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  • leewileyfan
    replied
    The more this thread evolves, the more it is about metrics employed than sample players being compared. This is probably just what it should be doing. However, many of the statistical titles being used are components that contribute to more comprehensive formulas that approach run production differently.

    Citing the model [Visitor and Home; Post #21, page 1 of this thread, here is a sampling of referents and the run production end products each creates [all relative to the Home-Visitor model]:

    Player ..... SLG ..... OB% ..... OPS ..... RC ........ RC2 ..... BsR

    Home ..... .450 ..... .367 ..... .817 ..... 100.8 ..... 99.2 ..... .93.1
    Visitor .... .450 ..... .349 ..... .799 ........92.6 ..... 94.3 ..... .94.7

    Above, RC = shortcut runs created, [BB+TB*BA] OR [TB*OB%]
    RC2 = a wrinkle on the above: [H + BB] * TB/PA

    BsR: currently favored by many as "accurate" by being more sensitive to baseball game dynamics "reality," combines Linear Weights input values for events with advancement factors and OUT values.

    If we take the above and apply them to actual players in actual seasons, we can see projected values and how they evaluate events:

    Ted Williams, 1941
    Jimmy Bloodworth 1949
    Cecil Travis 1941
    Lou Whittaker 1988

    PlayerName ...... AB ... Hits ..... BB ... HR ... TB ...... SLG % ...OBAvg ... Pl. OPS ... RC ...... RC2 ...... BsR ... Ba.-Ref. RC

    Williams '41 ... 456 ... 193 ... 147 ... 37 ... 335 ... .744 ... .564 ....... 1.298 ... 204.0 ... 188.9 ... 188.2 ... 183
    Bloodworth '49... 452 ... 118 ... 27 ... 9 ... 174 ... .385 ... .303 ....... .688 ... 52.5 ... 52.7 ... 51.4 ... 53
    Travis ,41 ........ 608 ... 218 ... 52 ... 7 ... 316 ... .520 ... .409 ....... .929 ... 131.9 ... 129.3 ... 121.7 ... 129
    Whittaker '88 ... 403 ... 111 ... 66 ... 12 ... 169 ... .419 ... .377 ....... .796 ... 64.7 ... 63.8 ... 66.3 ... 67

    Point being ... if we discuss player run creation value, we should define terms so that we are on the same page, apples-to-apples. I was personally surprised with the BsR numbers for Home-Visitor ... being the only metric that reversed run values.

    I allow that I may have erred in calculation; but I ran the numbers six times, so I suppose they are right. It's just odd that BsR would, in this instance, not only differ from other metrics, bur actually reverse tha valuations [runs created].

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  • dominik
    replied
    to go back to the original mantle vs. hornsby example:

    I looked at wRC+ at fangraphs and was very surprised that they are both at 171. so actually mantle looks better with that stat than with OPS+ which has him 4 points back.

    But I think this is not because of the xBHs. slugging does overrate XBHs (we can discuss about linear weights being correctly but nobody who is sane will think that a HR is worth 4 times as many runs as a single) but at the same time it also underrates walks (doesn't count them so that a walk is only included in the OBP component).

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  • Jackaroo Dave
    replied
    yes and yes.

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  • Joltin' Joe
    replied
    Originally posted by leewileyfan View Post
    As I read the thread, the INITIAL poster [Joltin' Joe] made no such restrictions. He introduced a premise of comparability [not exactitude] and SUGGESTED the possible key role of BA as "tiebreaker," if such were needed.

    Or did I miss something?
    I think Dave might have been referring to this thread => http://www.baseball-fever.com/showth...hitter-and-why

    That thread and this thread kind of got mixed up. I never created this thread. This thread was "created" by a mod that felt the stat discussion deviated too much from the original thread about Dwight Evans. He deleted the discussion portion of that thread and moved it over here, which is the thread you see here. Nonetheless, regardless of the origin, it has turned into an interesting discussion.

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  • Jackaroo Dave
    replied
    Leewileyfan,

    First I want to say that on re-reading, my post seemed a lot brusquer and less civil than I'd intended. I'm sorry; it's a weakness. Frustration with a problem appears as if frustration with the reader.

    I did as you suggested and looked through the figures, and I think I can express my problem more clearly and succinctly:

    The Visitor reaches base in 235/673 plate appearances, for an on base average of .350. The Home player reaches in 235/637 plate appearances, for an on base average of .370.

    Using your data and MLB 2011 OB, SLG figures, Visitor has an unadjusted ops+ of 1.22, Home of 1.28.

