42.1 介绍
这一章用Hitters数据集演示线性回归、回归自变量选择, 岭回归、lasso回归, 以及如何进行超参数调优。
考虑ISLR包的Hitters数据集。 此数据集有322个运动员的20个变量的数据, 其中的变量Salary(工资)是我们关心的。 变量包括:
library(tidyverse)
library(ISLR) # 参考书对应的包
data(Hitters)
names(Hitters)
## [1] "AtBat" "Hits" "HmRun" "Runs" "RBI" "Walks" "Years" "CAtBat" "CHits" "CHmRun" "CRuns" "CRBI" "CWalks" "League" "Division" "PutOuts" "Assists" "Errors" "Salary" "NewLeague"
数据集的详细变量信息如下:
glimpse(Hitters)
## Rows: 322
## Columns: 20
## $ AtBat <int> 293, 315, 479, 496, 321, 594, 185, 298, 323, 401, 574, 202, 418, 239, 196, 183, 568, 190, 407, 127, 413, 426, 22, 472, 629, 587, 324, 474, 550, 513, 313, 419, 517, 583, 204, 379, 161, 268, 346, 241, 181, 216, 200, 217, 194, 254, 416, 205, 542, 526, 457, 214, 19, 591, 403, 405, 244, 235, 313, 627, 416, 155, 236, 216, 24, 585, 191, 199, 521, 419, 311, 138, 512, 507, 529, 424, 351, 195, 388, 339, 561, 255, 677, 227, 614, 329, 637, 280, 155, 458, 314, 475, 317, 511, 278, 382, 565…
## $ Hits <int> 66, 81, 130, 141, 87, 169, 37, 73, 81, 92, 159, 53, 113, 60, 43, 39, 158, 46, 104, 32, 92, 109, 10, 116, 168, 163, 73, 129, 152, 137, 84, 108, 141, 168, 49, 106, 36, 60, 98, 61, 41, 54, 57, 46, 40, 68, 132, 57, 140, 146, 101, 53, 7, 168, 101, 102, 58, 61, 78, 177, 113, 44, 56, 53, 3, 139, 37, 53, 142, 113, 81, 31, 131, 122, 137, 119, 97, 55, 103, 96, 118, 70, 238, 46, 163, 83, 174, 82, 41, 114, 83, 123, 78, 138, 69, 119, 148, 71, 115, 110, 151, 132, 49, 106, 114, 37, 95, 154,…
## $ HmRun <int> 1, 7, 18, 20, 10, 4, 1, 0, 6, 17, 21, 4, 13, 0, 7, 3, 20, 2, 6, 8, 16, 3, 1, 16, 18, 4, 4, 10, 6, 20, 9, 6, 27, 17, 6, 10, 0, 5, 5, 1, 1, 0, 6, 7, 7, 2, 7, 8, 12, 13, 14, 2, 0, 19, 12, 18, 9, 3, 6, 25, 24, 6, 0, 1, 0, 31, 4, 5, 20, 1, 3, 8, 26, 29, 26, 6, 4, 5, 15, 4, 35, 7, 31, 7, 29, 9, 31, 16, 12, 13, 13, 27, 7, 25, 3, 13, 24, 2, 27, 15, 17, 9, 2, 16, 23, 8, 23, 22, 31, 4, 16, 16, 24, 31, 14, 34, 12, 14, 4, 3, 21, 16, 5, 11, 2, 16, 13, 5, 15, 21, 14, 10, 7, 1, 5, 4, 40, 6,…
## $ Runs <int> 30, 24, 66, 65, 39, 74, 23, 24, 26, 49, 107, 31, 48, 30, 29, 20, 89, 24, 57, 16, 72, 55, 4, 60, 73, 92, 32, 50, 92, 90, 42, 55, 70, 83, 23, 38, 19, 24, 31, 34, 15, 21, 23, 32, 19, 28, 57, 34, 46, 71, 42, 30, 1, 80, 45, 49, 28, 24, 32, 98, 58, 21, 27, 31, 1, 93, 12, 29, 67, 44, 42, 18, 69, 78, 86, 57, 55, 24, 59, 37, 70, 49, 117, 23, 89, 50, 89, 44, 21, 67, 39, 76, 35, 76, 24, 54, 90, 27, 97, 70, 61, 69, 41, 48, 67, 15, 55, 76, 101, 19, 70, 33, 81, 91, 30, 91, 63, 45, 42, 30, …
## $ RBI <int> 29, 38, 72, 78, 42, 51, 8, 24, 32, 66, 75, 26, 61, 11, 27, 15, 75, 8, 43, 22, 48, 43, 2, 62, 102, 51, 18, 56, 37, 95, 30, 36, 87, 80, 25, 60, 10, 25, 53, 12, 21, 18, 14, 19, 29, 26, 49, 32, 75, 70, 63, 29, 2, 72, 53, 85, 25, 39, 41, 81, 69, 23, 15, 15, 0, 94, 17, 22, 86, 27, 30, 21, 96, 85, 97, 46, 29, 33, 47, 29, 94, 35, 113, 20, 83, 39, 116, 45, 29, 57, 46, 93, 35, 96, 21, 58, 104, 29, 71, 47, 84, 47, 23, 56, 67, 19, 58, 84, 108, 18, 73, 52, 105, 101, 42, 108, 54, 47, 36, 4…
## $ Walks <int> 14, 39, 76, 37, 30, 35, 21, 7, 8, 65, 59, 27, 47, 22, 30, 11, 73, 15, 65, 14, 65, 62, 1, 74, 40, 70, 22, 40, 81, 90, 39, 22, 52, 56, 12, 30, 17, 15, 30, 14, 33, 15, 14, 9, 30, 22, 33, 9, 41, 84, 22, 23, 1, 39, 39, 20, 35, 21, 12, 70, 16, 15, 11, 22, 2, 62, 14, 21, 45, 44, 26, 38, 52, 91, 97, 13, 39, 30, 39, 23, 33, 43, 53, 12, 75, 56, 56, 47, 22, 48, 16, 72, 32, 61, 29, 36, 77, 14, 68, 36, 78, 54, 18, 35, 53, 15, 37, 43, 41, 11, 80, 37, 62, 64, 24, 52, 30, 26, 66, 20, 60, 41,…
## $ Years <int> 1, 14, 3, 11, 2, 11, 2, 3, 2, 13, 10, 9, 4, 6, 13, 3, 15, 5, 12, 8, 1, 1, 6, 6, 18, 6, 7, 10, 5, 14, 17, 3, 9, 5, 7, 14, 4, 2, 16, 1, 2, 18, 9, 4, 11, 6, 3, 5, 16, 6, 17, 2, 4, 9, 12, 6, 4, 14, 12, 6, 1, 16, 4, 4, 3, 17, 4, 3, 4, 12, 17, 3, 14, 18, 15, 9, 4, 8, 6, 4, 16, 15, 5, 5, 11, 9, 14, 2, 16, 4, 5, 4, 1, 3, 8, 12, 14, 15, 3, 7, 10, 2, 8, 10, 13, 6, 3, 14, 5, 1, 14, 5, 13, 3, 18, 6, 4, 16, 9, 8, 15, 20, 5, 5, 11, 13, 5, 8, 5, 7, 7, 5, 18, 4, 9, 3, 6, 15, 5, 2, 2, 4, 12, …
## $ CAtBat <int> 293, 3449, 1624, 5628, 396, 4408, 214, 509, 341, 5206, 4631, 1876, 1512, 1941, 3231, 201, 8068, 479, 5233, 727, 413, 426, 84, 1924, 8424, 2695, 1931, 2331, 2308, 5201, 6890, 591, 3571, 1646, 1309, 6207, 1053, 350, 5913, 241, 232, 7318, 2516, 694, 4183, 999, 932, 756, 7099, 2648, 6521, 226, 41, 4478, 5150, 950, 1335, 3926, 3742, 3210, 416, 6631, 1115, 926, 159, 7546, 773, 514, 815, 4484, 8247, 244, 5347, 7761, 6661, 3651, 1258, 1313, 2174, 1064, 6677, 6311, 2223, 1325, 5017, 3…
## $ CHits <int> 66, 835, 457, 1575, 101, 1133, 42, 108, 86, 1332, 1300, 467, 392, 510, 825, 42, 2273, 102, 1478, 180, 92, 109, 26, 489, 2464, 747, 491, 604, 633, 1382, 1833, 149, 994, 452, 308, 1906, 244, 78, 1615, 61, 50, 1926, 684, 160, 1069, 236, 273, 192, 2130, 715, 1767, 59, 13, 1307, 1429, 231, 333, 1029, 968, 927, 113, 1634, 270, 210, 28, 1982, 163, 120, 205, 1231, 2198, 53, 1397, 1947, 1785, 1046, 353, 338, 555, 290, 1575, 1661, 737, 324, 1388, 948, 2024, 113, 1338, 298, 405, 471, 78…
## $ CHmRun <int> 1, 69, 63, 225, 12, 19, 1, 0, 6, 253, 90, 15, 41, 4, 36, 3, 177, 5, 100, 24, 16, 3, 2, 67, 164, 17, 13, 61, 32, 166, 224, 8, 215, 44, 27, 146, 3, 5, 235, 1, 4, 46, 46, 32, 64, 21, 24, 32, 235, 77, 281, 2, 1, 113, 166, 29, 49, 35, 35, 133, 24, 98, 1, 9, 0, 315, 16, 8, 22, 32, 100, 12, 221, 347, 291, 32, 16, 25, 80, 11, 442, 154, 93, 44, 266, 145, 247, 25, 181, 28, 28, 108, 7, 28, 32, 41, 305, 60, 45, 38, 275, 14, 7, 86, 241, 36, 31, 131, 92, 4, 209, 71, 271, 53, 348, 107, 14, …
## $ CRuns <int> 30, 321, 224, 828, 48, 501, 30, 41, 32, 784, 702, 192, 205, 309, 376, 20, 1045, 65, 643, 67, 72, 55, 9, 242, 1008, 442, 291, 246, 349, 763, 1033, 80, 545, 219, 126, 859, 156, 34, 784, 34, 20, 796, 371, 86, 486, 108, 113, 117, 987, 352, 1003, 32, 3, 634, 747, 99, 164, 441, 409, 529, 58, 698, 116, 118, 20, 1141, 61, 57, 99, 612, 950, 33, 712, 1175, 1082, 461, 196, 144, 285, 123, 901, 1019, 349, 156, 813, 575, 978, 61, 746, 160, 156, 292, 35, 87, 258, 287, 1135, 753, 156, 335, 8…
## $ CRBI <int> 29, 414, 266, 838, 46, 336, 9, 37, 34, 890, 504, 186, 204, 103, 290, 16, 993, 23, 658, 82, 48, 43, 9, 251, 1072, 198, 108, 327, 182, 734, 864, 46, 652, 208, 132, 803, 86, 29, 901, 12, 29, 627, 230, 76, 493, 117, 121, 107, 1089, 342, 977, 32, 4, 563, 666, 138, 179, 401, 321, 472, 69, 661, 64, 69, 12, 1179, 74, 40, 103, 344, 909, 32, 815, 1152, 949, 301, 110, 149, 274, 108, 1210, 608, 401, 158, 822, 528, 1093, 70, 805, 123, 159, 343, 35, 110, 192, 294, 1234, 596, 119, 174, 1015…
## $ CWalks <int> 14, 375, 263, 354, 33, 194, 24, 12, 8, 866, 488, 161, 203, 207, 238, 11, 732, 39, 653, 56, 65, 62, 3, 240, 402, 317, 180, 166, 308, 784, 1087, 31, 337, 136, 66, 571, 107, 18, 560, 14, 45, 483, 195, 32, 608, 118, 80, 51, 431, 289, 619, 27, 4, 319, 526, 64, 194, 333, 170, 313, 16, 777, 57, 114, 9, 727, 52, 39, 78, 422, 690, 55, 548, 1380, 989, 112, 117, 153, 186, 55, 608, 820, 171, 67, 617, 635, 495, 63, 875, 122, 76, 267, 32, 71, 162, 227, 791, 259, 99, 258, 709, 90, 106, 248,…
## $ League <fct> A, N, A, N, N, A, N, A, N, A, A, N, N, A, N, A, N, A, A, N, N, A, A, N, A, A, N, N, N, A, A, N, N, A, A, N, A, N, A, N, A, N, N, A, A, A, N, A, A, N, A, N, A, A, A, N, N, A, N, A, A, N, A, N, A, A, N, A, A, A, N, N, A, A, A, A, N, N, A, A, A, N, A, A, N, A, N, A, A, A, A, N, A, A, N, N, A, N, N, N, A, A, A, A, A, A, N, A, A, A, A, N, N, N, N, A, A, A, N, A, N, N, A, N, N, A, A, A, N, A, N, N, A, A, N, N, A, A, A, A, A, A, N, N, A, N, A, A, A, A, A, A, N, N, N, A, N, N, A, A, …
## $ Division <fct> E, W, W, E, E, W, E, W, W, E, E, W, E, E, E, W, W, W, W, W, E, W, W, W, E, E, E, W, W, W, W, W, W, E, W, W, E, W, E, W, E, W, W, E, E, E, W, E, E, W, W, E, E, W, E, W, W, E, W, E, E, E, W, W, W, E, E, W, E, E, W, E, W, E, E, E, W, E, W, W, W, E, E, W, W, W, W, E, W, W, W, E, E, W, W, W, E, W, W, W, E, E, E, E, E, E, W, W, E, E, W, W, E, W, E, W, W, W, W, E, E, W, W, E, W, W, W, W, E, W, E, E, W, W, W, E, E, E, E, W, W, E, E, W, W, E, E, E, E, E, W, W, W, W, E, W, E, E, W, W, …
## $ PutOuts <int> 446, 632, 880, 200, 805, 282, 76, 121, 143, 0, 238, 304, 211, 121, 80, 118, 105, 102, 912, 202, 280, 361, 812, 518, 1067, 434, 222, 732, 262, 267, 127, 226, 1378, 109, 419, 72, 70, 442, 0, 166, 326, 103, 69, 307, 325, 359, 73, 58, 697, 303, 389, 109, 0, 67, 316, 161, 142, 425, 106, 240, 203, 53, 125, 73, 80, 0, 391, 152, 107, 211, 153, 244, 119, 808, 280, 224, 226, 83, 182, 104, 463, 51, 1377, 92, 303, 276, 278, 148, 165, 246, 533, 226, 45, 157, 142, 59, 292, 360, 274, 292, 1…
## $ Assists <int> 33, 43, 82, 11, 40, 421, 127, 283, 290, 0, 445, 45, 11, 151, 45, 0, 290, 177, 88, 22, 9, 22, 84, 55, 157, 9, 3, 83, 329, 5, 221, 7, 102, 292, 46, 170, 149, 59, 0, 172, 29, 84, 1, 25, 22, 30, 177, 4, 61, 9, 39, 7, 0, 147, 6, 10, 14, 43, 206, 482, 70, 88, 199, 152, 4, 0, 38, 3, 242, 2, 223, 21, 216, 108, 10, 286, 7, 2, 9, 213, 32, 54, 100, 2, 6, 6, 9, 4, 9, 389, 40, 10, 122, 7, 210, 156, 9, 32, 2, 6, 88, 327, 132, 41, 2, 115, 10, 439, 17, 5, 218, 87, 62, 111, 4, 334, 377, 6, 48…
## $ Errors <int> 20, 10, 14, 3, 4, 25, 7, 9, 19, 0, 22, 11, 7, 6, 8, 0, 10, 16, 9, 2, 5, 2, 11, 3, 14, 3, 3, 13, 16, 3, 7, 4, 8, 25, 5, 24, 12, 6, 0, 10, 5, 5, 1, 1, 2, 4, 18, 4, 9, 9, 4, 3, 0, 4, 5, 3, 2, 4, 7, 13, 10, 3, 13, 11, 0, 0, 8, 5, 23, 1, 10, 4, 12, 2, 5, 8, 3, 1, 4, 9, 8, 8, 6, 2, 6, 2, 9, 2, 1, 18, 4, 6, 26, 8, 10, 9, 5, 5, 7, 3, 13, 20, 10, 7, 4, 15, 7, 10, 10, 12, 16, 3, 8, 11, 4, 21, 26, 5, 19, 12, 9, 16, 7, 4, 20, 0, 5, 1, 4, 5, 15, 20, 0, 16, 1, 2, 3, 13, 5, 9, 14, 6, 3, 4, …
## $ Salary <dbl> NA, 475.000, 480.000, 500.000, 91.500, 750.000, 70.000, 100.000, 75.000, 1100.000, 517.143, 512.500, 550.000, 700.000, 240.000, NA, 775.000, 175.000, NA, 135.000, 100.000, 115.000, NA, 600.000, 776.667, 765.000, 708.333, 750.000, 625.000, 900.000, NA, 110.000, NA, 612.500, 300.000, 850.000, NA, 90.000, NA, NA, 67.500, NA, NA, 180.000, NA, 305.000, 215.000, 247.500, NA, 815.000, 875.000, 70.000, NA, 1200.000, 675.000, 415.000, 340.000, NA, 416.667, 1350.000, 90.000, 275.000, 2…
## $ NewLeague <fct> A, N, A, N, N, A, A, A, N, A, A, N, N, A, N, A, N, A, A, N, N, N, A, N, A, A, N, N, N, A, A, N, N, A, A, N, A, N, A, N, A, N, N, A, A, A, N, A, A, N, A, N, A, A, A, N, N, A, N, A, A, N, A, N, A, A, N, A, A, A, N, N, A, A, A, N, A, N, A, A, A, N, A, A, N, A, N, A, A, A, A, N, A, A, N, N, A, N, N, N, A, A, A, A, A, A, N, A, A, A, A, A, N, N, N, A, A, A, N, A, N, N, A, A, N, A, A, A, N, A, N, N, A, A, N, N, A, A, N, N, A, A, N, N, A, N, A, A, A, A, A, A, N, N, N, A, N, N, A, A, …
希望以Salary为因变量,查看其缺失值个数:
