Jay Jaffe FanGraphs Chat – 1/31/19

12:02
Jay Jaffe: Good afternoon from Brooklyn, where it’s a comparatively balmy 11 degrees (-4 with wind chill). The Hall of Fame circus has left town, but having missed last week’s post-announcement chat slot, I’ll still take questions on that topic, as well as hot stove stuff

12:04
Syndergaardians of the Galaxy : Even though I am an obsessive baseball fan, i don’t know much about Hector Santiago. So I was surprised to see him #6 on the Mets starter depth chart in Szymborski’s ZIPS article on the Mets, ahead of Cory Oswalt. Is this just a projections thing, or has there been word that the Mets see him this way?

12:06
Jay Jaffe: I wouldn’t read much into it, honestly. Santiago has been a versatile and occasionally competent swingman over the years, while Oswalt was dreadful as a rookie last year. We’re talking about a projection for 38 innings versus one for 19 innings, and the likelihood is that there will be some jockeying in the spring, and perhaps another free agent added on a minor league deal who supersedes them both.

12:06
Guest: I tweeted you this already but:
Scott Rolen:
70.2/43.7/56.9/ 17 Yrs / 7 ASG / 122 OPS+

Biggio:
65.5/41.8/53.7/ 20 Yrs / 7 ASG / 112 OPS+

Thoughts?  Shouldn’t he be getting a lot more love from stat people?

12:08
Jay Jaffe: Rolen gets plenty of love from “stat people” — it’s the general BBWAA electorate that has been relatively reserved (17% included him this year), but that’s also a function of the clogged ballot, which will become considerably roomier over the next five years, as I wrote earlier this week (https://blogs.fangraphs.com/closing-the-floodgates-the-next-five-years…). I expect Rolen’s vote share to climb, especially as he’ll be the next guy in the Raines-Martinez-Walker lineage of players who get a push from the analytics community

12:09
yojiveself: Would you give Harper/Machado a 10 year contract?

Read the rest of this entry »


2019 ZiPS Projections – New York Mets

After having typically appeared in the hallowed pages of Baseball Think Factory, Dan Szymborski’s ZiPS projections have now been released at FanGraphs for more than half a decade. The exercise continues this offseason. Below are the projections for the New York Mets.

Batters

The lineup feels a lot like one fielded by the St. Louis Cardinals. There are no bonafide superstar projections on the offense (Robinson Cano‘s projections don’t look like they used to, though ZiPS thinks he’ll still be a good player) but there’s a surprising amount of depth, providing a number of solid options for those times when stuff hits the fan. That approach is a smart way for a team in contention to construct its roster, given that teams with serious playoff aspirations should be more risk-averse than middling or rebuilding teams are; depth is certainly a preferable strategy to hoping injuries somehow pass you by. There’s one thing St. Louis has that the New York Mets have lacked, however: a track record of actually doing a good job shuffling their offensive talent around. The Cardinals very rarely bury players, but the Mets have been known to do all sorts of weird things, such as going into seasons without an obvious starting job for Michael Conforto, signing Jose Reyes and then playing him way too often, prioritizing Jay Bruce’s playing time, and needing some bad luck on the injury front to actually give Brandon Nimmo a full-time job coming off a .379 on-base percentage in 69 games in 2017. Whether you want to blame their managers or ownership, the Mets have made some real head-scratching decisions.

And so while are a lot of options here, the Mets will have to prove that they can deploy their talent effectively. Jeff McNeil doesn’t have an obvious starting role, so the team has to demonstrate that they want to find at-bats for him, not just give them to him grudgingly as they did in 2018, only after the obviously worse options played very obviously worse. Once Peter Alonso is down in the minors just long enough to get another year of cost control for the Mets … errr … I mean once Peter Alonso is finished polishing his game coincidentally in just enough games to delay his free agency for a year, getting him playing time should be the priority over the more expensive Todd Frazier. Yoenis Cespedes‘ heel surgeries will likely keep the Mets from having to make any tricky outfield decisions (his ZiPS projection is mostly theoretical) for a while, but that won’t last forever.

Pitchers

I like Jed Lowrie, but if you could buy baseball players from a catalog, I’d be calling customer service and telling the agent “Yeah, there’s nothing wrong with him, and he works fine and everything, but do you have him in pitcher?” The front four looks very solid, but the team has given every indication that Jason Vargas will take the fifth starter job if no other options are acquired this winter. Remember what I said about how contending teams should be risk-averse? Vargas is an extremely risky pitcher, and even though it hasn’t been so long since he pretended to be Greg Maddux for a few months in early 2017, I’d really like the team to do better here, given the noise they’ve made about contending and the very real improvements in other parts of the roster.

Edwin Diaz is a significant addition, and it’s surprising how cheaply they were able to add Diaz and Cano to the roster, both in terms of money and prospects. Of all the ZiPS teams to go up on FanGraphs so far, Diaz has the highest projected WAR of any relief pitcher and the lowest ERA, by three-tenths of a run. And that’s not just because I’ve run bad teams; Craig Kimbrel, Kenley Jansen, Andrew Miller, and Brad Hand have already gone live. Signing Luis Avilan to just a minor league contract with a non-roster invitation to spring training may go down as one of the best low-key deals of the winter, and the back end of the bullpen is better than many think.

Bench and Prospects

Perhaps my favorite projection for the Mets this year is the league-average projection for minor league reliever Stephen Villines, who I suspect would attract the interest of my friend/mortal enemy/ex-FanGraphs editor Carson Cistulli. He’s not really on the prospect radar much, but he had an interesting first professional season, striking out 54 of 138 batters in the Sally League, 25 of 77 for Hi-A St. Lucie, and then after a final promotion to Double-A Binghamton, striking out 17 of 43 batters. That’s 96 strikeouts against just 13 walks and three homers in 66.2 innings. Now, if he was doing this by blowing batters away with a 95 mph fastball, he’d be on prospects lists. But he doesn’t — he’s a soft-tosser who gets by on changing speeds and a slow slider. But he’s also a sidearmer, with a motion that looks like he wants to throw submarine but gives up halfway and just whips it around, kinda like Terry Leach’s delivery (I’m dating myself). We’ve seen sidearmers/submariners survive with slower stuff than you’d expect was sustainable — guys like Chad Bradford and Mike Myers come to mind — so while Villines could blow up in a bad way against Triple-A hitters, I’m intrigued.

