One of the analytics leads for the Red Sox came to Harvard to give a presentation. I asked if he could quantify the effects analytics was having compared to the conventional wisdom developed over the course of 150 years of pro baseball.

He thought that analytics was changing the probabilities of discrete events by single digits. Essentially, nobody was doing anything wrong, there were just optimizations that were/are available.

Remember that the book/movie is about the A’s, who were eliminated in the first round of the baseball playoffs.

Each baseball game is so high variance that even a 5 or 7 game series is still largely a crap shoot. Unlike the NFL or NBA, any MLB team that makes the playoffs has a puncher's chance to with the title. It's one of the beauties of the game. (Unless you're a Dodgers fan.)

I think part of the point though was that the As were performing far better, and progressing further than you'd expect given a dramatically lower budget for players.

If you can have a competitive team filling 80% of the seats as your competitors at 50% the payroll..

Before Moneyball there were other controversial stats, largely driven by Bill James. By and large they had the same footprint you're describing. In any particular game they were such a small effect as to be meaningless. But of the course of a season? That could be the difference between playoffs or not.

The one that pops into mind offhand was putting the "cleanup hitter" as leadoff, even though at the time "leadoff hitter" was a very specific physical archetype as was the "cleanup hitter". Yet the latter was often the best hitter on the team, and by putting them top of the batting order they'd get more at bats over the course of a season.

>He thought that analytics was changing the probabilities of discrete events by single digits.

That is actually huge in baseball. As an example, the player who was least likely to get a hit last year did it in 19.6% of their at bats (this typically isn't represented as a percentage and would instead be listed as .196 batting average), while the player who was most likely to get a hit did it 33.2% of the time, meanwhile the league average was 24.3%. That means "changing the probabilities of discrete events by single digits" is what separates the average player from the outliers at both the top and bottom of the talent pool.

Famously, Billy Bean said "his (stuff) doesn't work in the playoffs." This is because top end talent still generally wins championships. The regular season is a slog and you can do very well by always beating the teams you should beat. But in the playoffs when everyone is giving maximum focus and effort, the talent gap is much more important than in the regular season. In basketball, I think of teams like this year's Cavaliers or the Budenholzer era Hawks. These teams won a lot of regular season games, but never felt like a legitimate threat to win the championship.

That might be true in-game (though I suspect the marginal gains compound fairly strongly) but I think the numbers when applied to recruitment and avoiding costly mistakes are much more impactful.