Here is my latest effort at THT.
Master of Fooling featuring Johan Santana and his feared change-up... and a few nice 3D charts.
Saturday, July 4, 2009
Friday, June 19, 2009
Friday, June 5, 2009
The best locations for each pitch
A followup to my first article at The Hardball Times.
This time both horizontal and vertical locations are taken into account (but not together yet).
Meanwhile, in case you missed it, the previous article generated a lot of discussion at The Book Blog.
This time both horizontal and vertical locations are taken into account (but not together yet).
Meanwhile, in case you missed it, the previous article generated a lot of discussion at The Book Blog.
Saturday, May 23, 2009
"Weighted" shift
My third article at The Hardball Times deals with defensive alignment too.
Some of the issues that arose from my first post here are taken into account.
There is already some discussion going on at The Book's Blog.
Some of the issues that arose from my first post here are taken into account.
There is already some discussion going on at The Book's Blog.
Sunday, May 10, 2009
On the shift again
Here's my second article at THT.
I'm looking at defensive alignment one more time. This time I try to see if moving slightly according to the pitch selection may help the fielders.
I'm looking at defensive alignment one more time. This time I try to see if moving slightly according to the pitch selection may help the fielders.
Friday, April 24, 2009
Painting the corners... at THT!
My plan was to analyze the table I posted a couple of weeks ago: I still would like to figure who are the pitchers that induce swings on balls way off the zone.
I changed plans because I got the call by The Hardball Times.
Here you can find my first article for them.
I should be writing there every other Thursday.
Please come back here now and then, maybe I will add something here too.
Saturday, April 18, 2009
The year of The Bird
I like doing statistical analysis and producing charts, so this is my tribute to Mark Fidrych.
Monday, April 13, 2009
Foolers - The other side of the coin
This will be a post consisting of three tables and very little commentary.
In my next to last post I looked at batters swinging at really bad pitches. Here I will present the numbers for the pitchers.
Here are the ten pitchers with the highest percentage of swings induced on balls way out of the zone (probability of being called strike lower than 10%).
And here are the bottom ten.
I have to look carefully at the tables yet.
At first glance I haven't been able to spot any pattern in the rankings, but here I give you the full table (2008 pitchers with at least 300 bad pitches thrown), in case you can find anything quicker than me.
In my next to last post I looked at batters swinging at really bad pitches. Here I will present the numbers for the pitchers.
Here are the ten pitchers with the highest percentage of swings induced on balls way out of the zone (probability of being called strike lower than 10%).
LAST | FIRST | n | swung | pct |
---|---|---|---|---|
Johnson | Josh | 309 | 162 | 52% |
Volstad | Chris | 334 | 160 | 48% |
Hampton | Mike | 338 | 150 | 44% |
Balester | Collin | 329 | 138 | 42% |
Nippert | Dustin | 300 | 124 | 41% |
Liriano | Francisco | 314 | 128 | 41% |
Davies | Kyle | 506 | 197 | 39% |
Lackey | John | 556 | 209 | 38% |
Baker | Scott | 575 | 216 | 38% |
Sabathia | C.C. | 880 | 329 | 37% |
And here are the bottom ten.
LAST | FIRST | n | swung | pct |
---|---|---|---|---|
Gorzelanny | Tom | 444 | 74 | 17% |
McGowan | Dustin | 385 | 60 | 16% |
Penny | Brad | 376 | 57 | 15% |
Miller | Andrew | 451 | 64 | 14% |
Chacon | Shawn | 389 | 53 | 14% |
Eaton | Adam | 440 | 55 | 12% |
Wang | Chien-Ming | 343 | 41 | 12% |
Glavine | Tom | 372 | 44 | 12% |
Bedard | Erik | 304 | 31 | 10% |
Dumatrait | Phil | 362 | 31 | 9% |
I have to look carefully at the tables yet.
At first glance I haven't been able to spot any pattern in the rankings, but here I give you the full table (2008 pitchers with at least 300 bad pitches thrown), in case you can find anything quicker than me.
LAST | FIRST | n | swung | pct |
---|---|---|---|---|
Johnson | Josh | 309 | 162 | 52% |
Volstad | Chris | 334 | 160 | 48% |
Hampton | Mike | 338 | 150 | 44% |
Balester | Collin | 329 | 138 | 42% |
Nippert | Dustin | 300 | 124 | 41% |
Liriano | Francisco | 314 | 128 | 41% |
Davies | Kyle | 506 | 197 | 39% |
Lackey | John | 556 | 209 | 38% |
Baker | Scott | 575 | 216 | 38% |
Sabathia | C.C. | 880 | 329 | 37% |
Street | Huston | 363 | 135 | 37% |
Kazmir | Scott | 743 | 276 | 37% |
Sowers | Jeremy | 447 | 162 | 36% |
Miner | Zach | 583 | 206 | 35% |
Halladay | Roy | 798 | 281 | 35% |
Campillo | Jorge | 674 | 237 | 35% |
Webb | Brandon | 815 | 286 | 35% |
Correia | Kevin | 481 | 168 | 35% |
Martinez | Pedro | 502 | 174 | 35% |
Rusch | Glendon | 302 | 104 | 34% |
Garza | Matt | 814 | 278 | 34% |
Morton | Charlie | 329 | 112 | 34% |
Wellemeyer | Todd | 738 | 251 | 34% |
Shields | James | 730 | 248 | 34% |
Lidge | Brad | 393 | 133 | 34% |
Kuroda | Hiroki | 751 | 254 | 34% |
Harden | Rich | 620 | 209 | 34% |
Liz | Radhames | 348 | 117 | 34% |
Perez | Odalis | 692 | 232 | 34% |
Buehrle | Mark | 815 | 273 | 33% |
Moehler | Brian | 463 | 155 | 33% |
Baek | Cha Seung | 506 | 169 | 33% |
Fogg | Josh | 366 | 122 | 33% |
Hamels | Cole | 759 | 251 | 33% |
Perkins | Glen | 403 | 133 | 33% |
Slowey | Kevin | 449 | 148 | 33% |
Dempster | Ryan | 816 | 267 | 33% |
Sonnanstine | Andy | 575 | 188 | 33% |
Lester | Jon | 784 | 256 | 33% |
Perez | Oliver | 810 | 264 | 33% |
Kershaw | Clayton | 415 | 135 | 33% |
Nolasco | Ricky | 637 | 207 | 32% |
Madson | Ryan | 317 | 103 | 32% |
Young | Chris | 406 | 131 | 32% |
de la Rosa | Jorge | 575 | 184 | 32% |
Lincecum | Tim | 791 | 253 | 32% |
Oswalt | Roy | 626 | 200 | 32% |