ZiPS already gives Andres Gimenez a win per 600 PA in 2019 and projects enough growth from him to make for an interesting decision for the Mets at shortstop in a few years. ZiPS has come off its love for Dominic Smith, but still thinks Dilson Herrera would at least be a good role player if he can stay healthy. Believe it or not, Herrera is still just 24 (he turns 25 in March) even though it feels like he’s been around forever. There’s really no room for him on the Mets the way the team is currently constructed, but he could still resurface elsewhere and have some type of major league career — people wrote off Jose Peraza at way too young an age, too.

One pedantic note for 2019: for the WAR graphic, I’m using FanGraphs’ depth chart playing time, not the playing time ZiPS spits out, so there will be occasional differences in WAR totals.

Ballpark graphic courtesy Eephus League. Depth charts constructed by way of those listed here at site.

Batters – Counting Stats
Player B Age PO G AB R H 2B 3B HR RBI BB SO SB CS
Michael Conforto L 26 LF 145 495 77 124 26 1 28 86 72 148 3 3
Jeff McNeil L 27 2B 144 551 76 151 26 8 14 63 37 79 11 3
Robinson Cano L 36 2B 115 456 59 124 24 1 16 66 36 68 0 1
Brandon Nimmo L 26 CF 135 445 67 107 23 5 13 47 71 138 7 5
Yoenis Cespedes R 33 LF 96 360 51 93 18 2 20 63 28 96 4 1
Jed Lowrie B 35 2B 135 502 61 123 27 2 13 61 58 102 0 0
Amed Rosario R 23 SS 156 583 77 155 26 10 11 55 29 117 25 10
Peter Alonso R 24 1B 122 460 64 110 23 1 24 71 49 134 1 3
Todd Frazier R 33 3B 127 455 60 102 21 0 21 72 51 120 8 5
Wilson Ramos R 31 C 112 394 38 102 18 0 15 63 26 78 0 0
J.D. Davis R 26 3B 126 473 58 113 24 1 17 60 37 139 3 2
Travis d’Arnaud R 30 C 94 316 35 76 14 1 11 42 23 64 0 0
Luis Guillorme L 24 SS 121 423 45 103 17 2 2 31 41 68 3 2
Christian Colon R 30 2B 93 294 31 70 12 0 3 23 27 45 7 3
Juan Lagares R 30 CF 97 250 30 62 10 3 3 19 11 51 6 3
Keon Broxton R 29 CF 129 399 49 79 14 4 14 41 42 180 24 6
Andres Gimenez L 20 SS 120 455 48 99 17 4 7 36 26 121 22 13
Dilson Herrera R 25 2B 113 379 44 84 15 2 12 43 29 116 4 5
Dominic Smith L 24 1B 147 542 63 132 28 2 14 60 38 134 2 0
T.J. Rivera R 30 3B 113 399 43 104 19 1 8 46 16 67 1 1
Patrick Mazeika L 25 C 90 325 36 74 15 0 6 31 31 55 1 1
Gavin Cecchini R 25 2B 113 434 48 106 20 2 6 38 31 73 3 3
Ali Sanchez R 22 C 90 327 30 70 13 1 5 27 14 54 3 3
Will Toffey L 24 3B 87 314 35 60 13 1 6 25 42 102 1 1
Tomas Nido R 25 C 100 354 35 77 17 1 7 38 14 81 0 0
Devin Mesoraco R 31 C 77 216 20 45 8 1 8 24 22 49 0 0
Jose Reyes B 36 3B 104 329 44 76 14 3 7 31 28 55 12 4
Rymer Liriano R 28 LF 107 384 46 79 12 2 13 44 35 147 8 6
Sam Haggerty B 25 3B 101 362 41 70 16 4 4 27 45 121 20 7
Colton Plaia R 28 C 61 199 20 39 8 0 4 18 16 70 0 0
Rajai Davis R 38 CF 100 235 35 50 9 1 2 9 14 58 20 6
Joey Terdoslavich B 30 1B 95 342 38 77 15 1 9 37 33 77 1 1
Adrian Gonzalez L 37 1B 58 187 14 44 9 0 4 26 14 38 0 0
Austin Jackson R 32 CF 102 333 34 79 17 2 4 31 26 104 4 3
Matt den Dekker L 31 CF 101 331 35 66 13 3 9 35 24 111 7 4
Johnny Monell L 33 C 79 261 27 52 10 1 5 26 21 77 1 1
David Wright R 36 3B 44 167 18 34 6 0 3 14 20 55 1 1
Braxton Lee L 25 RF 112 406 41 91 13 2 2 26 36 94 9 10
David Thompson R 25 3B 111 401 42 86 20 1 9 42 21 110 5 3
Ty Kelly B 30 2B 120 347 39 74 15 3 5 34 37 88 2 2
Cody Asche L 29 3B 107 351 39 74 16 2 10 39 32 106 1 3
Kevin Kaczmarski L 27 CF 102 355 37 78 13 4 2 26 32 92 8 7
Kevin Taylor L 27 LF 120 429 42 98 16 2 3 32 32 72 1 1
Luis Carpio R 21 2B 124 458 44 90 17 1 10 37 37 125 10 10
Desmond Lindsay R 22 CF 98 347 33 61 10 4 6 28 34 142 6 8
Jhoan Urena B 24 RF 128 458 48 95 19 3 11 48 38 146 3 3
Gregor Blanco L 35 CF 111 301 37 66 11 3 4 20 30 82 8 3
Tim Tebow L 31 LF 97 333 28 58 12 1 7 25 21 145 1 1