    Hence my point that the two players aren't comparable--in the sense that their productivity is visibly different at the beginning. So I'd say that there's nor role for BA as a tie breaker, because there is no tie.

    Using 2011 WOBA, I get .352 for visitor and .359 for home.

    Using Bill James's Runs Created for Dummmies formula, Visitor has about 94 runs created, Home about 100 (no real difference from your finding).

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  • leewileyfan
    replied
    Originally posted by Jackaroo Dave View Post
    "Interested" in what, exactly? IIRC, we started out trying to investigate whether two players with identical OPS(+) could be ranked by BA. So that means, to me, at any rate, they have to enter the comparison with the same initial assets. Since outs are the medium of exchange for runs, a comparison that doesn't hold outs constant is giving one player a hidden advantage, run inflation if you will, since he's paying more for his productivity.
    As I read the thread, starting at Post #1, the concepts of evaluating individual inputs of batting performance were being weighed, considering the relative merits of BA, OBP, OPS and OPS+. The initial poster suggested the value of BA as a tie-breaker.

    Since BA and OBP [and related spin-offs] have different denominators BA and OBP], then the fixity of disparate elements being perfectly equal, kind of restricts the scope of testing the data.

    : In Leewileyfan's Home-Visitor example, the visitor comes into the comparison with a bonus of 36 extra outs. Before I (anyhow) can compare them, I have to figure out to to restore this disparity to equity.
    I made the batters comparable, as they certainly are in the critical areas of ABs and Total Bases. The other data are variables, conforming only to the limits of AB and Total Bases.

    :The initial poster was very careful to make PA, outs, OB, SLG, OPS come out even and let the difference in batting average drive the other differences: ISOP, hits, and walks. As far as I can tell, it seemed that there just wasn't that much wiggle room left, and the difference in ISOP (more efficient use of total bases) more or less balanced out the difference between a walk and a single (greater runner advancement for the latter)--in this particular case.
    As I read the thread, the INITIAL poster [Joltin' Joe] made no such restrictions. He introduced a premise of comparability [not exactitude] and SUGGESTED the possible key role of BA as "tiebreaker," if such were needed.

    Or did I miss something?[/QUOTE]

    When I alluded to "interested" posters, I was suggesting that the thread MIGHT benefit from various POV and varied perspectives on what sabermetric value formulas different posters might want to apply. I even suggested that one might want to modify the model exactly to his/her liking before applying the math.

    My own quick evaluation is that the Visitor model will create 92.6 runs. The Home model will create 100.7 runs. Essentially this is the shortcut RC formula that uses TB + BB * BA. This is at least consistent with the original poster's view that BA might make a good tie breaker. [POST 21 of this thread provides the model to which I am referring].
    Last edited by leewileyfan; 03-15-2012, 09:54 AM.

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  • Jackaroo Dave
    replied
    Originally posted by leewileyfan View Post
    I posted that a while back; so I won't deny it may have been an oversight on my part. What interested posters MIGHT want to is to look at BOTH players from two perspectives:
    1. exactly as presented in the original model; OR
    2. by adding TPA into the equation, with Visitor having 673 total plate appearances, and Home having 637 TPA
    #2 would make their BA "profiles" equivalent, with AB and Hits preserved.
    "Interested" in what, exactly? IIRC, we started out trying to investigate whether two players with identical OPS(+) could be ranked by BA. So that means, to me, at any rate, they have to enter the comparison with the same initial assets. Since outs are the medium of exchange for runs, a comparison that doesn't hold outs constant is giving one player a hidden advantage, run inflation if you will, since he's paying more for his productivity.

    In Leewileyfan's Home-Visitor example, the visitor comes into the comparison with a bonus of 36 extra outs. Before I (anyhow) can compare them, I have to figure out to to restore this disparity to equity.

    I can see the point of holding PA's constant, as each represents an opportunity to do something. But if you have two batters putting the same number of runs on the board in the same number of PA's but one using more outs, well, he's consuming more of the team's assets, so they aren't starting off even.

    The initial poster was very careful to make PA, outs, OB, SLG, OPS come out even and let the difference in batting average drive the other differences: ISOP, hits, and walks. As far as I can tell, it seemed that there just wasn't that much wiggle room left, and the difference in ISOP (more efficient use of total bases) more or less balanced out the difference between a walk and a single (greater runner advancement for the latter)--in this particular case.

    Or did I miss something?
    Last edited by Jackaroo Dave; 03-14-2012, 05:16 PM.