Pineiro | Joel | 456 | 145 | 32% |
Broxton | Jonathan | 302 | 96 | 32% |
Haren | Dan | 746 | 237 | 32% |
Hernandez | Felix | 656 | 208 | 32% |
Galarraga | Armando | 696 | 220 | 32% |
Peavy | Jake | 792 | 250 | 32% |
Santana | Johan | 720 | 226 | 31% |
Marcum | Shaun | 615 | 193 | 31% |
McClellan | Kyle | 306 | 96 | 31% |
Blackburn | Nick | 552 | 173 | 31% |
Santana | Ervin | 812 | 254 | 31% |
Greinke | Zack | 716 | 222 | 31% |
Ramirez | Ramon | 313 | 97 | 31% |
Beckett | Josh | 619 | 191 | 31% |
Moyer | Jamie | 869 | 266 | 31% |
Durbin | Chad | 407 | 124 | 30% |
Bergmann | Jason | 572 | 174 | 30% |
Maddux | Greg | 503 | 153 | 30% |
Billingsley | Chad | 880 | 267 | 30% |
Danks | John | 612 | 185 | 30% |
Matsuzaka | Daisuke | 748 | 226 | 30% |
Lowe | Derek | 950 | 287 | 30% |
Johnson | Randy | 649 | 196 | 30% |
Pettitte | Andy | 792 | 239 | 30% |
Wolf | Randy | 803 | 242 | 30% |
Franklin | Ryan | 342 | 103 | 30% |
Sheets | Ben | 646 | 194 | 30% |
Byrd | Paul | 483 | 145 | 30% |
Maholm | Paul | 644 | 193 | 30% |
Olsen | Scott | 596 | 178 | 30% |
Vazquez | Javier | 757 | 226 | 30% |
Garland | Jon | 717 | 213 | 30% |
Carmona | Fausto | 465 | 138 | 30% |
Cain | Matt | 738 | 219 | 30% |
Looper | Braden | 803 | 238 | 30% |
Bonser | Boof | 413 | 122 | 30% |
Masterson | Justin | 404 | 119 | 29% |
Lee | Cliff | 520 | 153 | 29% |
Burnett | A.J. | 915 | 269 | 29% |
Pelfrey | Mike | 837 | 246 | 29% |
Jurrjens | Jair | 827 | 243 | 29% |
Rowland-Smith | Ryan | 409 | 120 | 29% |
Cueto | Johnny | 805 | 236 | 29% |
Jackson | Edwin | 739 | 216 | 29% |
Parra | Manny | 625 | 182 | 29% |
Floyd | Gavin | 798 | 232 | 29% |
Park | Chan Ho | 394 | 114 | 29% |
Lannan | John | 730 | 211 | 29% |
Lilly | Ted | 564 | 163 | 29% |
Robertson | Nate | 583 | 168 | 29% |
Olson | Garrett | 552 | 159 | 29% |
Wainwright | Adam | 462 | 133 | 29% |
Grilli | Jason | 351 | 101 | 29% |
Litsch | Jesse | 602 | 173 | 29% |
Affeldt | Jeremy | 348 | 100 | 29% |
Chamberlain | Joba | 470 | 135 | 29% |
Harang | Aaron | 670 | 192 | 29% |
Cormier | Lance | 311 | 89 | 29% |
Marquis | Jason | 664 | 190 | 29% |
Dickey | R.A. | 406 | 116 | 29% |
Davis | Doug | 649 | 185 | 29% |
Rodriguez | Wandy | 509 | 145 | 28% |
Saunders | Joe | 720 | 205 | 28% |
Gallagher | Sean | 528 | 150 | 28% |
Bush | Dave | 695 | 197 | 28% |
Backe | Brandon | 682 | 193 | 28% |
Weathers | David | 364 | 103 | 28% |
Sampson | Chris | 354 | 100 | 28% |
Jimenez | Ubaldo | 812 | 229 | 28% |
Snell | Ian | 649 | 183 | 28% |
Cordero | Francisco | 401 | 113 | 28% |
Rasner | Darrell | 401 | 113 | 28% |
Howell | J.P. | 396 | 111 | 28% |
Mussina | Mike | 655 | 183 | 28% |
Villanueva | Carlos | 445 | 124 | 28% |
Delcarmen | Manny | 316 | 88 | 28% |
Ponson | Sidney | 504 | 140 | 28% |
Lohse | Kyle | 749 | 208 | 28% |
Zambrano | Carlos | 729 | 202 | 28% |
Green | Sean | 307 | 85 | 28% |
Weaver | Jered | 695 | 192 | 28% |
Heilman | Aaron | 375 | 103 | 27% |
Smith | Greg | 883 | 242 | 27% |
Verlander | Justin | 831 | 227 | 27% |
Bannister | Brian | 719 | 196 | 27% |
Bell | Heath | 305 | 83 | 27% |
Hammel | Jason | 324 | 88 | 27% |
Banks | Josh | 321 | 87 | 27% |
Blanton | Joe | 838 | 226 | 27% |
Myers | Brett | 802 | 216 | 27% |
Volquez | Edinson | 844 | 227 | 27% |
Zito | Barry | 819 | 220 | 27% |
Rogers | Kenny | 686 | 184 | 27% |
Romero | J.C. | 358 | 96 | 27% |
Duke | Zach | 567 | 152 | 27% |
Lincoln | Mike | 342 | 91 | 27% |
Guthrie | Jeremy | 654 | 174 | 27% |
Gaudin | Chad | 340 | 90 | 26% |
Arroyo | Bronson | 811 | 214 | 26% |
Sarfate | Dennis | 430 | 113 | 26% |
Redding | Tim | 709 | 186 | 26% |
Suppan | Jeff | 744 | 193 | 26% |
Millwood | Kevin | 541 | 140 | 26% |
Guerrier | Matt | 369 | 95 | 26% |
Hanrahan | Joel | 402 | 103 | 26% |
Burres | Brian | 523 | 134 | 26% |
Meche | Gil | 855 | 217 | 25% |
Bass | Brian | 332 | 84 | 25% |
Torres | Salomon | 329 | 83 | 25% |
Cook | Aaron | 580 | 146 | 25% |
Wright | Jamey | 330 | 83 | 25% |
Yates | Tyler | 327 | 82 | 25% |
Grabow | John | 329 | 82 | 25% |
Hochevar | Luke | 514 | 128 | 25% |
Cabrera | Daniel | 754 | 186 | 25% |
Feldman | Scott | 532 | 130 | 24% |
Padilla | Vicente | 621 | 150 | 24% |
Sanchez | Jonathan | 647 | 156 | 24% |
Buchholz | Clay | 307 | 74 | 24% |
Silva | Carlos | 561 | 135 | 24% |
Duchscherer | Justin | 488 | 117 | 24% |
Kendrick | Kyle | 627 | 150 | 24% |
Marmol | Carlos | 368 | 88 | 24% |
Reyes | Jo-Jo | 470 | 112 | 24% |
Rupe | Josh | 389 | 92 | 24% |
Hernandez | Livan | 747 | 175 | 23% |
Francis | Jeff | 631 | 147 | 23% |
Rivera | Saul | 391 | 91 | 23% |
Hendrickson | Mark | 482 | 111 | 23% |
Washburn | Jarrod | 666 | 153 | 23% |
Wakefield | Tim | 565 | 129 | 23% |
Maine | John | 597 | 133 | 22% |
Eveland | Dana | 686 | 146 | 21% |
Batista | Miguel | 530 | 111 | 21% |
Ledezma | Wilfredo | 309 | 64 | 21% |
McClung | Seth | 433 | 87 | 20% |
Bennett | Jeff | 404 | 79 | 20% |
Hudson | Tim | 569 | 111 | 20% |
Gregg | Kevin | 352 | 67 | 19% |
Owings | Micah | 405 | 72 | 18% |
Pinto | Renyel | 312 | 55 | 18% |
Laffey | Aaron | 358 | 62 | 17% |
Bonderman | Jeremy | 334 | 57 | 17% |
Contreras | Jose | 468 | 78 | 17% |
Gorzelanny | Tom | 444 | 74 | 17% |
McGowan | Dustin | 385 | 60 | 16% |
Penny | Brad | 376 | 57 | 15% |
Miller | Andrew | 451 | 64 | 14% |
Chacon | Shawn | 389 | 53 | 14% |
Eaton | Adam | 440 | 55 | 12% |
Wang | Chien-Ming | 343 | 41 | 12% |
Glavine | Tom | 372 | 44 | 12% |
Bedard | Erik | 304 | 31 | 10% |
Dumatrait | Phil | 362 | 31 | 9% |
Monday, April 6, 2009
Hitting where the ball is pitched
I play amateur baseball. I'm a second baseman with no power who makes a lot of contact. Since I rarely hit a ball past the outfielders, I always try to hit 'em where they ain't, to spray the balls to all the field, to hit it where it's pitched... pull the inside pitch, place the outside one in the opposite field.
