2017 ZiPS Projections – Tampa Bay Rays

After having typically appeared in the very famous pages of Baseball Think Factory, Dan Szymborski’s ZiPS projections have been released at FanGraphs the past few years. The exercise continues this offseason. Below are the projections for the Tampa Bay Rays. Szymborski can be found at ESPN and on Twitter at @DSzymborski.

Other Projections: Arizona / Atlanta / Chicago NL / Cleveland / Detroit / Houston / San Diego / Toronto / Washington.

Batters
Due to their limited resources, the Rays have been compelled to search for value in places where it isn’t readily apparent. These financial constraints, for example, led pretty directly to the phenomenon known as Ben Zobrist, Improbable Superstar. The ascent of Kevin Kiermaier (502 PA, 4.2 zWAR) is almost equally improbable as Zobrist’s, though. Selected in the 31st round of the 2010 draft out of Parkland College, Kiermaier has now averaged more than four wins per season over his first three major-league campaigns. Much of that value, of course, is a product of Kiermaier’s defensive acumen. ZiPS calls for more of the same in that regard, projecting Kiermaier to save 17 more runs than the average center fielder.

With the exception of Evan Longoria (658, 3.9), unfortunately, the club doesn’t currently employ any field players who profile as anything much better than average — and the short-term prognosis for newly acquired Wilson Ramos (465, 2.5), one of only four batters who receives a forecast for more than two wins, is uncertain in light of the season-ending injury he suffered at the end of 2016.

Pitchers
Please note, while regarding the depth-chart image below, that the members of the Rays’ starting rotation are arranged in order of projected WAR, not in the order they’re likely to be deployed by manager Kevin Cash. Here’s why such a note is relevant: owing to his youth and relative inexperience, left-hander Blake Snell (148.0 IP, 2.5 zWAR) isn’t expected to enter the 2017 season as Tampa Bay’s No. 3 starter. That he’s qualifed to fill such a role, however, is an argument one could make based on the numbers produced by Dan Szymborski’s computer. Another argument one could make is that Chris Archer (195.1, 4.1) is more likely to resemble the 2015, and not 2016, version of himself this next year.

The Rays bullpen produced the second-fewest collective wins in the league last year by the version of WAR calculated with fielding-independent pitching (FIP-WAR) and finished among the bottom third of all clubs by the version of WAR calculated with runs allowed (RA9-WAR). That’s poor. While the group here doesn’t seem to profile as obviously elite, they do look something much closer to average than their 2016 numbers would suggest. Alex Colome (61.1, 1.0) receives the top projection.

Bench/Prospects
First baseman Jake Bauers (581 PA, 1.6 zWAR) enters just his age-21 season, but possesses the top projection among all Tampa Bay field players unlikely to appear in the club’s starting lineup. Like Bauers, infielders Willy Adames (534, 1.2) and Daniel Robertson (475, 1.3) also have recorded zero plate appearances. Per ZiPS, however, they already offer the value of a competent major-league bench player.

Among pitchers, Matt Andriese (143.0 IP, 2.3 zWAR) receives a distinctly positive forecast — that of a slightly above-average starter — for a player who both (a) recorded a considerable quantity of innings this past year but (b) is nevertheless likely to begin this next year at Triple-A. He provides excellent depth for the rotation. Right-hander Brent Honeywell (127.1, 1.0) earns the top WAR projections among pitching prospects. He spoke with Eno Sarris at the Arizona Fall League about his screwball.

