Offensive Projections
Name P Age AVG OBP SLG G AB R H 2B 3B HR RBI BB K SB CS OPS+
Pablo Sandoval# 3b 23 .320 .368 .516 157 597 85 191 43 4 22 110 44 81 2 2 129
Ryan Garko 1b 29 .285 .356 .460 129 435 44 124 23 1 17 67 34 71 0 0 113
Fred Lewis* lf 29 .274 .352 .427 129 391 68 107 22 7 8 46 44 98 9 4 104
Mark DeRosa 3b 35 .273 .345 .434 121 433 63 118 24 2 14 73 44 88 2 1 104
Nate Schierholtz* rf 26 .289 .325 .459 131 425 55 123 27 6 11 62 20 68 4 2 103
John Bowker* lf 26 .269 .338 .434 137 475 62 128 25 4 15 76 47 100 4 3 102
Aaron Rowand cf 32 .273 .335 .431 132 476 59 130 31 1 14 72 32 104 3 1 100
Buster Posey c 23 .263 .343 .398 126 467 67 123 25 1 12 67 53 83 3 1 95
Freddy Sanchez 2b 32 .296 .331 .413 126 506 72 150 32 3 7 60 25 67 1 1 92
Edgar Renteria ss 33 .280 .336 .388 116 443 55 124 23 2 7 52 38 63 6 2 90
Juan Uribe 3b 30 .269 .311 .442 122 398 43 107 24 3 13 58 24 77 1 2 95
Travis Ishikawa* 1b 26 .253 .316 .409 125 403 50 102 21 3 12 63 34 107 2 1 89
Matt Downs 2b 26 .273 .317 .407 118 472 63 129 29 2 10 67 27 67 8 4 89
Jesus Guzman 1b 26 .271 .320 .395 120 479 55 130 23 3 10 64 31 87 1 2 87
Bengie Molina c 35 .271 .298 .424 117 432 38 117 22 1 14 80 15 49 0 0 87
Kevin Frandsen 2b 28 .271 .328 .380 127 421 53 114 21 2 7 48 23 40 4 3 86
Andres Torres# cf 32 .254 .315 .397 107 343 50 87 15 8 6 36 29 88 9 3 86
Rich Aurilia 1b 38 .266 .312 .393 83 214 18 57 10 1 5 32 15 34 0 0 84
Stephen Holm c 30 .253 .320 .373 79 233 25 59 13 0 5 23 21 45 0 0 82
Ryan Rohlinger 3b 26 .254 .315 .382 132 484 60 123 28 2 10 70 36 89 2 2 83
Eugenio Velez# lf 28 .266 .309 .393 128 448 62 119 23 8 6 54 27 78 20 9 83
Joe Borchard# rf 31 .234 .298 .397 92 282 36 66 15 2 9 42 24 76 1 1 81
Brett Pill 1b 25 .258 .300 .381 132 504 60 130 30 1 10 83 28 86 3 2 78
Clay Timpner* cf 27 .265 .312 .361 123 441 53 117 19 4 5 47 29 62 7 6 77
Conor Gillaspie* 3b 22 .254 .321 .331 133 508 55 129 26 2 3 62 49 80 1 2 73
Emmanuel Burriss# 2b 25 .270 .323 .332 106 371 52 100 13 2 2 34 25 49 23 9 73
Roger Kieschnick* rf 23 .234 .281 .385 137 546 68 128 28 6 14 86 33 149 4 1 73
Darren Ford cf 24 .231 .303 .318 115 446 70 103 17 5 4 41 44 121 25 10 64
Eli Whiteside c 30 .241 .281 .357 77 241 24 58 11 1 5 32 11 59 1 1 67
Francisco Peguero cf 22 .248 .276 .323 92 371 40 92 13 3 3 38 12 79 13 3 57
Defensive Projections
Name CThr 1b 2b 3b ss lf cf rf
Sandoval# Fr Av/89 Fr/95
Garko Av/81
Lewis* Vg/141 Pr/167 Av/141
DeRosa Av/78 Fr/115 Av/93 Av/78 Av/78
Schierholtz* Av/83 Av/83
Bowker* Av/142 Av/112 Pr/134 Av/98
Rowand Av/89
Posey Vg
Sanchez Av/86
Renteria Fr/100
Uribe Av/74 Av/96 Av/96
Ishikawa* Vg/123
Downs Av/117 Av/117 Av/117 Pr/133 Av/117 Av/117
Guzman Av/117 Pr/185 Pr/166 Av/117
Molina Av
Frandsen Av/111 Av/111 Fr/139 Av/120 Av/120
Torres# Vg/126 Av/44 Vg/115
Aurilia Av/101 Fr/113
Holm Fr
