2014 ZiPS Projections – San Francisco Giants

After having typically appeared in the entirely venerable pages of Baseball Think Factory, Dan Szymborski’s ZiPS projections were released at FanGraphs last year. The exercise continues this offseason. Below are the projections for the San Francisco Giants. Szymborski can be found at ESPN and on Twitter at @DSzymborski.

Other Projections: Arizona / Atlanta / Baltimore / Boston / Chicago AL / Chicago NL / Cincinnati / Cleveland / Colorado / Detroit / Houston / Kansas City / Los Angeles AL / Los Angeles NL / Miami / Milwaukee / Minnesota / New York AL / New York NL / Oakland / Philadelphia / Pittsburgh / San Diego / Seattle / St. Louis / Tampa Bay / Texas / Toronto / Washington.

Batters
A haphazard inspection of the 29 ZiPS posts to have preceded this one reveals that only one field player (Mike Trout, at 9.5) is projected to produce as many wins in 2014 as Buster Posey. Andrew McCutchen also crosses the six-win threshold. Everyone else: less than that. Offensively, Posey has demonstrated excellent control of the strike zone and also power on contact. Defensively, he plays a difficult position and plays it well. That’s an ideal player, more or less.

Not entirely like Buster Posey is free-agent acquisition and probable left fielder Michael Morse. Other people smarter than the present author have questioned the wisdom of the Morse signing for the Giants. Germane to this post is that ZiPS renders objectively the reasons for those questions. Morse has one skill, his raw power, nor is ZiPS even particularly confident about that: the .162 mark projected here would only be fourth on the club, not much greater than the figures assigned to Roger Kieschnick and Brett Pill.

Pitchers
The starting pitchers in the depth-chart graphic below are arranged not in order of expected rotation slot, but rather by projected WAR according to ZiPS. They also include just the five pitchers most likely to begin the season in the rotation. Were that latter caveat removed, however, Ryan Vogelsong would be omitted from the list, replaced by either Edwin Escobar or Clayton Blackburn. Of note, also: after outperforming his defense-independent figures by three wins between 2011 and -12, Vogelsong’s runs-allowed WAR actually underperformed his traditional one this past year by 1.2 wins.

By both park-adjusted FIP and park-adjusted ERA, the Giants bullpen was one of the majors’ worst five last season. Given the relative paucity of innings thrown by relievers and the other vagaries associated with them, that sort of unfortunate achievement is prone to positive regression. In the case of the Giants, however, ZiPS isn’t particularly optimistic about considerable improvement. Beyond Sergio Romo and maybe Javier Lopez, much of the unit is expected to hover around a league-average ERA. Fine in a vacuum, that, but even average relievers generally outperform starters by about a run of ERA.

Bench/Prospects
Neither shortstop Ehire Adrianza nor catcher Andrew Susac are considered elite prospects — not even within the system, really, as their omission from the top 10 of both Marc Hulet’s and Baseball America’s organizational lists suggests. That said, their projections here — and also those produced by Steamer, as well — would seem to indicate that they’re skilled enough to contribute in some capacity at the major-league level. In fact, the Giants have a number of these sorts. Gary Brown, Adam Duvall, Joe Panik: all three of them are projected to record figures somewhere between replacement-level and average.

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Depth Chart
Below is a rough depth chart for the present incarnation of the Giants, with rounded projected WAR totals for each player. For caveats regarding WAR values see disclaimer at bottom of post. Click to embiggen image.

Giants Depth

Ballpark graphic courtesy Eephus League. Depth charts constructed by way of those listed here at site and author’s own haphazard reasoning.

