To the extent that this is a criticism it's extremely easy to discuss when a specific case actually arises (and generally, thee really isn't).
Suggesting the baby needs to be thrown out with the bath water is a very inhumane approach to analysis akin to using a butchers knife to perform open heart surgery.
"This isn’t stats vs scouts - this is stats and scouts working together, building an organization that blends the best of both worlds. This is the blueprint for how a baseball organization should be run. And, whether the baseball men of the 20th century like it or not, this is where baseball is going."---Dave Cameron, U.S.S. Mariner
I only remember one time (can't remember specifics) where a poster tried to sneak a brWAR into a post simply because it fit his case. Other than that, most have been real good about either citing which WAR is used, or sticking with fWAR, which is generally the most commonly accepted WAR.
I did mention that I hope going forward the 2 websites will be on the same page as well, and I was specifically relating to UZR. I'm sure advances will be made in fielding metrics which in turn will lead to a more zeroed in WAR. This will allow the 2 sites to have the opportunity to "one-up" the other yet again, unless a deal has been made that they will agree on any changes - I hope that such a deal has been made.
The one WAR/UZR critique that has always bugged me is that its variance necessarily implies the metric is terribly flawed, that the variance must be a function of measurement error as opposed to performance variance.
For example, I see no reason why a guy can't be a +10 fielder in half a season. I think it's quite unlikely that it's a rate of performance that is sustainable over big samples, but people seem to forget that a half season of defense is like a month of hitting. We wouldn't say that OPS is a flawed stat because a guy put up a 1.400 OPS month, but when a guy does the equivalent of that in UZR, people freak out.
And of course, that's not to say UZR is necessarily right/accurate either, just that the critique described above is overplayed.
Last edited by RedsManRick; 03-11-2013 at 04:17 PM.
Games are won on run differential -- scoring more than your opponent. Runs are runs, scored or prevented they all count the same. Worry about scoring more and allowing fewer, not which positions contribute to which side of the equation or how "consistent" you are at your current level of performance.
Or even in the case of a season, if a guy has a .390 BABIP, it still happened. It isn't likely to happen again, and it may not be his true skill level, but for that time period, he did it. If a guy is usually a neutral defender, but then busts out a +15 run defensive season, again, people freak out and call shenanigans.
My biggest problem with WAR is when oWAR and dWAR are summed to make a total WAR value. I refuse to believe that dWAR is as important as oWAR.
The war (probably) won't be over until the "tude" about metrics is toned down
http://www.sbnation.com/longform/201...ecap-ssac-2013
http://www.baseballprospectus.com/ar...rticleid=19853If there's genius on display at Sloan, it's this: When scouts or coaches or old school GMs get something wrong, it's an example of traditional scouting methods failing. When analytics get something wrong, it's "randomness" that you can't control. A small part of a much bigger process, and teams and fans should trust that process until they get a better outcome. Any skeptics must be simple-minded conservative talk radio reactionaries, eating giant chocolate chip cookies.
Speaking of which, every afternoon at Sloan features a buffet of giant cookies. Chocolate chip, peanut butter, and oatmeal. They are delicious.
If you're reading Baseball Prospectus, you're probably tempted to reflexively say "Sharp is wrong." I was too. But, if we're going to be intellectually honest, this critique deserves a more thoughtful answer. One thing that sabermetrics can pride itself on is that we've made great strides in analyzing baseball while minimizing the biases that go along with "the human element." If we're going to be good scientists, we can't let this bias bring us down. Otherwise, we're just cheerleaders for spreadsheets.
There is a lot of randomness in baseball. Balls take weird hops when they hit a pebble. Wind air currents push a ball just inside the line for a double, rather than a loud foul ball. Teams have years where they win 80 percent of their one-run games. How much can we blame on random noise when we (as a group) don't get something right? How many of our correct predictions are the result of random noise breaking our way, rather than our own brilliant ideas? And is there room to say that "old school" methods (to the extent that the stereotype of the scout going purely by gut feel even exists any more) might have some credence, but might also have to deal with the problem of bad luck as well? There isn't a way to directly answer these questions fully, but the questions themselves raise some important issues.
