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  • Progressing Toward Better Stats Thread

    This chart shows Road Relative OPS+ or rrOPS+ which essentially puts a players RAW OPS+ into better perspective.

    It gives a more accurate depiction of a player's true ability, by giving him his home park as a road park...so his rrOPS+ is him playing in all parks equally.

    The method is simple.

    Players road SA divided by his leagues road SA. Same thing with OBP. These two relative numbers are added, subtracted by 1, and then multiplied by the league OPS+. This removes pitchers from the league.

    In order to give the player his home park as a road park, the next step is (ROAD REL OPS+ * 3) + (RAW OPS+) / 4 (normalized to eight team league)

    Further perspective is given through rrOPS++ by weighing by playing time.


    Code:
                           raw OPS+ in ( )  weighted by 10k PA
    PLAYER          rrOPS+        rrOPS++
    Code:
    RUTH             209.5 (206)       216.3
    T.WILLIAMS       191.2 (190)       189.2
    GEHRIG           183.5 (179)       180.6
    Ba.BONDS         177.4 (182)       197.5
    COBB ('08-'28)   173.0 (170)       186.8
    J.JACKSON        173.0 (170)       141.5
    HORNSBY          172.1 (175)       168.3
    MANTLE           166.9 (172)       166.2
    J.DiMAGGIO       164.2 (155)       149.2
    PUJOLS           161.6 (162)       156.9
    McGWIRE          160.1 (163)       146.0
    M.RAMIREZ        159.3 (154)       157.9
    MUSIAL           158.6 (159)       174.5
    FOXX             156.1 (163)       154.2
    MAYS             155.9 (156)       169.8
    AARON            154.5 (155)       176.1
    D.ALLEN          154.1 (156)       138.8
    C.KELLER         152.9 (152)       124.3
    M.CABRERA        152.8 (154)       141.2
    MIZE             152.8 (158)       139.6
    OTT              152.6 (155)       159.6
    SPEAKER          150.9 (158)       161.0
    F.THOMAS         149.7 (156)       150.0
    F.ROBINSON       149.1 (154)       157.6
    HEILMANN         149.0 (148)       143.9
    PIAZZA           148.9 (142)       138.0
    E.MARTINEZ       148.7 (147)       142.2
    E.MATHEWS        148.2 (143)       148.6
    THOME            147.4 (147)       148.7
    SCHMIDT          147.3 (147)       147.5
    McCOVEY          145.8 (147)       144.3
    BAGWELL          144.8 (149)       142.2
    B.TERRY          144.7 (136)       131.7
    GREENBERG        144.4 (158)       127.0
    KILLEBREW        144.1 (143)       143.3
    STARGELL         144.0 (147)       139.7
    BERKMAN          143.7 (144)    
    A.BELLE          143.4 (144)       128.9
    B.HERMAN         143.4 (141)       127.0
    R.JACKSON        142.9 (139)       148.9
    A.RODRIGUEZ      141.8 (140)       151.0
    MCGRIFF          141.8 (134)       142.5
    KINER            141.5 (149)       125.9
    V.GUERRERO       140.9 (140)       137.0
    H.WILSON         140.3 (144)       122.3
    D.ORTIZ          140.1 (141)       140.1   
    SNIDER           138.3 (140)       131.5
    SHEFFIELD        137.9 (140)       141.4
    E.COLLINS        137.6 (136)       131.6
    CRAVATH          137.5 (154)       111.7
    F.HOWARD         136.9 (142)       127.1
    MAUER            136.9 (133)       121.2
    C.JONES          136.7 (141)       138.9
    VAUGHAN          136.6 (136)       128.2
    CASH             136.6 (139)       128.9
    K.MITCHELL       136.4 (142)       117.0
    TENACE           136.1 (136)       119.9
    B.GILES          135.4 (136)       127.7
    BERGER           135.3 (138)       119.9
    COLAVITO         135.0 (132)       126.4
    J.GONZALEZ       134.3 (132)       124.5
    J.ROBINSON       133.5 (132)       119.4
    B.JOHNSON        133.4 (139)       126.8
    L.WALKER         133.4 (141)       126.8
    GOSLIN           133.1 (128)       132.5
    KALINE           133.1 (134)       138.3 
    R.SMITH 132.9 (137) PALMEIRO 132.8 (132) 139.5 D.WINFIELD 132.7 (130) 135.9 CAREW 132.5 (131) 134.2 BRETT 132.3 (135) 137.5 W.CLARK 132.3 (137) CANSECO 132.2 (132) 126.1 EDMONDS 132.1 (132) 125.6 A.SIMMONS 131.6 (133) 130.0 P.WANER 131.4 (134) 133.8 B.NICHOLSON 131.3 (132) 120.0 SISLER 131.1 (125) 128.0 Bo.BONDS 130.9 (129) 124.9 COCHRANE 130.7 (129) 119.0 KRUK 130.7 (134) 114.1 STRAWBERRY 130.3 (138) 119.1 K.WILLIAMS 130.2 (138) 116.9 GRIFFEY JR 130.0 (136) 133.9 K.HERNANDEZ 129.9 (128) 125.5 R.HENDERSON 129.4 (127) 139.2 GWYNN 129.4 (132) 130.0 E.MURRAY 129.4 (129) 137.7 Bi.WILLIAMS 129.1 (133) 130.6 MEDWICK 129.1 (134) 123.6 GEHRINGER 128.9 (124) 129.6 MORGAN 128.9 (132) 132.7 HELTON 128.6 (133) 127.0 M.VAUGHN 128.5 (132) 118.2 WHEAT 128.3 (129) VEACH 127.2 (129) 118.8 J.GORDON 126.9 (120) 117.5 Dw.EVANS 126.7 (127) 128.2 DICKEY 126.5 (127) 118.7 CLEMENTE 126.4 (130) 126.9 SOSA 126.2 (128) 125.9 BENCH 126.1 (126) 122.6 STAUB 126.1 (124) 129.3 KLEIN 125.9 (137) 118.5 K.GIBSON 125.7 (123) 117.1 GRICH 125.6 (125) 121.0 ABREU 125.0 (128) 125.2 YASTRZEMSKI 124.6 (130) 134.4 AVERILL 124.3 (133) 117.5 BOUDREAU 124.2 (120) 116.9 KENT 123.9 (123) HARTNETT 123.5 (126) 117.1 J.RICE 123.2 (128) 121.0 LAZZERI 122.9 (121) 116.7 CEDENO 122.8 (123) ROLEN 122.2 (122) 118.9 HODGES 122.1 (120) 117.9 FLYNN 122.0 (129) 117.4 SLAUGHTER 121.0 (124) 119.0 DAWSON 120.9 (119) 122.5 BERRA 120.7 (125) 117.3 GARCIAPARRA 120.6 (124) 112.5 BELTRE HJOHNSON 120.5 (118) 111.7 RAINES 120.4 (123) 121.1 MOLITOR 120.2 (122) 124.5 BOGGS 119.7 (131) 121.1 DaEVANS 119.0 (119) 120.4 DPARKER 118.5 (121) 118.8 FISK 118.3 (117) 118.0 H.HOOPER 115.3 (114) W.DAVIS 111.7 (106) SEWELL 105.8 (108) RIZZUTO 90.5 (93) CONCEPCION 88.0 (88)

