2013 ZiPS Projections – St. Louis Cardinals

Dan Szymborski’s ZiPS projections, which have typically appeared in the pages of Baseball Think Factory, are being released at FanGraphs this year. Below are the projections for the St. Louis Cardinals. Szymborski can be found on Twitter at @DSzymborski.

Other 2013 Projections: Angels / Astros / Athletics / Blue Jays / Brewers / Cubs / Diamondbacks / Giants / Mets / Nationals / Phillies / Pirates / Rangers / Reds / Rockies / Royals / Tigers / White Sox.

Batters
The Cardinals have a number of hitters who’ve posted above-average offensive numbers over the last three years on the strength of high batting averages on balls in play. David Freese (.359 BABIP, 1200 PA), Jon Jay (.348, 1328), Matt Holliday (.333, 1879), and Allen Craig (.329, 857): each has posted a ball-in-play figure considerably above league average (which typically falls in the .290-.300 range).

The production of high BABIPs certainly can be a skill; however, as Dan Szymborski suggested recently with regard to Detroit’s Austin Jackson (who’s also posted high ball-play-numbers), it takes rather a large sample for that skill to reveal itself in the numbers. Accordingly, the ZiPS projections are going to appear conservative for players whose offensive value has been informed more considerably by his batted-ball profile.

Pitchers
Injuries have affected the Cardinals’ top-three starters considerably in recent years. Tommy John surgery, of course, prevented Adam Wainwright from pitching at all in 2011. Nerve and shoulder issues limited Chris Carpenter to just three regular-season starts in 2012. Jaime Garcia missed probably a little more than a third of his starts in 2012, as well, with shoulder trouble. ZiPS doesn’t know any of those details precisely, of course; what it does know is that the staff’s innings have been curtailed.

In light of Lance Lynn‘s 2012 season, which saw him post a 180:64 strikeout-to-walk ratio, 92 xFIP-, and 2.9 WAR in 176.0 innings, his projection here might seem rather lacking in generosity. It’s worth noting, however, that he’s been considerably more proficient in his brief major-league career than he really ever was as a minor leaguer (which he was up to, and including much of, 2011). In 414.1 minor-league innings, Lynn posted strikeout and walk rates of 7.8 and 3.3, respectively, per nine innings. As a major leaguer, in fewer (210.2) innings, he’s posted strikeout and walk rates of 9.4 and 3.2, respectively, per nine innings. It’s generally not the case that pitchers’ raw numbers improve with a promotion to a higher level.

Bench/Prospects
The Cardinals’ young talent is the most noteworthy aspect of these ZiPS forecasts. Two of the club’s top-five field players by projected WAR, Oscar Taveras (2.6) and Kolten Wong (2.3), are likely to begin 2013 in the minors — probably at Triple-A Memphis, in both cases. It’s entirely possible — at just 21 and 22 years old, respectively — that their aging curves will bring them into All-Star territory before very long. Shortstops Greg Garcia and Ryan Jackson, meanwhile, both profile as competent infield depth — not a distinction to be overlooked. And while both scouting reports and ZiPS ask questions about the former’s (i.e. Garcia’s) defensive ability at short, he’s also young enough to improve his overall game at this point.

There are encouraging signs among the the Cardinals’ pitching prospects, as well. Per ZiPS, all three from Joe Kelly, Shelby Miller, and Trevor Rosenthal are capable of throwing something similar to league-average innings as a starter. With the relative fragility of the rotation, that hypothetical might become a reality.

