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Thread: Digging Deep into Plate Discipline and Unlocking a Secret to Hitting

  1. #16
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    Re: Digging Deep into Plate Discipline and Unlocking a Secret to Hitting

    Fabulous work, Cyclone.

    It would be an interesting analysis to see if players "learn" plate discipline over time. Can they really get noticably better at this?

    Another interesting look would be at a guy like Vlad, who is known to swing at everything.

    I cannot say enough what an interesting read that was. Thank you Cyclone for taking the time.


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  3. #17
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    Re: Digging Deep into Plate Discipline and Unlocking a Secret to Hitting

    It seems to be such a simple concept, but few seem to grasp just how important the strike zone really is. It’s a 17 x 30-inch vertical space on a baseball field, and occupies only 510 square inches, but its magnitude of importance generally determines who wins and who doesn’t.
    Isn't the size of the strike zone dependent on the height/stance of the batter?

    What am I missing?

    BTW, that was a great post. Tried to rep you but says I have to spread it around. The other day I tried giving rep points to someone I hadn't repped since early November! Maybe there should be a time limit built into this system as well.
    "Enjoy this Reds fans, you are watching a legend grow up before your very eyes" ... DoogMinAmo on Adam Dunn

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    Re: Digging Deep into Plate Discipline and Unlocking a Secret to Hitting

    Here's slugging percentage by count to try to see what the progression was like, as oneupper suggested ...

    Code:
    
    SLG By Count
    Player              0-2   1-2   2-2   3-2
    
    Barry Bonds        .297  .334  .458  .509
    Albert Pujols      .348  .443  .482  .630
    Alex Rodriguez     .352  .373  .401  .464
    Frank Thomas       .353  .368  .361  .452
    Jeff Bagwell       .277  .369  .383  .461
    
    Adam Dunn          .267  .202  .326  .406
    Sean Casey         .358  .340  .318  .368
    Austin Kearns      .258  .152  .213  .390
    Wily Mo Pena       .130  .200  .333  .255
    Ken Griffey, Jr    .317  .340  .409  .465
    Felipe Lopez       .217  .291  .221  .552
    Ryan Freel         .159  .302  .249  .376
    Scott Hatteberg    .223  .257  .264  .367
    Edwin Encarnacion  .235  .138  .216  .464
    Tony Womack        .238  .239  .265  .356
    Rich Aurilia       .444  .155  .357  .436
    Jason LaRue        .141  .272  .252  .340
    Javier Valentin    .232  .178  .397  .377
    Sample size is a major problem here, as some hitters have only a handful of plate appearances with specific counts. After a rough look at those figures, the discrepancy between slugging percentage at 3-2 counts vs. 0-2/1-2/2-2 counts may not be as large as I originally believed. I'm going to see if I can pile up some league or even team data, something at least with a much larger sample size to try to gain a better indicator what the upward trend in slugging percentage looks like as a hitter progresses 0-2 ---> 3-2.

    Below are some of the same charts as in the first post, but with slugging percentage included ...

    Code:
    
    Teams             HCPA     SLG    OPS    Total PA    HCPA %
    
    San Diego         2405    .454   .920      6271     38.351%
    New York (A)      2455    .528  1.020      6406     38.323%
    Philadelphia      2426    .481   .966      6345     38.235%
    Boston            2403    .527  1.023      6403     37.529%
    Cincinnati        2344    .567  1.055      6321     37.083%
    Arizona           2335    .527  1.009      6327     36.905%
    Los Angeles (N)   2233    .451   .913      6134     36.404%
    Texas             2277    .583  1.054      6301     36.137%
    Oakland           2247    .496   .960      6275     35.809%
    Toronto           2224    .501   .963      6233     35.681%
    Atlanta           2207    .573  1.060      6186     35.677%
    Cleveland         2225    .556  1.032      6255     35.572%
    Seattle           2162    .500   .954      6095     35.472%
    ----------------------------------------------------
    Milwaukee         2143    .531  1.017      6156     34.812%
    Los Angeles (A)   2126    .494   .952      6186     34.368%
    Minnesota         2120    .486   .953      6192     34.238%
    Baltimore         2090    .542   .993      6134     34.072%
    New York (N)      2087    .532  1.006      6146     33.957%
    St. Louis         2115    .515   .999      6246     33.862%
    Colorado          2110    .523  1.011      6238     33.825%
    Washington        2073    .475   .946      6142     33.751%
    San Francisco     2020    .466   .917      6077     33.240%
    Chicago (N)       2031    .526   .982      6161     32.965%
    Tampa Bay         2016    .485   .937      6120     32.941%
    Pittsburgh        2049    .503   .979      6221     32.937%
    Florida           2041    .455   .928      6214     32.845%
    Houston           2005    .505   .982      6139     32.660%
    Chicago (A)       2006    .483   .930      6146     32.639%
    Detroit           1970    .519   .962      6136     32.106%
    Kansas City       1948    .474   .931      6086     32.008%
    			
