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Chris Dial offers his OPD metric (off, def, pos, no baserunning). Since Google Docs (and Edit Grid) are now blocked at the office, I can’t make a more informed opinion on the results. So, I will just respond to the comments of the article. The first is from Chris Dial:
Here are three AL players:
BA OBA SLG
.223 .326 .393
.225 .319 .400
.275 .326 .400Some people still believe that if you have two players with equal OPS, but one has a higher BA, that the one with the higher BA is more valuable. They believe this despite the fact that more sophisticated run estimators show them to be of nearly identical value, with an edge for the lower BA if anything (with the caveat that we are considering a normal environment in the modern major leagues). This is illustrated by these player’s RGs, which are 4.45, 4.51, and 4.43 respectively. Not that I intend this to prove anything, but the player’s (R + RBI)/Out are .32, .33, and .31 respectively. (R + RBI - HR)/Out are .29, .28, .27.
You should always remember that if you have identical OPS but varying BA, the player with the lower BA has a better combination of secondary skills. Incidentally, the players are Brandon Boggs, Gary Sheffield, and Billy Butler.
We had a discussion about this in another thread. I decided to run some scenarios through my sim.
Justin gives us a best-of-breed. He also applies my revised positional adjustments, which, as of today, are these:
+1.25 C
+0.75 SS
+0.25 2B/3B/CF
-0.75 LF/RF
-1.25 1B
-1.75 DH ... Should be -2.25, but then I add in 0.50 for the DH penalty of how hard it is to hit off the bench.
Colin provides his data for easy access, along with his intro article.
Here is my second stab at trying to describe Situational Wins. (My first stab, less technical, easier to read, a few days earlier is here.) Please provide comments, especially as it pertains to readability. I will then make the necessary modifications, and I’ll submit it to THT for publication for the general public to consume.
Depends on your definition of “superstar” of course. Then again, no matter what the definition, we know that Pujols is and Bloomquist is not, so that does not necessarily preclude a discussion or an analysis.
Here’s one thing everyone can try:
I posted this at Primer:
I’m not discussing whether WPA/LI is appropriate or not for Cy Young (I would lean toward not). I’m asking a more general question about what Balrick thinks that WPA/LI is trying to do.
***
Thank to fret for bringing up that game.
In that particular inning, the WPA totaled -.049 wins. Indeed, every scoreless top of the half will give the defense -.049 wins in WPA, regardless whether you had 3 or 6 batters. People who like just runs like that. Those who care about number of runners allowed don’t.
WPA/LI for the game in question for the top of the 1st was +.019. (Plus is bad for the defense.) What WPA/LI does is treat each PA in isolation, unleverages WPA so that it scales the performance so that each PA is weighted at exactly 1.0, and weights each event (walk, homer, strikeout, etc) with respect to the game state (e.g., K are more impactful with runner on 3b and less than 2 outs than otherwise).
Is it necessarily a bad thing that a team that allows 2 runners out of 4 batter to reach base to show that they are below average (even though they got out of the inning scoreless)? I don’t think it’s necessarily a bad thing. I don’t know that it’s necessarily a good thing.
But to dismiss WPA/LI would be preferable with reasoning behind it.
WPA/LI is exactly perfect for a hitter, if you believe that it matters when a hitter strikes out with runner on 3B and less than 2 outs, and you don’t think that it’s just another out. That is, you believe that the batter and pitcher realize that that situation requires a fairly strong change in approach. Only WPA/LI will give you what you need, under this belief premise. Linear Weights by the 24 base/out states is a close second.
WPA/LI is not as good for a pitcher, since a pitcher is his own team, and each PA should not necessarily be treated as if they are as impactful as any other PA. WPA/LI forces each PA to be worth exactly 1.0.
There are different ways to do Linear Weights. You can do it by men on base, as SG is doing here, or by the base/out states, or by game state (inning, score, base, out, and shown at Fangraphs as WPA/LI). They all tell a story. The nice thing about the men on base one is that it’s only 8 lines per player, which is a heckavu lot easier to swallow than 24 or the thousands by game state.
