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Fangraphs: The Orioles and Accepting Random Variation


Can_of_corn

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I wish he would have looked at what qualities the teams that outperform their projections have. Things like team age, bullpen performance, home run power, defense...all of the things the Orioles do well. If other teams that outperform have the same qualities, that would be interesting.

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Cameron is actually pretty funny. When a team outperforms his model he says its part of the standard deviation from the norm which prove the model is correct.

What it really means is the model can't really predict what is going to happen. And in his way of thinking deviations from the expected outcome are perfectly normal.

This leaves him happy with his model because occurrences fall within the wide range that he has set.

I guess you can twist anything to make it look like you want it to.

But don't expect that his model can predict how a team will perform. Not when the range of performance is so wide that it can mean any number of wins in correct under the parameters of the model.

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Cameron is actually pretty funny. When a team outperforms his model he says its part of the standard deviation from the norm which prove the model is correct.

What it really means is the model can't really predict what is going to happen. And in his way of thinking deviations from the expected outcome are perfectly normal.

This leaves him happy with his model because occurrences fall within the wide range that he has set.

I guess you can twist anything to make it look like you want it to.

But don't expect that his model can predict how a team will perform. Not when the range of performance is so wide that it can mean any number of wins in correct under the parameters of the model.

Well since according to the projection we are only going to win another eight games this season, I find that amusing.

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Jeez. You guys don't seem to understand what a model is or the point of it. If I made a model for dice rolling, and you rolled snake eyes two out of ten times, would you immediately start investigating the dice?

What he is saying is that on the whole, this model is doing its job exactly as expected. If it weren't, a bunch of teams would be outliers along with the orioles. Now I don't think this is an attack on the O's or their style of baseball, just a defense of what is a very broad prediction system.

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Jeez. You guys don't seem to understand what a model is or the point of it. If I made a model for dice rolling, and you rolled snake eyes two out of ten times, would you immediately start investigating the dice?

What he is saying is that on the whole, this model is doing its job exactly as expected. If it weren't, a bunch of teams would be outliers along with the orioles. Now I don't think this is an attack on the O's or their style of baseball, just a defense of what is a very broad prediction system.

Oh, I agree. It just amusing that it seem like the model can stretch to include everything. An if that is true what number is not valid.

They can say with the O's players they should win 81 games. But if they win 100 they are still correct under the standard deviation of the model. No prediction in wrong under those terms.

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Oh, I agree. It just amusing that it seem like the model can stretch to include everything. An if that is true what number is not valid.

They can say with the O's players they should win 81 games. But if they win 100 they are still correct under the standard deviation of the model. No prediction in wrong under those terms.

No SINGLE prediction is wrong. You are correct. Again, if you flip a coin and get 162 times and get 100 heads, this doesn't make your prediction of 82 heads wrong in any way.

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I understand why Orioles fans are frustrated with being told that their team isn’t as good as their quality record for the second time in three years. We don’t like accepting randomness as an answer, and when someone tells us that regression is coming and then it doesn’t come as soon as they said it should, confirmation bias kicks in, allowing us to believe that the prediction was wrong all along. It is difficult for human beings to observe a repeated event over any real length of time and not find a cause for the results.

If the Orioles win the World Series, I really won't care if "their team isn't as good as their quality record for the second time in three years." Just ride the wave, baby! If the Orioles have the wind at their back so be it. None of these systems were saying the Red Sox were a fluke last year, and yet look how they did in 2012 and 2014.

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If the Orioles win the World Series, I really won't care if "their team isn't as good as their quality record for the second time in three years." Just ride the wave, baby! If the Orioles have the wind at their back so be it. None of these systems were saying the Red Sox were a fluke last year, and yet look how they did in 2012 and 2014.

They will tell you that the Sox woefully underperformed in 2012. Remember when the, I think it was, ESPN power ranking were handed over to the stat guys that year? And they kept putting the Sox in the top third of the league despite the losses? It got so bad they had to end the experiment.

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I think a common flaw people make is applying a statistical model to predict what happens to just one team, or just one season, or just one coin flip.

This guys model works pretty well to predict how wins will correlate to runs across all of baseball over a full season (or multiple seasons).

It says nothing at all about which team will be the outlier in a given time frame. It just says there should be an outlier or 2 every season.

Luckily for us, the Orioles have been outliers 2 out of 3 years.

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