Opponent OPS

August 15, 2013
 

Over the last several years, it's been clear that pitching in Major League Baseball has become more dominant. In fact, it has been over 20 years since the league ERA has been as low as it has been so far this year. This year's MLB ERA is 3.88, the lowest since the 3.75 mark in 1992.

Some of the high points in ERA in that time were 4.71 in 2000, 4.77 in 2001 and 4.53 in 2006. Since 2006 ERA has been trending downward as seen in this chart of MLB ERAs:

Season ERA Opponent OPS
2006 4.53 .768
2007 4.47 .758
2008 4.32 .749
2009 4.32 .751
2010 4.08 .728
2011 3.94 .720
2012 4.01 .724
2013 3.88 .714

 

ERA is a useful summary statistic, but my favorite stat for pitchers is Opponent OPS. For MLB, overall, Opponent OPS is pretty consistent with ERA, but for an individual pitcher, it is much more indicative of his true pitching performance than ERA. ERA has many biases that Opponent OPS does not have. For example, ERA rewards pitchers who allow most of their home runs with no runners on base or are able to strand runners at the end of innings, even though those events are generally believed to be random and out of the pitcher’s control. Another example is the effect a relief pitcher has on his predecessor's ERA when it comes to stranded runners.

Here are the MLB leaders in Opponent OPS in 2013:

Best Opponent OPS (qualified starters)
Pitcher Opponent OPS
Clayton Kershaw .502
Matt Harvey .509
Jose Fernandez .534
Max Scherzer .564
Madison Bumgarner .566

 

And here are the MLB leaders in ERA this season:

Best ERA (qualified starters)
Pitcher ERA
Clayton Kershaw 1.88
Matt Harvey 2.23
Felix Hernandez 2.28
Hiroki Kuroda 2.33
Jeff Locke 2.43

 

As you can see, the OPS leaders are bit different. Clayton Kershaw and Matt Harvey have been tremendous by any measure. However, that is where the similarities end. Opponent OPS prefers the rookie phenom Jose Fernandez, major-league win-leader Max Scherzer, and Madison Bumgarner while ERA prefers Felix Hernandez, Hiroki Kuroda, and Jeff Locke.

 
 

COMMENTS (9 Comments, most recent shown first)

tangotiger
I agree wholeheartedly with Chris.
9:52 AM Aug 27th
 
cderosa
joeashp

In Ask Bill, joeashp noted that I hadn't specified what my problem was with OPS. I’ll take that bait.

On-base Plus Slugging (OPS) was a lamentable turn for sabermetrics because it isn’t an attempt to measure offense, it’s just adding up good stuff willy-nilly.

Around the time that Bill James was explaining to a national readership how Runs Created pretty accurately predicts a team’s runs scored, there was a writer in a prominent newspaper arguing that if you added guys’ hits, homers, RBIs, and doubles (or something like that), it proved Don Mattingly was the best player in baseball. In other words, if you added up all the stuff Don Mattingly was really good at, then Don Mattingly was the best.

That’s what OPS is to me: people who already believe that on base percentage and slugging percentage are the most important stats, telling you that when you add these together, it gives you the best hitters. That’s a poor argument to approach anyone who isn’t already down with the basic sabermetric understanding of how runs are created.

And if you are already versed in those arguments, then OPS isn’t enough for you. You’ve got to fine-tune it for the offensive environment, and hence, OPS+. In his question to Bill, joeashp proposes fixing OPS to get around a double-counting issue. Now you are going to a lot of trouble to refine a stat that was never intended to make an accurate measure of offense in the first place. Its only selling point was its accessibility.

The way I remember it, this thing had been around for a while but it was Rob Neyer’s ESPN column that popularized it (that column popularized many good things, despite OPS). Neyer’s argument was that OPS correlated with team runs *almost* as well as Runs Created and other complex measures anyway, and it was a lot easier to figure.

While easy to figure, though, it has no compelling logic and pushes us farther than we need to be away from expressing value in runs. If somebody has a 1.107 or a .718 OPS, what’s that? It’s not runs. You can’t even describe it as bases-per-something, because you’ve added together elements with different denominators. So you need to internalize a new set of standards to contextualize a stat that was just supposed to be a convenient prop.

Any time you combine strong offensive indicators, you are going to get some strong-looking connection with team runs. That doesn’t mean that just adding the good stuff together is the best way to go. It isn’t much more complex to figure on-base *times* slugging than it is to figure on-base *plus* slugging. On-base percentage times slugging percentage (OBP x SLG) is just basic Runs Created divided by at bats. With no real added difficulty in terms of calculation, you’d have a stat that is grounded in a demonstrated predictive relationship with actual team runs, that is expressed in runs, and is easily toggled between a rate and a total.