Batters – Rate Stats
Player BA OBP SLG OPS+ ISO BABIP RC/27 Def WAR No. 1 Comp
Michael Conforto .251 .352 .477 125 .226 .301 6.0 3 3.7 Steve Kemp
Jeff McNeil .274 .329 .426 106 .152 .299 5.3 -4 2.8 Todd Zeile
Robinson Cano .272 .329 .434 107 .162 .290 5.2 0 2.5 George Kell
Brandon Nimmo .240 .359 .402 109 .162 .320 5.1 -6 2.5 Andy Van Slyke
Yoenis Cespedes .258 .314 .486 115 .228 .299 5.6 5 2.3 Cleon Jones
Jed Lowrie .245 .325 .384 94 .139 .284 4.5 1 2.3 Joe Randa
Amed Rosario .266 .303 .401 91 .136 .316 4.6 -1 2.3 Garry Templeton
Peter Alonso .239 .324 .450 110 .211 .285 5.1 3 2.2 Justin Morneau
Todd Frazier .224 .310 .409 95 .185 .258 4.4 2 2.1 Ed Sprague
Wilson Ramos .259 .302 .419 95 .160 .289 4.6 -2 1.7 Javy Lopez
J.D. Davis .239 .297 .402 90 .163 .303 4.2 0 1.5 Eddie Williams
Travis d’Arnaud .241 .297 .396 88 .155 .270 4.2 0 1.3 Nelson Santovenia
Luis Guillorme .243 .312 .307 71 .064 .286 3.4 2 1.0 Jeff Treadway
Christian Colon .238 .310 .310 71 .071 .272 3.4 6 1.0 Ted Sizemore
Juan Lagares .248 .286 .348 73 .100 .301 3.6 7 0.9 Rufino Linares
Keon Broxton .198 .278 .358 73 .160 .317 3.7 1 0.9 D.J. Dozier
Andres Gimenez .218 .278 .319 64 .101 .281 3.0 7 0.8 Chris Moritz
Dilson Herrera .222 .283 .367 77 .145 .287 3.4 3 0.8 Nick Green
Dominic Smith .244 .296 .380 84 .137 .299 4.1 4 0.7 Adam Lind
T.J. Rivera .261 .296 .373 82 .113 .296 4.0 -1 0.7 Terry Tiffee
Patrick Mazeika .228 .309 .329 76 .102 .258 3.5 -3 0.5 Paul Ellis
Gavin Cecchini .244 .297 .341 75 .097 .282 3.5 -2 0.3 Chris Demetral
Ali Sanchez .214 .245 .306 50 .092 .243 2.5 6 0.2 Rogelio Arias
Will Toffey .191 .289 .296 61 .105 .262 2.8 2 0.1 Ronald Bourquin
Tomas Nido .218 .249 .331 57 .113 .263 2.8 2 0.0 Jeff Winchester
Devin Mesoraco .208 .295 .366 80 .157 .233 3.7 -6 0.0 Dave Valle
Jose Reyes .231 .290 .356 76 .125 .258 3.7 -4 0.0 Spike Owen
Rymer Liriano .206 .278 .349 71 .143 .295 3.2 3 -0.1 Jed Hansen
Sam Haggerty .193 .286 .293 60 .099 .278 3.0 -1 -0.3 Joe Redfield
Colton Plaia .196 .258 .296 52 .101 .280 2.6 -1 -0.3 Ray Stephens
Rajai Davis .213 .265 .285 51 .072 .274 2.9 0 -0.3 Lou Brock
Joey Terdoslavich .225 .293 .354 77 .129 .266 3.6 -1 -0.3 Chris Pritchett
Adrian Gonzalez .235 .286 .348 73 .112 .276 3.5 -1 -0.4 Glenn Adams
Austin Jackson .237 .293 .336 72 .099 .333 3.4 -6 -0.4 Gino Cimoli
Matt den Dekker .199 .256 .338 61 .139 .270 2.9 -2 -0.5 Nate Murphy
Johnny Monell .199 .262 .303 55 .103 .263 2.6 -3 -0.5 Chad Moeller
David Wright .204 .289 .293 61 .090 .284 2.8 -4 -0.6 Charlie Hayes
Braxton Lee .224 .289 .281 58 .057 .287 2.5 6 -0.7 Mike Kingery
David Thompson .214 .261 .337 63 .122 .273 3.0 -3 -0.7 Ronald Garth
Ty Kelly .213 .290 .317 67 .104 .272 3.1 -8 -0.7 Kevin Stocker
Cody Asche .211 .282 .353 73 .142 .272 3.3 -8 -0.7 Dave Baker
Kevin Kaczmarski .220 .290 .296 62 .076 .291 2.8 -4 -0.8 Deron McCue
Kevin Taylor .228 .285 .296 60 .068 .268 2.9 2 -0.9 Andre David
Luis Carpio .197 .256 .303 53 .107 .248 2.4 2 -0.9 Vicente Garcia
Desmond Lindsay .176 .254 .280 46 .104 .276 2.0 2 -1.0 Jason Knoedler
Jhoan Urena .207 .269 .334 64 .127 .279 3.0 -3 -1.2 Brian Suarez
Gregor Blanco .219 .291 .316 67 .096 .288 3.2 -13 -1.3 Andy Van Slyke
Tim Tebow .174 .231 .279 39 .105 .282 2.1 -12 -3.1 Colin Porter

