These 2023 projections are guaranteed to be awful, wrong in many ways ranging from tragic to comic. But despite being absolutely premature and littered with horrible misses, projected standings at this point are actually quite useful, and useful is the best description any kind of predictive model can strive for. Standings at this point are a poor predictor of the 2023 season — and even the eventual 2023 projections themselves — but what they are able to do is give a “state of the union” estimate for each team. These standings represent the best estimates ZiPS can make at this point about where a team sits in the league’s pecking order, based solely on the players currently under contract with the team. It’s hard to get where you want to go if you don’t know where you’re starting.

The methodology I’m using here is the same one I use in the regular season, and as such, it isn’t identical to the one we use in our Projected Standings. So how does ZiPS calculate the upcoming season? Stored within ZiPS are the first through 99th percentile projections for each player. I start by making a generalized depth chart, using our Depth Charts as an initial starting point. Since these are my curated projections, I make changes based on my personal feelings about who will receive playing time, as filtered through arbitrary whimsy my logic and reasoning. ZiPS then generates a million versions of each team in Monte Carlo fashion — the computational algorithms, that is (no one is dressing up in a tuxedo and playing baccarat like James Bond).

After that is done, ZiPS applies another set of algorithms with a generalized distribution of injury risk, which change the baseline PAs/IPs selected for each player. Of note here is that higher-percentile projections already have more playing time baked in than lower-percentile projections before this step. ZiPS then automatically “fills in” playing time from the next players on the list (proportionally) to get to a full slate of plate appearances and innings. Read the rest of this entry »

The ghost of 18th-century statistician Thomas Bayes did not see his shadow, so we are about to launch this year’s 2023 ZiPS projections. As usual, this is a space to talk about some of the basics, answer a few common questions, and wax philosophic about the very nature of predicting baseball futures. A lot of the background can be found by reading MLB’s glossary entry for ZiPS, which gives most of the basics except for the origin story.

ZiPS is a computer projection system I initially developed in 2002–04; it officially went live for the 2004 season. The origin of ZiPS is similar to Tom Tango’s Marcel the Monkey, coming from discussions I had with Chris Dial, one of my best friends (my first interaction with Chris involved me being called an expletive!) and a fellow stat nerd, in the late 1990s. ZiPS moved quickly from its original inception as a reasonably simple projection system, and now does a lot more and uses a lot more data than I ever envisioned it would 20 years ago. At its core, however, it’s still doing two primary tasks: estimating what the baseline expectation for a player is at the moment I hit the button, and then estimating where that player may be going using large cohorts of relatively similar players.

Why is ZiPS named ZiPS? At the time, Voros McCracken’s theories on the interaction of pitching, defense, and balls in play were fairly new, and since I wanted to integrate some of his findings, I wanted my system to rhyme with DIPS (defense-independent pitching statistics), with his blessing. I didn’t like SIPS, so I went with the next letter in my last name, Z. I originally named my work ZiPs as a reference to one of my favorite shows to watch as a kid, CHiPs. I typoed ZiPs as ZiPS when I released the projections publicly, and since my now-colleague Jay Jaffe had already reported on ZiPS for his Futility Infielder blog, I decided to just go with it. I never expected that all of this would be useful to anyone but me; if I had, I would have surely named it in less bizarre fashion. Read the rest of this entry »