MGL's superLWTS (March 10, 2004)
MGL requested I post his csv file, so here it is.
--posted by TangoTiger at 03:23 PM EDT
Posted 5:39 p.m.,
March 10, 2004
(#1) -
Miko
Thanks to both MGL and Tango!
How come the adjusted stats changed to per 150 games as opposed to per 162?
Posted 7:16 p.m.,
March 10, 2004
(#2) -
MGL
How come the adjusted stats changed to per 150 games as opposed to per 162?
No particular reason. It's a "rounder" number? Actually, because it is closer to the number of games an average starter plays per year (I think), so that it is easier to "eyeball" relative value among starters...
Posted 7:36 p.m.,
March 10, 2004
(#3) -
MGL
A word of caution. If anyone wants to use a 4-year Superlwts total to "represent" a player's true talent (such as "I'd rather have so-and-so on my team than so-and-so," or "so-and-so is 'better' than so-and-so"), please at the very least regress his sample Superlwts to the league average of zero. It is simple. Use 400/(400+TPA) as the regression coefficient. For example, if a player has a 4-year Superlwts of +20 per 150 and he has 2000 PA, then the regression coefficient is 400/(2400), or .167. So regress the +20 16.7% towards zero, or simply mutliply +20 by 1-.167 (.833). So his true Superlwts is 16.7 rather than +20. This is critical when comparing players who have a large difference in their number of PA's and for players whose sample Superlwts far from zero (plus or minus). If you want to get even more accurate (as far as a player's true talent now or at some point in the future), you can do some kind of age adjustment by using the following rule of thumb: A player gains 4 runs per year (150 games) prior to age 26, loses 2 runs per year after age 26 and 4 runs per year after age 35...
Posted 11:25 p.m.,
March 10, 2004
(#4) -
tangotiger
To be more accurate, you should regress each component independently. No need to lump in fielding and hitting together. The hitting component will regress with a value of 200 and fielding with 420. I don't buy MGL's comment about using 400 overall. That just looks wrong.
On the other hand, doing it independently is kinda wrong too. After all, a player is not just a sum of his parts. KNowing how good a fielder is might be another thing to use in the regression for him as a HITTER. (And vice-versa. Possible.)
***
Btw, I have nothing to do with superLWTS. I only post the file as-is.
Posted 11:47 p.m.,
March 10, 2004
(#5) -
Darren
MGL, if we need to regress a player's SLWTs to find his real LWTS, why don't you just regress them before you publish them?
Or as Rob Reiner would say, "Why don't just make it a little louder but call the loudest one 10, rather than 11?"
BTW, you guys need to link to this on Clutch Hits. I would have missed it completely if not for a random mention over there. It's great stuff.
Posted 1:13 a.m.,
March 11, 2004
(#6) -
MGL
MGL, if we need to regress a player's SLWTs to find his real LWTS, why don't you just regress them before you publish them?
I present the precise, actual sample data, you guys can do whatever you want with it.
Tango, sure, you should regress each of the components differently, and yes, the regressions probably interact with one another - i.e., you should use a multiple regression equation. However, a more than adequate, Q&D regression can be done with the Superlwts total.
The "400" came directly from the y-t-y "r" for the total Superlwts. However, there was a bug in my program that compiled the regression data. After fixing the bug, the y-t-y "r" for players with at least 300 PA in back to back years is .612 (avg. of 507 PA). That gives us a regression of .388 for 507 PA's. Since that 507 PA's is only an "average," we should probably use like 520 PA's for the .388 regression. That gives us an "x" of 330, rather than 400. Does that look better?
For those who don't understand what the heck I am doing above, just substitute 330 for the 400 in the "regression formula" I posted in #3. So the amount of regression (towards zero) is 330/(TPA+330).
Tango didn't mention it, but if you also want to be more accurate with the regression, you can use something other than "zero" to regress everyone's sample Superlwts towards. Remember that the "zero" is the theoretical mean of the population from which the player comes. Since we already are adjusting for defensive position, that is already taken care of. There are other "populations" you can create for any given player, such as players who are big and strong, players who hit lefy or righty, players who were top prospects, players who were not (as long as whether they were prospects or not was not heavily influenced by their actual AA or AAA stats, since those are part of the Superlwts data), etc.