Pitchers – Counting Stats
Player T Age W L ERA G GS IP H ER HR BB SO
Jacob deGrom R 31 13 7 2.75 30 30 196.3 164 60 18 45 223
Noah Syndergaard R 26 11 7 3.06 26 26 159.0 148 54 12 38 165
Zack Wheeler R 29 10 8 3.59 27 27 163.0 151 65 16 54 152
Edwin Diaz R 25 4 2 2.36 74 0 72.3 48 19 8 22 115
Steven Matz L 28 7 7 4.07 26 26 132.7 131 60 19 48 126
Jeurys Familia R 29 7 4 2.96 67 0 67.0 55 22 3 27 72
Justin Wilson L 31 5 3 3.21 66 0 53.3 41 19 4 29 71
Walker Lockett R 25 7 9 4.54 26 25 142.7 151 72 21 39 109
Seth Lugo R 29 5 5 4.30 40 12 104.7 105 50 17 29 95
Franklyn Kilome R 24 6 7 4.54 26 26 127.0 128 64 11 71 97
Corey Taylor R 26 4 4 3.80 49 2 68.7 70 29 5 22 47
Luis Avilan L 29 2 2 3.47 67 0 49.3 44 19 4 20 52
Drew Smith R 25 4 4 3.86 52 0 63.0 61 27 5 25 51
Stephen Villines R 23 5 4 3.69 46 0 61.0 53 25 8 22 71
Robert Gsellman R 25 4 4 3.95 71 0 79.7 79 35 8 29 65
Ian Krol L 28 2 2 3.92 51 0 59.7 56 26 6 28 58
Daniel Zamora L 26 2 2 3.79 51 0 54.7 48 23 6 24 61
Chris Flexen R 24 6 8 4.61 21 17 93.7 98 48 14 34 76
AJ Ramos R 32 2 2 3.92 49 0 43.7 36 19 4 26 52
Drew Gagnon R 29 6 7 4.74 31 23 138.7 137 73 22 56 130
Anthony Kay L 24 8 10 4.76 23 23 113.3 114 60 12 69 92
Hector Santiago L 31 5 7 4.81 37 15 112.3 105 60 19 62 108
Jerry Blevins L 35 2 2 3.96 61 0 38.7 35 17 4 19 42
Joshua Torres R 25 4 4 4.18 43 0 56.0 52 26 6 27 55
Eric Hanhold R 25 2 2 4.21 43 0 51.3 50 24 6 22 46
Ryan O’Rourke L 31 1 1 4.28 41 0 33.7 30 16 5 14 39
Tyler Bashlor R 26 3 3 4.25 46 0 53.0 48 25 6 30 55
Arquimedes Caminero R 32 2 2 4.24 46 0 46.7 44 22 6 23 47
Matt Purke L 28 2 3 4.47 40 0 52.3 48 26 4 38 48
Joe Zanghi R 24 2 2 4.35 40 0 60.0 61 29 5 28 43
Tim Peterson R 28 3 3 4.37 50 0 59.7 58 29 11 17 64
Jason Vargas L 36 7 10 5.08 22 22 106.3 113 60 22 33 92
Buddy Baumann L 31 2 2 4.65 35 1 40.7 39 21 6 22 41
Jacob Rhame R 26 3 3 4.45 55 0 62.7 61 31 11 20 67
Zach Lee R 27 7 10 5.00 24 23 126.0 144 70 19 39 77
Joshua Torres R 25 4 5 4.70 39 2 59.3 58 31 9 28 58
Paul Sewald R 29 4 5 4.57 55 0 65.0 64 33 10 22 65
Logan Taylor R 27 1 2 4.91 33 4 47.7 47 26 6 29 43
David Peterson R 29 2 2 4.70 35 0 46.0 51 24 5 17 27
P.J. Conlon L 25 5 8 5.04 25 22 121.3 136 68 19 44 80
Ryder Ryan R 24 3 4 4.70 44 0 51.7 51 27 7 25 48
Cody Martin R 29 4 6 5.24 23 17 91.0 95 53 16 40 79
Kyle Dowdy R 26 8 11 5.25 27 19 111.3 121 65 19 47 87
Chris Mazza R 29 3 5 5.16 21 14 83.7 96 48 13 30 49
Corey Oswalt R 25 6 8 5.19 26 22 111.0 121 64 21 41 88
Aaron Laffey L 34 3 4 5.37 17 9 58.7 69 35 9 21 31
A.J. Griffin R 31 4 6 5.56 19 18 87.3 90 54 20 36 73
Vance Worley R 31 4 6 5.44 25 12 81.0 95 49 13 33 47
Stephen Nogosek R 24 2 3 5.50 42 0 52.3 52 32 8 36 52
David Roseboom L 27 2 3 5.51 43 0 50.7 53 31 10 27 47
Harol Gonzalez R 24 6 11 5.70 23 22 124.7 147 79 23 51 71