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

Cards Depth

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
Yadier Molina R 30 C 545 51 142 25 0 14 70 9 4
Matt Holliday R 33 LF 609 80 150 34 1 22 87 6 4
Oscar Taveras L 21 CF 540 64 138 32 7 14 77 6 3
Carlos Beltran B 36 RF 467 52 109 22 3 18 64 7 3
Kolten Wong L 22 2B 598 67 153 25 6 8 53 19 12
Jon Jay L 28 CF 548 69 138 26 3 8 48 14 7
David Freese R 30 3B 439 47 107 19 1 13 62 2 2
Allen Craig R 28 1B 489 66 126 28 1 19 82 3 1
Rafael Furcal B 35 SS 465 61 110 18 4 7 44 11 4
Ryan Jackson R 25 SS 559 48 123 24 3 5 44 3 2
Greg Garcia L 23 SS 513 62 107 21 5 4 37 9 6
Adron Chambers L 26 CF 515 58 113 16 7 5 41 15 7
Daniel Descalso L 26 2B 485 55 109 21 5 5 43 5 3
Starlin Rodriguez B 23 2B 493 52 113 21 5 7 45 10 9
Justin Christian R 33 CF 463 59 105 20 4 5 37 23 4
Matt Adams L 24 1B 486 51 120 26 1 16 66 2 1
Matt Carpenter L 27 1B 496 53 110 24 4 8 53 4 2
Tony Cruz R 26 C 277 24 62 15 1 4 28 0 2
Jermaine Curtis R 25 3B 458 46 103 16 2 1 33 5 1
Pete Kozma R 25 2B 595 58 122 23 4 8 62 7 3
Rob Johnson R 28 C 228 26 44 11 1 4 25 2 0
Shane Robinson R 28 RF 274 32 62 13 2 3 25 6 1
J.R. Towles R 29 C 206 20 41 12 0 2 22 1 1
Jose Garcia R 25 3B 470 46 108 16 1 4 34 15 7
Ty Wigginton R 35 1B 418 42 89 16 1 11 48 2 1
Aaron Bates R 29 1B 357 33 75 14 0 4 29 0 0
Luis Montanez R 31 RF 331 30 72 12 2 3 31 2 3

***

Batters, Rates and Averages

Player PA BB% K% ISO BABIP BA OBP SLG wOBA
Yadier Molina 545 7.5% 9.0% .137 .296 .289 .348 .426 .332
Matt Holliday 609 10.5% 17.2% .192 .312 .281 .365 .473 .358
Oscar Taveras 540 6.9% 13.5% .178 .301 .279 .331 .457 .329
Carlos Beltran 467 10.7% 18.0% .199 .291 .265 .345 .464 .338
Kolten Wong 598 6.4% 13.2% .111 .310 .279 .328 .390 .311
Jon Jay 548 6.4% 14.8% .115 .323 .282 .342 .397 .317
David Freese 439 8.4% 21.0% .152 .323 .272 .340 .424 .332
Allen Craig 489 7.2% 18.2% .195 .311 .283 .333 .478 .348
Rafael Furcal 465 8.2% 12.0% .112 .287 .262 .325 .374 .305
Ryan Jackson 559 7.0% 18.8% .089 .295 .243 .296 .332 .272
Greg Garcia 513 10.1% 18.7% .097 .296 .239 .329 .336 .293
Adron Chambers 515 8.7% 22.7% .099 .322 .249 .325 .348 .296
Daniel Descalso 485 8.2% 15.9% .107 .296 .254 .322 .361 .293
Starlin Rodriguez 493 4.9% 23.1% .115 .320 .252 .304 .367 .288
Justin Christian 463 5.4% 13.6% .101 .276 .246 .292 .347 .285
Matt Adams 486 5.8% 22.0% .168 .311 .265 .307 .433 .314
Matt Carpenter 496 11.3% 18.5% .131 .306 .257 .346 .388 .321
Tony Cruz 277 5.4% 20.2% .113 .290 .240 .283 .353 .272
Jermaine Curtis 458 9.0% 14.2% .058 .305 .259 .346 .317 .298
Pete Kozma 595 7.2% 21.2% .102 .277 .226 .281 .328 .265
Rob Johnson 228 7.9% 26.8% .123 .286 .217 .288 .340 .275
Shane Robinson 274 6.6% 13.9% .104 .281 .249 .305 .353 .289
J.R. Towles 206 6.8% 17.5% .099 .267 .225 .299 .324 .276
Jose Garcia 470 5.5% 19.8% .070 .308 .249 .298 .319 .272
Ty Wigginton 418 7.9% 19.4% .135 .270 .236 .301 .371 .293
Aaron Bates 357 8.4% 23.8% .081 .303 .233 .305 .314 .280
Luis Montanez 331 7.3% 15.1% .083 .277 .240 .303 .323 .277

