Identifying Impact Hitters: Proof of Concept

Earlier this season I set out to build a tool similar in nature to my dSCORE tool, except this one was meant to identify swing-change hitters. Along the course of its construction and early-alpha testing, it morphed into something different, and maybe something more useful. What I ended up with was a tool called cHit (“change Hit”, named for swing changers but really I was just too lazy to bother coming up with a more apt acronym for what the tool actually does). cHit, in its current beta form, aims to identify hitters that tend to profile for “impact production” — simply defined as hit balls hard, and hit them in the air. Other research has identified those as ideal for XBH, so I really didn’t need to reinvent the wheel. Although I’d really like to pull in Statcast data offerings in a more refined form of this tool, simple batted ball data offered here on FanGraphs does the trick nicely.

The inner workings of this tool takes six different data points (BB%, GB%, FB%, Hard%, Soft%, Spd), compares each individual player’s stat against a league midpoint for that stat, then buffs it using a multiplier that serves to normalize each stat based on its importance to ISO. I chose ISO as it’s a pretty clean catch-all for power output.

Now here’s the trick of this tool: it’s not going to identify “good” hitters from “bad” hitters. Quality sticks like Jean Segura, Dee Gordon, Cesar Hernandez, and others show up at the bottom of the results because their game doesn’t base itself on the long ball. They do just fine for themselves hitting softer liners or ground balls and using their legs for production. Frankly, chances are if a player at the bottom of the list has a high Speed component, they’ve got a decent chance of success despite a low cHit. Nuance needs to be accounted for by the user.

Here’s how I use it to identify swing-changers (and/or regression candidates): I pulled in data for previous years, back to 2014. I compared 2017 data to 2016 data (I’ll add in comparisons for previous years in later iterations) and simply checked to see who were cHit risers or fallers. The results were telling — players we have on record as swing changers show up with significant positive gains, and players that endured some significant regression fell.

There’s an unintended, possible third use for this tool: identifying injured hitters. Gregory Polanco, Freddie Freeman, and Matt Holliday all suffered/played through injury this year, and they all fell precipitously in the rankings. I’ll need a larger sample size to see whether injuries and a fall in cHit are related or if that’s just noise.

Data!

