Does misusing math demonstrate a flaw in the use or does it demonstrate a flaw in mathematics itself?

Girardi does have a lot of statistics at hand, and studies probably as intensely as any MLB manager. He was an engineering major at Northwestern. I think we all know engineering types. They like their numbers. Let us also not forget that Girardi was a professional MLB player and a catcher. He of all people knows that small sample sizes mean nothing. A player being 1-6 against a specific pitcher is simply a data point, but it not the determining factor. As I’ve heard Girardi explain at varies times, he’ll look at the match-up of hitter vs. pitcher. Does the pitcher throw a slider? Is the hitter good against sliders? He’ll consider how the hitter actually performed in the ABs against specific pitchers, not necessarily the final result, because a small sample size means nothing. The player going 1-6 might have actually scorched the ball all six times against the pitcher. He considers all these aspects, but just because he binder says the player was 1-6 doesn’t mean that stat determined anything.

Actually sabermetrics is the analyses of baseball statistics. Part of this analyses is noticing when data is insufficient or just plain wrong. This is why sabermetricians are cautious in using batting average and shy away from RBI and pitcher wins altogether. Sabermetricians will acknowledge the danger of small sample size, and (s)he will know that the larger sample of the whole season against multiple pitchers is more valuable then the small sample against a specific pitcher. Proper analyses will tell you not to follow hitter/pitcher matchups. If you decide to follow it anyway then you are as much a sabermetrician as an astrologer is a physicist.

PRIME example and the worst by far of all of Girardi’s decisions – starting Hughes in game 2 (& therefore 6) in Texas because he had good numbers in Texas.

He was a rookie then, unknown. It was years ago, it was against a Texas lineup where half of the guys he faced are out of baseball because they were so terrible. Texas now have a really good potent lineup with speed and power.

While the numbers were good, if you looked into the numbers, you would see it was a small sample size, and of no real value. And that was the stated reason by Girardi.

For example, if I flipped a coin 5 times, collected that data, and then used it to presume that the coin would come up heads on the next flip, that would *not* be sound statistics. If I had put that on one of my tests in grad school, I would have likely been kicked out of the program. Thus, I wouldn’t say that I was using “statistics” to make that conclusion. I see this in the same way. If the data is used incorrectly, or at least to make a conclusion that isn’t sound, then it’s not sabermetrics under my definition of the term.

This is what sunk Elias vis-a-vis Bill James; Elias was always trying to make the most minute diagnoses (which are useless) while James was trying to approach it scientifically. Unfortunately, those garbage statistics have spawned a whole generation of people like Girardi who thinks that they mean something.

If you go outside and observe where the moon is, and you write the co-ordinates down in your notebook, that is “object data” and the recording and analysis of that data is “science”. Whether there is enough data there to determine where the moon will be tomorrow is an interesting question, but this does not make the data any less factual, nor the process any less of a science

Kinda like you are your BABIP.