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.

The year of The Bird

I like doing statistical analysis and producing charts, so this is my tribute to Mark Fidrych.

Click on the chart to have it zoomed.
A red cross (plus day of the week) is placed on games started by The Bird. Information on attendance is not available for a couple of his starts at the end of the season.
Thanks a lot to Retrosheet for providing the data.

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%).

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%

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).

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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

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.

RHBs

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".

RHBs

LHBs

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

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:

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%

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.

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

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).

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.