Baseball ProGUESTus: The Rookie Effect

Believe it or not, most of our writers didn't enter the world sporting an @baseballprospectus.com address; with a few exceptions, they started out somewhere else. In an effort to up your reading pleasure while tipping our caps to some of the most illuminating work being done elsewhere on the internet, we'll be yielding the stage once a week to the best and brightest baseball writers, researchers and thinkers from outside of the BP umbrella. If you'd like to nominate a guest contributor (including yourself), please drop us a line.

Brian Mills is a dual graduate student in Sport Management and Statistics and runs the blog Prince of Slides. As a former college player and high school coach, he continues to find ways to keep his mind on baseball and off of real life. While Brian mostly encounters management and economic problems in the office, he enjoys dabbling in sports analytics and playing fantasy baseball in his free time. He and his fiancée have two cats, Callie and Ripken. You can probably figure out who got to name them.

Every year we hear about rookies breaking out unexpectedly and tearing through the first half of the season. Then it all falls apart. Sportswriters often conclude that the player must have been "figured out" by the opposing team: perhaps when players are first called up, in order to save time and energy, opposing pitchers simply put the ball over the plate to allow them to make their own outs. In some cases, this ends up being a big mistake.

To see whether this rookie adjustment is real, I set out to look for any systematic differences in pitch locations to rookie and veteran players, and for evidence of adaptation by opposing pitchers later in the season. My first step was to see if the location of pitches for rookies (defined here as players who debuted during the 2010 season) differs in any way from more veteran guys. We can do this in two ways: Check the difference in percentage of pitches within the rulebook strike zone for rookie batters and veterans; and check to see if the average distance from the center of the plate differs between these two groups of players. If pitchers aren’t worried about putting a ball over the plate to rookies, then it seems reasonable that these players would see more pitches near the center of the plate and within the strike zone.

As a first step, I ran a regression analysis of average linear distance from the center of the plate, controlling for count, pitcher, batter handedness, whether or not the pitch is within the strike zone (as defined by the edge of the plate, a bottom of the zone at 1.75 feet, and a top of the zone at 3.45 feet), whether there are runners on base, the inning, the outs, the count, the spread in score (rookies may be more likely to play in blowout situations when pitchers would be less fine in their location), and whether or not the pitcher or the batter debuted in 2010. The result: there is no discernable difference in how far pitchers are from "grooving" pitches to players who debuted in the current season.

But this is likely not the whole story. If pitchers are throwing pitches in some sort of systematic dichotomy—rookies get pitches down the pipe or way off the plate, while veterans see pitches mostly near the edges of the strike zone—we may not see any difference in this average linear distance variable. Therefore, it is also important to examine the percentage of pitches within the strike zone. To do this, I used a logistic regression, with similar independent variables from the previous analysis, and then re-ran my first regression—for the distance of the pitch from the center of the zone—separately for pitches within and outside the strike zone. The results are similar: no significant difference for 2010 debuts and the rest of the players in the data. The pitch maps below show the location densities for each group of players.

Strikingly similar pictures of pitch location, and this turns out to be the case even when you break down pitches by count. (See tables at the end of this article.)

However, I’m still not completely satisfied. Perhaps pitchers adjust to the player’s tendencies during the course of the season, rather than being consistent through the entire year. Maybe this is why our maps look so similar: the adjustment eventually smooths things out to look identical.

Solving this took a bit more statistical muscle. First, I sequenced each pitch seen for every player, to see if there are any changes during the players’ first season in the bigs. From there, I took the average percentage of pitches within the strike zone for each pitch (first to last) to all rookies. A simple regression shows a very small statistically significant result in the expected direction: as time goes by, pitchers are less likely to throw the ball down the middle.

There is a slight change here, noted by the red lines. However, it turns out that this effect is not real. Only 25 of the 142 players in the sample saw a full 633 pitches. If we restrict the sample to only these players, the "adjustment" slope disappears.