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

rays-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
Kevin Kiermaier L 27 CF 502 63 118 22 8 13 46 18 5
Evan Longoria R 31 3B 658 79 160 36 3 30 88 1 2
Wilson Ramos R 29 C 465 43 113 17 0 17 64 0 0
Logan Forsythe R 30 2B 496 61 115 21 3 15 50 6 4
Matt M. Duffy R 26 SS 512 59 120 20 3 11 51 11 3
Jake Bauers L 21 RF 581 73 132 26 2 18 71 8 6
Brad Miller L 27 1B 538 66 120 23 5 20 66 7 4
Corey Dickerson L 28 LF 460 51 107 27 3 19 55 3 3
Daniel Robertson R 23 SS 475 50 102 18 3 6 38 2 2
Steven Souza R 28 RF 442 58 96 17 1 17 48 11 6
Willy Adames R 21 SS 534 61 109 22 4 12 50 8 4
Desmond Jennings R 30 LF 311 36 65 14 2 8 27 8 3
Nick Franklin B 26 2B 463 51 98 19 2 12 49 10 2
Casey Gillaspie B 24 1B 479 62 104 20 1 18 57 3 1
Ryan Brett B 24 2B 420 46 96 18 3 8 35 12 6
Curt Casali R 28 C 311 34 57 11 0 9 30 0 0
Tim Beckham R 27 SS 264 29 57 11 4 6 25 3 3
Luke Maile R 26 C 364 36 70 16 1 5 32 1 1
Hank Conger B 29 C 246 21 47 11 1 7 26 0 1
Johnny Field R 25 CF 487 53 104 25 3 12 50 12 5
Justin O’Conner R 25 C 286 27 56 12 1 8 27 2 1
J.P. Arencibia R 31 C 371 40 77 14 0 18 52 0 1
Mike Marjama R 27 C 329 34 76 17 2 7 33 2 2
Cade Gotta R 25 RF 372 38 80 18 2 6 34 14 5
Dayron Varona R 29 RF 426 45 95 22 3 12 49 7 5
Logan Morrison L 29 1B 434 49 94 18 2 13 48 5 3
Justin Williams L 21 RF 461 48 110 21 2 12 50 2 2
Eury Perez R 27 LF 322 32 72 9 3 3 23 18 6
Mikie Mahtook R 27 CF 461 47 97 20 3 9 40 9 3
Jake Goebbert L 29 LF 401 47 79 14 2 10 41 2 2
Joe McCarthy L 23 1B 382 42 80 14 2 7 35 13 5
Alexei Ramirez R 35 SS 542 51 127 25 2 8 52 14 7
Kean Wong L 22 2B 511 48 114 19 2 5 40 10 10
Jake Hager R 24 2B 511 44 107 20 2 3 34 6 5

***

Batters, Rates and Averages
Player PA BB% K% ISO BABIP AVG OBP SLG wOBA
Kevin Kiermaier 502 7.0% 18.9% .168 .298 .258 .316 .426 .328
Evan Longoria 658 6.8% 21.7% .219 .298 .266 .318 .485 .334
Wilson Ramos 465 5.4% 18.1% .156 .284 .260 .299 .416 .304
Logan Forsythe 496 8.1% 20.4% .162 .302 .259 .329 .421 .329
Matt M. Duffy 512 5.9% 18.6% .125 .295 .255 .304 .380 .301
Jake Bauers 581 8.4% 20.7% .162 .294 .253 .320 .415 .322
Brad Miller 538 8.6% 23.0% .192 .291 .248 .313 .440 .328
Corey Dickerson 460 6.5% 25.9% .210 .302 .251 .300 .461 .322
Daniel Robertson 475 8.0% 21.3% .099 .301 .241 .316 .340 .294
Steven Souza 442 8.6% 32.1% .177 .329 .242 .314 .419 .328
Willy Adames 534 9.2% 32.4% .137 .327 .228 .300 .365 .296
Desmond Jennings 311 9.0% 21.5% .153 .282 .236 .312 .389 .312
Nick Franklin 463 8.4% 24.8% .141 .294 .235 .302 .376 .299
Casey Gillaspie 479 9.6% 26.1% .178 .300 .244 .319 .422 .322
Ryan Brett 420 4.0% 21.7% .121 .295 .244 .282 .365 .291
Curt Casali 311 10.0% 28.9% .139 .274 .209 .298 .348 .285
Tim Beckham 264 6.1% 29.5% .152 .319 .236 .286 .388 .295
Luke Maile 364 6.0% 22.5% .099 .259 .208 .260 .307 .250
Hank Conger 246 7.7% 25.2% .153 .260 .212 .279 .365 .280
Johnny Field 487 4.9% 27.1% .148 .296 .231 .278 .379 .292
Justin O’Conner 286 2.8% 36.7% .138 .294 .204 .231 .342 .249
J.P. Arencibia 371 2.7% 33.4% .191 .274 .217 .245 .408 .279
Mike Marjama 329 3.0% 21.0% .134 .289 .243 .271 .377 .281
Cade Gotta 372 5.6% 23.7% .115 .290 .231 .275 .346 .281
Dayron Varona 426 2.8% 22.1% .158 .275 .235 .265 .393 .289
Logan Morrison 434 9.0% 18.0% .157 .271 .242 .318 .399 .313
Justin Williams 461 2.4% 23.9% .137 .301 .247 .267 .384 .281
Eury Perez 322 4.0% 19.9% .081 .301 .243 .289 .324 .284
Mikie Mahtook 461 5.2% 28.4% .124 .304 .228 .278 .352 .279
Jake Goebbert 401 9.2% 24.9% .135 .275 .221 .297 .356 .288
Joe McCarthy 382 8.6% 20.2% .116 .285 .238 .318 .354 .307
Alexei Ramirez 542 3.9% 12.0% .103 .268 .247 .279 .350 .281
Kean Wong 511 4.9% 19.4% .080 .292 .241 .278 .321 .269
Jake Hager 511 4.3% 24.3% .069 .293 .223 .259 .292 .245