So that's why I've always felt OPS was a wrong-headed detour.

Chris DeRosa

11:38 AM Aug 26th
 
bjames
Well, for what it is worth I certainly am not convinced that Opposition OPS is as good a measure of a pitcher's ability as is ERA. I would state my belief this way: If you're looking at a sample of 50 innings, there is no doubt that Opposition OPS is a better representation of the pitcher's ability than ERA, because of the random turbulence in things such as the combinations of hits and outs. But if you're looking at samples of 1000 innings, I would have little doubt that ERA is a better measure than opposition OPS, because OOPS excludes too many real factors from the pitcher's game, such as his ability to control the running game, his ability to work off the stretch, and his tendency to coast and then work out of trouble. Opp OPS also partially or largely excludes the effects of double play rates.

The questions, then, are

1) Can we document that these "excluded" skills are real? (I don't doubt that they are real, but without a study focused on that issue, we don't know the scope of them.)

2) Where is the crossover, in innings, at which ERA becomes preferable to Opposition OPS?

I would guess that it is in the range of 180 to 200 innings, but that is just a guess.
7:54 PM Aug 24th
 
cderosa
Well I think there are times when you don't want to introduce park effect adjustments. Any time you adjust for park effects, you are entering the argument of how best to adjust for those effects. Are you using one year, three years, five years? Are the seasons weighted? Are you mixing different methods because some parks have been around longer than others?
To the extent that the author is actually rating pitchers, saying who is better than who, yes, he should deal with the park issue as best as he can. I think we'd agree the site's "Total Runs," which doesn't deal with park effects (or even outs used), doesn't cut it as a stand-alone rating. But sometimes when you are working on a smaller part of the question, and it isn't helpful to get bogged down in gray areas.
Here, the issue the author seems to be after is the variance between pitchers' ERAs and their results on a PA-by-PA basis. A good opportunity, I think, for the site to take better advantage of the information it has on hand. The Component ERA was designed to study this very issue.
As to OPS, I thought I was being generous by half an ass.
7:35 AM Aug 19th
 
jemanji
And no need at all to ever refer to the "half-***'ed" AVG stat, by that logic.

Supposing I'm on the Seattle Mariners' site, and not logged into BJOL, I've got access to the "half-***'ed" OBP and SLG for Hisashi Iwakuma and I can use them to check how lucky or not his ERA is.

I think we should install a "swear jar" and fine every 'net rat a buck for every time he refers to a stat that doesn't normalize for park. Especially we should fine James and Dewan -- who INVENTED the concept of normalizing for park.

Power to the people,
Jeff


12:27 AM Aug 17th
 
cderosa
This site actually publishes Component ERA in the player profiles, which addresses the very question. There's no need at all to resort to the half-assed OPS stat.
8:29 AM Aug 16th
 
jeffsol
My one question about this method would be why Opponent OPS as opposed to, say, Opponent OPS+ or something else that doesn't lump apples and oranges and call them all "fruit". We know that a point of OBP and a point of SLG are nothing close to equivalent value so this just seems lazy on surface. If we are going to take the time to eliminate certain biases, why introduce a new one?
7:53 AM Aug 16th
 
jemanji
By 'generally believed,' John is referring to a vast consensus that strand rate is not sustainable from one year to the next. He might as well have said it is 'generally believed' that fit shortstops are more desirable than real fat ones.

I don't mean to be snotty, but as a poster on a Bill James site, quibbles like that seem like they set a pretty low standard for idea exchange.

.........

It is self-evident that a pitcher's OBP+SLG will edit out things like 'batting average with runners in scoring position', and that ERA will capture them. It is also self-evident why this has value.

It's okay if you couldn't deduce that for yourself, but it comes off as poor form to lecture John for sloppy thinking when the reverse was the case.

Your friend,
Jeff


5:10 PM Aug 15th
 
DanaKing
"For example, ERA rewards pitchers who allow most of their home runs with no runners on base or are able to strand runners at the end of innings, even though those events are generally believed to be random and out of the pitcher’s control."

Really? Is there evidence of this, either way? It seems intuitive there would be some pitchers who were less like to surrender home runs with men on base because they refused to give in, and would prefer the walk to the home run if they couldn't get the hitter to expand his strike zone. (Jim Palmer being the extreme example; no grand slams in almost 4,000 IP.) If this is true, then it is not unreasonable to believe there are pitchers better suited to leave men on base, if only because they don't panic.

I don't mean to be snotty, but on a site dedicated to studying and quantifying such things, "generally believed" seems to be a pretty low standard.
4:11 PM Aug 15th
 
 
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