Rohlinger Vg/97
Velez# Pr/160 Vg/186 Av/179
Super Joe# Av/119 Av/119
Pill Av/112
Timpner* Av/125 Av/125 Av/125
Gillaspie* Av/151
Burriss# Vg/144 Av/138
Kieschnick* Av/79
Ford Av/183
Whiteside Av
Peguero Vg/159 Vg/134
* - Bats Left
# - Switch Hitter
ODDIBE (Odds of Important Baseball Events)
Name PO EX VG AV FR PO COMP 1 COMP 2 COMP 3
SandovalPablo 3B 53% 33% 10% 3% 1%LindstromFreddie RamirezAramis LansfordCarney
GarkoRyan 1B 7% 24% 27% 32% 10% SheetsLarry MorelandKeith JohnsonLamar
SchierholtzNate RF 5% 14% 21% 31% 29% GloadRoss BassKevin CarterSteve
LewisFred LF 5% 17% 23% 31% 24% BumbryAl TuckerMichael BarrettJohnny
DeRosaMark 3B 10% 23% 29% 25% 13% BoyerKen GarnerPhil DeCincesDoug
RowandAaron CF 13% 19% 33% 26% 9% AllenEthan BrandtJackie WilliamsDick
BowkerJohn LF 2% 10% 19% 33% 37% SpilborghsRyan HughesKeith TuckerMichael
SanchezFreddy 2B 11% 14% 21% 28% 26% AdairJerryGrudzielanekMark TrilloManny
PoseyBuster C 6% 37% 35% 20% 2% SuzukiKurt RamosJohn SaxDave
UribeJuan 3B 2% 10% 19% 32% 37% TrubyChris FelizPedro SeabolScott
RenteriaEdgar SS 10% 17% 32% 26% 15% FletcherScott UrbanskiBilly RojekStan
DownsMatt 2B 4% 10% 18% 33% 35% PhillipsBrandon LansingMike GarrisonWebster
MolinaBengie C 3% 16% 29% 35% 17% LyonsBarry DiazBo BooneBob
IshikawaTravis 1B 0% 1% 3% 25% 72% JacksonRyan LankfordDerrick DeedsDoug
TorresAndres CF 1% 5% 22% 43% 29% WebsterMitch MorenoOmar LittleMark
GuzmanJesus 1B 0% 0% 1% 15% 83% BelkTim JacksonRyan TolentinoJose
FrandsenKevin 2B 2% 5% 12% 29% 52% HajekDaveWhiteheadBurgess StennettRennie
VelezEugenio LF 0% 1% 3% 11% 85% SmithIra VarshoGary MartinezManny
AuriliaRich 1B 0% 0% 1% 12% 87% JordanBrian WoodJason PhilleyDave
HolmSteve C 1% 8% 24% 45% 22% TackettJeff BennettGary McDonaldKeith
RohlingerRyan 3B 0% 1% 5% 23% 71% AlfaroJason GrindellNate SeitzerBrad
PillBrett 1B 0% 0% 0% 5% 95% NavarreteRay WestJeremy McGowanSean
BorchardJoe RF 0% 1% 1% 7% 91% HowittDann BufordDamon SmithMark
BurrissEmmanuel 2B 0% 0% 2% 12% 86% CastroBernieMachadoAlejandro ReynoldsHarold
TimpnerClay CF 0% 1% 2% 12% 85% SchumakerSkip EllisonJason GlanvilleDoug
KieschnickRoger RF 0% 0% 0% 2% 98% MartinAl PoeCharles HamiltonJon
GillaspieConor 3B 0% 0% 0% 3% 97% CiofronePeter AybarWilly BaldirisAarom
WhitesideEli C 0% 0% 2% 13% 85% MosqueraJulio CharlesFrank ColbertCraig
FordDarren CF 0% 0% 0% 5% 95% CurryMike DuncanJeff ScottLorenzo
PegueroFrancisco CF 0% 0% 0% 2% 98% HaynesNathan McGeeWillie MoranJavon
Name .300 BA .375 OBP .500 SLG 140 OPS+ 45 2B 10 3B 30 HR 30 SB
SandovalPablo 79% 36% 61% 27% 43% 2% 15% 0%
GarkoRyan 29% 24% 16% 5% 0% 0% 3% 0%
SchierholtzNate 36% 4% 13% 2% 1% 12% 0% 0%
LewisFred 17% 20% 5% 2% 0% 19% 0% 0%
DeRosaMark 18% 15% 9% 3% 0% 0% 1% 0%
RowandAaron 16% 7% 7% 1% 4% 0% 1% 0%
BowkerJohn 11% 7% 4% 1% 0% 3% 1% 0%
SanchezFreddy 42% 6% 3% 1% 4% 0% 0% 0%