cHit 2017
Name Team Age AB cHit Score BB% GB% FB% Hard% Soft% Spd ISO
Joey Gallo Rangers 23 449 27.56 14.10% 27.90% 54.20% 46.40% 14.70% 5.5 0.327
J.D. Martinez – – – 29 432 23.52 10.80% 38.30% 43.20% 49.00% 14.00% 4.7 0.387
Matt Carpenter Cardinals 31 497 22.46 17.50% 26.90% 50.80% 42.20% 12.10% 3.1 0.209
Aaron Judge Yankees 25 542 21.56 18.70% 34.90% 43.20% 45.30% 11.20% 4.8 0.343
Lucas Duda – – – 31 423 19.69 12.20% 30.30% 48.60% 42.10% 14.50% 0.5 0.279
Cody Bellinger Dodgers 21 480 19.26 11.70% 35.30% 47.10% 43.00% 14.00% 5.5 0.315
Miguel Sano Twins 24 424 17.73 11.20% 38.90% 40.50% 44.80% 13.50% 2.9 0.243
Jay Bruce – – – 30 555 16.50 9.20% 32.50% 46.70% 40.30% 11.70% 2.6 0.254
Trevor Story Rockies 24 503 16.39 8.80% 33.70% 47.90% 40.30% 14.40% 4.7 0.219
Justin Turner Dodgers 32 457 16.16 10.90% 31.40% 47.80% 38.90% 9.80% 3.3 0.208
Khris Davis Athletics 29 566 15.64 11.20% 38.40% 42.30% 42.10% 13.50% 3.4 0.281
Brandon Belt Giants 29 382 15.38 14.60% 29.70% 46.90% 38.40% 14.00% 4.2 0.228
Nick Castellanos Tigers 25 614 14.94 6.20% 37.30% 38.20% 43.40% 11.50% 4.6 0.218
Eric Thames Brewers 30 469 14.52 13.60% 38.40% 41.30% 41.50% 16.00% 4.6 0.271
Justin Upton – – – 29 557 14.43 11.70% 36.80% 43.70% 41.00% 19.80% 4 0.268
Justin Smoak Blue Jays 30 560 14.38 11.50% 34.30% 44.50% 39.40% 13.10% 1.7 0.259
Wil Myers Padres 26 567 14.32 10.80% 37.50% 42.90% 41.40% 19.50% 5.3 0.220
Paul Goldschmidt Diamondbacks 29 558 14.31 14.10% 46.30% 34.90% 44.30% 11.30% 5.6 0.265
Chris Davis Orioles 31 456 14.28 11.60% 36.70% 39.80% 41.50% 12.80% 2.7 0.208
Kyle Seager Mariners 29 578 13.57 8.90% 31.30% 51.60% 35.70% 13.10% 2.2 0.201
Nelson Cruz Mariners 36 556 13.35 10.90% 40.40% 41.80% 40.70% 14.70% 1.7 0.261
Mike Zunino Mariners 26 387 13.31 9.00% 32.00% 45.60% 38.60% 17.50% 1.9 0.258
Mike Trout Angels 25 402 13.16 18.50% 36.70% 44.90% 38.30% 19.00% 6.2 0.323
Corey Seager Dodgers 23 539 13.08 10.90% 42.10% 33.10% 44.00% 12.90% 2.7 0.184
Logan Morrison Rays 29 512 12.74 13.50% 33.30% 46.20% 37.40% 17.50% 2.4 0.270
Randal Grichuk Cardinals 25 412 12.61 5.90% 35.90% 42.70% 40.20% 18.20% 5.2 0.235
Salvador Perez Royals 27 471 12.50 3.40% 33.30% 47.00% 38.10% 16.50% 2.4 0.227
Michael Conforto Mets 24 373 12.42 13.00% 37.80% 37.80% 41.60% 20.20% 3.6 0.276
Matt Davidson White Sox 26 414 12.19 4.30% 36.20% 46.50% 38.20% 15.80% 1.8 0.232
Mike Napoli Rangers 35 425 12.15 10.10% 33.20% 52.10% 35.50% 21.90% 2.7 0.235
Miguel Cabrera Tigers 34 469 12.03 10.20% 39.80% 32.90% 42.50% 9.90% 1.1 0.149
Brandon Moss Royals 33 362 11.83 9.20% 33.10% 44.50% 37.30% 13.60% 2.3 0.221
Curtis Granderson – – – 36 449 11.69 13.50% 32.60% 48.80% 35.30% 17.60% 4.8 0.241
Ian Kinsler Tigers 35 551 11.64 9.00% 32.90% 46.50% 37.00% 18.70% 5.6 0.176
Edwin Encarnacion Indians 34 554 11.01 15.50% 37.10% 41.80% 37.60% 15.50% 2.7 0.245