Why? Well, it turns out that the players that saw fewer pitches were most likely lower-level rookies, and therefore received more pitches near the middle of the plate. Once these guys are weeded out, the remaining rookies pull the average Within Zone Percentage down (and Distance From Center upward). So what we're seeing seems to be simply an effect of better rookies—who last longer—seeing fewer pitches down the pipe. Essentially, top rookie hitters are treated similarly to top veteran hitters, while those without known power are treated like David Eckstein.

In the end, it seems that once a player hits the majors, the book is out on him. Certainly there could be cases where batters suddenly stop getting pitches grooved down the middle, but in general it's not happening often enough to show up in the data. As a whole, each player tends to see a similar approach throughout the entire season, rather than a sudden—or even gradual—in season adjustment to the swinging tendencies.

Table 1:

2010 Rookies

	Total Pitches Seen	Total Pitches Within Zone	Percent of Pitches Within Zone
0-0 Count	11878	4845	40.79%
0-1 Count	5701	1870	32.80%
0-2 Count	2853	637	22.33%
1-0 Count	4894	2057	42.03%
1-1 Count	4652	1697	36.48%
1-2 Count	4185	1145	27.36%
2-0 Count	1694	796	46.99%
2-1 Count	2411	1021	42.35%
2-2 Count	3580	1286	35.92%
3-0 Count	541	250	46.21%
3-1 Count	962	477	49.58%
3-2 Count	2068	947	45.79%
Totals All Counts	45419	17028	37.49%

**Green indicates that the rate is higher than the more veteran players, while Red indicates the rate is lower.

2010 Veterans

	Total Pitches Seen	Total Pitches Witin Zone	Percent of Pitches Within Zone
0-0 Count	166992	68635	41.10%
0-1 Count	79418	25958	32.69%
0-2 Count	37355	8172	21.88%
1-0 Count	69284	29225	42.18%
1-1 Count	65852	24657	37.44%
1-2 Count	57346	15330	26.73%
2-0 Count	24695	11097	44.94%
2-1 Count	35426	15303	43.20%
2-2 Count	49540	17226	34.77%
3-0 Count	8418	3767	44.75%
3-1 Count	15332	7454	48.62%
3-2 Count	30224	13852	45.83%
Totals All Counts	639882	240676	37.61%

**Green indicates that the rate is higher than the MLB 2010 Debuts, while Red indicates the rate is lower.

Table 2: Player by Player Pitches Seen Within Strike Zone (>300 Pitches Seen; Includes Pitchers)