PoseyBuster 5% 9% 0% 0% 0% 0% 0% 0%
UribeJuan 12% 1% 10% 0% 0% 0% 1% 0%
RenteriaEdgar 23% 8% 1% 0% 0% 0% 0% 0%
DownsMatt 14% 1% 1% 0% 1% 0% 0% 0%
MolinaBengie 18% 1% 10% 0% 0% 0% 2% 0%
IshikawaTravis 3% 1% 1% 0% 0% 0% 0% 0%
TorresAndres 6% 3% 2% 0% 0% 32% 0% 0%
GuzmanJesus 10% 1% 0% 0% 0% 0% 0% 0%
FrandsenKevin 13% 3% 0% 0% 0% 0% 0% 0%
VelezEugenio 8% 0% 0% 0% 0% 32% 0% 4%
AuriliaRich 20% 5% 1% 0% 0% 0% 0% 0%
HolmSteve 8% 4% 0% 0% 0% 0% 0% 0%
RohlingerRyan 2% 0% 0% 0% 1% 0% 0% 0%
PillBrett 3% 0% 0% 0% 1% 0% 0% 0%
BorchardJoe 1% 1% 1% 0% 0% 0% 0% 0%
BurrissEmmanuel 11% 2% 0% 0% 0% 0% 0% 12%
TimpnerClay 7% 1% 0% 0% 0% 2% 0% 0%
KieschnickRoger 0% 0% 0% 0% 0% 10% 0% 0%
GillaspieConor 1% 1% 0% 0% 0% 0% 0% 0%
WhitesideEli 3% 0% 0% 0% 0% 0% 0% 0%
FordDarren 0% 0% 0% 0% 0% 4% 0% 24%
PegueroFrancisco 2% 0% 0% 0% 0% 1% 0% 0%
Pitching Statistics - Starters
Name Age ERA W L G GS INN H ER HR BB K ERA+
Tim Lincecum 26 2.68 16 6 34 33 225.0 177 67 13 78 260 162
Matt Cain 25 3.51 13 9 34 34 217.2 197 85 20 80 179 124
Madison Bumgarner* 20 4.05 8 6 28 26 133.1 137 60 12 42 86 107
Jonathan Sanchez* 27 4.15 10 11 30 28 156.0 141 72 17 77 169 105
Randy Johnson* 46 4.33 6 8 21 20 114.1 116 55 17 32 98 100
Barry Zito* 32 4.48 11 14 32 32 184.2 183 92 21 83 132 97
Ramon Ortiz 34 4.77 5 8 33 17 126.1 137 67 17 39 83 91
Kevin Pucetas 25 4.80 6 10 28 27 144.1 161 77 16 46 74 91
Joe Martinez 27 5.16 5 9 24 21 111.2 134 64 12 38 64 84
Henry Sosa 24 5.37 2 4 15 14 63.2 72 38 9 31 36 81
Matt Kinney 33 5.55 6 13 27 26 146.0 167 90 28 48 97 78
Clayton Tanner* 22 5.72 6 13 26 24 122.2 146 78 17 62 68 76
Steve Hammond* 28 6.24 6 16 29 27 145.2 178 101 27 69 78 70
Steve Johnson 22 6.93 4 16 27 25 124.2 149 96 28 83 83 63
Pitching Statistics - Relievers
Name Age ERA W L G GS INN H ER HR BB K ERA+
Sergio Romo 27 3.21 5 3 52 0 53.1 44 19 5 19 54 136
Brian Wilson 28 3.47 5 3 67 0 70.0 61 27 5 30 72 125
Jeremy Affeldt* 31 3.48 2 1 74 0 64.2 56 25 5 29 58 125
Eugene Espineli* 27 4.08 3 3 54 0 64.0 69 29 5 19 36 107
Alex Hinshaw* 27 4.10 2 2 60 0 59.1 50 27 6 37 64 106
Osiris Matos 25 4.52 2 3 49 0 61.2 65 31 7 22 45 96
Brandon Medders 30 4.65 3 4 59 0 69.2 71 36 8 37 51 93
Dan Runzler* 25 4.72 2 3 55 0 55.1 51 29 6 41 53 92
Waldis Joaquin 23 4.76 3 5 53 0 62.1 63 33 5 39 48 91
Merkin Valdez 28 5.04 1 2 42 1 44.2 47 25 5 26 35 86
Steve Palazzolo 28 5.22 2 4 33 0 50.0 54 29 6 28 32 83
* - Throws Left
ODDIBE (Odds of Important Baseball Events)
Player PO TOP MID BOT COMP 1 COMP 2 COMP 3
LincecumTim SP 99% 1% 0% BlackwellEwell RijoJose PascualCamilo
RomoSergio RP 64% 32% 4% JenksBobby DavisRon LeskanicCurt
WilsonBrian RP 59% 35% 5% WardDuane RadatzDick SelmaDick
AffeldtJeremy RP 50% 43% 7% ChristiansenJason LaRocheDave OroscoJesse
CainMatt SP 85% 15% 0% SeleAaron LeaCharlie MillerWade