If you identify or create one of these, or some other, "populations," you can use the mean total Superlwts for that population, rather than "zero" to regress towards...
Posted 7:26 a.m.,
March 11, 2004
(#7) -
David Smyth
Does this mean that we're not going to get a 2004 Slwts "article", with the better formatting (by Tango?) for 2003 and 2001-2003?
Posted 2:02 p.m.,
March 11, 2004
(#8) -
MGL
David,
I submitted the file to Dan S. about 2 months ago and was hoping to have it up on Primer in a nice format. Finally, I asked Tango to post it. I probably should rewrite an "article" briefly describing the method for calculating each component, as a few things have changed since the original Superlwts article. If I have time, I'll do that and submit it to Dan and hopefully he can put everything up somewhere in a nice format. I don't know what takes so long. I feel like Superlwts is the best (by far) total evaluation "system" out there, especially after one does the regressions (or at least some kind of Q&D regression), so it should probably get a little more pub than just a blip on Primate Studies...
Posted 4:16 p.m.,
March 11, 2004
(#9) -
Jay Fan
Great work MGL. Question, now that the UZR and offence weights are combined, is the UZR calculated based the assumption that fielders are completely 100% responsible for balls in play, or is it discounted somewhat to account for the pitcher's responsibility (if there is any?). I'm sorry if I have asked a question debated previously on this site (I'm new), however the UZR looks high in relation to the offense side for some players. Thanks
Posted 4:53 p.m.,
March 11, 2004
(#10) -
Jay Fan
Sorry, I should probably give an example. For instance, Darin Erstad one season saved 56 runs with his glove. He saved more runs with his glove that season that AROD created with his bat during his MVP season last year (48). In fact of the 2327 seasons listed there from 2000 to 2003 Erstad saved more runs with his glove that season than any other player created with his bat in one season; with the exception of just 20 seasons. I know the research states this, but it seems hard to believe thinking about it.
Posted 8:45 p.m.,
March 11, 2004
(#11) -
MGL
Jay Fan, good questions. No, the UZR ratings are not "discounted" for whatever influence a player's pitchers have on balls in play. UZR IS adjusted for handedness, G/F ratio, etc. (read the articles on UZR). On the average, the variance of UZR is about half that of offense (mayebe a little more), I think. Remember that hitting and defense are pretty much independent, so that any player who happens to have his hitting lwts be around zero will likley have a UZR that is further from zero than his hitting lwts. That doesn't mean anything in and of itself. Also, there is no particular reason why hitting has to be more "important" (greater variance) than defense. It is, but it doesn't have to be. One of the things you get when you come up with a more "accurate" metric (like UZR comapred to ZR), is a greater spread in observed talent (assuming that there is a large spread in actual talent). That is a good thing. In fact, the "spread" of a "perfect metric" is always the spread (variance) of true talent PLUS the random variance associated with a sample of that talent.
As far as Erstad and his 56 runs saved one year, don't forget that there is always sample error associated with a sample UZR. Therefore almost any particular sample UZR (+56, -100) is theoretically possible. Given enough players and enough seasons, we will see some +100 and -100's, or whatever. There is a limit to what we could possibly see, as there are only so many balls a player can be "repsonsible" for in any one season (the tails of the curve do not extend infinitely). The +56 for one season doesn't mean much in and of itself (it is simply a one-year sample of his true UZR) other than it is likely that Erstad is a very, very good defender. If we want to estimate exactly how good, we can look at x number of years of UZR, regress, and come up with a reasonable answer.
Posted 4:57 p.m.,
March 13, 2004
(#12) -
arbitrage
MGL, Can you explain in any detail what "SB/CS" and "GDP" are? It seems to me that both of these things would be taken into consideration in the batting category assuming you are using linear weights to calculate a batting players value (i.e. the negative value associated with a GDP and CS and the positive value associated with a SB). But, I don't know exactly what "SB/CS" or "GDP" are and what they are measuring? As always, interesting stuff.
Posted 7:54 p.m.,
March 13, 2004
(#13) -
Silver King
Thank you - cool, cool, cool!