***

Batters, Assorted Other

Player PA RC/27 OPS+ Def WAR No.1 Comp
Yadier Molina 545 5.6 112 7 4.4 Earl Battey
Matt Holliday 609 6.4 129 -2 3.4 Paul O’Neill
Oscar Taveras 540 5.7 115 -4 2.6 Ken Griffey Jr.
Carlos Beltran 467 5.9 121 0 2.3 Ellis Burks
Kolten Wong 598 4.7 98 2 2.3 Buddy Lewis
Jon Jay 548 5.1 103 1 2.3 Terry Whitfield
David Freese 439 5.3 110 0 2.2 Tim Naehring
Allen Craig 489 6.0 121 -2 2.1 Lamar Johnson
Rafael Furcal 465 4.5 92 -3 1.6 Tony Fernandez
Ryan Jackson 559 3.5 73 2 1.2 Tim Naehring
Greg Garcia 513 3.8 84 -3 1.2 Ernest Riles
Adron Chambers 515 4.1 86 0 1.1 Jeff Stone
Daniel Descalso 485 4.2 89 -2 1.0 Rance Mulliniks
Starlin Rodriguez 493 3.8 84 2 1.0 Manuel Lee
Justin Christian 463 4.0 76 1 1.0 Jim Busby
Matt Adams 486 4.9 101 -1 0.9 Adam LaRoche
Matt Carpenter 496 4.9 103 -2 0.9 Rusty Greer
Tony Cruz 277 3.4 74 4 0.9 David Duff
Jermaine Curtis 458 4.1 85 -3 0.8 Scott Campbell
Pete Kozma 595 3.2 68 4 0.7 Nate Frese
Rob Johnson 228 3.5 72 0 0.5 Danny Ardoin
Shane Robinson 274 4.1 81 2 0.4 Jake Weber
J.R. Towles 206 3.3 72 0 0.4 Bill Dobrolsky
Jose Garcia 470 3.4 71 -4 -0.1 Mike Champion
Ty Wigginton 418 4.0 85 -5 -0.4 Carl Everett
Aaron Bates 357 3.4 72 -1 -0.5 Juan Richardson
Luis Montanez 331 3.3 73 -3 -0.6 Alan Cockrell

***

Pitchers, Counting Stats

Player T Age G GS IP SO BB HR H R ER
Adam Wainwright R 31 27 27 173.7 157 46 14 165 71 66
Kyle Lohse R 34 27 27 168.7 114 36 16 167 73 68
Jaime Garcia L 26 27 27 160.7 130 45 13 165 73 68
Joe Kelly R 25 33 28 168.3 109 62 13 176 82 77
Trevor Rosenthal R 23 33 21 123.0 114 51 12 110 56 52
Lance Lynn R 26 32 24 149.7 135 56 15 148 74 69
Chris Carpenter R 38 13 13 91.7 73 21 7 93 41 38
Shelby Miller R 22 26 26 132.7 128 71 10 126 65 61
Jason Motte R 31 64 0 60.7 67 17 6 49 21 20
Jake Westbrook R 35 25 25 152.0 91 52 14 164 80 75
Mitchell Boggs R 29 66 0 70.0 57 23 6 65 29 27
Fernando Salas R 28 66 0 65.0 67 24 6 57 27 25
Edward Mujica R 29 66 0 67.0 55 12 8 63 28 26
Randy Choate L 37 65 0 31.7 31 13 3 28 13 12
Brandon Dickson R 28 26 23 143.7 92 41 19 162 82 77
Marc Rzepczynski L 27 69 0 54.7 48 23 6 52 27 25
Maikel Cleto R 24 60 0 67.0 70 34 7 61 33 31
Brian Fuentes L 37 42 0 38.7 34 15 4 37 19 18
Tyler Lyons L 25 28 20 116.7 82 49 14 125 68 64
Jess Todd R 27 50 0 61.3 51 27 7 63 33 31
Eduardo Sanchez R 24 43 0 41.0 38 31 4 37 24 22
Eric Fornataro R 25 62 0 66.3 40 33 5 70 36 34
Victor Marte R 32 53 0 55.0 42 25 6 58 31 29
John Gast L 24 26 26 143.7 87 62 17 159 88 82
Sam Freeman L 26 65 0 63.7 46 35 6 65 36 34
Keith Butler R 24 53 0 52.0 44 35 6 52 31 29
Barret Browning L 28 53 0 64.3 44 37 6 68 37 35
Kevin Siegrist L 23 20 17 87.3 54 52 11 96 58 54
Jorge Rondon R 24 53 0 53.7 41 42 5 55 34 32
Michael Blazek R 24 35 15 95.0 73 67 14 103 66 62