    League           64893    .509   .979    186292     34.834%
    
    Code:
    
    Player            HCPA     SLG    OPS    Total PA    HCPA %  HCPA+
    
    Barry Bonds       5276    .715  1.287     10519     50.157%   144
    Albert Pujols     1404    .726  1.283      3427     40.969%   118
    Frank Thomas      4304    .653  1.198      8602     50.035%   144
    Alex Rodriguez    2718    .677  1.200      7084     38.368%   110
    Jeff Bagwell      4161    .632  1.174      9428     44.134%   127
    Code:
    
    Player            HCPA     SLG    OPS    Total PA    HCPA %  HCPA+
    
    Adam Dunn         1244    .629  1.186      2782     44.716%   128
    Scott Hatteberg   1674    .512  1.003      3847     43.514%   125
    Austin Kearns      609    .555  1.061      1467     41.513%   119
    Edwin Encarnacion   95    .603  1.034       234     40.598%   117
    Ken Griffey, Jr   3573    .645  1.132      9053     39.468%   113
    Ryan Freel         446    .384   .882      1187     37.574%   108
    Rich Aurilia*      173    .523   .991       467     37.045%   106
    Sean Casey        1627    .543  1.030      4490     36.236%   104
    Felipe Lopez       588    .577  1.065      1663     35.358%   102
    Javier Valentin    364    .505   .961      1049     34.700%   100
    Jason LaRue        729    .513   .961      2303     31.654%    91
    Wily Mo Pena       268    .516   .942       897     29.877%    86
    Tony Womack       1556    .432   .881      5256     29.604%    85
    
    * Due to site errors, I only had access to Aurilia's 2005 splits
    Code:
    
    Team              PCPA     SLG    OPS    Total PA    PCPA %
    
    New York (A)      1802    .364   .616      6406     28.130%
    Boston            1832    .351   .594      6403     28.612%
    San Diego         1826    .305   .527      6271     29.118%
    Cleveland         1844    .358   .586      6255     29.480%
    Atlanta           1828    .308   .511      6186     29.551%
    Cincinnati        1882    .322   .537      6321     29.774%
    Philadelphia      1902    .331   .561      6345     29.976%
    Texas Rangers     1894    .342   .564      6301     30.059%
    Arizona           1909    .296   .514      6327     30.172%
    Los Angeles (N)   1851    .297   .511      6134     30.176%
    San Francisco     1851    .283   .490      6077     30.459%
    Oakland           1917    .323   .548      6275     30.550%
    Seattle           1877    .295   .518      6095     30.796%
    Los Angeles (A)   1914    .315   .547      6186     30.941%
    ----------------------------------------------------
    Milwaukee         1914    .307   .515      6156     31.092%
    Houston           1910    .308   .517      6139     31.113%
    St. Louis         1949    .337   .580      6246     31.204%
    Toronto           1950    .333   .569      6233     31.285%
    Chicago (N)       1933    .347   .573      6161     31.375%
    Baltimore         1938    .335   .575      6134     31.594%
    Colorado          1978    .303   .527      6238     31.709%
    Minnesota         1969    .333   .564      6192     31.799%
    Chicago (A)       1966    .327   .549      6146     31.988%
    Washington        1980    .305   .529      6142     32.237%
    New York (N)      1987    .304   .512      6146     32.330%
    Kansas City       1994    .311   .529      6086     32.764%
    Pittsburgh        2039    .302   .522      6221     32.776%
    Tampa Bay         2007    .343   .584      6120     32.794%
    Florida           2047    .328   .575      6214     32.942%
    Detroit           2048    .337   .569      6136     33.377%
    			
    League           57738    .322   .547    186292     30.993%
    
    Code:
    
