Naturally, once the ZiPS elves have finished baking the ZiPS, the first thing I want to do — at least after actually getting some sleep — is to crank out some ZiPS projected standings. So let’s wrap up ZiPS Week (I’m possibly the only person calling it this) by doing the first run of the ZiPS projected standings for the 2020 season.
The methodology I use is not identical to the one we use in our Standings, so there will naturally be some important differences in the results. So how does ZiPS calculate the season?
Stored within ZiPS is the first through 99th percentile projections for each player it projects. I start by making a generalized depth chart, using our depth charts as an initial starting point. Since these are my curated projections, I then make changes based on my personal feelings on who will receive playing time, as filtered by
arbitrary whimsy my logic and reasoning. ZiPS then generates a million versions of each team in Monte Carlo fashion. The computational algorithms, that is, not dressing up in a tuxedo and playing baccarat like James Bond.
After this is done, then ZiPS applies another set of algorithms with a generalized distribution of injury risk, which changes the baseline PAs/IPs selected for each player. Of note is that higher-percentile projections already have more playing time than lower-percentile projections before this step. It then automatically “fills in” playing time from the next players on the list (proportionally) to get to 700 plate appearances for each position and 1458 innings. Read the rest of this entry »