***

Pitchers, Rates and Averages

Player IP TBF K% BB% BABIP ERA FIP ERA- FIP-
Adam Wainwright 173.7 732 21.4% 6.3% .295 3.42 3.16 90 83
Kyle Lohse 168.7 709 16.1% 5.1% .280 3.63 3.65 95 96
Jaime Garcia 160.7 692 18.8% 6.5% .303 3.81 3.37 100 89
Joe Kelly 168.3 743 14.7% 8.3% .295 4.12 3.98 108 105
Trevor Rosenthal 123.0 530 21.5% 9.6% .284 3.80 3.95 100 104
Lance Lynn 149.7 653 20.7% 8.6% .303 4.15 3.82 109 100
Chris Carpenter 91.7 389 18.8% 5.4% .302 3.73 3.21 98 85
Shelby Miller 132.7 595 21.5% 11.9% .307 4.14 3.93 109 103
Jason Motte 60.7 248 27.0% 6.9% .275 2.97 3.01 78 79
Jake Westbrook 152.0 672 13.5% 7.7% .294 4.44 4.16 117 109
Mitchell Boggs 70.0 298 19.1% 7.7% .284 3.47 3.65 91 96
Fernando Salas 65.0 276 24.3% 8.7% .288 3.46 3.25 91 85
Edward Mujica 67.0 276 19.9% 4.3% .275 3.49 3.50 92 92
Randy Choate 31.7 136 22.8% 9.6% .290 3.41 3.69 90 97
Brandon Dickson 143.7 634 14.5% 6.5% .302 4.82 4.51 127 119
Marc Rzepczynski 54.7 239 20.1% 9.6% .287 4.12 4.03 108 106
Maikel Cleto 67.0 296 23.6% 11.5% .298 4.16 4.02 109 106
Brian Fuentes 38.7 168 20.2% 8.9% .292 4.19 3.84 110 101
Tyler Lyons 116.7 524 15.6% 9.3% .299 4.94 4.71 130 124
Jess Todd 61.3 274 18.6% 9.9% .301 4.55 4.29 120 113
Eduardo Sanchez 41.0 191 19.9% 16.2% .287 4.83 4.78 127 126
Eric Fornataro 66.3 302 13.2% 10.9% .297 4.61 4.54 121 119
Victor Marte 55.0 248 16.9% 10.1% .302 4.75 4.35 125 114
John Gast 143.7 652 13.3% 9.5% .298 5.14 4.86 135 128
Sam Freeman 63.7 291 15.8% 12.0% .295 4.81 4.62 126 121
Keith Butler 52.0 243 18.1% 14.4% .299 5.02 5.10 132 134
Barret Browning 64.3 298 14.8% 12.4% .298 4.90 4.76 129 125
Kevin Siegrist 87.3 410 13.2% 12.7% .296 5.56 5.49 146 144
Jorge Rondon 53.7 258 15.9% 16.3% .301 5.37 5.24 141 138
Michael Blazek 95.0 455 16.0% 14.7% .302 5.87 5.75 154 151