First Name	Last Name	% of Pitches Within Strike Zone	Total Pitches Seen	MLB Debut in 2010
Drew	Butera	45.36%	582	Yes
Darwin	Barney	45.35%	333	Yes
Peter	Bourjos	45.08%	701	Yes
Danny	Valencia	42.48%	1163	Yes
Danny	Worth	42.27%	414	Yes
Cole	Gillespie	41.98%	455	Yes
Chris	Heisey	41.61%	858	Yes
Ruben	Tejada	41.47%	914	Yes
Jason	Donald	41.46%	1153	Yes
Jose	Tabata	41.19%	1595	Yes
Lorenzo	Cain	40.97%	642	Yes
Scott	Sizemore	40.76%	628	Yes
Daniel	Nava	40.48%	751	Yes
Brad	Davis	40.09%	459	Yes
Austin	Jackson	40.03%	2703	Yes
Will	Rhymes	40.03%	742	Yes
Jonathan	Lucroy	39.49%	1175	Yes
Wilson	Ramos	39.27%	303	Yes
Casper	Wells	39.24%	367	Yes
Ryan	Kalish	39.00%	741	Yes
Allen	Craig	38.48%	499	Yes
Jesus	Feliciano	38.22%	437	Yes
Starlin	Castro	38.05%	1832	Yes
Carlos	Santana	37.55%	799	Yes
Dayan	Viciedo	36.72%	354	Yes
Chris	Carter	36.63%	303	Yes
Mike	Stanton	36.49%	1592	Yes
Domonic	Brown	36.33%	311	Yes
Jordan	Brown	36.11%	324	Yes
Pedro	Alvarez	36.11%	1501	Yes
Danny	Espinosa	35.48%	434	Yes
Josh	Bell	35.15%	549	Yes
Jason	Heyward	35.13%	2582	Yes
Logan	Morrison	35.03%	1179	Yes
Justin	Smoak	34.92%	1532	Yes
Mitch	Moreland	34.67%	675	Yes
Jon	Jay	34.60%	1234	Yes
Jason	Castro	34.09%	883	Yes
Lucas	Duda	32.51%	363	Yes
Brennan	Boesch	31.66%	1769	Yes
Brett	Wallace	31.44%	633	Yes
Ike	Davis	30.19%	2375	Yes
Chris	Carter	28.57%	623	Yes
Matt	Treanor	47.21%	985	No
Mike	McCoy	47.16%	335	No
Roy	Halladay	47.15%	333	No
Juan	Castro	46.99%	498	No
Jack	Wilson	46.15%	728	No
Marco	Scutaro	46.15%	2802	No
John	McDonald	45.00%	560	No
David	Eckstein	44.99%	1847	No
Jason	Kendall	44.69%	1828	No
Brent	Lillibridge	44.59%	370	No
Lou	Marson	44.39%	1131	No
Elvis	Andrus	44.30%	2686	No
Jamey	Carroll	44.30%	1799	No
Eric	Young, Jr.	44.09%	694	No
Francisco	Cervelli	43.87%	1158	No
Dustin	Pedroia	43.84%	1510	No
Kevin	Cash	43.74%	471	No
Eric	Patterson	43.64%	857	No
Rob	Johnson	43.63%	855	No
Bobby	Wilson	43.44%	389	No
Ramon	Castro	43.35%	489	No
Kevin	Frandsen	43.32%	561	No
Placido	Polanco	43.11%	2120	No
Sean	Rodriguez	43.09%	1432	No
Brett	Carroll	42.77%	346	No
Kevin	Youkilis	42.50%	1854	No
Angel	Sanchez	42.50%	1026	No
Brendan	Harris	42.49%	466	No
Jayson	Nix	42.41%	1271	No
David	Ross	42.40%	592	No
Jason	Repko	42.18%	569	No
Jose	Molina	42.18%	671	No
Freddy	Sanchez	42.17%	1750	No
Ben	Francisco	42.16%	733	No
Jacoby	Ellsbury	42.07%	309	No
John	Hester	42.06%	428	No
Tommy	Manzella	42.04%	1068	No
Kurt	Suzuki	41.99%	1879	No
Garrett	Atkins	41.97%	579	No
Paul	Janish	41.97%	834	No
Jed	Lowrie	41.96%	777	No
Joaquin	Arias	41.93%	508	No
Mike	Lowell	41.69%	897	No
Kelly	Shoppach	41.63%	723	No
Andrew	McCutchen	41.62%	2626	No
Reed	Johnson	41.59%	690	No
Jeff	Mathis	41.59%	731	No