Manny Machado Orioles 24 630 10.79 7.20% 42.10% 42.10% 39.50% 18.50% 3.3 0.213
Freddie Freeman Braves 27 440 10.72 12.60% 34.90% 40.60% 37.50% 12.40% 4.3 0.280
Nolan Arenado Rockies 26 606 10.60 9.10% 34.00% 44.90% 36.70% 17.60% 4.1 0.277
Anthony Rendon Nationals 27 508 10.41 13.90% 34.00% 47.20% 34.30% 13.00% 3.5 0.232
Yonder Alonso – – – 30 451 10.34 13.10% 33.90% 43.20% 36.00% 13.20% 2.4 0.235
Kyle Schwarber Cubs 24 422 10.24 12.10% 38.30% 46.50% 36.40% 21.30% 2.8 0.256
Carlos Gomez Rangers 31 368 10.19 7.30% 39.10% 40.30% 39.00% 16.50% 5 0.207
Luis Valbuena Angels 31 347 9.81 12.00% 38.40% 47.30% 35.80% 22.00% 1.3 0.233
Dexter Fowler Cardinals 31 420 9.61 12.80% 39.40% 38.20% 38.10% 12.70% 5.9 0.224
Jed Lowrie Athletics 33 567 9.40 11.30% 29.40% 43.50% 34.50% 12.10% 2.7 0.171
Giancarlo Stanton Marlins 27 597 8.96 12.30% 44.60% 39.40% 38.90% 20.80% 2.3 0.350
Jose Abreu White Sox 30 621 8.95 5.20% 45.30% 36.40% 40.50% 15.80% 4.4 0.248
Josh Donaldson Blue Jays 31 415 8.92 15.30% 41.00% 42.30% 36.30% 17.30% 1.6 0.289
Joey Votto Reds 33 559 8.87 19.00% 39.00% 38.00% 36.30% 10.40% 2.8 0.258
Victor Martinez Tigers 38 392 8.75 8.30% 42.10% 34.20% 39.90% 12.40% 0.9 0.117
Charlie Blackmon Rockies 31 644 8.63 9.00% 40.70% 37.00% 39.00% 17.10% 6.4 0.270
Mitch Moreland Red Sox 31 508 8.43 9.90% 43.40% 36.20% 38.90% 13.50% 1.7 0.197
Scott Schebler Reds 26 473 8.29 7.30% 45.60% 38.20% 39.40% 19.30% 3.9 0.252
Paul DeJong Cardinals 23 417 8.19 4.70% 33.70% 42.90% 36.40% 21.40% 2.5 0.247
Ryan Zimmerman Nationals 32 524 8.18 7.60% 46.40% 33.70% 40.50% 14.10% 2.2 0.269
Mookie Betts Red Sox 24 628 7.76 10.80% 40.40% 42.80% 35.70% 18.20% 5.5 0.194
Rougned Odor Rangers 23 607 7.61 4.90% 41.50% 42.20% 36.80% 18.50% 5.6 0.193
Francisco Lindor Indians 23 651 7.42 8.30% 39.20% 42.40% 35.20% 14.30% 5.1 0.232
Brad Miller Rays 27 338 7.39 15.50% 47.40% 36.10% 38.40% 18.10% 4.6 0.136
Daniel Murphy Nationals 32 534 6.97 8.80% 33.50% 38.90% 35.70% 16.70% 3.8 0.221
Travis Shaw Brewers 27 538 6.87 9.90% 42.50% 37.60% 37.10% 15.80% 4.5 0.240
Jake Lamb Diamondbacks 26 536 6.86 13.70% 41.10% 38.30% 35.70% 12.90% 4.4 0.239
Todd Frazier – – – 31 474 6.75 14.40% 34.20% 47.50% 32.20% 23.20% 3.1 0.215
Yasmani Grandal Dodgers 28 438 6.63 8.30% 43.50% 40.00% 36.50% 17.60% 1.1 0.212
Brian Dozier Twins 30 617 6.60 11.10% 38.40% 42.60% 34.10% 15.90% 5.2 0.227
Adam Duvall Reds 28 587 6.55 6.00% 33.20% 48.60% 31.80% 17.50% 3.9 0.232
Hunter Renfroe Padres 25 445 6.52 5.60% 37.90% 45.40% 34.60% 23.50% 3.2 0.236
Justin Bour Marlins 29 377 6.40 11.00% 43.40% 33.60% 38.80% 19.60% 1.6 0.247
Carlos Correa Astros 22 422 6.33 11.00% 47.90% 31.70% 39.50% 15.00% 3.2 0.235
Marcell Ozuna Marlins 26 613 6.09 9.40% 47.10% 33.50% 39.10% 18.30% 2.3 0.237
Domingo Santana Brewers 24 525 5.85 12.00% 44.90% 27.70% 39.70% 11.70% 4 0.227
