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WAR, What is it good for?


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56. Larry Walker (17) 72.6 L

57. Harry Heilmann+ (17) 72.1 R

58. Derek Jeter (20) 71.8 R

59. Rafael Palmeiro (20) 71.6 L

60. Johnny Mize+ (15) 71.0 L

61. Bobby Grich (17) 70.9 R

62. Frankie Frisch+ (19) 70.4 B

Ron Santo+ (15) 70.4 R

Alan Trammell (20) 70.4 R

65. Barry Larkin+ (19) 70.2 R

Bobby Wallace+ (25) 70.2 R

67. Scott Rolen (17) 70.0 R

68. Gary Carter+ (19) 69.9 R

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56. Larry Walker (17) 72.6 L

57. Harry Heilmann+ (17) 72.1 R

58. Derek Jeter (20) 71.8 R

59. Rafael Palmeiro (20) 71.6 L

60. Johnny Mize+ (15) 71.0 L

61. Bobby Grich (17) 70.9 R

62. Frankie Frisch+ (19) 70.4 B

Ron Santo+ (15) 70.4 R

Alan Trammell (20) 70.4 R

65. Barry Larkin+ (19) 70.2 R

Bobby Wallace+ (25) 70.2 R

67. Scott Rolen (17) 70.0 R

68. Gary Carter+ (19) 69.9 R

One of these guys took 20 years and not 17.

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Just means that WAR is more valuable in a segment that it may be over the course of a career. If you want to compare a group of guys from 2012-2015, it's still useful, as long as that group of guys were all in the majors and healthy during that time.

I can't say I fully understand WAR, but I don't blow it off or undervalue it. Really, I think single-season or short-term segments are where it's most valuable.

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Just means that WAR is more valuable in a segment that it may be over the course of a career. If you want to compare a group of guys from 2012-2015, it's still useful, as long as that group of guys were all in the majors and healthy during that time.

I can't say I fully understand WAR, but I don't blow it off or undervalue it. Really, I think single-season or short-term segments are where it's most valuable.

I think Grich was as good as Jeter. Myself.

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The other day I was looking at the fWAR list, I believe yours is rWAR. In fWAR 100% of eligible position players (discounting the very recent PED suspects) over 70 are in. 2/3rds of those between 60-70 are in. And about 50% from 55-60. I'd assume a decent, declining correlation as you step down to Ray Schalk at 22.

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I think Grich was as good as Jeter. Myself.

I agree and I was trying to figure out from the original post what the intention was of the bolding. Who's the one that doesn't belong?

Grich had a 125 career OPS+, while Jeter's was only 115

Grich was a far better defender (+16 dwar career), even though his move to short cost him a significant amount of dwar, while Jeter had a dwar of -9.7 career.

This is a case where WAR might not be the best comparison, since the difference in time played is so great, but using WAA, Grich turns a .500 team into a .521 team over the games he played and Jeter bumps a .500 team only to .510.

Offsetting Grich's superior performance is Jeter's longevity (12,600 ABs to 8,200 for Grich).

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I agree and I was trying to figure out from the original post what the intention was of the bolding. Who's the one that doesn't belong?

Grich had a 125 career OPS+, while Jeter's was only 115

Grich was a far better defender (+16 dwar career), even though his move to short cost him a significant amount of dwar, while Jeter had a dwar of -9.7 career.

This is a case where WAR might not be the best comparison, since the difference in time played is so great, but using WAA, Grich turns a .500 team into a .521 team over the games he played and Jeter bumps a .500 team only to .510.

Offsetting Grich's superior performance is Jeter's longevity (12,600 ABs to 8,200 for Grich).

It pains me to defend Jeter, but that also completely ignores the postseason. Which is arguably many times more important on a per-whatever basis. Jeter had 158 games in the postseason where he played almost exactly as well as he did during the regular season. Jeter was a four-win player per 150 games. You could argue that his post season career was worth 10 or 15 or more wins above his 71 fWAR.

Grich played before the current playoff format, but he hit .182 in 24 postseason games. It's hard to argue that added anything to his resume.

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Question about WAR: does it take into account when certain stats (a run batted in, steal whatever) occur? I would think it should, as a player that has a knack for hitting homers late in close games is more valuable than someone that only hits homers against mop up relievers up or down by 5 runs.

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Question about WAR: does it take into account when certain stats (a run batted in, steal whatever) occur? I would think it should, as a player that has a knack for hitting homers late in close games is more valuable than someone that only hits homers against mop up relievers up or down by 5 runs.

WAR makes no account for these things because overall it has been shown that professional players do not have a knack for such things, and that things like RBIs are too influenced by situation. There are stats that track Clutch situations if you'd be interested.

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WAR makes no account for these things because overall it has been shown that professional players do not have a knack for such things, and that things like RBIs are too influenced by situation. There are stats that track Clutch situations if you'd be interested.

R WAR

Version 2.2, March 2013

Based on discussions with FanGraphs and others, we decided to drop the replacement level to .294 from .320. This means that 2013 MLB has 1000 WAR in the entire major leagues. This was applied retroactively, so that it was applied to all previous AL, NL, and NA seasons. Other Major Leagues (AA, UA, PL, FL) were maintained at the same level relative to the NL.