Batters, Counting Stats

Player B Age PO PA R H 2B 3B HR RBI SB CS
Buster Posey R 27 C 583 71 150 31 2 18 83 3 1
Pablo Sandoval B 27 3B 555 64 140 28 3 17 81 1 1
Brandon Belt L 26 1B 562 73 130 31 4 16 70 9 4
Hunter Pence R 31 RF 665 87 161 30 4 20 93 12 3
Brandon Crawford L 27 SS 500 53 108 22 4 7 46 3 3
Marco Scutaro R 38 2B 545 65 139 23 4 4 44 4 1
Angel Pagan B 32 CF 508 69 124 25 7 6 47 19 6
Andrew Susac R 24 C 429 45 81 14 2 5 33 1 1
Ehire Adrianza B 24 SS 512 52 102 22 5 3 39 11 5
Gregor Blanco L 30 CF 441 52 92 15 5 4 33 17 6
Andres Torres B 35 CF 269 34 55 14 3 3 21 9 3
Adam Duvall R 25 3B 508 55 103 21 4 13 55 3 2
Joe Panik L 23 2B 621 70 141 26 4 4 54 7 4
Hector Sanchez B 24 C 327 29 76 16 0 6 47 0 1
Gary Brown R 25 CF 573 67 122 25 5 7 54 19 12
Brett Pill R 29 1B 483 56 120 26 2 13 63 3 2
Joaquin Arias R 29 3B 311 30 76 12 3 3 28 3 1
Brandon Hicks R 28 SS 411 44 76 16 2 11 39 6 3
Tony Abreu B 29 2B 401 42 92 22 4 5 40 4 4
Mac Williamson R 23 RF 460 57 99 19 1 10 44 5 1
Nick Noonan L 25 2B 454 47 97 18 2 3 39 4 3
Guillermo Quiroz R 32 C 255 24 50 12 1 4 24 0 0
Michael Morse R 32 RF 427 48 100 20 1 14 47 0 1
Jeff Arnold R 26 C 336 33 58 16 1 5 27 2 0
Juan Perez R 27 RF 549 60 126 27 6 7 50 15 8
Mark Minicozzi R 31 3B 460 50 94 19 0 6 39 2 1
Javier Herrera R 29 LF 540 60 113 27 2 10 53 15 7
Roger Kieschnick L 27 RF 441 49 88 19 6 10 46 3 3
Skyler Stromsmoe B 30 SS 256 26 50 9 1 1 17 5 4
Todd Linden B 34 1B 270 26 51 12 2 3 23 1 1
Chris Dominguez R 27 3B 522 51 111 22 3 9 52 4 4
Angel Villalona R 23 1B 540 55 105 23 0 14 53 0 0

***

Batters, Rates and Averages

Player PA BB% K% ISO BABIP BA OBP SLG wOBA
Buster Posey 583 9.9% 14.2% .174 .316 .293 .367 .467 .357
Pablo Sandoval 555 7.7% 13.7% .169 .296 .279 .335 .448 .333
Brandon Belt 562 10.9% 23.3% .177 .327 .264 .349 .441 .343
Hunter Pence 665 7.2% 18.5% .161 .299 .264 .319 .425 .325
Brandon Crawford 500 7.6% 19.6% .113 .288 .238 .301 .351 .282
Marco Scutaro 545 6.6% 7.0% .087 .297 .283 .332 .370 .307
Angel Pagan 508 6.9% 13.4% .122 .298 .266 .316 .388 .308
Andrew Susac 429 9.6% 32.4% .086 .318 .212 .294 .298 .270
Ehire Adrianza 512 7.6% 21.7% .090 .287 .224 .290 .314 .266
Gregor Blanco 441 10.4% 20.6% .095 .299 .238 .319 .333 .291
Andres Torres 269 10.0% 21.6% .122 .294 .232 .315 .354 .298
Adam Duvall 508 6.3% 23.6% .147 .269 .222 .281 .369 .284
Joe Panik 621 6.8% 12.7% .081 .281 .249 .303 .330 .281
Hector Sanchez 327 4.9% 21.4% .112 .302 .250 .291 .362 .284
Gary Brown 573 4.9% 21.5% .107 .289 .232 .285 .339 .274
Brett Pill 483 3.7% 14.3% .152 .284 .264 .297 .416 .308
Joaquin Arias 311 2.9% 13.8% .091 .291 .259 .282 .350 .271
Brandon Hicks 411 7.1% 37.0% .140 .302 .202 .263 .342 .269
Tony Abreu 401 3.0% 20.4% .118 .294 .243 .271 .361 .271
Mac Williamson 460 5.4% 26.1% .121 .303 .235 .293 .356 .291
Nick Noonan 454 6.4% 21.1% .074 .292 .232 .282 .306 .256
Guillermo Quiroz 255 6.3% 25.5% .113 .279 .216 .273 .329 .263
Michael Morse 427 5.6% 23.2% .162 .303 .253 .304 .415 .312
Jeff Arnold 336 6.0% 36.9% .107 .291 .187 .245 .294 .243
Juan Perez 549 3.6% 22.6% .116 .304 .242 .275 .358 .276
Mark Minicozzi 460 7.4% 30.7% .088 .320 .225 .287 .313 .270
Javier Herrera 540 6.5% 27.6% .123 .305 .229 .285 .352 .282
Roger Kieschnick 441 7.0% 30.4% .151 .294 .218 .272 .369 .278
Skyler Stromsmoe 256 7.4% 20.7% .062 .278 .219 .286 .281 .252
Todd Linden 270 7.0% 30.0% .102 .293 .206 .270 .308 .260
Chris Dominguez 522 3.1% 29.3% .110 .301 .223 .253 .333 .257
Angel Villalona 540 3.3% 30.6% .128 .270 .205 .239 .333 .251