Pitchers – Rate Stats
Player TBF K/9 BB/9 HR/9 BABIP ERA+ ERA- FIP WAR No. 1 Comp
Jacob deGrom 789 10.22 2.06 0.83 .292 140 71 2.80 5.0 Kevin Brown
Noah Syndergaard 656 9.34 2.15 0.68 .311 126 79 2.85 3.5 Roy Halladay
Zack Wheeler 691 8.39 2.98 0.88 .293 108 93 3.70 2.6 Bob Rush
Edwin Diaz 289 14.31 2.74 1.00 .288 169 59 2.53 2.5 Antonio Osuna
Steven Matz 575 8.55 3.26 1.29 .299 95 105 4.36 1.3 Doug Davis
Jeurys Familia 281 9.67 3.63 0.40 .294 131 77 2.88 1.3 Claude Jonnard
Justin Wilson 228 11.98 4.89 0.68 .301 124 80 3.15 0.9 Marshall Bridges
Walker Lockett 614 6.88 2.46 1.32 .297 85 118 4.50 0.7 Nick Blackburn
Seth Lugo 445 8.17 2.49 1.46 .293 90 111 4.39 0.6 Danny Graves
Franklyn Kilome 577 6.87 5.03 0.78 .299 85 117 4.59 0.6 Mike Torrez
Corey Taylor 297 6.16 2.88 0.66 .297 102 98 3.86 0.6 Pedro Borbon
Luis Avilan 211 9.49 3.65 0.73 .301 111 90 3.43 0.6 Tippy Martinez
Drew Smith 274 7.29 3.57 0.71 .296 103 97 3.94 0.5 Ray Herbert
Stephen Villines 258 10.48 3.25 1.18 .294 105 95 3.81 0.5 Jorge Julio
Robert Gsellman 346 7.34 3.28 0.90 .297 98 102 4.10 0.5 Chad Kimsey
Ian Krol 263 8.75 4.22 0.91 .299 102 98 4.12 0.4 Tippy Martinez
Daniel Zamora 235 10.04 3.95 0.99 .298 102 98 3.83 0.4 Grant Jackson
Chris Flexen 411 7.30 3.27 1.35 .298 84 119 4.72 0.3 Michael Macdonald
AJ Ramos 192 10.72 5.36 0.82 .296 99 101 3.88 0.3 Heathcliff Slocumb
Drew Gagnon 606 8.44 3.63 1.43 .294 82 123 4.70 0.3 Dan Petry
Anthony Kay 522 7.31 5.48 0.95 .298 81 123 4.91 0.2 Greg Kubes
Hector Santiago 501 8.65 4.97 1.52 .280 83 121 5.22 0.2 Ray Searage
Jerry Blevins 170 9.78 4.42 0.93 .304 98 102 4.03 0.2 Marshall Bridges
Joshua Torres 247 8.84 4.34 0.96 .297 92 108 4.24 0.2 Joe Hudson
Eric Hanhold 225 8.06 3.86 1.05 .297 92 109 4.34 0.1 Casey Daigle
Ryan O’Rourke 144 10.43 3.74 1.34 .294 93 107 4.10 0.1 Bob McClure
Tyler Bashlor 237 9.34 5.09 1.02 .296 91 110 4.47 0.1 Clay Bryant
Arquimedes Caminero 207 9.06 4.44 1.16 .297 91 110 4.48 0.1 Dennis Higgins
Matt Purke 242 8.25 6.54 0.69 .295 89 112 4.66 0.0 Jim Roland
Joe Zanghi 268 6.45 4.20 0.75 .298 89 113 4.40 0.0 Gary Ross
Tim Peterson 253 9.65 2.56 1.66 .297 88 113 4.41 0.0 Jack Krawczyk
Jason Vargas 461 7.79 2.79 1.86 .294 79 127 5.15 0.0 Chris Michalak
Buddy Baumann 182 9.07 4.87 1.33 .297 86 117 4.82 0.0 Tim Adkins
Jacob Rhame 267 9.62 2.87 1.58 .299 87 115 4.35 0.0 Rick Anderson
Zach Lee 558 5.50 2.79 1.36 .300 77 129 4.98 -0.1 A.J. Sager
Joshua Torres 264 8.80 4.25 1.37 .297 82 122 4.78 -0.1 Joe Davenport
Paul Sewald 279 9.00 3.05 1.38 .300 85 118 4.26 -0.1 Brian Edmondson
Logan Taylor 219 8.12 5.48 1.13 .297 79 127 5.00 -0.2 Ken Wright
David Peterson 204 5.28 3.33 0.98 .301 82 122 4.63 -0.2 Jim Todd
P.J. Conlon 540 5.93 3.26 1.41 .299 77 131 5.10 -0.2 Jason Dickson
Ryder Ryan 231 8.36 4.35 1.22 .299 82 122 4.74 -0.2 Joe Davenport
Cody Martin 406 7.81 3.96 1.58 .297 76 131 5.18 -0.2 Robert Ellis
Kyle Dowdy 501 7.03 3.80 1.54 .299 76 132 5.26 -0.3 Peter Bauer
Chris Mazza 375 5.27 3.23 1.40 .299 75 134 5.25 -0.3 Jim Owens
Corey Oswalt 494 7.14 3.32 1.70 .297 74 134 5.32 -0.4 Sean Lawrence
Aaron Laffey 264 4.76 3.22 1.38 .300 72 139 5.31 -0.4 Jose Santiago
A.J. Griffin 387 7.52 3.71 2.06 .277 72 140 5.86 -0.5 Jackson Todd
Vance Worley 368 5.22 3.67 1.44 .303 71 141 5.45 -0.6 Karl Drews
Stephen Nogosek 244 8.94 6.19 1.38 .303 72 138 5.39 -0.6 Jeff Kennard
David Roseboom 231 8.35 4.80 1.78 .299 70 143 5.64 -0.7 Wes Pierorazio
Harol Gonzalez 569 5.13 3.68 1.66 .297 68 148 5.81 -1.2 Mark Mangum

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 2019. 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 I have made a mistake. This is very possible, as a lot of minor-league signings go generally unreported in the offseason.

ZiPS’ projections are based on the American League having a 4.29 ERA and the National League having a 4.15 ERA.

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

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


Job Posting: Dodgers Associate Quantitative Analyst

Position: Associate Quantitative Analyst

Department: Baseball Research & Development
Status: Part-Time
Reports to: Director, Quantitative Analysis
Deadline: March 1, 2019

Description:
The Los Angeles Dodgers are seeking an Associate Quantitative Analyst for the team’s Research & Development group within Baseball Operations. This position will run for 12 weeks during the 2019 MLB season.

Job Functions:

  • Develop statistical/machine learning models to support player evaluation, development, and strategic decision-making
  • Perform ad hoc data analysis to answer urgent questions from the front office and other groups within Baseball Operations
  • Prepare reports and presentations to track progress and disseminate model/analysis results
  • Collaborate with other members of the Analytics team and organizational relationship-building

Basic Requirements/Qualifications:

  • Pursuing a degree in Mathematics, Statistics, Computer Science, Operations Research, or a related quantitative field
  • Knowledge of recent advances within the public baseball research community
  • Experience building and validating mathematical, statistical, and/or machine learning models, preferably in Python or R
  • Some computer programming experience
  • Familiarity with SQL
  • Proficient in Microsoft Office
  • Excellent analytical and problem-solving skills
  • Desire to work in a collaborative team environment

When applying for this position, please include answers to following questions in your cover letter, using 500 words or fewer:

  • What dates are you available for this internship?
  • Based on published baseball research and blogs, what areas are worth performing further research on, and would it be beneficial to a team/players, etc. Why?
  • What experience do you have building mathematical and/or statistical models?

Additionally, if you are enrolled in a university degree program, please include with your application, a complete list of the technical courses that you have taken or in which you are currently enrolled, along with course numbers and grades.

To Apply:
To apply, please visit this site and complete the application.

The Dodgers are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.

The content in this posting was created and provided solely by the Los Angeles Dodgers.


Job Posting: Giants Baseball Operations

Please note, this posting contains three positions.

Position: Baseball Operations Analyst

Reports To: Director of Baseball Analytics
Department: Baseball Operations
Status: Full-Time/Exempt
Location: Scottsdale, Arizona

Position Summary:
The San Francisco Giants are seeking an Analyst to join the Baseball Operations department. This individual will be part of the R&D team and provide research and analysis to support the front office and player development staff. This position will also work closely with the application development team to design and develop statistical models and tools using advanced data sources within new and existing applications. The ideal candidate will possess strong analytical skills, the ability to communicate effectively to non-technical people, and both passion and intellectual curiosity for the game of baseball.

