I have a terrible confession to make

[typefitter]

I cannot keep your various projects straight. That said, is he Asian? That might be a hook.

She. And no.

The book you're going to hate read is the next one, not this one. Signed the contract this week.

 

[Songbird]

I will put the verse that begins, "In the clearing stands a boxer ..." up against any verse in the history of recorded American music.

Come at me, Bob Dylan.

"But here you are, in the 9th, 2 men out and 3 men on ... "

And it's not even close. Pashan's 8 scouts were closer in their ashessment of Ohtani.

 

[Dick Whitman]

She. And no.

The book you're going to hate read is the next one, not this one. Signed the contract this week.

I think it's going to be really bad, but I think that your girl scientist book is probably going to be really good.

 

[typefitter]

I think it's going to be really bad, but I think that your girl scientist book is probably going to be really good.

You have no data to prove your ashertions. Therefore they must be invalid. Right?

 

[Dick Whitman]

You have no data to prove your ashertions. Therefore they must be invalid. Right?

Let's reset the argument from the Ohtani thread:

1. Scouts tell Jeff Pashan that Ohtani will not be a good hitter in the major leagues this season.
2. Ohtani has a very productive initial 19 plate appearances in the major leagues.
3. Poin asherts that the scouts have been, at that point, "proven spectacularly wrong."
4. But I say the scouts had not been "proven spectacularly wrong," because 19 plate appearances is not enough to determine definitively whether a player is good or not.

That's it. That's the argument.

This is not high-level math, such as your girl scientist subject engages/engaged in. It certainly is not an argument that data trumps scouting or that scouting is useless. I have stated, on this site, many times that traditional scouting is the key battleground now because teams all have the same data. It is not an argument that the scouts were not, in fact, spectacularly wrong. That is still in play. It is, in fact, the likely most likely result. I just disagreed that they had been already proven so, after 19 plate appearances.

 

[typefitter]

Let's reset the argument from the Ohtani thread:

1. Scouts tell Jeff Pashan that Ohtani will not be a good hitter in the major leagues this season.
2. Ohtani has a very productive initial 19 plate appearances in the major leagues.
3. Poin asherts that the scouts have been, at that point, "proven spectacularly wrong."
4. But I say the scouts had not been "proven spectacularly wrong," because 19 plate appearances is not enough to determine definitively whether a player is good or not.

That's it. That's the argument.

This is not high-level math, such as your girl scientist subject engages/engaged in. It certainly is not an argument that data trumps scouting or that scouting is useless. I have stated, on this site, many times that traditional scouting is the key battleground now because teams all have the same data. It is not an argument that the scouts were not, in fact, spectacularly wrong. That is still in play. It is, in fact, the likely most likely result. I just disagreed that they had been already proven so, after 19 plate appearances.

Thank you for basically outlining the thesis of the really bad book I'm going to write.

Some stats are good. Sometimes good stats are used badly, but they are still given credence because they are stats. (Such as the fact that Ohtani is X-for-19, which, as you correctly ashert, is a meaningless sample over the course of a season and a career.) And some fields of human endeavour are resistant to statistical analysis, no matter how hard quants might wish for them not to be. Sometimes the human eye or brain is a better instrument. Not always. Maybe not even often. But sometimes.

 

[Dick Whitman]

Thank you for basically outlining the thesis of the really bad book I'm going to write.

Some stats are good. Sometimes good stats are used badly, but they are still given credence because they are stats. (Such as the fact that Ohtani is X-for-19, which, as you correctly ashert, is a meaningless sample over the course of a season and a career.) And some fields of human endeavour are resistant to statistical analysis, no matter how hard quants might wish for them not to be. Sometimes the human eye or brain is a better instrument. Not always. Maybe not even often. But sometimes.

Here is what I think: I think that in large part, the baseball quants have been right about what wins and loses baseball games. But, as entertainment, the sport is worse for it. Baseball is at its best for viewing when the ball is in play. But now the play is hardly ever in play, it seems. They figured out the sport but they broke the sport.

It's like "Flowers for Algernon."

 

[doctorquant]

Thank you for basically outlining the thesis of the really bad book I'm going to write.