Big leaguers have power.
Some of them are known to pull every ball, others seem to place the ball according to where it is pitched.
During the next paragraphs we will look at this issue.
I looked for a number to quantify the amount to which a hitter responds to the location of a pitch.
Here's what I've done.
Using gameday hit locations I calculated the trajectory of every batted ball, varying from -45° (down the LF line) to 45° (down the RF line); then I rescaled the trajectory value to have it varying from -1 to 1 (this made life easier for me in the following calculations).
Note: actually the trajectory of some hits, e.g. the groundballs that leave the infield inside the bag then roll in foul territory, exceeds the -45°/+45° boundary, but I coded those hits like having a trajectory of (-)45°.
Then, from PitchF/x, I took the horizontal coordinate of the pitches resulting in balls in play. Again I rescaled the values to have them bounded from -1 (inside for a RHB) to +1.
Note: I did not assign the value 1 to the outermost ball (for a RHB) in my dataset, because I had some severe outliers; I rescaled to one the 95th percentile coordinate. Same thing for -1 and LHBs.
With this couple of values for every ball in play I have all I need to get a value for hitting 'em where they're pitched.
I just need to calculate, for all the hitters, the correlation between the trajectory values and the location values: high correlation (near 1) means the hitter has a tendency to pull inside pitches and hit outside pitches the other way; zero correlation means that where the ball is put into play by the hitter is absolutely unrelated to where the pitch was located; inverse correlation (near -1) would mean the hitter hits... inside-out and outside-in.
Here are the top ten and bottom ten lists. I reported the correlation coefficient (rho) and the 95% confidence interval (lcl = lower confidence limit, hcl = higher confidence limit).
At the end of the post I'll give you a table containing all the players with at least 200 balls in play in 2008.
Bottom ten
OK, nobody hits the "wrong way".
I wondered if hitting the ball the "right way" improves the outcome of the batted ball.
A first (expected) answer is positive, since no player in the Majors hits inside-out and outside-in.
But I wanted some more.
I divided the batted balls in four quadrants, according to the sign of the trajectory and of the location values. Thus a pitch thrown outside to a RHB (location value approaching 1) hit to right field (trajectory value approaching 1) is in the first quadrant; similarly a ball with negative location value and positive trajectory value is in the second quadrant, negative-negative is in the third and positive-negative is the fourth.
Actually I removed a bunch of batted balls and put them in a fifth box; they are the balls with either the location or the trajectory value between -0.2 and 0.2.
Here are the average run values for balls in play by quadrant (quadrant numbers in the corners in roman).
As we would expect in the hypothesis that hitting the ball where it's pitched has a positive effect, we see higher values for the first and third quadrant: those are the boxes representing outside pitches hit the other way and inside pitches pulled by RHBs, respectively (those boxes also contain, respectively, pulled inside pitches and "pushed" outside pitches by LHBs).
Let's split RHBs and LHBs.
Accordingly to common sense we get higher values in the third quadrant for RHBs and in the first quadrant for LHBs: those are their pull quadrants for inside pitches.
The relative differences among quadrants also make some sense: the inside pitch pulled by the LHB can be snatched by one of the right infielders and converted into an out; for a RHB, the shortstop (or third baseman) making a diving catch on a hard roller still has a lot to do to get the out - opposite reasoning goes for opposite field batted balls on outside pitches (and thus the higher gap between 1st and 3rd quadrant for RHBs).
There's still something that might be polluting my numbers. Maybe in the first and third quadrants there are a lot of balls hit by players who are pull hitters who wait for the inside pitch. So we probably have some bias: in those two quandrants we simply have many balls hit by the best batters.
I redid the calculations.
For every batted ball I subtracted, from the outcome run value, the hitter's (the one who put the ball in play) average run value on batted balls. Now the values in the quadrants should be "cleaner".
Again we see the effects described before.
I don't think there's anything groundbreaking in this post. I just wanted to quantify a couple of things that are quite known.
Note: I haven't considered the vertical coordinate of the pitch location at all. I acknowledge this can be an issue.
Here is the full table I promised before.
Big leaguers have power.
Some of them are known to pull every ball, others seem to place the ball according to where it is pitched.
During the next paragraphs we will look at this issue.
I looked for a number to quantify the amount to which a hitter responds to the location of a pitch.
Here's what I've done.
Using gameday hit locations I calculated the trajectory of every batted ball, varying from -45° (down the LF line) to 45° (down the RF line); then I rescaled the trajectory value to have it varying from -1 to 1 (this made life easier for me in the following calculations).
Note: actually the trajectory of some hits, e.g. the groundballs that leave the infield inside the bag then roll in foul territory, exceeds the -45°/+45° boundary, but I coded those hits like having a trajectory of (-)45°.
Then, from PitchF/x, I took the horizontal coordinate of the pitches resulting in balls in play. Again I rescaled the values to have them bounded from -1 (inside for a RHB) to +1.
