OOPSY 2026 Top 100 Prospects
This article unveils OOPSY’s first WAR-based Top 100 prospects list.
Broadly put, OOPSY (https://blogs.fangraphs.com/yet-another-projection-system-a-brief-introduction-to-oopsy/) mirrors the other projections systems at FanGraphs, but it uses its own ingredients, including its own aging curves, regression amounts, recency weights, major league equivalencies, and park factors. In terms of accuracy, it has held its own (https://blogs.fangraphs.com/reviewing-oopsys-debut-season/) with the other projection systems, including when projecting rookies.
Since 2024 (https://fantasy.fangraphs.com/there-is-such-thing-as-a-pitching-prospect-the-top-10-by-projected-era-at-peak/) , I have published (https://fantasy.fangraphs.com/the-top-30-projected-hitting-prospects-entering-2024/) OOPSY’s top prospect lists over at RotoGraphs with more of a fantasy focus, ranking pitchers by peak ERA and hitters by peak wRC+. In 2025, I began incorporating average fastball velocity into my prospect pitching projections, using data from The Board (https://www.fangraphs.com/prospects/the-board) , as well as Stuff+, provided by Eno Sarris (https://www.nytimes.com/athletic/7010771/2026/02/03/mlb-starting-pitcher-rankings-2026-fantasy-baseball/) , where possible. Midway through 2025, I started (https://fantasy.fangraphs.com/oopsys-top-60-prospects-final-2025-update/) accounting for EV90 in my prospect hitting projections, using data from Prospect Savant (https://prospectsavant.com/leaders) ; I also include bat speed (https://baseballsavant.mlb.com/leaderboard/bat-tracking) where data permits. And now that OOPSY accounts for defense (https://x.com/RosenJordanBlum/status/2019057021518045369?s=20) as well as baserunning, I can rank prospects by projected WAR, to theoretically align more closely with the valuations used by major league organizations.
Before getting into the rankings, I want to discuss my approach to projecting defense. Previously, OOPSY borrowed its defensive projections from Steamer; now I project it myself. For major league players, the defensive runs above average (https://library.fangraphs.com/defense/def/) projections are based on a player’s fielding run value from Statcast (https://baseballsavant.mlb.com/leaderboard/fielding-run-value) , aligning with how FanGraphs’ WAR accounts (https://blogs.fangraphs.com/2024-fangraphs-war-update/) for defense; OOPSY also uses a positional adjustment (https://blogs.fangraphs.com/explaining-win-values-part-three/) , in keeping with FanGraphs’ approach.
The absence of publicly available Statcast fielding data for minor leaguers necessitates a different approach when it comes to prospects. I use a scouting-based approach, leveraging the listed position and Fielding grades from our prospect team’s essential work on The Board (https://www.fangraphs.com/prospects/the-board) . Using scouting grades to help formulate rookie projections is an old idea (https://www.insidethebook.com/ee/index.php/site/comments/successandfailureratesoftopmlb_prospects/) in the sabermetrics community. For players not listed on The Board, I’ve assigned a primary position based on where they played the most in 2025, using data provided to me by Thomas Nestico (https://x.com/TJStats) , and formulated a naïve projection that assumes the player will be slightly below average at their primary position at the major league level. For players included on The Board, listed position and Fielding grades work well to formulate a simple defensive projection for rookies, with a 10-point increase in Fielding grade associated with a five-run increase in fielding run value above average per 4,000 outs (i.e., per full season):
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