    Post #69 has the original work bb-fever was screwing up the coding lineup


    Code:
            
    ROAD RELATIVE SLUGGING EFFICIENCY                    
    
          TB ÷ (AB - H)         HOME        ROAD    LG SPECIFIC  (ROAD SLGeff ÷ LG ROAD SLGeff)
              SLGeff     SLGeff   -.SLGeff    ROAD SLGeff         ROAD REL SLGeff          LG OPS+         (HOME AS ROAD)
    Code:
    Ruth               1.048     1.068     1.029      .5058               2.034               94.00
    
    Gehrig             .9583     .9236     .9921      .5424               1.829               93.76
    
    TWilliams          .9667     1.020     .9143      .5018               1.822               93.57    
    
    JDiMaggio          .8569     .7983     .9154      .5131               1.784               93.46    
    
    JJackson          .8030      .8460       .7622     .4314         1.766         93.92  
    Cobb ('08-'28) .8287 .8228 .8331 .4725 1.763 94.00
    Hornsby .8987 .9193 .8790 .5130 1.713 93.73 Aaron .7978 .7993 .7964 .4995 1.594 93.56 BaBonds .8645 .8833 .8471 .5323 1.591 93.95 Musial .8354 .8770 .7967 .5035 1.582 93.13 Mantle .7932 .8191 .7690 .4900 1.569 93.38 WMays .7983 .8120 .7856 .5015 1.566 92.90 Foxx .9030 1.011 .8091 .5238 1.544 93.60 Piazza .7876 .7297 .8419 .5468 1.539 94.50 - C Mize .8170 .8795 .7576 .4972 1.523 93.46 Heilmann .7905 .8071 .7751 .5093 1.521 93.94 BTerry .7678 .7265 .8097 .5334 1.517 93.57 Ott .7661 .7938 .7398 .5066 1.460 93.45 Stargell .7357 .7643 .7093 .4864 1.458 93.28 McGwire .7978 .8004 .7953 .5489 1.448 98.37 EMathews .6989 .6634 .7321 .5060 1.446 92.88 Simmons .8033 .8560 .7548 .5255 1.436 93.70 Schmidt .7198 .7419 .6995 .4888 1.431 93.61 FRobinson .7607 .8248 .7039 .4928 1.428 94.19 MRamirez .8511 .8569 .8455 .5955 1.419 99.26 Greenberg .8813 1.028 .7443 .5272 1.411 93.46 McCovey .7048 .7221 .6890 .4915 1.401 93.27 VGuerrero .8097 .8392 .7795 .5566 1.400 97.12 Speaker ('08-'28) .7648 .8509 .6865 .4725 1.452 94.00 Goslin .7304 .7008 .7580 .5417 1.399 93.88 JGonzalez .7956 .8090 .7833 .5621 1.393 99.88 Snider .7661 .8167 .7168 .5151 1.391 92.88 ABelle .7996 .8302 .7710 .5582 1.381 99.91 Medwick .7459 .8175 .6812 .4935 1.380 93.41 Colavito .6656 .6595 .6710 .4874 1.376 93.28 HWilson .7859 .8365 .7363 .5358 1.374 93.58 FHoward .6862 .7052 .6679 .4865 1.372 93.25 Bagwell .7683 .8040 .7345 .5404 1.359 94.13 RJackson .6640 .6459 .6814 .5021 1.357 98.00 Kiner .7597 .8333 .6888 .5096 1.351 93.10 ARodriguez .7966 .8287 .7660 .5685 1.347 99.90 Wheat ('14-'27) .6795 .7088 .6511 .4838 1.345 94.07 Maris .6432 .6341 .6514 .4848 1.343 93.25 Dawson .6692 .6686 .6697 .5011 1.336 94.33 EMartinez .7486 .7500 .7474 .5593 1.336 99.88 Clemente .6960 .7279 .6664 .4999 1.333 92.88 McGriff .7113 .7058 .7165 .5428 1.320 97.00 Winfield .6614 .6395 .6820 .5172 1.318 97.72 Cash .6702 .7115 .6308 .4796 1.315 94.00 Delgado .7580 .7681 .7482 .5697 1.313 98.17 Gwynn .6928 .7092 .6773 .5179 1.307 93.85 Thome .7658 .8001 .7318 .5598 1.307 98.90 Bench .6495 .6672 .6322 .4844 1.305 93.47 - C CJones .7598 .8130 .7091 .5443 1.302 94.21 Sosa .7344 .7670 .7031 .5417 1.297 95.77 Lombardi .6626 .6861 .6398 .4931 1.297 93.41 - C BiWilliams .6927 .7519 .6354 .4912 1.293 93.66 Sheffield .7256 .7485 .7038 .5444 1.292 96.54 KWilliams .7791 .9070 .6571 .5086 1.291 94.00 Berra .6740 .7071 .6434 .4985 1.290 93.57 - C FThomas .7939 .8621 .7270 .5661 1.284 99.89 Edmonds .7364 .7514 .7215 .5625 1.282 96.52 LWalker .8224 .9767 .6849 .5346 1.281 94.11 Klein .7986 .9553 .6528 .5097 1.280 93.35 EMurray .6678 .6601 .6751 .5294 1.275 98.42 Brett .7010 .7431 .6614 .5196 1.272 100.0 Canseco .7009 .6962 .7052 .5543 1.272 99.94 Carew .6384 .6504 .6272 .4969 1.262 97.78 Kingman .6254 .6264 .6244 .4960 1.258 95.00 EDavis .6597 .6593 .6600 .5245 1.258 95.11 Hodges .6697 .6992 .6421 .5128 1.252 93.00 Sisler .7096 .7848 .6381 .5104 1.250 94.03 Griffey Jr .7508 .8136 .6941 .5552 1.250 97.70 Averill .7821 .8950 .6744 .5396 1.249 93.61 KHernandez .6195 .6269 .6126 .4906 1.248 94.05 Garvey .6319 .6528 .6118 .4911 1.245 93.52 DParker .6628 .7125 .6183 .4968 1.244 95.00 Banks .6882 .7566 .6226 .5056 1.231 92.89 KBoyer .6481 .6835 .6136 .5010 1.224 92.86 JRice .7152 .8022 .6349 .5201 1.220 100.0 Buhner .6614 .6466 .6762 .5565 1.215 99.93 JLopez .6888 .7117 .6673 .5504 1.212 95.33 - C Helton .7885 .9273 .6573 .5442 1.207 94.23 Tenace .5651 .5447 .5839 .4858 1.201 95.20 - C DMurphy .6382 .6938 .5864 .4925 1.190 93.72 GCarter .5948 .6107 .5799 .4891 1.185 93.73 - C Fisk .6248 .6462 .6042 .5121 1.179 99.12 - C Ripken Jr .6176 .5934 .6406 .5478 1.169 99.95 Yastrzemski .6463 .7249 .5734 .4906 1.168 96.34 Larkin .6301 .6481 .6121 .5283 1.158 93.94 Campanella .6902 .7992 .5973 .5174 1.154 93.10 - C Caminiti .6135 .6198 .6073 .5269 1.152 94.13 Rose .5871 .6181 .5581 .4859 1.148 93.33 Greenwell .6642 .7121 .6189 .5417 1.142 100.0 Sandberg .6312 .7017 .5635 .5016 1.123 93.75 JCarter .6268 .6472 .6067 .5406 1.122 99.37 Santo .6417 .7422 .5461 .4903 1.113 93.33 IRodriguez .6596 .6961 .6250 .5628 1.110 99.23 - C Boggs .6586 .7593 .5654 .5465 1.034 99.94
    Attached Files
    Last edited by Sultan_1895-1948; 08-31-2019, 12:47 PM.