Kris Bryant Cubs 25 549 5.83 14.30% 37.70% 42.40% 32.80% 14.80% 4.4 0.242
Gary Sanchez Yankees 24 471 5.47 7.60% 42.30% 36.60% 36.90% 18.60% 2.6 0.253
Asdrubal Cabrera Mets 31 479 5.46 9.30% 43.50% 36.20% 36.80% 17.20% 2.5 0.154
Austin Hedges Padres 24 387 5.37 5.50% 36.60% 45.70% 33.10% 22.30% 2.7 0.183
Logan Forsythe Dodgers 30 361 5.33 15.70% 44.00% 33.10% 36.60% 13.20% 2.8 0.102
Yadier Molina Cardinals 34 501 5.25 5.20% 42.20% 37.40% 36.40% 16.50% 3.9 0.166
Bryce Harper Nationals 24 420 5.07 13.80% 40.40% 37.60% 34.30% 13.30% 3.7 0.276
Neil Walker – – – 31 385 5.01 12.30% 36.20% 41.70% 32.80% 17.70% 2.8 0.174
Aaron Altherr Phillies 26 372 5.01 7.80% 43.10% 37.50% 36.40% 20.10% 5.5 0.245
Andrew McCutchen Pirates 30 570 4.90 11.20% 40.70% 37.40% 35.20% 17.50% 4.3 0.207
Eduardo Escobar Twins 28 457 4.86 6.60% 33.70% 45.30% 31.40% 16.00% 5.1 0.195
Anthony Rizzo Cubs 27 572 4.79 13.20% 40.70% 39.20% 34.40% 19.80% 4.4 0.234
Ryan Braun Brewers 33 380 4.73 8.90% 49.20% 31.90% 39.00% 19.20% 5.3 0.218
Kendrys Morales Blue Jays 34 557 4.56 7.10% 48.40% 33.20% 37.90% 15.20% 1.1 0.196
Jose Ramirez Indians 24 585 4.54 8.10% 38.90% 39.70% 34.00% 16.70% 6 0.265
Mike Moustakas Royals 28 555 4.51 5.70% 34.80% 45.70% 31.90% 21.20% 1.1 0.249
Andrew Benintendi Red Sox 22 573 4.50 10.60% 40.10% 38.40% 34.30% 16.60% 4.5 0.154
Jose Bautista Blue Jays 36 587 4.47 12.20% 37.70% 45.80% 31.40% 21.70% 3.4 0.164
Jason Castro Twins 30 356 4.36 11.10% 41.90% 33.50% 36.00% 14.00% 1.5 0.146
Albert Pujols Angels 37 593 4.12 5.80% 43.50% 38.10% 35.10% 15.90% 2.1 0.145
Hanley Ramirez Red Sox 33 496 4.04 9.20% 41.80% 37.10% 35.30% 20.00% 1.5 0.188
Tommy Joseph Phillies 25 495 3.99 6.20% 41.70% 39.00% 35.00% 20.90% 2.2 0.192
Tim Beckham – – – 27 533 3.99 6.30% 48.80% 29.50% 39.10% 15.50% 4.4 0.176
Jonathan Schoop Orioles 25 622 3.90 5.20% 41.90% 37.20% 36.10% 23.00% 2.2 0.211
George Springer Astros 27 548 3.58 10.20% 48.30% 33.80% 36.70% 17.90% 3.1 0.239
Carlos Beltran Astros 40 467 3.54 6.50% 43.10% 40.40% 33.70% 17.50% 1.8 0.152
Alex Bregman Astros 23 556 3.52 8.80% 38.40% 39.90% 33.00% 18.00% 5.9 0.191
Carlos Santana Indians 31 571 3.49 13.20% 40.80% 39.30% 33.00% 18.40% 4 0.196
Eugenio Suarez Reds 25 534 3.33 13.30% 38.90% 37.10% 33.80% 20.70% 3.1 0.200
Scooter Gennett Reds 27 461 3.29 6.00% 41.30% 37.60% 34.40% 17.20% 4.3 0.236
Mark Reynolds Rockies 33 520 3.26 11.60% 42.10% 36.30% 34.50% 19.00% 2.7 0.219
Josh Reddick Astros 30 477 3.23 8.00% 33.60% 42.30% 31.10% 17.20% 4.8 0.170
Mitch Haniger Mariners 26 369 2.97 7.60% 44.00% 36.70% 34.70% 17.70% 4.3 0.209
Ian Happ Cubs 22 364 2.92 9.40% 40.20% 39.70% 32.80% 18.70% 5.7 0.261
Josh Harrison Pirates 29 486 2.90 5.20% 36.50% 40.80% 32.40% 18.70% 4.9 0.160
Keon Broxton Brewers 27 414 2.78 8.60% 45.10% 34.60% 35.30% 17.00% 7.4 0.200
Matt Joyce Athletics 32 469 2.69 12.10% 37.80% 42.80% 30.30% 16.30% 3.2 0.230