sum( is.na(Hitters$Salary) )
## [1] 59
为简单起见,去掉有缺失值的观测:
da_hit <- na.omit(Hitters); dim(da_hit)
## [1] 263 20
42.2 划分训练集和测试集
rsample包的initial_split
可以将一个数据集随机拆分为两个数据集, 称为训练集和测试集, 用prop
指定比例, 用strata
指定分层抽样基于的变量。 基于因变量使用分层抽样法划分训练集、测试集可以更具有代表性。
library(rsample)
set.seed(101)
hit_split <- initial_split(
da_hit, prop = 0.80, strata = Salary)
hit_train <- training(hit_split)
hit_test <- testing(hit_split)
42.3 回归自变量选择
42.3.1 最优子集选择
用leaps包的regsubsets()
函数计算最优子集回归, 办法是对某个试验性的子集自变量个数p̂ 值, 都找到p̂ 固定情况下残差平方和最小的变量子集, 这样只要在这些不同p̂ 的最优子集中挑选就可以了。 挑选可以用AIC、BIC等方法。
可以先进行一个包含所有自变量的全集回归:
regfit.full <- regsubsets(
Salary ~ ., data=hit_train, nvmax=19)
reg.summary <- summary(regfit.full)
reg.summary
## Subset selection object
## Call: regsubsets.formula(Salary ~ ., data = hit_train, nvmax = 19)
## 19 Variables (and intercept)
## Forced in Forced out
## AtBat FALSE FALSE
## Hits FALSE FALSE
## HmRun FALSE FALSE
## Runs FALSE FALSE
## RBI FALSE FALSE
## Walks FALSE FALSE
## Years FALSE FALSE
## CAtBat FALSE FALSE
## CHits FALSE FALSE
## CHmRun FALSE FALSE
## CRuns FALSE FALSE
## CRBI FALSE FALSE
## CWalks FALSE FALSE
## LeagueN FALSE FALSE
## DivisionW FALSE FALSE
## PutOuts FALSE FALSE
## Assists FALSE FALSE
## Errors FALSE FALSE
## NewLeagueN FALSE FALSE
## 1 subsets of each size up to 19
## Selection Algorithm: exhaustive
## AtBat Hits HmRun Runs RBI Walks Years CAtBat CHits CHmRun CRuns CRBI CWalks LeagueN DivisionW PutOuts Assists Errors NewLeagueN
## 1 ( 1 ) " " " " " " " " " " " " " " " " " " " " " " "*" " " " " " " " " " " " " " "
## 2 ( 1 ) " " "*" " " " " " " " " " " " " " " " " " " "*" " " " " " " " " " " " " " "
## 3 ( 1 ) " " "*" " " " " " " " " " " " " " " " " " " "*" " " " " "*" " " " " " " " "
## 4 ( 1 ) " " "*" " " " " " " " " " " " " " " " " " " "*" " " " " "*" "*" " " " " " "
## 5 ( 1 ) "*" "*" " " " " " " " " " " " " " " " " " " "*" " " " " "*" "*" " " " " " "
## 6 ( 1 ) "*" "*" " " " " " " "*" " " " " " " " " " " "*" " " " " "*" "*" " " " " " "
## 7 ( 1 ) "*" "*" " " " " " " "*" " " " " " " " " " " "*" "*" " " "*" "*" " " " " " "
## 8 ( 1 ) "*" "*" " " " " " " "*" " " " " " " " " "*" "*" "*" " " "*" "*" " " " " " "
## 9 ( 1 ) "*" "*" " " " " " " "*" " " " " " " "*" "*" " " "*" " " "*" "*" "*" " " " "
## 10 ( 1 ) "*" "*" " " " " " " "*" " " "*" " " " " "*" "*" "*" " " "*" "*" "*" " " " "
## 11 ( 1 ) "*" "*" " " " " " " "*" " " "*" " " " " "*" "*" "*" "*" "*" "*" "*" " " " "
## 12 ( 1 ) "*" "*" " " "*" " " "*" " " "*" " " " " "*" "*" "*" "*" "*" "*" "*" " " " "
## 13 ( 1 ) "*" "*" " " "*" " " "*" "*" "*" " " " " "*" "*" "*" "*" "*" "*" "*" " " " "
## 14 ( 1 ) "*" "*" " " "*" "*" "*" "*" "*" " " " " "*" "*" "*" "*" "*" "*" "*" " " " "
## 15 ( 1 ) "*" "*" " " "*" "*" "*" "*" "*" " " " " "*" "*" "*" "*" "*" "*" "*" "*" " "
## 16 ( 1 ) "*" "*" " " "*" "*" "*" "*" "*" "*" "*" "*" "*" "*" "*" "*" "*" "*" " " " "
## 17 ( 1 ) "*" "*" " " "*" "*" "*" "*" "*" "*" "*" "*" "*" "*" "*" "*" "*" "*" "*" " "
## 18 ( 1 ) "*" "*" " " "*" "*" "*" "*" "*" "*" "*" "*" "*" "*" "*" "*" "*" "*" "*" "*"
## 19 ( 1 ) "*" "*" "*" "*" "*" "*" "*" "*" "*" "*" "*" "*" "*" "*" "*" "*" "*" "*" "*"
这里用nvmax=
指定了允许所有的自变量都参加, 缺省行为是限制最多个数的。 上述结果表格中每一行给出了固定p̂ 条件下的最优子集。
试比较这些最优模型的BIC值:
reg.summary$bic
## [1] -63.90242 -86.59469 -90.68877 -93.51559 -96.29865 -96.35699 -95.24328 -94.33547 -91.79438 -89.31463 -85.07463 -80.40798 -75.33025 -70.12122 -64.82873 -59.53306 -54.25553 -48.92352 -43.58870
plot(reg.summary$bic)
图42.1: Hitters数据最优子集回归BIC
其中p̂ =5,6的值相近,都很低, 取p̂ =6。 用coef()
加id=6
指定第六种子集:
coef(regfit.full, id=6)
## (Intercept) AtBat Hits Walks CRBI DivisionW PutOuts
## 149.0951521 -2.1064928 8.2070703 3.2517011 0.6351933 -136.2935330 0.2646021
这种方法实现了选取BIC最小的自变量子集, 有6个自变量。
42.3.2 逐步回归方法
在用lm()
做了全集回归后, 把全集回归结果输入到stats::step()
函数中可以执行逐步回归。 如:
lm.full <- lm(Salary ~ ., data = hit_train)
print(summary(lm.full))
##
## Call:
## lm(formula = Salary ~ ., data = hit_train)
##
## Residuals:
## Min 1Q Median 3Q Max
## -918.96 -183.16 -35.62 138.30 1799.45
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 241.67291 109.57064 2.206 0.02862 *
## AtBat -2.48494 0.76899 -3.231 0.00145 **
## Hits 8.15485 2.84403 2.867 0.00461 **
## HmRun -0.37929 7.64779 -0.050 0.96050
## Runs -2.12109 3.59273 -0.590 0.55564
## RBI 0.76668 3.11770 0.246 0.80602
## Walks 6.27568 2.18144 2.877 0.00448 **
## Years -7.18987 15.10209 -0.476 0.63457
## CAtBat -0.14891 0.16372 -0.909 0.36425
## CHits 0.23486 0.78151 0.301 0.76411
## CHmRun 0.50158 1.97716 0.254 0.80002
## CRuns 1.11476 0.92330 1.207 0.22881
## CRBI 0.70183 0.84282 0.833 0.40606
## CWalks -0.83644 0.37968 -2.203 0.02881 *
## LeagueN 47.02170 94.26262 0.499 0.61848
## DivisionW -120.60207 48.51038 -2.486 0.01379 *
## PutOuts 0.26292 0.09121 2.883 0.00440 **
## Assists 0.38272 0.26915 1.422 0.15670
## Errors -1.28251 5.36074 -0.239 0.81118
## NewLeagueN -7.16809 94.61668 -0.076 0.93969
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 336.8 on 188 degrees of freedom
## Multiple R-squared: 0.5146, Adjusted R-squared: 0.4655
## F-statistic: 10.49 on 19 and 188 DF, p-value: < 2.2e-16
stats::step(lm.full)
## Start: AIC=2439.89
## Salary ~ AtBat + Hits + HmRun + Runs + RBI + Walks + Years +
## CAtBat + CHits + CHmRun + CRuns + CRBI + CWalks + League +
## Division + PutOuts + Assists + Errors + NewLeague
##
## Df Sum of Sq RSS AIC
## - HmRun 1 279 21327132 2437.9
## - NewLeague 1 651 21327504 2437.9
## - Errors 1 6493 21333346 2437.9
## - RBI 1 6860 21333713 2438.0
## - CHmRun 1 7301 21334153 2438.0
## - CHits 1 10245 21337098 2438.0
## - Years 1 25712 21352565 2438.1
## - League 1 28228 21355081 2438.2
## - Runs 1 39540 21366393 2438.3
## - CRBI 1 78662 21405515 2438.7
## - CAtBat 1 93836 21420689 2438.8
## - CRuns 1 165367 21492220 2439.5
## <none> 21326853 2439.9
## - Assists 1 229372 21556225 2440.1
## - CWalks 1 550572 21877425 2443.2
## - Division 1 701147 22028000 2444.6
## - Hits 1 932679 22259532 2446.8
## - Walks 1 938864 22265716 2446.8
## - PutOuts 1 942588 22269441 2446.9
## - AtBat 1 1184571 22511424 2449.1
##
## Step: AIC=2437.89
## Salary ~ AtBat + Hits + Runs + RBI + Walks + Years + CAtBat +
## CHits + CHmRun + CRuns + CRBI + CWalks + League + Division +
## PutOuts + Assists + Errors + NewLeague
##
## Df Sum of Sq RSS AIC
## - NewLeague 1 566 21327698 2435.9
## - Errors 1 6443 21333575 2436.0
## - CHmRun 1 7539 21334671 2436.0
## - CHits 1 9986 21337118 2436.0
## - RBI 1 12495 21339627 2436.0
## - Years 1 25478 21352610 2436.1
## - League 1 27950 21355082 2436.2
## - Runs 1 53429 21380561 2436.4
## - CAtBat 1 94340 21421471 2436.8
## - CRBI 1 96689 21423821 2436.8
## - CRuns 1 185367 21512499 2437.7
## <none> 21327132 2437.9
## - Assists 1 235593 21562725 2438.2
## - CWalks 1 575407 21902539 2441.4
## - Division 1 720408 22047540 2442.8
## - PutOuts 1 947076 22274208 2444.9
## - Walks 1 1002501 22329633 2445.4
## - Hits 1 1073306 22400438 2446.1
## - AtBat 1 1185325 22512457 2447.1
##
## Step: AIC=2435.9
## Salary ~ AtBat + Hits + Runs + RBI + Walks + Years + CAtBat +
## CHits + CHmRun + CRuns + CRBI + CWalks + League + Division +
## PutOuts + Assists + Errors
##
## Df Sum of Sq RSS AIC
## - Errors 1 6155 21333853 2434.0
## - CHmRun 1 7339 21335037 2434.0
## - CHits 1 9541 21337239 2434.0
## - RBI 1 12817 21340515 2434.0
## - Years 1 25398 21353097 2434.2
## - Runs 1 53335 21381033 2434.4
## - League 1 75071 21402769 2434.6
## - CAtBat 1 93812 21421510 2434.8
## - CRBI 1 98282 21425981 2434.9
## - CRuns 1 190610 21518308 2435.8
## <none> 21327698 2435.9
## - Assists 1 236010 21563708 2436.2
## - CWalks 1 577288 21904986 2439.4
## - Division 1 720061 22047759 2440.8
## - PutOuts 1 948064 22275762 2442.9
## - Walks 1 1003786 22331484 2443.5
## - Hits 1 1091940 22419639 2444.3
## - AtBat 1 1223590 22551289 2445.5
##
## Step: AIC=2433.96
## Salary ~ AtBat + Hits + Runs + RBI + Walks + Years + CAtBat +
## CHits + CHmRun + CRuns + CRBI + CWalks + League + Division +
## PutOuts + Assists
##
## Df Sum of Sq RSS AIC
## - CHmRun 1 6724 21340577 2432.0
## - CHits 1 7824 21341677 2432.0
## - RBI 1 11220 21345072 2432.1
## - Years 1 24104 21357956 2432.2
## - Runs 1 57526 21391379 2432.5
## - League 1 70922 21404775 2432.7
## - CAtBat 1 90644 21424497 2432.8
## - CRBI 1 100984 21434837 2432.9
## - CRuns 1 201382 21535235 2433.9
## <none> 21333853 2434.0
## - Assists 1 313674 21647527 2435.0
## - CWalks 1 593539 21927392 2437.7
## - Division 1 722945 22056798 2438.9
## - PutOuts 1 942739 22276592 2440.9
## - Walks 1 1040700 22374553 2441.9
## - Hits 1 1161864 22495717 2443.0
## - AtBat 1 1281359 22615212 2444.1
##
## Step: AIC=2432.03
## Salary ~ AtBat + Hits + Runs + RBI + Walks + Years + CAtBat +
## CHits + CRuns + CRBI + CWalks + League + Division + PutOuts +
## Assists
##
## Df Sum of Sq RSS AIC
## - CHits 1 2192 21342770 2430.1
## - RBI 1 12586 21353163 2430.2
## - Years 1 24971 21365548 2430.3
## - Runs 1 63054 21403631 2430.6
## - League 1 71042 21411619 2430.7
## - CAtBat 1 86281 21426858 2430.9
## <none> 21340577 2432.0
## - Assists 1 306971 21647548 2433.0
## - CRuns 1 433335 21773912 2434.2
## - CWalks 1 631568 21972145 2436.1
## - Division 1 716579 22057157 2436.9
## - PutOuts 1 954537 22295114 2439.1
## - CRBI 1 1001899 22342476 2439.6
## - Walks 1 1036407 22376984 2439.9
## - Hits 1 1187105 22527683 2441.3
## - AtBat 1 1283747 22624325 2442.2
##
## Step: AIC=2430.05
## Salary ~ AtBat + Hits + Runs + RBI + Walks + Years + CAtBat +
## CRuns + CRBI + CWalks + League + Division + PutOuts + Assists
##
## Df Sum of Sq RSS AIC
## - RBI 1 13190 21355960 2428.2
## - Years 1 29638 21372407 2428.3
## - League 1 72742 21415512 2428.8
## - Runs 1 81521 21424290 2428.8
## <none> 21342770 2430.1
## - CAtBat 1 230265 21573034 2430.3
## - Assists 1 307170 21649939 2431.0
## - CRuns 1 713710 22056479 2434.9
## - Division 1 715586 22058356 2434.9
## - CWalks 1 929774 22272544 2436.9
## - PutOuts 1 978714 22321484 2437.4
## - CRBI 1 1002770 22345540 2437.6
## - Walks 1 1086910 22429680 2438.4
## - AtBat 1 1599684 22942453 2443.1
## - Hits 1 1779918 23122687 2444.7
##
## Step: AIC=2428.18
## Salary ~ AtBat + Hits + Runs + Walks + Years + CAtBat + CRuns +
## CRBI + CWalks + League + Division + PutOuts + Assists
##
## Df Sum of Sq RSS AIC
## - Years 1 26692 21382651 2426.4
## - League 1 70307 21426266 2426.9
## - Runs 1 73753 21429713 2426.9
## <none> 21355960 2428.2
## - CAtBat 1 249406 21605365 2428.6
## - Assists 1 295538 21651497 2429.0
## - CRuns 1 702284 22058244 2432.9
## - Division 1 734085 22090044 2433.2
## - CWalks 1 937348 22293308 2435.1
## - PutOuts 1 1002301 22358261 2435.7
## - Walks 1 1086003 22441962 2436.5
## - CRBI 1 1439193 22795152 2439.7
## - AtBat 1 1640165 22996124 2441.6
## - Hits 1 1787801 23143761 2442.9
##
## Step: AIC=2426.43
## Salary ~ AtBat + Hits + Runs + Walks + CAtBat + CRuns + CRBI +
## CWalks + League + Division + PutOuts + Assists
##
## Df Sum of Sq RSS AIC
## - Runs 1 69079 21451730 2425.1
## - League 1 87548 21470199 2425.3
## <none> 21382651 2426.4
## - Assists 1 314039 21696690 2427.5
## - CAtBat 1 492567 21875218 2429.2
## - Division 1 725175 22107827 2431.4
## - CRuns 1 880113 22262764 2432.8
## - CWalks 1 988001 22370652 2433.8
## - PutOuts 1 1049648 22432299 2434.4
## - Walks 1 1079896 22462547 2434.7
## - CRBI 1 1420036 22802687 2437.8
## - AtBat 1 1614330 22996981 2439.6
## - Hits 1 1772982 23155633 2441.0
##
## Step: AIC=2425.11
## Salary ~ AtBat + Hits + Walks + CAtBat + CRuns + CRBI + CWalks +
## League + Division + PutOuts + Assists
##
## Df Sum of Sq RSS AIC
## - League 1 113492 21565223 2424.2
## <none> 21451730 2425.1
## - Assists 1 399827 21851557 2426.9
## - CAtBat 1 428452 21880182 2427.2
## - Division 1 727359 22179089 2430.0
## - CRuns 1 811308 22263038 2430.8
## - CWalks 1 947776 22399506 2432.1
## - Walks 1 1029714 22481444 2432.9
## - PutOuts 1 1153252 22604982 2434.0
## - CRBI 1 1434607 22886337 2436.6
## - AtBat 1 1793723 23245454 2439.8
## - Hits 1 1825947 23277677 2440.1
##
## Step: AIC=2424.2
## Salary ~ AtBat + Hits + Walks + CAtBat + CRuns + CRBI + CWalks +
## Division + PutOuts + Assists
##
## Df Sum of Sq RSS AIC
## <none> 21565223 2424.2
## - CAtBat 1 366456 21931678 2425.7
## - Assists 1 423017 21988240 2426.2
## - CRuns 1 756041 22321264 2429.4
## - Division 1 762166 22327389 2429.4
## - CWalks 1 998625 22563847 2431.6
## - Walks 1 1124976 22690198 2432.8
## - PutOuts 1 1245275 22810497 2433.9
## - CRBI 1 1393594 22958817 2435.2
## - Hits 1 1785448 23350671 2438.8
## - AtBat 1 1830070 23395292 2439.2
##
## Call:
## lm(formula = Salary ~ AtBat + Hits + Walks + CAtBat + CRuns +
## CRBI + CWalks + Division + PutOuts + Assists, data = hit_train)
##
## Coefficients:
## (Intercept) AtBat Hits Walks CAtBat CRuns CRBI CWalks DivisionW PutOuts Assists
## 235.9278 -2.5863 7.7364 5.9827 -0.1210 1.2468 0.9302 -0.9100 -123.4092 0.2893 0.3770
最后保留了10个自变量。
42.3.3 预测根均方误差计算
仅用训练集估计模型。 为了在测试集和交叉验证集上用模型进行预报并估计预测均方误差, 需要自己写一个预测函数:
predict.regsubsets <- function(object, newdata, id, ...){
form <- as.formula(object$call[[2]])
mat <- model.matrix(form, newdata)
coefi <- coef(object, id=id)
xvars <- names(coefi)
mat[, xvars] %*% coefi
}
42.3.4 用10折交叉验证方法选择最优子集
用交叉验证方法比较不同的模型, 使用tidymodels扩展包有标准的做法, 参见47.3。 这里为了对方法进行更直接的演示, 直接调用交叉验证函数进行超参数调优并在测试集上计算预测精度指标。
下列程序对数据中每一行分配一个折号:
set.seed(102)
hit_fold <- vfold_cv(hit_train, v = 10)
下面,对10折中每一折都分别当作测试集一次, 得到不同子集大小的根均方误差:
cv.errors <- matrix( as.numeric(NA), 10, 19, dimnames=list(NULL, paste(1:19)) )
for(j in 1:10){ # 折
d_ana <- analysis(hit_fold$splits[[j]])
d_ass <- assessment((hit_fold$splits[[j]]))
best.fit <- regsubsets(
Salary ~ .,
data = d_ana, nvmax=19)
for(i in 1:19){
pred <- predict(
best.fit, d_ass, id=i)
cv.errors[j, i] <-
mean( (d_ass[["Salary"]] - pred)^2 ) |> sqrt()
}
}
cv.errors[1:3, 1:5]
## 1 2 3 4 5
## [1,] 527.1116 448.7947 541.2805 486.2844 500.2707
## [2,] 380.8413 417.8030 339.0055 320.3588 294.5357
## [3,] 425.7064 407.8210 401.5712 381.7351 365.8554
cv.errors
是一个10×19矩阵, 每行对应一折作为测试集(或称评估集)的情形, 每列是一个子集大小, 元素值是预测的根均方误差。
对每列的10个元素求平均, 可以得到每个子集大小的平均根均方误差:
mean.cv.errors <- rowMeans(cv.errors)
mean.cv.errors
## [1] 446.5360 348.7238 370.0678 519.2774 403.6128 254.5081 298.6319 302.1066 387.7379 353.0201
best.id <- which.min(mean.cv.errors)
plot(mean.cv.errors, type='b',
main = "RMSE",
xlab = "p")
图42.2: Hitters数据CV均方误差
这样找到的最优子集大小是6, RMSE=254.5。 注意, 一般不需要用户自己进行这种交叉验证调参, 机器学习的函数一般都集成了这个功能。
用这种方法找到最优子集大小后, 可以对全数据集重新建模但是选择最优子集大小为6:
reg.best <- regsubsets(Salary ~ ., data = da_hit, nvmax=19)
coef(reg.best, id=best.id)
## (Intercept) AtBat Hits Walks CRBI DivisionW PutOuts
## 91.5117981 -1.8685892 7.6043976 3.6976468 0.6430169 -122.9515338 0.2643076
这样的模型可以用于同一问题的新增数据的预测。
42.4 岭回归
当自变量个数太多时,模型复杂度高, 可能有过度拟合, 模型不稳定。 自变量子集选择是降低复杂度的一种方法。
另一种方法是对较大的模型系数施加二次惩罚, 把最小二乘问题变成带有二次惩罚项的惩罚最小二乘问题:
min∑i=1n(yi−β0−β1xi1−⋯−βpxip)2+λ∑j=1pβ2j.
这比通常最小二乘得到的回归系数绝对值变小, 但是求解的稳定性增加了,避免了共线问题。 这种方法称为“正则化”(regularization), 其中的∑pj=1β2j称为正则项或者L2惩罚项。
实际上, 与线性模型Y=Xβ+ε 的普通最小二乘解 β̂ =(XTX)−1XTY 相比, 岭回归问题的解为
β̃ =(XTX+sI)−1XTY
其中I为单位阵,s>0与λ有关。
λ称为调节参数,λ越大,相当于模型复杂度越低。 适当选择λ可以在方差与偏差之间找到适当的折衷, 从而减小预测误差。 这样的参数不能从数据中直接估计, 称为“超参数”, 需要用模型比较的方法获得最优值。
由于量纲问题,在不同自变量不可比时,数据集应该进行标准化。
用R的glmnet包计算岭回归。 用glmnet()
函数, 指定参数alpha=0
时执行的是岭回归。 用参数lambda=
指定一个调节参数网格, 岭回归的算法可以进行一轮计算就获得所有这些调节参数上对应的参数估计。 用coef()
从回归结果中取得不同调节参数对应的回归系数估计, 结果是一个矩阵,每列对应于一个调节参数。
仍采用上面去掉了缺失值的Hitters数据集结果da_hit
。
glmnet包不支持R的公式界面, 所以用如下程序把回归的设计阵与因变量提取出来:
x <- model.matrix(Salary ~ ., hit_train)[,-1]
y <- hit_train$Salary
岭回归涉及到调节参数λ的选择, 为了绘图, 先选择λ的一个网格:
grid <- 10^seq(10, -2, length=100)
用所有数据针对这样的调节参数网格计算岭回归结果, 注意glmnet()
函数允许调节参数λ输入多个值:
ridge.mod <- glmnet(x, y, alpha=0, lambda=grid)
dim(coef(ridge.mod))
## [1] 20 100
glmnet()
函数默认对数据进行标准化。coef()
的结果是一个矩阵, 每列对应一个调节参数值, 其中的数值是回归系数估计值。
42.4.1 用10折交叉验证选取调节参数
如何进行超参数调优并在测试集上计算性能, tidymodels有系统的方法, 参见47.3。 这里为了对方法进行更直接的演示, 直接调用交叉验证函数进行超参数调优并在测试集上计算预测精度指标。
在训练集用交叉验证选择调节参数, 称为参数调优或者超参数调优。 cv.glmnet()
函数本身可以执行交叉验证, 不需要自己划分折:
set.seed(1)
cv.out <- cv.glmnet(x, y, alpha=0)
plot(cv.out)
图42.3: Hitters数据岭回归参数选择
bestlam <- cv.out$lambda.min
bestlam
## [1] 25.22831
这样获得了最优调节参数λ= 25.2283126。 用最优调节参数对测试集作预测, 得到预测根均方误差:
ridge.pred <- predict(
ridge.mod, s = bestlam,
newx = model.matrix(Salary ~ ., hit_test)[,-1])
mean( (ridge.pred - hit_test$Salary)^2 ) |> sqrt()
## [1] 240.7377
根均方误差240.7,比最优自变量子集方法的254.5要好。
最后,用选取的最优调节系数对全数据集建模, 得到相应的岭回归系数估计:
x <- model.matrix(Salary ~ ., da_hit)[,-1]
y <- da_hit$Salary
out <- glmnet(x, y, alpha=0)
predict(out, type='coefficients', s=bestlam)[1:20,]
## (Intercept) AtBat Hits HmRun Runs RBI Walks Years CAtBat CHits CHmRun CRuns CRBI CWalks LeagueN DivisionW PutOuts Assists Errors NewLeagueN
## 8.112693e+01 -6.815959e-01 2.772312e+00 -1.365680e+00 1.014826e+00 7.130224e-01 3.378558e+00 -9.066800e+00 -1.199478e-03 1.361029e-01 6.979958e-01 2.958896e-01 2.570711e-01 -2.789666e-01 5.321272e+01 -1.228345e+02 2.638876e-01 1.698796e-01 -3.685645e+00 -1.810510e+01
这样的模型可以用在同一问题的新数据预测上。
42.5 Lasso回归
另一种对回归系数的惩罚是L1惩罚:
min∑i=1n(yi−β0−β1xi1−⋯−βpxip)2+λ∑j=1p|βj|.(42.1)
奇妙地是, 当调节参数λ较大时, 可以使得部分回归系数变成零, 达到了即减小回归系数的绝对值又挑选重要变量子集的效果。
事实上,(42.1)等价于约束最小值问题
min∑i=1n(yi−β0−β1xi1−⋯−βpxip)2s.t.∑j=1p|βj|≤s.
