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OBP....and its importance


Sports Guy

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OBP is important because it is the inverse of the probability of getting an out. Its very simplistic but still true: the more players a team sends to the plate over the course of the game, the more runs are likely to be scored.

Pretty simple formula:

Runs Scored = Total PA - outs - LOB

Outs are usually 27, so the team controls the total PA (measured by OBP) and the LOB (a function of, among other things, SLG).

In 2008 and 2009, the Orioles were pretty consistent. In their wins, then sent ~40 batters to the plate. That means in a typical game, the top four hitters got 5 plate appearances. In their losses, they sent ~37 batters to the plate, maybe only Roberts get his 5th time up.

The primary importance of OBP is a measure of the probability of making an out. Its not seeing pitches, its not getting into the bullpen. Its sending the most players to the plate in any given game, a certain proportion of which are likely to turn into runs.

Bottom line: Every game I root for the number 9 hitter to get 5 plate appearances. Our offensive slogan for this year should be: Get Cesar his 5th at bat!

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Let me put it this way: to my understanding, if you have two players whose OPS's are equal, the one who has the higher OBP and the lower SLG is the one who produces more runs. Just to give an example:

Michael Cuddyer, .276/.342/.520/.862, 5.89 RC/27

Victor Martinez, .303/.381/.480/.861, 6.58 RC/27

Doesn't RC weigh OBP in its calculation, and as a result, the difference in RC is a measure of the relative weight RC gives to OBP over slugging and not any intrinsic difference in value?

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Doesn't RC weigh OBP in its calculation, and as a result, the difference in RC is a measure of the relative weight RC gives to OBP over slugging and not any intrinsic difference in value?

The relative weight that RC gives to OBP over SLG reflects a measure of difference in value. It's not just some random number they made up. Difference in value is why it's there.

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rshack, you're right that it doesn't add up. Your point about the irrelevance of team stats, however, I would not agree with. At least in the context of the OP dealing with team runs and team OBP, it is relevant. This thread and the SLG thread each show some correlation between the single measure and RC; in reality there is even greater correlation between team OPS and team RC. I can't speak for Sports Guy but I think the implied question of the threads is, "What kind of players should the Orioles be looking for?"

It is confusing to look at individual contributions (favoring OBP) and collective team performance (favoring OPS), and come to a single conclusion. After all, you assemble a team by adding together individual players. While the riddle remains, it still seems relevant to ask, "What makes sense as a team approach to hitting (or building a roster)?" I don't think the team stat correlations can be ignored when addressing this question.

Even if you stick with the individual result, you still have to wonder why, in the team stats, the adjusted OPS' (using the 1.8 factor) is only marginally better than plain OPS (OBP + SLG).

The team stats don't tell you what hitter stats tell you. I think it's fine to care about hitter stats, and fine to care about team stats. What's not fine is to look at the correlations found in team stats and conclude that tells you anything much about the value of individual hitter traits.

When they did the thing that produced the 1.8 factor, they were comparing how different aspects of individual hitting performance contributed to production relative to each other. It was a comparison between the two aspects of hitting. That's not what is going on here. He's just seeing how strong the correlation is between each team stat and total team runs. That's not telling you anything about how much the hitting-thing that each stat measures contributes to runs.

Look at it this way: Let's pretend we had a whole league of guys who had exactly the same hitting stats, they were perfect clones of each other. Let's say that their performance was consistent with OBP having that factor of 1.8 vs. SLG. OK? If that happened, then OBP would not have 1.8 times the correlation with runs as SLG. To the contrary, OBP and SLG would have the same correlation with runs. OBP would not correlate any better or worse than SLG did, even though OBP deserved the greater weight in helping to create those runs. If the players were all 5'10", then their height would correlate perfectly with runs too, but that doesn't mean you'd think you should hire only those hitters who are 5'10". While irrelevant-height and more-valuable-OBP and less-valuable-SLG all had the same correlation with runs, and therefore could predict runs to the same degree, that doesn't mean they all played the same role in contributing to those runs.

From what this guy did, we know that team-OPS has a tighter correlation with team-runs than either team-OBP or team-SLG. We know that team-OBP and team-SLG have virtually the same correlation. But that does not mean that OBP and SLG contribute to those runs equally.

Maybe this will help... Let's say that, for every 10 miles I traveled, I walked 1 mile and drove 9 miles. Everybody would agree that driving played a much bigger role in accumulating my overall distance than walking did, by a factor of 9. Yet if I maintained that pattern, the correlation between each of those 2 travel methods and my total distance would be exactly the same. Regardless of whether it was walking or driving, if you knew the number, then you could tell how many total miles I went. The fact that the constant factors are different (1 vs. 9) doesn't matter, the strength of the correlation between the 2 travel modes and the total travel distance is the same. If you plotted a graph of all my trips, with total distance on one axis and the distance for just one of the two travel modes on the other axis, connecting the dots would form a perfectly straight line regardless of which of the 2 travel modes you were plotting. Whether that straight line is at a 45-degree angle depends solely on the scales you use for the two axes, and you can do that however you want, it's the straight line part that matters. The strength of correlation measures how close you are to having all the data points fall on a straight line. It has nothing to do with what how much one component (driving, or OBP) contributed to the total result (total distance, or team runs) compared to how much the other component (walking, or SLG) did, it's just about how close you get to forming a straight line when you plot them.