Derek Dietrich Marlins 27 406 2.65 7.80% 36.50% 40.70% 32.10% 20.50% 3.9 0.175
Ryon Healy Athletics 25 576 2.56 3.80% 42.80% 38.20% 33.90% 16.50% 1.4 0.181
Evan Longoria Rays 31 613 2.50 6.80% 43.40% 36.80% 34.30% 18.00% 3.8 0.163
Zack Cozart Reds 31 438 2.49 12.20% 38.20% 42.30% 30.80% 19.50% 5.3 0.251
Robinson Cano Mariners 34 592 2.48 7.60% 50.00% 30.60% 36.90% 12.80% 2 0.172
Max Kepler Twins 24 511 2.39 8.30% 42.80% 39.50% 32.90% 18.70% 4.2 0.182
Steven Souza Jr. Rays 28 523 2.22 13.60% 44.60% 34.30% 34.10% 16.50% 4.8 0.220
Michael Taylor Nationals 26 399 2.17 6.70% 42.90% 36.70% 34.00% 18.10% 5.9 0.216
Yulieski Gurriel Astros 33 529 2.12 3.90% 46.20% 35.20% 35.10% 15.90% 2.8 0.187
Corey Dickerson Rays 28 588 1.24 5.60% 41.80% 35.80% 33.60% 18.70% 4 0.207
Whit Merrifield Royals 28 587 1.01 4.60% 37.70% 40.50% 30.60% 15.40% 6.7 0.172
Chris Taylor Dodgers 26 514 0.88 8.80% 41.50% 35.80% 32.40% 15.80% 6.4 0.208
A.J. Pollock Diamondbacks 29 425 0.81 7.50% 44.60% 32.10% 35.00% 19.80% 7.5 0.205
Marwin Gonzalez Astros 28 455 0.71 9.50% 43.90% 36.20% 32.70% 18.60% 3.2 0.226
Yangervis Solarte Padres 29 466 0.62 7.20% 41.60% 42.10% 31.10% 25.20% 2.4 0.161
Shin-Soo Choo Rangers 34 544 0.57 12.10% 48.80% 26.20% 36.10% 12.20% 4.7 0.162
Buster Posey Giants 30 494 0.50 10.70% 43.60% 33.00% 33.00% 14.10% 2.8 0.142
Jedd Gyorko Cardinals 28 426 0.48 9.80% 40.50% 39.30% 30.80% 19.20% 3.8 0.200
Yasiel Puig Dodgers 26 499 0.30 11.20% 48.30% 35.60% 32.90% 18.30% 4.4 0.224
Eddie Rosario Twins 25 542 0.12 5.90% 42.40% 37.40% 31.70% 16.70% 3.9 0.218
J.T. Realmuto Marlins 26 532 -0.01 6.20% 47.80% 34.30% 33.30% 14.90% 5 0.173
Jorge Bonifacio Royals 24 384 -0.20 8.30% 39.30% 34.80% 32.20% 20.20% 2.9 0.177
Gerardo Parra Rockies 30 392 -0.27 4.70% 46.80% 30.30% 34.70% 14.40% 3 0.143
Willson Contreras Cubs 25 377 -0.34 10.50% 53.30% 29.30% 35.50% 17.00% 2.4 0.223
Kole Calhoun Angels 29 569 -0.37 10.90% 43.90% 35.00% 31.80% 17.00% 3.7 0.148
Robbie Grossman Twins 27 382 -0.43 14.70% 40.70% 34.40% 30.90% 16.00% 3.5 0.134
Matt Holliday Yankees 37 373 -0.46 10.80% 47.70% 37.50% 31.80% 21.20% 2.1 0.201
Mark Trumbo Orioles 31 559 -0.47 7.00% 43.30% 40.60% 30.40% 20.90% 2.5 0.163
Stephen Piscotty Cardinals 26 341 -0.80 13.00% 49.20% 33.20% 32.70% 17.90% 2.7 0.132
Tommy Pham Cardinals 29 444 -0.86 13.40% 51.70% 26.10% 35.50% 15.40% 6 0.214
Joe Mauer Twins 34 525 -0.92 11.10% 51.50% 23.60% 36.40% 12.80% 2.4 0.112
Jackie Bradley Jr. Red Sox 27 482 -0.94 8.90% 49.00% 32.60% 33.30% 17.50% 4.5 0.158
Brandon Crawford Giants 30 518 -0.98 7.40% 46.20% 34.40% 32.60% 19.30% 2.5 0.151
Nomar Mazara Rangers 22 554 -1.13 8.90% 46.50% 34.20% 32.60% 20.90% 2.6 0.170
Ben Zobrist Cubs 36 435 -1.35 10.90% 51.10% 33.30% 32.30% 14.90% 3.6 0.143
Javier Baez Cubs 24 469 -1.36 5.90% 48.60% 36.00% 32.40% 21.30% 5.3 0.207
