Matt Swartz is rolling out a 5-part series this week on his updated SIERA metric at FanGraphs. (Part 4 was published today. Part 5 will come tomorrow.) Basically, SIERA appears to be a slight upgrade over xFIP because it does a better job of incorporating the small room for statistical control over HR/FB, GB/FB, and LOB% that some pitchers have shown. Also, it better factors in run environment.

It's a lot of reading and numbers heavy, but I highly recommend reading this to anyone interested in seeing the latest on where statistical study of baseball is in 2011. This isn't just a useless exercise in juggling numbers. It's a solid advance towards better understanding and evaluating the game.

Part 1 ("Pitchers with high strikeouts have low BABIPs")
Part 2 ("Unlocking underrated pitching skills")
Part 3 ("Differences between xFIP and SIERA")
Part 4 ("Testing")
Part 5

Shocking to me that FIP and xFIP are already appearing outdated and are no longer fashionable.

Shocking to me that FIP and xFIP are already appearing outdated and are no longer fashionable.

That's called progress.

ERA ------------------------------------>FIP ----->xFIP--->SIERA

For example:

Table 1. Estimators' RMSE of difference between Park-Adjusted ERA (IP>=40 both years), Un-weighted, 2009-2010

SIERA: 1.083
xFIP: 1.139
FIP: 1.180
tERA: 1.220
ERA: 1.322

So you and Jamey Newberg can stick with ERA if you'd like... but you're using an inferior measuring stick.

Doesn't Siera factor in if a guy has avg luck?

That of course assumes that the park adjustment in Park Adjusted ERA isn't another poorly thought out and calculated stats. Most Park adjustments are. I don't believe you can get to a good number with a linear analysis, one size fits all park adjustment, and most park adjustment schemes I've seen are flat silly.

I am a stat junkie, but I know a pitcher or a ball player when I see one. All these new metrics? I got no use for.

That of course assumes that the park adjustment in Park Adjusted ERA isn't another poorly thought out and calculated stats.

Then plug in unadjusted ERA if you'd like. It would very likely show an RMSE even higher than the park-adjusted ERA.

ERA is a 19th Century sportswriter's invention. If you don't want to have to learn new statistics, that's fine. But I think you are smart enough to know why using ERA will lead you to more erroneous conclusions about player performance than 21st Century statistician-reviewed metrics will.

What you're doing is the equivalent of trying to measure large areas with rulers and string as opposed to just learning how to use the satellite and infrared tools now available.

IP and RA (I don't like ERA because of the Earned/unearned distinction) tells me most of what I want to know in what happened in the past.

I really don't need to know a bunch of estimators for future performance. Those predictors don't seem to do much better than me using old timey stats and my own judgement.

Now, to folks like you, who apparently have no idea what they are watching when they watch games, and are better off reading numbers off tables, those stats might be useful.

I like era plus myself

Those predictors don't seem to do much better than me using old timey stats and my own judgement.

Hilarious.

Good luck carrying that into a serious discussion of baseball statistical analysis.

I haven't gotten around to reading the SIERA series yet, but I'm going to try and run through all five articles later this morning.

Of course, this is an interesting admission from Dave Cameron:

Using SIERA or xFIP is basically a matter of preference, as 99% of the time, they’re going to give the same answer. When they differ, the margin is still very small. If you prefer one to the other, that’s great, and we’re happy to offer both here on FanGraphs.

Good luck carrying that into a serious discussion of baseball statistical analysis.

The older I get, the less interested I am of doing that. Most of the folks trying to discuss Stats are wannabees anyway that really don't understand the stats they are discussing. I think there is a very good reason why teams usually balance their sabr guys with their better scouts, and why guys like Parks weren't at all surprised to see Harrison pitching better than Holland.

I'm a fan who tries to understand many of these metrics, and they may serve their purpose to some, but here is the main reason why many of them will NEVER be widely accepted: Basic stats like BA, ERA, OBP, SP are stats that are not only easily understood, the average baseball fan can also easily learn how to figure them out themselves. What reading I've done on some of these new stats contain mathematical formulas that are hard to understand (like exactly why do you multiply by this coefficient instead of some other one?).
You want sabermetrics to be more widely accepted and less arguments over their worth? Figure out how to get Joe Average to easily understand them.

