2013 ZiPS Projections – San Francisco Giants

by
December 19, 2012

Dan Szymborski’s ZiPS projections, which have typically appeared in the pages of Baseball Think Factory, will be released at FanGraphs this year. Below is the first set of 2013’s projections — for the World Series champion San Francisco Giants. Don’t hesitate to leave notes regarding format/presentation in the comments section, as the author frequently has no idea what he’s doing.

Other thing: Szymborski himself will be chatting at Noon ET today in these very same electronic pages, and will happily answer any questions readers have regarding the projections themselves.

Batters
The Giants’ success is tied pretty strongly to the health and success of Buster Posey — not merely because only one player (i.e. Mike Trout) posted a higher WAR than Posey in 2012, but also because San Francisco’s catching corps lacks anything like impact talent. At 23, Hector Sanchez certainly has some promise, but even approaching Posey’s production would be a considerable challenge.

Of some interest will be how well the club is able to account for the departure of Melky Cabrera. While they were obviously able to win a championship following his suspension, Cabrera was also integral to the Giants’ regular-season performance, posting a 4.6 WAR in just 113 games (501 plate appearances). Manning the corners now will be Hunter Pence in right field and (likely) a platoon of Gregor Blanco and Andres Torres in left. ZiPS is optimistic neither about Blanco’s ability to match his career-high 2.4 wins from 2012, nor Pence’s ability to earn the entirety of the ca. $14 million he’s likely to receive in arbitration.

Pitchers
Allow the author to make all necessary caveats and disclaimers regarding, in particular, Matt Cain’s ability to prevent runs above and beyond those inputs for which WAR accounts. Adjudged solely by runs allowed per nine innings, Cain was worth 6.1 wins in 2012 — and has exceeded his WAR totals by ca. 10 wins by that measure over the course of his career. He’s good. Everyone acknowledges it. Huz-zah.

Otherwise, besides the departure of Brian Wilson (who was non-tendered) and a couple pieces maybe at the very back end of the bullpen, almost the entire pitching staff returns. Tim Lincecum’s No. 1 comparable player, Tom Gordon, is notable, perhaps: Gordon was an undersized right-hander who made 203 starts between his age-20 and -29 seasons before becoming a dominant reliever. Lincecum, who enters his own age-29 season, has made 188 starts. Despite an underwhelming season in the rotation, Lincecum was excellent out of the bullpen during the postseason.

Bench/Prospects
Mostly owing to their defensive acumen — which is substantiated by scouting reports — both outfielder Gary Brown and shortstop Ehire Adrianza profile as potentially useful pieces in the present, should injury or ineffectiveness elsewhere require their presence. Much of Joe Panik‘s profile — high-contact infielder who’s probably more appropriately deployed at second base than shortstop — resembles the recently re-signed Marco Scutaro’s. Now out of options, Conor Gillaspie will serve as depth at first and third (and maybe second) at the major-league level.

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Depth Chart
Here’s a rough depth chart for the Giants, with rounded projected WAR totals for each player (click to embiggen):

Ballpark graphic courtesy Eephus League. Credit to MLB Depth Charts for roster information.

Batters, Counting Stats

Player B Age PO PA R H 2B 3B HR RBI SB CS
Buster Posey R 26 C 583 75 153 30 2 20 86 3 1
Pablo Sandoval B 26 3B 547 68 141 30 3 18 76 2 3
Angel Pagan B 31 CF 610 81 151 32 9 8 55 25 8
Brandon Belt L 25 1B 544 63 124 28 5 13 67 12 5
Gary Brown R 24 CF 654 78 151 30 6 6 52 29 16
Hunter Pence R 30 RF 665 82 159 28 4 18 90 9 4
Andres Torres B 35 CF 425 54 87 21 6 6 37 14 5
Joe Panik L 22 SS 640 77 153 27 4 4 57 7 4
Marco Scutaro R 37 2B 542 53 132 24 3 5 45 6 3
Conor Gillaspie L 25 3B 566 59 132 23 5 8 57 2 4
Brandon Crawford L 26 SS 475 49 99 21 4 6 42 4 5
Ehire Adrianza B 23 SS 531 50 106 26 5 4 42 10 4
Hector Sanchez B 23 C 362 34 88 20 1 6 57 0 1
Joaquin Arias R 28 SS 371 39 90 15 3 4 35 6 1
Adam Duvall R 24 3B 615 63 122 25 4 16 67 4 4
Gregor Blanco L 29 RF 400 50 78 14 4 4 25 21 5
Brett Pill R 28 1B 543 56 131 29 2 13 67 4 3
Nick Noonan L 24 SS 548 55 121 21 3 4 47 6 4
Guillermo Quiroz R 31 C 333 35 68 14 2 6 38 0 1
Freddy Sanchez R 35 2B 224 23 55 11 1 3 24 1 1
Francisco Peguero R 25 RF 515 56 129 17 9 4 54 13 6
Roger Kieschnick L 26 LF 398 48 83 16 5 10 43 4 4
Aubrey Huff L 36 1B 278 24 59 12 0 5 28 2 1
Todd Linden B 33 1B 387 42 82 17 4 5 35 2 2
Juan Perez R 26 RF 573 61 129 26 6 7 48 14 11
Ryan Theriot R 33 2B 487 54 118 19 2 1 36 11 7
Tyler LaTorre L 30 C 179 17 33 8 0 1 15 0 1
Xavier Nady R 34 LF 254 22 51 10 0 4 23 1 0
Wes Hodges R 28 1B 384 33 83 19 1 6 35 2 1

