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This is an amazingly awesome study over at Hardball Times about fastball speeds. Got some really amazing stuff on what you could do with the Pitch f/x data.
I still get the feeling that MLB is just providing this data free until we get addicted, then they're going to screw everyone to the wall & charge massive amounts of cash just to look at it.
My venting is over, but go read this study. It's ri-****-donkulous.
good stuff.
What's that have to do with anything? Is it bad to use a stat that is expressed in a familiar format - the run? He didn't just randomly select numbers. There's actual logic and fact behind it. It's not an exact number that measures exactly what someone did, like hits or home runs, but it is a very valuable estimator.Quote:
Originally Posted by yankee hater
I like my good friend Matthew Carruth's stuff better.
Till fastball speed:accuracy is actually VIABLY used then this is all hypothetical ;)
Linear weights, or run values, are time-tested and very well accepted by anybody with any knowledge of baseball stats at all beyond batting average. The concept is mind-numbingly simple. Each batting outcome is assigned a number of average runs:Quote:
Originally Posted by yankee hater
The averages come from the actual real-life averages. It's incredibly simple. See Batting Runs.Quote:
Anyway, batting runs measures a player's run production above that of the average batter, by assigning a run value to the various outcomes of a plate appearance—for example, a single is worth (on average) just under half a run, the value of a walk is around one-third of a run, an out is worth around negative .25 runs, and so on.
Of course, it gets more involved as you go deeper into linear weights, but the basic premise is ridiculously simple.
Too simple, if you ask me...
Ah...great...this has already degenerated into a flame war of "it's simple, if you don't get it, you're stupid"...
Can't we all just enjoy the article?
Nobody's flamed anybody...Quote:
Originally Posted by Redsauce
Thing is, these types of studies don't really do anything for the average fan, whether or not they're based on more "accepted" methods. Like you said, they're more for the sabermetrically-minded, or... major league teams, where it can actually be put to good use, and major leagues teams should really understand the concepts of linear weights (although, I'm afraid, there's still a portion of teams that don't).
It can't be accepted as viable if it doesn't use already accepted methods? The ones that we "accept" now had to start somewhere, correct?Quote:
Originally Posted by yankee hater
It's really irrelevent because the study does use a method that is commonly accepted by anybody with any reasonable amount of baseball statistical knowledge. It's just not widely known by the mainstream.Quote:
Originally Posted by AndrewOsborn
And after all, statistical studies should use methods that are commonly accepted by statisticians, not by the fans, just like scientific studies should use methods that are commonly accepted by scientists, not by the common person.
I didn't call it a science.Quote:
Originally Posted by yankee hater
It was an analogy. Scientific studies should use methods which are accepted by scientists. Likewise, statistical studies should use methods which are accepted by statisticians.Quote:
Originally Posted by yankee hater
But, technically, sabermetrics is a science. Sabermetrics is statistical analysis, which is a mathmatical science.
If you enjoy the article, you're stupid.Quote:
Originally Posted by Redsauce
:D
You're doing fine... you don't need to argue every point until you and everyone else is blue in the face, is all. State your opinion, others will do the same, and move on. That's really been the only problem ever, is that there's a certain group of people (and it's definitely not just you) who just won't let it go. If a couple of y'all get together in one thread, all of a sudden we get 50 posts in the space of an hour or two with nothing but back and forth talk about... well, nothing really.Quote:
Originally Posted by yankee hater
I think he qualifies his "averaging out" point well, nor does he say it's a fact - rather, an assumption:
He had to, or he wouldn't have any remotely significant sample size.Quote:
As for the other effects, like pitch sequence, count and the like: from necessity, I'm going to assume that this stuff averages out. I'm forced to do this because if I divide the data up too much, I won't have enough pitches in any sub-group to analyze.