其中s与λ一一对应。 这样的约束区域是带有顶点的凸集, 而目标函数是二次函数, 最小值点经常在约束区域顶点达到, 这些顶点是某些坐标等于零的点。 见图42.4。 图中阴影部分是约束区域, 注意4个顶点处都有一个回归系数等于0; 同心的椭圆线是目标函数的等值线, 椭圆中心处是目标函数的无约束最小值点, 即普通最小二乘的解, 而约束区域与目标函数值最小的等值线的交点出现在顶点处, 该处的β1=0。
knitr::include_graphics("figs/lasso-min.png")
图42.4: Lasso约束优化问题图示
对于每个调节参数λ, 都应该解出(42.1)的相应解, 记为β̂ (λ)。 幸运的是, 不需要对每个λ去解最小值问题(42.1), 存在巧妙的算法使得问题的计算量与求解一次最小二乘相仿。
通常选取λ的格子点,计算相应的惩罚回归系数。 用交叉验证方法估计预测的均方误差。 选取使得交叉验证均方误差最小的调节参数(一般R函数中已经作为选项)。
用R的glmnet包计算lasso。 用glmnet()
函数, 指定参数alpha=1
时执行的是lasso。 用参数lambda=
指定一个调节参数网格, lasso将输出这些调节参数对应的结果。 对回归结果使用plot()
函数可以画出调节参数变化时系数估计的变化情况。
仍使用gmlnet包的glmnet()
函数计算Lasso回归, 指定一个调节参数网格(沿用前面的网格):
x <- model.matrix(Salary ~ ., hit_train)[,-1]
y <- hit_train$Salary
lasso.mod <- glmnet(x, y, alpha=1, lambda=grid)
plot(lasso.mod)
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm): collapsing to unique 'x' values
图42.5: Hitters数据lasso轨迹
对lasso结果使用plot()
函数可以绘制延调节参数网格变化的各回归系数估计,横坐标不是调节参数而是调节参数对应的系数绝对值和, 可以看出随着系数绝对值和增大,实际是调节参数变小, 更多地自变量进入模型。
42.5.1 用交叉验证估计调节参数
如何进行超参数调优并在测试集上计算性能, tidymodels有系统的方法, 参见47.3。 这里为了对方法进行更直接的演示, 直接调用交叉验证函数进行超参数调优并在测试集上计算预测精度指标。
按照前面划分的训练集与测试集, 仅使用训练集数据做交叉验证估计最优调节参数:
set.seed(1)
cv.out <- cv.glmnet(x, y, alpha=1)
plot(cv.out)
![北京大学R语言教程(李东风)第42章: 正则化与惩罚回归](http://182.92.67.96/wp-content/uploads/2022/06/lazy.png)
bestlam <- cv.out$lambda.min; bestlam
## [1] 2.19423
得到调节参数估计后,对测试集计算预测均方误差:
lasso.pred <- predict(
lasso.mod, s = bestlam,
newx = model.matrix(Salary ~ ., hit_test)[,-1])
mean( (lasso.pred - hit_test$Salary)^2 ) |> sqrt()
## [1] 242.0375
RMSE=242.0, 这个效果比岭回归(RMSE=240.7)效果略差, 比最优子集方法(RMSE=254.5)好。
为了充分利用数据, 使用前面获得的最优调节参数, 对全数据集建模:
x <- model.matrix(Salary ~ ., da_hit)[,-1]
y <- da_hit$Salary
out <- glmnet(x, y, alpha=1, lambda=grid)
lasso.coef <- predict(
out, type='coefficients', s=bestlam)[1:20,]
lasso.coef[lasso.coef != 0]
## (Intercept) AtBat Hits HmRun Walks Years CAtBat CHmRun CRuns CRBI CWalks LeagueN DivisionW PutOuts Assists Errors
## 1.348925e+02 -1.689582e+00 5.971182e+00 9.734402e-02 4.978211e+00 -1.019167e+01 -9.794493e-05 5.650266e-01 7.036826e-01 3.867695e-01 -5.851131e-01 3.305686e+01 -1.193420e+02 2.760478e-01 2.008473e-01 -2.277618e+00
选择的自变量子集有15个自变量。
42.6 附录
42.6.1 Hitters数据
knitr::kable(Hitters)
AtBat | Hits | HmRun | Runs | RBI | Walks | Years | CAtBat | CHits | CHmRun | CRuns | CRBI | CWalks | League | Division | PutOuts | Assists | Errors | Salary | NewLeague | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
-Andy Allanson | 293 | 66 | 1 | 30 | 29 | 14 | 1 | 293 | 66 | 1 | 30 | 29 | 14 | A | E | 446 | 33 | 20 | NA | A |
-Alan Ashby | 315 | 81 | 7 | 24 | 38 | 39 | 14 | 3449 | 835 | 69 | 321 | 414 | 375 | N | W | 632 | 43 | 10 | 475.000 | N |
-Alvin Davis | 479 | 130 | 18 | 66 | 72 | 76 | 3 | 1624 | 457 | 63 | 224 | 266 | 263 | A | W | 880 | 82 | 14 | 480.000 | A |
-Andre Dawson | 496 | 141 | 20 | 65 | 78 | 37 | 11 | 5628 | 1575 | 225 | 828 | 838 | 354 | N | E | 200 | 11 | 3 | 500.000 | N |
-Andres Galarraga | 321 | 87 | 10 | 39 | 42 | 30 | 2 | 396 | 101 | 12 | 48 | 46 | 33 | N | E | 805 | 40 | 4 | 91.500 | N |
-Alfredo Griffin | 594 | 169 | 4 | 74 | 51 | 35 | 11 | 4408 | 1133 | 19 | 501 | 336 | 194 | A | W | 282 | 421 | 25 | 750.000 | A |
-Al Newman | 185 | 37 | 1 | 23 | 8 | 21 | 2 | 214 | 42 | 1 | 30 | 9 | 24 | N | E | 76 | 127 | 7 | 70.000 | A |
-Argenis Salazar | 298 | 73 | 0 | 24 | 24 | 7 | 3 | 509 | 108 | 0 | 41 | 37 | 12 | A | W | 121 | 283 | 9 | 100.000 | A |
-Andres Thomas | 323 | 81 | 6 | 26 | 32 | 8 | 2 | 341 | 86 | 6 | 32 | 34 | 8 | N | W | 143 | 290 | 19 | 75.000 | N |
-Andre Thornton | 401 | 92 | 17 | 49 | 66 | 65 | 13 | 5206 | 1332 | 253 | 784 | 890 | 866 | A | E | 0 | 0 | 0 | 1100.000 | A |
-Alan Trammell | 574 | 159 | 21 | 107 | 75 | 59 | 10 | 4631 | 1300 | 90 | 702 | 504 | 488 | A | E | 238 | 445 | 22 | 517.143 | A |
-Alex Trevino | 202 | 53 | 4 | 31 | 26 | 27 | 9 | 1876 | 467 | 15 | 192 | 186 | 161 | N | W | 304 | 45 | 11 | 512.500 | N |
-Andy VanSlyke | 418 | 113 | 13 | 48 | 61 | 47 | 4 | 1512 | 392 | 41 | 205 | 204 | 203 | N | E | 211 | 11 | 7 | 550.000 | N |
-Alan Wiggins | 239 | 60 | 0 | 30 | 11 | 22 | 6 | 1941 | 510 | 4 | 309 | 103 | 207 | A | E | 121 | 151 | 6 | 700.000 | A |
-Bill Almon | 196 | 43 | 7 | 29 | 27 | 30 | 13 | 3231 | 825 | 36 | 376 | 290 | 238 | N | E | 80 | 45 | 8 | 240.000 | N |
-Billy Beane | 183 | 39 | 3 | 20 | 15 | 11 | 3 | 201 | 42 | 3 | 20 | 16 | 11 | A | W | 118 | 0 | 0 | NA | A |
-Buddy Bell | 568 | 158 | 20 | 89 | 75 | 73 | 15 | 8068 | 2273 | 177 | 1045 | 993 | 732 | N | W | 105 | 290 | 10 | 775.000 | N |
-Buddy Biancalana | 190 | 46 | 2 | 24 | 8 | 15 | 5 | 479 | 102 | 5 | 65 | 23 | 39 | A | W | 102 | 177 | 16 | 175.000 | A |
-Bruce Bochte | 407 | 104 | 6 | 57 | 43 | 65 | 12 | 5233 | 1478 | 100 | 643 | 658 | 653 | A | W | 912 | 88 | 9 | NA | A |
-Bruce Bochy | 127 | 32 | 8 | 16 | 22 | 14 | 8 | 727 | 180 | 24 | 67 | 82 | 56 | N | W | 202 | 22 | 2 | 135.000 | N |
-Barry Bonds | 413 | 92 | 16 | 72 | 48 | 65 | 1 | 413 | 92 | 16 | 72 | 48 | 65 | N | E | 280 | 9 | 5 | 100.000 | N |
-Bobby Bonilla | 426 | 109 | 3 | 55 | 43 | 62 | 1 | 426 | 109 | 3 | 55 | 43 | 62 | A | W | 361 | 22 | 2 | 115.000 | N |
-Bob Boone | 22 | 10 | 1 | 4 | 2 | 1 | 6 | 84 | 26 | 2 | 9 | 9 | 3 | A | W | 812 | 84 | 11 | NA | A |
-Bob Brenly | 472 | 116 | 16 | 60 | 62 | 74 | 6 | 1924 | 489 | 67 | 242 | 251 | 240 | N | W | 518 | 55 | 3 | 600.000 | N |
-Bill Buckner | 629 | 168 | 18 | 73 | 102 | 40 | 18 | 8424 | 2464 | 164 | 1008 | 1072 | 402 | A | E | 1067 | 157 | 14 | 776.667 | A |
-Brett Butler | 587 | 163 | 4 | 92 | 51 | 70 | 6 | 2695 | 747 | 17 | 442 | 198 | 317 | A | E | 434 | 9 | 3 | 765.000 | A |
-Bob Dernier | 324 | 73 | 4 | 32 | 18 | 22 | 7 | 1931 | 491 | 13 | 291 | 108 | 180 | N | E | 222 | 3 | 3 | 708.333 | N |
-Bo Diaz | 474 | 129 | 10 | 50 | 56 | 40 | 10 | 2331 | 604 | 61 | 246 | 327 | 166 | N | W | 732 | 83 | 13 | 750.000 | N |
-Bill Doran | 550 | 152 | 6 | 92 | 37 | 81 | 5 | 2308 | 633 | 32 | 349 | 182 | 308 | N | W | 262 | 329 | 16 | 625.000 | N |
-Brian Downing | 513 | 137 | 20 | 90 | 95 | 90 | 14 | 5201 | 1382 | 166 | 763 | 734 | 784 | A | W | 267 | 5 | 3 | 900.000 | A |
-Bobby Grich | 313 | 84 | 9 | 42 | 30 | 39 | 17 | 6890 | 1833 | 224 | 1033 | 864 | 1087 | A | W | 127 | 221 | 7 | NA | A |
-Billy Hatcher | 419 | 108 | 6 | 55 | 36 | 22 | 3 | 591 | 149 | 8 | 80 | 46 | 31 | N | W | 226 | 7 | 4 | 110.000 | N |
-Bob Horner | 517 | 141 | 27 | 70 | 87 | 52 | 9 | 3571 | 994 | 215 | 545 | 652 | 337 | N | W | 1378 | 102 | 8 | NA | N |
-Brook Jacoby | 583 | 168 | 17 | 83 | 80 | 56 | 5 | 1646 | 452 | 44 | 219 | 208 | 136 | A | E | 109 | 292 | 25 | 612.500 | A |
-Bob Kearney | 204 | 49 | 6 | 23 | 25 | 12 | 7 | 1309 | 308 | 27 | 126 | 132 | 66 | A | W | 419 | 46 | 5 | 300.000 | A |
-Bill Madlock | 379 | 106 | 10 | 38 | 60 | 30 | 14 | 6207 | 1906 | 146 | 859 | 803 | 571 | N | W | 72 | 170 | 24 | 850.000 | N |
-Bobby Meacham | 161 | 36 | 0 | 19 | 10 | 17 | 4 | 1053 | 244 | 3 | 156 | 86 | 107 | A | E | 70 | 149 | 12 | NA | A |
-Bob Melvin | 268 | 60 | 5 | 24 | 25 | 15 | 2 | 350 | 78 | 5 | 34 | 29 | 18 | N | W | 442 | 59 | 6 | 90.000 | N |
-Ben Oglivie | 346 | 98 | 5 | 31 | 53 | 30 | 16 | 5913 | 1615 | 235 | 784 | 901 | 560 | A | E | 0 | 0 | 0 | NA | A |
-Bip Roberts | 241 | 61 | 1 | 34 | 12 | 14 | 1 | 241 | 61 | 1 | 34 | 12 | 14 | N | W | 166 | 172 | 10 | NA | N |
-BillyJo Robidoux | 181 | 41 | 1 | 15 | 21 | 33 | 2 | 232 | 50 | 4 | 20 | 29 | 45 | A | E | 326 | 29 | 5 | 67.500 | A |
-Bill Russell | 216 | 54 | 0 | 21 | 18 | 15 | 18 | 7318 | 1926 | 46 | 796 | 627 | 483 | N | W | 103 | 84 | 5 | NA | N |
-Billy Sample | 200 | 57 | 6 | 23 | 14 | 14 | 9 | 2516 | 684 | 46 | 371 | 230 | 195 | N | W | 69 | 1 | 1 | NA | N |
-Bill Schroeder | 217 | 46 | 7 | 32 | 19 | 9 | 4 | 694 | 160 | 32 | 86 | 76 | 32 | A | E | 307 | 25 | 1 | 180.000 | A |
-Butch Wynegar | 194 | 40 | 7 | 19 | 29 | 30 | 11 | 4183 | 1069 | 64 | 486 | 493 | 608 | A | E | 325 | 22 | 2 | NA | A |
-Chris Bando | 254 | 68 | 2 | 28 | 26 | 22 | 6 | 999 | 236 | 21 | 108 | 117 | 118 | A | E | 359 | 30 | 4 | 305.000 | A |
-Chris Brown | 416 | 132 | 7 | 57 | 49 | 33 | 3 | 932 | 273 | 24 | 113 | 121 | 80 | N | W | 73 | 177 | 18 | 215.000 | N |
-Carmen Castillo | 205 | 57 | 8 | 34 | 32 | 9 | 5 | 756 | 192 | 32 | 117 | 107 | 51 | A | E | 58 | 4 | 4 | 247.500 | A |
-Cecil Cooper | 542 | 140 | 12 | 46 | 75 | 41 | 16 | 7099 | 2130 | 235 | 987 | 1089 | 431 | A | E | 697 | 61 | 9 | NA | A |