Mark	Ellis	41.58%	1787	No
Julio	Lugo	41.57%	991	No
Austin	Kearns	41.52%	1864	No
Pat	Burrell	41.51%	1838	No
Edgar	Renteria	41.50%	1065	No
Henry	Blanco	41.47%	516	No
Aaron	Hill	41.45%	2118	No
Omar	Infante	41.39%	1795	No
Brandon	Inge	41.38%	2383	No
Matt	Tuiasosopo	41.37%	539	No
Bobby	Crosby	41.36%	723	No
Mike	Aviles	41.24%	1559	No
Reggie	Willits	41.24%	788	No
Taylor	Teagarden	41.23%	342	No
Casey	Blake	41.23%	2416	No
Wil	Nieves	41.21%	597	No
Chone	Figgins	41.20%	2893	No
Rajai	Davis	41.20%	1903	No
Ryan	Theriot	41.17%	2334	No
Ty	Wigginton	41.17%	2390	No
Willie	Bloomquist	41.17%	651	No
Brandon	Wood	41.12%	890	No
Denard	Span	41.10%	2657	No
B.J.	Upton	41.03%	2364	No
Geovany	Soto	41.03%	1555	No
Matt	Carson	41.00%	300	No
Michael	Young	40.96%	2695	No
Howie	Kendrick	40.96%	2395	No
Jeff	Keppinger	40.94%	2196	No
Wilson	Valdez	40.93%	1224	No
Martin	Prado	40.86%	2555	No
Asdrubal	Cabrera	40.79%	1547	No
Craig	Tatum	40.78%	434	No
Scott	Podsednik	40.78%	2283	No
Jason	Bartlett	40.76%	2024	No
Ronny	Paulino	40.76%	1288	No
Buster	Posey	40.74%	1706	No
Michael	Brantley	40.73%	1311	No
Ryan	Spilborghs	40.71%	1523	No
Gregor	Blanco	40.70%	1081	No
Alex	Gonzalez	40.58%	2319	No
Jason	Bay	40.57%	1521	No
Nick	Stavinoha	40.56%	429	No
Aaron	Cunningham	40.53%	486	No
Wes	Helms	40.51%	1212	No
Juan	Pierre	40.51%	2723	No
Mike	Cameron	40.50%	684	No
J.J.	Hardy	40.49%	1482	No
Kevin	Kouzmanoff	40.48%	1969	No
Jonathan	Herrera	40.44%	1041	No
Cody	Ross	40.44%	2238	No
Carlos	Ruiz	40.42%	1806	No
Adam	Rosales	40.40%	995	No
Alberto	Gonzalez	40.40%	703	No
Gerald	Laird	40.31%	1084	No
Magglio	Ordonez	40.30%	1320	No
Josh	Wilson	40.25%	1441	No
Luis	Valbuena	40.24%	1250	No
Andy	Marte	40.24%	758	No
Chris	Iannetta	40.23%	952	No
Ryan	Hanigan	40.22%	982	No
Darnell	McDonald	40.22%	1380	No
Nick	Punto	40.21%	1144	No
Mark	Grudzielanek	40.18%	448	No
Brendan	Ryan	40.12%	1797	No
Brett	Gardner	40.08%	2617	No
Adam	Moore	40.07%	801	No
Gaby	Sanchez	40.07%	2423	No
Yadier	Molina	40.05%	1890	No
David	Freese	40.02%	1022	No
Ronny	Cedeno	40.01%	1932	No
Ramon	Hernandez	40.00%	1280	No
Gordon	Beckham	39.98%	1801	No
Chris	Denorfia	39.97%	1231	No
Adam	Everett	39.94%	338	No
Melvin	Mora	39.91%	1383	No
Max	Ramirez	39.89%	351	No
Bill	Hall	39.87%	1565	No
Matt	Diaz	39.86%	838	No
Ronnie	Belliard	39.81%	731	No
Tony	Abreu	39.78%	729	No
Erick	Aybar	39.76%	2032	No
Jose	Lopez	39.74%	2114	No
Jason	Bourgeois	39.71%	549	No
Orlando	Cabrera	39.70%	1791	No
Jerry	Hairston	39.68%	1797	No
Pedro	Feliz	39.66%	1402	No
Mark	DeRosa	39.64%	391	No
Nick	Hundley	39.60%	1149	No
Alexi	Casilla	39.58%	614	No
Bengie	Molina	39.54%	1449	No
Yunel	Escobar	39.49%	1932	No
Alcides	Escobar	39.46%	2101	No
