I second that. “The Drunkard’s Walk” is a fantastic book that illuminates society misunderstanding of probabilities (especially conditional) and statistics.

@georgmi
The problem, I think, lies in defining “random”. For the purposes of baseball performance, “random” has to mean unpredictable and uncontrollable.

I think we needed this. When flipping a coin there are obviously forces at work that could be measured with the proper technology. How hard it is flipped, where it lands, at what angle it lands, etc. But putting together all those variables is like trying to predict a molecule’s drunkard’s walk. You really can’t do it. Entering a baseball season or a game, there are enough variables going on, with the pitcher, his fielders, and the opposing batters, that finding the true cause of something can be virtually impossible. Because the results, perhaps babip or HR/FB, follow a random pattern (even if that pattern the result of a bunch of other small random variables: see central limit theorem) it should be modeled as such. A random patter that, all else equal, regresses toward the player’s mean (or possibly league mean).

For example, Ichiro’s career batting average is .331. If he hits .340 or .315 in a season, most people accept that as the impact of randomness. On the other side of the valley is Asdrubal Cabrerra turning an unassisted triple play in 2008. There have been 14 of those recorded in all of MLB history, about 1 per 10 years. An extremely low probability event, and nobody tries to claim that, for that one play, Cabrerra somehow raised his true talent level of defense a couple or orders of magnitude.

Or Cammy’s 4 HR game back in the Good Old Days. He’s a decent hitter, and has power, but people don’t insist he did something different that day. It was just his day, things went well. Maybe he was seeing the ball really well, but people accept that as part of the randomness of life.

It’s stuff in the middle that they want an explanation for.

I’d recommend a book: “The Drunkard’s Walk: How Randomness Rules Our Lives”, by Leonard Mlodinow.

I’ve worked for a couple of decades as a consulting statistician, and probably the one thing I can really say about people and statistics is: people don’t have the first goddam clue about statistics. Their brains just don’t deal with ‘em. Mlodinow uses as a terrific example the “Monte Hall” problem, and points out that the overwhelming majority of people don’t get that they’re wrong about it, even after you explain it to them.

The same thing is true in baseball about, oh, what, batting average? ERA? Things everyone is sure mean lots and lots, but which actually mean not very much. It’s no wonder there’s an uphill fight in getting people to accept numerical approaches with actual predictive value: our brains just don’t work that way.

14 consecutive coin flips? That’s amazing!

That’s why they play flip the games coins.

To use a flawed analogy for illustrative purposes – BABIP in aggregate may very well fit a random model because of the size of the population involved; however that doesn’t mean that short term swings in an individual’s BABIP are always random (I realize that’s not what Dave is saying anyway). Maybe the guy hurt his leg and is slower getting to first than when he’s healthy (not random). Or, maybe he really is on an extended unlucky streak (random). But with enough individuals lumped together, circumstances such as injuries should average out, assuming getting injured is a more or less random occurrence (so we can’t effectively use this concept for, say, anything involving Jack Wilson or anyone playing alongside Yuniesky Betancourt).

I agree with Conor, you should link to your other pieces in the sidebar.

Clearly, the outcome of the coin flips is entirely deterministic–it is the confluence of the starting condition of and forces applied to the coin, and the chemical impulses in the calling player’s brain that led him to make the prediction he did.

But those forces cannot be controlled sufficiently accurately as to control the fall of the coin, nor known precisely enough to allow for prediction.

A phenomenon can be both deterministic and “random” at the same time.

First, nothing can happen without a cause, the cause might not be apparent or might be practically impenetrable, but it must be there or else we have creation ex nihilo on our hands and at an absurdly mundane level. Secondly, randomness or chance cannot be that cause.

Max Planck and Werner Heisenberg would disagree with you. As would the entire scientific establishment.

I’m not saying that baseball performance has all that much to do with quantum mechanics, but the flawed assumption you’re starting from is the same one that scientists had wrong for centuries until quantum theory became generally accepted. Randomness certainly can be the cause of a particular result, at least at the level of what we can observe, measure, and control.