Position Responsibilities:

  • Provide statistical analysis and quantitative research to support Baseball Operations staff
  • Communicate analysis to Baseball Operations staff effectively
  • Research, design, and test predictive and statistical models using data and technology to support all aspects of Baseball Operations
  • Collaborate with application development team to design and integrate analytic tools into existing baseball information system
  • Maintain understanding of new public baseball research and emerging statistical tools, as well as all potential vendor data/technology options

Knowledge and Skills:

  • Bachelor’s degree in computational field, such as statistics, engineering, computer science, or applied math
  • Proficiency with SQL and relational databases (Microsoft SQL preferred)
  • Bilingual in Spanish is a plus.
  • Experience with additional programming languages (e.g. R, Python) is strongly preferred
  • Understanding of statistical modeling and machine learning techniques
  • Ability to communicate effectively to all members of Baseball Operations
  • Passion for baseball, intellectual curiosity, and understanding of sabermetric concepts
  • Ability to work evenings, weekends, holidays, and travel as dictated by the baseball calendar
  • Must be willing to travel extensively

To Apply:
To apply, please submit your cover letter and resume here. The deadline to apply is February 15, 2019.

Position: Data Scientist

Reports To: Director of Baseball Analytics
Department: Baseball Operations
Status: Full-Time/Exempt

Position Summary:
The San Francisco Giants are seeking a Data Scientist to join the Baseball Operations department. This individual will be part of the R&D team and develop advanced predictive models to support front office and in-game decision making. This position will also work closely with the application development team to integrate these decision-support tools into new and existing applications. The ideal candidate will possess advanced data modeling skills, the ability to communicate effectively to non-technical people, and both passion and intellectual curiosity for the game of baseball.

Position Responsibilities:

  • Research, design, and test predictive and statistical models using data and technology to support all aspects of Baseball Operations
  • Collaborate with application development team to design and integrate decision-support systems and tools into baseball information system
  • Share technical expertise with junior members of department
  • Maintain understanding of new public baseball research and emerging statistical tools, as well as all potential vendor data/technology options
  • Communicate findings to Baseball Operations staff effectively
  • Stay abreast of ongoing technical and baseball research

Knowledge and Skills:

  • Graduate degree in computational field, such as computer science, statistics, engineering, or applied math
  • Four years of work experience in mathematical, statistical, and predictive modeling
  • Understanding of statistical modeling and machine learning techniques
  • Expertise in programming languages (e.g. R, Python)
  • Proficiency with SQL and relational databases
  • Ability to communicate effectively to all members of the Baseball Operations staff
  • Passion for baseball, intellectual curiosity, and understanding of sabermetric concepts

To Apply:
To apply, please submit your cover letter and resume here. The deadline to apply is February 15, 2019.

Position: Sports Science Analyst

Reports To: Director of Baseball Analytics
Department: Baseball Operations
Status: Full-Time/Exempt

Position Summary:
The San Francisco Giants are seeking a Sports Science Analyst to join the Baseball Operations department. This individual will be part of the R&D team and provide research and analysis to support the medical, training, and player development staffs. This position will also work closely with the application development team to design and develop statistical models and tools using advanced data sources within new and existing applications. The ideal candidate will possess a strong foundation with advanced training in performance science disciplines, strong analytical skills, the ability to communicate effectively to non-technical people, and both passion and intellectual curiosity for the game of baseball.

Position Responsibilities:

  • Collaborate with medical and training staffs to integrate performance tracking information into sports science, injury prevention and training programs
  • Collect and manage sports science data sources across the Giants organization
  • Provide analysis and reporting on sports science data to optimize player performance and minimize injury risk
  • Explore new sports science technologies and maintain knowledge of public research to provide innovative value to the organization
  • Conduct quantitative research to support ad-hoc requests from Medical staff to improve decision-making process
  • Work with application development and analytics teams to integrate data sources into internal information systems

Knowledge and Skills:

  • Work experience and/or degree in analytical field, such as statistics, computer science, applied math, or engineering
  • Foundational knowledge in performance science disciplines, including biomechanics, sports medicine, exercise physiology, and/or athletic training
  • Experience working with large data sets
  • Interest and comfort working with new performance tracking technology
  • Familiarity with programming languages and concepts is a plus
  • Ability to communicate effectively to all members of the Baseball Operations and Medical staffs

To Apply:
To apply, please submit your cover letter and resume here. The deadline to apply is February 15, 2019.

The Giants are an equal employment opportunity employer and consider applicants for all positions regardless of race, religious creed, color, national origin, ancestry, medical condition or disability, genetic condition, marital status, domestic partnership status, sex, gender, gender identity, gender expression, age, sexual orientation, military or veteran status and any other protected class under federal, state or local law. Pursuant to the San Francisco Fair Chance Ordinance, they will consider for employment qualified applicants with arrest and conviction records. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

The content in this posting was created and provided solely by the San Francisco Giants.


Effectively Wild Episode 1329: Statheaded Elsewhere

EWFI
Ben Lindbergh and ESPN’s Sam Miller banter about offseason content-creation strategies, recurring columns, and an alternate history in which Orlando Cepeda could have prevented writers from citing stats in stories, then (21:45) talk to longtime Baseball Prospectus writer (and author of The Shift) Russell Carleton about his departure from BP to take a job with the New York Mets, his most influential articles, what he learned from his previous MLB consulting gig, the evolution of sabermetric analysis, critical thinking vs. technical skills, and more.

