350.3780.478
Mitch Moreland0.3630.2760.3450.504
Joc Pederson0.3620.2320.3340.502
Brock Holt0.3620.3170.3950.437
Justin Turner0.3610.3030.3710.47
Charlie Blackmon0.3610.2970.3720.464
Jay Bruce0.360.2510.3480.481
Adrian Gonzalez0.3580.2940.360.477
Evan Longoria0.3560.270.3420.489
Brandon Moss0.3550.2450.3220.506
J.D. Martinez0.3540.2640.3170.517
Prince Fielder0.3530.2950.3550.471
DJ LeMahieu0.3520.3230.3810.438
Hanley Ramirez0.3520.2880.3450.481
Brett Gardner0.3510.2780.3670.436
Jorge Soler0.3480.2770.3540.448
Luis Valbuena0.3480.2360.3150.497
Eric Hosmer0.3460.2860.3570.443
Logan Forsythe0.3460.2730.3460.456
Lorenzo Cain0.3460.2960.3380.477
Albert Pujols0.3460.2720.3310.478
Mookie Betts0.3450.2810.3350.474
Kris Bryant0.3450.2350.3240.473
David DeJesus0.3450.2950.360.44
Yasmani Grandal0.3450.260.3520.437
David Ortiz0.3450.2590.350.438
Carlos Santana0.3430.2470.3460.439
Pedro Alvarez0.3430.2690.3460.444
Brian Dozier0.3430.2510.3270.468
Buster Posey0.3420.2930.3690.416
Will Middlebrooks0.3420.2650.3230.476
Miguel Montero0.3420.2570.3470.435
Alex Rodriguez0.3420.2430.3340.451
Michael Brantley0.3410.2860.3610.425
Matt Holliday0.3410.2880.3760.4
Brad Miller0.3410.260.3350.454
Joe Panik0.3410.290.3640.421
Gerardo Parra0.3410.3020.3410.461
Chris Carter0.340.1970.3010.482
Adam Lind0.3390.2690.3360.45
Joe Mauer0.3390.2990.3620.419
George Springer0.3380.2510.350.417
David Peralta0.3380.2680.3420.438
Chris Coghlan0.3380.2630.3410.439
Chris Colabello0.3380.2840.3440.44
Brandon Crawford0.3380.2620.3330.449
Steven Souza0.3370.2390.3150.467
Kendrys Morales0.3360.260.3210.462
Neil Walker0.3360.2640.3370.439
Colby Rasmus0.3360.2150.3130.458
Chris Davis0.3360.2220.3190.45
Yasmany Tomas0.3360.2980.350.431
Ryan Howard0.3350.2520.3090.474
Adam Jones0.3350.2840.3220.466
Andre Ethier0.3350.2610.3290.446
Kolten Wong0.3340.2820.3490.422
Daniel Murphy0.3340.2950.3520.423
Denard Span0.3330.2990.3620.405
Nolan Arenado0.3330.2620.2980.488
Justin Upton0.3330.2390.3280.433
Mark Trumbo0.3330.2470.30.479
Jose Abreu0.3320.2860.330.445
Logan Morrison0.3320.2620.3280.44
Yonder Alonso0.3320.3020.3750.38
Robinson Cano0.3320.2910.3490.418
Carlos Beltran0.3310.2550.3230.445
Mike Napoli0.3310.2220.3130.449
A.J. Pollock0.3310.2850.3390.43
Russell Martin0.3310.270.3460.411
Matt Kemp0.3310.2780.3350.431
Mark Teixeira0.3310.2340.3270.428
Alex Gordon0.330.2540.3440.407
Kevin Kiermaier0.330.2750.3390.422
Adam Eaton0.3290.2950.3540.405
Cory Spangenberg0.3290.290.3510.407
Justin Maxwell0.3280.2420.3170.44
Stephen Vogt0.3270.2530.340.405
Nelson Cruz0.3270.2380.3220.427
Kyle Seager0.3270.2680.3270.431
Juan Lagares0.3260.2830.3240.438
J.T. Realmuto0.3260.2930.3290.435
Gregory Polanco0.3250.260.340.402
Troy Tulowitzki0.3250.2690.3180.438
Martin Prado0.3240.2970.3420.412
Adam LaRoche0.3240.2370.3250.415
Wilmer Flores0.3240.2860.3310.425
Brian McCann0.3230.2450.3090.441
Yoenis Cespedes0.3230.2510.2920.466
Chase Utley0.3230.2440.3270.412
Jhonny Peralta0.3230.2740.3380.405
Ben Revere0.3230.3040.3630.378
Howie Kendrick0.3220.3030.3480.398
Nick Markakis0.3220.290.3730.353
Andrelton Simmons0.3220.2960.3440.401
Mark Canha0.3220.2420.310.434
Michael Taylor0.3220.2420.3030.442
Carlos Gonzalez0.3210.2420.3150.424
Chase Headley0.3210.2790.3510.381
Francisco Cervelli0.3210.2730.3410.394
Ryan Zimmerman0.3210.2610.3240.416
Ender Inciarte0.320.3040.3430.401
Marcell Ozuna0.320.2620.3230.414
Cameron Maybin0.320.2740.3350.4