After the positional adjustment was applied we forced the major league average to be zero across the league.

A small amount of smoothing was done to transition between decade-long league-vs-league replacement levels.

Version 2.1, May 2012

After launching version 2.0 on May 4th, we immediately became aware of an issue that had concerned us, but we thought we still had right. Pitchers were being overvalued due to a runs-to-win estimate that broke down for extreme performances. A stingy pitcher drives down the runs per win, but not to the degree we were showing.

A major change to runs-to-win calculation. See our Runs to Wins Page for a full explanation. We now handle runs-to-wins calculations in an exact rather than an estimated way.

With the change in runs-to-wins calculation, we can now display Wins Above Average, a related win-loss % and a related win-loss% for 162 games played.

Leverage Index adjustment is now only applied to relief pitchers.

Leverage Index used is now the LI at the time the reliever entered the game rather than the average LI for all of their plate appearances. This is weighted by number of batters faced.

Converted Offensive WAR from afWAR back to oWAR. Note that oWAR + dWAR now double counts position, so adding them will not give WAR.

The adjustment for the difference in league starter and reliever ERA has been moved to the calculation of league average rather than the league replacement level.

BUG: Fixed a park factor bug. Pitcher opponent strength was not neutralized, so a park factor was being applied to a non-park adjusted number. Now the pitcher opponent strength is converted to a neutral environment, averaged for all opponents and then park adjusted based on a custom park factor for each pitcher based on the exact parks they pitched in.

Some feedback of version 2.0 we incorporated: Inside the Book and its readers helped immensely with the runs to wins issue.

Version 2.01, May 2012

We made a minor change converting oWAR to afWAR (or average fielding WAR). This has been rolled back and is not in place now.

Version 2.0, May 2012

Previous to launch of 2012 WAR numbers, we undertook a top to bottom evaluation of our WAR numbers and added a number of improvements.

Switch from BaseRuns for batting to an advanced wRAA metric.

Folding ROE, infield singles, SO vs. Non-SO into wRAA.

Excluding pitchers' hitting and averaging by league rather than year from the league averages for wOBA and wRAA.

Estimation of CS numbers for leagues they are missing.

Use of Baseball Info Solutions Defensive Runs Saved from 2003-present (in our view the most advanced defensive metric).

Use of a player-influenced runs-to-win conversion for both batters and pitchers based on PythagenPat.

Use of a player-specific park factor for pitchers weighted by actual appearances in each park.

After a preliminary WAR calculation, we fine-tune the replacement level on a playing time basis, so the total WAR in each league is very consistent year-to-year.

dWAR now contains the position component as we feel this better captures player defensive value. In our view, even a poor defensive catcher is likely equally valuable to a good defensive first baseman in terms of team defense.

Version 1.0, pre-May 2012

Sean Smith produced the original framework for the site and until May 2012 we used his numbers and methodology in all locations. We still use his replacement level and position levels, but we have changed much of the remainder of the system.

The Concept of Replacement Players

Average is a well-defined concept. You sum up all of the observations and then divide by the number of observations. We compute averages every day.

So why don't we compute Wins Above Average rather than Wins above Replacement? When computing the value of a major league player, average is a poor baseline for comparison. Average players are relatively rare and can be expensive to acquire. Average players don't make the league minimum. Plus, not all average performances are equal. A team would pay much more for 200 league average innings than for 50. When a star player is injured, they are rarely replaced by an average player -- usually their replacement is much worse.

That last point is our premise here. Average players are relatively rare and difficult to obtain. Replacement level players, by their very definition, are players easy to obtain when a starter goes down. These are the players who receive non-roster invites at the start of the year, or the players who are 6-year minor league free agents. Baseball talent among the population is generally distributed normally, but only the very right-end of that curve plays professional baseball.

http://www.baseball-reference.com/about/war_explained.shtml

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Replacement, not average.

The idea behind the WAR framework is that we want to know how much better a player is than a player that would typically be available to replace that player. We start by comparing the player to average in a variety of venues, then compare our theoretical replacement player to the average player and add the two results together.
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WAR makes no account for these things because overall it has been shown that professional players do not have a knack for such things, and that things like RBIs are too influenced by situation. There are stats that track Clutch situations if you'd be interested.

Right, that quickly becomes a philosophical discussion. There are individual differences in clutch performance, but they're essentially indistinguishable from random noise. If you ran a simulation of 140 years of MLB history and didn't include any adjustments for clutch ability whatsoever the results would be basically identical to what's observed in real life. Even the few good studies that seemed to identify an ability such as this concluded the impact was very small, with less of an impact than platoon splits or park.

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Right, that quickly becomes a philosophical discussion. There are individual differences in clutch performance, but they're essentially indistinguishable from random noise. If you ran a simulation of 140 years of MLB history and didn't include any adjustments for clutch ability whatsoever the results would be basically identical to what's observed in real life. Even the few good studies that seemed to identify an ability such as this concluded the impact was very small, with less of an impact than platoon splits or park.

519jZNUDVtL._SX317_BO1,204,203,200_.jpg

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