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  • leewileyfan
    replied
    Originally posted by brett View Post
    A problem in your model is that you gave them the same number of at bats. They should have the same number of plate appearances probably, (or for a team, outs).
    I posted that a while back; so I won't deny it may have been an oversight on my part. What interested posters MIGHT want to is to look at BOTH players from two perspectives:

    1. exactly as presented in the original model; OR
    2. by adding TPA into the equation, with Visitor having 673 total plate appearances, and Home having 637 TPA

    #2 would make their BA "profiles" equivalent, with AB and Hits preserved.

    Leave a comment:


  • brett
    replied
    Originally posted by dominik View Post
    I would say even in a very wrong environment linear weights are still a lot more precise than the SLG coefficients. the value of a double might change from .7 to .75 but it never has twice the value of a single.

    I think it is pretty safe to say that if SLG is equal the guy with the higher BA and lower ISO will produce more.
    Remember that the higher BA lower ISO guy will also have to draw more walks to keep his OB% the same.

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  • brett
    replied
    Originally posted by leewileyfan View Post
    The model is a self-fulfilling prophecy. The guy with the highest BA is presumed to have the same OB% and SLG and the guy batting around .190. One can create an arithmetic model to suit and point under debate.

    In the context of recent remarks posted here, I tried to construct a reasonable pair of batters with very comparable stats OTHER than their respective BAs, which, in themselves are fairly well apart but not so extreme as to forbid reasonable comparisons.

    Player "Visitor" posts these numbers:

    AB 600
    H 162
    BA .270
    HR 30
    3B 0
    2B 18
    1B 114
    BB 73
    TB 270

    Player "Home" puts up these numbers:

    AB 600
    Hits 198
    BA .330
    HR 12
    3B 4
    2B 29
    1B 152
    BB 37
    TB 270

    The hour grows late, so I penalized Home a single. There is nothing in the figures that would indicate DPs batted into by either player. One has 48 extra base hits; the other 45. The big disparity would seem to be HRs; but hen the question is legitimately raised WHEN and under what circumstances game/conditions each of those 18 big hits were belted. In a full season, there's enough random chance in PA where 18 "bombs" may not be all that telling, especially when the trailer is collecting 36 more hits on his side of the ledger.
    A problem in your model is that you gave them the same number of at bats. They should have the same number of plate appearances probably, (or for a team, outs).

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  • leewileyfan
    replied
    Thanks, J-J and to all who posted. Speaking of King Kong and Heath, they were quite an exciting pair of players to watch at the plate. Both were built for compact power and both generated fearsome swipes at the ball.

    I recall a ballgame at Yankee Stadium where a brawl broke out and concentrated in a heap out by the pitching mound. During the brawl, Joe DiMaggio and Charlie Keller, in the outfield, meandered over toward each other and passed some time in conversation. I kind of nudged my Dad asking why they were staying so out-of-the fight.

    My father answered to the effect that, at least as Charlie Keller was concerned, it was probably good for the health and safety of the brawlers that Keller was keeping the peace.

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  • Joltin' Joe
    replied
    Good stuff LWF, and very interesting posts by everyone. I am surprised at the results between King Kong & Heath.

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  • leewileyfan
    replied
    OK and thanks to those who posted. This sampling and discussion need not end with this post, because in revealing the year and the players involved, anyone interested in pursuing evaluation metrics further can look up the statistical line for each player and have the full input values at hand.

    The year was 1941, and the players were all from the American League.

    A. Charlie Keller
    B. Taft Wright
    C. Ken Keltner
    D. Barney McCosky
    E. Rudy York
    F. Harlond Clift
    G. Walt Judnich
    H. Roy Cullenbine
    I. Buddy Lewis
    J. Bob Johnson
    K. Joe Cronin
    L. Tommy Henrich
    M. Jeff Heath

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  • leewileyfan
    replied
    Just to round out the evaluation data with yet another consideration, I took LWTS [measures run creation ABOVE AVERAGE], here's how the thirteen players fare against league average for the season. [To convert to "wins" divide by 10].

    A. 59.2
    M. 57.5
    H. 51.6
    K. 44.6
    I. 40.8
    J. 37.6
    B. 34.8
    G. 30.7
    F. 29.3
    I. 29.3 [rounding]
    E. 28.2
    D. 27.0
    B. 22.4

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  • Ubiquitous
    replied
    Tango has a chart of custom linear weights by team and year based on BsR at his website for those curious about that.

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