Posted 8:29 p.m.,
March 13, 2004
(#14) -
tangotiger
MGL sent me this last month with his file:
The defensive position listed for a player is his primary position
for that year, but in the defensive lwts category, his entire
combined UZR for the year is given. I know that's not right, but
it's close enough for government work.
The "position adjusted" categories are simply the unadjusted values
with the following adjustments made:
C +15
1B -11
2B +6
3B +3
SS +9
LF -11
CF -1
RF -8
DH -6
These are roughly derived from the 4-year Superlwts averages at each
position.
I removed the "moving runners over" category and essentialy included
it (at least as far as handedness, GB and GB rate are concerned) in
the batting lwts category. Since last year, I added the SB/CS
categories.
Posted 11:02 p.m.,
March 13, 2004
(#15) -
MGL
SB/CS is simply SB*.18 - CS*.46 (or something close to that). The interesting thing about net SB/CS runs, is that there is almost no y-t-y correlation (near zero) for all players (with a min number of PA's per year). I suspect 3 things are going on there. One, all players, fast, slow, medium, good or bad basestealers, tend to run themsleves into a break even or slightly negative net SB/CS runs total. Two, there is only a small window of time (at a certain age) where a player has a good net SB/CS runs total. Three, there are only a relatively few players who, for whatever reasons, are able to maintain for several years a positive SB/CS net run total.
SB/CS are not inlcuded in the batting lwts. Neither are GDP's. All outs are treated as single outs, although GB outs and FB outs are given different values. Also GB outs by a RHB are treated differently (given a different lwts value) than those by a LHB. A GB out by a LHB is less negative because the advance runners more often. FB outs are around the same for RHB and LHB (I think, off the top of my head). Also, ROE's are NOT considered outs in the batting lwts. ROE's are given a separate positive value (around the same as a single, a little more I think). There is a fairly signifciant y-t-y correlation for a player's ROE's even after their G/F ratio and handedness are taken into account.
GDP's are figured sepatately and are based on a player's number of GDP'S PER OPPORTUNITY (runner on first, less than 2 outs) above or below average.
The whole idea of Superlwts is to try and measure anything we can think of that a player "controls" and that adds or subtracts from his team's runs scored or allowed. As Tango says, each of these "things" has a different y-t-y correlation (the player "controls" more or less), so that if we want to use Superlwts to do a projection for a player (how valuable will he be in any future time period to an average team), or to estimate a player's true talent or value, we have to regress each "thing" separately and differently (using different regression coefficients). As I said in a previous post, a Q&D, and more than adequate, method of regression for projections and estimating true talent or value, is to regress the Superlwts total around "50% per 330 PA's" (see the formula in one of my above posts).
If there is anything of value and a player has control over that I may have missed, feel free to let me know, as long as it is not trivial...
Posted 12:47 p.m.,
March 14, 2004
(#16) -
Silver King
"GDP's are figured sepatately and are based on a player's number of GDP'S PER OPPORTUNITY (runner on first, less than 2 outs) above or below average."
Is that for all of his PAs in that situation (such that a high-OBA batter's high OBA will 'carry' him toward better-than-average in gdp/opp.), or is it for BIP, or outs, or nKo (non-strikeout outs) in that situation?
Am I correct that the gdp/opp. runs saved (or lost) is based on if he'd had a league-average number of opportunities during his real number of PAs? (Same question for baserunning runs, etc.)
What's the average # of gdps in N PAs, in recent years? I came up with about 12.8 per 650PA... Are the extra ones, below or above expected in the slwts column, valued at +/-.55 runs?
Further curiosity: I'd like to know the run values of A. an average nKo without a gdp, B. an average strikeout, and C. an average nKo plus a gdp. Is that knowledge you have handy? =) Or the differences between the values... I know how to operate Palmer's lwts formula and get the out value for a league, but I realize that this, call it o, is the 'stew' out value, mixing together the average proportions of nKo, k, and dp. None of those three is actually equal to o.