***

Pitchers, Assorted Other

Player IP K/9 BB/9 HR/9 ERA+ WAR No. 1 Comp
Adam Wainwright 173.7 8.13 2.38 0.73 111 3.2 Kevin Millwood
Kyle Lohse 168.7 6.08 1.92 0.85 104 2.7 Ken Forsch
Jaime Garcia 160.7 7.28 2.52 0.73 99 2.2 Glendon Rusch
Joe Kelly 168.3 5.83 3.32 0.70 92 1.6 Mike LaCoss
Trevor Rosenthal 123.0 8.34 3.73 0.88 99 1.6 Kelvim Escobar
Lance Lynn 149.7 8.12 3.37 0.90 91 1.3 Willie Banks
Chris Carpenter 91.7 7.16 2.06 0.69 101 1.3 Jon Lieber
Shelby Miller 132.7 8.68 4.82 0.68 91 1.3 Jason Schmidt
Jason Motte 60.7 9.93 2.52 0.89 127 0.9 Jerry Spradlin
Jake Westbrook 152.0 5.39 3.08 0.83 85 0.9 Steve Sparks
Mitchell Boggs 70.0 7.33 2.96 0.77 109 0.6 Cory Bailey
Fernando Salas 65.0 9.28 3.32 0.83 109 0.6 Heath Bell
Edward Mujica 67.0 7.39 1.61 1.07 108 0.6 Mark Huismann
Randy Choate 31.7 8.80 3.69 0.85 111 0.3 Tony Fossas
Brandon Dickson 143.7 5.76 2.57 1.19 78 0.1 Tim Harikkala
Marc Rzepczynski 54.7 7.90 3.78 0.99 92 0.0 David Rosario
Maikel Cleto 67.0 9.40 4.57 0.94 91 0.0 Billy Sadler
Brian Fuentes 38.7 7.91 3.49 0.93 90 0.0 Vic Darensbourg
Tyler Lyons 116.7 6.32 3.78 1.08 77 -0.1 Dean Hartgraves
Jess Todd 61.3 7.49 3.96 1.03 83 -0.3 Roy Corcoran
Eduardo Sanchez 41.0 8.34 6.80 0.88 78 -0.3 Josh Banks
Eric Fornataro 66.3 5.43 4.48 0.68 82 -0.4 Gary Ross
Victor Marte 55.0 6.87 4.09 0.98 80 -0.4 Jim Dedrick
John Gast 143.7 5.45 3.88 1.06 74 -0.4 Jake Woods
Sam Freeman 63.7 6.50 4.95 0.85 79 -0.5 Chad Brown
Keith Butler 52.0 7.62 6.06 1.04 75 -0.5 Pete Sikaras
Barret Browning 64.3 6.16 5.18 0.84 77 -0.6 Tom Doyle
Kevin Siegrist 87.3 5.57 5.36 1.13 68 -0.7 Brian Holliday
Jorge Rondon 53.7 6.87 7.04 0.84 70 -0.8 Heathcliff Slocumb
Michael Blazek 95.0 6.92 6.35 1.33 64 -1.3 Alonso Beltran

***

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.




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Carson Cistulli occasionally publishes spirited ejaculations at The New Enthusiast.


60 Responses to “2013 ZiPS Projections – St. Louis Cardinals”

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  1. Ziggy says:

    But will Trevor Rosenthal ever have an opportunity to start??

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  2. Ziggy says:

    Kolten Wong seems to be ranked fairly high – a result of his defense entering the equation? I like the optimism with Wong, however he has never been projected to have much pop. How different do you anticipate his ceiling being from the numbers listed here? 10-15 HR a year max? Jose Altuve is already nearing those numbers for power… seems to reason Wong might have more pop than him, no?

    Please rank over the next 5 years: Altuve, Wong, Segura, Kipnis, Espinosa, Profar. Thanks!

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  3. Go-Toba says:

    Oscar Taveras’ top comp is Ken Griffey Jr. Woah!

    +13 Vote -1 Vote +1

  4. Haastile says:

    What sort of team win probability can you take from ZIPs? The reason I ask, is the Cardinals total WAR tally of 31 seems low, especially compared to the Reds and their WAR tally of 44. Could this indicate that the Reds are more heavily favored than most people thought?

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    • Tim says:

      They got hurt by some rounding. Molina is projected to be worth 4.4 and Holliday 3.4 and both of those are rounded down so thats almost a whole extra win right there.

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      • phoenix2042 says:

        still, if the replacement level team is 49 or 50 wins or so, then the cards are projected to be just barely at .500. if the replacement level team is 47 wins (which i thought i saw somewhere), then they are projected to lose more than win. they seem like a better team than that.

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      • BobbyS says:

        You also have to remember that playing time isn’t factored in to the ‘rough’ depth chart. So players who play more than the projected amount will see their WAR increase, or be complimented by the value of whoever is taking up the missing playing time. Only one player is projected at 600 PA, and then if somebody like Carpenter manages 180 IP, he’s doubling his surface value here.

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    • themiddle54 says:

      There are only 19 players listed in the depth chart above. The sum of the 2013 Cardinals will be greater than those 19.

      Freese is projected at 2WAR in under 500 PA. Ditto Furcal, Descalso, Craig, Beltran. In those five positions there are > 750 PA unaccounted for. Either those players are healthy, play more, and produce more, or they are hurt and subs fill in and produce something. There are only five RP listed above, and STL will use at least twice that many, with the others having some value.

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  5. BobbyS says:

    2010 AAA is really messing with Lynn…

    Oscar, nice!

