claydavenport.com
The official Hall balloting will be announced in two days, and I only have two names on my inductee list for this year: Randy Johnson and Pedro Martinez.
Of course, two names for me is by definition. I set up my own Hal of Fame rather diferently from the official Hall or from the way other listers (notably Jay Jaffe) do it.
Most objective Hall guides rely on comparing players to those who are already in the Hall of Fame. Mine does not. The only way it uses the existing Hall was to establish how many Hall of Fame players there should be. It turns out that if you look at the number of players in the Hall for their major league performance – not counting managers, executives, pioneers, or even the Negro League players – then you will find that there is roughly one Hall of Fame player for every 12 or so major league teams.
My own Hall starts with 1936, same as the real Hall. At that time, I show there should have been space for 72 players. For the first 5 years, I let my Hall add 5 players a year. I let it drop to 4 players ayear, and then to three players. Up until 1960, I consider any player who had been retired for five years; starting then, I pick up the idea of the 5/20 window – retired for 5 years, but not more than 20, in order to be considered.
At that point, the highest rated players available to fill the open spots are chosen.
In the current setup, with 30 teams in the majors, it means that my Hall is going to add 2.5 players per year, so I alternate between classes of 2 and 3. Last year (2014) was a three year class; this year, 2015, is just a two. I have the Hall rated for 224 players; there are currently 222 in. And, as I already said, my two for this year are Pedro Martinez and Randy Johnson. They are the two highest-rated players available who are not already in my Hall.
Which raises the question – how are the players rated? I use what I call my “MVP career” method, which is a contrived way of saying it is a weighted average of all of the seasons of a player’s career. The idea is borrowed from the way the MVP ballot works for a given season – where your first place votes count for 14 points, second place for 9, third for 8, and so on down to tenth place an 1 point. In my system, a player’s best season, as measured by WARP3, counts 14 times (gets a weight of 14, gets multiplied by 14, whatever). The second best season counts 9 times, third best counts eight times, and so on. The tenth best season – as well as all seasons beyond the tenth – count once.
The effect is that it rewards both peak ability and career length. A long career without a high peak, like, say, Harold Baines – that won’t make this Hall. A short sharp peak without length – Jack Chesbro, Norm Cash – won’t do it either.
The very best score ever, by this method, is 749 points, run up by Walter Johnson. Babe Ruth is right there with him, with 742. Because of the way I let the selection process travel in time – just picking the best available for that time – the standard for Hall entry varies. The lowest rated player in my Hall is Eddie Stanky, whose 311 score was enough to make the 1968 list. In recent years, it has generally taken a 400 score to be one of the top available players. Johnson and Martinez score at 520 and 507; they are easy picks. John Smoltz is at 411, and it is not clear when he will get in; he won’t make any of the 2016-19 picks, which are largely set. I’m thinkg 2021, depending on exactly when some currently active players retire. The 2018 list (which shows Johan Santana) and 2019 (Alex Rodriguez) could change if those guys play in 2015. Schilling is a point behind him, at 410.
Of course, if I had a real Hall of Fame ballot, I’d have to account for the fact that there are nine players on it who I have already put into my Hall of Fame. And, for that matter, that there are four more players on it who will make my Hall of Fame in the next four years. If I’m going to use all 10 slots, my rankings go like this:
Player MVP score OverallRank PositionRank
1. Barry Bonds 721 3 1 - LF (My Hall, 2013)
2. Roger Clemens 628 5 2 - SP 2013
3. Randy Johnson 520 28 10 - SP 2015
4. Pedro Martinez 507 34 13 - SP 2015
5. Jeff Kent 444 67 9 - 2B 2014
6. Alan Trammell 443 68 10 - SS 2002
7. Sammy Sosa 443 69 5 - RF 2016
8. Jeff Bagwell 439 73 8 - 1B 2011
9. Mark McGwire 428 83 10 - 1B 2007
10. Craig Biggio 426 87 11 - 2B 2016
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11. Mike Mussina 426 88 27 - SP 2017
12. Mike Piazza 414 108 3 - C 2018
13. John Smoltz 411 115 39 - SP 2021?
14. Curt Schilling 410 119 40 - SP
15. Tim Raines 408 121 8 - LF 2008
16. Nomar Garciaparra 407 123 15 - SS 2009
17. Edgar Martinez 404 127 1 - DH 2002
18. Gary Sheffield 401 132 10 - RF
19. Brian Giles 355 224 17 - LF
20. Carlos Delgado 338 273 26 - 1B
21. Larry Walker 337 279 24 - RF
22. Don Mattingly 330 295 29 - 1B