Jorge Polanco Twins 23 488 -1.42 7.50% 37.90% 42.80% 27.70% 19.90% 4.9 0.154
Avisail Garcia White Sox 26 518 -1.70 5.90% 52.20% 27.50% 35.30% 15.70% 4.3 0.176
Matt Kemp Braves 32 438 -1.76 5.80% 48.50% 28.20% 34.70% 17.40% 1.7 0.187
Maikel Franco Phillies 24 575 -2.04 6.60% 45.40% 36.70% 30.90% 20.80% 1.5 0.179
Nick Markakis Braves 33 593 -2.17 10.10% 48.60% 29.20% 33.10% 15.60% 1.9 0.110
Tucker Barnhart Reds 26 370 -2.46 9.90% 46.00% 27.80% 33.20% 16.50% 3.4 0.132
Trey Mancini Orioles 25 543 -2.48 5.60% 51.00% 29.70% 34.10% 19.60% 3.2 0.195
Christian Yelich Marlins 25 602 -2.51 11.50% 55.40% 25.20% 35.20% 15.90% 5.2 0.156
Lorenzo Cain Royals 31 584 -2.79 8.40% 44.40% 32.90% 31.10% 18.70% 6.5 0.140
Josh Bell Pirates 24 549 -2.87 10.60% 51.10% 31.20% 32.60% 20.60% 3.5 0.211
Jose Reyes Mets 34 501 -3.00 8.90% 37.20% 43.10% 26.70% 26.10% 7.2 0.168
Carlos Gonzalez Rockies 31 470 -3.04 10.50% 48.60% 31.70% 31.90% 20.50% 3.2 0.162
Adam Jones Orioles 31 597 -3.27 4.30% 44.80% 34.30% 30.90% 20.10% 2.7 0.181
Byron Buxton Twins 23 462 -3.57 7.40% 38.70% 38.00% 27.60% 18.20% 8.2 0.160
Kevin Kiermaier Rays 27 380 -3.81 7.40% 49.60% 32.10% 31.80% 22.00% 5.9 0.174
Chase Headley Yankees 33 512 -3.90 10.20% 43.50% 31.70% 30.00% 17.10% 4.3 0.133
Xander Bogaerts Red Sox 24 571 -4.31 8.80% 48.90% 30.50% 31.40% 19.70% 6.7 0.130
Jordy Mercer Pirates 30 502 -4.33 9.10% 48.30% 30.90% 31.00% 19.00% 2.9 0.151
Brandon Drury Diamondbacks 24 445 -4.44 5.80% 48.80% 29.40% 31.70% 16.60% 2.4 0.180
Alex Gordon Royals 33 476 -4.69 8.30% 42.60% 33.00% 29.20% 19.40% 4.3 0.107
Ben Gamel Mariners 25 509 -4.84 6.50% 44.90% 33.30% 29.40% 18.70% 4.9 0.138
Hernan Perez Brewers 26 432 -4.85 4.40% 48.30% 33.50% 30.40% 21.20% 5.3 0.155
Matt Wieters Nationals 31 422 -4.94 8.20% 42.50% 36.40% 27.40% 18.10% 2 0.118
Brett Gardner Yankees 33 594 -5.07 10.60% 44.50% 33.20% 28.80% 20.00% 6 0.163
Odubel Herrera Phillies 25 526 -5.10 5.50% 44.10% 34.70% 29.40% 24.40% 4.3 0.171
Freddy Galvis Phillies 27 608 -5.11 6.80% 36.70% 39.20% 25.50% 18.10% 5.3 0.127
Elvis Andrus Rangers 28 643 -5.13 5.50% 48.50% 31.50% 30.50% 18.70% 5.7 0.174
Danny Valencia Mariners 32 450 -5.93 8.00% 47.90% 31.00% 29.80% 20.50% 3.3 0.156
Kevin Pillar Blue Jays 28 587 -6.25 5.20% 43.10% 36.40% 27.30% 22.50% 4.4 0.148
Dansby Swanson Braves 23 488 -6.35 10.70% 47.40% 29.40% 29.30% 18.00% 3.2 0.092
Jose Altuve Astros 27 590 -6.45 8.80% 47.00% 32.70% 28.20% 19.00% 6.4 0.202
Alcides Escobar Royals 30 599 -6.47 2.40% 40.80% 37.40% 26.80% 22.80% 4.3 0.107
Andrelton Simmons Angels 27 589 -6.62 7.30% 49.50% 31.50% 29.30% 20.60% 5 0.143
Didi Gregorius Yankees 27 534 -6.91 4.40% 36.20% 43.80% 23.10% 24.40% 2.7 0.191
Ryan Goins Blue Jays 29 418 -6.94 6.80% 50.30% 34.80% 27.70% 19.60% 2.7 0.120
Gregory Polanco Pirates 25 379 -7.00 6.60% 42.20% 37.50% 25.90% 22.80% 3.7 0.140