Note: I did not assign the value 1 to the outermost ball (for a RHB) in my dataset, because I had some severe outliers; I rescaled to one the 95th percentile coordinate. Same thing for -1 and LHBs.
With this couple of values for every ball in play I have all I need to get a value for hitting 'em where they're pitched.
I just need to calculate, for all the hitters, the correlation between the trajectory values and the location values: high correlation (near 1) means the hitter has a tendency to pull inside pitches and hit outside pitches the other way; zero correlation means that where the ball is put into play by the hitter is absolutely unrelated to where the pitch was located; inverse correlation (near -1) would mean the hitter hits... inside-out and outside-in.
Here are the top ten and bottom ten lists. I reported the correlation coefficient (rho) and the 95% confidence interval (lcl = lower confidence limit, hcl = higher confidence limit).
At the end of the post I'll give you a table containing all the players with at least 200 balls in play in 2008.
Top ten
LAST | FIRST | rho | lcl | hcl |
---|---|---|---|---|
Mientkiewicz | Doug | 0.42 | 0.31 | 0.52 |
Byrd | Marlon | 0.42 | 0.32 | 0.50 |
Morneau | Justin | 0.41 | 0.33 | 0.48 |
Dobbs | Greg | 0.40 | 0.27 | 0.51 |
Roberts | Brian | 0.40 | 0.32 | 0.47 |
Payton | Jay | 0.39 | 0.29 | 0.49 |
Fukudome | Kosuke | 0.39 | 0.30 | 0.47 |
Johjima | Kenji | 0.39 | 0.30 | 0.48 |
DeJesus | David | 0.38 | 0.30 | 0.46 |
Lopez | Jose | 0.38 | 0.31 | 0.45 |
Bottom ten
LAST | FIRST | rho | lcl | hcl |
---|---|---|---|---|
Willingham | Josh | 0.08 | -0.04 | 0.20 |
Kendrick | Howie | 0.08 | -0.04 | 0.19 |
Martinez | Victor | 0.07 | -0.07 | 0.20 |
Rodriguez | Alex | 0.06 | -0.04 | 0.16 |
Beltran | Carlos | 0.05 | -0.03 | 0.14 |
Hall | Bill | 0.05 | -0.06 | 0.17 |
Aybar | Willy | 0.04 | -0.07 | 0.15 |
Berroa | Angel | 0.04 | -0.11 | 0.18 |
Rollins | Jimmy | 0.01 | -0.08 | 0.09 |
Hawpe | Brad | 0.00 | -0.10 | 0.11 |
I wondered if hitting the ball the "right way" improves the outcome of the batted ball.
A first (expected) answer is positive, since no player in the Majors hits inside-out and outside-in.
But I wanted some more.
I divided the batted balls in four quadrants, according to the sign of the trajectory and of the location values. Thus a pitch thrown outside to a RHB (location value approaching 1) hit to right field (trajectory value approaching 1) is in the first quadrant; similarly a ball with negative location value and positive trajectory value is in the second quadrant, negative-negative is in the third and positive-negative is the fourth.
Actually I removed a bunch of batted balls and put them in a fifth box; they are the balls with either the location or the trajectory value between -0.2 and 0.2.
Here are the average run values for balls in play by quadrant (quadrant numbers in the corners in roman).
As we would expect in the hypothesis that hitting the ball where it's pitched has a positive effect, we see higher values for the first and third quadrant: those are the boxes representing outside pitches hit the other way and inside pitches pulled by RHBs, respectively (those boxes also contain, respectively, pulled inside pitches and "pushed" outside pitches by LHBs).
Let's split RHBs and LHBs.
Accordingly to common sense we get higher values in the third quadrant for RHBs and in the first quadrant for LHBs: those are their pull quadrants for inside pitches.
The relative differences among quadrants also make some sense: the inside pitch pulled by the LHB can be snatched by one of the right infielders and converted into an out; for a RHB, the shortstop (or third baseman) making a diving catch on a hard roller still has a lot to do to get the out - opposite reasoning goes for opposite field batted balls on outside pitches (and thus the higher gap between 1st and 3rd quadrant for RHBs).
There's still something that might be polluting my numbers. Maybe in the first and third quadrants there are a lot of balls hit by players who are pull hitters who wait for the inside pitch. So we probably have some bias: in those two quandrants we simply have many balls hit by the best batters.
I redid the calculations.
For every batted ball I subtracted, from the outcome run value, the hitter's (the one who put the ball in play) average run value on batted balls. Now the values in the quadrants should be "cleaner".