Some stats are good. Sometimes good stats are used badly, but they are still given credence because they are stats. And some fields of human endeavour are resistant to statistical analysis, no matter how hard quants might wish for them not to be. Sometimes the human eye or brain is a better instrument. Not always. Maybe not even often. But sometimes.

Couple of years ago we hired this ... person ... whom I just can't stand. This person is one of the most obnoxious people I've ever met. Loud as fork in public. Monopolizes every conversation, presentation, meeting ... You'd just looooove this person.

This person is always going on and on and on about how artificial intelligence and data mining are going to do away with all of these things you're (likely) going to be talking about. And while mostly when I'm around her/him I just sit quietly, the better to make it end quicker, the last time he/she started prattling on -- at a million forking decibels -- I waded in. It was not pretty. But at least he/she clams up when I'm around these days.

Also ... In prepping for this book, you might take a pash through How We Know What Isn't So by Thomas Gilovich.

 

[typefitter]

Couple of years ago we hired this ... person ... whom I just can't stand. This person is one of the most obnoxious people I've ever met. Loud as fork in public. Monopolizes every conversation, presentation, meeting ... You'd just looooove this person.

This person is always going on and on and on about how artificial intelligence and data mining are going to do away with all of these things you're (likely) going to be talking about. And while mostly when I'm around her/him I just sit quietly, the better to make it end quicker, the last time he/she started prattling on -- at a million forking decibels -- I waded in. It was not pretty. But at least he/she clams up when I'm around these days.

Also ... In prepping for this book, you might take a pash through How We Know What Isn't So by Thomas Gilovich.

Thanks for the rec. Will do! I will gladly take all such help.

One of the best examples I can give about the limits of statistical analysis is movie making. Why are some movies hits and some movies bombs? Nobody forking knows. An entire media company, Relativity, was built on the idea that they had "cracked the code." They had an army of quants dictate how and when and why to make certain movies. Plug the numbers into their giant humming machines and green light or no.

Their movies almost all sucked, they lost billions, and they went bankrupt.

 

[Small Town Guy]

Here is what I think: I think that in large part, the baseball quants have been right about what wins and loses baseball games. But, as entertainment, the sport is worse for it. Baseball is at its best for viewing when the ball is in play. But now the play is hardly ever in play, it seems. They figured out the sport but they broke the sport.

It's like "Flowers for Algernon."

I'm also feeling this way with the 3-pointer. I get the math. I get it. I loved shooting them as a player. I love shooting them in old man's league. I marvel at Steph Curry being as revolutionary of a player as the game's ever seen. But the game is becoming more boring to me. Every team running pick and roll and launching dozens of 3s a game has started to bore me. The Marc Gasol who takes 600 3-pointers the past 2 seasons is not a more entertaining player than the Marc Gasol who took 60 in his first eight seasons. The corner 3 is borderline fascist. A 3 on 1 break that ends with two guys flaring out for a wing 3 is mathematically beautiful, and a bore to view.

@typefitter Stat book sounds a little (but still quite different) like a book Jesse Singal of New York Mag is writing. About the replication process in psychology. in his words, "In short, a bunch of past psychological findings that have been more or less accepted as true by many researchers seem to run into problems when psychologists try to rediscover them with new, sometimes more rigorously conducted, experiments."

 

[doctorquant]

@typefitter Stat book sounds a little (but still quite different) like a book Jesse Singal of New York Mag is writing. About the replication process in psychology. in his words, "In short, a bunch of past psychological findings that have been more or less accepted as true by many researchers seem to run into problems when psychologists try to rediscover them with new, sometimes more rigorously conducted, experiments."

Oh, hell, the experiments don't even need to be more rigorously conducted for the problems to be revealed. The "file drawer" issue -- "significant" results get published, "not significant" results get tossed aside -- means that a goodly portion (1 in 20, maybe 1 in 5) of these breakthroughs were merely random error.

 

[doctorquant]

One of the best examples I can give about the limits of statistical analysis is movie making. Why are some movies hits and some movies bombs? Nobody forking knows.

Music. Fashion. Taste. What the market's underlying risk-free interest rate is (or will be). The list goes on and on.