23. Fred McGriff 312 368 36 - 1B
24. Lee Smith 294 459 9 - RP
25. Jason Schmidt 265 690 265 - SP
26. Tom Gordon 256 677 256 - SP
27. Cliff Floyd 234 820 61 - LF
28. Rich Aurilia 214 997 84 - SS
29. Jermaine Dye 208 1054 82 - RF
30. Darin Erstad 201 1142 75 - CF
31. Troy Percival 191 1250 63 - RP
32. Aaron Boone 159 1660 112 - 3B
33. Eddie Guardado 157 1678 90 - RP
34. Tony Clark 120 2332 149 - 1B
My full Hall list:
johnswa01 WALTER JOHNSON 1936 SP 748.9 alexape01 PETE ALEXANDER 1936 SP 625.1 wagneho01 HONUS WAGNER 1936 SS 593.2 mathech01 CHRISTY MATHEWSON 1936 SP 583.2 cobbty01 TY COBB 1936 CF 565.4 Runners-up 1936 walshed01 lajoina01 barnero01 collied01 speaktr01 walshed01 ED WALSH 1937 SP 555.9 lajoina01 NAP LAJOIE 1937 SB 552.2 barnero01 ROSS BARNES 1937 SB 529.3 collied01 EDDIE COLLINS 1937 SB 528.5 speaktr01 TRIS SPEAKER 1937 CF 513.7 Runners-up 1937 youngcy01 broutda01 connoro01 delahed01 ansonca01 youngcy01 CY YOUNG 1938 SP 511.2 broutda01 DAN BROUTHERS 1938 FB 509.6 connoro01 ROGER CONNOR 1938 FB 496.3 delahed01 ED DELAHANTY 1938 LF 461.8 ansonca01 CAP ANSON 1938 FB 459.4 Runners-up 1938 glassja01 kellyki01 dahlebi01 planked01 ewingbu01 glassja01 JACK GLASSCOCK 1939 SS 448.4 kellyki01 KING KELLY 1939 RF 424.9 dahlebi01 BILL DAHLEN 1939 SS 417.6 planked01 EDDIE PLANK 1939 SP 413.2 ewingbu01 BUCK EWING 1939 C 412.0 Runners-up 1939 flickel01 hamilbi01 whitede01 jacksjo01 davisge01 flickel01 ELMER FLICK 1940 RF 410.4 hamilbi01 BILLY HAMILTON 1940 CF 406.2 whitede01 DEACON WHITE 1940 C 406.2 jacksjo01 JOE JACKSON 1940 RF 396.7 davisge01 GEORGE DAVIS 1940 SS 395.4 Runners-up 1940 wadderu01 jennihu01 rusieam01 mcgrajo01 seweljo01 ruthba01 BABE RUTH 1941 RF 742.3 vanceda01 DAZZY VANCE 1941 SP 420.7 wadderu01 RUBE WADDELL 1941 SP 390.5 jennihu01 HUGHIE JENNINGS 1941 SS 390.4 Runners-up 1941 rusieam01 mcgrajo01 seweljo01 ruckena01 clarkjo01 rusieam01 AMOS RUSIE 1942 SP 389.4 mcgrajo01 JOHN MCGRAW 1942 TB 387.4 seweljo01 JOE SEWELL 1942 SS 385.3 ruckena01 NAP RUCKER 1942 SP 384.3 Runners-up 1942 clarkjo01 cicoted01 jackstr01 brownth01 childcu01 hornsro01 ROGERS HORNSBY 1943 SB 563.2 friscfr01 FRANKIE FRISCH 1943 SB 403.6 clarkjo01 JOHN CLARKSON 1943 SP 383.0 cicoted01 EDDIE CICOTTE 1943 SP 382.5 Runners-up 1943 jackstr01 brownth01 childcu01 wallabo01 bennech01 jackstr01 TRAVIS JACKSON 1944 SS 378.4 brownth01 THREE_FINGER BROWN 1944 SP 375.3 childcu01 CUPID CHILDS 1944 SB 374.5 wallabo01 BOBBY WALLACE 1944 SS 372.5 Runners-up 1944 bennech01 covelst01 dunlafr01 willine01 cochrmi01 gehrilo01 LOU GEHRIG 1945 FB 559.6 bennech01 CHARLIE BENNETT 1945 C 368.1 covelst01 STAN COVELESKI 1945 SP 368.1 dunlafr01 FRED DUNLAP 1945 SB 367.0 Runners-up 1945 willine01 cochrmi01 thompsa01 wrighge01 terrybi01 willine01 NED WILLIAMSON 1946 TB 366.6 cochrmi01 MICKEY COCHRANE 1946 C 364.3 thompsa01 SAM THOMPSON 1946 RF 363.9 wrighge01 GEORGE WRIGHT 1946 SS 363.3 Runners-up 1946 terrybi01 whitnji01 chancfr01 bancrda01 keelewi01 grovele01 LEFTY GROVE 1947 SP 428.3 hartnga01 GABBY HARTNETT 1947 C 384.6 ferrewe01 WES FERRELL 1947 SP 371.5 terrybi01 BILL TERRY 1947 FB 363.1 Runners-up 1947 whitnji01 chancfr01 bancrda01 keelewi01 richaha01 gehrich01 CHARLIE GEHRINGER 1948 SB 451.6 whitnji01 JIM WHITNEY 1948 SP 362.8 chancfr01 FRANK CHANCE 1948 FB 360.5 bancrda01 DAVE BANCROFT 1948 SS 355.8 Runners-up 1948 keelewi01 richaha01 faberre01 whitedo01 colliji01 hubbeca01 CARL HUBBELL 1949 SP 478.4 keelewi01 WILLIE KEELER 1949 RF 354.4 richaha01 HARDY RICHARDSON 1949 SB 354.0 faberre01 RED FABER 1949 SP 352.3 Runners-up 1949 whitedo01 colliji01 radboch01 jossad01 vaughhi01 whitedo01 DOC WHITE 1950 SP 352.1 colliji01 JIMMY COLLINS 1950 TB 351.8 simmoal01 AL SIMMONS 1950 LF 349.8 kleinch01 CHUCK KLEIN 1950 RF 346.1 Runners-up 1950 radboch01 jossad01 vaughhi01 longhe01 mcginjo01 foxxji01 JIMMIE FOXX 1951 FB 463.3 cronijo01 JOE CRONIN 1951 SS 451.2 wanerpa01 PAUL WANER 1951 RF 440.9 warnelo01 LON WARNEKE 1951 SP 359.7 Runners-up 1951 radboch01 jossad01 vaughhi01 longhe01 mcginjo01 dickebi01 BILL DICKEY 1952 C 412.5 lyonste01 TED LYONS 1952 SP 356.1 radboch01 CHARLES RADBOURN 1952 SP 344.7 jossad01 ADDIE JOSS 1952 SP 344.2 Runners-up 1952 vaughhi01 longhe01 mcginjo01 heilmha01 bartedi01 ottme01 MEL OTT 1953 RF 481.3 hermabi01 BILLY HERMAN 1953 SB 397.0 greenha01 HANK GREENBERG 1953 FB 389.2 deandi01 DIZZY DEAN 1953 SP 378.7 Runners-up 1953 passecl01 ruffire01 vaughhi01 longhe01 mcginjo01 vaughar01 ARKY VAUGHAN 1954 SS 489.2 medwijo01 JOE MEDWICK 1954 LF 414.6 passecl01 CLAUDE PASSEAU 1954 SP 371.7 ruffire01 RED RUFFING 1954 SP 346.4 Runners-up 1954 vaughhi01 longhe01 mcginjo01 heilmha01 bartedi01 vaughhi01 HIPPO VAUGHN 1955 SP 343.6 longhe01 HERMAN LONG 1955 SS 343.3 mcginjo01 JOE MCGINNITY 1955 SP 342.1 heilmha01 HARRY HEILMANN 1955 RF 341.4 Runners-up 1955 bartedi01 carutbo01 fletcar01 sislege01 hackst01 gordojo01 JOE