How the Best Pitching Tools Translate to the Majors

Intermittently, over the past month or so, the present author — leaning heavily on historical data from Baseball America — has examined the ways in which prospects distinguished for possessing certain tools as minor-leaguers have ultimately fared at the major-league level. The goal: ideally, to develop a better sense of what does and doesn’t correlate to future success, with a view towards better assessing contemporary prospects.

The first of these posts considered the 2005 “class,” as it were, of best-tool prospects and their respective major-league futures; the second post, that collection of prospects from 2005 to -09 who had been recognized both for their hit tool and plate discipline simultaneously; and the third, that subset of the best-hitting, most-disciplined prospects who had also been recognized for their defensive acumen.

While no immutable conclusions have been reached by means of this brief series, it’s also fair to say that certain themes have presented themselves. Like, for example: prospects with readily apparent hitting and plate-discipline skills are more likely to succeed than other manner of prospects (like those, for example, distinguished for power or speed or athleticism). And like also, for example: prospects who pair those sorts of offensive skills with promising defensive abilities become, almost with exception, above-average major-leaguers — regardless of where they’ve appeared on a top-100 list.

What has been absent from the three aforementioned posts, however, has been any consideration of pitchers — which type of baseball player the reader will immediately recognize as a pretty important type of baseball player. To remedy this oversight, I’ve composed this post, which at least begins to examine the relationship between certain pitcher tools and how they translate to the majors.

Pitcher tools, if I might use technical language for a moment, are a little bit kind of weird. While the tools utilized to describe field-playing prospects generally provide a decent portrait of the player in question, those relevant to pitchers — or, at least those presented in Baseball America’s annual handbook — concern repertoire almost exclusively.

Here they are, as follows:

  • Best Fastball
  • Best Curveball
  • Best Slider
  • Best Changeup
  • Best Control

Four of those five tools are merely different offerings within a pitcher’s repertoire — and two of them, the curve and the slider, exist along a spectrum of similarly shaped pitches. (See conversation regarding Craig Kimbrel‘s breaking ball for some idea of the difficulties inherent to distinguishing between the two.)

Despite the peculiarities or seemingly narrow scope of the commonly used pitching tools, I’m also not sure how one would improve upon them. I’m also not prepared to give the matter much constructive thought at the moment, on account of the priority — in this post, at least — is merely to examine how the tools as presently classified have fared in the majors.

As with the first version of these best-tools posts, what I did was to begin by recording which pitchers from the 2005 edition of BA’s Prospect Handbook were distinguished for possessing the aforementioned traits within their respective organizations.

After assembling that list of all the Best Tool pitchers from each of the 30 organizations, I produced five separate custom leaderboards with the metrics that might be most relevant to assessing the quality of a major leaguer. That information appears below, in a number of forms and accompanied by mediocre commentary.

While, as noted in previous posts, one doesn’t expect talent to have been distributed evenly among every minor-league system — and, accordingly, can’t expect the pitcher with the best fastball in a talent-poor system to match the skills of the pitcher with the best fastball in a talent-rich one — the value of the Best Tool designations is that they function as a reasonable proxy for more sophisticated data that isn’t available publicly.

Below are five leaderboards, each containing the pitchers who (a) were distinguished by Baseball America for possessing one of the five relevant tools named above and (b) also recorded at least a single inning in the majors. Players are sorted by career RA9-WAR to date — i.e. WAR as calculated by means of runs-allowed instead of FIP. Also included are the number of pitchers demonstrating the relevant tool to have graduated to the majors and the number of those pitchers to have recorded at least 5.0 RA9-WAR over the course of their respective career.