Jason Castro0.3190.2420.3240.403
Adrian Beltre0.3190.2750.3120.434
Marlon Byrd0.3190.2380.2930.449
Austin Jackson0.3180.2680.340.387
Yangervis Solarte0.3180.2780.3340.398
Seth Smith0.3180.2370.3260.395
Evan Gattis0.3170.250.290.453
Matt Duffy0.3170.2790.3310.401
David Freese0.3160.2590.3190.409
Trevor Plouffe0.3160.240.3050.424
Travis Snider0.3160.250.3260.394
Edwin Encarnacion0.3140.2220.3080.409
Mike Moustakas0.3140.2780.330.395
Robinson Chirinos0.3140.2230.2960.426
Christian Yelich0.3140.2540.3310.382
Brandon Phillips0.3140.2910.3260.403
Brett Lawrie0.3140.250.2990.428
Jean Segura0.3140.2940.3220.41
Torii Hunter0.3130.2480.3010.424
Dexter Fowler0.3130.2310.3290.374
Shin-Soo Choo0.3120.2320.3240.382
A.J. Pierzynski0.3120.2810.3320.388
Jimmy Paredes0.3120.2580.3050.419
Yunel Escobar0.3120.2810.3380.377
Michael Cuddyer0.3120.270.3170.404
Avisail Garcia0.3110.2720.3130.409
Kole Calhoun0.3110.2490.3270.38
Caleb Joseph0.3110.2440.3080.407
Marcus Semien0.3110.2450.3080.408
Angel Pagan0.3110.2740.350.354
Billy Burns0.3110.3060.3420.378
Dustin Pedroia0.3110.2630.320.394
Nori Aoki0.310.2860.3460.362
Alexi Amarista0.310.2690.3380.367
Danny Espinosa0.310.250.3090.403
Starling Marte0.3090.2640.310.404
Lonnie Chisenhall0.3090.2650.3060.41
Nick Hundley0.3080.260.3290.372
Jason Heyward0.3080.2670.3350.364
Ian Kinsler0.3070.2580.3290.37
Adeiny Hechavarria0.3070.2860.3250.386
Xander Bogaerts0.3070.2690.3090.402
Anthony Gose0.3070.2670.330.369
Billy Butler0.3060.2520.3070.399
Odubel Herrera0.3060.2630.3160.386
Sam Fuld0.3060.2570.3330.358
Carlos Gomez0.3050.2560.3070.396
Eric Sogard0.3050.2640.3360.354
Salvador Perez0.3040.2570.2910.418
Will Venable0.3040.2610.3320.356
Josh Harrison0.3040.2850.30.411
Pablo Sandoval0.3040.2730.3080.395
Wilson Ramos0.3030.2610.3040.397
Jose Altuve0.3030.2760.3130.388
Jon Jay0.3010.2860.3370.352
Yadier Molina0.3010.2690.3140.38
Jose Reyes0.3010.2590.3260.356
Eduardo Escobar0.30.2420.2860.407
Melky Cabrera0.30.2680.3210.365
Juan Uribe0.30.2480.3210.356
Kevin Pillar0.2990.2660.2940.401
Dee Gordon0.2980.3010.330.36
Elvis Andrus0.2980.2610.3210.358
Zack Cozart0.2980.2440.2980.387
Chris Owings0.2970.2760.2980.392
Mike Zunino0.2970.1740.2580.42
Asdrubal Cabrera0.2970.2160.2860.392
Cody Asche0.2970.240.3010.376
Ian Desmond0.2970.2430.290.392
Jordy Mercer0.2970.2520.3030.376
Kurt Suzuki0.2950.2480.2950.383
Derek Norris0.2950.2210.2750.403
Jung-ho Kang0.2940.230.30.368
Michael Bourn0.2940.2380.3370.31
Jace Peterson0.2930.2380.3150.345
Nick Castellanos0.2930.2310.2820.392
Addison Russell0.2930.2280.2960.37
Johnny Giavotella0.2930.2590.3160.349
Jake Marisnick0.2920.240.2910.378
Jimmy Rollins0.2920.2260.3060.352
Chris Young0.2910.2280.2760.392
Aramis Ramirez0.290.240.2890.375
Alcides Escobar0.2890.2680.3020.363
Rene Rivera0.2890.2140.2690.394
Freddy Galvis0.2890.2590.2980.365
Alberto Callaspo0.2860.2390.3240.312
Alexei Ramirez0.2860.250.3010.351
Didi Gregorius0.2860.2350.2970.351
Ryan Goins0.2850.2340.2980.348
Leonys Martin0.2850.2160.2810.367
Carlos Ruiz0.2840.2530.3080.336
Billy Hamilton0.2840.250.3170.319
Brayan Pena0.2790.2590.3440.268
Starlin Castro0.2780.2340.2810.352
Jose Iglesias0.2770.2830.3190.311
Erick Aybar0.2760.260.3020.324
Mark Reynolds0.2710.1990.2760.328
Nick Ahmed0.2690.220.2840.318
Matt Joyce0.2680.1930.2830.309
Stephen Drew0.2670.1860.2690.326
Danny Santana0.2650.2710.2670.343
Omar Infante0.2440.220.2470.3