Audio intro: Margo Price, "Don’t Say It"
Audio interstitial: The Posies, "Farewell Typewriter"
Audio outro: Van Morrison, "Starting a New Life"

Link to Hirsch’s Mays bio
Link to Russell and Kate’s front-office series
Link to Russell on the 30-run manager
Link to Russell on Inge
Link to Russell on the grind
Link to Russell on statistical stability
Link to Russell on player development
Link to Russell on feeding minor leaguers
Link to Russell on intentional walks
Link to preorder The MVP Machine

 iTunes Feed (Please rate and review us!)
 Sponsor Us on Patreon
 Facebook Group
 Effectively Wild Wiki
 Twitter Account
 Get Our Merch!
 Email Us: podcast@fangraphs.com


Effectively Wild Episode 1328: National Past Time

EWFI
Ben Lindbergh and Jeff Sullivan banter about players playing for their lives, Bryce Harper rumors, Harper’s fame vs. Mike Trout’s, feeling less intense anticipation than they used to, the Red Sox signing the previously permabanned Jenrry Mejia, and uncertainty surrounding the latest labor strife. Then (30:06) Ben talks to Chris Enns, author of The Death Row All Stars, about baseball in the Old West and the strange saga of the 1911 Wyoming State Penitentiary team, an all-convict squad that played to stave off execution and caused a statewide scandal. Lastly (1:00:21), Jeff rejoins for a conversation with Wes Abarca (co-founder, commissioner, and Crestline Highlanders captain) and Joe Billheimer (Highlanders “behind”) of the Southern California Vintage Base Ball League to discuss the popularity of vintage baseball, the strategic intricacies of playing under 1886 rules, the challenge of playing with period equipment, the importance of staying in character, whether they prefer old or new baseball, and more.

Audio intro: Spoon, "Something to Look Forward To"
Audio interstitial 1: Skip James, "Hard Time Killing Floor Blues"
Audio interstitial 2: Paul McCartney, "Vintage Clothes"
Audio outro: Dr. Dog, "Survive"

Link to Rosenthal article
Link to Ben’s old article about the MLB revenue split
Link to Chris Enss site
Link to Conan’s vintage baseball video
Link to Vintage Base Ball Association site
Link to SoCal Vintage Base Ball League site
Link to Crestline Highlanders site
Link to SoCal league video
Link to Highlanders game photo album
Link to SCVBB Rules
Link to preorder The MVP Machine

 iTunes Feed (Please rate and review us!)
 Sponsor Us on Patreon
 Facebook Group
 Effectively Wild Wiki
 Twitter Account
 Get Our Merch!
 Email Us: podcast@fangraphs.com


The Diamondbacks Will Try to Create a Center Fielder

Last season, the Diamondbacks were one of the best defensive teams in either league. In the end, it wasn’t enough to get them to the playoffs, but it took a September collapse for them to fall out of first place. Arizona finished first by a large margin in Defensive Runs Saved. They weren’t quite so good by Ultimate Zone Rating, but that also doesn’t give them credit for their quality work behind the plate. Looking at Statcast’s difference between actual and expected wOBA allowed, the Diamondbacks finished behind only the A’s. It wasn’t a perfect season in the desert, but it wasn’t the defense that let them down.

Now we’re looking at a team in transition. There’s no easy way to lose Paul Goldschmidt. There’s no easy way to lose A.J. Pollock. There’s no easy way to lose Patrick Corbin. The expectations for the Diamondbacks aren’t going to be high, because of the talent they’ve already lost. Given that, they’ve turned into an easy team to overlook. But it’s interesting to see what’s been going on this offseason. After how good the defense just was, the Diamondbacks are moving forward without Jeff Mathis. They’re going to have Jake Lamb try to learn first base. Wilmer Flores is going to take over at second base. And Ketel Marte is moving to center field. For the second offseason in a row, a team is going to try to plug a hole in center with a second baseman.

Read the rest of this entry »


Greg Holland Takes a Pay Cut

The last 15 months have not gone particularly well for Greg Holland. Coming off a solid return from Tommy John surgery with the Rockies in 2017 — albeit one with a lesser second half than first — he bypassed a reported multiyear offer to return, then was met with a frosty reception amid a free agent market that was generally more hospitable to relievers than other players. He finally signed a one-year, $14 million deal with the Cardinals after Opening Day, but struggled to the point of being released on August 1. After salvaging his season at least somewhat with a strong showing with the Nationals over the final two months, he hit free agency again. On Monday, the 33-year-old righty reportedly agreed to a one-year, $3.5 million-plus-incentives deal with the Diamondbacks, pending a physical. It’s a living, but ouch.

Admittedly, it’s suboptimal to carry a season with a 4.99 ERA, 3.83 FIP, 0.3 WAR, and just three saves into a market flooded with alternatives coming off stronger showings, but one might have thought that the Scott Boras client could have built upon his late-season resurgence in Washington and the lack of a qualifying offer this time around. Then again, it was presumably Boras’ misread of Holland’s market last winter that got him into this jam in the first place. At least this time, he’s going to spring training.

By not signing until two days after Opening Day last year — and that only after Luke Gregerson was lost to a hamstring injury — Holland missed the entirety of exhibition season, and after making just a pair of tune-up appearances with the Cardinals’ Hi-A Palm Beach affiliate, he walked four out of the five batters he faced in his April 9 debut. He didn’t get his first save chance until April 27, but he blew that, and he never assumed the full-time closer role. He never found his control in St. Louis, and a three-week stint on the disabled list for impingement in his right hip, from late May to mid-June, didn’t help. All told, in 32 appearances totaling 25 innings with the Cardinals, his walk, strikeout, and earned run totals were identical: 22 (7.92 per nine) — not what you want. Six days after being released, he joined the Nationals, and at least righted the ship, posting a 0.84 ERA and 2.97 FIP while striking out 31.3% of hitters in 21.1 innings as the team played out the string.

The key, or at least one of them, was a more reliable slider that generated more chases and less zone contact when he backed off using it quite so heavily:


 
According to Brooks Baseball, while with St. Louis, Holland’s slider was hit for a .268 average and .357 slugging percentage, with a 19.8% whiff rate (37.3% whiffs per swing), while with Washington, the slider yielded an .081 batting average (all singles) with a 25.2% whiff rate (48.5% whiffs per swing). His fastball became less of a meatball with the transition as well (.342 AVG/.463 SLG before, .208/.375 after, with a whiff rate climbing from 4.2% to 10.7%); via Baseball Savant, his xwOBA dropped from .354 with the Cardinals to .239 with the Nationals. Granted, we’re dealing with small samples in terms of innings and pitches, with the latter ranging from 30 plate appearances ending with fastballs in Washington to 60 PA ending with sliders in St. Louis, but whatever changed did seem to work, allowing him to recover his first-half 2017 form — when he earned All-Star honors with the Rockies — if not his magic with the Royals. Life is just different when your fastball averages 92.9 mph instead of 96.9 (his average in 2013, according to Pitch Info).