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  6. Jay says:

    The projections for Taveras and Wong are very encouraging. As for everyone else… I’ll take the over. The Cardinals posted the highest WAR total in the NL last year with 52+. Some regression is expected, but 20 WAR?

    Also, while of course ZiPS shouldn’t account for this, the reason Lynn has seen his strikeout rate go up is due to an increase in velocity. He’s throwing much harder now than he was when he was drafted. There’s actually an upward trend in his minor league strikeout numbers as he added velocity.

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    • Baltar says:

      The total from the depth chart is 31 WAR, not 20. Still, the number is shockingly low. The post explains much of this.
      I’m sure the Cards will come out better when Zym does the team projections.

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  7. Sparkles Peterson says:

    So does ZiPS ever come around on guys with high BABIPs? I know the Coors issue complicates things, but Holliday’s career marks are quite consistent, and even using his career road BABIP and adjusting the few points for a standard home/away BABIP split will put him in the mid .330s.

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  8. john joe says:

    Wasn’t there an article on fangraphs last year indicating that the cardinals high bapips were largely based on their approach and the fact that they consistently crush the ball on the ground? Zips is using bapip numbers far below career averages for almost every player. I”m aware that no one particularly cares about my math, but with conservative projections on playing time and using career bapips I came up with around 42-43 WAR…

    Vote -1 Vote +1

  9. Bad Bill says:

    One thing that ZiPS doesn’t know about Lance Lynn is that some time around the latter third of 2010, he suddenly found about 4 extra mph on his fastball. That transformed him in 2011 from a workmanlike back-of-the-rotation guy to a fire-breathing reliever who was able to carry the velocity upgrade over into the starting rotation in 2012. There is every reason that that upgrade is here to stay.

    A shortcoming of ZiPS — no criticism implied, it’s the nature of the beast — is that it cannot deal accurately with someone who has, as they say, “figured something out.” Lynn seems to qualify. I will be very interested to see this year whether Pete Kozma has figured something out too. No way will he be as good as his magical month of September 2012, but there may be other explanations than (or on top of) small sample size. If so, a 50-point upgrade in his OPS might be coming, which still leaves him well short of stardom but at least promotes him into the realm of the useful.

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  10. Matt says:

    The Cardinals never profile very well with projection systems because they have a typically high amount of guys with significant injury risk. Obviously no different this year.

    Wonder why Holliday isn’t highly regarded. He’s typically one of the most consistent players in MLB.

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  11. Evan says:

    Yeah, these projections look terrible, especially for the hitters. Molina’s dropping back down to 4 WAR? Jay’s average is going to drop 20 points? Holliday and Beltran are going to lose all their power?

    Nope.

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    • BobbyS says:

      Holliday’s power looks about the same (22 HR in 609 PA ZiPS vs 27 HR in 688 PA 2012), ISO isn’t fair for regression. Same with Beltran.

      Molina has a 4.4 WAR as a mean projection… which is very solid, and of course there are good odds he can out perform that.

      Yup.

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  12. I’d probably take the over on Holliday too, but not to an extreme.

    I’ll reiterate what I said in the Mets comments. Take a 33-year-old, solidly above-average player. Put an X where his recent play has been and draw a distribution curve for what you expect his possible projected results should be. If the curve you’ve drawn is symmetrical, you’ve missed the plot.

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  13. Baron Samedi says:

    The comments on these projections are consistently hilarious.

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  14. stan says:

    How crazy is it that the comps for both Freese and Jackson are Tim Naehring?

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  15. MSom13 says:

    Probably a dumb question but I’ll ask anyway. Does a ‘final review’ of ZIPS get published in terms of comparing actual and projected production somewhere? I Would be curious to see this.

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  16. byron says:

    I take Carlos Martinez’s absence to indicate ZiPS thinks he’d be a trainwreck in the majors this year?

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  17. Bob says:

    So, lemme get this straight.

    Cubs = 30 WAR according to ZiPS.

    StL = 31 WAR.

    That’s hucking filarious.

    Tell you what, Dan. How much do you trust your system? I’ll give you the Cubs and 5 games in the standings for $100. And you get 2-1 odds. Whadda ya say? How about 10 games in the standings, even-up, for $200?