Breaking Blue will soon look closer at certain players that interest us, including Blue Jays and any players under- or over-performing by a notable amount.

We’d also like to create a permanent page on the website that has an oft-updated leaderboard table for the xSeries, since we believe it is a valuable resource. The next version of the statistics may run Wednesday or Thursday of this week.

Chris Colabello Makes His Case, But It Is Not Enough
Continuing Our 'xSeries' By Estimating BABIP, Using StatCast and BIS Data

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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2 Comments

  1. Colabello has posted a substantial OBA and BAvg but is he really a long term hitter or a flash in pan. As of late, the pitchers are starting to exploit his weakness. I believe he was able to benefit from strength of the lineup in general – that is the pitchers were focused on his team mates. Now that he has put some numbers he is no longer flying under the radar. Last night against Boston his performance at the plate single was abominable. He left the bases loaded twice standing six runners and bringing the rallies to a halt. In the 8th inning he hit into a double play and stranded two more runners.

    His defensive work is suspect at best. I am afraid that Chris is not ready as an everyday player. I would suggest that we play Justin Smoak,

    Post a Reply
    • Thanks for the comment, Mike.

      Colabello is probably a league-average hitter going forward, which at first base isn’t special. His xSlash of .284/.344/.440 is definitely encouraging but not enough to really change the conversation about him. His current sky-high numbers are definitely a flash in the pan. I would not expect him to stay with the Major League club through Spring Training 2016.

      I generally don’t buy into lineup strength affecting hitters, or the idea that pitchers will pitch him better now that they know who he is. It’s more likely that Colabello just doesn’t have the requisite talent to be a significantly above-average hitter and over a long period of playing time, that mediocre talent level will shine through. Justin Smoak does marginalize his skillset, certainly.

      Post a Reply

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