For the 22nd consecutive season, the ZiPS projection system is unleashing a full set of prognostications. For more information on the ZiPS projections, please consult this year’s introduction, as well as MLB’s glossary entry. The team order is selected by lot, and the first team up is the Philadelphia Phillies.

Batters

The Phillies offense kept right on rolling for another season, once again scoring nearly 800 runs, and finishing with a wRC+ of 109, the team’s best total during this era. As expected, Philadelphia’s rotation was terrific, but the offense contributed more than its fair share to the team’s 96 wins, the second most in baseball.

There are worries lurking on the horizon, however. Trea Turner had what was certainly his best season in Philadelphia, but he’s entering his mid-30s, a very dangerous time for a middle infielder. I was actually surprised to see the drop-off in the ZiPS projection for Turner, but noticed that Steamer was basically projecting the same thing. Also entering his mid-30s is Bryce Harper, who has solidified his chances of a plaque in Cooperstown, but appears to now be off his peak years. Kyle Schwarber and J.T. Realmuto are free agents, and I think both stand a real chance of returning to Philadelphia, though both are also entering the likely decline phases of their careers; indeed, Realmuto probably already has. Read the rest of this entry »

As soon as one story in baseball ends, another begins. And so, with the 2025 season dissipating into silence as the champions hoist the World Series trophy, its remnants seed the next phase of the sport’s existence out from the quantum foam. The four months between now and Opening Day feel like an interminable gap, but we have the Hot Stove League to keep the MLB baseballmatic universe rolling. That means, as has been the case for nearly a quarter of a century now, it’s time for me to start rolling out the ZiPS projections for next season.

For those new to my projections, ZiPS is a computer projection system I initially developed in 2002–04. It officially went live for the public in 2005, after it had reached a level of non-craptitude I was content with. The origins of ZiPS are similar to Tom Tango’s Marcel the Monkey, coming out of discussions I had in the late 1990s with Chris Dial, one of my best friends (our first interaction involved Chris calling me an expletive!) and a fellow stat nerd. ZiPS quickly evolved from its original iteration as a reasonably simple projection system, and it now both 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.

So 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 decided (with his blessing) that the name of my system would rhyme with DIPS (defense-independent pitching statistics). I didn’t like SIPS, so I went with the next letter in my last name. I originally named my work ZiPs as a nod to CHiPs, one of my favorite shows to watch as a kid, but I mis-typed 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 chose to just go with it. I never expected that all of this would be useful to anyone but me; if I had, I would surely have named it in less bizarre fashion. Read the rest of this entry »