GORDON 1956 SB 422.4 applilu01 LUKE APPLING 1956 SS 413.1 waltebu01 BUCKY WALTERS 1956 SP 398.9 Runners-up 1956 bartedi01 carutbo01 fletcar01 sislege01 hackst01 dimagjo01 JOE DIMAGGIO 1957 CF 465.8 doerrbo01 BOBBY DOERR 1957 SB 401.4 bartedi01 DICK BARTELL 1957 SS 341.0 Runners-up 1957 carutbo01 fletcar01 sislege01 hackst01 nichoki01 boudrlo01 LOU BOUDREAU 1958 SS 469.3 carutbo01 BOB CARUTHERS 1958 SP 339.1 fletcar01 ART FLETCHER 1958 SS 337.5 Runners-up 1958 sislege01 hackst01 nichoki01 camildo01 wardmo01 mizejo01 JOHNNY MIZE 1959 FB 427.5 leonadu02 DUTCH LEONARD 1959 SP 357.3 sislege01 GEORGE SISLER 1959 FB 337.3 Runners-up 1959 hackst01 nichoki01 camildo01 wardmo01 griffcl01 hackst01 STAN HACK 1960 TB 336.7 nichoki01 KID NICHOLS 1960 SP 335.7 camildo01 DOLPH CAMILLI 1960 FB 333.2 Runners-up 1960 wardmo01 griffcl01 johnsbo01 luquedo01 tanneje01 newhoha01 HAL NEWHOUSER 1961 SP 470.3 kinerra01 RALPH KINER 1961 LF 356.6 stephve01 VERN STEPHENS 1961 SS 331.9 Runners-up 1961 johnsbo01 galanau01 gomezle01 freylo01 stanked01 fellebo01 BOB FELLER 1962 SP 502.6 robinja02 JACKIE ROBINSON 1962 SB 433.3 johnsbo01 BOB JOHNSON 1962 LF 326.5 Runners-up 1962 galanau01 gomezle01 freylo01 stanked01 elliobo01 troutdi01 DIZZY TROUT 1963 SP 368.8 camparo01 ROY CAMPANELLA 1963 C 353.3 galanau01 AUGIE GALAN 1963 LF 322.9 Runners-up 1963 gomezle01 freylo01 stanked01 elliobo01 brechha01 lemonbo01 BOB LEMON 1964 SP 344.9 Runners-up 1964 reesepe01 gomezle01 freylo01 stanked01 elliobo01 reesepe01 PEE_WEE REESE 1965 SS 337.2 slaugen01 ENOS SLAUGHTER 1965 RF 316.9 Runners-up 1965 freylo01 stanked01 elliobo01 brechha01 peskyjo01 willite01 TED WILLIAMS 1966 LF 578.2 freylo01 LONNY FREY 1966 SB 311.6 Runners-up 1966 stanked01 elliobo01 brechha01 peskyjo01 nichobi01 garvene01 NED GARVER 1967 SP 319.4 Runners-up 1967 stanked01 elliobo01 brechha01 peskyjo01 nichobi01 ashburi01 RICHIE ASHBURN 1968 CF 436.4 stanked01 EDDIE STANKY 1968 SB 311.4 Runners-up 1968 elliobo01 brechha01 peskyjo01 nichobi01 rosenal01 musiast01 STAN MUSIAL 1969 LF 556.5 wynnea01 EARLY WYNN 1969 SP 345.8 Runners-up 1969 hodgegi01 schoere01 elliobo01 brechha01 peskyjo01 piercbi02 BILLY PIERCE 1970 SP 339.5 hodgegi01 GIL HODGES 1970 FB 330.2 Runners-up 1970 schoere01 snidedu01 elliobo01 brechha01 peskyjo01 spahnwa01 WARREN SPAHN 1971 SP 524.7 berrayo01 YOGI BERRA 1971 C 367.3 Runners-up 1971 foxne01 schoere01 snidedu01 elliobo01 brechha01 roberro01 ROBIN ROBERTS 1972 SP 472.4 koufasa01 SANDY KOUFAX 1972 SP 463.7 Runners-up 1972 frienbo01 foxne01 schoere01 snidedu01 elliobo01 frienbo01 BOB FRIEND 1973 SP 347.1 foxne01 NELLIE FOX 1973 SB 338.2 Runners-up 1973 fordwh01 schoere01 snidedu01 elliobo01 brechha01 matheed01 EDDIE MATHEWS 1974 TB 483.5 mantlmi01 MICKEY MANTLE 1974 CF 468.3 Runners-up 1974 fordwh01 schoere01 colavro01 snidedu01 jacksla01 drysddo01 DON DRYSDALE 1975 SP 435.5 boyerke01 KEN BOYER 1975 TB 361.5 Runners-up 1975 fordwh01 schoere01 colavro01 snidedu01 jacksla01 fordwh01 WHITEY FORD 1976 SP 328.2 schoere01 RED SCHOENDIENST 1976 SB 325.3 Runners-up 1976 colavro01 snidedu01 jacksla01 rosenal01 antonjo02 bankser01 ERNIE BANKS 1977 SS 448.3 bunniji01 JIM BUNNING 1977 SP 420.0 Runners-up 1977 pascuca02 colavro01 snidedu01 jacksla01 rosenal01 clemero01 ROBERTO CLEMENTE 1978 RF 370.3 pascuca02 CAMILO PASCUAL 1978 SP 341.1 Runners-up 1978 mazerbi01 willsma01 colavro01 snidedu01 jacksla01 mayswi01 WILLIE MAYS 1979 CF 646.3 mazerbi01 BILL MAZEROSKI 1979 SB 323.5 willsma01 MAURY WILLS 1979 SS 319.1 Runners-up 1979 colavro01 snidedu01 jacksla01 antonjo02 wilheho01 santoro01 RON SANTO 1980 TB 481.6 kalinal01 AL KALINE 1980 RF 397.5 Runners-up 1980 cepedor01 colavro01 cashno01 snidedu01 jacksla01 gibsobo01 BOB GIBSON 1981 SP 532.6 maricju01 JUAN MARICHAL 1981 SP 450.7 Runners-up 1981 cepedor01 osteecl01 colavro01 cashno01 snidedu01 aaronha01 HANK AARON 1982 RF 526.9 robinfr02 FRANK ROBINSON 1982 RF 501.1 Runners-up 1982 cepedor01 osteecl01 colavro01 cashno01 snidedu01 allendi01 DICK ALLEN 1983 TB 407.0 wynnji01 JIM WYNN 1983 CF 380.9 Runners-up 1983 robinbr01 cepedor01 torrejo01 osteecl01 colavro01 woodwi01 WILBUR WOOD 1984 SP 378.1 robinbr01 BROOKS ROBINSON 1984 TB 347.9 Runners-up 1984 cepedor01 torrejo01 osteecl01 colavro01 cashno01 cepedor01 ORLANDO CEPEDA 1985 FB 346.5 torrejo01 JOE TORRE 1985 C 330.9 hunteca01 CATFISH HUNTER 1985 SP 322.5 Runners-up 1985 osteecl01 colavro01 cashno01 fregoji01 snidedu01 mccovwi01 WILLIE MCCOVEY 1986 FB 413.2 osteecl01 CLAUDE OSTEEN 1986 SP 317.3 Runners-up 1986 colavro01 cashno01 fregoji01 jacksla01 stottme01 bondsbo01 BOBBY BONDS 1987 RF 339.4 colavro01 ROCKY COLAVITO 1987 RF 315.7 Runners-up 1987 cashno01 fregoji01 jacksla01 stottme01 lolicmi01 tiantlu01 LUIS TIANT 1988 SP 368.0 smithre06 REGGIE SMITH 1988 RF 322.4 Runners-up 1988 belanma01 stargwi01 cashno01 fregoji01 jacksla01 benchjo01 JOHNNY BENCH 1989 C 