Again we see the effects described before.
I don't think there's anything groundbreaking in this post. I just wanted to quantify a couple of things that are quite known.
Note: I haven't considered the vertical coordinate of the pitch location at all. I acknowledge this can be an issue.
Here is the full table I promised before.
LAST | FIRST | rho | lcl | hcl |
---|---|---|---|---|
Mientkiewicz | Doug | 0.42 | 0.31 | 0.52 |
Byrd | Marlon | 0.42 | 0.32 | 0.50 |
Morneau | Justin | 0.41 | 0.33 | 0.48 |
Dobbs | Greg | 0.40 | 0.27 | 0.51 |
Roberts | Brian | 0.40 | 0.32 | 0.47 |
Payton | Jay | 0.39 | 0.29 | 0.49 |
Fukudome | Kosuke | 0.39 | 0.30 | 0.47 |
Johjima | Kenji | 0.39 | 0.30 | 0.48 |
DeJesus | David | 0.38 | 0.30 | 0.46 |
Lopez | Jose | 0.38 | 0.31 | 0.45 |
Polanco | Placido | 0.38 | 0.30 | 0.45 |
Blanco | Gregor | 0.38 | 0.28 | 0.47 |
Dellucci | David | 0.37 | 0.26 | 0.48 |
Matsui | Kazuo | 0.37 | 0.27 | 0.46 |
Scutaro | Marco | 0.37 | 0.28 | 0.45 |
Gutierrez | Franklin | 0.37 | 0.26 | 0.46 |
Torrealba | Yorvit | 0.36 | 0.23 | 0.48 |
Cairo | Miguel | 0.36 | 0.23 | 0.48 |
Helton | Todd | 0.36 | 0.24 | 0.47 |
Jackson | Conor | 0.36 | 0.28 | 0.44 |
Ordonez | Magglio | 0.36 | 0.28 | 0.44 |
Nady | Xavier | 0.36 | 0.27 | 0.44 |
Lee | Carlos | 0.36 | 0.27 | 0.44 |
Belliard | Ronnie | 0.36 | 0.24 | 0.47 |
Reed | Jeremy | 0.36 | 0.24 | 0.46 |
Lowrie | Jed | 0.36 | 0.23 | 0.47 |
Infante | Omar | 0.36 | 0.25 | 0.45 |
Hairston | Scott | 0.36 | 0.24 | 0.46 |
Burriss | Emmanuel | 0.35 | 0.23 | 0.47 |
Butler | Billy | 0.35 | 0.26 | 0.44 |
Anderson | Garret | 0.35 | 0.27 | 0.43 |
Hernandez | Ramon | 0.35 | 0.26 | 0.43 |
Miles | Aaron | 0.34 | 0.24 | 0.43 |
Gerut | Jody | 0.34 | 0.23 | 0.44 |
Pedroia | Dustin | 0.34 | 0.27 | 0.41 |
Kinsler | Ian | 0.34 | 0.25 | 0.42 |
Catalanotto | Frank | 0.34 | 0.21 | 0.45 |
Cabrera | Melky | 0.33 | 0.23 | 0.42 |
Pujols | Albert | 0.33 | 0.24 | 0.41 |
Bradley | Milton | 0.33 | 0.22 | 0.43 |
Braun | Ryan | 0.33 | 0.24 | 0.40 |
Barajas | Rod | 0.32 | 0.21 | 0.42 |
Grudzielanek | Mark | 0.32 | 0.21 | 0.42 |
Castillo | Luis | 0.32 | 0.20 | 0.43 |
Eckstein | David | 0.32 | 0.21 | 0.42 |
Weeks | Rickie | 0.32 | 0.22 | 0.41 |
Lamb | Mike | 0.32 | 0.19 | 0.44 |
Cabrera | Orlando | 0.32 | 0.24 | 0.39 |
Iwamura | Akinori | 0.31 | 0.23 | 0.39 |
Kapler | Gabe | 0.31 | 0.18 | 0.44 |
Lopez | Felipe | 0.31 | 0.22 | 0.40 |
Inglett | Joe | 0.31 | 0.20 | 0.41 |
Youkilis | Kevin | 0.31 | 0.23 | 0.39 |
Callaspo | Alberto | 0.31 | 0.18 | 0.43 |
Kubel | Jason | 0.31 | 0.21 | 0.40 |
Floyd | Cliff | 0.31 | 0.18 | 0.43 |
Hill | Aaron | 0.31 | 0.16 | 0.44 |
Molina | Yadier | 0.31 | 0.22 | 0.39 |
Wilson | Jack | 0.31 | 0.19 | 0.41 |
Reyes | Jose | 0.31 | 0.23 | 0.38 |
Ortiz | David | 0.31 | 0.21 | 0.40 |
Loretta | Mark | 0.31 | 0.18 | 0.42 |
German | Esteban | 0.30 | 0.17 | 0.43 |
Francoeur | Jeff | 0.30 | 0.22 | 0.38 |
Young | Michael | 0.30 | 0.22 | 0.38 |
Zimmerman | Ryan | 0.30 | 0.20 | 0.40 |
Tejada | Miguel | 0.30 | 0.22 | 0.38 |
Crosby | Bobby | 0.30 | 0.21 | 0.38 |
Gonzalez | Edgar | 0.30 | 0.18 | 0.41 |
Counsell | Craig | 0.30 | 0.17 | 0.42 |
Hinske | Eric | 0.30 | 0.18 | 0.40 |
Drew | J.D. | 0.30 | 0.19 | 0.40 |
Vizquel | Omar | 0.30 | 0.18 | 0.41 |
Rivas | Luis | 0.30 | 0.15 | 0.43 |
Theriot | Ryan | 0.29 | 0.21 | 0.37 |
Furcal | Rafael | 0.29 | 0.14 | 0.43 |
Matsui | Hideki | 0.29 | 0.18 | 0.40 |
Lind | Adam | 0.29 | 0.18 | 0.40 |
Berkman | Lance | 0.29 | 0.20 | 0.37 |
Brown | Emil | 0.29 | 0.19 | 0.39 |
Navarro | Dioner | 0.29 | 0.20 | 0.38 |
Dye | Jermaine | 0.29 | 0.21 | 0.37 |
Suzuki | Ichiro | 0.29 | 0.22 | 0.36 |
Martin | Russell | 0.29 | 0.20 | 0.37 |
Bautista | Jose | 0.29 | 0.18 | 0.39 |
Schumaker | Skip | 0.29 | 0.20 | 0.37 |
DeWitt | Blake | 0.29 | 0.18 | 0.39 |
Dunn | Adam | 0.29 | 0.19 | 0.38 |
Byrnes | Eric | 0.29 | 0.14 | 0.43 |
Hardy | J.J. | 0.29 | 0.20 | 0.37 |
Spilborghs | Ryan | 0.29 | 0.15 | 0.41 |
Taveras | Willy | 0.29 | 0.19 | 0.37 |
Sheffield | Gary | 0.29 | 0.18 | 0.38 |
Buck | John | 0.28 | 0.17 | 0.39 |
Izturis | Maicer | 0.28 | 0.17 | 0.39 |
Sanchez | Freddy | 0.28 | 0.20 | 0.36 |
Izturis | Cesar | 0.28 | 0.19 | 0.37 |
Beltre | Adrian | 0.28 | 0.19 | 0.36 |
Boone | Aaron | 0.28 | 0.13 | 0.42 |
Schneider | Brian | 0.28 | 0.17 | 0.39 |
Hairston | Jerry | 0.28 | 0.15 | 0.40 |