***

Batters, Rates and Averages

Player PA BB% K% ISO BABIP BA OBP SLG wOBA
Buster Posey 583 10.1% 15.6% .184 .326 .299 .372 .482 .363
Pablo Sandoval 547 7.9% 13.7% .182 .300 .285 .338 .467 .334
Angel Pagan 610 6.9% 14.4% .132 .306 .270 .320 .403 .311
Brandon Belt 544 12.3% 22.8% .164 .330 .264 .358 .429 .341
Gary Brown 654 5.5% 17.0% .101 .303 .255 .314 .356 .293
Hunter Pence 665 7.4% 18.6% .148 .299 .262 .317 .410 .316
Andres Torres 425 10.4% 22.8% .136 .298 .233 .318 .369 .303
Joe Panik 640 7.2% 11.3% .080 .290 .262 .318 .342 .292
Marco Scutaro 542 6.3% 7.9% .092 .283 .269 .316 .360 .294
Conor Gillaspie 566 7.4% 15.9% .111 .295 .256 .313 .367 .293
Brandon Crawford 475 7.6% 23.2% .109 .293 .230 .292 .340 .272
Ehire Adrianza 531 6.8% 21.1% .100 .279 .221 .280 .321 .262
Hector Sanchez 362 3.9% 20.7% .117 .308 .257 .285 .373 .283
Joaquin Arias 371 3.2% 13.5% .095 .288 .258 .285 .352 .275
Adam Duvall 615 7.0% 24.4% .145 .268 .219 .283 .364 .281
Gregor Blanco 400 11.8% 22.0% .099 .292 .227 .322 .326 .293
Brett Pill 543 4.1% 14.4% .142 .280 .258 .295 .400 .298
Nick Noonan 548 6.4% 19.5% .078 .295 .241 .290 .318 .264
Guillermo Quiroz 333 6.0% 25.5% .118 .286 .223 .275 .341 .266
Freddy Sanchez 224 5.4% 14.7% .107 .304 .268 .312 .376 .294
Francisco Peguero 515 2.5% 19.8% .095 .320 .262 .283 .357 .276
Roger Kieschnick 398 6.0% 30.4% .152 .303 .226 .274 .378 .279
Aubrey Huff 278 9.4% 15.8% .109 .267 .239 .309 .348 .285
Todd Linden 387 8.0% 25.6% .114 .310 .234 .302 .349 .286
Juan Perez 573 3.8% 23.6% .109 .303 .238 .271 .346 .267
Ryan Theriot 487 6.0% 11.1% .058 .297 .265 .312 .323 .277
Tyler LaTorre 179 8.4% 26.3% .069 .286 .208 .282 .277 .246
Xavier Nady 254 5.5% 24.8% .094 .278 .218 .272 .312 .258
Wes Hodges 384 3.6% 25.0% .107 .291 .227 .258 .334 .259