Drew	Stubbs	39.45%	2337	No
Russell	Martin	39.44%	1463	No
Jayson	Werth	39.43%	2830	No
Paul	Konerko	39.42%	2542	No
Ryan	Ludwick	39.42%	2164	No
Cliff	Pennington	39.41%	2286	No
Mike	Napoli	39.36%	2078	No
Rickie	Weeks	39.35%	2948	No
Orlando	Hudson	39.34%	2102	No
Derek	Jeter	39.32%	2706	No
Gabe	Kapler	39.26%	591	No
A.J.	Ellis	39.24%	502	No
Jason	Michaels	39.22%	770	No
Oscar	Salazar	39.21%	607	No
Troy	Glaus	39.16%	1910	No
Rusty	Ryal	39.16%	835	No
Miguel	Tejada	39.12%	2285	No
Rafael	Furcal	39.11%	1685	No
Ian	Kinsler	39.11%	1749	No
Scott	Hairston	39.07%	1336	No
Xavier	Nady	39.05%	1306	No
Chris	Snyder	39.02%	1594	No
Alberto	Callaspo	39.02%	2040	No
Trevor	Crowe	39.01%	1784	No
Brett	Hayes	39.00%	300	No
Cesar	Izturis	38.85%	1668	No
Daric	Barton	38.84%	2997	No
Jose	Guillen	38.76%	2201	No
Chris	Young	38.73%	2778	No
Aaron	Rowand	38.73%	1255	No
Tony	Gwynn	38.69%	1326	No
Miguel	Cairo	38.69%	822	No
Ian	Desmond	38.65%	2005	No
Andres	Blanco	38.60%	614	No
Ryan	Raburn	38.48%	1593	No
Ramiro	Pena	38.47%	616	No
Jorge	Cantu	38.47%	2007	No
Dewayne	Wise	38.46%	416	No
Marlon	Byrd	38.44%	2237	No
Jeff	Baker	38.43%	869	No
Michael	Cuddyer	38.43%	2480	No
Andy	LaRoche	38.38%	1003	No
Casey	McGehee	38.37%	2489	No
Edwin	Encarnacion	38.36%	1405	No
Franklin	Gutierrez	38.33%	2640	No
Corey	Hart	38.32%	2354	No
Dexter	Fowler	38.31%	2041	No
Alexei	Ramirez	38.28%	2223	No
Josh	Willingham	38.27%	1879	No
Augie	Ojeda	38.25%	332	No
Mike	Sweeney	38.23%	586	No
Alex	Rios	38.22%	2224	No
Ramon	Santiago	38.22%	1345	No
Yorvit	Torrealba	38.21%	1387	No
Matt	Kemp	38.20%	2623	No
Fred	Lewis	38.16%	1858	No
Derrek	Lee	38.16%	2639	No
Eli	Whiteside	38.12%	543	No
Anderson	Hernandez	38.12%	467	No
Matt	Downs	38.06%	423	No
Omar	Vizquel	38.04%	1509	No
Clint	Barmes	38.00%	1571	No
Yuniesky	Betancourt	37.96%	1860	No
Brandon	Phillips	37.93%	2481	No
J.D.	Drew	37.93%	2220	No
Rod	Barajas	37.86%	1157	No
Carlos	Quentin	37.85%	1873	No
Ryan	Sweeney	37.84%	1308	No
Felipe	Lopez	37.77%	1689	No
Troy	Tulowitzki	37.77%	1909	No
Scott	Rolen	37.77%	2142	No
Coco	Crisp	37.74%	1219	No
Aramis	Ramirez	37.73%	1948	No
Mark	Kotsay	37.72%	1368	No
Dan	Uggla	37.72%	2821	No
Milton	Bradley	37.69%	1101	No
Jason	Varitek	37.61%	468	No
Joe	Mauer	37.61%	2247	No
David	DeJesus	37.57%	1549	No
Evan	Longoria	37.51%	2567	No
Vernon	Wells	37.50%	2088	No
Julio	Borbon	37.50%	1560	No
Justin	Upton	37.48%	2385	No
Nate	McLouth	37.48%	1190	No
Nyjer	Morgan	37.47%	2191	No
Ryan	Zimmerman	37.47%	2410	No
Billy	Butler	37.46%	2544	No
Cameron	Maybin	37.44%	1282	No
Everth	Cabrera	37.41%	882	No
Casey	Kotchman	37.41%	1799	No
Xavier	Paul	37.40%	500	No
Michael	Bourn	37.39%	2423	No
Aaron	Miles	37.38%	503	No
Juan	Uribe	37.35%	2051	No