***

Batters, Assorted Other
Player PA RC/27 OPS+ Def zWAR No.1 Comp
Kevin Kiermaier 502 5.1 105 17 4.2 Ken Landreaux
Evan Longoria 658 5.6 120 -1 3.9 Gary Gaetti
Wilson Ramos 465 4.5 97 1 2.5 Shanty Hogan
Logan Forsythe 496 5.0 108 0 2.5 Junior Spivey
Matt M. Duffy 512 4.3 90 -2 1.7 Jason Bartlett
Jake Bauers 581 4.7 103 2 1.6 Nick Markakis
Brad Miller 538 4.9 108 3 1.5 Ben Broussard
Corey Dickerson 460 4.9 109 1 1.4 Kevin Reimer
Daniel Robertson 475 3.8 84 0 1.3 Pedro Castellano
Steven Souza 442 4.7 103 1 1.3 Jack Voigt
Willy Adames 534 3.8 85 -3 1.2 Alex Gonzalez
Desmond Jennings 311 4.4 95 6 1.2 Melvin Mora
Nick Franklin 463 4.2 88 -2 1.0 Jay Canizaro
Casey Gillaspie 479 4.8 105 0 1.0 Mo Vaughn
Ryan Brett 420 3.7 78 2 0.7 John Wehner
Curt Casali 311 3.5 80 -3 0.7 B.J. Waszgis
Tim Beckham 264 3.8 86 -1 0.6 Chris Woodward
Luke Maile 364 2.7 58 5 0.6 Brian Moon
Hank Conger 246 3.4 78 -2 0.5 Alan Ashby
Johnny Field 487 3.7 81 -3 0.4 Jim Lindeman
Justin O’Conner 286 2.7 57 3 0.3 Johnny Cuevas
J.P. Arencibia 371 3.4 78 -7 0.3 Dave Duncan
Mike Marjama 329 3.6 79 -6 0.2 Edwin Bellorin
Cade Gotta 372 3.5 72 6 0.2 Kyle Logan
Dayron Varona 426 3.6 81 4 0.2 Nate Grindell
Logan Morrison 434 4.5 99 -3 0.1 Brad Bierley
Justin Williams 461 3.6 79 4 0.1 Pedro Valdes
Eury Perez 322 3.6 71 4 0.0 Peter Bergeron
Mikie Mahtook 461 3.5 75 -3 0.0 Joaquin Contreras
Jake Goebbert 401 3.6 82 1 0.0 Pat Brady
Joe McCarthy 382 4.1 88 0 0.0 Tom Lombarski
Alexei Ramirez 542 3.5 75 -9 -0.3 Bill Russell
Kean Wong 511 3.0 67 -1 -0.6 Gregorio Petit
Jake Hager 511 2.5 54 -1 -1.4 Travis Hanson