***

Batters, Assorted Other

Player PA RC/27 OPS+ Def WAR No.1 Comp
Buster Posey 583 6.9 139 5 6.5 Joe Torre
Pablo Sandoval 547 5.9 125 2 4.1 Jim Lefebvre
Angel Pagan 610 4.9 103 4 3.5 Mookie Wilson
Brandon Belt 544 5.7 121 1 2.7 Johnny Callison
Gary Brown 654 4.0 89 5 2.1 Lemmie Miller
Hunter Pence 665 4.8 104 -1 2.1 Gary Matthews
Andres Torres 425 4.2 94 4 2.1 Mitch Webster
Joe Panik 640 4.0 87 -6 1.9 Liu Rodriguez
Marco Scutaro 542 4.2 91 0 1.9 Mark Loretta
Conor Gillaspie 566 4.0 91 1 1.8 Ernest Riles
Brandon Crawford 475 3.3 78 6 1.7 Craig Cooper
Ehire Adrianza 531 3.2 69 3 1.5 Pedro Sanchez
Hector Sanchez 362 3.8 84 0 1.3 Rich Gedman
Joaquin Arias 371 3.8 79 -2 1.2 Luis Maza
Adam Duvall 615 3.5 82 -3 1.2 Corey Smith
Gregor Blanco 400 4.0 84 4 1.1 Reggie Williams
Brett Pill 543 4.3 94 0 1.0 Dan Rohrmeier
Nick Noonan 548 3.2 72 -5 0.7 Gregorio Petit
Guillermo Quiroz 333 3.2 73 -3 0.7 Chad Moeller
Freddy Sanchez 224 4.3 94 0 0.7 Mark Grudzielanek
Francisco Peguero 515 3.7 79 4 0.6 Alexis Rios
Roger Kieschnick 398 3.5 82 1 0.4 Matt Cimo
Aubrey Huff 278 3.8 86 0 0.4 Dave May
Todd Linden 387 3.7 84 0 0.3 Mitch Webster
Juan Perez 573 3.2 73 4 0.2 Drew Anderson
Ryan Theriot 487 3.6 80 -7 0.0 Brian Dallimore
Tyler LaTorre 179 2.5 59 -1 -0.3 Tom Nieto
Xavier Nady 254 3.0 65 0 -0.3 Chad Moeller
Wes Hodges 384 3.0 66 -1 -0.5 Nilson Robledo

***

Pitchers, Counting Stats

Player T Age G GS IP SO BB HR H R ER
Matt Cain R 28 31 31 210.7 179 55 17 179 75 70
Madison Bumgarner L 23 33 33 209.0 195 49 19 190 80 75
Tim Lincecum R 29 31 31 188.7 194 78 18 169 82 77
Ryan Vogelsong R 35 28 27 163.7 130 57 15 155 72 67
Sergio Romo R 30 66 0 52.0 64 11 4 39 14 13
Barry Zito L 35 24 23 135.7 91 53 15 134 70 65
Santiago Casilla R 32 60 0 56.3 51 24 5 49 22 21
Chris Heston R 25 23 23 136.7 86 50 11 148 72 67
Jose Mijares L 28 65 0 50.7 48 21 4 44 20 19
Jeremy Affeldt L 34 58 0 55.0 48 22 4 50 22 21
Brian Wilson R 31 47 0 48.0 49 23 3 42 19 18
Mike Kickham L 24 25 24 123.3 99 64 11 123 65 61
Eric Surkamp L 24 19 19 104.3 81 50 7 107 52 49
Javier Lopez L 35 65 0 41.3 31 17 2 39 17 16
Brett Bochy R 25 41 0 47.3 54 27 4 37 20 19
George Kontos R 28 51 2 70.0 58 25 7 67 32 30
Clay Hensley R 33 53 3 61.3 49 27 6 57 29 27
Heath Hembree R 24 51 0 47.3 47 28 4 40 21 20
Chad Gaudin R 30 37 3 63.7 49 23 6 64 31 29
Yusmeiro Petit R 28 21 17 98.0 67 30 10 111 55 51
Dan Runzler L 28 43 4 48.0 44 27 3 47 25 23
Brad Penny R 35 22 10 73.0 37 25 7 82 41 38
Shane Loux R 33 41 0 53.3 29 16 4 56 26 24
Dan Otero R 28 48 0 59.0 38 12 5 65 29 27
Guillermo Mota R 39 34 0 42.7 39 16 5 42 21 20
Boof Bonser R 31 17 8 42.0 24 20 4 47 26 24
Jake Dunning R 24 44 3 71.7 48 26 6 79 39 36
Clayton Blackburn R 20 22 22 125.7 95 27 24 137 75 70
Mitch Lively R 27 50 0 69.0 47 32 5 71 36 34
Scott Munter R 33 38 1 49.3 36 27 4 53 29 27
Jean Machi R 31 56 0 57.3 37 25 6 63 33 31
Steve Edlefsen R 28 50 0 56.3 36 32 5 60 33 31
Brian Burres L 32 24 21 107.3 65 50 15 126 72 67
Eric Hacker R 30 27 24 134.0 75 55 15 166 88 82
Edwin Escobar L 21 20 19 91.7 60 39 18 108 65 61