Wigginton | Ty | 0.28 | 0.17 | 0.38 |
Fontenot | Mike | 0.28 | 0.14 | 0.40 |
Inge | Brandon | 0.28 | 0.16 | 0.39 |
Ibanez | Raul | 0.28 | 0.19 | 0.36 |
McLouth | Nate | 0.28 | 0.19 | 0.36 |
Glaus | Troy | 0.27 | 0.18 | 0.36 |
Ross | Cody | 0.27 | 0.17 | 0.37 |
Aurilia | Rich | 0.27 | 0.17 | 0.37 |
Coste | Chris | 0.27 | 0.15 | 0.39 |
Tulowitzki | Troy | 0.27 | 0.17 | 0.37 |
Rios | Alex | 0.27 | 0.19 | 0.35 |
Stairs | Matt | 0.27 | 0.14 | 0.39 |
Casilla | Alexi | 0.27 | 0.17 | 0.37 |
Damon | Johnny | 0.27 | 0.18 | 0.35 |
Zaun | Gregg | 0.27 | 0.13 | 0.40 |
Michaels | Jason | 0.27 | 0.13 | 0.39 |
Ellsbury | Jacoby | 0.27 | 0.18 | 0.35 |
Suzuki | Kurt | 0.27 | 0.18 | 0.35 |
Sweeney | Ryan | 0.27 | 0.16 | 0.37 |
Lewis | Fred | 0.27 | 0.16 | 0.36 |
Kotchman | Casey | 0.26 | 0.18 | 0.35 |
McCann | Brian | 0.26 | 0.17 | 0.35 |
Gross | Gabe | 0.26 | 0.15 | 0.37 |
Markakis | Nick | 0.26 | 0.18 | 0.35 |
Lee | Derrek | 0.26 | 0.18 | 0.34 |
Huff | Aubrey | 0.26 | 0.18 | 0.34 |
Bay | Jason | 0.26 | 0.17 | 0.35 |
LaRoche | Adam | 0.26 | 0.16 | 0.36 |
Ellis | Mark | 0.26 | 0.16 | 0.36 |
Blake | Casey | 0.26 | 0.17 | 0.35 |
Erstad | Darin | 0.26 | 0.14 | 0.37 |
Burrell | Pat | 0.26 | 0.17 | 0.35 |
Bartlett | Jason | 0.26 | 0.17 | 0.35 |
Ethier | Andre | 0.26 | 0.17 | 0.34 |
Hamilton | Josh | 0.26 | 0.17 | 0.34 |
Atkins | Garrett | 0.26 | 0.17 | 0.34 |
Guillen | Carlos | 0.26 | 0.15 | 0.35 |
Murphy | David | 0.25 | 0.15 | 0.35 |
Snyder | Chris | 0.25 | 0.12 | 0.37 |
Molina | Jose | 0.25 | 0.12 | 0.37 |
Loney | James | 0.25 | 0.17 | 0.33 |
Bako | Paul | 0.25 | 0.12 | 0.38 |
Barton | Daric | 0.25 | 0.15 | 0.35 |
Lowell | Mike | 0.25 | 0.15 | 0.35 |
Chavez | Endy | 0.25 | 0.13 | 0.36 |
Edmonds | Jim | 0.25 | 0.13 | 0.36 |
Blalock | Hank | 0.25 | 0.11 | 0.38 |
Betancourt | Yuniesky | 0.25 | 0.16 | 0.33 |
Longoria | Evan | 0.25 | 0.15 | 0.34 |
Cabrera | Miguel | 0.25 | 0.16 | 0.33 |
Giambi | Jason | 0.25 | 0.14 | 0.34 |
Crawford | Carl | 0.25 | 0.15 | 0.33 |
Gload | Ross | 0.24 | 0.14 | 0.34 |
Shoppach | Kelly | 0.24 | 0.11 | 0.37 |
Fielder | Prince | 0.24 | 0.15 | 0.33 |
Carroll | Jamey | 0.24 | 0.13 | 0.35 |
Barmes | Clint | 0.24 | 0.14 | 0.35 |
Phillips | Brandon | 0.24 | 0.15 | 0.33 |
Sizemore | Grady | 0.24 | 0.16 | 0.32 |
Amezaga | Alfredo | 0.24 | 0.12 | 0.35 |
Pierre | Juan | 0.24 | 0.14 | 0.33 |
Keppinger | Jeff | 0.24 | 0.14 | 0.32 |
Konerko | Paul | 0.24 | 0.13 | 0.33 |
Abreu | Bobby | 0.24 | 0.15 | 0.32 |
Guerrero | Vladimir | 0.24 | 0.15 | 0.32 |
Escobar | Yunel | 0.23 | 0.14 | 0.32 |
Kent | Jeff | 0.23 | 0.14 | 0.33 |
Hunter | Torii | 0.23 | 0.14 | 0.32 |
Thomas | Frank | 0.23 | 0.09 | 0.37 |
Young | Delmon | 0.23 | 0.14 | 0.32 |
Bourn | Michael | 0.23 | 0.13 | 0.33 |
Cust | Jack | 0.23 | 0.12 | 0.34 |
Kennedy | Adam | 0.23 | 0.12 | 0.34 |
DeRosa | Mark | 0.23 | 0.13 | 0.32 |
Jones | Chipper | 0.23 | 0.13 | 0.32 |
Ramirez | Manny | 0.23 | 0.14 | 0.31 |
Iannetta | Chris | 0.23 | 0.10 | 0.35 |
Matthews | Gary | 0.23 | 0.12 | 0.33 |
Soto | Geovany | 0.22 | 0.12 | 0.32 |
Kouzmanoff | Kevin | 0.22 | 0.13 | 0.31 |
Pena | Tony | 0.22 | 0.08 | 0.36 |
Bowker | John | 0.22 | 0.10 | 0.34 |
Mathis | Jeff | 0.22 | 0.08 | 0.35 |
Renteria | Edgar | 0.22 | 0.12 | 0.31 |
Punto | Nick | 0.22 | 0.10 | 0.33 |
Garko | Ryan | 0.22 | 0.12 | 0.31 |
Moss | Brandon | 0.22 | 0.06 | 0.36 |
Rivera | Juan | 0.22 | 0.09 | 0.34 |
Hudson | Orlando | 0.22 | 0.11 | 0.32 |
Aviles | Mike | 0.22 | 0.11 | 0.31 |
Patterson | Corey | 0.22 | 0.10 | 0.32 |
Utley | Chase | 0.21 | 0.13 | 0.29 |
Rodriguez | Luis O. | 0.21 | 0.07 | 0.35 |
Pierzynski | A.J. | 0.21 | 0.12 | 0.30 |
Gathright | Joey | 0.21 | 0.09 | 0.33 |
Giles | Brian | 0.21 | 0.12 | 0.30 |
Granderson | Curtis | 0.21 | 0.12 | 0.30 |
Molina | Bengie | 0.21 | 0.12 | 0.29 |
Buscher | Brian | 0.21 | 0.06 | 0.35 |
Werth | Jayson | 0.21 | 0.10 | 0.31 |
Milledge | Lastings | 0.21 | 0.11 | 0.30 |
Jenkins | Geoff | 0.21 | 0.08 | 0.33 |
Easley | Damion | 0.21 | 0.09 | 0.32 |
Lugo | Julio | 0.20 | 0.07 | 0.34 |
Cano | Robinson | 0.20 | 0.12 | 0.29 |
Sexson | Richie | 0.20 | 0.06 | 0.34 |
Rolen | Scott | 0.20 | 0.10 | 0.31 |
Holliday | Matt | 0.20 | 0.11 | 0.29 |
Wells | Vernon | 0.20 | 0.10 | 0.30 |
Iguchi | Tadahito | 0.20 | 0.07 | 0.32 |
Kearns | Austin | 0.20 | 0.08 | 0.32 |
Guillen | Jose | 0.20 | 0.11 | 0.29 |
Wright | David | 0.20 | 0.11 | 0.28 |