468.5 perryga01 GAYLORD PERRY 1989 SP 458.5 Runners-up 1989 jenkife01 yastrca01 campabe01 matlajo01 belanma01 morgajo02 JOE MORGAN 1990 SB 538.3 jenkife01 FERGIE JENKINS 1990 SP 423.8 Runners-up 1990 yastrca01 palmeji01 campabe01 matlajo01 belanma01 yastrca01 CARL YASTRZEMSKI 1991 LF 420.1 palmeji01 JIM PALMER 1991 SP 416.2 carewro01 ROD CAREW 1991 SB 388.0 Runners-up 1991 campabe01 koosmje01 matlajo01 belanma01 stargwi01 seaveto01 TOM SEAVER 1992 SP 530.9 grichbo01 BOBBY GRICH 1992 SB 471.3 Runners-up 1992 rosepe01 campabe01 fostege01 bluevi01 koosmje01 niekrph01 PHIL NIEKRO 1993 SP 420.1 rosepe01 PETE ROSE 1993 LF 399.3 Runners-up 1993 campabe01 fostege01 bluevi01 jacksre01 ceyro01 carltst01 STEVE CARLTON 1994 SP 517.4 campabe01 BERT CAMPANERIS 1994 SS 370.9 Runners-up 1994 fostege01 bluevi01 conceda01 suttodo01 guidrro01 schmimi01 MIKE SCHMIDT 1995 TB 550.8 fostege01 GEORGE FOSTER 1995 LF 367.3 evansda01 DARRELL EVANS 1995 TB 364.6 Runners-up 1995 bluevi01 conceda01 suttodo01 guidrro01 jacksre01 hernake01 KEITH HERNANDEZ 1996 FB 410.6 bluevi01 VIDA BLUE 1996 SP 361.1 Runners-up 1996 conceda01 suttodo01 guidrro01 jacksre01 ceyro01 reuscri01 RICK REUSCHEL 1997 SP 363.6 conceda01 DAVE CONCEPCION 1997 SS 360.8 Runners-up 1997 evansdw01 suttodo01 guidrro01 jacksre01 templga01 cartega01 GARY CARTER 1998 C 442.7 blylebe01 BERT BLYLEVEN 1998 SP 436.9 evansdw01 DWIGHT EVANS 1998 RF 358.6 Runners-up 1998 suttodo01 guidrro01 jacksre01 templga01 guerrpe01 yountro01 ROBIN YOUNT 1999 SS 427.0 brettge01 GEORGE BRETT 1999 TB 425.4 Runners-up 1999 ryanno01 tananfr01 suttodo01 guidrro01 jacksre01 ryanno01 NOLAN RYAN 2000 SP 424.2 tananfr01 FRANK TANANA 2000 SP 375.7 suttodo01 DON SUTTON 2000 SP 350.8 Runners-up 2000 guidrro01 jacksre01 gossari01 templga01 guerrpe01 guidrro01 RON GUIDRY 2001 SP 347.9 jacksre01 REGGIE JACKSON 2001 RF 345.9 Runners-up 2001 whitalo01 gossari01 templga01 guerrpe01 randowi01 smithoz01 OZZIE SMITH 2002 SS 469.7 trammal01 ALAN TRAMMELL 2002 SS 443.3 dawsoan01 ANDRE DAWSON 2002 CF 396.3 Runners-up 2002 violafr01 dykstle01 whitalo01 gossari01 templga01 sandbry01 RYNE SANDBERG 2003 SB 455.9 violafr01 FRANK VIOLA 2003 SP 385.7 Runners-up 2003 dykstle01 murraed02 whitalo01 gossari01 templga01 dykstle01 LENNY DYKSTRA 2004 CF 382.0 eckerde01 DENNIS ECKERSLEY 2004 SP 379.5 molitpa01 PAUL MOLITOR 2004 TB 369.5 Runners-up 2004 murraed02 whitalo01 gossari01 templga01 guerrpe01 boggswa01 WADE BOGGS 2005 TB 438.5 murraed02 EDDIE MURRAY 2005 FB 355.0 Runners-up 2005 whitalo01 langsma01 gossari01 templga01 guerrpe01 hershor01 OREL HERSHISER 2006 SP 420.8 clarkwi02 WILL CLARK 2006 FB 411.1 goodedw01 DWIGHT GOODEN 2006 SP 406.7 Runners-up 2006 belleal01 whitalo01 langsma01 gossari01 templga01 ripkeca01 CAL RIPKEN 2007 SS 562.1 mcgwima01 MARK MCGWIRE 2007 FB 428.2 Runners-up 2007 gwynnto01 saberbr01 belleal01 fernato01 whitalo01 gwynnto01 TONY GWYNN 2008 RF 426.1 saberbr01 BRET SABERHAGEN 2008 SP 419.6 raineti01 TIM RAINES 2008 LF 407.7 Runners-up 2008 finlech01 belleal01 fernato01 whitalo01 langsma01 henderi01 RICKEY HENDERSON 2009 LF 545.4 bellja01 JAY BELL 2009 SS 398.0 Runners-up 2009 coneda01 finlech01 belleal01 fernato01 whitalo01 larkiba01 BARRY LARKIN 2010 SS 442.5 alomaro01 ROBERTO ALOMAR 2010 SB 420.2 martied01 EDGAR MARTINEZ 2010 OT 404.2 Runners-up 2010 coneda01 finlech01 appieke01 belleal01 fernato01 brownke01 KEVIN BROWN 2011 SP 446.0 bagweje01 JEFF BAGWELL 2011 FB 439.0 Runners-up 2011 coneda01 finlech01 olerujo01 appieke01 belleal01 coneda01 DAVID CONE 2012 SP 380.8 finlech01 CHUCK FINLEY 2012 SP 373.9 olerujo01 JOHN OLERUD 2012 FB 373.6 Runners-up 2012 appieke01 belleal01 fernato01 palmera01 whitalo01 bondsba01 BARRY BONDS 2013 LF 720.8 clemero02 ROGER CLEMENS 2013 SP 628.2 Runners-up 2013 sosasa01 biggicr01 piazzmi01 schilcu01 appieke01 maddugr01 GREG MADDUX 2014 SP 577.1 thomafr04 FRANK THOMAS 2014 FB 444.8 kentje01 JEFF KENT 2014 SB 443.6 Runners-up 2014 sosasa01 biggicr01 mussimi01 glavito02 piazzmi01 johnsra05 RANDY JOHNSON 2015 SP 519.7 martipe02 PEDRO MARTINEZ 2015 SP 507.1 Runners-up 2015 sosasa01 biggicr01 mussimi01 glavito02 piazzmi01 griffke02 KEN GRIFFEY 2016 CF 458.4 sosasa01 SAMMY SOSA 2016 RF 443.2 biggicr01 CRAIG BIGGIO 2016 SB 425.8 Runners-up 2016 mussimi01 glavito02 piazzmi01 smoltjo01 schilcu01 mussimi01 MIKE MUSSINA 2017 SP 425.7 glavito02 TOM GLAVINE 2017 SP 415.3 Runners-up 2017 piazzmi01 smoltjo01 schilcu01 edmonji01 garcino01 rolensc01 SCOTT ROLEN 2018 TB 434.1 santajo01 JOHAN SANTANA 2018 SP 425.7 piazzmi01 MIKE PIAZZA 2018 C 414.3 Runners-up 2018 jonesch06 smoltjo01 schilcu01 edmonji01 garcino01 rodrial01 ALEX RODRIGUEZ 2019 SS 510.1 riverma01 MARIANO RIVERA 2019 RP 471.1 Runners-up 2019 hallaro01 heltoto01 jonesch06 smoltjo01 schilcu01
Still very much a work in progress…but as a present to everyone, story my first cut on 2015 projections are out.