***

Pitchers, Rates and Averages

Player IP TBF K% BB% BABIP ERA FIP ERA- FIP-
Matt Cain 210.7 853 21.0% 6.5% .265 2.99 3.30 78 86
Madison Bumgarner 209.0 850 23.0% 5.8% .285 3.23 3.11 84 81
Tim Lincecum 188.7 800 24.3% 9.8% .289 3.67 3.53 96 92
Ryan Vogelsong 163.7 689 18.9% 8.3% .283 3.68 3.76 96 98
Sergio Romo 52.0 202 31.6% 5.4% .279 2.25 2.33 59 61
Barry Zito 135.7 583 15.6% 9.1% .273 4.31 4.36 112 114
Santiago Casilla 56.3 236 21.6% 10.2% .277 3.36 3.66 88 95
Chris Heston 136.7 601 14.3% 8.3% .300 4.41 4.18 115 109
Jose Mijares 50.7 213 22.6% 9.9% .285 3.38 3.53 88 92
Jeremy Affeldt 55.0 232 20.7% 9.5% .289 3.44 3.55 90 92
Brian Wilson 48.0 205 23.9% 11.2% .296 3.38 3.24 88 84
Mike Kickham 123.3 551 18.0% 11.6% .294 4.45 4.38 116 114
Eric Surkamp 104.3 464 17.5% 10.8% .306 4.23 4.00 110 104
Javier Lopez 41.3 174 17.8% 9.8% .296 3.48 3.24 91 84
Brett Bochy 47.3 201 26.9% 13.5% .281 3.61 3.56 94 93
George Kontos 70.0 299 19.4% 8.4% .282 3.86 3.94 101 103
Clay Hensley 61.3 263 18.6% 10.3% .277 3.96 4.14 103 108
Heath Hembree 47.3 208 22.6% 13.5% .278 3.80 4.17 99 109
Chad Gaudin 63.7 273 18.0% 8.4% .295 4.10 3.96 107 103
Yusmeiro Petit 98.0 430 15.6% 7.0% .309 4.68 4.16 122 108
Dan Runzler 48.0 215 20.5% 12.6% .311 4.31 3.82 112 100
Brad Penny 73.0 321 11.5% 7.8% .291 4.68 4.40 122 114
Shane Loux 53.3 228 12.7% 7.0% .287 4.05 3.94 105 103
Dan Otero 59.0 250 15.2% 4.8% .306 4.12 3.67 107 96
Guillermo Mota 42.7 183 21.3% 8.7% .294 4.22 3.98 110 104
Boof Bonser 42.0 191 12.6% 10.5% .297 5.14 4.76 134 124
Jake Dunning 71.7 316 15.2% 8.2% .307 4.52 4.06 118 106
Clayton Blackburn 125.7 535 17.8% 5.0% .279 5.01 4.90 130 128
Mitch Lively 69.0 306 15.4% 10.5% .298 4.43 4.24 115 110
Scott Munter 49.3 224 16.0% 12.0% .309 4.93 4.45 128 116
Jean Machi 57.3 256 14.5% 9.8% .298 4.87 4.58 127 119
Steve Edlefsen 56.3 257 14.0% 12.4% .296 4.95 4.78 129 125
Brian Burres 107.3 492 13.2% 10.2% .300 5.62 5.24 146 136
Eric Hacker 134.0 614 12.2% 9.0% .317 5.51 4.80 143 125
Edwin Escobar 91.7 418 14.4% 9.3% .289 5.99 5.84 156 152