On that note, it’s worth a brief historical review. Once upon a time, Holland ranked among the game’s elite relievers. From 2011 — his first full season in the majors — to 2014, he posted ERAs below 2.00 three times out of four, with FIPS below 2.00 twice. Over that span, only three pitchers (Craig Kimbrel, Eric O’Flaherty, and Wade Davis) outdid his 1.86 ERA, and only Kimbrel surpassed his 1.92 FIP and 9.1 WAR. In August 2012, he assumed the closer duties for the Royals, and over the next two seasons became a key part of their march to respectability, aided by a dominant bullpen. He made the All-Star team in both 2013 and ’14, ranking second in the AL in saves each year. In 2013, he led all relievers in FIP (1.36) while ranking second in WAR (3.0), while in 2014, after placing within the top handful in ERA, FIP, and WAR, he went 7-for-7 in saves while yielding just one run and four hits in 11 innings while striking out 15 during the Royals’ postseason run.

Holland did not get to pitch during the Royals’ 2015 championship run. His velocity dipped from its typical 95-96 mph average into the low 90s in late August, and he was soon discovered to have suffered a partial tear in his ulnar collateral ligament. He tried to pitch through it — reportedly, he had been experiencing elbow discomfort as far back as August 2014 — but went to the sidelines in mid-September, yielding the closer’s job to Davis, and on October 2 went under the knife. He didn’t re-emerge until signing a one-year, $7 million contract with the Rockies in January 2017, a deal that included a mutual option, more on which momentarily.

Holland burst out of the gate in 2017, converting 23 straight save chances with a 1.09 ERA through June 14. He made the NL All-Star team on the strength of a 1.62 ERA and 2.80 FIP; a dreadful 9.1-inning, 14-run stretch in August blew up his second-half stats (6.38 ERA, 4.99 FIP), but he helped the Rockies snag an NL Wild Card berth, and finished with a league-high 41 saves along with a 3.61 ERA and 3.72 FIP (72 ERA- and 81 FIP-).

When Holland signed with the Rockies, he had a $10 million mutual option for 2018, with a $1 million buyout. By reaching either 50 games pitched or 30 games finished, that option converted into a $15 million player option, about on par with his total take in 2017 ($15.1 million) thanks to his having earned $9.1 million in incentive bonuses thanks to his 61 appearances, 58 games finished, and 2017 NL Comeback Player of the Year award. Holland declined the option and the $17.4 million qualifying offer that followed. Later he reportedly snubbed a three-year, $51 or $52 million deal from the Rockies, though whether that was a firm offer or a “conceptual” one (as Buster Olney phrased it) is up for debate. The Rockies instead signed Davis to a three-year, $52 million deal in late December — thanks, old pal — and a better offer apparently never came Holland’s way.

Hence, the mess in which Holland wound up, though he was hardly alone in misreading the market. The exact details of his new contract are unknown at this writing, but he can earn a maximum of $3.5 million in incentives, some of which probably depend upon his returning to closer duty. With Brad Boxberger departed in free agency (unsigned at this writing, actually), it’s not clear yet whether he or Archie Bradley, who excelled in a setup role, will be manager Torey Lovullo’s top ninth-inning choice. If Holland can stay healthy and maintain his old form, he stands to be quite a bargain for the Snakes regardless of his role, but one can’t help imagining that if he could play out the last year-and-change again, he’d be in a much better position than he is today.


Ryne Stanek Rode Spin Efficiency to New Heights

Ryne Stanek was the Tampa Bay Rays’ most-frequently-used opener in 2018. The 27-year-old right-hander made 29 such appearances, throwing two-or-fewer-innings on each occasion. He was also utilized as a conventional reliever. Stanek strolled out of the bullpen 30 such times, usually in the seventh or eighth inning.

He was good in both roles. All told, the former Arkansas Razorback logged a 2.98 ERA while allowing just 45 hits and fanning 81 in 66.1 frames.

Usage aside, he’s a very different pitcher than he once was. Drafted 29th overall by the Rays in 2013, Stanek was originally groomed as a starter. Moreover, his M.O. was to locate his high-octane heater down in the zone. Ground balls were a goal.

His two-seamer became history a few years ago. A dip, followed by a rise, played a role. So did TrackMan readings.

“Coming off hip surgery [in December 2013], my velo was down a lot from what it had been,” explained Stanek. “I don’t know why, it just was. I’d thrown all two-seams in college, and I think my sinker played pretty well, but when I started throwing harder again, they decided a four-seamer would be a better weapon.”

Stanek’s four-seam spin rate was in the 81st percentile (per StatCast) this past season. His average velocity with the pitch was a crisp 98.4 mph, and he’s reportedly been clocked as high as 103. Read the rest of this entry »


Kiley McDaniel Chat – 1/30/19

12:05

Kiley McDaniel: Hello friends and also other people, it is time for us to chat

12:05

Kiley McDaniel: ICYMI, we posted an Orioles list and tomorrow we’ll be posting the Yankees list, but I’m taking a quick break from writing reports to chat with you people. Here’s the prospects index page with anything you may need from us: https://www.fangraphs.com/prospects/

12:05

Tommy N.: Mejia, Morejon, Renfroe too much for Realmuto if he doesn’t want an extension?

12:06

Kiley McDaniel: I don’t think Realmuto is being traded with an understanding he’ll sign an extension with the new team. I get the impression this is a 2-year rental and then he hits the market and maybe he likes his two years with you enough to give you a slight discount when everyone is bidding.

12:07

Kiley McDaniel: And that package isn’t insane, I’m not sure SD wants to pay that much and I don’t have a sense for if the market has cratered enough that you have to pay as much as we thought some teams may at the beginning of the offseason

12:07

Jeremy: How do you evaluate Yusei Kikuchi against other guys in his (likely) 55 FV bracket, like Chris Paddack, Brent Honeywell or Mitch Keller? Clearly higher ceiling and lower floor, but would that change his FV as well?

Read the rest of this entry »