-Chili Davis | 526 | 146 | 13 | 71 | 70 | 84 | 6 | 2648 | 715 | 77 | 352 | 342 | 289 | N | W | 303 | 9 | 9 | 815.000 | N |
-Carlton Fisk | 457 | 101 | 14 | 42 | 63 | 22 | 17 | 6521 | 1767 | 281 | 1003 | 977 | 619 | A | W | 389 | 39 | 4 | 875.000 | A |
-Curt Ford | 214 | 53 | 2 | 30 | 29 | 23 | 2 | 226 | 59 | 2 | 32 | 32 | 27 | N | E | 109 | 7 | 3 | 70.000 | N |
-Cliff Johnson | 19 | 7 | 0 | 1 | 2 | 1 | 4 | 41 | 13 | 1 | 3 | 4 | 4 | A | E | 0 | 0 | 0 | NA | A |
-Carney Lansford | 591 | 168 | 19 | 80 | 72 | 39 | 9 | 4478 | 1307 | 113 | 634 | 563 | 319 | A | W | 67 | 147 | 4 | 1200.000 | A |
-Chet Lemon | 403 | 101 | 12 | 45 | 53 | 39 | 12 | 5150 | 1429 | 166 | 747 | 666 | 526 | A | E | 316 | 6 | 5 | 675.000 | A |
-Candy Maldonado | 405 | 102 | 18 | 49 | 85 | 20 | 6 | 950 | 231 | 29 | 99 | 138 | 64 | N | W | 161 | 10 | 3 | 415.000 | N |
-Carmelo Martinez | 244 | 58 | 9 | 28 | 25 | 35 | 4 | 1335 | 333 | 49 | 164 | 179 | 194 | N | W | 142 | 14 | 2 | 340.000 | N |
-Charlie Moore | 235 | 61 | 3 | 24 | 39 | 21 | 14 | 3926 | 1029 | 35 | 441 | 401 | 333 | A | E | 425 | 43 | 4 | NA | A |
-Craig Reynolds | 313 | 78 | 6 | 32 | 41 | 12 | 12 | 3742 | 968 | 35 | 409 | 321 | 170 | N | W | 106 | 206 | 7 | 416.667 | N |
-Cal Ripken | 627 | 177 | 25 | 98 | 81 | 70 | 6 | 3210 | 927 | 133 | 529 | 472 | 313 | A | E | 240 | 482 | 13 | 1350.000 | A |
-Cory Snyder | 416 | 113 | 24 | 58 | 69 | 16 | 1 | 416 | 113 | 24 | 58 | 69 | 16 | A | E | 203 | 70 | 10 | 90.000 | A |
-Chris Speier | 155 | 44 | 6 | 21 | 23 | 15 | 16 | 6631 | 1634 | 98 | 698 | 661 | 777 | N | E | 53 | 88 | 3 | 275.000 | N |
-Curt Wilkerson | 236 | 56 | 0 | 27 | 15 | 11 | 4 | 1115 | 270 | 1 | 116 | 64 | 57 | A | W | 125 | 199 | 13 | 230.000 | A |
-Dave Anderson | 216 | 53 | 1 | 31 | 15 | 22 | 4 | 926 | 210 | 9 | 118 | 69 | 114 | N | W | 73 | 152 | 11 | 225.000 | N |
-Doug Baker | 24 | 3 | 0 | 1 | 0 | 2 | 3 | 159 | 28 | 0 | 20 | 12 | 9 | A | W | 80 | 4 | 0 | NA | A |
-Don Baylor | 585 | 139 | 31 | 93 | 94 | 62 | 17 | 7546 | 1982 | 315 | 1141 | 1179 | 727 | A | E | 0 | 0 | 0 | 950.000 | A |
-Dann Bilardello | 191 | 37 | 4 | 12 | 17 | 14 | 4 | 773 | 163 | 16 | 61 | 74 | 52 | N | E | 391 | 38 | 8 | NA | N |
-Daryl Boston | 199 | 53 | 5 | 29 | 22 | 21 | 3 | 514 | 120 | 8 | 57 | 40 | 39 | A | W | 152 | 3 | 5 | 75.000 | A |
-Darnell Coles | 521 | 142 | 20 | 67 | 86 | 45 | 4 | 815 | 205 | 22 | 99 | 103 | 78 | A | E | 107 | 242 | 23 | 105.000 | A |
-Dave Collins | 419 | 113 | 1 | 44 | 27 | 44 | 12 | 4484 | 1231 | 32 | 612 | 344 | 422 | A | E | 211 | 2 | 1 | NA | A |
-Dave Concepcion | 311 | 81 | 3 | 42 | 30 | 26 | 17 | 8247 | 2198 | 100 | 950 | 909 | 690 | N | W | 153 | 223 | 10 | 320.000 | N |
-Darren Daulton | 138 | 31 | 8 | 18 | 21 | 38 | 3 | 244 | 53 | 12 | 33 | 32 | 55 | N | E | 244 | 21 | 4 | NA | N |
-Doug DeCinces | 512 | 131 | 26 | 69 | 96 | 52 | 14 | 5347 | 1397 | 221 | 712 | 815 | 548 | A | W | 119 | 216 | 12 | 850.000 | A |
-Darrell Evans | 507 | 122 | 29 | 78 | 85 | 91 | 18 | 7761 | 1947 | 347 | 1175 | 1152 | 1380 | A | E | 808 | 108 | 2 | 535.000 | A |
-Dwight Evans | 529 | 137 | 26 | 86 | 97 | 97 | 15 | 6661 | 1785 | 291 | 1082 | 949 | 989 | A | E | 280 | 10 | 5 | 933.333 | A |
-Damaso Garcia | 424 | 119 | 6 | 57 | 46 | 13 | 9 | 3651 | 1046 | 32 | 461 | 301 | 112 | A | E | 224 | 286 | 8 | 850.000 | N |
-Dan Gladden | 351 | 97 | 4 | 55 | 29 | 39 | 4 | 1258 | 353 | 16 | 196 | 110 | 117 | N | W | 226 | 7 | 3 | 210.000 | A |
-Danny Heep | 195 | 55 | 5 | 24 | 33 | 30 | 8 | 1313 | 338 | 25 | 144 | 149 | 153 | N | E | 83 | 2 | 1 | NA | N |
-Dave Henderson | 388 | 103 | 15 | 59 | 47 | 39 | 6 | 2174 | 555 | 80 | 285 | 274 | 186 | A | W | 182 | 9 | 4 | 325.000 | A |
-Donnie Hill | 339 | 96 | 4 | 37 | 29 | 23 | 4 | 1064 | 290 | 11 | 123 | 108 | 55 | A | W | 104 | 213 | 9 | 275.000 | A |
-Dave Kingman | 561 | 118 | 35 | 70 | 94 | 33 | 16 | 6677 | 1575 | 442 | 901 | 1210 | 608 | A | W | 463 | 32 | 8 | NA | A |
-Davey Lopes | 255 | 70 | 7 | 49 | 35 | 43 | 15 | 6311 | 1661 | 154 | 1019 | 608 | 820 | N | E | 51 | 54 | 8 | 450.000 | N |
-Don Mattingly | 677 | 238 | 31 | 117 | 113 | 53 | 5 | 2223 | 737 | 93 | 349 | 401 | 171 | A | E | 1377 | 100 | 6 | 1975.000 | A |
-Darryl Motley | 227 | 46 | 7 | 23 | 20 | 12 | 5 | 1325 | 324 | 44 | 156 | 158 | 67 | A | W | 92 | 2 | 2 | NA | A |
-Dale Murphy | 614 | 163 | 29 | 89 | 83 | 75 | 11 | 5017 | 1388 | 266 | 813 | 822 | 617 | N | W | 303 | 6 | 6 | 1900.000 | N |
-Dwayne Murphy | 329 | 83 | 9 | 50 | 39 | 56 | 9 | 3828 | 948 | 145 | 575 | 528 | 635 | A | W | 276 | 6 | 2 | 600.000 | A |
-Dave Parker | 637 | 174 | 31 | 89 | 116 | 56 | 14 | 6727 | 2024 | 247 | 978 | 1093 | 495 | N | W | 278 | 9 | 9 | 1041.667 | N |
-Dan Pasqua | 280 | 82 | 16 | 44 | 45 | 47 | 2 | 428 | 113 | 25 | 61 | 70 | 63 | A | E | 148 | 4 | 2 | 110.000 | A |
-Darrell Porter | 155 | 41 | 12 | 21 | 29 | 22 | 16 | 5409 | 1338 | 181 | 746 | 805 | 875 | A | W | 165 | 9 | 1 | 260.000 | A |
-Dick Schofield | 458 | 114 | 13 | 67 | 57 | 48 | 4 | 1350 | 298 | 28 | 160 | 123 | 122 | A | W | 246 | 389 | 18 | 475.000 | A |
-Don Slaught | 314 | 83 | 13 | 39 | 46 | 16 | 5 | 1457 | 405 | 28 | 156 | 159 | 76 | A | W | 533 | 40 | 4 | 431.500 | A |
-Darryl Strawberry | 475 | 123 | 27 | 76 | 93 | 72 | 4 | 1810 | 471 | 108 | 292 | 343 | 267 | N | E | 226 | 10 | 6 | 1220.000 | N |
-Dale Sveum | 317 | 78 | 7 | 35 | 35 | 32 | 1 | 317 | 78 | 7 | 35 | 35 | 32 | A | E | 45 | 122 | 26 | 70.000 | A |
-Danny Tartabull | 511 | 138 | 25 | 76 | 96 | 61 | 3 | 592 | 164 | 28 | 87 | 110 | 71 | A | W | 157 | 7 | 8 | 145.000 | A |
-Dickie Thon | 278 | 69 | 3 | 24 | 21 | 29 | 8 | 2079 | 565 | 32 | 258 | 192 | 162 | N | W | 142 | 210 | 10 | NA | N |
-Denny Walling | 382 | 119 | 13 | 54 | 58 | 36 | 12 | 2133 | 594 | 41 | 287 | 294 | 227 | N | W | 59 | 156 | 9 | 595.000 | N |
-Dave Winfield | 565 | 148 | 24 | 90 | 104 | 77 | 14 | 7287 | 2083 | 305 | 1135 | 1234 | 791 | A | E | 292 | 9 | 5 | 1861.460 | A |
-Enos Cabell | 277 | 71 | 2 | 27 | 29 | 14 | 15 | 5952 | 1647 | 60 | 753 | 596 | 259 | N | W | 360 | 32 | 5 | NA | N |
-Eric Davis | 415 | 115 | 27 | 97 | 71 | 68 | 3 | 711 | 184 | 45 | 156 | 119 | 99 | N | W | 274 | 2 | 7 | 300.000 | N |
-Eddie Milner | 424 | 110 | 15 | 70 | 47 | 36 | 7 | 2130 | 544 | 38 | 335 | 174 | 258 | N | W | 292 | 6 | 3 | 490.000 | N |
-Eddie Murray | 495 | 151 | 17 | 61 | 84 | 78 | 10 | 5624 | 1679 | 275 | 884 | 1015 | 709 | A | E | 1045 | 88 | 13 | 2460.000 | A |
-Ernest Riles | 524 | 132 | 9 | 69 | 47 | 54 | 2 | 972 | 260 | 14 | 123 | 92 | 90 | A | E | 212 | 327 | 20 | NA | A |
-Ed Romero | 233 | 49 | 2 | 41 | 23 | 18 | 8 | 1350 | 336 | 7 | 166 | 122 | 106 | A | E | 102 | 132 | 10 | 375.000 | A |
-Ernie Whitt | 395 | 106 | 16 | 48 | 56 | 35 | 10 | 2303 | 571 | 86 | 266 | 323 | 248 | A | E | 709 | 41 | 7 | NA | A |
-Fred Lynn | 397 | 114 | 23 | 67 | 67 | 53 | 13 | 5589 | 1632 | 241 | 906 | 926 | 716 | A | E | 244 | 2 | 4 | NA | A |
-Floyd Rayford | 210 | 37 | 8 | 15 | 19 | 15 | 6 | 994 | 244 | 36 | 107 | 114 | 53 | A | E | 40 | 115 | 15 | NA | A |
-Franklin Stubbs | 420 | 95 | 23 | 55 | 58 | 37 | 3 | 646 | 139 | 31 | 77 | 77 | 61 | N | W | 206 | 10 | 7 | NA | N |
-Frank White | 566 | 154 | 22 | 76 | 84 | 43 | 14 | 6100 | 1583 | 131 | 743 | 693 | 300 | A | W | 316 | 439 | 10 | 750.000 | A |
-George Bell | 641 | 198 | 31 | 101 | 108 | 41 | 5 | 2129 | 610 | 92 | 297 | 319 | 117 | A | E | 269 | 17 | 10 | 1175.000 | A |
-Glenn Braggs | 215 | 51 | 4 | 19 | 18 | 11 | 1 | 215 | 51 | 4 | 19 | 18 | 11 | A | E | 116 | 5 | 12 | 70.000 | A |
-George Brett | 441 | 128 | 16 | 70 | 73 | 80 | 14 | 6675 | 2095 | 209 | 1072 | 1050 | 695 | A | W | 97 | 218 | 16 | 1500.000 | A |
-Greg Brock | 325 | 76 | 16 | 33 | 52 | 37 | 5 | 1506 | 351 | 71 | 195 | 219 | 214 | N | W | 726 | 87 | 3 | 385.000 | A |
-Gary Carter | 490 | 125 | 24 | 81 | 105 | 62 | 13 | 6063 | 1646 | 271 | 847 | 999 | 680 | N | E | 869 | 62 | 8 | 1925.571 | N |
-Glenn Davis | 574 | 152 | 31 | 91 | 101 | 64 | 3 | 985 | 260 | 53 | 148 | 173 | 95 | N | W | 1253 | 111 | 11 | 215.000 | N |
-George Foster | 284 | 64 | 14 | 30 | 42 | 24 | 18 | 7023 | 1925 | 348 | 986 | 1239 | 666 | N | E | 96 | 4 | 4 | NA | N |
-Gary Gaetti | 596 | 171 | 34 | 91 | 108 | 52 | 6 | 2862 | 728 | 107 | 361 | 401 | 224 | A | W | 118 | 334 | 21 | 900.000 | A |
-Greg Gagne | 472 | 118 | 12 | 63 | 54 | 30 | 4 | 793 | 187 | 14 | 102 | 80 | 50 | A | W | 228 | 377 | 26 | 155.000 | A |