Best Fastball
Graduated to Majors: 27
Number Above 5.0 RA9-WAR: 7

Name G GS GS% IP K% BB% GB% FIP- ERA- WAR RA9-WAR
Felix Hernandez 270 270 100.0% 1830.7 22.7% 7.0% 54.0% 79 78 41.4 42.8
Ervin Santana 268 265 98.9% 1686.7 18.6% 7.4% 39.8% 105 100 19.6 22.1
Jonathan Papelbon 529 3 0.6% 562.3 29.0% 6.4% 37.7% 63 57 17.9 18.8
Scott Kazmir 210 209 99.5% 1187.3 22.5% 10.1% 39.2% 97 98 19.0 17.1
Edwin Jackson 266 236 88.7% 1449.3 17.6% 8.9% 44.8% 101 106 17.8 13.3
Homer Bailey 144 144 100.0% 857.3 19.4% 7.6% 43.8% 99 106 10.4 8.0
Santiago Casilla 385 0 0.0% 383.3 20.2% 10.7% 48.1% 101 84 0.9 5.1
Matt Lindstrom 436 0 0.0% 388.7 18.4% 8.5% 48.8% 80 85 4.9 3.5
Chris Ray 283 0 0.0% 281.0 19.1% 10.2% 39.3% 102 94 1.0 2.8
Brandon League 436 0 0.0% 471.0 17.0% 8.0% 59.6% 97 93 1.9 2.0
Anthony Reyes 67 52 77.6% 293.3 16.1% 9.3% 35.9% 118 118 1.0 1.6
Angel Guzman 88 14 15.9% 157.0 20.8% 10.6% 40.3% 100 105 0.9 1.2
Jason Bulger 125 0 0.0% 133.0 24.2% 13.1% 40.5% 104 101 0.2 0.6
Eude Brito 11 7 63.6% 40.3 13.3% 12.7% 39.8% 114 119 0.2 0.2
Sean Tracey 7 0 0.0% 8.0 8.8% 14.7% 32.0% 168 71 -0.1 0.1
Travis Chick 3 0 0.0% 5.0 6.5% 32.3% 47.4% 191 287 -0.1 -0.2
Jose Capellan 99 2 2.0% 123.3 18.1% 9.2% 33.5% 113 110 -0.4 -0.2
J.D. Durbin 23 11 47.8% 72.7 13.4% 12.5% 48.2% 106 135 0.3 -0.4
Thomas Diamond 16 3 18.8% 29.0 26.1% 13.0% 29.1% 119 165 0.0 -0.5
Juan Morillo 9 1 11.1% 10.7 14.3% 12.5% 26.3% 216 287 -0.4 -0.5
Merkin Valdez 74 1 1.4% 72.7 17.6% 12.5% 43.9% 117 134 -0.3 -0.8
Frankie de la Cruz 26 1 3.8% 32.0 12.7% 16.6% 52.3% 136 192 -0.3 -0.9
Ezequiel Astacio 28 14 50.0% 86.7 18.2% 7.8% 37.5% 146 142 -0.9 -0.9
Yorman Bazardo 25 8 32.0% 60.3 13.1% 12.1% 44.8% 109 162 0.2 -1.1
Collin Balester 73 22 30.1% 185.0 17.5% 9.5% 40.1% 133 128 -1.1 -1.1
Anthony Lerew 20 11 55.0% 61.3 13.8% 11.0% 36.1% 170 175 -1.2 -1.1
Denny Bautista 131 21 16.0% 223.3 17.4% 12.7% 44.5% 108 133 0.8 -1.6
Average 150 48 32.0% 396.0 17.6% 11.4% 41.8% 118 128 4.9 4.8