David Peralta Diamondbacks 29 525 -7.02 7.50% 55.10% 26.50% 31.80% 21.20% 4.6 0.150
Kolten Wong Cardinals 26 354 -7.11 10.00% 48.10% 31.80% 28.20% 20.80% 5.4 0.127
Orlando Arcia Brewers 22 506 -7.74 6.60% 51.60% 28.50% 30.20% 22.90% 4.1 0.130
Martin Maldonado Angels 30 429 -7.80 3.20% 48.50% 36.60% 26.70% 21.60% 2.3 0.147
Cory Spangenberg Padres 26 444 -7.85 7.00% 49.30% 27.80% 29.20% 16.90% 5 0.137
Joe Panik Giants 26 511 -7.96 8.00% 44.00% 34.10% 26.10% 20.10% 4.2 0.133
David Freese Pirates 34 426 -8.08 11.50% 57.00% 22.60% 31.90% 19.40% 1 0.108
Melky Cabrera – – – 32 620 -8.14 5.40% 48.90% 29.00% 28.90% 19.00% 2.3 0.137
Hunter Pence Giants 34 493 -8.28 7.40% 57.20% 29.40% 29.40% 18.50% 3.6 0.126
Manuel Margot Padres 22 487 -8.30 6.60% 40.50% 36.30% 25.40% 25.90% 6.1 0.146
Trea Turner Nationals 24 412 -8.61 6.70% 51.70% 33.50% 26.70% 18.00% 8.9 0.167
Jonathan Villar Brewers 26 403 -8.85 6.90% 57.40% 21.90% 33.20% 27.00% 5.4 0.132
Starlin Castro Yankees 27 443 -9.19 4.90% 51.80% 28.00% 29.20% 21.80% 3.5 0.153
Denard Span Giants 33 497 -9.30 7.40% 45.00% 33.60% 25.10% 18.60% 5.5 0.155
Jacoby Ellsbury Yankees 33 356 -9.73 10.00% 45.90% 31.00% 26.10% 22.70% 7.7 0.138
Delino DeShields Rangers 24 376 -9.93 10.00% 45.10% 34.80% 23.90% 20.10% 7.1 0.098
Adam Frazier Pirates 25 406 -9.98 7.90% 47.90% 26.80% 27.50% 17.90% 5.7 0.123
DJ LeMahieu Rockies 28 609 -10.42 8.70% 55.60% 19.70% 30.60% 15.40% 3.9 0.099
Yolmer Sanchez White Sox 25 484 -10.53 6.60% 44.50% 33.90% 24.00% 19.30% 5.3 0.147
Jason Heyward Cubs 27 432 -10.54 8.50% 47.40% 32.70% 25.50% 25.80% 4.3 0.130
Tim Anderson White Sox 24 587 -10.66 2.10% 52.70% 28.00% 28.30% 21.30% 6.2 0.145
Jean Segura Mariners 27 524 -10.79 6.00% 54.30% 26.40% 28.30% 19.70% 5.5 0.128
Cameron Maybin – – – 30 395 -10.88 11.30% 57.70% 27.90% 27.40% 20.10% 6.9 0.137
Dustin Pedroia Red Sox 33 406 -10.90 10.60% 48.80% 28.80% 25.90% 20.10% 2.2 0.099
Jose Iglesias Tigers 27 463 -10.91 4.30% 50.40% 26.40% 28.40% 23.40% 4.2 0.114
Eric Hosmer Royals 27 603 -11.30 9.80% 55.60% 22.20% 29.50% 21.80% 3.4 0.179
Eduardo Nunez – – – 30 467 -12.27 3.70% 53.40% 29.10% 26.70% 24.50% 4.8 0.148
Jon Jay Cubs 32 379 -12.53 8.50% 47.10% 23.90% 25.30% 11.50% 5.3 0.079
Brandon Phillips – – – 36 572 -12.97 3.50% 49.50% 28.30% 25.50% 21.70% 4.1 0.131
Guillermo Heredia Mariners 26 386 -15.19 6.30% 47.40% 34.90% 20.40% 23.80% 2.2 0.088
Ender Inciarte Braves 26 662 -15.36 6.80% 47.00% 29.10% 22.10% 20.90% 5.4 0.106
Jonathan Lucroy – – – 31 423 -16.18 9.60% 53.50% 27.90% 22.30% 20.50% 3.1 0.106
Jose Peraza Reds 23 487 -16.45 3.90% 47.10% 31.30% 21.40% 26.60% 5.8 0.066
Cesar Hernandez Phillies 27 511 -18.08 10.60% 52.80% 24.60% 22.10% 23.50% 6 0.127
Billy Hamilton Reds 26 582 -21.80 7.00% 45.80% 30.60% 16.00% 25.00% 9 0.088
Dee Gordon Marlins 29 653 -28.88 3.60% 57.60% 19.60% 16.10% 24.70% 8.5 0.067