Cantu | Jorge | 0.20 | 0.12 | 0.28 |
Harris | Brendan | 0.20 | 0.09 | 0.30 |
Gomez | Carlos | 0.20 | 0.11 | 0.29 |
Prado | Martin | 0.20 | 0.06 | 0.33 |
Howard | Ryan | 0.20 | 0.10 | 0.29 |
Figgins | Chone | 0.20 | 0.10 | 0.29 |
Feliz | Pedro | 0.20 | 0.10 | 0.29 |
Tracy | Chad | 0.20 | 0.06 | 0.32 |
Baker | Jeff | 0.19 | 0.06 | 0.32 |
Ruiz | Carlos | 0.19 | 0.09 | 0.30 |
Gonzalez | Luis | 0.19 | 0.08 | 0.30 |
Hermida | Jeremy | 0.19 | 0.09 | 0.29 |
Guzman | Cristian | 0.19 | 0.11 | 0.28 |
Ramirez | Aramis | 0.19 | 0.10 | 0.28 |
Reynolds | Mark | 0.19 | 0.09 | 0.30 |
Olivo | Miguel | 0.19 | 0.06 | 0.32 |
Young | Chris | 0.19 | 0.10 | 0.28 |
Crede | Joe | 0.19 | 0.07 | 0.30 |
Drew | Stephen | 0.19 | 0.10 | 0.27 |
Cuddyer | Michael | 0.19 | 0.05 | 0.32 |
Delgado | Carlos | 0.19 | 0.10 | 0.28 |
Johnson | Kelly | 0.19 | 0.10 | 0.28 |
Rodriguez | Ivan | 0.19 | 0.08 | 0.29 |
Laird | Gerald | 0.19 | 0.07 | 0.30 |
Francisco | Ben | 0.19 | 0.08 | 0.29 |
Vazquez | Ramon | 0.19 | 0.06 | 0.31 |
Gonzalez | Carlos | 0.18 | 0.05 | 0.31 |
Overbay | Lyle | 0.18 | 0.09 | 0.28 |
Winn | Randy | 0.18 | 0.10 | 0.27 |
Johnson | Reed | 0.18 | 0.06 | 0.30 |
Davis | Rajai | 0.18 | 0.03 | 0.32 |
Gordon | Alex | 0.18 | 0.08 | 0.28 |
Velez | Eugenio | 0.18 | 0.05 | 0.30 |
Millar | Kevin | 0.18 | 0.08 | 0.27 |
Hart | Corey | 0.18 | 0.09 | 0.26 |
Cabrera | Asdrubal | 0.17 | 0.06 | 0.29 |
Duncan | Chris | 0.17 | 0.02 | 0.32 |
Greene | Khalil | 0.17 | 0.06 | 0.29 |
Jacobs | Mike | 0.17 | 0.07 | 0.27 |
Swisher | Nick | 0.17 | 0.07 | 0.27 |
Jeter | Derek | 0.17 | 0.09 | 0.26 |
Kendall | Jason | 0.17 | 0.08 | 0.26 |
Scott | Luke | 0.17 | 0.07 | 0.27 |
Span | Denard | 0.17 | 0.05 | 0.28 |
Vidro | Jose | 0.17 | 0.05 | 0.28 |
Castillo | Jose | 0.17 | 0.06 | 0.27 |
Mauer | Joe | 0.17 | 0.08 | 0.25 |
Crisp | Coco | 0.16 | 0.05 | 0.27 |
Teahen | Mark | 0.16 | 0.07 | 0.25 |
Cedeno | Ronny | 0.16 | 0.01 | 0.31 |
Gonzalez | Adrian | 0.16 | 0.07 | 0.25 |
Encarnacion | Edwin | 0.16 | 0.06 | 0.26 |
Stewart | Shannon | 0.16 | -0.01 | 0.32 |
Rowand | Aaron | 0.16 | 0.06 | 0.25 |
Upton | B.J. | 0.16 | 0.06 | 0.25 |
Thames | Marcus | 0.16 | 0.02 | 0.28 |
Flores | Jesus | 0.16 | 0.02 | 0.28 |
Thome | Jim | 0.16 | 0.05 | 0.26 |
Victorino | Shane | 0.16 | 0.07 | 0.24 |
Varitek | Jason | 0.15 | 0.05 | 0.26 |
Jones | Adam | 0.15 | 0.05 | 0.25 |
Kemp | Matt | 0.15 | 0.06 | 0.24 |
Griffey Jr. | Ken | 0.15 | 0.05 | 0.25 |
Durham | Ray | 0.15 | 0.04 | 0.26 |
Helms | Wes | 0.15 | 0.00 | 0.29 |
Doumit | Ryan | 0.15 | 0.04 | 0.25 |
Cameron | Mike | 0.15 | 0.03 | 0.26 |
Peralta | Jhonny | 0.15 | 0.06 | 0.23 |
Tatis | Fernando | 0.15 | 0.01 | 0.28 |
Bruntlett | Eric | 0.14 | -0.00 | 0.29 |
Soriano | Alfonso | 0.14 | 0.04 | 0.25 |
Hannahan | Jack | 0.14 | 0.03 | 0.25 |
Kotsay | Mark | 0.14 | 0.04 | 0.24 |
Ramirez | Alexei | 0.14 | 0.04 | 0.23 |
Aybar | Erick | 0.13 | 0.02 | 0.24 |
Headley | Chase | 0.13 | -0.00 | 0.26 |
Ramirez | Hanley | 0.13 | 0.04 | 0.22 |
Harris | Willie | 0.13 | 0.01 | 0.24 |
Ludwick | Ryan | 0.13 | 0.03 | 0.23 |
Dukes | Elijah | 0.13 | -0.01 | 0.26 |
Blum | Geoff | 0.13 | 0.00 | 0.24 |
Quentin | Carlos | 0.12 | 0.02 | 0.22 |
Wilkerson | Brad | 0.12 | -0.02 | 0.26 |
Pence | Hunter | 0.12 | 0.03 | 0.21 |
Ankiel | Rick | 0.12 | 0.01 | 0.23 |
Church | Ryan | 0.12 | -0.01 | 0.25 |
Davis | Chris | 0.12 | -0.03 | 0.26 |
Choo | Shin-Soo | 0.11 | -0.02 | 0.24 |
Bruce | Jay | 0.11 | -0.00 | 0.22 |
Pena | Carlos | 0.11 | 0.00 | 0.21 |
Ausmus | Brad | 0.11 | -0.05 | 0.26 |
Teixeira | Mark | 0.10 | 0.01 | 0.19 |
Uggla | Dan | 0.10 | -0.00 | 0.21 |
Mora | Melvin | 0.10 | 0.01 | 0.20 |
Uribe | Juan | 0.10 | -0.02 | 0.22 |
Ojeda | Augie | 0.10 | -0.04 | 0.24 |
Votto | Joey | 0.10 | 0.00 | 0.19 |
Upton | Justin | 0.10 | -0.04 | 0.23 |
Balentien | Wladimir | 0.09 | -0.07 | 0.24 |
Marte | Andy | 0.09 | -0.06 | 0.23 |
Willingham | Josh | 0.08 | -0.04 | 0.20 |
Kendrick | Howie | 0.08 | -0.04 | 0.19 |
Martinez | Victor | 0.07 | -0.07 | 0.20 |
Rodriguez | Alex | 0.06 | -0.04 | 0.16 |
Beltran | Carlos | 0.05 | -0.03 | 0.14 |
Hall | Bill | 0.05 | -0.06 | 0.17 |
Aybar | Willy | 0.04 | -0.07 | 0.15 |
Berroa | Angel | 0.04 | -0.11 | 0.18 |
Rollins | Jimmy | 0.01 | -0.08 | 0.09 |
Hawpe | Brad | 0.00 | -0.10 | 0.11 |
Wednesday, April 1, 2009
Bad ball swingers
As the new season is ready to roll, I take some time to give away the 2008 Vladimir Guerrero Award.