Best Curveball
Graduated to Majors: 23
Number Above 5.0 RA9-WAR: 11

Name G GS GS% IP K% BB% GB% FIP- ERA- WAR RA9-WAR
Justin Verlander 267 267 100.0% 1778.0 22.7% 7.4% 40.1% 79 79 44.2 43.2
Felix Hernandez 270 270 100.0% 1830.7 22.7% 7.0% 54.0% 79 78 41.4 42.8
Matt Cain 267 266 99.6% 1726.0 20.2% 8.2% 37.4% 92 84 28.9 36.2
Adam Wainwright 249 186 74.7% 1321.7 20.9% 6.3% 49.4% 79 78 28.1 30.5
Ubaldo Jimenez 213 212 99.5% 1281.7 21.5% 10.5% 47.4% 88 91 23.5 21.2
John Danks 181 181 100.0% 1109.7 17.8% 7.5% 42.4% 98 95 16.6 17.8
Gio Gonzalez 160 154 96.3% 936.3 22.9% 10.4% 47.0% 92 89 15.0 16.3
Gavin Floyd 199 187 94.0% 1151.3 18.3% 7.9% 44.7% 99 102 15.6 14.0
Jason Hammel 216 159 73.6% 996.0 16.6% 7.9% 45.1% 99 109 12.9 8.0
Homer Bailey 144 144 100.0% 857.3 19.4% 7.6% 43.8% 99 106 10.4 8.0
Bobby Jenks 348 0 0.0% 357.3 23.4% 8.2% 53.6% 71 78 8.1 7.5
Rich Hill 181 70 38.7% 465.7 21.9% 10.9% 35.1% 97 106 5.9 4.2
Manny Delcarmen 298 0 0.0% 292.7 19.5% 10.6% 46.3% 89 87 3.1 3.3
Taylor Buchholz 158 27 17.1% 311.0 17.7% 6.6% 41.9% 95 95 3.1 2.6
Adam Loewen 35 29 82.9% 164.0 17.9% 14.2% 49.3% 106 118 1.7 0.8
Dustin Nippert 119 23 19.3% 268.0 17.6% 11.2% 38.6% 107 116 1.2 0.7
J.D. Martin 24 24 100.0% 125.0 12.3% 6.3% 36.9% 130 105 -0.1 0.6
Charlie Morton 110 109 99.1% 595.3 14.9% 8.8% 54.7% 108 119 4.3 0.4
David Purcey 111 21 18.9% 206.0 18.8% 12.8% 33.9% 108 116 1.1 0.3
Christian Garcia 13 0 0.0% 12.7 31.3% 4.2% 28.6% 96 54 0.1 0.3
J.D. Durbin 23 11 47.8% 72.7 13.4% 12.5% 48.2% 106 135 0.3 -0.4
Ben Hendrickson 14 12 85.7% 58.3 13.2% 10.4% 52.2% 109 169 0.3 -1.0
Denny Bautista 131 21 16.0% 223.3 17.4% 12.7% 44.5% 108 133 0.8 -1.6
Average 162 103 63.6% 701.8 19.2% 9.1% 44.1% 97 102 11.6 11.1

Best Slider
Graduated to Majors: 22
Number Above 5.0 RA9-WAR: 9

Name G GS GS% IP K% BB% GB% FIP- ERA- WAR RA9-WAR
Ervin Santana 268 265 98.9% 1686.2 18.6% 7.4% 39.8% 105 100 19.6 22.1
Jonathan Papelbon 529 3 0.6% 562.1 29.0% 6.4% 37.7% 63 57 17.9 18.8
Chad Billingsley 219 190 86.8% 1175.1 20.6% 9.8% 46.3% 91 92 17.2 18.1
Scott Kazmir 210 209 99.5% 1187.1 22.5% 10.1% 39.2% 97 98 19.0 17.1
Huston Street 516 0 0.0% 533.0 25.3% 6.4% 37.5% 77 70 9.9 12.4
Jesse Crain 532 0 0.0% 532.0 19.8% 9.3% 43.1% 88 70 6.4 10.5
Tom Gorzelanny 236 121 51.3% 820.1 18.2% 9.8% 41.5% 105 105 6.8 6.8
Ramon Ramirez 423 0 0.0% 433.2 19.8% 10.3% 41.6% 89 81 4.6 5.6
Chad Qualls 664 0 0.0% 658.1 18.2% 6.6% 57.8% 91 92 3.8 5.5
Brian Bannister 117 114 97.4% 667.1 13.2% 7.7% 42.3% 109 115 6.8 3.9
Brad Hennessey 148 44 29.7% 360.2 12.0% 9.2% 45.2% 114 108 0.6 2.5
Will Ohman 483 0 0.0% 353.0 21.8% 10.3% 40.7% 98 98 1.4 1.7
Bill Bray 258 0 0.0% 197.1 21.9% 10.3% 37.1% 91 88 1.2 1.6
Scott Olsen 130 127 97.7% 723.0 16.6% 9.2% 40.2% 113 113 3.9 1.5
Jim Miller 48 0 0.0% 64.2 19.9% 12.9% 34.6% 114 69 -0.1 0.9
Dana Eveland 114 61 53.5% 392.2 14.2% 10.7% 50.3% 105 129 3.1 0.0
Chris Oxspring 5 0 0.0% 12.0 22.5% 12.2% 35.5% 124 97 -0.1 -0.2
Travis Hughes 24 0 0.0% 25.2 12.5% 12.5% 46.0% 172 148 -0.7 -0.3
Macay McBride 132 0 0.0% 103.1 20.7% 13.5% 45.0% 88 98 0.9 -0.5
Zack Segovia 9 1 11.1% 15.1 8.6% 10.0% 46.4% 125 190 -0.1 -0.5
Clint Nageotte 16 5 31.3% 41.2 12.3% 14.2% 57.5% 129 176 -0.1 -1.0
Denny Bautista 131 21 16.0% 223.1 17.4% 12.7% 44.5% 108 133 0.8 -1.6
Average 237 53 22.3% 489.2 18.4% 10.1% 43.2% 104 106 5.6 5.7