-George Hendrick | 283 | 77 | 14 | 45 | 47 | 26 | 16 | 6840 | 1910 | 259 | 915 | 1067 | 546 | A | W | 144 | 6 | 5 | 700.000 | A |
-Glenn Hubbard | 408 | 94 | 4 | 42 | 36 | 66 | 9 | 3573 | 866 | 59 | 429 | 365 | 410 | N | W | 282 | 487 | 19 | 535.000 | N |
-Garth Iorg | 327 | 85 | 3 | 30 | 44 | 20 | 8 | 2140 | 568 | 16 | 216 | 208 | 93 | A | E | 91 | 185 | 12 | 362.500 | A |
-Gary Matthews | 370 | 96 | 21 | 49 | 46 | 60 | 15 | 6986 | 1972 | 231 | 1070 | 955 | 921 | N | E | 137 | 5 | 9 | 733.333 | N |
-Graig Nettles | 354 | 77 | 16 | 36 | 55 | 41 | 20 | 8716 | 2172 | 384 | 1172 | 1267 | 1057 | N | W | 83 | 174 | 16 | 200.000 | N |
-Gary Pettis | 539 | 139 | 5 | 93 | 58 | 69 | 5 | 1469 | 369 | 12 | 247 | 126 | 198 | A | W | 462 | 9 | 7 | 400.000 | A |
-Gary Redus | 340 | 84 | 11 | 62 | 33 | 47 | 5 | 1516 | 376 | 42 | 284 | 141 | 219 | N | E | 185 | 8 | 4 | 400.000 | A |
-Garry Templeton | 510 | 126 | 2 | 42 | 44 | 35 | 11 | 5562 | 1578 | 44 | 703 | 519 | 256 | N | W | 207 | 358 | 20 | 737.500 | N |
-Gorman Thomas | 315 | 59 | 16 | 45 | 36 | 58 | 13 | 4677 | 1051 | 268 | 681 | 782 | 697 | A | W | 0 | 0 | 0 | NA | A |
-Greg Walker | 282 | 78 | 13 | 37 | 51 | 29 | 5 | 1649 | 453 | 73 | 211 | 280 | 138 | A | W | 670 | 57 | 5 | 500.000 | A |
-Gary Ward | 380 | 120 | 5 | 54 | 51 | 31 | 8 | 3118 | 900 | 92 | 444 | 419 | 240 | A | W | 237 | 8 | 1 | 600.000 | A |
-Glenn Wilson | 584 | 158 | 15 | 70 | 84 | 42 | 5 | 2358 | 636 | 58 | 265 | 316 | 134 | N | E | 331 | 20 | 4 | 662.500 | N |
-Harold Baines | 570 | 169 | 21 | 72 | 88 | 38 | 7 | 3754 | 1077 | 140 | 492 | 589 | 263 | A | W | 295 | 15 | 5 | 950.000 | A |
-Hubie Brooks | 306 | 104 | 14 | 50 | 58 | 25 | 7 | 2954 | 822 | 55 | 313 | 377 | 187 | N | E | 116 | 222 | 15 | 750.000 | N |
-Howard Johnson | 220 | 54 | 10 | 30 | 39 | 31 | 5 | 1185 | 299 | 40 | 145 | 154 | 128 | N | E | 50 | 136 | 20 | 297.500 | N |
-Hal McRae | 278 | 70 | 7 | 22 | 37 | 18 | 18 | 7186 | 2081 | 190 | 935 | 1088 | 643 | A | W | 0 | 0 | 0 | 325.000 | A |
-Harold Reynolds | 445 | 99 | 1 | 46 | 24 | 29 | 4 | 618 | 129 | 1 | 72 | 31 | 48 | A | W | 278 | 415 | 16 | 87.500 | A |
-Harry Spilman | 143 | 39 | 5 | 18 | 30 | 15 | 9 | 639 | 151 | 16 | 80 | 97 | 61 | N | W | 138 | 15 | 1 | 175.000 | N |
-Herm Winningham | 185 | 40 | 4 | 23 | 11 | 18 | 3 | 524 | 125 | 7 | 58 | 37 | 47 | N | E | 97 | 2 | 2 | 90.000 | N |
-Jesse Barfield | 589 | 170 | 40 | 107 | 108 | 69 | 6 | 2325 | 634 | 128 | 371 | 376 | 238 | A | E | 368 | 20 | 3 | 1237.500 | A |
-Juan Beniquez | 343 | 103 | 6 | 48 | 36 | 40 | 15 | 4338 | 1193 | 70 | 581 | 421 | 325 | A | E | 211 | 56 | 13 | 430.000 | A |
-Juan Bonilla | 284 | 69 | 1 | 33 | 18 | 25 | 5 | 1407 | 361 | 6 | 139 | 98 | 111 | A | E | 122 | 140 | 5 | NA | N |
-John Cangelosi | 438 | 103 | 2 | 65 | 32 | 71 | 2 | 440 | 103 | 2 | 67 | 32 | 71 | A | W | 276 | 7 | 9 | 100.000 | N |
-Jose Canseco | 600 | 144 | 33 | 85 | 117 | 65 | 2 | 696 | 173 | 38 | 101 | 130 | 69 | A | W | 319 | 4 | 14 | 165.000 | A |
-Joe Carter | 663 | 200 | 29 | 108 | 121 | 32 | 4 | 1447 | 404 | 57 | 210 | 222 | 68 | A | E | 241 | 8 | 6 | 250.000 | A |
-Jack Clark | 232 | 55 | 9 | 34 | 23 | 45 | 12 | 4405 | 1213 | 194 | 702 | 705 | 625 | N | E | 623 | 35 | 3 | 1300.000 | N |
-Jose Cruz | 479 | 133 | 10 | 48 | 72 | 55 | 17 | 7472 | 2147 | 153 | 980 | 1032 | 854 | N | W | 237 | 5 | 4 | 773.333 | N |
-Julio Cruz | 209 | 45 | 0 | 38 | 19 | 42 | 10 | 3859 | 916 | 23 | 557 | 279 | 478 | A | W | 132 | 205 | 5 | NA | A |
-Jody Davis | 528 | 132 | 21 | 61 | 74 | 41 | 6 | 2641 | 671 | 97 | 273 | 383 | 226 | N | E | 885 | 105 | 8 | 1008.333 | N |
-Jim Dwyer | 160 | 39 | 8 | 18 | 31 | 22 | 14 | 2128 | 543 | 56 | 304 | 268 | 298 | A | E | 33 | 3 | 0 | 275.000 | A |
-Julio Franco | 599 | 183 | 10 | 80 | 74 | 32 | 5 | 2482 | 715 | 27 | 330 | 326 | 158 | A | E | 231 | 374 | 18 | 775.000 | A |
-Jim Gantner | 497 | 136 | 7 | 58 | 38 | 26 | 11 | 3871 | 1066 | 40 | 450 | 367 | 241 | A | E | 304 | 347 | 10 | 850.000 | A |
-Johnny Grubb | 210 | 70 | 13 | 32 | 51 | 28 | 15 | 4040 | 1130 | 97 | 544 | 462 | 551 | A | E | 0 | 0 | 0 | 365.000 | A |
-Jerry Hairston | 225 | 61 | 5 | 32 | 26 | 26 | 11 | 1568 | 408 | 25 | 202 | 185 | 257 | A | W | 132 | 9 | 0 | NA | A |
-Jack Howell | 151 | 41 | 4 | 26 | 21 | 19 | 2 | 288 | 68 | 9 | 45 | 39 | 35 | A | W | 28 | 56 | 2 | 95.000 | A |
-John Kruk | 278 | 86 | 4 | 33 | 38 | 45 | 1 | 278 | 86 | 4 | 33 | 38 | 45 | N | W | 102 | 4 | 2 | 110.000 | N |
-Jeffrey Leonard | 341 | 95 | 6 | 48 | 42 | 20 | 10 | 2964 | 808 | 81 | 379 | 428 | 221 | N | W | 158 | 4 | 5 | 100.000 | N |
-Jim Morrison | 537 | 147 | 23 | 58 | 88 | 47 | 10 | 2744 | 730 | 97 | 302 | 351 | 174 | N | E | 92 | 257 | 20 | 277.500 | N |
-John Moses | 399 | 102 | 3 | 56 | 34 | 34 | 5 | 670 | 167 | 4 | 89 | 48 | 54 | A | W | 211 | 9 | 3 | 80.000 | A |
-Jerry Mumphrey | 309 | 94 | 5 | 37 | 32 | 26 | 13 | 4618 | 1330 | 57 | 616 | 522 | 436 | N | E | 161 | 3 | 3 | 600.000 | N |
-Joe Orsulak | 401 | 100 | 2 | 60 | 19 | 28 | 4 | 876 | 238 | 2 | 126 | 44 | 55 | N | E | 193 | 11 | 4 | NA | N |
-Jorge Orta | 336 | 93 | 9 | 35 | 46 | 23 | 15 | 5779 | 1610 | 128 | 730 | 741 | 497 | A | W | 0 | 0 | 0 | NA | A |
-Jim Presley | 616 | 163 | 27 | 83 | 107 | 32 | 3 | 1437 | 377 | 65 | 181 | 227 | 82 | A | W | 110 | 308 | 15 | 200.000 | A |
-Jamie Quirk | 219 | 47 | 8 | 24 | 26 | 17 | 12 | 1188 | 286 | 23 | 100 | 125 | 63 | A | W | 260 | 58 | 4 | NA | A |
-Johnny Ray | 579 | 174 | 7 | 67 | 78 | 58 | 6 | 3053 | 880 | 32 | 366 | 337 | 218 | N | E | 280 | 479 | 5 | 657.000 | N |
-Jeff Reed | 165 | 39 | 2 | 13 | 9 | 16 | 3 | 196 | 44 | 2 | 18 | 10 | 18 | A | W | 332 | 19 | 2 | 75.000 | N |
-Jim Rice | 618 | 200 | 20 | 98 | 110 | 62 | 13 | 7127 | 2163 | 351 | 1104 | 1289 | 564 | A | E | 330 | 16 | 8 | 2412.500 | A |
-Jerry Royster | 257 | 66 | 5 | 31 | 26 | 32 | 14 | 3910 | 979 | 33 | 518 | 324 | 382 | N | W | 87 | 166 | 14 | 250.000 | A |
-John Russell | 315 | 76 | 13 | 35 | 60 | 25 | 3 | 630 | 151 | 24 | 68 | 94 | 55 | N | E | 498 | 39 | 13 | 155.000 | N |
-Juan Samuel | 591 | 157 | 16 | 90 | 78 | 26 | 4 | 2020 | 541 | 52 | 310 | 226 | 91 | N | E | 290 | 440 | 25 | 640.000 | N |
-John Shelby | 404 | 92 | 11 | 54 | 49 | 18 | 6 | 1354 | 325 | 30 | 188 | 135 | 63 | A | E | 222 | 5 | 5 | 300.000 | A |
-Joel Skinner | 315 | 73 | 5 | 23 | 37 | 16 | 4 | 450 | 108 | 6 | 38 | 46 | 28 | A | W | 227 | 15 | 3 | 110.000 | A |
-Jeff Stone | 249 | 69 | 6 | 32 | 19 | 20 | 4 | 702 | 209 | 10 | 97 | 48 | 44 | N | E | 103 | 8 | 2 | NA | N |
-Jim Sundberg | 429 | 91 | 12 | 41 | 42 | 57 | 13 | 5590 | 1397 | 83 | 578 | 579 | 644 | A | W | 686 | 46 | 4 | 825.000 | N |
-Jim Traber | 212 | 54 | 13 | 28 | 44 | 18 | 2 | 233 | 59 | 13 | 31 | 46 | 20 | A | E | 243 | 23 | 5 | NA | A |
-Jose Uribe | 453 | 101 | 3 | 46 | 43 | 61 | 3 | 948 | 218 | 6 | 96 | 72 | 91 | N | W | 249 | 444 | 16 | 195.000 | N |
-Jerry Willard | 161 | 43 | 4 | 17 | 26 | 22 | 3 | 707 | 179 | 21 | 77 | 99 | 76 | A | W | 300 | 12 | 2 | NA | A |
-Joel Youngblood | 184 | 47 | 5 | 20 | 28 | 18 | 11 | 3327 | 890 | 74 | 419 | 382 | 304 | N | W | 49 | 2 | 0 | 450.000 | N |
-Kevin Bass | 591 | 184 | 20 | 83 | 79 | 38 | 5 | 1689 | 462 | 40 | 219 | 195 | 82 | N | W | 303 | 12 | 5 | 630.000 | N |
-Kal Daniels | 181 | 58 | 6 | 34 | 23 | 22 | 1 | 181 | 58 | 6 | 34 | 23 | 22 | N | W | 88 | 0 | 3 | 86.500 | N |
-Kirk Gibson | 441 | 118 | 28 | 84 | 86 | 68 | 8 | 2723 | 750 | 126 | 433 | 420 | 309 | A | E | 190 | 2 | 2 | 1300.000 | A |
-Ken Griffey | 490 | 150 | 21 | 69 | 58 | 35 | 14 | 6126 | 1839 | 121 | 983 | 707 | 600 | A | E | 96 | 5 | 3 | 1000.000 | N |
-Keith Hernandez | 551 | 171 | 13 | 94 | 83 | 94 | 13 | 6090 | 1840 | 128 | 969 | 900 | 917 | N | E | 1199 | 149 | 5 | 1800.000 | N |
-Kent Hrbek | 550 | 147 | 29 | 85 | 91 | 71 | 6 | 2816 | 815 | 117 | 405 | 474 | 319 | A | W | 1218 | 104 | 10 | 1310.000 | A |
-Ken Landreaux | 283 | 74 | 4 | 34 | 29 | 22 | 10 | 3919 | 1062 | 85 | 505 | 456 | 283 | N | W | 145 | 5 | 7 | 737.500 | N |
-Kevin McReynolds | 560 | 161 | 26 | 89 | 96 | 66 | 4 | 1789 | 470 | 65 | 233 | 260 | 155 | N | W | 332 | 9 | 8 | 625.000 | N |
-Kevin Mitchell | 328 | 91 | 12 | 51 | 43 | 33 | 2 | 342 | 94 | 12 | 51 | 44 | 33 | N | E | 145 | 59 | 8 | 125.000 | N |
-Keith Moreland | 586 | 159 | 12 | 72 | 79 | 53 | 9 | 3082 | 880 | 83 | 363 | 477 | 295 | N | E | 181 | 13 | 4 | 1043.333 | N |