Okay, so here’s the breakdown. I pulled all 2017 hitters with 400 at-bats or more so I could capture some significant hitters that didn’t have qualifying numbers of ABs due to injury. Ball-bludgeon extraordinaire Joey Gallo is a pretty solid name to have heading up this list, as he’s pretty much the human definition of what this tool is trying to identify. JD Martinez, Aaron Judge, Cody Bellinger, Miguel Sano, Trevor Story, and Justin Turner all in the top 10 is pretty much all the proof-of-concept I needed.

Interesting notes:

Brandon Belt at 12 — Someone needs to tell the Giants to trade him to literally any other team, stat.

Giancarlo Stanton at 46 — Surprisingly, the MVP fell off from his stats in 2016. His grounders and soft contact rose by 3 or more percentage points, and shaved off the equivalent from hard and fly balls. His output was fueled by adding almost 200 ABs to his season — he could actually get better if he can stay healthy and add those hard flies back in!

Francisco Lindor at 58 — The interesting part of this is even though Lindor is still a decent way down the list, he actually was the biggest gainer from last season to this, adding 9.52 points to his cHit. We knew he was gunning for flies from the outset of the season, and it looks like his mission was accomplished.

Mike Moustakas at 87 — Frankly, being bookended by Jose Ramirez and Andrew Benintendi should, in a vacuum, should be great company. But this is a prime example of how cHit requires users to not take the numbers at face value. Ramirez and Benintendi aren’t slug-first hitters like Moose. They’ve got significantly better Speed scores, plus aren’t as prone to soft contact. I’d be very wary of Moose regressing, as he seems to rely on sneaking some less-than ideal homers over fences. If he goes to San Francisco I could see his value crater (see Belt, Brandon).

Eric Hosmer at 206 — Nope, negative, pass, I’m trying to sign quality hitters here <— Suggested responses for GMs when approached this offseason by Scott Boras on behalf of Hosmer.

Final Notes:

  •  Batted-ball distribution data is noticeably absent. In one of my iterations I added in those stats, and found that they actually regressed the accuracy of the formula. It doesn’t matter where you hit the ball, as long as you hit it hard.
  • Medium% and LD% are noisy stats. They also regressed the formula.
  • I may look to replace BB% in future iterations. For now though, it does a decent job of capturing plate discipline and selectivity.
  • K% doesn’t seem to have much of an impact on cHit (see Gallo, Joey).
  • R-squared numbers over the last four years of data hold pretty steady between .65 and .75, which is really encouraging. Also, the bigger the pool of data per year (number of batters analyzed), the higher R-squared goes; which is ultimately the most encouraging result of this whole endeavor.

Input is greatly appreciated! I’m not a mathematician in any stretch of the imagination, so if there’s a better way of going about this I’d love to hear it. I’ll do a writeup about my swing-change findings at a later date.



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MaxFreeze7
Member

It’s a really nice idea and a lot data to digest. Not sure how you’ve weighted each category but it seems like the FB% and Spd score are a little wacky. An elevated FB% isn’t necessarily a positive for all players. Look at Kyle Seager and Carpenter, both over 50% in 2017 but took steps back from previous years. There’s a limit and every player is different. Also I’m not sure a high speed score helps Gallo that much with his high FB%. A three true outcome player like Gallo isn’t going to benefit from a high speed score as much as other players.

Again, I don’t know how you’ve weighted them or your equation, I’m just observing from the outside

otis
Member

Nice article! One note on your blurb about Stanton: while his ground ball and weak contact rates went up a bit, his strikeout rate also decreased significantly (over 6%, from 29.8% to 23.6%). Without a large change to his walk rate, this increases his volume of fly balls despite the decrease on a rate basis. We can’t know if it’s possible for him to maintain this lower strikeout rate while simultaneously raising his hard hit and ground ball rates to previous levels.