  • #2
    I realized that I can compare the players' outs to the league rate of outs to figure out how many extra plate appearances a player like Ruth "earned for himself". Rbat already has a cost value of making outs. What I want to account for is that the low out producer is getting some of his extra plate appearances because he is saving outs.

    So let's work through the math for Babe Ruth 1921, which I chose simply because it is the highest Rbat total in history at 116.

    Rbat: 116 (above average)
    PAs: 693
    Batting outs: 336 (I will not look at Sacs or GIDPs at this point as they may be situational and also were not always official or kept stats. So I just take AB-H)

    League runs: 6296
    League PAs: 48698
    League outs: 30280

    The next part I am going to have to figure out how to put in into an algebraic equation later, but using plugging and checking I got that Ruth's 693 PAs were 103% higher because he made few outs. The average player would have gotten just 675.

    (Basically and to within about 1 PA, The average player got 1.61 PAs per out. Multiplying by 336 outs that Ruth made, they would have gotten 540 PAs in the same number of outs that he got 693, however, only 1/9 of his 153 extra PAs would have gone to himself, so an average player in Ruth's spot would have only gotten 674-675 PAs while he got 693).

    In 675 PAs the average player produced 87.3 Rbat.

    Ruth had 116.

    (116+87.3)/87.3= 2.33, or 233%, strikingly similar to his OPS+ of 238

    Comment


    • #3
      As for earned runs, Rbat actually estimates a players runs created whether they are earned or unearned so I believe it is more accurate.

      As for the walk thing, its minor. Origially I was looking at how many runs Ruth produced above average (116) and what the average player did in the same number of plate appearances (693 which would be 89 runs) but I realized that Ruth's low outs meant that he GOT 693 PAS, but an average hitter would only have gotten about 675, so I'm actually giving Ruth more credit for making fewer outs. Ruth produced over 693 PAs but an average guy should only count his rate of production through 675 because Ruth effectively created 18 more plate appearances for himself.