-Ken Oberkfell | 503 | 136 | 5 | 62 | 48 | 83 | 10 | 3423 | 970 | 20 | 408 | 303 | 414 | N | W | 65 | 258 | 8 | 725.000 | N |
-Ken Phelps | 344 | 85 | 24 | 69 | 64 | 88 | 7 | 911 | 214 | 64 | 150 | 156 | 187 | A | W | 0 | 0 | 0 | 300.000 | A |
-Kirby Puckett | 680 | 223 | 31 | 119 | 96 | 34 | 3 | 1928 | 587 | 35 | 262 | 201 | 91 | A | W | 429 | 8 | 6 | 365.000 | A |
-Kurt Stillwell | 279 | 64 | 0 | 31 | 26 | 30 | 1 | 279 | 64 | 0 | 31 | 26 | 30 | N | W | 107 | 205 | 16 | 75.000 | N |
-Leon Durham | 484 | 127 | 20 | 66 | 65 | 67 | 7 | 3006 | 844 | 116 | 436 | 458 | 377 | N | E | 1231 | 80 | 7 | 1183.333 | N |
-Len Dykstra | 431 | 127 | 8 | 77 | 45 | 58 | 2 | 667 | 187 | 9 | 117 | 64 | 88 | N | E | 283 | 8 | 3 | 202.500 | N |
-Larry Herndon | 283 | 70 | 8 | 33 | 37 | 27 | 12 | 4479 | 1222 | 94 | 557 | 483 | 307 | A | E | 156 | 2 | 2 | 225.000 | A |
-Lee Lacy | 491 | 141 | 11 | 77 | 47 | 37 | 15 | 4291 | 1240 | 84 | 615 | 430 | 340 | A | E | 239 | 8 | 2 | 525.000 | A |
-Len Matuszek | 199 | 52 | 9 | 26 | 28 | 21 | 6 | 805 | 191 | 30 | 113 | 119 | 87 | N | W | 235 | 22 | 5 | 265.000 | N |
-Lloyd Moseby | 589 | 149 | 21 | 89 | 86 | 64 | 7 | 3558 | 928 | 102 | 513 | 471 | 351 | A | E | 371 | 6 | 6 | 787.500 | A |
-Lance Parrish | 327 | 84 | 22 | 53 | 62 | 38 | 10 | 4273 | 1123 | 212 | 577 | 700 | 334 | A | E | 483 | 48 | 6 | 800.000 | N |
-Larry Parrish | 464 | 128 | 28 | 67 | 94 | 52 | 13 | 5829 | 1552 | 210 | 740 | 840 | 452 | A | W | 0 | 0 | 0 | 587.500 | A |
-Luis Rivera | 166 | 34 | 0 | 20 | 13 | 17 | 1 | 166 | 34 | 0 | 20 | 13 | 17 | N | E | 64 | 119 | 9 | NA | N |
-Larry Sheets | 338 | 92 | 18 | 42 | 60 | 21 | 3 | 682 | 185 | 36 | 88 | 112 | 50 | A | E | 0 | 0 | 0 | 145.000 | A |
-Lonnie Smith | 508 | 146 | 8 | 80 | 44 | 46 | 9 | 3148 | 915 | 41 | 571 | 289 | 326 | A | W | 245 | 5 | 9 | NA | A |
-Lou Whitaker | 584 | 157 | 20 | 95 | 73 | 63 | 10 | 4704 | 1320 | 93 | 724 | 522 | 576 | A | E | 276 | 421 | 11 | 420.000 | A |
-Mike Aldrete | 216 | 54 | 2 | 27 | 25 | 33 | 1 | 216 | 54 | 2 | 27 | 25 | 33 | N | W | 317 | 36 | 1 | 75.000 | N |
-Marty Barrett | 625 | 179 | 4 | 94 | 60 | 65 | 5 | 1696 | 476 | 12 | 216 | 163 | 166 | A | E | 303 | 450 | 14 | 575.000 | A |
-Mike Brown | 243 | 53 | 4 | 18 | 26 | 27 | 4 | 853 | 228 | 23 | 101 | 110 | 76 | N | E | 107 | 3 | 3 | NA | N |
-Mike Davis | 489 | 131 | 19 | 77 | 55 | 34 | 7 | 2051 | 549 | 62 | 300 | 263 | 153 | A | W | 310 | 9 | 9 | 780.000 | A |
-Mike Diaz | 209 | 56 | 12 | 22 | 36 | 19 | 2 | 216 | 58 | 12 | 24 | 37 | 19 | N | E | 201 | 6 | 3 | 90.000 | N |
-Mariano Duncan | 407 | 93 | 8 | 47 | 30 | 30 | 2 | 969 | 230 | 14 | 121 | 69 | 68 | N | W | 172 | 317 | 25 | 150.000 | N |
-Mike Easler | 490 | 148 | 14 | 64 | 78 | 49 | 13 | 3400 | 1000 | 113 | 445 | 491 | 301 | A | E | 0 | 0 | 0 | 700.000 | N |
-Mike Fitzgerald | 209 | 59 | 6 | 20 | 37 | 27 | 4 | 884 | 209 | 14 | 66 | 106 | 92 | N | E | 415 | 35 | 3 | NA | N |
-Mel Hall | 442 | 131 | 18 | 68 | 77 | 33 | 6 | 1416 | 398 | 47 | 210 | 203 | 136 | A | E | 233 | 7 | 7 | 550.000 | A |
-Mickey Hatcher | 317 | 88 | 3 | 40 | 32 | 19 | 8 | 2543 | 715 | 28 | 269 | 270 | 118 | A | W | 220 | 16 | 4 | NA | A |
-Mike Heath | 288 | 65 | 8 | 30 | 36 | 27 | 9 | 2815 | 698 | 55 | 315 | 325 | 189 | N | E | 259 | 30 | 10 | 650.000 | A |
-Mike Kingery | 209 | 54 | 3 | 25 | 14 | 12 | 1 | 209 | 54 | 3 | 25 | 14 | 12 | A | W | 102 | 6 | 3 | 68.000 | A |
-Mike LaValliere | 303 | 71 | 3 | 18 | 30 | 36 | 3 | 344 | 76 | 3 | 20 | 36 | 45 | N | E | 468 | 47 | 6 | 100.000 | N |
-Mike Marshall | 330 | 77 | 19 | 47 | 53 | 27 | 6 | 1928 | 516 | 90 | 247 | 288 | 161 | N | W | 149 | 8 | 6 | 670.000 | N |
-Mike Pagliarulo | 504 | 120 | 28 | 71 | 71 | 54 | 3 | 1085 | 259 | 54 | 150 | 167 | 114 | A | E | 103 | 283 | 19 | 175.000 | A |
-Mark Salas | 258 | 60 | 8 | 28 | 33 | 18 | 3 | 638 | 170 | 17 | 80 | 75 | 36 | A | W | 358 | 32 | 8 | 137.000 | A |
-Mike Schmidt | 20 | 1 | 0 | 0 | 0 | 0 | 2 | 41 | 9 | 2 | 6 | 7 | 4 | N | E | 78 | 220 | 6 | 2127.333 | N |
-Mike Scioscia | 374 | 94 | 5 | 36 | 26 | 62 | 7 | 1968 | 519 | 26 | 181 | 199 | 288 | N | W | 756 | 64 | 15 | 875.000 | N |
-Mickey Tettleton | 211 | 43 | 10 | 26 | 35 | 39 | 3 | 498 | 116 | 14 | 59 | 55 | 78 | A | W | 463 | 32 | 8 | 120.000 | A |
-Milt Thompson | 299 | 75 | 6 | 38 | 23 | 26 | 3 | 580 | 160 | 8 | 71 | 33 | 44 | N | E | 212 | 1 | 2 | 140.000 | N |
-Mitch Webster | 576 | 167 | 8 | 89 | 49 | 57 | 4 | 822 | 232 | 19 | 132 | 83 | 79 | N | E | 325 | 12 | 8 | 210.000 | N |
-Mookie Wilson | 381 | 110 | 9 | 61 | 45 | 32 | 7 | 3015 | 834 | 40 | 451 | 249 | 168 | N | E | 228 | 7 | 5 | 800.000 | N |
-Marvell Wynne | 288 | 76 | 7 | 34 | 37 | 15 | 4 | 1644 | 408 | 16 | 198 | 120 | 113 | N | W | 203 | 3 | 3 | 240.000 | N |
-Mike Young | 369 | 93 | 9 | 43 | 42 | 49 | 5 | 1258 | 323 | 54 | 181 | 177 | 157 | A | E | 149 | 1 | 6 | 350.000 | A |
-Nick Esasky | 330 | 76 | 12 | 35 | 41 | 47 | 4 | 1367 | 326 | 55 | 167 | 198 | 167 | N | W | 512 | 30 | 5 | NA | N |
-Ozzie Guillen | 547 | 137 | 2 | 58 | 47 | 12 | 2 | 1038 | 271 | 3 | 129 | 80 | 24 | A | W | 261 | 459 | 22 | 175.000 | A |
-Oddibe McDowell | 572 | 152 | 18 | 105 | 49 | 65 | 2 | 978 | 249 | 36 | 168 | 91 | 101 | A | W | 325 | 13 | 3 | 200.000 | A |
-Omar Moreno | 359 | 84 | 4 | 46 | 27 | 21 | 12 | 4992 | 1257 | 37 | 699 | 386 | 387 | N | W | 151 | 8 | 5 | NA | N |
-Ozzie Smith | 514 | 144 | 0 | 67 | 54 | 79 | 9 | 4739 | 1169 | 13 | 583 | 374 | 528 | N | E | 229 | 453 | 15 | 1940.000 | N |
-Ozzie Virgil | 359 | 80 | 15 | 45 | 48 | 63 | 7 | 1493 | 359 | 61 | 176 | 202 | 175 | N | W | 682 | 93 | 13 | 700.000 | N |
-Phil Bradley | 526 | 163 | 12 | 88 | 50 | 77 | 4 | 1556 | 470 | 38 | 245 | 167 | 174 | A | W | 250 | 11 | 1 | 750.000 | A |
-Phil Garner | 313 | 83 | 9 | 43 | 41 | 30 | 14 | 5885 | 1543 | 104 | 751 | 714 | 535 | N | W | 58 | 141 | 23 | 450.000 | N |
-Pete Incaviglia | 540 | 135 | 30 | 82 | 88 | 55 | 1 | 540 | 135 | 30 | 82 | 88 | 55 | A | W | 157 | 6 | 14 | 172.000 | A |
-Paul Molitor | 437 | 123 | 9 | 62 | 55 | 40 | 9 | 4139 | 1203 | 79 | 676 | 390 | 364 | A | E | 82 | 170 | 15 | 1260.000 | A |
-Pete O’Brien | 551 | 160 | 23 | 86 | 90 | 87 | 5 | 2235 | 602 | 75 | 278 | 328 | 273 | A | W | 1224 | 115 | 11 | NA | A |
-Pete Rose | 237 | 52 | 0 | 15 | 25 | 30 | 24 | 14053 | 4256 | 160 | 2165 | 1314 | 1566 | N | W | 523 | 43 | 6 | 750.000 | N |
-Pat Sheridan | 236 | 56 | 6 | 41 | 19 | 21 | 5 | 1257 | 329 | 24 | 166 | 125 | 105 | A | E | 172 | 1 | 4 | 190.000 | A |
-Pat Tabler | 473 | 154 | 6 | 61 | 48 | 29 | 6 | 1966 | 566 | 29 | 250 | 252 | 178 | A | E | 846 | 84 | 9 | 580.000 | A |
-Rafael Belliard | 309 | 72 | 0 | 33 | 31 | 26 | 5 | 354 | 82 | 0 | 41 | 32 | 26 | N | E | 117 | 269 | 12 | 130.000 | N |
-Rick Burleson | 271 | 77 | 5 | 35 | 29 | 33 | 12 | 4933 | 1358 | 48 | 630 | 435 | 403 | A | W | 62 | 90 | 3 | 450.000 | A |
-Randy Bush | 357 | 96 | 7 | 50 | 45 | 39 | 5 | 1394 | 344 | 43 | 178 | 192 | 136 | A | W | 167 | 2 | 4 | 300.000 | A |
-Rick Cerone | 216 | 56 | 4 | 22 | 18 | 15 | 12 | 2796 | 665 | 43 | 266 | 304 | 198 | A | E | 391 | 44 | 4 | 250.000 | A |
-Ron Cey | 256 | 70 | 13 | 42 | 36 | 44 | 16 | 7058 | 1845 | 312 | 965 | 1128 | 990 | N | E | 41 | 118 | 8 | 1050.000 | A |
-Rob Deer | 466 | 108 | 33 | 75 | 86 | 72 | 3 | 652 | 142 | 44 | 102 | 109 | 102 | A | E | 286 | 8 | 8 | 215.000 | A |
-Rick Dempsey | 327 | 68 | 13 | 42 | 29 | 45 | 18 | 3949 | 939 | 78 | 438 | 380 | 466 | A | E | 659 | 53 | 7 | 400.000 | A |
-Rich Gedman | 462 | 119 | 16 | 49 | 65 | 37 | 7 | 2131 | 583 | 69 | 244 | 288 | 150 | A | E | 866 | 65 | 6 | NA | A |
-Ron Hassey | 341 | 110 | 9 | 45 | 49 | 46 | 9 | 2331 | 658 | 50 | 249 | 322 | 274 | A | E | 251 | 9 | 4 | 560.000 | A |
-Rickey Henderson | 608 | 160 | 28 | 130 | 74 | 89 | 8 | 4071 | 1182 | 103 | 862 | 417 | 708 | A | E | 426 | 4 | 6 | 1670.000 | A |
-Reggie Jackson | 419 | 101 | 18 | 65 | 58 | 92 | 20 | 9528 | 2510 | 548 | 1509 | 1659 | 1342 | A | W | 0 | 0 | 0 | 487.500 | A |
-Ricky Jones | 33 | 6 | 0 | 2 | 4 | 7 | 1 | 33 | 6 | 0 | 2 | 4 | 7 | A | W | 205 | 5 | 4 | NA | A |
-Ron Kittle | 376 | 82 | 21 | 42 | 60 | 35 | 5 | 1770 | 408 | 115 | 238 | 299 | 157 | A | W | 0 | 0 | 0 | 425.000 | A |
-Ray Knight | 486 | 145 | 11 | 51 | 76 | 40 | 11 | 3967 | 1102 | 67 | 410 | 497 | 284 | N | E | 88 | 204 | 16 | 500.000 | A |
-Randy Kutcher | 186 | 44 | 7 | 28 | 16 | 11 | 1 | 186 | 44 | 7 | 28 | 16 | 11 | N | W | 99 | 3 | 1 | NA | N |