Consider that almost no one, sabermetrically inclined or not, predicted the Orioles or A's (see, Moneyball works!) to be even close to the playoffs last year. Everyone missed badly on those two, except for a few optimistic fans. Sure, the Orioles caught some very lucky breaks along the way, and if the season were played again a few million times over in parallel universes, I don't think that they would get that lucky again very often. But here I am blaming luck for something that I didn't get right. Then again, had one of my models predicted the A's as AL West champions, I would certainly point to this as confirmation of my awesome powers of awesomeness. This despite the fact that the model most likely to have produced that prediction would have been for me to have chosen a team from the AL West out of a hat and proclaimed them to be my pre-season favorite.
I agree with what you both said, Rick and Doug. But there are "major" advancements coming down the pike in terms of fielding metrics, right? (If I'm not mistaken you have mentioned them Doug, even saying that teams have access to them now)
Gotta think they will eventually fall into Fangraphs' hands.
Not to divert the discussion, but you describe the way I feel about RBI's and how they should be used to describe what happened.
RBI's do not project forward and are team dependent. But if one year 2 players come up with 200 (made up that number) men on base (distributed equally) over the course of a season, and one guy knocks in 80 and the other knocks in 60. The first guy should start off with a 2 WAR advantage over the other if you ask me. (Maybe it's not that simple but hopefully you catch my drift). I get that discussions are usually talking about what a player is going to do going forward, and RBI's shouldn't be used. But I find it odd that RBI's/% of runners knocked in are kind of scoffed at in terms of what happened in the past.
Yeah, the Field F/X system is already in place, but from what I have heard, it isn't likely to see the public. I can't say for certain why, but it is a little disappointing that we don't have at least some access to either Hit F/X or Pitch F/X data. While Sportsvision and even MLBAM did outstanding things with Pitch F/X, the public, the fans, did a whole lot as well to further the product and improve it both in terms of the usefulness to the casual fan (pitch identification for example) as well as how the data could be used to determine the values of pitches thrown and well, a whole lot of other things. Many teams went out and hired guys off of the internet who were Pitch F/X gurus and had them shut down their online presence/delete their work. We simply aren't getting that kind of stuff with the other data and I have to wonder if we aren't going to be missing out on that kind of stuff because of it. Also, I want to check out the data myself. I am selfish like that and would love to parse through it like I can the Pitch F/X data.
That all really depends though. Who were the base runners? How was guy A pitched versus guy B? Did one guy draw a whole lot more walks than the other, thus negating his actual chances despite both having 200 runners on? Did one guy play in GABP and the other in Petco, where the pure HR factor could lead to quite a difference in true chances despite what appears to be the same number of chances? Did one guy have his 200 runners spread out over 150 at bats versus the other guy have his spread out over just 110 (they could theoretically both have had the exact same line of say .300/.400/.500 and one guy would have a whole lot more RBI).
As someone who often makes sabermetric-based arguments, I have to say that this sentiment is actually pretty rare, at least on redszone:
Just as some critiques above have been described as overplayed, the notion that if someone makes a strong argument that person is also declaring it as fact is more overplayed than "Sweet Home Alabama" is on a jukebox in a redneck bar in Tuscaloosa.Any skeptics must be simple-minded conservative talk radio reactionaries, eating giant chocolate chip cookies.
Truthfully, there is much more ad hominem directed at sabermetric arguments than there is in the other direction. This very thread wasn't ten posts old before someone felt the need to lob an unprovoked insult toward people who favor WAR.
"This isn’t stats vs scouts - this is stats and scouts working together, building an organization that blends the best of both worlds. This is the blueprint for how a baseball organization should be run. And, whether the baseball men of the 20th century like it or not, this is where baseball is going."---Dave Cameron, U.S.S. Mariner
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