Wrestling with unbelievable parity in the American League.
Kind of upstaged by today’s events, but I uploaded the 2014 Cuban stats to the site this weekend. Check under the “DTs by League” tab, and then change League to Cuban Serie Nacional.
I was working on a longer post to detail the fairly major change I made to the DT procedure for Cubans, but decided I kind of have to go now. So, short form and I’ll try to fill in the details at a later time.
So, first, a general word on the Cuban Serie Nacional, their top level league. The league consists of 16 teams, one for each of the country’s 15 provinces, plus one for the city of Havana. Until a few years it was one for each of the nation’s 14 provinces, plus two for Havana, but then the province of La Habana got split in two. They actually played with 17 teams for one year before axing one of Havana city’s two teams. Players generally play for their home region; there is little movement between teams.
The normal schedule length for the SN is 90 games, which allows for home-and-away three game series against each of the other 15 teams. The season runs roughly early November through March. In years with a World Baseball Classic, they have played just 45, sacrificing half the season to get their best players in front of the world. This past year – by that I mean the 2013/14 season, not the one that is currently being played – they played a 45 games schedule for all 16 teams, and then followed that with another 45 games between just the top 8 teams from the first half. It appears that some level of taking players from the bottom 8 teams was permitted. I’m honestly not sure how to handle the two halves. The stats listed under the link is just for the first half; the stats for the second half are listed here, under the “CB2” label. The second half had a slightly higher quality rating than the first half, which is reflected in the translations and part of why I didn’t just want to run them all together.
The quality rating for the league came in at .60, exactly halfway between my ratings for the high A leagues (.551) and AA (.642). The second half, with just the supplemented stronger teams rated as essentially AA (.63). That is stronger than I have rated the league in the past, but backed up by the performances of multiple players.
On the first run of the stats, I used the same DT method as last year, but took a close look at all the Cuban players who played outside of Cuba. For the first time, this included several players from the just-completed Cuban season, as a few Cuban players were allowed to play in Mexico and Japan. I compared the translation I made for their last three seasons in Cuba with those of their first three seasons after Cuba; I ignored players who had less than 200 total PA on either side of the transition; I ignored players who had a three-year or more layoff between their Cuban and American playing days.
I found that I was generally too pessimistic, especially in one particular category
EQA POW SPD Krt Wrt BABIP Average of Cuba DT .226 2 1 -1 -1 -13 Average non-Cuba DT .246 3 -1 0 -4 -2
The component scores reflect how many runs above or below average a player is based on a particular aspect of his performance. The Power score, for instance, reflects how many runs better than an average player he would be if his power – home runs and some doubles – were the only thing that was different between him and an average player over the course of 600 plate appearances.The SPD score is based on steals, triples, and doubles; the Krt is all about strikout rates; the Wrt is all about walks (and hit by pitch). The BABIP is about singles, and that is where my translations went wildly wrong in many cases. Yoennis Cespedes came to the US with a -17 BABIP , but he’s really been +2.
And it wasn’t simply that the translation program was too harsh – the BABIP numbers just didn’t match up. For the 30 players I tested, the correlations between Cuba BABIP and American BABIP was just .16. By contrast, POW had an .89 correlation, and SPD .77. EQA was at .55. The procedure was just a complete mess on this particular statistic.
I found, with testing, that I could make a much better estimate of the Cuban players’ American BABIP scores by looking at their other (Cuban) statistics. The regression equation that came out was
BABIP = -2 + 1.1*SPD + .30*POW + .49*Wrt + .20*Krt
Take Cespedes, for instance. The average of his last three years in Cuba was for a .244 EQA, and component scores of POW 9, SPD 3, Krt 2, Wrt -2, and BA -17. Apply the function above, and we get a new projected BABIP of +4.
Work that back into the statistics, the new translation for Cespedes looks like
AB H DB TP HR BB SO R RBI SB CS Out BA OBP SLG EqA EqR POW SPD KRt WRt BIP 593 136 32 3 24 49 100 93 79 9 2 849 .230 .291 .416 .244 68 9 3 2 -2 -17 593 171 28 3 24 49 100 100 86 9 2 785 .289 .344 .469 .278 88 8 1 2 -2 4 591 165 31 6 27 46 115 96 108 11 7 1202 .280 .335 .491 .278 89 13 2 -2 -2 2
the first line is the old way of doing the DT, for Cespedes’ 2009-2011 seasons. The second line is the revised way, and the third line is his combined 2012-2014 totals. (All have been adjusted to 650 PA, with the exception of the Outs column). Clearly – a much better fit.
It wasn’t just Cespedes who benefitted. The correlation between projected and actual BABIP improved from .16 to .43. The correlation between projected and actual EQA improved from .55 to .63. It just works better, and I guess I’d have to be crazy not to use it.
I’ve rerun all the player cards with a 2015 projection, so you should be able to see indivduals up now.
Not that they won’t change between now and April, as I have any number of things to work through that are not included in this version. As a for instance, the default setting for league offense for 2015 is for the AL and NL to be the same as in 2014.
When I ran the cards for 2014, that default meant that I used the 2013 averages. That wasn’t so bad in the NL – league offense came in at 4.01 runs per 9 innings in 2014, compared to 4.04 in 2013 – but in the AL, offense had a far more substantial drop from 4.31 to 4.15. My forecasts for the majors as a whole was high by almost 500 runs, 2.4%; but about 350 of that came from the AL, against only 150 in the NL.
Stepping back for a historical perspective:
That’s runs per nine innings in the AL on a yearly basis (blue dashed lines) and as a 5-year moving average (solid red line). You’ll note that the 5-year average right now is on a solidly down and linear trend. It has fallen by 13, 9, 9, 9, and 6 points over the last five years. Should that trend continue, then next year’s 5-year average should fall another 9 points to 4.27 – which means that next year’s RPG would need to be about 4.01. The individual year trends also run to about 10 points per year, suggesting a 4.05. Absent some action by the league, it is hard to see the offense not dropping at least a little further next year. I’m thinking that something like 4.08 is a better forecast would be a better forecast than the 4.15 I would use by default.
