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Schoenfield's ESPN Sweet Spot featuring the O's today


isestrex

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Here's another way to look at it, that any baseball fan would understand:

Fact: The O's hitting is 21st in MLB in OPS and 18th in Run Scored.

Fact: The O's pitching is 27th in Quality Starts and has given up the 7th most Runs overall.

Fact: The O's defense leads the league in errors.

Conclusion: The O's are one of the best teams in baseball.

That conclusion doesn't exactly follow, does it? That's all the Pythag arguments are doing. Pointing that out using a single stat.

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Are they using the cumulative numbers of the season to date to calculate the odds of their future success? If so, I'd be interested in looking at how often teams play the first and second halves of the season fairly equally.

I'm sure most teams' second half records are fairly close to their first half. But individual cases will be all over the place.

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"The stats", whatever those are, say no such thing. The stats don't talk in black and white, they express probabilities. No solid analysis would ever say that a true talent 72-win team can't win the World Series. It would simply say that is very unlikely. And the Orioles successes have been very unlikely. And (as we've said countless times) they don't get any more likely unless the team starts playing better. But there have been thousands of team-seasons in MLB history, so unlikely occasionally happens.

But clearly those models are not appropriate for analyzing this team this season. That doesn't mean it's a bad model, but that in some cases it's not adequate. The Orioles seem like they are that case.

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Team of luck or team of destiny? That's the question that will be answered come October. There's all kinds of formulas that predict the Orioles should be bad. Maybe they will create a new formula at the end of the year to explain how the 2012 world champion Baltimore Orioles beat the odds. Has a ring to it, huh? In any case, all the baseball greats played at unatainable levels, and are bound to fall off. Does that mean their careers were just luck up until then? In more cases than not, the stats give you a general prediction of what's going to happen. If you go by those though, the last yankees, red sox, and phillies should have been alternating championships the last decade. Every now and then, a team defies the odds, and goes against the rules. Why can't that team be our 2012 Baltimore Orioles? Instead of asking how are they doing it, ask why not?

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But clearly those models are not appropriate for analyzing this team this season. That doesn't mean it's a bad model, but that in some cases it's not adequate. The Orioles seem like they are that case.

On the contrary, I think it is a fantastic way of looking at this team because it forces us into helpful granular analysis to figure out how the Orioles have managed to distribute a pretty terrible run differential into positive outcomes. This Orioles team may be the best argument for the validity of the pythag as an analytical tool.

One of the reasons why baseball statistics are so awesome is because of the heavy component of uncertainty inherent in nearly all aspects of the game. Outliers, to me, are a strong argument for the necessity of statistics - without the statistics we wouldn't really even know that the Orioles are doing something differently.

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Team of luck or team of destiny? That's the question that will be answered come October. There's all kinds of formulas that predict the Orioles should be bad. Maybe they will create a new formula at the end of the year to explain how the 2012 world champion Baltimore Orioles beat the odds. Has a ring to it, huh? In any case, all the baseball greats played at unsustainable levels, and are bound to fall off. Does that mean their careers were just luck up until then? In more cases than not, the stats give you a general prediction of what's going to happen. If you go by those though, the yankees, red sox, and phillies should have been alternating championships the last decade. Every now and then, a team defies the odds, and goes against the rules. Why can't that team be our 2012 Baltimore Orioles? Instead of asking how are they doing it, ask why not?

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Here's another way to look at it, that any baseball fan would understand:

Fact: The O's hitting is 21st in MLB in OPS and 18th in Run Scored.

Fact: The O's pitching is 27th in Quality Starts and has given up the 7th most Runs overall.

Fact: The O's defense leads the league in errors.

Conclusion: The O's are one of the best teams in baseball.

That conclusion doesn't exactly follow, does it? That's all the Pythag arguments are doing. Pointing that out using a single stat.

I think this is a gross over simplification of what people are saying. If statistically the Orioles are not one of the best teams in baseball, why is their W-L record not reflective of that? "Luck" is the only thing I can think of. And if luck is what explains it, then what value is statistical modeling? Predicting what should happen but isn't?

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People are saying that the Orioles are unlikely to continue winning if they continue to be outscored similarly to what they've been outscored so far.

If similar means we play our remaining games in the same pattern as up to this point where we get mostly quality starts and fantastic relief pitching that allows us to win close games, seasoned with a dash of blowout losses, then I don't know why it would be unlikely that we do continue to win at current pace.

I wonder what our median run differential is. What about the quartiles? Wouldn't that give a better picture of the run difference we should expect for an O's game? In other words what happens most often not what happens on average. I'm not a baseball stats guy at all. Just curious.

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If similar means we play our remaining games in the same pattern as up to this point where we get mostly quality starts and fantastic relief pitching that allows us to win close games

We're 27th in baseball in quality starts, though.

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But clearly those models are not appropriate for analyzing this team this season. That doesn't mean it's a bad model, but that in some cases it's not adequate. The Orioles seem like they are that case.

They're absolutely appropriate. When a model says that it's essentially impossible for a team to be outscored by 50 runs and still win 55% of their games, and in real life just a tiny handful of teams have done that in the past 110 years, that's a pretty darned good model. You don't throw out your model because some tiny fraction of 1% isn't within a half a standard deviation.

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I think this is a gross over simplification of what people are saying. If statistically the Orioles are not one of the best teams in baseball, why is their W-L record not reflective of that? "Luck" is the only thing I can think of. And if luck is what explains it, then what value is statistical modeling? Predicting what should happen but isn't?

Yeah, you shoulda been ready for a "gross oversimplification" when I started a post with "that any baseball fan would understand."

Plus, you ever hear of the exception that proves the rule?

That's what's going on here.

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