One of the things you have to get used to when you work with projections is being wrong. Like, All. Of. The. Time. While I’d like to believe that the projections are accurate and it’s just real life that mucked things up, that isn’t quite how they work. There are always events you didn’t see coming, assumptions you made erroneously, and just plain old irreducible error, all of which are going to thwart you.
On a basic level, you’re supposed to be wrong. Imagine a world in which you knew, for an exact fact, that every team was a coin flip to win every game. With this perfect knowledge, you’d still expect nearly a quarter of the league to win either 73 games or fewer, or 89 games or more, through nothing but luck. For the math-inclined, this is a hypergeometric distribution, not a binomial one; the coin flips are not independent because the win totals will still add up to 2,430 and one team’s win invariably is another team’s loss. Here’s a quick table for some of the win totals, showing the probability of a team winning exactly X games and how many of the teams you’d expect to have won up to X games:
Win Probabilities, Major League Coin-Flipping