Using Pitchf/x data I looked at the players who swing frequently at bad pitches, and I tried to figure if they hurt themselves by trying to hit everything.
Initially I planned to look at all swings occurred on a pitch that was a ball according to the rulebook strike zone; then I decided to do things differently.
Using spatial smoothing I calculated the probability of a pitch to be called strike, given it's location. A previous study I run on my Italian website, and other researches by other authors at THT and elsewhere, had showed that batter handedness influences umpire decisions more than pitcher handedness, so I calculated different probabilities for RHB and LHB.
A couple of charts will summarize this part.
I decided to classify a pitch as a "bad ball" when its probability to be called strike is lower than 10% (the cutoff value is purely subjective, and I'd welcome suggestions for a different choice).
Here are the top ten bad ball swingers:
No Vlad on the list? I must have done something wrong!... No, he's the eleventh, just out of the table, at 37%.
I compared my full list with the one at FanGraphs and while they don't coincide, they are quite similar. Anyway they don't have to coincide, since FG charts outside zone swing %, while I'm charting "really outside zone swing %".
Here's the bottom of the list.
For this work I selected players who have seen at least 300 bad pitches. I don't know if this choice caused some players who don't swing at bad pitches to be left out.
Next thing I investigated is run value for swings on bad balls.
Many players are notorious bad ball swingers, but they are also feared because they can do a lot of damage even when they chase pitches in the dirt.
In the following table I summed up the run values obtained by hitters when they swung at a bad pitch.
But what if all those pitches were let go by?
I calculated the net run value for bad pitches, which you will find in the next table, as following:
- if the batter didn't swing, assign the run value of the pitch (likely the run value of a ball; but if the ump called it a strike, then the run value of a strike);
- if the batter swung, assign the run value of the event minus the expected run value of the pitch had the batter not swung (that is something like 90+% * run value of a ball + 10-% * run value of a strike).
As we see from the table, Gary Sheffield is the only player in MLB to have a positive value for his bad pitch swinging (at 29% his swinging percentage on bad pitches is middle-of-the-pack). Jose Reyes, the worst in this ranking, has lost 32 runs by swinging at balls way out of the zone.
Players like Ryan Howard and Vladimir Guerrero can have a gross production of more than 11 runs when swinging at bad balls, but when you look at what they would have produced had they let those pitches go by you get a net loss of nearly 30 runs.
I think I made you wander too long in the dark by giving just a few top-ten tables. Here's a spreadsheet with all the players that made my cut of 300 bad pitches seen.
Using Pitchf/x data I looked at the players who swing frequently at bad pitches, and I tried to figure if they hurt themselves by trying to hit everything.
Initially I planned to look at all swings occurred on a pitch that was a ball according to the rulebook strike zone; then I decided to do things differently.
Using spatial smoothing I calculated the probability of a pitch to be called strike, given it's location. A previous study I run on my Italian website, and other researches by other authors at THT and elsewhere, had showed that batter handedness influences umpire decisions more than pitcher handedness, so I calculated different probabilities for RHB and LHB.
A couple of charts will summarize this part.
I decided to classify a pitch as a "bad ball" when its probability to be called strike is lower than 10% (the cutoff value is purely subjective, and I'd welcome suggestions for a different choice).
Here are the top ten bad ball swingers:
LAST | FIRST | swing_pct |
Soriano | Alfonso | 43% |
Barmes | Clint | 42% |
Headley | Chase | 41% |
Span | Denard | 41% |
Ramirez | Alexei | 41% |
Aviles | Mike | 40% |
Stewart | Ian | 40% |
Gomez | Carlos | 39% |
Uribe | Juan | 38% |
Lowrie | Jed | 38% |
No Vlad on the list? I must have done something wrong!... No, he's the eleventh, just out of the table, at 37%.
I compared my full list with the one at FanGraphs and while they don't coincide, they are quite similar. Anyway they don't have to coincide, since FG charts outside zone swing %, while I'm charting "really outside zone swing %".
Here's the bottom of the list.
LAST | FIRST | swing_pct |
Matthews | Gary | 19% |
Dellucci | David | 19% |
Lewis | Fred | 19% |
Murphy | David | 18% |
Crede | Joe | 18% |
Matsui | Hideki | 16% |
Sexson | Richie | 16% |
Upton | Justin | 16% |
Castillo | Luis | 10% |
Helton | Todd | 5% |
Next thing I investigated is run value for swings on bad balls.
Many players are notorious bad ball swingers, but they are also feared because they can do a lot of damage even when they chase pitches in the dirt.
In the following table I summed up the run values obtained by hitters when they swung at a bad pitch.
LAST | FIRST | swing_run_value |
Sheffield | Gary | 9.37 |
Garko | Ryan | 7.28 |
Stewart | Ian | 5.86 |
Mauer | Joe | 4.99 |
Glaus | Troy | 4.87 |
Ortiz | David | 4.24 |
Cust | Jack | 4.02 |
Kubel | Jason | 3.95 |
Huff | Aubrey | 3.74 |
Hinske | Eric | 2.55 |
I calculated the net run value for bad pitches, which you will find in the next table, as following:
- if the batter didn't swing, assign the run value of the pitch (likely the run value of a ball; but if the ump called it a strike, then the run value of a strike);
- if the batter swung, assign the run value of the event minus the expected run value of the pitch had the batter not swung (that is something like 90+% * run value of a ball + 10-% * run value of a strike).
LAST | FIRST | net_run_value |
Sheffield | Gary | 1.85 |
Stewart | Ian | -1.77 |
Glaus | Troy | -2.34 |
Hinske | Eric | -2.76 |
Cust | Jack | -3.08 |
Murphy | David | -3.39 |
Mauer | Joe | -3.84 |
Kubel | Jason | -3.85 |
Helton | Todd | -3.97 |
Bourn | Michael | -4.31 |
As we see from the table, Gary Sheffield is the only player in MLB to have a positive value for his bad pitch swinging (at 29% his swinging percentage on bad pitches is middle-of-the-pack). Jose Reyes, the worst in this ranking, has lost 32 runs by swinging at balls way out of the zone.
Players like Ryan Howard and Vladimir Guerrero can have a gross production of more than 11 runs when swinging at bad balls, but when you look at what they would have produced had they let those pitches go by you get a net loss of nearly 30 runs.
I think I made you wander too long in the dark by giving just a few top-ten tables. Here's a spreadsheet with all the players that made my cut of 300 bad pitches seen.
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