***

Batters, Assorted Other

Player PA RC/27 OPS+ Def zWAR No.1 Comp
Buster Posey 583 6.6 138 5 6.5 Thurman Munson
Pablo Sandoval 555 5.6 123 -2 3.4 Jim Lefebvre
Brandon Belt 562 5.7 126 1 2.7 Dan Driessen
Hunter Pence 665 5.1 112 0 2.6 Gary Ward
Brandon Crawford 500 3.7 87 6 2.2 Chris Gomez
Marco Scutaro 545 4.7 102 -3 2.2 Mark Grudzielanek
Angel Pagan 508 4.7 102 -2 2.1 Mookie Wilson
Andrew Susac 429 3.0 72 1 1.3 Ray Corbett
Ehire Adrianza 512 3.2 74 3 1.3 Manuel Francois
Gregor Blanco 441 3.9 89 -1 1.3 Alex Cole
Andres Torres 269 4.1 95 3 1.3 Mitch Webster
Adam Duvall 508 3.6 85 0 1.2 Clay Bellinger
Joe Panik 621 3.6 83 -2 1.1 Tim Harkrider
Hector Sanchez 327 3.7 87 -2 1.1 Joe Oliver
Gary Brown 573 3.3 79 2 1.0 Chris Sheff
Brett Pill 483 4.5 103 0 0.8 Ron Coomer
Joaquin Arias 311 3.6 81 2 0.7 Francisco Matos
Brandon Hicks 411 3.1 73 -2 0.6 Seth Bynum
Tony Abreu 401 3.4 80 0 0.5 Jose Olmeda
Mac Williamson 460 3.8 86 -1 0.4 Wil Culmer
Nick Noonan 454 3.0 70 3 0.4 Jack Hannahan
Guillermo Quiroz 255 3.1 73 -3 0.3 George Mitterwald
Michael Morse 427 4.5 105 -9 0.2 Dan Ford
Jeff Arnold 336 2.5 54 1 0.2 Francisco Morales
Juan Perez 549 3.5 81 2 0.1 Alexis Gomez
Mark Minicozzi 460 3.1 73 -3 0.1 Chris Saunders
Javier Herrera 540 3.5 83 -2 0.0 Justin Ruggiano
Roger Kieschnick 441 3.4 83 0 -0.1 Andy Tomberlin
Skyler Stromsmoe 256 2.6 64 -4 -0.3 Doug Baker
Todd Linden 270 2.8 66 0 -0.7 Dann Howitt
Chris Dominguez 522 2.8 67 -6 -0.7 Greg Porter
Angel Villalona 540 2.7 63 -5 -2.3 Jim Scharrer

***

Pitchers, Counting Stats

Player T Age G GS IP SO BB HR H R ER
Madison Bumgarner L 24 32 32 204.7 196 54 17 167 70 65
Matt Cain R 29 30 30 191.7 164 51 18 165 73 68
Tim Hudson R 38 25 25 164.7 126 46 10 153 64 60
Tim Lincecum R 30 29 29 180.0 177 71 17 162 81 76
Edwin Escobar L 22 25 24 133.0 107 37 11 126 57 53
Clayton Blackburn R 21 23 23 133.0 104 33 13 131 59 55
Sergio Romo R 31 63 0 52.7 58 11 4 42 15 14
Ryan Vogelsong R 36 24 23 134.3 98 45 14 134 64 60
Kyle Crick R 21 19 19 84.7 82 61 4 72 39 36
Chris Heston R 26 21 21 122.7 86 45 10 123 59 55
Yusmeiro Petit R 29 20 20 116.3 88 28 13 119 57 53
Ty Blach L 23 22 20 126.7 86 40 12 130 62 58
Javier Lopez L 36 63 0 37.0 31 14 2 33 14 13
Josh Osich L 25 47 0 56.0 47 20 4 51 22 21
Adalberto Mejia L 21 22 16 94.3 63 28 10 97 47 44
Derek Law R 23 43 0 62.3 62 23 6 55 26 24
Jean Machi R 32 59 0 62.3 48 18 4 59 26 24
Santiago Casilla R 33 56 0 49.7 41 22 4 44 20 19
Jose De Paula L 26 20 18 92.7 52 31 7 99 47 44
Brett Bochy R 26 44 0 51.7 47 17 4 46 21 20
Heath Hembree R 25 59 0 56.3 53 24 5 50 24 22
Jeremy Affeldt L 35 49 0 44.0 35 18 3 40 18 17
George Kontos R 29 67 0 75.3 62 21 7 72 32 30
Dontrelle Willis L 32 9 8 44.3 30 19 4 45 22 21
Hunter Strickland R 25 45 0 47.0 36 15 4 45 20 19
Jake Dunning R 25 57 0 73.3 50 24 5 71 32 30
Kendry Flores R 22 18 17 100.0 65 19 15 106 52 49
Juan Gutierrez R 30 35 0 38.0 33 14 4 36 17 16
Jose Casilla R 25 33 1 50.7 27 15 4 52 24 22
Sandy Rosario R 28 54 0 58.0 41 23 4 57 27 25
Kameron Loe R 32 55 5 78.7 47 23 8 83 39 36
Guillermo Moscoso R 30 31 20 130.0 98 58 17 126 70 65
Mason Tobin R 26 22 0 25.0 15 13 2 26 14 13
Shane Loux R 34 20 9 67.7 28 22 7 75 37 35
Mike Kickham L 25 27 23 125.3 94 57 13 127 68 64
Rafael Dolis R 26 40 0 46.0 29 22 3 46 24 22
Erik Cordier R 28 31 6 54.0 41 38 5 54 31 29
Dan Runzler L 29 46 3 54.3 44 37 5 52 30 28
Barry Zito L 36 24 21 117.0 74 45 14 127 66 62
Adam Reifer R 28 32 0 36.3 24 22 4 37 21 20
Mitch Lively R 28 39 9 87.7 58 46 9 89 49 46
Steve Edlefsen R 29 48 0 53.7 34 40 5 56 33 31
Jason Berken R 30 30 21 123.3 67 52 15 141 76 71