    Or to put it another way, I believe one of your co-workers quoted Sky K. as putting the Cubs’ chances of 91 wins at 3%. I’m guessing the Cardinals’ odds are roughly 30-40%. St. Louis has apparently broken your system. ;)

    -7 Vote -1 Vote +1

    • BobbyS says:

      The problem is, you don’t have it straight. Insert winky face.

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    • Let’s count the fails.

      1. Let’s add up the rounded WARs! Not actual WARs.
      2. Let’s only count the starters and ignore PAs and replacements!
      3. Let’s simply add up mean WARs and count that a projection!

      ZiPS actually projects the Cardinals, as of now, to win 86 games.

      Power tip for dealing with projections: bothering to understand what they actually are is more than half the battle.

      +24 Vote -1 Vote +1

    • Baltar says:

      These are not his team projections. Zym does not regard these WAR totals as valid for team projection. He will do that separately later.
      Still, the Cards will probably come out lower than any of us would have expected.
      I will bet you a large amount at very high odds that if you project WAR for all teams or all players, that ZiPS will be far closer to correct in aggregate.

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  18. Atari says:

    I love these projections. The comps section is the most fun for me. One of the takeaways I got from these is that Ellis Burks is very underrated. I saw the comp next to Beltran and thought Beltran was better, until I looked at Burks page. 48.2 career WAR , .379 wOBA and 126 wRC+. Obviously the run environment is different now but look at some of his individual years. Baseball continues to surprise me.

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    • Sparkles Peterson says:

      Ellis Burks is one of those guys you could make a sketchy Hall of Fame case for if you argued that the league averages were distorted by PEDs but presumed (Very probably unwisely) that Burks was clean for that stellar run in the second half of his career. Underrated while he was playing, and definitely now.

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  19. Joe Morgan says:

    “In 414.1 minor-league innings, Lynn posted strikeout and walk rates of 7.8 and 3.3, respectively, per nine innings. As a major leaguer, in fewer (210.2) innings, he’s posted strikeout and walk rates of 9.4 and 3.2, respectively, per nine innings. It’s generally not the case that pitchers’ raw numbers improve with a promotion to a higher level.”

    Clearly, he’s not a minor league pitcher, he’s a major league pitcher.

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  20. Sabean Wannabe says:

    Can someone tell me what the base number of wins expected from a replacement level team? I’m sure its somewhere, I just can’t find it.

    For example, this reports shows all the Cardinal regulars (no bench players) adding up to 31 WAR. What number is that added to to estimate their projected number of team wins for the year?

    Thanks.

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  21. Baltar says:

    For entertainment purposes only, the following shows the number of wins that would be projected for a team using Dan Szymborski’s projection of 45 for an all-replacement level team and the total rounded WAR from the depth chart for each team whose ZiPS have been published so far.
    Note: this calculation is not valid, for reasons Dan has written many times, but it is interesting to me as a very rough indication, and perhaps it will be for some of you.

    AL East

    Blue Jays 90

    AL Central

    Tigers 92
    White Sox 84
    Royals 83
    Astros 61

    AL West

    Angels 96
    Rangers 88
    Athletics 78

    NL East

    Nationals 92
    Phillies 80
    Mets 64

    NL Central

    Reds 91
    Brewers 80
    Cardinals 76
    Cubs 75
    Pirates 75

    NL West

    Giants 88
    D’backs 81
    Rockies 78

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    • Sabean Wannabe says:

      Thanks. I realize the caveats – rounding, PAs, no numbers from reserve among others, etc. Its just an interesting talking point. I had thought the replacement level team number was 51 or 54 or something like that. I guess I was wrong.

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    • Dave S says:

      I didn’t know the Astros were in the AL Central

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      • Baltar says:

        You’re right–they are in the West. I will change them to the correct division before I post this chart again.
        Thank you.

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    • Considering the misuse of WAR in this context (not you, you clearly outlined why it doesn’t work), I’m probably only going to release WAR in the final spreadsheet next year. Despite my non-stop statements that it’s an invalid method for calculating the projected wins, I’m getting non-stop angry emails and tweets from people who do it anyway, and then blame me when the result from an invalid method isn’t what they wanted. I prefer my normal level of grief reception.

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      • psuedoscience says:

        Dan, don’t weenie out like that. There’s a fraction of people who will always ignore and/or misuse the results. Just explain the caveats enough to refer wingnuts back to some key text, and let the other 98% enjoy and peruse the results on a realistic, useful schedule.