Same deal in the NL:
Next year the last 4.40 RPG will scroll off the 5-year average, which is going to depress it even without further drops in the one-year average. Repeating last year’s 4.01 will cut the 5-yr average by another 7 points, to 4.11. Continuing the 10-point per year trend line would mean a one-year forecast of 3.87. You’ll note that the NL has operated with an apparent floor of about 3.8 runs, that only the 1968 season has penetrated since the dead ball era, so we are approaching the offensive levels at which the league has historically stepped in to make changes. I’m not as certain that the NL will decline further (as compared to the AL), so I think I will just let last year’s average roll forward.
A year go at this time, I was recuperating from brain surgery. And I had the idea that, for the anniversary of Jackie Robinson’s first major league game, I would run the translation process for Jackie Robinson’s 1946 season.
As it happened, I didn’t get home from the hospital unti April 12, which (combined with my fatigue level) meant I didn’t get a post ready by April 15. I did get it together shortly thereafter…can’t really remember now, but it was maybe a wek later.
But I didn’t post it. What would be better, I thought, was not just Jackie in isolation, but the whole International League for 1946.
And a little while later I had that, with a little help from the stats posted at baseball-reference.com. But I still didn’t post. Even better, I said to myself, would be the whole AAA for 1946, to be able to place Jackie in a reasonable prospect position. Sure I hadn’t planned on it, but after seeing what they had at b-ref I thought it would be pretty easy.
And it was. Still a little later on, I had the IL, PCL, and AA for 1946 all drawn up. It was nowhere close to Robinson’s debut date anymore, and I wasn’t coming up with any hook to wrap around it for a good post. So instead of posting anything, I just kept going, working my way through the AAA of 1947. And 1948. And so on.
By then we were through with the entire baseball season, and I still hadn’t posted anything about it. I had completed doing all the AAA teams, right up to 1980 where I had everything, and then started on b-ref’s list of Japanese teams.
So now, a year later, my head’s healed, and its another Jackie Robinson Day, and if I haven’t buried the lead enough already, and I’ve got translations for all AAA teams and players going back to 1946 posted on the site. And the Japanese Central and Pacific Leagues, along with all of their players, are translated back to those league’s debut in 1950. The links will be found under the “DTs by League” tab. The link for the league that started it all is here:
https://claydavenport.com/stats/webpages/1946/1946pageINTyearALL.shtml
In addition, the DTs links for all players should reflect their AAA stats.
There’s still some work to do with them. I still haven’t finished getting all of the fielding stats added, so lots of players are listed at the position “DH” – that’s the default when no fielding data is found. The park and difficulty factors are not as complete as they are for recent years…nature of the beast, I’m afraid. And there is, of course, no split data for minor league seasons before 2005.
Year Team Lge AB H DB TP HR BB SO R RBI SB CS Out BA OBP SLG EqA EqR POW SPD KRt WRt BIP 1946 Montreal____ Int 470 137 33 5 3 67 42 90 52 33 11 349 .291 .392 .402 .284 75 -14 10 18 6 4 1947 Brooklyn____ NL 600 168 37 3 16 68 54 134 50 39 0 445 .280 .372 .432 .289 100 -2 14 17 2 -4
Robinson’s 1946 DT shows a clearly above average hitter, one with excellent contact skills and outstanding speed. He has a bigtime number of doubles – interestingly enough, his minor league double count would be 42 when projected to the same 600 AB as his 1947 major league line – but a distinct lack of home runs. With the exception of the home runs, his lines are extremely close (and his 1948 would be equally similar).
Not quite two weeks into the season, and already a number of expected starters have dropped off the radar for the season.
Players who changed teams: Eduardo Nunez from NYY to MIN, the Mariners lose Carlos Triunfel to the Dodgers, Mike Fontenot goes from the Nationals to the Rays, the Cubs release Mitch Maier, the Brewers release Joe Thurston, Henry Blanco retires from the Diamondbacks, and the Giants waive Roger Kieschnick and the Diamondbacks pick him up; Nunez was the only one of the group I expected to have more than token playing time.
Among pitchers, Pedro Beato goes from the Reds to the Braves, Michael Brady travels from Miami to Anaheim, Prestonm Guilmet is traded from Cleveland to Baltimore, and Brian Omogrosso was released by the White Sox. I don’t think any of the pitchers were projected for more than 20 innings.
Other adjustments:
Braves: Dan Uggla’s .146 EQA has me raising the chances of him being replaced, by either Pastornicky or La Stella; BJ Upton’s .125 won’t hold off Logan Schafer. Ian Thomas, Gus Schlosser, and Pedro Beato pick up bullpen garbage time. The Marlins have to deal with Jacob Turner’ shoulder injury…I’ve taken 10 starts off him for now, but its still TBD how much time he’ll miss. The Mets had a more drastic shakeup of the pitching staff. With Parnell out, Valverde takes over as closer, and Torres moves to a setup slot that pretty much removes him from starter contention. It also looks like Duda has moved ahead of Davis in the first base race. Nothing changed for the Phillies except a little shaking out of the back end of the bullpen. The Nationals lose a month of Wilson Ramos; it also looks like Ryan Zimmerman will get time at 1B, which likely works out to plus time for Danny Espinosa.
Orioles: Small changes. Boosted Delmon Young at Nolan Reimold’s expense, raised the innings for guys currently in the pen like Britton, Stinson, and Meek; took Suk-min Yoon out of starter contention down the line after a disastrous first start in Norfolk. For Boston, The injuries to Middlebrooks and Victorino don’t really change their projections, but Bradley’s early hitting raises his future – that comes off my projections for Nava, Gomes, and Carp. Ryan Roberts slots in as a 3B backup. For the Yankees Yangervis Solarte soaks up most of the PA I’d given to Nunez. Scott Sizemore is off to a hot start, which could push out one of Brian Roberts or Kelly Johnson. No big changes for the Jays, while in Tampa Matt Moore’s injury really shakes up the rotation. I’ll bring in Erik Bedard for a dozen starts, add Cesar Ramos for a few, enhance Matt Andriese and Nate Karns, and shore up Jake Odorizzi’s job security.
White Sox: Avisail Garcia’s shoulder injury forces the Sox into the outfield I’d have started with (never been a Garcia fan). The forecasts for all of them were a little muddy, with four fairly equal players for three spots; Jordan Danks is less likely to force any of Eaton/Viciedo/De Aza out of a job. I guessed wrong about Nate Jones getting the closer job out of camp, so there’s a pretty strong bullpen shuffle there. Lindstrom’s not clearly better than any of Downs, Webb, or Jones, but the guy who has the job now has a clear advantage for playing time over any contender. No substantive changes for the Indians. The Carlos Santana experiment has lasted this long, so it gets a little bump up. Twins: Scaled back Buxton’s arrival, as his wrist injury isn’t healing rapidly…plus, its a wrist injury. Terrible ting for a ballplayer. Switched Chris Colabello in for things that were Parmelee. For the Tigers, the only thing I’ve got is some worry about Joe Nathan. I don’t have even that much to change for the Royals.