***

Pitchers, Assorted Other

Player IP K/9 BB/9 HR/9 ERA+ WAR No. 1 Comp
Matt Cain 210.7 7.65 2.35 0.73 121 4.2 Freddy Garcia
Madison Bumgarner 209.0 8.40 2.11 0.82 112 3.5 Eric Milton
Tim Lincecum 188.7 9.25 3.72 0.86 98 2.2 Tom Gordon
Ryan Vogelsong 163.7 7.15 3.13 0.82 98 1.9 Mike Torrez
Sergio Romo 52.0 11.08 1.90 0.69 161 1.4 Ugueth Urbina
Barry Zito 135.7 6.04 3.52 0.99 84 0.6 Bob Knepper
Santiago Casilla 56.3 8.15 3.84 0.80 108 0.5 Doug Bochtler
Chris Heston 136.7 5.66 3.29 0.72 82 0.4 Mike LaCoss
Jose Mijares 50.7 8.52 3.73 0.71 107 0.4 Randy Choate
Jeremy Affeldt 55.0 7.85 3.60 0.65 105 0.4 Scott Schoeneweis
Brian Wilson 48.0 9.19 4.31 0.56 107 0.4 Mike MacDougal
Mike Kickham 123.3 7.23 4.67 0.80 81 0.3 Brandon Claussen
Eric Surkamp 104.3 6.99 4.31 0.60 82 0.3 John Daniels
Javier Lopez 41.3 6.76 3.70 0.44 104 0.3 Vic Darensbourg
Brett Bochy 47.3 10.27 5.14 0.76 100 0.2 Eric Cammack
George Kontos 70.0 7.46 3.21 0.90 94 0.2 Joey McLaughlin
Clay Hensley 61.3 7.19 3.96 0.88 91 0.1 Jim Czajkowski
Heath Hembree 47.3 8.94 5.33 0.76 95 0.1 Brad Voyles
Chad Gaudin 63.7 6.92 3.25 0.85 88 0.1 Steve Crawford
Yusmeiro Petit 98.0 6.15 2.76 0.92 77 0.0 Doug Waechter
Dan Runzler 48.0 8.25 5.06 0.56 84 -0.1 Steve Colyer
Brad Penny 73.0 4.56 3.08 0.86 77 -0.1 Jim Barr
Shane Loux 53.3 4.90 2.70 0.68 89 -0.1 Mike Barlow
Dan Otero 59.0 5.80 1.83 0.76 88 -0.2 Jeff Tam
Guillermo Mota 42.7 8.22 3.37 1.05 86 -0.2 Jose Mesa
Boof Bonser 42.0 5.14 4.29 0.86 70 -0.3 Elmer Riddle
Jake Dunning 71.7 6.03 3.26 0.75 80 -0.4 Rich DeLosSantos
Clayton Blackburn 125.7 6.80 1.93 1.72 72 -0.5 John Gardner
Mitch Lively 69.0 6.13 4.17 0.65 81 -0.6 Jose Segura
Scott Munter 49.3 6.57 4.93 0.73 73 -0.7 Ernie Camacho
Jean Machi 57.3 5.81 3.93 0.94 74 -0.9 Mike Sullivan
Steve Edlefsen 56.3 5.75 5.12 0.80 73 -0.9 Ryan Baker
Brian Burres 107.3 5.45 4.19 1.26 64 -1.2 Brian Barnes
Eric Hacker 134.0 5.04 3.69 1.01 66 -1.3 Dennis Tankersley
Edwin Escobar 91.7 5.89 3.83 1.77 60 -1.4 Greg Hibbard

***

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 2012. 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 4.09 ERA and the NL having a 3.92 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 WAR.

Dan Szymborski can be found on Twitter @DSzymborski.





 

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

66 Comments
Oldest
Newest Most Voted
Izzy Hechkoff
13 years ago

Is he planning on doing career projections for certain players on each team, as he has done in the past?

1
Dr. Chaleeko
13 years ago
Reply to  Izzy Hechkoff

Dan,

Thanks these. Huge treat. I second Izzy Hecoff above. Please do the career extrapolations!!! They are my favorite part of your ZIPS articles each year.

0
rorschach
13 years ago

I really don’t see Buster Posey hitting below .300 next year. He’s too consistent.

-2
Clifford
13 years ago
Reply to  rorschach

he hit .284 in 2011….and seriously, you are really gonna harp on 0.01 points of batting average?

11
TKDC
13 years ago
Reply to  Clifford

Nope, Posey is a true talent .368 BABIP guy, just like he showed last year.

Interestingly, if you included post season numbers, Posey only hit .322 last year, which would make this less regression than from his league leading .336. I wonder if post season numbers are included in ZiPs?

3
rorschach
13 years ago
Reply to  Clifford

@Clifford: Harping? Really? I was merely expressing the opinion that Buster Posey won’t hit below .300 for a full season, and you bring up a season in which he played all of 45 games to counter that. Talk about harping.

-4
jda
13 years ago
Reply to  Clifford

@TKDC: Yes, Dan has said in the past that he’s been using post-season numbers for a few years now.