Best Changeup
Graduated to Majors: 18
Number Above 5.0 RA9-WAR: 4

Name G GS GS% IP K% BB% GB% FIP- ERA- WAR RA9-WAR
Cole Hamels 245 244 99.6% 1596.7 23.2% 6.1% 43.2% 85 82 30.8 35.5
Shaun Marcum 188 161 85.6% 995.0 19.4% 7.3% 38.4% 101 94 13.0 16.5
Jeff Francis 228 216 94.7% 1249.0 15.3% 6.8% 44.7% 95 108 18.1 12.3
Zach Duke 216 169 78.2% 1086.7 11.9% 6.2% 48.9% 102 110 10.1 6.7
Juan Dominguez 32 17 53.1% 109.7 14.9% 8.7% 43.9% 110 98 1.0 1.2
Mike Neu 33 0 0.0% 46.0 10.4% 13.2% 52.9% 111 83 0.0 0.3
Pat Misch 78 24 30.8% 200.7 13.2% 6.5% 44.7% 114 116 0.4 0.2
Cesar Jimenez 62 3 4.8% 65.3 16.5% 10.5% 37.3% 111 121 0.4 0.2
Matt DeSalvo 9 6 66.7% 29.7 7.8% 13.1% 34.5% 125 172 0.1 -0.1
Mike Gosling 58 9 15.5% 117.0 13.4% 13.1% 39.1% 128 108 -0.6 -0.1
Jason Windsor 4 3 75.0% 13.7 9.2% 7.7% 40.4% 119 148 0.1 -0.3
Blake Hawksworth 124 8 6.5% 183.3 15.7% 8.5% 49.6% 116 106 -0.5 -0.3
Abe Alvarez 4 1 25.0% 10.3 9.4% 13.2% 25.0% 224 243 -0.4 -0.4
Mitch Talbot 43 41 95.3% 232.7 12.3% 10.3% 45.8% 124 132 0.5 -0.5
Julio DePaula 16 0 0.0% 20.0 8.1% 10.1% 54.5% 174 192 -0.4 -0.6
Kyle Davies 151 144 95.4% 768.0 15.7% 10.6% 39.1% 112 129 5.3 -1.1
Chad Orvella 69 0 0.0% 82.3 16.3% 13.1% 35.5% 129 132 -0.7 -1.7
Hayden Penn 33 15 45.5% 82.3 12.4% 13.4% 43.9% 153 218 -0.9 -3.5
Average 89 59 66.6% 382.7 13.6% 9.9% 42.3% 124 133 4.2 3.6