***

Pitchers, Rates and Averages

Player IP TBF K% BB% BABIP ERA FIP ERA- FIP-
Madison Bumgarner 204.7 835 23.5% 6.5% .267 2.86 3.01 80 84
Matt Cain 191.7 791 20.7% 6.4% .267 3.19 3.43 89 96
Tim Hudson 164.7 693 18.2% 6.6% .283 3.28 3.19 92 89
Tim Lincecum 180.0 773 22.9% 9.2% .288 3.80 3.50 106 98
Edwin Escobar 133.0 562 19.0% 6.6% .288 3.59 3.52 100 98
Clayton Blackburn 133.0 563 18.5% 5.9% .291 3.72 3.67 104 102
Sergio Romo 52.7 211 27.5% 5.2% .277 2.39 2.41 67 67
Ryan Vogelsong 134.3 582 16.8% 7.7% .286 4.02 4.00 112 112
Kyle Crick 84.7 387 21.2% 15.8% .290 3.83 4.11 107 115
Chris Heston 122.7 536 16.0% 8.4% .291 4.04 3.96 113 111
Yusmeiro Petit 116.3 496 17.7% 5.6% .293 4.10 3.85 114 107
Ty Blach 126.7 550 15.6% 7.3% .291 4.12 4.04 115 113
Javier Lopez 37.0 158 19.6% 8.9% .282 3.16 2.98 88 83
Josh Osich 56.0 239 19.7% 8.4% .285 3.37 3.49 94 97
Adalberto Mejia 94.3 408 15.4% 6.9% .289 4.20 4.18 117 117
Derek Law 62.3 265 23.4% 8.7% .288 3.47 3.52 97 98
Jean Machi 62.3 264 18.2% 6.8% .287 3.47 3.22 97 90
Santiago Casilla 49.7 215 19.1% 10.2% .274 3.44 3.66 96 102
Jose De Paula 92.7 408 12.7% 7.6% .295 4.27 4.11 119 115
Brett Bochy 51.7 218 21.5% 7.8% .286 3.48 3.35 97 93
Heath Hembree 56.3 243 21.8% 9.9% .285 3.51 3.77 98 105
Jeremy Affeldt 44.0 190 18.4% 9.5% .282 3.48 3.58 97 100
George Kontos 75.3 319 19.4% 6.6% .288 3.58 3.54 100 99
Dontrelle Willis 44.3 197 15.2% 9.6% .289 4.26 4.23 119 118
Hunter Strickland 47.0 201 17.9% 7.5% .285 3.64 3.65 102 102
Jake Dunning 73.3 315 15.9% 7.6% .286 3.68 3.69 103 103
Kendry Flores 100.0 425 15.3% 4.5% .285 4.41 4.46 123 124
Juan Gutierrez 38.0 164 20.1% 8.5% .286 3.79 3.79 106 106
Jose Casilla 50.7 219 12.3% 6.8% .282 3.91 4.08 109 114
Sandy Rosario 58.0 254 16.1% 9.1% .288 3.88 3.68 108 103
Kameron Loe 78.7 342 13.7% 6.7% .287 4.12 4.06 115 113
Guillermo Moscoso 130.0 574 17.1% 10.1% .277 4.50 4.70 126 131
Mason Tobin 25.0 114 13.2% 11.4% .293 4.68 4.70 131 131
Shane Loux 67.7 300 9.3% 7.3% .284 4.66 4.73 130 132
Mike Kickham 125.3 560 16.8% 10.2% .293 4.60 4.41 128 123
Rafael Dolis 46.0 206 14.1% 10.7% .289 4.30 4.21 120 118
Erik Cordier 54.0 254 16.1% 15.0% .295 4.83 5.02 135 140
Dan Runzler 54.3 252 17.5% 14.7% .289 4.64 4.68 130 131
Barry Zito 117.0 523 14.1% 8.6% .292 4.77 4.53 133 126
Adam Reifer 36.3 168 14.3% 13.1% .285 4.95 5.15 138 144
Mitch Lively 87.7 398 14.6% 11.6% .287 4.72 4.85 132 135
Steve Edlefsen 53.7 257 13.2% 15.6% .291 5.20 5.40 145 151
Jason Berken 123.3 563 11.9% 9.2% .299 5.18 4.99 145 139