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The relative weight that RC gives to OBP over SLG reflects a measure of difference in value. It's not just some random number they made up. Difference in value is why it's there.

RC pretty much is OBP X SLG X AB

So they are weighted equally.

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No one's arguing with that. What I take exception to is the simplistic notion that walks are always better than outs. In some situations they aren't. People who want to reduce baseball to absolutes are ill advised.

Ok, so 99.999% of the time a walk is better than an out. Good?

I don't get why this has merited such a long thread. There's no debate. Getting on base is the single most important offensive event. Taken as independent events, getting on base is more important than collecting long hits. High OBP/low SLG guys are vastly more valuable than low OBP/high SLG guys with almost no real life exceptions. Teams that get on base at a high clip almost always outscore teams that don't. Brett Butler generates far more runs than Tony Batista. This is Baseball 101.

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RC pretty much is OBP X SLG X AB

So they are weighted equally.

That's the shorthand version. There are umpteen different versions. I'm neither qualified nor interested in getting into a big to-do about that.

The crux of my response to LJ is the same regardless of RC: When people introduce weighting factors for OBP vs. SLG, they do so to reflect what they believe is a difference in value between them. That's the point, not whether or not the simple version of RC is right, or best, or whatever.

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rshack,

Interesting philosophical question raised by this discussion. Does causation trump correlation? Your stance suggests it does. I'm not so sure. I think maybe demonstrated causation is just a more tangible form of correlation. If you have mathematical proof that OBP is 1.8 times as important as SLG in contributing to runs, you have a causal relationship. Any yet the correlation to runs is still equal. You can say the correlation is simply coincidental, or circumstantial, like the correlation with 5-10 in height. I would say that if, say, an increase in batters' height correlates strongly with runs produced, I would take seriously the recruitment of taller players even if I could not yet discover a causal relationship. Correlation might come about because of hidden factors of causation.

The analogy of walking and driving miles is an elegant way of illustrating your point. It also shows how we are talking about different issues here. One issue is, what are the most accurate weights of OBP and SLG in a formula that approximates RC?

- one answer (1.8:1) yields what is called OPS'

- one answer (1:1) yields what is called OPS

- yet, I believe (correct me if I'm wrong) that OPS' and OPS are actually closer to 1:1 when compared with each other, than 1:8 to 1.

The analogy of the miles breaks down when you consider the correlation chart as a whole, where different hitting metrics do not all share the same correlation with runs produced. Clearly homers contribute more to runs than walks - and this is reflected by higher correlation. Clearly SLG contributes more than homers alone - and this also is shown by higher correlation. Clearly OBP+SLG contributes, as well as correlates, more strongly to run production than either of those measures alone. The whole point of the chart is to show, by strength of correlation, which factors contribute most to run production. (And note, this is total runs scored, not the RC formula).

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I don't get why this has merited such a long thread. There's no debate. Getting on base is the single most important offensive event. Taken as independent events, getting on base is more important than collecting long hits. High OBP/low SLG guys are vastly more valuable than low OBP/high SLG guys with almost no real life exceptions. Teams that get on base at a high clip almost always outscore teams that don't. Brett Butler generates far more runs than Tony Batista. This is Baseball 101.

It's because of that guy's graph that showed team-OBP and team-SLG having the same correlation with team-runs.

Some folks are taking that picture as evidence that OBP and SLG have equal value.

Apart from some inconsequential BS, that's the main thing that did it...

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Ok, so 99.999% of the time a walk is better than an out. Good?

I don't get why this has merited such a long thread. There's no debate. Getting on base is the single most important offensive event. Taken as independent events, getting on base is more important than collecting long hits. High OBP/low SLG guys are vastly more valuable than low OBP/high SLG guys with almost no real life exceptions. Teams that get on base at a high clip almost always outscore teams that don't. Brett Butler generates far more runs than Tony Batista. This is Baseball 101.

Okay, then how do you account for the chart results showing that OBP and SLG are (roughly) equally correlated with runs scored?

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Okay, since my graph got this whole mess started, I'll settle it with another graph.

Correlation != Causation

Hey, let's give credit where credit is due. Actually SG started this whole mess with his OP's lining up OBP and SLG numbers with team runs scored. ;)

P.S. I've emailed Dan Fox who produced the run estimation chart, for his thoughts and clarification. Will keep you posted...

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That's the shorthand version. There are umpteen different versions. I'm neither qualified nor interested in getting into a big to-do about that.

The crux of my response to LJ is the same regardless of RC: When people introduce weighting factors for OBP vs. SLG, they do so to reflect what they believe is a difference in value between them. That's the point, not whether or not the simple version of RC is right, or best, or whatever.

That simple version also breaks down to OBP X TB.

I like to use wOBA and the wRC used on fangraphs is based on wOBA. So IMO the wRC is better than RC (basic).

2004 Tejada had a basic RC of 125.64 and a wRC of 112.9.

You can see how Tejada OBP hurts him more on wRC over the basic RC formula.

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