The A’s needed a lot of work, led by the demotion of Jim Johnson from closer. He could straighten himself out and regain the role, so he retains a share of the saves, but only as part of an even spread. The first base/DH spot is breaking a little differently than I envisioned, although more Callaspo/less Barton is a pretty good call for the team. In LA, the Angels will be without Josh Hamilton for a quarter of the season after he hurt his thumb sliding head-first into first. That should mean a lot more JB Shuck, as well as more Cowbell…er, excuse me, Cowgill…thrown in as well. I also did a little reshuffling in the bullpen, with Burnett being slow to return and Brian Moran lost for the season. The Rangers’ rotation remains an injury-riddled mess, with Scott Baker added as another option. With the Mariners, I shorted Logan Morrison a bit, as we get to see how the OF/1B/DH shuffle arranges itself. Nothing has changed yet for the Astros.
Arizona is already starting to question their starting pitching choices in the wake of Patrick Corbin’s injury, as Randall Delgado will move to relief while Josh Collmenter gets another shot at starting. Archie Bradley will be up there sooner or later. The Dodgers were pretty much set – though I did change second base from “Leans Dee Gordon” to “Safe Dee Gordon”. For the Giants, I enhanced Michael Morse as a clearer LF starter. With the Padres, I didn’t even have that. All I’ve got for the Rockies is to clarify Charlie Blackmon as the primary center fielder.
Chicago’s Cubs are another team getting into the closer shuffle, as Jose Veras is demoted. I also have to go stronger on Emilio Bonifacio than I wanted to. The Cardinals are still just as set as they were coming in – I’m just amazed at how much minor league talent they still have in the wings. With the Brewers, Henderson loses the closer fight with Francisco Rodriguez, among many changes in their bullpen from my forecast. For Cincinnati, I’m getting extremely worried about Mat Latos’ condition, so he gets a big drop in starts. On the plus side, Aroldis Chapman seems to be coming along on the short side of initial estimates, so his PT actually egts raised a bit. The biggest change I made for the Pirates is to bump up Gregory Polanco’s time, because the way he’s hammering AAA they won’t be able to keep him down much longer.
Hello everybody. Peabody here.
Shame I can’t earn any endorsements for the upcoming movie, because I can so do that voice. At least the original one, and when I’m not cold-ridden like I’ve been this weekend, pretty much confining myself to the room with the wood stove.
So I have looked back at the projections I released two weeks ago, and I did find one major mistake. Yes,there was much criticism of my methods being extremely conservative and not deviating very far from average – criticism which I didn’t necessarily take at full value, because, well, it is generally true. The methods, and the decisions leading to those methods – things like forcing the league totals to conform to last season’s league totals – force the system into a conservative mode. My default assumption is that there was nothing out of the ordinary.
But when I ran followup tests, like the average error of forecast components from the last few years – I found that I was going seriously astray. The process was something like this:
a) run analysis of the player’s performance over the last three years to set a baseline of expected performance. That is essentially just a weighted average of the last 3 seasons, with weights that vary by stat – some are more sensitive to just the most recent season, some to the entire three-year average, and some have little predictability at all.
b) compare that baseline performance with the baselines of players from baseball history. try to see if there is a consistent deviation from those baselines that can be applied to the current player.
Now, the weights in step A could be something like .523, .233, .150, which are for the hitter’s strikeout component. You’ll notice that they only add up to .896. That difference between the sum opf the components and 1 is a measure, a recognition, of regression to the mean – partiuclarly since my components are zero-based to league average. For a highly predictive statistic like batter K, the sum is close to 1. For hitter batting average, the sum is only .620; for pitcher delta-runs, it is barely 0.2.
The second step goes something like Baseline+delta*x, where delta is the difference between comparison players and their baselines, and x is an indicator of how useful those adjustments are. They go as high as 1, for speed and power, and are pretty near zero for things like those pitcher delta-runs.
The trouble is that I calculated the x component in a way that repeated the regression to the mean, essentially (baseline+delta)*x. The RTM was being double counted.
For an average player, the difference was essentially meaningless. But the more extreme they were, in any facet that I measured, then the bigger the effect. So Mike Trout, above average across the board, went from
BA OBA SLG EQA EQR WARP cPOW cSPD cSO cBB cBA
Mike Trout 0.302 0.386 0.510 .316 110 7.3 11 4 0 5 12
0.306 0.406 0.530 .332 123 8.9 12 7 -1 8 15
(these are from the ‘all hitters’ section, straight from the computer, without regressing to league norms; the numbers on the projection pages will be a little lower).
Speed was dramatically affected, in part because the most extreme players are so much farther from the average. Trout went from 26 SB to 40; Billy Hamilton went from 43 to 72. His power dropped from a -9 component before to -11 now (sometimes the R-T-M works in your favor). Miguel Cabrera went from 30 HR to 36.
Fortunately, the pitchers weren’t similarly affected; the double-counting coding error didn’t happen in that directory. I did take advantage of my analysis to updte the weights, which made for some differences. And the overdone regression to means had infected the fielding analysis as well, so that teams with good fielding weren’t getting enough credit for it, which did feed back on the pitcher ratings.
The effect on teams was dependent on having extreme players. Those that did, benefitted by perhaps a win, maybe two. It did let a little more spread into the standings, with peak wins inching up from 91 to 93 and min wins dropping from 67 to to 66.
So a quick look at the changes on the team level since 1/24, not all of which come from my code changes:
AL East: was TB 90 Bos 86 NY 85 Tor 78 Bal 77
now 90 89 86 79 81
The Orioles’ gain is mostly from me jumping the gun and sending A.J. Burnett their way, as he represents a big upgrade over their assorted fifth starter contenders. There was also a component for opponent quality that wasn’t kicking in – while the teams in the AL East were being judged harshly because of their ferocious schedule (playing other AL East teams), they weren’t receiving the compensating break – that their record isn’t an unbiased assessment of quality when they are NOT playing in the AL East.
AL Central: was DET 91 Cle 85 CWS 79 KC 77 Min 72
Det 89 82 78 77 71
And that quality change I just spoke kicks the AL Central in the teeth. Kansas City does well to stand pat with their 77-win forecast – the addition of Bruce Chen helps a little – while everyone else drops 1-3 games.