Maicer	Izturis	37.34%	924	No
Jose	Bautista	37.33%	2869	No
Miguel	Olivo	37.23%	1566	No
Brayan	Pena	37.22%	634	No
Chris	Getz	37.18%	952	No
Alex	Gordon	37.18%	1127	No
Carlos	Lee	37.13%	2203	No
Lastings	Milledge	37.12%	1479	No
Torii	Hunter	37.12%	2511	No
Matt	LaPorta	37.11%	1622	No
Laynce	Nix	37.10%	601	No
Luis	Castillo	37.06%	1190	No
Hunter	Pence	37.05%	2397	No
Manny	Ramirez	37.04%	1277	No
Willy	Aybar	37.01%	1232	No
Kila	Ka'aihue	37.01%	862	No
Ivan	Rodriguez	37.00%	1454	No
Nelson	Cruz	36.93%	1703	No
Matt	Tolbert	36.93%	352	No
Conor	Jackson	36.87%	933	No
Jhonny	Peralta	36.83%	2414	No
Todd	Helton	36.82%	2048	No
Stephen	Drew	36.81%	2502	No
Victor	Martinez	36.80%	2076	No
Craig	Counsell	36.79%	897	No
Corey	Patterson	36.79%	1120	No
Shin-Soo	Choo	36.78%	2518	No
Nolan	Reimold	36.77%	514	No
Delmon	Young	36.76%	1972	No
Skip	Schumaker	36.75%	1929	No
Adrian	Beltre	36.75%	2392	No
Geoff	Blum	36.73%	814	No
Mitch	Maier	36.73%	1669	No
Mark	Reynolds	36.71%	2563	No
Josh	Bard	36.67%	450	No
Emilio	Bonifacio	36.66%	821	No
Jorge	Posada	36.66%	1803	No
Alex	Avila	36.65%	1326	No
Carlos	Gomez	36.63%	1133	No
Marcus	Thames	36.62%	912	No
Hideki	Matsui	36.61%	2256	No
Ryan	Braun	36.59%	2539	No
Bobby	Abreu	36.58%	2840	No
Shelley	Duncan	36.54%	1018	No
Brian	Schneider	36.54%	561	No
Josh	Thole	36.54%	873	No
David	Wright	36.52%	2640	No
Nick	Markakis	36.51%	2821	No
Eric	Chavez	36.48%	466	No
Chris	Johnson	36.43%	1304	No
Shane	Victorino	36.34%	2372	No
Felix	Pie	36.33%	1035	No
Adam	LaRoche	36.32%	2448	No
Jeremy	Hermida	36.32%	939	No
Randy	Winn	36.31%	895	No
Adam	Jones	36.31%	2253	No
Alex	Rodriguez	36.27%	2338	No
Jack	Cust	36.18%	1755	No
Chris	Coghlan	36.18%	1603	No
Mark	Teahen	36.12%	1066	No
Joe	Inglett	36.10%	615	No
Andruw	Jones	36.08%	1361	No
Ken	Griffey	36.05%	430	No
Brian	Roberts	36.04%	1060	No
Carl	Crawford	36.02%	2482	No
Brooks	Conrad	36.01%	711	No
Jeff	Francoeur	35.98%	1779	No
Tyler	Greene	35.94%	434	No
John	Jaso	35.94%	1661	No
Nick	Swisher	35.91%	2545	No
Russell	Branyan	35.90%	1724	No
Chris	Dickerson	35.90%	429	No
Juan	Rivera	35.84%	1638	No
Ryan	Langerhans	35.84%	586	No
John	Buck	35.81%	1614	No
Humberto	Quintero	35.77%	942	No
Angel	Pagan	35.76%	2332	No
Adam	Kennedy	35.74%	1564	No
Willie	Harris	35.69%	1090	No
Johnny	Damon	35.68%	2511	No
Gabe	Gross	35.66%	959	No
A.J.	Pierzynski	35.65%	1596	No
Raul	Ibanez	35.57%	2533	No
Don	Kelly	35.54%	937	No
Ben	Zobrist	35.50%	2687	No
Jimmy	Rollins	35.50%	1462	No
Travis	Snider	35.47%	1201	No
Miguel	Montero	35.44%	1329	No
Roger	Bernadina	35.43%	1781	No
Jason	Jaramillo	35.36%	362	No
Seth	Smith	35.29%	1564	No
Andre	Ethier	35.29%	2196	No
Akinori	Iwamura	35.28%	890	No
Carlos	Guillen	35.26%	1021	No