***

Pitchers, Assorted Other

Player IP K/9 BB/9 HR/9 ERA+ zWAR No. 1 Comp
Madison Bumgarner 204.7 8.62 2.37 0.75 120 3.8 Eric Milton
Matt Cain 191.7 7.70 2.39 0.85 108 2.8 Mark Portugal
Tim Hudson 164.7 6.89 2.51 0.55 105 2.2 Tom Candiotti
Tim Lincecum 180.0 8.85 3.55 0.85 90 1.3 Jason Bere
Edwin Escobar 133.0 7.24 2.50 0.74 96 1.3 Joe Kennedy
Clayton Blackburn 133.0 7.04 2.23 0.88 92 1.1 Joe Blanton
Sergio Romo 52.7 9.91 1.88 0.68 144 0.8 Rafael Betancourt
Ryan Vogelsong 134.3 6.57 3.02 0.94 85 0.6 Bobby Witt
Kyle Crick 84.7 8.71 6.48 0.43 90 0.6 Roger Pavlik
Chris Heston 122.7 6.31 3.30 0.73 85 0.5 Steve Kelly
Yusmeiro Petit 116.3 6.81 2.17 1.01 84 0.4 Oil Can Boyd
Ty Blach 126.7 6.11 2.84 0.85 83 0.4 Hilly Hathaway
Javier Lopez 37.0 7.54 3.41 0.49 109 0.2 Vic Darensbourg
Josh Osich 56.0 7.55 3.21 0.64 102 0.2 Ray Beasley
Adalberto Mejia 94.3 6.01 2.67 0.95 82 0.2 Matt Blank
Derek Law 62.3 8.96 3.32 0.87 99 0.1 Andy Ghelfi
Jean Machi 62.3 6.93 2.60 0.58 99 0.1 Terry Leach
Santiago Casilla 49.7 7.42 3.98 0.72 100 0.1 Brian Boehringer
Jose De Paula 92.7 5.05 3.01 0.68 80 0.1 Lee Guetterman
Brett Bochy 51.7 8.18 2.96 0.70 99 0.1 Paul Mancuso
Heath Hembree 56.3 8.47 3.84 0.80 98 0.1 Tony Blasucci
Jeremy Affeldt 44.0 7.16 3.68 0.61 99 0.1 Vic Darensbourg
George Kontos 75.3 7.41 2.51 0.84 96 0.1 Don Cooper
Dontrelle Willis 44.3 6.09 3.86 0.81 81 0.1 Jim Abbott
Hunter Strickland 47.0 6.89 2.87 0.77 94 0.0 Jeff Tam
Jake Dunning 73.3 6.14 2.95 0.61 93 0.0 Todd Williams
Kendry Flores 100.0 5.85 1.71 1.35 78 0.0 Dave Geeve
Juan Gutierrez 38.0 7.82 3.32 0.95 91 -0.1 Nate Field
Jose Casilla 50.7 4.79 2.66 0.71 88 -0.1 Pedro Borbon
Sandy Rosario 58.0 6.36 3.57 0.62 89 -0.2 Mike Gardner
Kameron Loe 78.7 5.37 2.63 0.91 83 -0.2 Danny Graves
Guillermo Moscoso 130.0 6.78 4.02 1.18 76 -0.3 John Leister
Mason Tobin 25.0 5.40 4.68 0.72 73 -0.3 Tommy Moore
Shane Loux 67.7 3.72 2.92 0.93 74 -0.3 Jose Santiago
Mike Kickham 125.3 6.75 4.09 0.93 75 -0.3 Derek Root
Rafael Dolis 46.0 5.67 4.30 0.59 80 -0.4 Ken Wright
Erik Cordier 54.0 6.83 6.33 0.83 71 -0.5 Ryan Baker
Dan Runzler 54.3 7.29 6.13 0.83 74 -0.5 Brian Shackelford
Barry Zito 117.0 5.69 3.46 1.08 72 -0.6 Jim Deshaies
Adam Reifer 36.3 5.95 5.45 0.99 69 -0.6 Brad Tweedlie
Mitch Lively 87.7 5.95 4.72 0.92 73 -0.6 Jarod Juelsgaard
Steve Edlefsen 53.7 5.70 6.70 0.84 66 -1.0 Marty McLeary
Jason Berken 123.3 4.89 3.80 1.09 66 -1.3 Giovanni Carrara