Best Control
Graduated to Majors: 24
Number Above 5.0 RA9-WAR: 9

Name G GS GS% IP K% BB% GB% FIP- ERA- WAR RA9-WAR
Cole Hamels 245 244 99.6% 1596.7 23.2% 6.1% 43.2% 85 82 30.8 35.5
Shaun Marcum 188 161 85.6% 995.0 19.4% 7.3% 38.4% 101 94 13.0 16.5
Joe Blanton 265 248 93.6% 1567.3 16.2% 6.1% 44.2% 102 109 18.9 14.5
Jeff Francis 228 216 94.7% 1249.0 15.3% 6.8% 44.7% 95 108 18.1 12.3
Brandon McCarthy 176 122 69.3% 796.0 15.7% 6.3% 41.4% 96 97 11.5 10.5
Tyler Clippard 348 8 2.3% 423.7 27.4% 10.4% 27.6% 95 75 4.4 8.6
Zach Duke 216 169 78.2% 1086.7 11.9% 6.2% 48.9% 102 110 10.1 6.7
Roberto Hernandez 217 178 82.0% 1105.3 14.3% 8.5% 57.7% 110 113 8.5 6.6
John Maine 112 105 93.8% 593.0 19.5% 10.5% 37.7% 111 106 4.5 5.6
Tim Stauffer 141 70 49.6% 513.7 17.2% 7.9% 48.7% 111 105 2.0 4.8
Steven Shell 43 0 0.0% 55.0 20.8% 10.0% 36.7% 97 57 0.2 1.3
Mike Hinckley 28 0 0.0% 23.3 12.9% 15.1% 45.3% 110 46 -0.2 0.8
Yusmeiro Petit 81 44 54.3% 284.0 18.2% 7.3% 31.9% 113 122 1.3 0.6
Brad Thompson 201 32 15.9% 405.3 10.8% 6.9% 51.9% 115 106 -0.8 0.6
Kyle Waldrop 24 0 0.0% 32.3 8.3% 8.3% 72.2% 120 89 -0.3 0.4
Pat Misch 78 24 30.8% 200.7 13.2% 6.5% 44.7% 114 116 0.4 0.2
Bobby Livingston 13 10 76.9% 61.3 10.6% 5.0% 42.6% 113 139 0.5 -0.2
Abe Alvarez 4 1 25.0% 10.3 9.4% 13.2% 25.0% 224 243 -0.4 -0.4
Dusty Hughes 80 1 1.3% 83.0 15.9% 10.6% 37.3% 114 119 -0.2 -0.5
Steve Schmoll 48 0 0.0% 46.7 14.2% 10.7% 44.8% 108 121 -0.2 -0.6
Virgil Vasquez 19 10 52.6% 61.3 12.5% 8.0% 37.4% 140 154 -0.4 -0.7
Ezequiel Astacio 28 14 50.0% 86.7 18.2% 7.8% 37.5% 146 142 -0.9 -0.9
Manny Parra 232 74 31.9% 561.7 21.0% 10.9% 48.0% 102 120 4.1 -1.6
Chad Orvella 69 0 0.0% 82.3 16.3% 13.1% 35.5% 129 132 -0.7 -1.7
Average 129 72 56.1% 496.7 15.9% 8.7% 42.6% 115 113 5.2 5.0

The various sizes of these leaderboards probably help to offer at least an initial idea of the degree to which certain tools have portended major-league success. Among the 30 prospects regarded as possessing the best fastball in 2005, 27 of those have recorded a major-league inning at some point. Meanwhile, despite graduating fewer pitchers to the majors, those prospects distinguished for their curveball have recorded the greatest number of career RA9-WAR marks of 5.0 or above (11, as compared to just seven for pitchers demonstrating their organization’s best fastball). Prospects recognized for their changeup, meanwhile, finished last both in terms of major-league graduates and career RA9-WAR marks over 5.0.

While I’ve included the averages for each group at the bottom of all the leaderboards above, those numbers have limited utility for our concerns here, as they pertain only to those prospects who eventually graduated to the majors. They’re not entirely without use, those figures; however, if our aim is to assess the future production of all the Best Tool prospects, it’s better to find the median figures, instead, for all 30 players named by BA in each tool category.

With that in mind, I’ve included below a table including the median figures (or 15th-best, at least) for several relevant metrics among each tool category — along with career WAR and RA9-WAR figures, as well.