    Player            PCPA     SLG    OPS    Total PA    PCPA %  PCPA+
    
    Barry Bonds       1839    .455   .703     10519     17.483%   177
    Frank Thomas      1653    .434   .694      8602     19.216%   161
    Jeff Bagwell      2211    .418   .670      9428     23.451%   132
    Albert Pujols      902    .503   .785      3427     26.291%   118
    Alex Rodriguez    2078    .466   .738      7084     29.334%   106
    Code:
    
    Player            PCPA     SLG    OPS    Total PA    PCPA %  PCPA+
    
    Adam Dunn          661    .304   .481      2782     23.760%   130
    Austin Kearns      356    .291   .490      1467     24.267%   128
    Ken Griffey, Jr   2292    .444   .692      9053     25.318%   122
    Scott Hatteberg    987    .288   .520      3847     25.656%   121
    Rich Aurilia*      120    .358   .583       467     25.696%   121
    Edwin Encarnacion   62    .274   .468       234     26.496%   117
    Ryan Freel         324    .330   .593      1187     27.296%   114
    Javier Valentin    298    .248   .406      1049     28.408%   110
    Sean Casey        1339    .396   .675      4490     29.822%   104
    Jason LaRue        738    .318   .538      2303     32.045%    97
    Wily Mo Pena       294    .266   .419       897     32.776%    95
    Felipe Lopez       548    .306   .512      1663     32.952%    94
    Tony Womack       1961    .280   .502      5256     37.310%    83
    
    * Due to site errors, I only had access to Aurilia's 2005 splits
    The Lost Decade Average Season: 74-88
    2014-22 Average Season: 71-91

  5. #19
    Mailing it in Cyclone792's Avatar
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    Re: Digging Deep into Plate Discipline and Unlocking a Secret to Hitting

    Quote Originally Posted by TeamBoone
    Isn't the size of the strike zone dependent on the height/stance of the batter?

    What am I missing?

    BTW, that was a great post. Tried to rep you but says I have to spread it around. The other day I tried giving rep points to someone I hadn't repped since early November! Maybe there should be a time limit built into this system as well.
    Thanks, TB. The strike zone is dependent on the height of the batter so those numbers probably resemble an average zone, not the zone for every hitter.

    Here's some interesting tidbits on how QuestTec ops determine the height of the zone ...

    http://www.edn.com/article/CA324410.html

    The QuesTec system doesn't know whether a pitch is a ball or a strike until after the game. It uses the fixed dimensions of home plate to determine whether a pitch is inside or outside, but determining whether a ball high or low is a bit more involved and requires the operator to supply the system with some crucial information. At the end of the game, the operator uses images of each batter in his stance—taken when the first pitch to each batter is approximately halfway to home plate—to assist the system in determining individual strike zones. With a few mouse clicks, the operator manually sets electronic lines indicating the bottom and the middle of the strike zone at the hollow of the batter's back knee and belt, respectively. The system then automatically calculates the top of the strike zone, marking a third electronic line at a distance of two-and-half baseballs above the batter's belt. The system calls any ball a strike if the ball passes over the plate within these vertical limits, and if the batter doesn't swing at it or hit it or the catcher doesn't drop it.
    The Lost Decade Average Season: 74-88
    2014-22 Average Season: 71-91

  6. #20
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    Re: Digging Deep into Plate Discipline and Unlocking a Secret to Hitting

    Cyclone, this is just amazing work on your part.

    On the downside, it kinda sucks that it's February and we probably just saw the post of the year.
    I'm not a system player. I am a system.

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    Re: Digging Deep into Plate Discipline and Unlocking a Secret to Hitting

    Quote Originally Posted by buckeyenut
    Fabulous work, Cyclone.

    It would be an interesting analysis to see if players "learn" plate discipline over time. Can they really get noticably better at this?

    Another interesting look would be at a guy like Vlad, who is known to swing at everything.

    I cannot say enough what an interesting read that was. Thank you Cyclone for taking the time.
    Thanks, buckeye. TangoTiger's got some interesting stuff up on aging patterns.

    http://www.tangotiger.net/agepatterns.txt

    Anyway, hitters always improve their walk ratio, they strikeout the least at age 29, get their best HR ratio at age 27, their balls in play success goes down almost instantly, their line drive power stays pretty flat for a long period of time, their speed as measured by triples goes down instantly, their speed as measured by SB peaks at 24 and goes down almost at the same rate as the triples.
    The key would be determining how much walk rate correlates with also getting into hitter counts/avoiding pitcher counts. My gut tells me there's at least some decent correlation, if not a strong one, but I have no idea if the actual data would back up that guess. Another way to examine whether it increases with age along with BB rate is to examine season-by-season data for guys such as Bonds, Thomas, Griffey and other hitters who have played for several years and that we have several years worth of hitting by count data for.
    The Lost Decade Average Season: 74-88
    2014-22 Average Season: 71-91

  8. #22
    Mailing it in Cyclone792's Avatar
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    Re: Digging Deep into Plate Discipline and Unlocking a Secret to Hitting

    Quote Originally Posted by M2
    Cyclone, this is just amazing work on your part.