      Comment


      • #4
        Gentlemen… please…

        http://en.wikipedia.org/wiki/Total_average

        http://www.baseball-reference.com/bullpen/Total_Average
        Your Second Base Coach
        Garvey, Lopes, Russell, and Cey started 833 times and the Dodgers went 498-335, for a .598 winning percentage. That’s equal to a team going 97-65 over a season. On those occasions when at least one of them missed his start, the Dodgers were 306-267-1, which is a .534 clip. That works out to a team going 87-75. So having all four of them added 10 wins to the Dodgers per year.
        http://www.youtube.com/watch?v=p5hCIvMule0

        Comment


        • #5
          Total average has the precise problem of dividing by player outs. Players don't get outs, and they don't really get plate appearances either. They get plate appearances plus or minus extra PAs created or lost by their rate of making outs.

          If Rbat (for war) is really a good weighted measure of run production above average, then Rbat divided by the league average run production for the same number of plate appearances plus or minus those created or lost for oneself would basically be an OPS+ like stat but that is actually meaningful and accurate throughout the entire range of player productivity. But because of some of the issues with coming up with the career-long run environment and league OB% for a player, maybe it would be better to just convert Rbat into batting wins above average. This would account for run environement and general park effects and weigh everything right.

          Babe Ruth has 1334 Rbat (above average)
          We can see that war shows that 1717 RAR converts to 163.2 WAR which means that 10.52 runs equals one win.
          So 1334/10.52= 126.8 career games won above average by hitting for Ruth.

          That is a darn good estimate of his career greatness as a hitter, and pretty simple to come up with. While there are a few flaws with the next step, on the order of tenths of wins, that also can be shown as a rate, 8.21 batting wins per 162 games.
          Ruth: +126.8/8.21
          Bonds: +111.9/6.07
          Williams: +106.0/7.49
          Cobb: +105.4/5.63
          Gehrig: +89.7/6.72
          Hornsby: +86.3/6.19
          Pujols: +65.3/5.40


          Also assuming 4.5 batting wins per full time player per 162 (which may be a little high because baserunning is not net zero) we would also come up with OPS+ like scores of the following:

          Ruth: 282
          Williams: 266
          Bonds: 235
          Cobb: 225
          Gehrig: 249
          Hornsby: 238
          Pujols: 220

          Which tend to support that OPS+ fails to stay proportional at very high levels, and so may underrate the best hitters. Remember though that this includes pitchers in the league totals. Still all of these guys would be over 200 relative rate of production even with pitchers taken out of the equation.

          Comment


          • #6
            I'm not certain that this fits the ends intended; but, for me, if we are going to bring an evaluation of outs clearly into the picture of base-runs net production, we should give special attention to what I call negative outs ... those outs, which, of their very nature, are particularly non-productive.

            I have looked at the top 30 or so run producers and determined the larger scope of total negative outs as relative percentage of all outs per player. I have also determined specific negative values for each K and DP, subtracting thier negative values from player RC as presented in B-R, Advanced Batting.

            If this data might be useful, I'll post it. Otherwise, I'll continue to listen.

            Comment


            • #7
              My "negative outs" approach regarding K and G[H]IDP numbers for each batter, relative to all his PA, AB and total outs, will not be so refined as to pitcher-batter handedness, fly ball/ground ball propensities or type of batted ball that was converted into a double play or triple play.

              That, on its face, may at first seem an open invitations to futility; but, as I see it, the bottom line will depend on a correlation among all bases collected on the + side of the ledger and all escalated out negative impacts on the run scoring machinery regardless of the luck or breaks involved in play execution, or the positive attributes of a K that makes the pitcher work harder.

              I am approaching this for the period 1901 - present. If I find anything worth while, I'll post it eventually. If not, I'll post that ... as a public confession of sorts ... and as a public safety announcement so others can avoid the quicksand pit I eagerly ran into.

              Comment


              • #8
                Originally posted by leewileyfan View Post
                My "negative outs" approach regarding K and G[H]IDP numbers for each batter, relative to all his PA, AB and total outs, will not be so refined as to pitcher-batter handedness, fly ball/ground ball propensities or type of batted ball that was converted into a double play or triple play.