2
gator32301
13 years ago
Reply to  rorschach

imagine if people regularly used .299 as an arbitrary benchmark instead of .300 – then you could have prevented the waste of time and energy on posting that utterly inane comment.

15
rorschach
13 years ago
Reply to  gator32301

@gator: Right, because expressing an opinion that a hitter will have a certain batting average is more a waste of time than belittling that person’s opinion. Imagine if you weren’t a pompous ass, then you could have prevented the waste of time and energy on posting that utterly inane comment.

-12
nieldale
13 years ago
Reply to  gator32301

You should feel bad, because you hurt rorschach’s feelings. I’m sure he has a few ink blots of buster posey’s batting average for you to look at.

1
rorschach
13 years ago
Reply to  gator32301

@neildale: ha

-2
Trey Baughn
13 years ago

This is a terrific snapshot of a team. Really hope we get this for all 30 as the off season unfolds. Thanks

2
SeanP
13 years ago

Adjudged solely by runs allowed per nine innings, Cain was worth 6.1 wins in 2012 — and has exceeded his WAR totals by ca. 10 runs by that measure over the course of his career.

Should that be 10 wins? 37.6 RA9-Wins vs. 27.5 WAR.

2
Carson CistulliMember
13 years ago
Reply to  SeanP

Yes! Fixed! Thanks!

2
Boxkutter
13 years ago

Any plans to list what defensive positions a player will be rated for, before the projection disk comes out?

2
Teddy
13 years ago

Maybe you should think about doing an analysis or summary on the team based purely on the predictions for us regular fans to get a better idea of what how the stats will relate to the overall team performance the next year. Just a suggestion.

2
Dan
13 years ago

Dan usually posts DMB positional/defensive grades. Any chance we can have those as well?

1
BobbyS
13 years ago
Reply to  Dan

He stated earlier somewhere that the AV/100 format for DMB users would be included in the spreadsheet… but it would be great to see it here as well if possible!

1
jda
13 years ago
Reply to  BobbyS

Seconded!

0
BobbyS
13 years ago

Since it’s all sorted by WAR, would you be able to add in a WAR column for pitchers as well? Thanks!

0
Carson CistulliMember
13 years ago
Reply to  BobbyS

Ack. Oversight on my part. Should be there now. Thanks.

1
HizouseMember since 2018
13 years ago
Reply to  Carson Cistulli

But it’s b-r WAR? Check Bumgarner vs Cain: Bumgarner would have the higher fWAR.

0
Kellin
13 years ago
Reply to  Carson Cistulli

I think the combination of MadBum’s higher HR/9 and AT&T’s obscene park factor bring his fWAR lower than Cain

0
Darren
13 years ago

Would love to see Pitcher WAR

0
LegallyMinded
13 years ago

Really a great write-up; I can’t wait to see the rest of the teams’ projections.

By the way, do you put much stock in the predictive value of the Number 1 Comps, or is it more just a curiosity? I ask out of sympathy for Madison Bumgarner and is comparison to Eric Milton. . . .

0
Dan Szymborski
13 years ago
Reply to  LegallyMinded

The top comp is listed for fun, I usually list the top 3 comps, but there’s not quite as much room here.

As we go, I’ll keep a spreadsheet posted somewhere with the 3 comps and the DMB defensive ratings, to trail the FG projections.

2
TomW
13 years ago

Um, where are the OPS+ and ERA+ numbers?

0
BobbyS
13 years ago
Reply to  TomW

In the 3rd block for both hitters and pitchers.

0
TomW
13 years ago
Reply to  BobbyS

Duh…it’s early lol.

1
C-Lo
13 years ago

Any chance of including the Av/100 format and what positions every player is eligible at before the spreadsheet comes out? Also, what happened to the ODDIBE! Those were one of my favorite parts of the old format.

I’m not sure if I’m in the majority or minority on this topic, but for me (as a DMB player), I sure liked the BBTF format a whole lot better.

Also, another question for Dan: I was also curious to know if you had seen the study on how different defensive ratings at each position translate to Runs Saved (http://fansofdmb.yuku.com/topic/2569#.UMeUxLbd4co) and if that factored at all into your ratings? For example, a guy like Sam Fuld (Ex/104 @ LF with VG arm) was estimated to save something like 35 runs over a full season last year, yet his DRS number on his fangraphs ZiPS projections last year was nowhere close to that number.