        I get the same thing all the time in my day job. It sucks, but I can’t hobble my analyses to suit the lower common denominator.

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      • Psuedo, I’m sure I won’t wuss out in the end. It’s just especially frustrating at times.

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  22. allan says:

    I think it is perceptive that you have lowered expectations for Cards’ hitters BABIP based on some limited MLB samples. You obviously anticipate a correction with projected lower hitting performances. I noted this last year with your projections and Steamers, too. However, another season went by and the same hitters in question duplicated their previous successes.

    I looked over your talking points. I then looked over the minor league BABIP’s of the players you mentioned, and their minor BABIPs were practically the same as the MLB performance.

    It appears to me that these guys are wonderfully consistent and have translated their high MiLB BABIP into MLB output.

    In watching most of these players, I note they frequently use all fields in their hitting approach. The memory of David Freese drive to the RF corner eluding Nelson Cruz in the 2011 playoff game 6 was not an anomaly for him. Freese seems to drive the ball to RF alot along with Craig and Holliday.

    Maybe there is something to this approach that defies the conventional wisdom that BABIP has to revert to mean.

    Otherwise, thanks for your great projections and hard work.

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  23. Ichiro! says:

    Exactly. Study spray charts of abnormally high BABIP performers; check for correlation. Do this, some industrious person!

    Allan!

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  24. wobatus says:

    Oscar Taveras is 20. He doesn’t turn 21 until June.

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  25. allan says:

    OK.

    I checked out Freese’s home season hit chart.

    Here is what I found unless I got the count wrong a little after staring at the blue and red boxes for awhile.

    Freese had 74 hits at home, 73 hits away. At home, he had 33 hits to left and left-center, 16 hits up the middle, and 25 to right center and right field. Despite Freese being a RH hitter, he only “pulled” 45% of his hits
    while going up the middle or going the “other way” 55% of his hits.

    The breakdown is this:
    Left- 45%
    Center- 21%
    Right – 34%

    Despite Freese’s fairly high K-rate, he is a hitter who has a disciplined approach to use the whole field. This seems to be reflected in his batting average, as he has hit above .290 in all three of his last seasons, and is a .296 career hitter. He appears pretty consistent.

    His HR numbers were even better going the opposite way.

    Of his eight home runs at home, he hit five of them to Right, and three to left, none to center, during the 2012 regular season. The breakdown:

    LF- 37.5%
    CF- 0%
    RF- 62.5%

    Perhaps, as I speculated, being able to use all fields, increases the chances of a higher BABIP and may prevent a regression to a mean BABIP. If Freese decides to hit more HR’s, which he hit the ’20′ plateau for the first time this past season, and becomes more “pull happy,” no doubt, his BABIP will suffer.

    Projection systems however, do not seem tailored to determine whether hitters use all fields consistently to determine BABIP on the high side, as such systems rely on numerical and statistical data. If this should stand as a reliable supposition, then such accounting of hit direction may contribute to a more subtle adjustment to BABIP and batting average projection.

    I am not sure yet how this correlates with the whole spectrum at all as I have only time to do one sample, David Freese, but having watched Craig and Holliday some, I have seen them use RF fairly well too, with Craig getting the big hit off Obando in the ’06 Series… to right field.

    The trend with the Cardinals’ hitters is that they have been taught to use
    “patience.” Translated, this means to go with what is being pitched rather than get frustrated looking for something you like, get behind in the count, and then be forced to hit the pitcher’s best offerings. Mark McGwire was the hitting coach and despite his HR proclivities, was a fairly patient hitter.

    Again, though, more samples would be ideal to make this more credible.

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  26. Jeffrey says:

    I don’t understand the comps.

    Are those comps for the players to perform like those players did in those specific years?

    Or are they comps for the players career?

    The Griffey one seems kind of out there, and I love Taveras! But I don’t see him having 50 home run power and being able to stay in center like Griffey…or eventually show 600 home runs.

    I think he is more like a Vlad Guerrero personally.

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  27. mike says:

    Could you expand the depth chart to include first two guys off the bench? Would like you to make a judgment call and just show the WAR projections of who the PH/def replacement/supersubs if possible. Don’t need a section for it every time as I like the bench/prospects section. I just think the depth chart needs to reveal a little more about the actual depth of the team…

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