That's the thing OSF, these saber guys don't want the average Joe to be able to calculate the hottest new stat. They want to be able to use these stats and sound smart. Those opinions that I tend to agree with most on these chats either using these metrics as a guide along with what they see on the field or they don't use them at all and actually watch what is going on. I tend to disagree with many of the straight metrics people. Look at Harrison as the main example. I think the average fan can understand that ERA is a good basis for telling who is good and who is not. I think they can also understand that someone pitching in Colorado will give up more runs than someone pitching in the A's ballpark. The adjustment doesn't need to be quantifiable in my opinion. "A little bet better" or "a little bit worse" is more than enough. Especially since statistical analysis allows for variances. My guess is the variances are wide enough on all of these metrics that "A little bet better" or "a little bit worse" is just as accurate as using the metrics themselves. Now, tell me I can't have a serious statistical discussion about baseball without using more than ERA. Please.

I want to create a political cartoon in which SABR guys and traditionalists all pout to their mothers about how the other side picked on them at school.

The kicker will be that their mothers don't care.

It'll be a real knee slapper.

"Are you crying? Are you crying? ARE YOU CRYING? There's no crying! THERE'S NO CRYING IN BASEBALL!" ~ Jimmy Dugan

It only illustrates my point, Joey. Keep in mind, I'm not debating the worth of any of the metrics. I see the worth of many of the new sabermetrics. I'm talking mass acceptance here. So I went and clicked on the link you provided. I went to the offensive statistics tab and chose, as an example, wOBA as something I want explained to me. Under things to remember, I read this: "Exactly how much to weigh each of the components of wOBA was determined using linear weights. See that page for more information." This is what I mean. Joe Average might understand the concept of wOBA through the article, but then gets lost in the explanation of how it is arrived at and thus, loses interest in the metric as a whole. When someone can figure out how to make this aspect more palatable to the masses, then you'll see the ESPN's of the world start incorporating them more.

why guys like Parks weren't at all surprised to see Harrison pitching better than Holland

I think what you mean to say is, "why guys like Parks weren't at all surprised to see the team's results in a small set of games were better with Harrison than they were with Holland."

If you really meant to say "Harrison pitching better than Holland," well the obvious answer to that is that Harrison hasn't pitched better than Holland this year, and xFIP and SIERA both show that.

But assuming you meant the former, that they weren't surprised at the team's results with both, well, I don't know how to respond as I don't know what Parks said about the two. Did he say that Holland would have a better SIERA but poorer luck stats in a small sample size? Or did he say that Harrison would be a better pitcher than Holland in 2011?

Basic stats like BA, ERA, OBP, SP are stats that are not only easily understood, the average baseball fan can also easily learn how to figure them out themselves.

Joe Posnanski, on the calculation of batting average:

"I’ve made the point before about how batting average SEEMS simple, but it is really one of the most advanced stats we have if you consider “advanced” to mean “bizarrely complicated and obtuse.” WAR and xFIP have NOTHING on batting average."

I think the average fan can understand that ERA is a good basis for telling who is good and who is not.

And the average fan is often just flat out wrong in simply thinking that. Tommy Hunter had a 3.75 ERA last year. So he was better than Yovani Gallardo (3.84), Derek Lowe (4.00), Zack Greinke (4.17), John Lackey (4.40), and so on.

Tyler Chatwood is a 3.71 ERA this year. Better than Danks, Gallardo, Jimenez, Colby Lewis, A.J. Burnett, and many others.

This is a joke. Hunter and Chatwood just simply weren't better than those other pitchers during these stretches, and we now have the secondary statistics to specifically explain what led to their ERAs giving such an erroneous summary of what they did.

I had the same reaction as you when I was first told that ERA was useless. I figured it was just stats nerds wanting to sound smart, contrarian, whatever. But I now, after having taken the time to read what they were reading, realize they were right. ERA is a 19th Century mess of a number created by people who didn't understand how statistics (in an academic sense) work. Fortunately we now have real stats to replace that mess.