Anyway, I was just curious if you were in the know on that study, and whether if it factored into your process at all (since the RS numbers that came with the projections on fangraphs last year did not line up with the numbers that the ratings gave in the DMB game).

3
Dan Szymborski
13 years ago
Reply to  C-Lo

Yup, I need to be even more conservative with the DMB ratings – the range bars are way too wide.

2
C-Lo
13 years ago
Reply to  Dan Szymborski

Thanks Dan!

That makes sense, but have you ever considered first coming up with the Defensive Runs Saved numbers, and then creating an Av/100 ranking for every player such that the DRS and DMB runs saved number lines up accordingly?

0
DrBGiantsfan
13 years ago

I am cautiously optimistic that Sandoval, Belt and Crawford will outperform their projections while I am guarded about Pagan, Scutaro, Torres and Blanco reaching theirs.

The pitching looks like it’s about where I would put it by eyeballing it.

1
SwitchRodeoMember since 2017
13 years ago

When will these be added to the player’s pages?

1
Dave
13 years ago

Are there plans to post a downloadable spreadsheet once all 30 teams are completed?

1
BJ
13 years ago

Those are some pretty optimistic numbers for Lincecum. I’m not sold on his bounceback, personally.

1
Bhaakon
13 years ago
Reply to  BJ

It’s projecting him as a modestly better than average starter. That’s a pretty bad year for him.

0
bradsbeard
13 years ago

Love the Eephus League graphic.

0
Tom
13 years ago

Hi,
Does anyone know if ZIPS changes their player projections anytime from now until season start? If so, do they change playing time or actual production numbers?

1
Erix
13 years ago

Can we use these as a projection of team record?

1
WA52
13 years ago
Reply to  Erix

Based on the rounded numbers provided, let’s call it 95-67.

0
Izzy Hechkoff
13 years ago
Reply to  WA52

Based on? You can’t just add up the WAR totals.

1
d_iMember since 2016
13 years ago

Didn’t Xavier Nady sign with the Royals?

1
Dan Szymborski
13 years ago
Reply to  d_i

Yup, Nady signed with the Royals. Since the FG crew needs to calculate some of the FG things I don’t calculate and get it into pretty tables (rather than my usual fixation with pre-formatted text), the lead time is a little bit longer than usual (and since this was the first one, this one even longer) Nady will also pop up in the KC post, with KC specific projections.

0
PT
13 years ago

How about a screen capture tweet pic of the DMB defensive ratings?

0
Tom
13 years ago

Dan,
What is the likely factor that can lead to player projection changes from now to season start?

1
WA43
13 years ago

With this being in fWAR (not bWAR), it would be more like 86. The players listed above don’t include the other 6 players on the 25-man roster. So, this projection would be 86 + whatever WAR is contributed by those players… probably something like 90-72.

-1
Michael Mitchell
13 years ago

Can’t wait to see LAA so we can see who Trout’s #1 comp is.

1
soladoras
13 years ago

I was expecting more Conor Gillaspie talk, Carson.

0
Bhaakon
13 years ago
Reply to  soladoras

He’s a great hitting shortstop trapped in the glove of a 1B.

1
soladoras
13 years ago

Adding the rounded WAR estimates together for the projected starting lineup, rotation and bullepn gives an estimate of around 86 wins, which seems intuitively correct to me. Posey, Pagan, Scutaro taking a bit of a step back, Torres/Blanco being a big step back from Melky’s production, and modest improvements from Crawford and Belt not enough to make up these gaps.

0
Spitball McPhee
13 years ago

LOVE THIS!

0
Bill
13 years ago

Any chance we get whip for those old school 4×4 leaguers?

0
kdm628496
13 years ago
Reply to  Bill

the components are there for you. get to work.

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blahblahblah
13 years ago

They sure have Scoot suffering too much in SanFran, with his lowest BABip of his last 5 seasons projected and a number more inline with his way-back-when Oakland lines when he used to watch an extreme amount of pitches that he now places (well, extreme for him)

I might be more inclined to trust the BillJames .301 BABip mark here since he has been .290-.320 the last five seasons (even over .312 both of the last two), and .283 just doesnt seem to fit Scutaro’s current incarnation much.