***

Disclaimer: ZiPS projections are computer-based projections of performance. Performances have not been allocated to predicted playing time in the majors — many of the players listed above are unlikely to play in the majors at all in 2014. ZiPS is projecting equivalent production — a .240 ZiPS projection may end up being .280 in AAA or .300 in AA, for example. Whether or not a player will play is one of many non-statistical factors one has to take into account when predicting the future.

Players are listed with their most recent teams unless Dan has made a mistake. This is very possible as a lot of minor-league signings are generally unreported in the offseason.

ZiPS is projecting based on the AL having a 4.04 ERA and the NL having a 3.81 ERA.

Players that are expected to be out due to injury are still projected. More information is always better than less information and a computer isn’t what should be projecting the injury status of, for example, a pitcher with Tommy John surgery.

Regarding ERA+ vs. ERA- (and FIP+ vs. FIP-) and the differences therein: as Patriot notes here, they are not simply mirror images of each other. Writes Patriot: “ERA+ does not tell you that a pitcher’s ERA was X% less or more than the league’s ERA. It tells you that the league’s ERA was X% less or more than the pitcher’s ERA.”

Both hitters and pitchers are ranked by projected zWAR — which is to say, WAR values as calculated by Dan Szymborski, whose surname is spelled with a z. WAR values might differ slightly from those which appear in full release of ZiPS. Finally, Szymborski will advise anyone against — and might karate chop anyone guilty of — merely adding up WAR totals on depth chart to produce projected team WAR.





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

53 Comments
Oldest
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Ivan Grushenko
12 years ago

Derek Law, porn cop. Also this team seems a cut below the Dodgers, Cardinals, Nationals, Braves and Reds….and about even with the Pirates.

Kram
12 years ago
Reply to  Ivan Grushenko

huh? Reds as good on paper as Dodgers, Cards, Nats, and Braves? You serious?

Ivan Grushenko
12 years ago
Reply to  Kram

I meant according to ZiPS, not according to me.

MrKnowNothing
12 years ago

Feels like I’ve been reading about Brown for a decade now. I have zero faith that he will do anything at all in MLB.

Dog puddles
12 years ago

Players with >6 WAR:

2013 MLB: 12 hitters, 6 pitchers
2014 ZiPS: 3 hitters, 0 pitchers

(unless I messed this up somehow)

IZZY2112
12 years ago
Reply to  Dog puddles

Worth mentioning that ZIPS is not projecting only 3 hitters to have 6 WAR. It is saying that only three hitters have a better than 50% chance of having 6 WAR. For instance, if I were to roll 100 dice, there would be no dice for which I would give a 50%+ chance of it landing on “3”. But in the aggregate, you’d expect 1/6 of them to roll a “3”.

Also, Kershaw has 6.6 WAR & Verlander has 6.1.

Dog puddles
12 years ago
Reply to  IZZY2112

True.

“A haphazard inspection of the 29 ZiPS posts to have preceded this one reveals that only one *field* player…”

It appears I have given Carson’s sentence a haphazard inspection.

DSzymborski
12 years ago
Reply to  IZZY2112

Bingo. As I was telling Ben Lindberg on Twitter after he expressed a similar note in the PECOTA release article, you’ll never successfully explain this to about 30% of readers.

I spent probably a month last year explaining why ZiPS only having 3 mean BAs at .300 and ZiPS projecting there to actually be 22 .300 BAs on average in 2013 are not mutually exclusive.

Baltar
12 years ago
Reply to  DSzymborski

Unfortunately, Dan, humans as a whole are very poor at understanding probability.

RMD
12 years ago
Reply to  DSzymborski

6+ WAR position players 2014 ZiPS:

3

6+ WAR among position players since 2003:

12,12,14,13,12,14,13,9,8,14,14

That’s remarkably consistent. What’s the point of pulling in past data to make projections if you’re projecting somethings that’s have never even come close to occurring? You’re running these simulations too many times to make results more bland and murky.