***

Pitchers, Counting Stats
Player T Age G GS IP K BB HR H R ER
Chris Archer R 28 32 32 195.3 222 64 20 168 79 74
Jake Odorizzi R 27 31 31 177.3 166 53 21 164 78 73
Blake Snell L 24 30 29 148.0 170 72 16 131 65 61
Matt Andriese R 27 36 22 143.0 126 30 16 140 63 59
Drew Smyly L 28 26 25 143.0 141 41 19 133 66 62
Alex Cobb R 29 17 17 102.0 85 35 11 100 47 44
Brent Honeywell R 22 25 25 127.3 104 36 17 130 66 62
Alex Colome R 28 61 0 61.3 73 17 7 51 21 20
Chase Whitley R 28 18 12 62.7 53 18 8 63 31 29
Jacob Faria R 23 25 24 131.3 124 66 17 125 73 68
Austin Pruitt R 27 26 25 142.0 101 34 21 154 79 74
Chih-Wei Hu R 23 24 23 125.7 89 42 17 134 71 66
Xavier Cedeno L 30 55 0 42.3 47 13 5 37 17 16
Danny Farquhar R 30 65 0 73.7 72 24 9 69 33 31
Brad Boxberger R 29 54 0 51.3 66 25 7 42 22 21
Jaime Schultz R 26 24 24 107.3 116 68 15 99 61 57
Adam Wilk L 29 21 19 113.0 79 31 17 124 64 60
Hunter Wood R 23 24 15 98.3 86 45 13 97 56 52
Jaye Chapman R 30 44 0 44.7 45 15 6 42 20 19
Diego Moreno R 29 33 2 58.3 51 21 7 57 29 27
Andrew Kittredge R 27 39 3 77.7 67 27 10 77 40 37
Dana Eveland L 33 45 3 55.3 47 21 6 56 28 26
Kevin Gadea R 22 21 0 27.7 29 10 3 25 13 12
Erasmo Ramirez R 27 66 0 86.0 52 25 11 90 42 39
Justin Marks L 29 26 16 103.7 81 48 14 107 60 56
Taylor Guerrieri R 24 23 22 112.7 69 41 16 123 66 62
Kevin Jepsen R 32 65 0 56.3 51 23 7 54 28 26
Jonny Venters L 32 10 0 10.3 8 5 1 11 5 5
Eddie Gamboa R 32 25 14 91.3 76 57 11 89 54 50
Andrew Bellatti R 25 30 2 48.3 45 19 7 47 26 24
Dylan Floro R 26 56 0 72.7 49 16 9 78 36 34
Burch Smith R 26 9 9 41.7 35 15 7 45 26 24
Grayson Garvin L 27 11 10 39.7 27 14 6 44 25 23
Ryan Garton R 27 50 0 67.0 58 28 8 66 34 32
Kyle Bird L 24 40 0 64.7 53 22 8 65 33 31
Casey Coleman R 29 38 2 65.7 50 30 7 67 35 33
Enny Romero L 26 61 0 57.3 57 28 7 53 30 28
Neil Wagner R 33 38 0 40.0 35 20 5 39 21 20
Greg Harris R 22 26 24 125.3 101 65 18 129 76 71
Ryne Stanek R 25 26 13 87.0 71 45 13 90 54 50
Christopher Kirsch L 25 24 23 125.0 79 56 18 138 78 73
Parker Markel R 26 45 0 66.3 46 30 8 70 37 35
Brad Schreiber R 26 45 0 61.0 48 27 9 63 35 33
Chris Pike R 24 24 22 122.3 61 44 19 145 81 76
Jose Alvarado L 22 38 0 65.0 65 66 8 60 44 41