BumgarnerMadison SP 47% 47% 6% MulderMark DukeZach TroutSteve
EspineliEugene RP 24% 51% 25% MeauxRyan JeffcoatMike CasianLarry
HinshawAlex RP 24% 54% 22% WilliamsMitch AlmanzaArmando WagnerBilly
SanchezJonathan SP 44% 48% 7% LangstonMark JohnsonRandy KoufaxSandy
JohnsonRandy SP 29% 49% 22% KoosmanJerry WellsDavid FinleyChuck
ZitoBarry SP 18% 62% 20% BohanonBrian AlvarezWilson HamptonMike
MatosOsiris RP 10% 49% 41% MabeusChris PattersonDave AcevedoJose
MeddersBrandon RP 8% 42% 51% DoughertyJim SaladinMiguel GryboskiKevin
RunzlerDan RP 9% 42% 50% AlmanzaArmando ClarkeStan JohnsonTyler
JoaquinWaldis RP 8% 39% 54% VasquezCarlos WigginsScott JacksonGrant
OrtizRamon SP 18% 43% 40% SparksSteve RossMark YoshiiMasato
PucetasKevin SP 9% 55% 36% JohnsonJoe FireovidSteve BeggChris
ValdezMerkin RP 5% 25% 70% SmithRoy ReichertDan HendersonRyan
MartinezJoe SP 5% 39% 56% SorensenLary MoehlerBrian MacdonaldMichael
PalazzoloSteve RP 3% 24% 73% GreenSean VaughanWilliam BauerGreg
SosaHenry SP 4% 26% 70% MilackiBob JacobsenLandon KylesStan
KinneyMatt SP 2% 19% 79% MartinezDennis HellingRick TollbergBrian
TannerClayton SP 0% 13% 87% GramanAlex KozlowskiBen GeorgeChris
HammondSteven SP 0% 2% 98% ProchaskaMike TeutNate RobertsChris
JohnsonSteven SP 0% 0% 100% BaylissJonah KnightBrandon RomanoMike
Player 130 ERA+ 100 ERA+ K/9 >8 BB/9 <2 HR/9
<1
LincecumTim 91% 100% 97% 1% 99%
RomoSergio 56% 92% 76% 7% 80%
WilsonBrian 52% 93% 85% 1% 91%
AffeldtJeremy 50% 91% 48% 0% 83%
CainMatt 43% 98% 20% 0% 82%
BumgarnerMadison 13% 72% 1% 5% 80%
EspineliEugene 19% 69% 1% 20% 87%
HinshawAlex 24% 66% 90% 0% 72%
SanchezJonathan 13% 73% 91% 0% 61%
JohnsonRandy 7% 51% 37% 17% 29%
ZitoBarry 2% 42% 4% 0% 57%
MatosOsiris 10% 52% 5% 4% 59%
MeddersBrandon 5% 36% 5% 0% 59%
RunzlerDan 6% 36% 71% 0% 64%
JoaquinWaldis 5% 39% 12% 0% 83%
OrtizRamon 5% 34% 7% 15% 38%
PucetasKevin 1% 28% 0% 4% 55%
ValdezMerkin 3% 23% 15% 0% 63%
MartinezJoe 0% 16% 0% 3% 62%
PalazzoloSteve 2% 21% 1% 0% 61%
SosaHenry 1% 12% 0% 0% 40%
KinneyMatt 0% 5% 2% 3% 5%
TannerClayton 0% 2% 0% 0% 32%
HammondSteven 0% 0% 0% 0% 4%
JohnsonSteven 0% 0% 1% 0% 1%
Extrapolated Career Statistics
Player W L S ERA G GS IP H HR BB SO ERA+
CainMatt 186 157 0 3.68 518 516 3285 2944 336 1291 2750 118
LincecumTim 198 85 0 3.25 441 437 2913 2335 196 1067 3331 134
SanchezJonathan 99 114 0 4.48 358 292 1639 1513 184 845 1759 97
ZitoBarry 193 179 0 4.11 496 494 2988 2767 324 1294 2215 107
Name BA OBP SLG G AB R H 2B 3B HR RBI BB SO SB CS OPS+
RenteriaEdgar .283 .340 .394 2293 8760 1261 2477 469 28 150 1015 769 1244 290 110 92
SanchezFreddy .294 .329 .409 1072 4098 544 1204 258 23 56 488 200 506 13 10 93
RowandAaron .274 .334 .435 1660 5583 757 1529 347 18 172 753 357 1182 68 28 98
All figures in % based on projection playing time
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 2009.