DSzymborski
12 years ago
Reply to  DSzymborski

RMD, see post directly above yours.

blank
12 years ago
Reply to  DSzymborski

I completely understand this point, so let me ask the follow up question: What is the probability distribution of a ZiPS projects? Is the sample size and relative independence of ABs enough to make it Gaussian? If so, what are the CVs? How much do they vary across positions/players? I apologize if this has been asked and answered on this web page previously.

(Also, yeah, I could probably back out a typical CV with the aforementioned 3 and 18 numbers, but I lazily ask the question instead.)

Andy
12 years ago
Reply to  DSzymborski

“you’ll never successfully explain this to about 30% of readers.”

Yet according to ZiPS projections, only three readers have > 50% chance of not understanding this.

Xeifrank
12 years ago
Reply to  Dog puddles

As it should be.

ZeezilMember since 2020
12 years ago
Reply to  Dog puddles

That’s because outlier seasons get regressed. You should see the same thing at the low end. The actual spread will almost always be larger than the projected spread. Also check out the distribution of actual team wins versus projected team wins, for any season.

brendan
12 years ago
Reply to  Dog puddles

RMD, the two questions are 1. how many 6 win players? 2. which players will accrue 6 wins?

answering the first question is easier than the second. presumably, several players projected for 5 WAR will exceed 6, while others projected for 5 accrue less.

Mike Green
12 years ago

I did not need to see the Thurman Munson comp for Posey. Spring training is almost here, and a simple wish for a great catcher’s good health seems to appropriate. Give me soul, or give me NotGraphs.

obsessivegiantscompulsive
12 years ago
Reply to  Mike Green

There has been no news about Posey taking up piloting planes, so we should be good on that.

EverettCase
12 years ago

When do we think all the ZiPS Projections will be added to the Projections tab and made exportable, a la Steamer?

Ivan Grushenko
12 years ago
Reply to  EverettCase

Maybe in the future

jim
12 years ago
Reply to  EverettCase

never

Ank
12 years ago
Reply to  EverettCase

Bump… anyone have any actual info?

Peter
12 years ago
Reply to  Ank

They were uploaded by 2/18 last year, so here’s to hoping we can see the aggregate projections soon!

ZeezilMember since 2020
12 years ago

Since Fangraphs posts Steamer, Oliver, and (eventually) ZiPS projections on the player pages, it would be useful to have a post that summarizes them, highlighting differences in key areas (perhaps in a simple table format). We could all consult the Google ourselves, but having someone else aggregate and explain data/methods is a large part of the reason we read Fangraphs.

Of course, it’s possible that there is such a post. I didn’t check because I’m lazy, which is consistent with my reason for wanting such a post in the first place.

ZeezilMember since 2020
12 years ago
Reply to  Zeezil

I should clarify that I meant a post the summarizes the different models, not the results.

Tyler
12 years ago

Explain how Blanco’s -1 defensively when his aggregate over the last 2 seasons is something like +20…..

walt526
12 years ago
Reply to  Tyler

I believe “Def” includes FA’s position adjustment and Blanco is considered to be a LFer. In other words, the positional penalty of being a LF dominates his (heavily regressed) defensive projection.

So basically, Zips has Blanco as something like a +5/150g defender with a -7.5 position adjustment, which nets out to -1 after adjusting for playing time.

Pitnick
12 years ago
Reply to  walt526

I don’t think that’s right. Belt wouldn’t be +1 if positional adjustment were included, nor would Pence (an average RFer) be 0.

BipMember since 2016
12 years ago
Reply to  walt526

Yes, based on all of the ZiPS numbers I’ve seen, it must be that the defense numbers do not include position adjustment, while the def numbers on the player pages do.

Astros Broadcast Booth
12 years ago

This explains the resume we just received from a B. Zito….

Wendy ThurmMember since 2016
12 years ago

Brett Pill will play in Korea this year. According to GM Brian Sabean, Yusmiero Petit, Escobar and David Huff are candidates for a rotation spot if someone is injured or Vogelsong falters badly out of the gate.

Ruki Motomiya
12 years ago
Reply to  Wendy Thurm

For a moment I thought you said Aubrey Huff and was very confused.

garbanzo24Member since 2023
12 years ago

Thanks Dan, Carson, and the Fangraphs team! I really appreciate all the work you put into this!

With that said, I need to complain for a moment. On the player pages, “Def” includes a positional adjustment. That’s how it works on the leaderboards, and that’s how it works on the Dashboard. I don’t necessarily support it becoming the metric du jour of understanding a position player’s run preventative contribution, but it’s not a huge deal. I can customize my dashboard and get rid of it.

But then, in these projections, “Def” is now treated without a positional adjustment, it seems. Why the inconsistency? If Fangraphs is going to redefine the term “Defense” to include a positional adjustment, why not at least be consistent?

