Lessons from Moneyball

Beane and the A's were mostly focusing on offense, because that's were they could find value. It's significantly harder to find value in pitchers, and pitchers can help damper some of the "luck" factors in the postseason, though it's very much open to randomness.

Modern baseball management is focused on building your team to win enough regular seasons to make the postseason, and then hope luck falls in your direction. If you can couple that with great starting pitching, you can reduce the amount of luck you need.

I'm not sure how relevant the techniques in Moneyball still are. At this point, every team is looking at Sabermetrics, and some of the high-value stuff isn't there any more. For example, getting on base isn't worth as many runs in 2011 as it was in 2002 because there are less home runs hit.

Reading the book, Moneyball, I came away with the conclusion that the success of Beane's system boiled down the fact that they started measuring everything and making empirical decisions based on data rather than emotion or "gut" checks. In turn, this let them find value where others saw failure. In a competitive environment with limited resources (players Beane's instance) this system will work up to the point where few, if any, try it--meaning lots of overlooked value exists.

One point at the end of the book was that the Red Sox, when they hired Theo Eptstein as their GM, brought in one of Beane's assistants to implement the system the A's were using. As more teams start using it, the quantity of undervalued players decreases because everyone starts valuing the same thing.

Start up takeaway: Measure everything and make decisions based on empirical results instead of "gut" checks. That's really what it boils down to. I'm not just talking about the front-end stuff like landing pages, conversion rates, clicks, etc. Measure it all, response times, database operation times, network transmission time, average request size, whatever you can get your hands on. Having all that data will allow you to make informed decisions and identify places for improvement to increase value.

That's my takeaway.

[1] http://en.wikipedia.org/wiki/Billy_Beane

What I find most interesting about the story is the different effect it has on people. Business types see it as "Take a great risk and it'll pay off (literally)." Science types see it as "Math works".

The reality is, you just have to do what you want to do and not care if other people tell you you're crazy. Was a situation like Moneyball an exception to the rule? Hell yes. But with out those 1 in 1000 exceptions to the rule we'd have very little to show for 50 thousand years on the planet.

I thought the real lesson was "massively outperform the limits of your shitty resources beyond anyone's expectations, by thinking outside the box and concentrating on algorithms and data modeling; and still not succeed. Then if someone is impressed and offers you more personal compensation than you can imagine, to do the same thing but for them, while actually being given enough resources to actually have a chance with it, then you go and fucking do it."

The startup analogy is easy: if you are solely responsible for running a free service with a million users on $300/month hosting budget, and you almost do it by inventing amazing algorithms, but the service still lags and sucks, but is almost there, then when Amazon makes you an offer to come and do the same thing for them you fucking take it.