Neil	Walker	35.25%	1790	No
Blake	DeWitt	35.23%	1842	No
Michael	Saunders	35.21%	1366	No
Andres	Torres	35.21%	2312	No
Lance	Berkman	35.20%	1909	No
Mike	Morse	35.14%	1070	No
Carlos	Gonzalez	35.13%	2266	No
Adam	Lind	35.06%	2319	No
Wilson	Betemit	35.05%	1304	No
Garret	Anderson	35.03%	588	No
Lyle	Overbay	35.01%	2359	No
Chase	Headley	34.99%	2638	No
Albert	Pujols	34.85%	2783	No
Matt	Holliday	34.85%	2565	No
Jonny	Gomes	34.78%	2001	No
Grady	Sizemore	34.75%	564	No
Jake	Fox	34.70%	709	No
Ichiro	Suzuki	34.69%	2724	No
Kendry	Morales	34.63%	800	No
Jason	Kubel	34.61%	2317	No
Kazuo	Matsui	34.56%	327	No
Jim	Edmonds	34.52%	1043	No
Carlos	Pena	34.51%	2286	No
Gregg	Zaun	34.48%	464	No
Rick	Ankiel	34.48%	931	No
Alex	Cora	34.48%	728	No
Cristian	Guzman	34.39%	1355	No
Mike	Fontenot	34.37%	1001	No
Jeff	Clement	34.36%	582	No
Jose	Reyes	34.34%	2216	No
Curtis	Granderson	34.29%	2164	No
Kelly	Johnson	34.24%	2757	No
Will	Venable	34.20%	1798	No
Hanley	Ramirez	34.18%	2285	No
George	Kottaras	34.16%	1013	No
David	Murphy	34.06%	1885	No
James	Loney	34.06%	2484	No
Eric	Hinske	33.99%	1268	No
Brad	Hawpe	33.99%	1430	No
Travis	Hafner	33.95%	1897	No
Landon	Powell	33.94%	495	No
Nick	Johnson	33.81%	420	No
John	Bowker	33.79%	651	No
Aubrey	Huff	33.72%	2556	No
Ian	Stewart	33.71%	1774	No
Kosuke	Fukudome	33.64%	1745	No
Matt	Wieters	33.64%	1974	No
Koyie	Hill	33.58%	816	No
Ryan	Doumit	33.57%	1716	No
Chipper	Jones	33.56%	1445	No
Dioner	Navarro	33.47%	502	No
Jim	Thome	33.43%	1421	No
Delwyn	Young	33.42%	796	No
Ryan	Church	33.33%	903	No
Justin	Maxwell	33.33%	579	No
Chris	Davis	33.27%	514	No
Joey	Votto	33.20%	2536	No
Scott	Moore	32.93%	334	No
Greg	Dobbs	32.93%	665	No
Matt	Joyce	32.91%	1091	No
Adam	Dunn	32.87%	2656	No
David	Ortiz	32.79%	2638	No
Matt	Stairs	32.77%	473	No
Jay	Bruce	32.76%	2134	No
Tyler	Colvin	32.75%	1435	No
Adam	Wainwright	32.69%	361	No
Mark	Teixeira	32.56%	2807	No
Dan	Johnson	32.54%	590	No
Adrian	Gonzalez	32.51%	2642	No
Reid	Brignac	32.42%	1274	No
Chase	Utley	32.32%	2033	No
Carlos	Beltran	32.22%	1015	No
Luke	Scott	32.14%	1991	No
Ross	Gload	31.95%	507	No
Colby	Rasmus	31.95%	2147	No
Josh	Hamilton	31.95%	2069	No
Jason	Giambi	31.93%	877	No
Nate	Schierholtz	31.90%	975	No
Robinson	Cano	31.90%	2414	No
Melky	Cabrera	31.84%	1903	No
Gerardo	Parra	31.84%	1382	No
Alfonso	Soriano	31.70%	2104	No
Travis	Ishikawa	31.67%	600	No
Brian	McCann	31.64%	2250	No
Miguel	Cabrera	31.52%	2367	No
Ryan	Howard	31.44%	2414	No
Garrett	Jones	31.34%	2578	No
Prince	Fielder	30.95%	2759	No
Vladimir	Guerrero	30.87%	2002	No
Kyle	Blanks	30.78%	510	No
John	Baker	30.77%	338	No
Justin	Morneau	30.31%	1356	No
Chad	Tracy	29.94%	628	No
Pablo	Sandoval	28.82%	2099	No