                That, on its face, may at first seem an open invitations to futility; but, as I see it, the bottom line will depend on a correlation among all bases collected on the + side of the ledger and all escalated out negative impacts on the run scoring machinery regardless of the luck or breaks involved in play execution, or the positive attributes of a K that makes the pitcher work harder.

                I am approaching this for the period 1901 - present. If I find anything worth while, I'll post it eventually. If not, I'll post that ... as a public confession of sorts ... and as a public safety announcement so others can avoid the quicksand pit I eagerly ran into.
                Sounds good. I love that last line!

                Before I enter EL REINO DE ARENAS MOVEDIZAS, I'm waiting to hear back on whether my last post was done properly, and if it's something worth replacing tOPS+ in my chart.

                Comment


                • #9
                  Who was a more efficient slugger between Ken Griffey Jr and Sam Crawford?

                  Griffey slugged 86 points higher, hit 533 more homers and 66 more doubles, but Crawford had 271 more triples.

                  Raw slugging efficiency (TB/OUTS) shows junior to be ahead .712 to .628.

                  Interestingly enough, when you factor in Junior's league slugged .424 and Crawford's .340, their difference is exactly the same, .288 above league.

                  Even a step further, dividing each ones 28.8 by their individual AB totals and multiplying by 550, Crawford eeks out the victory 1.65 to 1.61.

                  Doing a couple other guys, Piazza and Mantle are dead even at 2.56. Never would have expected that. Especially from a catcher whose league slugged .420 and Mantle's slugged just .387. Piazza was a flat out stud!

                  Comment


                  • #10
                    -----------------------------------
                    Last edited by Sultan_1895-1948; 07-21-2014, 06:48 PM.

                    Comment


                    • #11
                      Hey Ubi, how do you post an Excel file, like you did in Historic Game Logs thread?

                      Nevermind, think I just figured it out. Has to be as attachment...our old friend, the paperclip.

                      So here are AL/NL league SAeff numbers through '46, TB/PUT OUTS. This will go a long ways towards making a better relative SAeff stat. If there's any volunteers to take the file and do a couple decades, that would be awesome..if not, I'll finish it.

                      Updated through 1977.
                      Attached Files
                      Last edited by Sultan_1895-1948; 04-22-2014, 04:34 PM.

                      Comment


                      • #12
                        Ok, complete through 2013.

                        Is there any way to account for the DH not being in the NL....like a certain % boost to the NL number? Or we just leave it as is?
                        Attached Files
                        Last edited by Sultan_1895-1948; 04-24-2014, 06:59 PM.

                        Comment


                        • #13
                          Originally posted by Sultan_1895-1948 View Post
                          Ok, complete through 2013.

                          Is there any way to account for the DH not being in the NL....like a certain % boost to the NL number? Or we just leave it as is?
                          You can try. Since OPS+ is about 6% lower with pitchers you could multiply the NL rates by 1.06, but DH's are something like 16% above average, spread through the lineup that would also be another 2% there. So 1.08. That's a first impression. In fact it raises an issue that even though pitchers are removed in finding OPS+, AL hitters are still compared to a lineup with a DH added.

                          Comment


                          • #14
                            Originally posted by brett View Post
                            You can try. Since OPS+ is about 6% lower with pitchers you could multiply the NL rates by 1.06, but DH's are something like 16% above average, spread through the lineup that would also be another 2% there. So 1.08. That's a first impression. In fact it raises an issue that even though pitchers are removed in finding OPS+, AL hitters are still compared to a lineup with a DH added.
                            So to create an even playing field, the goal is to statistically figure out a way to remove the pitcher and supplant a hypothetical DH into the NL? That would be easier and more accurate than doing the reverse; that is, to attempt to remove the DH from the AL, correct? Seems the latter would create sooo many more issues.

                            From 1994 to 2007, the AL AVERAGED .557 SAeff....the NL had NO SINGLE SEASON that high in the same span.

                            On a side note...for SAeff.....

                            Do we just divide the players' total by their league AVG total to get relative?
                            Last edited by Sultan_1895-1948; 04-24-2014, 08:24 PM.

                            Comment


                            • #15
                              Originally posted by Sultan_1895-1948 View Post

                              Do we just divide the players' total by their league AVG total to get relative?
                              Yes, that is the way to do it.

                              Comment

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