***

Pitchers, Rates and Averages
Player IP TBF K% BB% BABIP ERA FIP ERA- FIP-
Chris Archer 195.3 818 27.1% 7.8% .291 3.41 3.21 84 79
Jake Odorizzi 177.3 749 22.2% 7.1% .283 3.70 3.72 91 91
Blake Snell 148.0 647 26.3% 11.1% .299 3.71 3.75 91 92
Matt Andriese 143.0 599 21.0% 5.0% .293 3.71 3.49 91 86
Drew Smyly 143.0 603 23.4% 6.8% .285 3.90 3.74 96 92
Alex Cobb 102.0 441 19.3% 7.9% .292 3.88 3.99 95 98
Brent Honeywell 127.3 548 19.0% 6.6% .294 4.38 4.22 107 103
Alex Colome 61.3 252 29.0% 6.7% .288 2.93 3.09 72 76
Chase Whitley 62.7 269 19.7% 6.7% .294 4.16 4.08 102 100
Jacob Faria 131.3 585 21.2% 11.3% .291 4.66 4.57 114 112
Austin Pruitt 142.0 614 16.4% 5.5% .295 4.69 4.47 115 110
Chih-Wei Hu 125.7 553 16.1% 7.6% .294 4.73 4.59 116 113
Xavier Cedeno 42.3 177 26.6% 7.3% .289 3.40 3.34 83 82
Danny Farquhar 73.7 314 22.9% 7.6% .293 3.79 3.84 93 94
Brad Boxberger 51.3 221 29.9% 11.3% .289 3.68 3.77 90 92
Jaime Schultz 107.3 489 23.7% 13.9% .296 4.78 4.83 117 118
Adam Wilk 113.0 494 16.0% 6.3% .296 4.78 4.62 117 113
Hunter Wood 98.3 437 19.7% 10.3% .292 4.76 4.60 117 113
Jaye Chapman 44.7 191 23.5% 7.8% .292 3.83 3.91 94 96
Diego Moreno 58.3 253 20.2% 8.3% .293 4.17 4.15 102 102
Andrew Kittredge 77.7 337 19.9% 8.0% .292 4.29 4.25 105 104
Dana Eveland 55.3 243 19.3% 8.6% .303 4.23 4.06 104 100
Kevin Gadea 27.7 118 24.6% 8.5% .297 3.90 3.72 96 91
Erasmo Ramirez 86.0 373 13.9% 6.7% .281 4.08 4.43 100 109
Justin Marks 103.7 466 17.4% 10.3% .292 4.86 4.80 119 118
Taylor Guerrieri 112.7 502 13.7% 8.2% .289 4.95 4.98 121 122
Kevin Jepsen 56.3 246 20.7% 9.4% .285 4.15 4.03 102 99
Jonny Venters 10.3 47 17.1% 10.7% .313 4.35 4.27 107 105
Eddie Gamboa 91.3 420 18.1% 13.6% .288 4.93 5.04 121 124
Andrew Bellatti 48.3 211 21.3% 9.0% .290 4.47 4.43 110 109
Dylan Floro 72.7 312 15.7% 5.1% .293 4.21 4.15 103 102
Burch Smith 41.7 185 18.9% 8.1% .301 5.18 4.83 127 118
Grayson Garvin 39.7 177 15.2% 7.9% .299 5.22 4.92 128 121
Ryan Garton 67.0 295 19.7% 9.5% .293 4.30 4.27 105 105
Kyle Bird 64.7 281 18.9% 7.8% .292 4.31 4.19 106 103
Casey Coleman 65.7 294 17.0% 10.2% .294 4.52 4.43 111 109
Enny Romero 57.3 253 22.5% 11.1% .288 4.40 4.22 108 103
Neil Wagner 40.0 179 19.6% 11.2% .291 4.50 4.56 110 112
Greg Harris 125.3 570 17.7% 11.4% .294 5.10 5.11 125 125
Ryne Stanek 87.0 396 17.9% 11.4% .294 5.17 5.14 127 126
Christopher Kirsch 125.0 569 13.9% 9.8% .294 5.26 5.23 129 128
Parker Markel 66.3 299 15.4% 10.0% .294 4.75 4.83 116 118
Brad Schreiber 61.0 273 17.6% 9.9% .290 4.87 4.88 119 119
Chris Pike 122.3 556 11.0% 7.9% .297 5.59 5.38 137 132
Jose Alvarado 65.0 321 20.2% 20.6% .292 5.68 5.89 139 144