-Rudy Law | 307 | 80 | 1 | 42 | 36 | 29 | 7 | 2421 | 656 | 18 | 379 | 198 | 184 | A | W | 145 | 2 | 2 | NA | A |
-Rick Leach | 246 | 76 | 5 | 35 | 39 | 13 | 6 | 912 | 234 | 12 | 102 | 96 | 80 | A | E | 44 | 0 | 1 | 250.000 | A |
-Rick Manning | 205 | 52 | 8 | 31 | 27 | 17 | 12 | 5134 | 1323 | 56 | 643 | 445 | 459 | A | E | 155 | 3 | 2 | 400.000 | A |
-Rance Mulliniks | 348 | 90 | 11 | 50 | 45 | 43 | 10 | 2288 | 614 | 43 | 295 | 273 | 269 | A | E | 60 | 176 | 6 | 450.000 | A |
-Ron Oester | 523 | 135 | 8 | 52 | 44 | 52 | 9 | 3368 | 895 | 39 | 377 | 284 | 296 | N | W | 367 | 475 | 19 | 750.000 | N |
-Rey Quinones | 312 | 68 | 2 | 32 | 22 | 24 | 1 | 312 | 68 | 2 | 32 | 22 | 24 | A | E | 86 | 150 | 15 | 70.000 | A |
-Rafael Ramirez | 496 | 119 | 8 | 57 | 33 | 21 | 7 | 3358 | 882 | 36 | 365 | 280 | 165 | N | W | 155 | 371 | 29 | 875.000 | N |
-Ronn Reynolds | 126 | 27 | 3 | 8 | 10 | 5 | 4 | 239 | 49 | 3 | 16 | 13 | 14 | N | E | 190 | 2 | 9 | 190.000 | N |
-Ron Roenicke | 275 | 68 | 5 | 42 | 42 | 61 | 6 | 961 | 238 | 16 | 128 | 104 | 172 | N | E | 181 | 3 | 2 | 191.000 | N |
-Ryne Sandberg | 627 | 178 | 14 | 68 | 76 | 46 | 6 | 3146 | 902 | 74 | 494 | 345 | 242 | N | E | 309 | 492 | 5 | 740.000 | N |
-Rafael Santana | 394 | 86 | 1 | 38 | 28 | 36 | 4 | 1089 | 267 | 3 | 94 | 71 | 76 | N | E | 203 | 369 | 16 | 250.000 | N |
-Rick Schu | 208 | 57 | 8 | 32 | 25 | 18 | 3 | 653 | 170 | 17 | 98 | 54 | 62 | N | E | 42 | 94 | 13 | 140.000 | N |
-Ruben Sierra | 382 | 101 | 16 | 50 | 55 | 22 | 1 | 382 | 101 | 16 | 50 | 55 | 22 | A | W | 200 | 7 | 6 | 97.500 | A |
-Roy Smalley | 459 | 113 | 20 | 59 | 57 | 68 | 12 | 5348 | 1369 | 155 | 713 | 660 | 735 | A | W | 0 | 0 | 0 | 740.000 | A |
-Robby Thompson | 549 | 149 | 7 | 73 | 47 | 42 | 1 | 549 | 149 | 7 | 73 | 47 | 42 | N | W | 255 | 450 | 17 | 140.000 | N |
-Rob Wilfong | 288 | 63 | 3 | 25 | 33 | 16 | 10 | 2682 | 667 | 38 | 315 | 259 | 204 | A | W | 135 | 257 | 7 | 341.667 | A |
-Reggie Williams | 303 | 84 | 4 | 35 | 32 | 23 | 2 | 312 | 87 | 4 | 39 | 32 | 23 | N | W | 179 | 5 | 3 | NA | N |
-Robin Yount | 522 | 163 | 9 | 82 | 46 | 62 | 13 | 7037 | 2019 | 153 | 1043 | 827 | 535 | A | E | 352 | 9 | 1 | 1000.000 | A |
-Steve Balboni | 512 | 117 | 29 | 54 | 88 | 43 | 6 | 1750 | 412 | 100 | 204 | 276 | 155 | A | W | 1236 | 98 | 18 | 100.000 | A |
-Scott Bradley | 220 | 66 | 5 | 20 | 28 | 13 | 3 | 290 | 80 | 5 | 27 | 31 | 15 | A | W | 281 | 21 | 3 | 90.000 | A |
-Sid Bream | 522 | 140 | 16 | 73 | 77 | 60 | 4 | 730 | 185 | 22 | 93 | 106 | 86 | N | E | 1320 | 166 | 17 | 200.000 | N |
-Steve Buechele | 461 | 112 | 18 | 54 | 54 | 35 | 2 | 680 | 160 | 24 | 76 | 75 | 49 | A | W | 111 | 226 | 11 | 135.000 | A |
-Shawon Dunston | 581 | 145 | 17 | 66 | 68 | 21 | 2 | 831 | 210 | 21 | 106 | 86 | 40 | N | E | 320 | 465 | 32 | 155.000 | N |
-Scott Fletcher | 530 | 159 | 3 | 82 | 50 | 47 | 6 | 1619 | 426 | 11 | 218 | 149 | 163 | A | W | 196 | 354 | 15 | 475.000 | A |
-Steve Garvey | 557 | 142 | 21 | 58 | 81 | 23 | 18 | 8759 | 2583 | 271 | 1138 | 1299 | 478 | N | W | 1160 | 53 | 7 | 1450.000 | N |
-Steve Jeltz | 439 | 96 | 0 | 44 | 36 | 65 | 4 | 711 | 148 | 1 | 68 | 56 | 99 | N | E | 229 | 406 | 22 | 150.000 | N |
-Steve Lombardozzi | 453 | 103 | 8 | 53 | 33 | 52 | 2 | 507 | 123 | 8 | 63 | 39 | 58 | A | W | 289 | 407 | 6 | 105.000 | A |
-Spike Owen | 528 | 122 | 1 | 67 | 45 | 51 | 4 | 1716 | 403 | 12 | 211 | 146 | 155 | A | W | 209 | 372 | 17 | 350.000 | A |
-Steve Sax | 633 | 210 | 6 | 91 | 56 | 59 | 6 | 3070 | 872 | 19 | 420 | 230 | 274 | N | W | 367 | 432 | 16 | 90.000 | N |
-Tony Armas | 16 | 2 | 0 | 1 | 0 | 0 | 2 | 28 | 4 | 0 | 1 | 0 | 0 | A | E | 247 | 4 | 8 | NA | A |
-Tony Bernazard | 562 | 169 | 17 | 88 | 73 | 53 | 8 | 3181 | 841 | 61 | 450 | 342 | 373 | A | E | 351 | 442 | 17 | 530.000 | A |
-Tom Brookens | 281 | 76 | 3 | 42 | 25 | 20 | 8 | 2658 | 657 | 48 | 324 | 300 | 179 | A | E | 106 | 144 | 7 | 341.667 | A |
-Tom Brunansky | 593 | 152 | 23 | 69 | 75 | 53 | 6 | 2765 | 686 | 133 | 369 | 384 | 321 | A | W | 315 | 10 | 6 | 940.000 | A |
-Tony Fernandez | 687 | 213 | 10 | 91 | 65 | 27 | 4 | 1518 | 448 | 15 | 196 | 137 | 89 | A | E | 294 | 445 | 13 | 350.000 | A |
-Tim Flannery | 368 | 103 | 3 | 48 | 28 | 54 | 8 | 1897 | 493 | 9 | 207 | 162 | 198 | N | W | 209 | 246 | 3 | 326.667 | N |
-Tom Foley | 263 | 70 | 1 | 26 | 23 | 30 | 4 | 888 | 220 | 9 | 83 | 82 | 86 | N | E | 81 | 147 | 4 | 250.000 | N |
-Tony Gwynn | 642 | 211 | 14 | 107 | 59 | 52 | 5 | 2364 | 770 | 27 | 352 | 230 | 193 | N | W | 337 | 19 | 4 | 740.000 | N |
-Terry Harper | 265 | 68 | 8 | 26 | 30 | 29 | 7 | 1337 | 339 | 32 | 135 | 163 | 128 | N | W | 92 | 5 | 3 | 425.000 | A |
-Toby Harrah | 289 | 63 | 7 | 36 | 41 | 44 | 17 | 7402 | 1954 | 195 | 1115 | 919 | 1153 | A | W | 166 | 211 | 7 | NA | A |
-Tommy Herr | 559 | 141 | 2 | 48 | 61 | 73 | 8 | 3162 | 874 | 16 | 421 | 349 | 359 | N | E | 352 | 414 | 9 | 925.000 | N |
-Tim Hulett | 520 | 120 | 17 | 53 | 44 | 21 | 4 | 927 | 227 | 22 | 106 | 80 | 52 | A | W | 70 | 144 | 11 | 185.000 | A |
-Terry Kennedy | 19 | 4 | 1 | 2 | 3 | 1 | 1 | 19 | 4 | 1 | 2 | 3 | 1 | N | W | 692 | 70 | 8 | 920.000 | A |
-Tito Landrum | 205 | 43 | 2 | 24 | 17 | 20 | 7 | 854 | 219 | 12 | 105 | 99 | 71 | N | E | 131 | 6 | 1 | 286.667 | N |
-Tim Laudner | 193 | 47 | 10 | 21 | 29 | 24 | 6 | 1136 | 256 | 42 | 129 | 139 | 106 | A | W | 299 | 13 | 5 | 245.000 | A |
-Tom O’Malley | 181 | 46 | 1 | 19 | 18 | 17 | 5 | 937 | 238 | 9 | 88 | 95 | 104 | A | E | 37 | 98 | 9 | NA | A |
-Tom Paciorek | 213 | 61 | 4 | 17 | 22 | 3 | 17 | 4061 | 1145 | 83 | 488 | 491 | 244 | A | W | 178 | 45 | 4 | 235.000 | A |
-Tony Pena | 510 | 147 | 10 | 56 | 52 | 53 | 7 | 2872 | 821 | 63 | 307 | 340 | 174 | N | E | 810 | 99 | 18 | 1150.000 | N |
-Terry Pendleton | 578 | 138 | 1 | 56 | 59 | 34 | 3 | 1399 | 357 | 7 | 149 | 161 | 87 | N | E | 133 | 371 | 20 | 160.000 | N |
-Tony Perez | 200 | 51 | 2 | 14 | 29 | 25 | 23 | 9778 | 2732 | 379 | 1272 | 1652 | 925 | N | W | 398 | 29 | 7 | NA | N |
-Tony Phillips | 441 | 113 | 5 | 76 | 52 | 76 | 5 | 1546 | 397 | 17 | 226 | 149 | 191 | A | W | 160 | 290 | 11 | 425.000 | A |
-Terry Puhl | 172 | 42 | 3 | 17 | 14 | 15 | 10 | 4086 | 1150 | 57 | 579 | 363 | 406 | N | W | 65 | 0 | 0 | 900.000 | N |
-Tim Raines | 580 | 194 | 9 | 91 | 62 | 78 | 8 | 3372 | 1028 | 48 | 604 | 314 | 469 | N | E | 270 | 13 | 6 | NA | N |
-Ted Simmons | 127 | 32 | 4 | 14 | 25 | 12 | 19 | 8396 | 2402 | 242 | 1048 | 1348 | 819 | N | W | 167 | 18 | 6 | 500.000 | N |
-Tim Teufel | 279 | 69 | 4 | 35 | 31 | 32 | 4 | 1359 | 355 | 31 | 180 | 148 | 158 | N | E | 133 | 173 | 9 | 277.500 | N |
-Tim Wallach | 480 | 112 | 18 | 50 | 71 | 44 | 7 | 3031 | 771 | 110 | 338 | 406 | 239 | N | E | 94 | 270 | 16 | 750.000 | N |
-Vince Coleman | 600 | 139 | 0 | 94 | 29 | 60 | 2 | 1236 | 309 | 1 | 201 | 69 | 110 | N | E | 300 | 12 | 9 | 160.000 | N |
-Von Hayes | 610 | 186 | 19 | 107 | 98 | 74 | 6 | 2728 | 753 | 69 | 399 | 366 | 286 | N | E | 1182 | 96 | 13 | 1300.000 | N |
-Vance Law | 360 | 81 | 5 | 37 | 44 | 37 | 7 | 2268 | 566 | 41 | 279 | 257 | 246 | N | E | 170 | 284 | 3 | 525.000 | N |
-Wally Backman | 387 | 124 | 1 | 67 | 27 | 36 | 7 | 1775 | 506 | 6 | 272 | 125 | 194 | N | E | 186 | 290 | 17 | 550.000 | N |
-Wade Boggs | 580 | 207 | 8 | 107 | 71 | 105 | 5 | 2778 | 978 | 32 | 474 | 322 | 417 | A | E | 121 | 267 | 19 | 1600.000 | A |
-Will Clark | 408 | 117 | 11 | 66 | 41 | 34 | 1 | 408 | 117 | 11 | 66 | 41 | 34 | N | W | 942 | 72 | 11 | 120.000 | N |
-Wally Joyner | 593 | 172 | 22 | 82 | 100 | 57 | 1 | 593 | 172 | 22 | 82 | 100 | 57 | A | W | 1222 | 139 | 15 | 165.000 | A |
-Wayne Krenchicki | 221 | 53 | 2 | 21 | 23 | 22 | 8 | 1063 | 283 | 15 | 107 | 124 | 106 | N | E | 325 | 58 | 6 | NA | N |
-Willie McGee | 497 | 127 | 7 | 65 | 48 | 37 | 5 | 2703 | 806 | 32 | 379 | 311 | 138 | N | E | 325 | 9 | 3 | 700.000 | N |
-Willie Randolph | 492 | 136 | 5 | 76 | 50 | 94 | 12 | 5511 | 1511 | 39 | 897 | 451 | 875 | A | E | 313 | 381 | 20 | 875.000 | A |
-Wayne Tolleson | 475 | 126 | 3 | 61 | 43 | 52 | 6 | 1700 | 433 | 7 | 217 | 93 | 146 | A | W | 37 | 113 | 7 | 385.000 | A |
-Willie Upshaw | 573 | 144 | 9 | 85 | 60 | 78 | 8 | 3198 | 857 | 97 | 470 | 420 | 332 | A | E | 1314 | 131 | 12 | 960.000 | A |
-Willie Wilson | 631 | 170 | 9 | 77 | 44 | 31 | 11 | 4908 | 1457 |
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