/rant over

BipMember since 2016
12 years ago
Reply to  garbanzo24

I don’t necessary expect them to be the same, because this field is an output of the ZIPS system, and I don’t see it as relating directly to a player’s page. However, I definitely think that note should be added to the disclaimer in the future if the system is not changed. It has led to a lot of confusion.

Shankbone
12 years ago

Steve Edlefsen? Never give up on a Minny guy? He’s unsigned as far as I can tell, not a Gigante right now. Guillermo Moscoso took his talents to Japan. Todd Linden retired, took up coaching for the Giants (does that include a refresher on “how to be a dick to your teammates?”)

No projection for Mike Broadway or Casey Weathers? You got practically every other minor league FA signing.

Hilly Hathaway’s full name is Hillary Houston Hathaway.

Mike Morse has a good chance of beating that projection if his wrist truly is healed and healthy. His defensive troubles will limit his late innings, but the Giants have some tricks up their sleeves for this whole deal, its not nearly the catastrophe that has been proclaimed.

MAC
12 years ago
Reply to  Shankbone

“And I base that on absolutely nothing.”

Tim Burwell
12 years ago

I would love to see Todd Linden hit a homerun for the Giants this season! His ilk harkens the times of Damon Minor, Lance Niekro and vintage Cody Ransom. I miss those days for some masochistic reason.

Bobby Melody
12 years ago

Thanks-Good stuff. I know the comps come from a group of players. Eric Milton as the #1 comp for Maddison Baumgarner.
I like the Oil Can Boyd comp for Yusimero Petit though.

Xeifrank
12 years ago

And here is how my simulator likes their batting order.

vs RHP
Crawford-Pagan-Sandoval-Posey-Belt-Pence-Scutaro-Morse-Pitcher

vs LHP
Pagan-Scutaro-Belt-Posey-Pence-Sandoval-Morse-Crawford-Pitcher

Ruki Motomiya
12 years ago
Reply to  Xeifrank

I’ve seen you make many posts about this and IIRC in, like, the Mets article you posted an article on it. Do you have articles on all the teams you simulate, and if so where can I see?

Xeifrank
12 years ago
Reply to  Ruki Motomiya

Click on the “my simulator” text in my post, or click on my username and it takes you directly to them.

Ruki Motomiya
12 years ago
Reply to  Xeifrank

I didn’t realize those were links. Cool!

BipMember since 2016
12 years ago
Reply to  Xeifrank

I have used fangraphs html link text on occasion, but the fact these comments do not in any way denote link text in a different color has discouraged me.

Bobby Melody
12 years ago

Based on the Runs Created from the starting line-up, that this line-up will outscore last year’s team by about 50 runs provided the starters stay healthy. If injuries to key players occur, there will be a significant drop-off. Not many position players with pop waiting in the wings.

DrBGiantsfan
12 years ago

Gotta say, if the 5 starters all turn in their projected ERA’s, Giants gonna be alright.

BipMember since 2016
12 years ago
Reply to  DrBGiantsfan

Zips is obviously considering AT&T to play like the most extreme of pitchers parks this year. For example, it considers Lincecum’s projected 3.80 to actually be worse than average. As another example, Posey’s projected wOBA of .357, something that would be pretty good in Detroit, is given an outstanding OPS+ rating of 138.

So if your starters turn in those ERAs, you very well may not be alright, because the bullpen in going to blow some leads, and the offense is expected to be pretty tame, due to park and run environment.

DrBGiantsfan
12 years ago
Reply to  Bip

You don’t know much about the Giants, do you?

Machaut
12 years ago
Reply to  DrBGiantsfan

This is a good, fact-based argument.

Bobby Melody
12 years ago

Dr BG Fan,
I agree. Having Tim Hudson instead of Barry Zito is a huge upgrade. If Vogelsong bounces back-it will be a solid year of pitching.

jordanjandrew
12 years ago

My God… poor Hunter Pence. Glad to know he will have his second worst OBP in his career. But with LESS POWER! And an equally bad slugging percentage! Didn’t know the dude was trending so down.

Bobby Melody
12 years ago
Reply to  jordanjandrew

Steamer, Oliver, and ZIPS are remarkably similar in their projections of Hunter Pence. The contract he signed was for a super-star. He is a star player and offers intangibles such as leadership and showing up in great shape. But a 5.1 RC projection-for the money they are paying him, I hope he does better than that.

garett68
12 years ago

Quick Side note, Looking to fill out the rest of a new Otto League (This is Fantasy Baseball). Auction Draft, Fangraphs Points, group arbitration $99, draft on 3/28. Email me at garettmarcum@gmail.com

SeattleSlew
12 years ago

Should the Giants or fantasy owners be worried about Matt Cain’s struggles in clutch situations? His 7 run collapse in the A’s 8-1 win was painful to watch.