Also think they are weighing last seasons career-low BB% way too heavily. Between the two, both the BA and OBP end up well short of realistic in my opinion (in fact they have him at, by far, his lowest marks since his second full season in 2005, and that just doesnt seem realistic to me based on his recent production level)

So I would bet money Marco would be closer to the James .281/.344/.378 line then the ZiPS .269/.316/.360 mark

2
Dan Szymborski
13 years ago
Reply to  blahblahblah

Don’t forget he’s a middle infielder that just turned 37 and was downright awful in Coors for 2/3 of a season.

-1
Lg4ny
13 years ago

Exciting stuff… numbers overload. I was just wondering how the comps were constructed. Are they based solely on the player’s expected 2013 performance, or is there some sort of weighted career metrics set up? Along the same lines, does the comp point to a specific single season performance or their whole career? The range of career performance for guys like Joe Torre and Freddy Garcia obviously isn’t consistent, so does the Posey/Torre comp point to more career comp or 2012 Posey MVP vs. 1971 Torre MVP?

0
J. Cross
13 years ago

Very cool. Always excited when ZiPS comes out and I love this presentation.

-1
rosborneMember since 2016
13 years ago

In the 3rd block for pitchers, not all the pitchers were listed . Is the information available?

Thanks.

1
Dan Szymborski
13 years ago
Reply to  rosborne

Seems to have gotten cut off.

0
Carson CistulliMember
13 years ago
Reply to  rosborne

My bad. Should be fixed now.

0
tbd
13 years ago

looking at the bullpen, zips is projecting worse years for every one of:

(may i use ERA?)

casilla: 3.36 (2012-2010 was 2.84 1.74 1.95)
affeldt: 3.44 (2012-2009 was 2.70 2.63 4.14 1.73)
romo: 2.25 (2012-2010 was 1.79 1.50 2.18)
lopez: 3.48 (2012-2010 was 2.50 2.72 1.42)

and kontos to regress from 2.47 to 3.86
and mijares (yeah very sss) 2.55 to 3.38

a worse season for every single reliever, significantly worse
for several? seems very pessimistic to me and unlikely to happen.

1
tbd
13 years ago

btw i think vogelsong has a good shot at a sub 3.00 era next year.

notice his first 21 starts of 2012:

10-5(w-l) 2.27 ERA 143 IP 111 H 38-36 R-ER 48 BB 105 K 10 HR .215 BAA .615 OPS

then starts #22-28 (fatigue or mechanics??):

2-4(w-l) 10.31 ERA 29.2 IP 48 H 35-34 R-ER 11 BB 38 K 6 HR .366 BAA 1.050 OPS

then final 3 starts of reg season plus 4 playoff starts (back on track):

5-0 0.86 ERA 41.2 IP 28 H 6-4 R-ER 13 BB 36 K 1 HR

1
jda
13 years ago

Are the OPS+ numbers off? Does anyone else notice this? I have my own event-specific park factors for singles, doubles/triples, and home runs for LHB and RHB that I use, but even if I use a single, generic number for park factors I get something pretty similar to what I otherwise would. And in both cases, my OPS+ numbers are closer to 100 than Dan’s. The high OPS+ guys aren’t as high. The low OPS+ guys aren’t as low. And when I calculate WAR, the results I get are almost identical to Dan’s, so either I’m making a mistake with my OPS+ calculations or something else may be wrong. Just curious!

0
jda
13 years ago

Second question – I’m curious about this. Dan, do you use event-specific park factors for ZiPS, or only when you input data into Diamond Mind’s event tables?

0
jda
13 years ago

And last question (maybe more of a comment), again involving Diamond Mind’s defensive ratings.

Let’s oversimplify and also assume average error rates for all defenders. Let’s also assume that the difference between each fielding grade (PR –> FR –> AV –> VG –> EX) is about 9 defensive runs saved over the course of a season. Dan, you’ve acknowledged this in the comments and said you’ll have to be even more conservative about awarding EX (and presumably PR) grades, but the way things are now it seems like you’ll have to be more conservative with all grades, including FR and VG. And even then you’ll essentially be penalizing players who are “pretty good” defenders but not close enough to +9 runs saved to warrant the grade bump (or penalty).

I wish we could add more defensive rating grades, but I know Imagine Sports has no incentive to do that. But I wonder if they’d be willing to tweak their algorithm so that the jump between AV and VG and EX, for example, is more like 5 runs saved.

Anyway, I guess the question is – have you figured out yet how you’re going to handle all of this? Talk with Imagine Sports about algorithm-tweaking? Be more conservative but just with EX grades? Be more conservative with all non-AV grades?

I’d have posted this stuff to Twitter but I’m too long-winded!

0