***

Pitchers, Assorted Other
Player IP K/9 BB/9 HR/9 ERA+ zWAR No. 1 Comp
Chris Archer 195.3 10.23 2.95 0.92 116 4.1 Juan Guzman
Jake Odorizzi 177.3 8.43 2.69 1.07 107 3.0 Todd Stottlemyre
Blake Snell 148.0 10.34 4.38 0.97 106 2.5 Tony Saunders
Matt Andriese 143.0 7.93 1.89 1.01 106 2.3 Ramiro Mendoza
Drew Smyly 143.0 8.87 2.58 1.20 101 2.0 Mark Redman
Alex Cobb 102.0 7.50 3.09 0.97 102 1.5 Omar Olivares
Brent Honeywell 127.3 7.35 2.55 1.20 90 1.0 Kelly Downs
Alex Colome 61.3 10.72 2.50 1.03 135 1.0 Tim Scott
Chase Whitley 62.7 7.61 2.58 1.15 95 0.6 Jason Dickson
Jacob Faria 131.3 8.50 4.52 1.17 85 0.6 Brian Holman
Austin Pruitt 142.0 6.40 2.15 1.33 84 0.6 Bill King
Chih-Wei Hu 125.7 6.37 3.01 1.22 84 0.4 Andy Taulbee
Xavier Cedeno 42.3 10.00 2.77 1.06 116 0.4 Chuck McElroy
Danny Farquhar 73.7 8.79 2.93 1.10 104 0.4 J.J. Putz
Brad Boxberger 51.3 11.58 4.39 1.23 107 0.3 Bart Miadich
Jaime Schultz 107.3 9.73 5.70 1.26 83 0.3 Phil Stockman
Adam Wilk 113.0 6.29 2.47 1.35 83 0.3 Dave Gassner
Hunter Wood 98.3 7.87 4.12 1.19 83 0.2 Oswaldo Peraza
Jaye Chapman 44.7 9.06 3.02 1.21 103 0.2 Nate Field
Diego Moreno 58.3 7.87 3.24 1.08 95 0.2 Dan Gakeler
Andrew Kittredge 77.7 7.76 3.13 1.16 92 0.2 Aaron Looper
Dana Eveland 55.3 7.65 3.42 0.98 93 0.1 C.J. Nitkowski
Kevin Gadea 27.7 9.42 3.25 0.97 101 0.1 Mark Worrell
Erasmo Ramirez 86.0 5.44 2.62 1.15 97 0.1 Rawly Eastwick
Justin Marks 103.7 7.03 4.17 1.22 81 0.1 Eddie Oropesa
Taylor Guerrieri 112.7 5.51 3.27 1.28 80 0.1 Zach McClellan
Kevin Jepsen 56.3 8.15 3.68 1.12 95 0.0 Jim Czajkowski
Jonny Venters 10.3 6.99 4.37 0.87 91 0.0 Mike Barlow
Eddie Gamboa 91.3 7.49 5.62 1.08 80 0.0 Bob Turley
Andrew Bellatti 48.3 8.39 3.54 1.30 88 0.0 Mike Sullivan
Dylan Floro 72.7 6.07 1.98 1.11 94 -0.1 Randy Graham
Burch Smith 41.7 7.55 3.24 1.51 76 -0.1 Garland Kiser
Grayson Garvin 39.7 6.12 3.17 1.36 76 -0.1 Danny Borrell
Ryan Garton 67.0 7.79 3.76 1.07 92 -0.1 Sean Green
Kyle Bird 64.7 7.37 3.06 1.11 92 -0.1 Dave Leiper
Casey Coleman 65.7 6.85 4.11 0.96 87 -0.1 Jake Robbins
Enny Romero 57.3 8.95 4.40 1.10 90 -0.2 Peter Bauer
Neil Wagner 40.0 7.88 4.50 1.13 88 -0.2 Jim Dedrick
Greg Harris 125.3 7.25 4.67 1.29 77 -0.2 Steve Trachsel
Ryne Stanek 87.0 7.34 4.66 1.34 76 -0.3 Jason Baker
Christopher Kirsch 125.0 5.69 4.03 1.30 75 -0.4 Kris Detmers
Parker Markel 66.3 6.24 4.07 1.09 83 -0.5 Scott Munter
Brad Schreiber 61.0 7.08 3.98 1.33 81 -0.6 Matt Smith
Chris Pike 122.3 4.49 3.24 1.40 71 -1.0 James Kirk
Jose Alvarado 65.0 9.00 9.14 1.11 70 -1.3 Tim Adkins

***

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 2017. 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 4.05 ERA and the NL having a 3.97 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.



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