Tool GS% IP K% BB% GB% FIP- ERA- WAR RA9-WAR Tot WAR Tot RA9-WAR
FA 16.0% 133.0 17.6% 10.7% 40.1% 109 118 0.2 0.1 133.6 129.9
CU 47.8% 292.2 17.8% 10.4% 42.4% 99 106 3.1 0.8 266.5 255.7
SL 0.0% 223.1 17.4% 10.3% 40.2% 109 108 0.9 0.9 122.8 124.9
CH 4.8% 29.2 9.4% 13.1% 37.3% 129 172 -0.5 -0.6 76.3 64.3
CO 30.8% 86.2 14.3% 8.5% 38.4% 113 116 0.2 0.4 124.2 118.9

Now, in lieu of further serious commentary, here are some observations presented by means of bullet point:

  • By total WAR and total RA9-WAR, prospects recognized for their curveballs have more or less doubled the figures produced by pitchers recognized for their fastball, their slider, or their control.
  • Perhaps unsurprisingly, prospects recognized for their sliders have been most likely to assume a relief role (as suggested by that group’s lowest-overall median games-started rate). Sliders, which typically feature more lateral than vertical movement, tend to neutralize same-handed batters, but are vulnerable to opposite-handed ones. Accordingly, pitchers who rely on that pitch might find themselves relegated to relief roles, in which they might be more easily deployed in situations where they possess the platoon advantage.
  • Perhaps it’s because the curveball typically demonstrates more vertical break — and therefore produces a less pronounced platoon split — that prospects distinguished for the curves have recorded the highest rate of games started and most innings. Because the pitchers in question would suffer less against opposite-handed batters, I mean.
  • Were that the case, however — i.e. that pitchers with curves have benefited from neutralizing batters’ platoon advantages more ably than pitchers with sliders — then one might reasonably expect prospects recognized for their changeups to have performed more admirably by the methodology utilized here. Indeed, such prospects have produced about one quarter the WAR recorded by prospects recognized for the curves and one half the totals recorded by pitchers from the other three groups.
  • Ultimately, this is probably a matter that demands a larger sample, as it’s entirely possible that the contributions of a few (Felix Hernandez and Justin Verlander, for example) are distorting the outcomes as a whole.



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Carson Cistulli has just published a book of aphorisms called Spirited Ejaculations of a New Enthusiast.


30 Responses to “How the Best Pitching Tools Translate to the Majors”

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  1. Edwin says:

    “Sliders, which typically feature more lateral than horizontal movement”

    Is that supposed to be vertical movement instead of horizontal? Otherwise I guess I’m a little confused about the difference between lateral and horizontal pitch movement.

    Vote -1 Vote +1

  2. This has been a great series and I’ve enjoyed every one. While the data is not enough to conclude anything, it is a great start to the conversation, in light of the fact, as you noted, that more sophisticated data isn’t available.

    Obviously, one way is to include, say, the lists from at least a 5-year period of “Best of” pitches. I also think it would be interesting to add this dimension to the data once you gather more: include cuts by where the pitcher fell in their team’s Top 30 list, so, Top 10, Top 11-20, Top 21-30. That could explain the extremes that you noted in each list. You could also include whether the pitcher was on the Top 100 list or not, that split would be interesting to see as well.

    And, I would like to add, I’ve followed you from the beginning and you have just gotten better and better. Keep up the good work.

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  3. baltic fox says:

    Interesting. When I think of Danks, I think: outstanding changeup. When I think of Gavin Floyd: slider.

    And having watched Hammel for a couple of years with the Orioles, I certainly don’t think curveball (having looked at his career stats, he greatly reduced the number of curveballs he threw while still with the Rays).

    Very surprised to see that Verlander wasn’t listed as possessing the best fastball in the Tigers system. Who was that masked man?

    On an unrelated note: Viva el presidente Ezequiel! The name won’t be remembered by baseball fans, but it certainly strikes a chord in fans of cinema.

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    • fly eli and tony plush says:

      From Ba in 2005: I was sure Joel Zumaya would be best fastball.