    On the downside, it kinda sucks that it's February and we probably just saw the post of the year.
    Thanks, M2! I've been trying to dig through some data and take a look at some stuff from some different angles. We all know hitters perform better when the count is more favorable, but I've never seen anybody actually measure how often different hitters can make the count more favorable.

    Part of me believes that type of information could be critically helpful in analyzing minor league and college stats to help see the progression prospects make in terms of plate discipline as they climb the ladder of minor league ranks. It's unfortunate that I've never seen stats by count for minor leaguers or college players, and I'm actually curious if the Reds front office tracks such a thing (if they don't, my first question would be why not?).
    The Lost Decade Average Season: 74-88
    2014-22 Average Season: 71-91

  9. #23
    Danger is my business! oneupper's Avatar
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    Re: Digging Deep into Plate Discipline and Unlocking a Secret to Hitting

    I'll borrow the conclusions of Cyclone's work to promote an obsession of mine: the need to develop an automated strike zone.

    Balls and Strikes are WAY too important to be left in the hands of human beings!
    "A person is smart. People are dumb, panicky, dangerous animals and you know it."

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    Re: Digging Deep into Plate Discipline and Unlocking a Secret to Hitting

    Fantastic post. Thanks a lot for the amount of work you put into this.

    Regarding hitting in a two strike count, ALL hitters have had it drilled into them since the beginning of time to protect the plate with two strikes. Even if they look like they haven't changed their approach, they have, mentally.

    Really outstanding work.

    We'll go down in history as the first society that wouldn't save itself because it wasn't cost effective ~ Kurt Vonnegut

  11. #25
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    Re: Digging Deep into Plate Discipline and Unlocking a Secret to Hitting

    My favorite visual aid

    Not talking about pitch count, but rather strike zone management



    We'll go down in history as the first society that wouldn't save itself because it wasn't cost effective ~ Kurt Vonnegut

  12. #26
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    Re: Digging Deep into Plate Discipline and Unlocking a Secret to Hitting

    Great stuff,

    BTW Aurilia in 2004 0-2 (.100/.156/.133/.289 - 30 Ab's ) 1-2 (.111/.128/.178/.306 45 ab's) 3-2( .194/.324/.237/.561 93 ab's) 3-2 (.195/.459/.244/.703 41 ab's)

  13. #27
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    Re: Digging Deep into Plate Discipline and Unlocking a Secret to Hitting

    Very nice work Cyclone. How about throwing in a comparison between your Magic 5 and some weaker hitters that walk a lot. Maybe Mark Bellhorn...Brad Wilkerson? I think the numbers would tend to skew slightly, as the more feared hitters in your big 5 get pitched around more often.

  14. #28
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    Re: Digging Deep into Plate Discipline and Unlocking a Secret to Hitting

    Quote Originally Posted by Cyclone792
    It’s a 17 x 30-inch vertical space on a baseball field, and occupies only 510 square inches, but its magnitude of importance generally determines who wins and who doesn’t.
    Not that the umps use it, but isn't the strike zone a three-dimensional space?

    1988 - "The Strike Zone is that area over home plate the upper limit of which is a horizontal line at the midpoint between the top of the shoulders and the top of the uniform pants, and the lower level is a line at the top of the knees. The Strike Zone shall be determined from the batter's stance as the batter is prepared to swing at a pitched ball."

    1996 - The Strike Zone is expanded on the lower end, moving from the top of the knees to the bottom of the knees.
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  15. #29
    You know his story Redsland's Avatar
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    Re: Digging Deep into Plate Discipline and Unlocking a Secret to Hitting

    Quote Originally Posted by Cyclone792
    *Stolen base percentages in 2005 are higher when the batters are behind in the count: 72.4 percent when behind vs. 68.8 percent when ahead. This suggests that poorer basestealers may be taking some highly unnecessary risks attempting to swipe bags.
    Great thread! I hope I don't screw it up by posting something that's been covered elsewhere, but I've been scarce of late, and I'm having a tough time keeping up (I miss DanO ).

