What is ZiPS? Definition, Formula, and Example
ZiPS is a player projection system created by Dan Szymborski that forecasts MLB hitter and pitcher performance using weighted historical data, similarity scores, and empirical aging curves.
What is ZiPS?
ZiPS is a player projection system created by Dan Szymborski that produces forward-looking forecasts for every MLB player and most upper-minors prospects. It outputs a full statistical line — batting average, OBP, slugging, wRC+, WAR for hitters; ERA, FIP, K/9, BB/9, WAR for pitchers — plus a full distribution of outcomes ranging from 80th-percentile breakout to 20th-percentile collapse. ZiPS is published at FanGraphs and is one of the three projection systems (alongside Steamer and Marcel) that feed FanGraphs' depth charts and standings forecasts. The name is a riff on the older PECOTA system; the "Z" is for Szymborski and "iPS" stands for "in-season Projection System."
How ZiPS is calculated
ZiPS blends three ingredients. First, a weighted recent-performance baseline: the most recent season counts heaviest, then the prior two to three years, with weights tuned by position and age. Second, similarity scores — for each player, ZiPS finds roughly the top 100 historical comparables matched on age, position, body type, and statistical profile, then uses how those comps aged to project the current player's trajectory. Third, aging curves empirically derived from MLB history: hitters typically peak from ages 25–28 and decline ~0.5 WAR per year after 30; pitchers age more chaotically. ZiPS also applies park factors, league offensive context, and regression to the mean for unstable rate stats (BABIP, HR/FB, strand rate). For prospects, ZiPS uses minor-league translations that adjust performance for league level, age relative to level, and park.
Worked example
Heading into 2024, ZiPS projected Aaron Judge for a .279/.408/.580 line with 50 home runs, 7.0 WAR, and a 169 wRC+ in 138 games. Judge actually hit .322/.458/.701 with 58 HR and 11.2 WAR over 158 games — well above his 80th-percentile band. On the bust side, ZiPS projected Anthony Rendon for a .254/.341/.405 line in 2023; he posted .236/.361/.318 in 43 games before injury — slightly below the median but well inside the projected range. ZiPS calibrates so that roughly 80% of player-seasons fall between the 20th and 80th percentile bands; outliers like Judge's 2024 are by design uncommon.
Why ZiPS matters
Front offices use ZiPS (and similar systems) for arbitration models, trade-value calculators, and free-agent contract sizing — multiplying projected WAR across each contract year by the current $/WAR rate (~$9M in 2025). Fantasy managers use ZiPS for draft prep because it accounts for playing time, park, and aging, all of which simple "last year's stats" rankings ignore. DFS players cross-reference ZiPS rest-of-season projections against current hot/cold streaks to find regression candidates. Bettors use the FanGraphs ZiPS-powered standings as a baseline for win totals and division odds.
Limitations and common misconceptions
ZiPS is not omniscient. It regresses to the mean aggressively, which means it will systematically under-project true breakout seasons and over-project veterans on the decline. It does not know about offseason mechanical changes, new pitches, or undisclosed injuries — the 2023 Ronald Acuña Jr. 40/70 season was outside every system's 90th percentile. ZiPS also struggles with extreme outliers (Shohei Ohtani's two-way line, knuckleballers, position changes mid-career). And critically, "ZiPS projects 4.5 WAR" is a median — the actual range of likely outcomes spans roughly ±2 WAR.
Related terms
In Legends Deck
ZiPS-style projections feed our season-ahead card variants. When you open a pack featuring a "ZiPS 2026" parallel of a player, the ratings reflect the median projected line for that season rather than backward-looking stats — meaning a high-comp prospect like Roman Anthony can have a strong projection card before his MLB debut even arrives.