      Best Fastball Eulogio de la Cruz
      Best Curveball Justin Verlander
      Best Slider Kyle Sleeth
      Best Changeup Kyle Sleeth
      Best Control Matt Vasquez

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      • FirstCasualtyofWAR says:

        Wow, I’d forgotten my 2005 great expectations for Kyle Sleeth. Gotta fire up the George Michael What Ever Happened to Sports Machine for him. Down the rabbit-hole I go…

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  4. Gingerbread Man says:

    Manny Parra was ranked for “Best Control” ???

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  5. chri521 says:

    Anyway to isolate that particular pitch for pitchers who show up on multiple lists (like Mr. Kate Upton and King Felix even Cole).

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  6. jfree says:

    It seems you’ve identified at least one big gap in scouting ‘best’ criteria. Most of the specific pitches only really have value in combo with other pitches in a repertoire. So it would seem better for a pitcher to have three ‘acceptable’ pitches than to merely have the uberhottest fastball in the organization.

    And why on Earth aren’t prospects being rated on their mechanics. Do teams just not get the connection between poor/inconsistent mechanics – and the millions of dollars thrown down the toilet each year paying for TJ/etc recuperation?

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    • DD says:

      “So it would seem better for a pitcher to have three ‘acceptable’ pitches than to merely have the uberhottest fastball in the organization.”

      Tell that to Denny Bautista.

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    • Bobby Ayala says:
      FanGraphs Supporting Member

      How would one quantify and grade pitching mechanics?

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      • jfree says:

        I assume that the MLB teams that are losing millions per year on pitching injuries can afford to figure that out. Seems easier to both quantify and grade than ‘how much grit/hustle/clubhouse character does this guy have’

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      • stevenam says:

        Actually, none of the “tools” are quantified, strictly speaking. The subjective rating of those tools is quantified, but I don’t believe that the BA ratings are based on objective pitch f/x or velocity readings, but rather human judgement (egads, scouts!) of those tools. But tell me if I’m wrong.

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  7. FirstCasualtyofWAR says:

    This very well could be my eyesight starting to fail me at my advanced age, but Verlander didn’t have one of the top 27 fastball grades?

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    • Michael says:

      As a prospect in 2005, apparently not.

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    • The Party Bird says:

      Seems even weirder that Joel “I threw harder than anyone not named Aroldis Chapman” Zumaya wasn’t the top fastball in the Tiger system when Verlander was there.

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  8. MrKnowNothing says:

    Be curious to see how these correlate to their rankings as prospects both within the system and as part of MLB at large.

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  9. Doug Gray says:

    Part of the issue with the pitcher rankings is that relievers and starters are grouped together. It would be a lot more interesting to see how the starters/relievers broke down, but BA groups them together so we don’t have those kinds of split groups to look at.

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  10. Brett Myers says:

    Hé Cistulli, maintenant vous pouvez me demander si j’ai arrêté de battre ma femme dans non pas un mais deux langues.

    +10 Vote -1 Vote +1

  11. B N says:

    I think this may need to be done with some sort of clustering with respect to each pitch’s quality grade. I think a big confound to this is that the majority of pitchers try to master a fastball, then master secondary pitches (which are literally called “secondary” pitches). So then, the very fact that you are developing effective curves, change-ups, and other pitches indicates that you probably have at least an adequate fastball.

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  12. Roger says:

    I’d like to see how appearing on multiple best pitching tool lists impacts a prospect’s chances of success.

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  13. Bomok says:

    I’m
    suprised Bartolo Colon is missing from the fastball and control list.
    I mean, fastball control is basically all he has. But he uses it VERY VERY well.

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    • dls says:

      I’m not. Seeing as this is based on Baseball America prospect rankings starting in 2005. And ca. 2005, good ol Bartolo was busy winning 21 games for the Angels in his 7th year in major league baseball.

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  14. Governator says:

    I suspect that the changeup list is weaker than expected because, oftentimes the best changeups in the system belong to those crafty low-velo college types.

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    • MH says:

      This. Guys who have major league fastballs don’t usually develop changeups till later. It’s more common that you’ll see a major league fastball plus major league breaking ball with a developing changeup from a high quality prospect than fastball+changeup.

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