I’m wondering, under the “less is more” scenario, construct the 24 base/out set into something more manageable. For example, we can have these states:
1- man on 1B, 3B (runner on 2B optional), less than 2 outs
2- man on 3B (excluding above), and less than 2 outs
3- man on 1B, 2B (excluding all the above), less than 2 outs
4- man on 1B (excluding all the above), less than 2 outs
5- man on 2B or 3B (excluding all the above)
6- man on base (excluding all the above… when I think just leaves me with man on 1B, 2 outs)
7- bases empty less than 2 outs
8- bases empty 2 outs
Do these make sense in terms of trying to segregate based on how the batter/pitcher might change his approach to the base/out state? This is my reasoning for those 8 categories:
Some good stuff from Poz. I like these quotes:
Or you can look at the Baseball Reference neutralized statistics for the two men through age 34:
Rose: .323/.392/.449
Jeter: .315/.386/.458Here’s a fun Rose statistic that tells you something: Rose is second all-time in doubles, and he led the league in doubles five times. But the thing that strikes a chord is that he never led the league in doubles BEFORE he turned 33. ... There are three men who hit 40 or more doubles three times after their 35th birthday. They are all Hall of Famers and all-time hustlers — Tris Speaker, George Brett and Craig Biggio. … Pete Rose did it four times.
Poz takes Rose over Jeter, and Allen Barra takes Raines over Rose. And I’ll complete the cycle and take, on a whim Raines over Jeter.
Good post by Peter:
My preliminary studies have shown that if I define three categories: intentional walk, strategic walk, and non-strategic walk, then I get more accurate results with run values set as .10 for IBB, .27 for SBB and .33 for NSBB with about 25% of the non-intentional walks falling in the SBB category.
The idea here is accurate, and really represented by win values of the walk.
We can see a more basic version here:
http://tangotiger.net/RE9902event.html
Where we only consider the base/out state (we should also consider inning/score).
On average, the run value of the walk is roughly 10% more extreme than the out, and of the opposite sign. So, if the run value of the out is -.30 runs, then the run value of the walk would be some +.33 runs.
If we go to the above link, we can see that the run value of the walk with bases empty and less than 2 outs is some 50% higher than the run value of the out. And with 2 outs, it’s some 10% higher. So, we can say that a walk in the less than 2 outs, bases empty situation that those are not strategic walks.
The more basic situation is the one with 1b open (runner on 2b) with 1 or 2 outs. In those cases, we see that the run value of the walk is some 40 to 50% LOWER than the run value of the out. These we could classify as “strategic” walks, especially if they were given to good hitters.
So, I agree that there are nuances to the run value of the walk, and calling them as Peter is doing is a great way to make the point, and to show which pitchers/batters are using the strategy. But, overall, the run value of the walk remains what it is.
I’ve had a very interesting email discussion with Clay, which I will reproduce here. The quoted parts are him. I also have to say it was very pleasant, as are all my discussions with him. He certainly seems willing to make corrections where needed, and offer alternate solutions.
BP has two measures that do similar things. One is called VORP, by Keith Woolner, and another is called RARP, by Clay Davenport. They both exist because BP was allowing its analysts to develop their own metrics, which is a good thing. According to BP’s glossary, VORP is “The number of runs contributed beyond what a replacement-level player at the same position would contribute if given the same percentage of team plate appearances” and RARP is “A statistic that compares a hitter’s Equivalent Run total to that of a replacement-level player who makes the same number of outs and plays the same position”.
First, a big thanks to BP for making the data so accessible. And, they are pretty good on name matches, making my life alot easier. There were only some 40 or so names out of 912 that I had to match manually.
The total VORP, as of today, is 4436 runs. And for RARP, it is 4735 runs. This is based on around 154650 PA, which means that per 700 PA, we have this:
VORP: +20.0 runs
RARP: +21.4 runs
As you can see, both have a very similar replacement baseline. Indeed, this is a very common baseline. MGL uses +19.4 runs, and I use (roughly) +19.8 runs.
The question is if either measure shows much difference. This is the 10 guys that VORP likes more than RARP:
Colin looks like he’s going to do what I’ve been meaning to do for years, and what others have been asking for a long time: look at run creation at the inning level, so that we can get far more extreme environments than simply looking at seasonal data or even game-level data. The article I am linking to is a preamble to his work next week. I’m looking forward to seeing the results.
Adam Dunn is what WPA/LI was invented for. In 4500 PA, his wins added over an average hitter, given the base/out inning/score opportunities presented to him was +18 wins.
The most similar player to Adam Dunn in terms of OBP, SLG, and PA is JD Drew. In his career, Drew is +25 wins.
Three other players with less PA are: Teixeira (+12 situational wins), Bay (+14 wins), and Miguel Cabrera (+20 wins). If you add up their totals (+46) to Drew’s (+25), and take 30% (to align them to the same number of PA as Dunn), you get +21 wins.
I think there may be something to the fact that Dunn is not a good situational hitter (or that his skillset doesn’t lend itself to good situational hitting).