AL West: was OAK 88 TEX 87 LAA 84 Sea 83 Hou 70
now 91 85 86 81 67
Fixing the RTMs hurt Houston. Seattle was especially hurt by the changes in fielding, as they will have a lot of positional uncertainty – even the presumptive addition of an overrated Nelson Cruz doesn’t save them from a drop. Hosuton was also hurt by that, but Oakland did just fine. Trout alone benefitted by 15 runs from fixing the RTM error, and the Angels gained two games.
NL East: was WAS 87 ATL 85 NY 78 Mia 75 PHI 72
now 88 84 77 73 73
The Nationals gain a game on the Braves, based on the changes I made, because I don’t believe there’s been any player movement outside the bullpens.
NL Central: was STL 90 PIT 83 CIN 80 MIL 77 CHC 67
now 93 83 78 80 66
The Brewers added Matt Garza and Francisco Rodriguez, both pretty nice pickups, and Mark Reynolds makes their first base situation a little less desperate…but I am surprised at how they’ve switched places with the Reds. I promise, I’m not making any deliberate moves to hold the Reds back, but they keep on slipping.
NL West: was LA 88 SF 85 SD 83 Ari 78 Col 71
89 85 81 78 72
Not much change here, with the most notable one being the Padres’ loss of Luebke for the season. I don’t see Arroyo doing much but adding depth – he’s no better than the mostly Randall Delgado innings he replaces – and ditto for Maholm and the Dodgers.
Davis’ component-power score is only projected to be a +35 (he says “only”), after putting up a surprising 50 last year.
His three-year line for power going into 2014 is 29, 27, 50. I did a quick search for players who
1) had 250 PA each across a four season span
2) were 26-30 in the fourth season (Davis will be 28 this year);
3) averaged at least a +15 power in the first two years
4) was at least 15 runs better than each of the first two years
That gave us this list:
yr4 age4 pow1 pow2 pow3 pow4 pow4-3
Jack Cust 2008 29 9 26 43 41 -2
Juan Diaz 2001 27 20 12 39 31 -8
Jim Gentile 1962 28 19 26 51 25 -26
Willie Horton 1969 26 22 26 41 21 -20
Todd Hundley 1997 28 19 20 43 36 -7
Adam LaRoche 2007 27 17 15 33 14 -19
Joey Meyer 1988 26 22 21 43 17 -26
Jai Miller 2012 27 20 19 38 16 -22
Kevin Mitchell 1990 28 16 18 54 32 -22
Mike Napoli 2009 27 22 15 39 19 -20
Dave Nicholson 1969 29 19 17 37 20 -17
Gene Oliver 1962 27 20 14 35 10 -25
David Ortiz 2004 28 17 17 32 34 2
Carlos Pena 2008 30 24 14 52 31 -21
Mark Reynolds 2010 26 20 22 39 34 -5
Tony Solaita 1976 29 22 19 54 15 -39
Gorman Thomas 1979 28 22 28 48 55 7
Jason Thompson 1982 27 12 21 42 30 -12
Jim Wynn 1968 26 15 16 35 29 -6
Only 2 out of 19 players (David Ortiz and Gorman Thomas) managed to up their power score yet again in the fourth year. The mean change from year3 is -15; the media change is -20. After averaging 42 in the boom year, they averaged a (still repectable, and still better than the first two years) 27 in the fourth year.
mark says:
Show your projections from last year.
On the Projections page, there are links to the 2012 and 2013. They are from the saved spreadsheets that I have from the dates given, and run through the same csv-to-webpage script I used to make the current pages.
tangotiger says:
To help people understand how the #1 team is forecasted to “average” 91 wins, can you also show the averages for #1 through #30? That is, take the highest win total for each of your simulations (regardless of team), and show us that average. Then do the same for the second highest and so on.
Andy says:
He has no team winning more than 91 games… very likely.. lol
Tom Sheffield says:
It’s still way too early for projections like this but I do find great fault with 91 wins being the best record in baseball this year. The AL East looks about right standings wise.
There’s an issue here that I find hard to explain.
It is almost certainly NOT the case that the best record in baseball will only amount to 91 wins. In fact, if you looked at the playoff chances page, you’ll see that the AL East says this
Average wins by position in AL East: 95.2 87.7 81.9 76.1 68.5
indicating that it will take 95 wins, on average, to win the division – even though no team in the division, on average, gets above 90. Every division, in fact, takes 94-95 wins to finish first. WTF? Teams don’t win _on average_. The winning team will be the one who combines a good projection AND beats their projection. If the past three years are any indication, the average team is going to be 5 games off these projections – and a couple of teams will miss by 20. In the odds page, I play the season out a million times. In the real world, it will only play once, and how you perform relative to your projection determines your final standing.
There is no doubt in my mind that the best teams will be better than their projection, and the worst teams will be worse. Last year, the six first place teams averaged 8.7 wins better than their projection. Only the Tigers were able to underperform their projection and still win their division.
The six second place teams were +6.5.
The third place teams averaged -0.2…basically zero. Just meeting your projection is a recipe for mediocrity.
The fourth place teams averaged -3.
The last place teams averaged -10.
Whether the projection error comes from mis-estimating the real quality, or just random luck, or a mid-season tradeoff of talent from the weak to the strong that exaggerates the difference…there will be errors, and they have as much to do with deciding the winners as real talent. I’m sorry if that sounds like a copout.
David Lowe says:
You might want to tweak your software. The Royals aren’t going to be 9 games worse than they were last year, bro.
arttieTHE1manparty says:
Insane! How does the computer project the Royals to get worse??? With that defense and relief corps? No way…
Any projection is going to upset fans of various teams, especially if the projection comes in lower than they think is deserved.
With the Royals, the big concern for me is the pitching. I expect Shields to come back about a half run in ERA, and I don’t see quality replacements for Santana and Chen, who surprisingly put up over 400 IP @ 3.50 ERA. Two things I will concede – there is some evidence, looking at the last two years of projections, that I under-count defense…or rather, that teams with good(bad) defense don’t get their runs allowed moved down(up) enough. The Royals and Orioles are two teams who might be suffering from that bias…if it is real. It didn’t show up in the 2011 data with nearly the same effect as in 2012-13.
Now, Guthrie at a 5.00-ish ERA. I’m perfectly comfortable with that projection. He was 20 runs above average in the DR component – my way of saying he gave up 20 runs less than expected, base don his other stats. He doesn’t have a history of putting up that kind of number, and even if he did, that component score heavily, heavily trends towards zero in future years. The issue I have with the projection, in retrospect, is that there’s no way he gets 30 starts with that levelof performance. Its not as though there’s a ton of depth there, though, so its not going to make a big difference, but future iterations are liable to come up a a couple of wins for them. It IS a process to run these stats, and this was just an opener.
JR says:
Sorry, but if you think the Reds will be under .500 your computer has a bad virus.
I predict that Cincinnati fans will become thoroughly sick of the phrase “you can’t steal first base” this season.