One thing that seems weird to me: you wrote in a past SLWTS article that a dp is .55 worse than a single out with a runner at first. (Does that mean that the difference between a an average solitary nKo and an nKo plus a dp is simply .55?) But a cs is 'only' -.45. How can the dp out be worse than the cs? The caught stealing is usually a guy who was on first, but sometimes he's on second which would be more precious, and surely the average guy who would attempt a steal is faster than than the average baserunner caught in a dp (who is either ordinary or more likely (?) worse), so he has a slightly better chance of scoring. Hmm. Even worse, some cs occur with nobody out, whereas with each dp out, there's at least one other out (the semi-simultaneous one).
I appreciate not only your work, but also the clarity with which you usually step the reader through your ideas and findings. Thanks!
ps: In the wake of that (heartfelt) compliment, lemme toss in this: how are the chances lookin' that eventually (like later this year) we'll get to see further into the past with uzr and slwts?
Posted 5:43 p.m.,
March 14, 2004
(#17) -
MGL
Lemme see if I can scrape up some numbers for you. If you download the A.S.S (Astros Daily) database and their software (or the retrosheet data), you can compute any of these numbers you want.
There are about .356 dp opps (runner on first, less than 2 outs) per game. 24.9% of the opps result in a GDP. I use -.567 as the additional value of the DP (difference between a DP and single out).
The way a player's GDP lwts is caluclated is to simply take the difference between his expected GDP given his number of opps and his actual GDP, multiplied by -.567, prorated to the average number of opps per 150 games. The player's OBA or anything else about him has nothing to do with it. I'm not even sure what you mean. Of course, if a player plays on a team and/or is in a lineup slot where the players ahead of him get on base more or less often than average, he will have greater or fewer number of opps such that his positive or negative GDP Superlwts value per 150 will actually be a little "higher." That is the essence of Tango's "custom lwts," and would apply to Superlwts as well.
Here are the lwt values of the various events for 00-03 in the NL:
PA 399,795
Avg RE .512
All out, no sac -.271
All out, no sac, no err -.283
out, no K, no sac -.266
out, no K, no err, no sac -.283
K out -.284
GDP inc. bunts -.822
GDP opp, GB out, no DP -.268
out, no DP, no K, no bunt -.255
GB out, no bunt -.265
FB out, no bunt -.262
LD out, no bunt -.288
GB out, no bunt, no err -.293
FB out, no bunt, no err -.266
LD out, no bunt, no err -.296
GB -.095
FB -.004
LD .357
Hit val, no bunt .646
Hit val, no bunt, no hr .540
GB hit, no bunt .477
FB hit, no bunt 1.023
FB hit, no bunt, no hr .691
LD hit, no bunt .577
LD hit, no bunt, no hr .545
GB err, no bunt .478
FB err, no bunt .608
LD err, no bunt .560
Non-int BB .301
HBP .328
BB+HBP .304
IBB .157
ROE (no sac) .492
S .452
D .764
T 1.065
HR 1.394
Suicide squeeze att -.181
Non-squeeze .002
Sac first att -.160
Sac first/second att -.092
Sac second att -.108
No Sac first .014
No Sac first/second .038
No Sac second -.008
SB .174
CS -.447
Posted 10:11 p.m.,
March 14, 2004
(#18) -
MGL
I'm using too high a number (too negative) for a marginal GDP. The -.567 should be like -.466, as the value of a single out with a runner on 1st and no DP is -.356. (These numbers are all NL 2000-2003.) I was using the difference between the GDP out (-.822) and value of the GB single out (-.268) as the value of a marginal GDP, rather than the difference between a GDP out and all single outs (with a GDP opp). So my GDP Superlwts numbers are around 20% too high (negative and positive).
Also, keep in mind that the lwt values (of all the events) are based on the average RE's of the before and after bases/outs states. IOW, it doesn't take into consideration that SB's are attempted more often by the faster baserunners and from certain lineup slots. As I said, it just uses the average RE's of the before and after states, which isn't quite right, but is close enough. I definitely don't use the actual runs scored after a certain event (SB or CS) and substract that from the "before RE's," although I suppose I could and that it might be more accurate...
Posted 3:12 a.m.,
March 15, 2004
(#19) -
Michael
MGL and Tango just great stuff. I agree with David #7 about the need for it to be presebted in a better format. I am going to go blind willingly looking at this stuff and it IS the best overall system out there. I understand how busy you guys are but anything you could do to help my eyes would be appreciated.....if we all need to rough Dan up let us know..
JK
Michael