He’d definitely be a good case study.
Here is the comparison line, as of today:
+18 situational wins, .247 / .380 / .519 Dunn
+21 situational wins, .290 / .382 / .522 Dunn’s top 4 comps (Tex, JD, Miguel, Bay)… situational wins prorated to Dunn’s PA.
UPDATE: This blog entry (not an article) has been linked from several places, and there are questions from non-LWTS followers about what the weights should be. One place to find them is the last line of this page. Had I intended to write this as an article, I would have been more complete in my description. I apologize to those who stumbled along here for the first time. Basically, anyone coming to this blog is walking into the middle of a conversation. Feel free to interrupt and ask a question.
***
Baseball Prospectus undervalues walks. By how much? As much as OPS. Don’t believe me? Let me walk you through the steps:
Your reliever gets an out. Your chances of winning go up. Your reliever allows a runner on. Your chances of winning go down. You add up the deltas of all the times that your chances went up, and you add up all the deltas of all the times your chances went down. Call the former “Win Advancement” (WA) and call the latter “Loss Advancement” (LA). WA+LA is GA (Game Advancement).
If you start the game at zero, you are marching toward 1 Win or 1 Loss. In a typical win, the pitching team will accumulate 1.8 WA and 0.8 LA. The difference in WA and LA, for every win, is always 1.0. Always. That is, on your march toward a win, you’ll accumulate some good things and some bad things. And in a win, you’ll accumulate alot more good things than bad things. The difference, in a win, will always be +1. Similarly, in a typical loss, the pitching team will accumulate 0.8 WA and 1.8 LA, with the difference always being -1.
So, in an average game, you have 1.3 WA, 1.3 LA, 0.5 wins, and 0.5 losses. The WA and LA capture the ebb and flow of the game, on your march toward the win or loss of the game. There is, on average, some 0.8 “wasted” WA and 0.8 “wasted” LA per game (2.6 GA minus 1 game). In order to align WA and LA to W and L, simply subtract the waste (average of 0.8 wasted advancements on each side) from the total accumulation in each game (average of 2.6 GA) from each of WA and LA.
Before we talk about relievers, let’s look at the last generation’s four greatest starters:
Bill James responds:
Q: Why do you prefer RC to linear weights for assessing individual hitter performance? Asked by: WTE
A: The essential problem with Lawootas is that they start everybody out in the middle and then move players up and down. This is totally contrary to the nature of baseball, which is that you start out at zero and build up. All of their other malfunctions stem from this central failing.
Doomed to repeat history are these three posts. I want to highlight these posts because while it tries to make a good effort to make a good estimate, the author doesn’t provide the proper framework to test his work. It must be done against realistic averages, and not simply looking at that someone goes 1 for 4 or some sh!t like that. I provided the proper framework last year. I’m going to make an authoritative statement so that it leaves no doubt where I stand: you must use the plus 1 method (or differentials). Anything else that anyone does is almost certainly mathematical gymnastics that gives sabermetrics a black eye and proves that there are damned lies and statistics.
Anyway, using the plus 1 method, here are the corresponding LWTS values, if we force the out value as minus .28 runs, for 3 different metrics:
Mar 22 02:00
Pre-Introducing Batted Ball FIP
Mar 22 01:11
Mike Silva on J.A. Happ
Mar 21 18:56
Morgan Ensberg has parental advice
Mar 21 18:17
MGL and Tango Interviews
Mar 21 12:03
Statistical Significance, or the reason that mathematician Ron Fisher is on MGL’s “On Notice” Board
Mar 21 08:18
Yahoo fantasy sabr league
Mar 20 21:32
BDB Database (MS Access)
Mar 20 15:42
Quickest ejection in MLB history?
Mar 20 10:20
Optimizing the batting order: Phillies and Yankees
Mar 20 02:31
Will Mariano Rivera save only 22 games this year, and with a 3.53 ERA?
THREADS
March 21, 2010
MGL and Tango Interviews
March 19, 2010
Lineup simulator
March 19, 2010
Goalies most involved in their own team’s goals scored
March 19, 2010
Morgan Ensberg has parental advice
March 19, 2010
B-R.com now has Win Probability
March 19, 2010
Will Mariano Rivera save only 22 games this year, and with a 3.53 ERA?
March 19, 2010
Arbitration and bias
March 18, 2010
A very good interview with Bill James, by Geoff Baker, the Seattle writer
March 18, 2010
Another brilliant quote…
March 18, 2010
Horizontal v Vertical Power
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