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 4.46 ERA and the NL having a 4.41 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.
Positional offense is ranked by RC/27 and divided into quintiles based on what the
most frequent starting players at each position did in 2007-2009. Excellent is the top
quintile, Very Good the 2nd quintile and so on.
Reader Comments and Retorts
Go to end of page
Statements posted here are those of our readers and do not represent the BaseballThinkFactory. Names are provided by the poster and are not verified. We ask that posters follow our submission policy. Please report any inappropriate comments.
The same arguments - OH MY GOD CANT YOU SEE HE CLICKED! And HES CLEARLY A SPECIAL PLAYER THAT NERDS DON'T UNDERSTAND (Not you, Sam). Turns out he wasn't a 313/397/473 guy after all!
Brock clearly has no less than a 1 in 100,000,000,000 chance of hitting 60 HRs next year.
You know, now he's going to hit .290/.350/.475....
I remember one of the old Bill James abstracts, where he mentioned that he projected someone to hit .220, the dude hit .280, James said he was wrong, but the next year (and every year after) the guy hit .220 or less...
Then came Rob Deer, who hit .232/.336/.494, and James said, "nope, not falling for it, if he could hit .232 he'd be useful, but he's going to hit .180...
A couple years later James said, OK I give up, he improved, he's better than he was in the minors, Deer immediately cratered and hovered around the mendoza line for the rest of his career.
I’ve mentioned this before, but if a guy hits .850 (in a league where the average player hits .750) in his first year (or in any year, and that’s all we know), and he gets better in talent (say by 20 OPS points), how many teams do you think understand that he is supposed to hit around .820 the next year, a “regression” of 30 points?
For those of you who are just casual readers, let me repeat that: If a player hits .850 (OPS) his first year and we KNOW (G-d comes down and tells us) that his true talent is going to increase the next year by 20 points (maybe because he is on the up-slope of his aging curve, like Martin presumably is, but it doesn’t matter why), then we expect him to hit around:
.820 the next year. Yes, we expect that a player who gets better in true talent will hit 30 points less than he hit the year before!
You know, I never forgot the lesson.
1 in 1,751,072,931,543,390
Dan, you need to watch him play!! The real odds are about 1 in 32.
Or BPro who kept calling for Marcus Giles to get more playing time. He gets some and kinda stinks and there might have been rumors of attitude problems too. So for the 2003 BPro, they finally give in and admit Cox is smarter than they are. And of course he goes out and rips the cover off the ball.