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TangoTiger1

4/08

Great job!

Reply to TangoTiger1

bmmillsy

Thanks, Tango. Appreciate the comment.

A quick note: While Pitchers remain in the table at the bottom, I DO remove pitchers from the original analysis in the article.

I did it with them in as well, but it didn't really change anything (given the 'non-pitcher' result, this should be expected, as I doubt the pitching approach to batting pitchers is really going to change: just let them make the out).

Reply to bmmillsy

lichtman

4/09

"In the end, it seems that once a player hits the majors, the book is out on him. Certainly there could be cases where batters suddenly stop getting pitches grooved down the middle, but in general it's not happening often enough to show up in the data. As a whole, each player tends to see a similar approach throughout the entire season, rather than a suddenâ€”or even gradualâ€”in season adjustment to the swinging tendencies."

Good work!

Let's be careful about these generalized conclusions! You are looking at only a coarse and specific "approach" by pitchers - namely pitch location distribution and even then only as measured front he center of the plate or in and out of the zone. There are all other kinds of "approaches" that may change against rookies as the season goes on. The one you typically hear about is the percentage of fastballs or off-speed pitches thrown. Even then, one would have to be careful about lumping everyone together as if one group of players were thrown more off-speed as the season goes on and another group were thrown more fastballs, overall, the percentages would not change, as one would offset the other. Same thing actually with your study. What if as the season went on, some rookies were thrown more strikes and others were thrown less, depending on their perceived strengths and weaknesses?

Reply to lichtman

Hey MGL,

Thanks for the comments. I agree with all of your points. I was hoping to go a bit further later on and look at individual player trajectories. And I generally look at location, rather than pitch selection here. There are absolutely more things to look at. One of the reasons I have focused on location is that I don't have pitch types clustered throughout the data outside of the Gameday stuff.

I am hoping to get into looking more specifically at individual player trajectories and rather than 'grooving it' vs. 'not grooving it', look more specifically at changes in average location (inside-to-outside, up-to-down). Going through each player that way is a pretty big project.

rawagman

Very interesting article, Brian. Reading it, like MGL, I was thinking that, if anything, the rookies would be treated more like weaker hitters in that the opposing pitchers would be trying to blow the ball by them, location be damned. Pitchers seem to have a limited numbers of breaking balls in them, and they want to save those for the bigger threats. I would be very interested in seeing this study repeated for pitch type instead of location (easier to control for that than the variable of a pitcher missing his spots, right?)

Reply to rawagman

BurrRutledge

4/10

This is very neat stuff. Like MGL, I think you'd have to look on an individual player-by-player basis. And also pitch type. When the pitchers figure out Rookie X taps curve balls to the shortstop, he's going to get a lot of sliders - but the pitch location may not necessarily change.

But, as you show, on a whole there is not a distinguishing difference in pitch location for rookies vs. established players.

Thanks for publishing this here!

Reply to BurrRutledge

"he's going to get a lot of curve balls

Thanks for the comments! Definitely think there's added value in looking player by player, and certainly at pitch types. Hoping to check these things out in the near future. Definitely other angles to take at the 'approach to rookies' question.

Baseball ProGUESTus: The Rookie Effect

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