    Anyway, the stat you noted above, rather than being surprising, is exactly what I'd expect from a conservative, by-the-books running philosophy.

    When the batter is behind in the count, the pitcher is more likely to waste a breaking pitch. All things being equal, that's a good time to go. (Pitchouts and strong-armed catchers notwithstanding.) When the batter is ahead, OTOH, you have to look for him to bring the gas, making a CS easier to obtain.

    Again, outstanding work, and I'm sorry if I've gone and Tim McCarver'ed everything.
    Makes all the routine posts.

  16. #30
    Mailing it in Cyclone792's Avatar
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    Re: Digging Deep into Plate Discipline and Unlocking a Secret to Hitting

    Quote Originally Posted by baseballPAP
    Very nice work Cyclone. How about throwing in a comparison between your Magic 5 and some weaker hitters that walk a lot. Maybe Mark Bellhorn...Brad Wilkerson? I think the numbers would tend to skew slightly, as the more feared hitters in your big 5 get pitched around more often.
    Someone else mentioned Guerrero so I decided to compare both groups. I'll throw the Magic Five out against three hitters whose value lies heavily in their walk totals and also against three well-known hacks while at the dish. I'll also include two current players whom I believe are two of the most underrated in the game today, Bobby Abreu and Brian Giles:

    Code:
    
    Player            HCPA     SLG    OPS    Total PA    HCPA %  HCPA+
    
    Barry Bonds       5276    .715  1.287     10519     50.157%   144
    Frank Thomas      4304    .653  1.198      8602     50.035%   144
    Jeff Bagwell      4161    .632  1.174      9428     44.134%   127
    Albert Pujols     1404    .726  1.283      3427     40.969%   118
    Alex Rodriguez    2718    .677  1.200      7084     38.368%   110
    Code:
    
    Player            HCPA     SLG    OPS    Total PA    HCPA %  HCPA+
    
    Brian Giles       2607    .601  1.147      5656     46.093%   132
    Mark Bellhorn      967    .520  1.042      2175     44.460%   128
    Bobby Abreu       2511    .640  1.214      5677     44.231%   127
    Nick Johnson       757    .532  1.067      1761     42.987%   123
    Brad Wilkerson    1106    .586  1.126      2675     41.346%   119
    
    Miguel Tejada     1939    .602  1.059      5380     36.041%   104
    Vladimir Guerrero 1688    .680  1.199      5494     30.724%    88
    Alfonso Soriano    994    .646  1.093      3484     28.530%    82
    Tejada's actually above average in getting himself into a hitting count, which I didn't expect, but there's Guerrero and Soriano down there in Wily Mo territory. Giles, Bellhorn, Abreu, Johnson and Wilkerson all get themselves into hitting counts at a rate/level near that of some of the Magic Five, though not quite at the level of Bonds or Thomas.

    Code:
    
    Player            PCPA     SLG    OPS    Total PA    PCPA %  PCPA+
    
    Barry Bonds       1839    .455   .703     10519     17.483%   177
    Frank Thomas      1653    .434   .694      8602     19.216%   161
    Jeff Bagwell      2211    .418   .670      9428     23.451%   132
    Albert Pujols      902    .503   .785      3427     26.291%   118
    Alex Rodriguez    2078    .466   .738      7084     29.334%   106
    Code:
    
    Player            PCPA     SLG    OPS    Total PA    PCPA %  PCPA+
    
    Brian Giles       1143    .430   .688      5656     20.209%   153
    Bobby Abreu       1437    .403   .645      5677     25.313%   122
    Mark Bellhorn      556    .249   .427      2175     25.563%   121
    Nick Johnson       488    .335   .573      1761     27.712%   112
    Brad Wilkerson     760    .364   .593      2675     28.411%   109
    
    Vladimir Guerrero 1598    .444   .717      5494     29.086%   107
    Miguel Tejada     1761    .372   .615      5380     32.732%    95
    Alfonso Soriano   1321    .381   .618      3484     37.916%    82
    There's good ole Soriano down there in Wily Mo territory again. Guerrero's above average in avoiding being behind in the count, while Tejada's slightly below average. Giles, Abreu, Bellhorn, Johnson and Wilkerson are all up there in Magic Five territory in their rate of reaching a hitting count.
    The Lost Decade Average Season: 74-88
    2014-22 Average Season: 71-91


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