Getting angry at the maker of a projection system because you don't like a projection of a particular player seems awfully strange to me -- but it's been a strange thread.
Keep 'em coming Dan; can't wait to see Vernon Wells's projection! (groan)
1 in 1,751,072,931,543,390
So, you're saying there's a chance!
1 in 1,751,072,931,543,390
Dan, how do you get that result? Clearly you're not running 1751 trillion simulations of the season. If you are running simulations, I can't imagine a PC could handle more than 1 million and still deliver results in a timely fashion.
Why are you getting such "precise" results?
I've been mulling this over for a long time and I wanted to ask you-how much effort do you put into predicting W's? Does ZiPS project it based entirely on the projected peripherals and IP or is the team offense and defense included somehow? I've always operated on the assumption that you wouldn't devote too much energy to such an unpredictable stat, but I'd love to know how much does go into it.
Along the same lines, does anybody have any thoughts on what stats you would look at to predict a high (or higher) winning percentage? I'm trying to rank teams based on how much they're projected to help their SP's get wins but there are so many variables. (Obviously this is a fantasy question-I'm in a 5x5 where a lot of us tend to value players similarly so I'm looking for some new tricks with some of the luckier categories).
Thanks again.
DeRosa to LF?
Well, it's not really that precise, but if there's a chance that, for example, so-and-so develops into a "true" 40 home-run hitter, there's a range of probabilities around that (which ZiPS looks for), even if a 60 home-run season is never the mean projection.
Wins are very volatile.
Previous years run totals regressed towards mean is a pretty good predictor of team offense. Number of seasons tend to be predictive (bullpen quality is a big fact, obviously, but decisions are also a residue of endurance, which tends to be predictive).
Win totals for starters work similarly to teams, though the exponent is higher.
1. Looks like he's got a very strong throwing arm.
2. After Strasburg clowned several hitters backdooring that slurve thing of his, Neal kept his hands back and roped it into left field for a hit.
3. Made a couple of outstanding running catches in left and nearly made a third.
Now one game is one game and I'm not about to change policies on evaluating players from one game. But just from a standard stat geek perspective, when you see how much he hit, your first concern would be his defensive ability. And it sure looked like that it wasn't an issue for him.
Sabean really confuses me as his organization seems to do all the difficult things well, and can't seem to do the easy thing which is put together a reasonable offense. A little known fact was that he was scheduled to be one of the guys at the infamous stats/scouts roundtable but pulled out. Pat Gillick was there as an observer but didn't participate.
I think this can be explained in a very simple way. Sabean uses BA instead of OBP. Sometimes he will end up getting guys with a decent OBP because they have high batting averages, and sometimes he will get guys with decent walk rates by sheer chance (Durham, Burks, a few others over the years).
Notice also that the Giants pitching staffs over the last several years have been near the top in walks allowed - no matter if their pitching has been good or bad overall. I suspect, but cannot proove - that there is an organizational philosophy around "nibbling" rather than challenging hitters.
It's obvious on the offensive side, that the organization values aggressive hackers.
I have a feeling that having Bonds getting thousands of walks, often in weak lineups has colored his position on this. Know Sabeans' media personality a bit, I wouldn't be surprised if he thinks this is a major competitive advantage.
Are you saying that Sabean learned that Bonds getting walks was what lead to the weak lineups? And thus should be avoided?
And I think that while most analysis indicates that he was walked "too much" opposing managers kept walking him - hence it must have been a good strategy - hence walks are overrated. It's really more of a gut feeling on my part more than anything tangible.
GM Psychoanalysis - worst blog idea evah?
Clearly, Sabean doesn't know the value of the walk. It would be pretty amusing (in a tragic way, since I'm a Giants fan), that Sabean's exposure to one of the greatest batters of all time, who had no problem using the walk as a weapon reinforced his view that walks are not great outcomes.
Actually, it's not at all surprising. The Giants, for the most part, did a poor job of leveraging Bonds's walks into runs, and the lesson someone might take from that is that walks tend to be issued in situations where they are far less valuable than statistical analysis would have you believe. (Ripple effects from walks, e.g. extra PAs for your better hitters, are not often considered in that context.)
-- MWE
You must be Registered and Logged In to post comments.
<< Back to main