How a lot WAR does FanGraphs mission Ronald Acuña Jr. for in 2026? It’s a extremely simple query. It ought to be particularly simple now that all of our projections are out. However because it seems, it’s much less clear lower than it sounds at first, and clarifying it has two advantages. First, it’ll enable you higher perceive our projections. Second, it’s enjoyable to play with math. So buckle up: We’re doing arithmetic.
First, let’s decide on what the “FanGraphs projection” even is. Right here’s the related part of Acuña participant web page:
Eight projections, every with tons of numbers. That’s lots! However once I say the “FanGraphs projection,” I’m referring to the primary inexperienced row, the FanGraphs Depth Charts projection or FGDC. That’s the top-line projection we use anyplace on the web site that pulls in projections to make predictions. Whenever you see “2026 (Proj),” it’s utilizing that quantity until in any other case acknowledged.
That’s settled then, proper? We’re projecting Acuña for five.4 WAR. Why did I’ve to waste your time with an article about it? It has to do with how we make that projection, a course of you’re about to find out about, in all probability in additional element than you needed.
Projection methods are, at their core, fairly easy issues. They could get there in difficult methods, however they’re all attempting to guess how good at baseball a given participant goes to be sooner or later, they usually all strive to do this by predicting the outcomes that that participant goes to accrue on the sector. When you’ve got a projection system, you’ve got projections for homers, singles, strikeouts, walks, stolen bases, and so forth, in addition to a projection for plate appearances, so that you by definition even have a per-plate look projection for every of these statistics.
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We don’t use a single mannequin in our official FGDC projections. We take a 50/50 mix of the per-plate look projections from ZiPS and Steamer. These projections work very well! I’m not going to enter the specifics of validation right here, however multi-model predictions constructed from good fashions are likely to work properly, and that’s what we use. The speed statistic projections we spit out are pretty much as good as we are able to presumably get them, not less than in our estimation. We discard the taking part in time projections from ZiPS and Steamer, although, as a result of we now have a separate course of for projecting taking part in time.
Going from that blended charge statistic projection to the numbers you see on the web site requires an excellent taking part in time estimate. Fortunately, that’s what Jason Martinez and Jon Becker do at RosterResource. They mission taking part in time for everybody in baseball; we multiply that taking part in time by the per-plate look outcomes, and that offers us a projected batting line. It additionally offers us projected baserunning and protection, to not point out all of the related metrics for pitchers, however for immediately’s instance, we’ll be specializing in Acuña’s batting statistics. You’ll be able to think about the identical course of taking part in out in each aspect of WAR.
How does the RosterResource staff assign taking part in time? They fill out every roster with their greatest guess of what that staff’s taking part in time will appear like. They don’t forecast accidents – how may they? Our depth chart projections appear like a depth chart, naturally sufficient. The starter on the depth chart is projected for a full-time function. That’s simply how it’s.
This makes good logical sense, although it would take a second to wrap your head round. Why not attempt to mission the imply consequence, with some likelihood of harm? Principally as a result of that’s not what individuals are truly on the lookout for in projections. “What number of dwelling runs do you mission Aaron Decide to hit this yr?” inherently assumes a wholesome season. “Solely 15, as a result of I mission him to get harm on Might 7” can be a extremely unusual reply to that query. If you happen to’re questioning what an on a regular basis participant’s projection seems like, “in a full season” is an unstated norm. The one exception to this rule is a sound one: presently injured gamers see their taking part in time lowered by the estimated time it would take them to return from harm. Zack Wheeler, for instance, is down for 127 innings this yr, as a result of he gained’t be prepared for Opening Day. For presently wholesome gamers, although, we assume continued well being.
Take Acuña’s projection, for instance. He’s averaged slightly below 500 plate appearances per full season to this point, with a number of catastrophic accidents slowing him down. If he reaches his FGDC projected 651 plate appearances, it might be the third-most he’s taken in his profession. However we’re not attempting to guess how properly Acuña’s knee would possibly maintain up in our preseason projection. We’re projecting what he’ll appear like if he performs a full season. That’s what folks need, in my estimation, the factor they’re truly asking for. Possibly not each individual. However within the combination, I believe that’s clearly the most typical use case for a projection system, probably the most truthful method to reply the query of how good a man goes be, which is what these fashions have been constructed to handle.
If you happen to’ll enable me a short playoff odds tangent, I’ve truly spent a great deal of time fascinated by how this method interprets to odds projections. And over-allocating taking part in time to the highest gamers on this method nonetheless works properly in our playoff odds mannequin. We simply add up the person contributions of each participant on a staff to determine how a staff tasks to play, then toss these outcomes into the BaseRuns formulation, which does a superb job of turning team-level outcomes into run scoring estimates. Certain, projecting Acuña for 651 plate appearances is somewhat optimistic, however we’re symmetrically optimistic. Now we have Mike Trout down for his most video games since 2019. Now we have Alex Bregman down for 679 plate appearances, a quantity he’s solely hit as soon as within the 2020s. It is a function, not a bug: We mission groups at full energy within the FGDC numbers. That playoff odds mannequin isn’t even taking a look at WAR (properly, the WAR-based odds mannequin is, however that’s a narrative for an additional day). It really works completely properly merely by taking a look at consequence statistics.
Our odds already deal with in-season accidents shortly; if a participant will get harm, their taking part in time declines to replicate that harm. We’ve additionally experimented with accounting for depth and likelihood of harm in our playoff odds. That methodology feels promising, and I’ll have extra on it as we get nearer to the season. However that’s a small adjustment to an already-good mannequin. The prevailing playoff odds mannequin already handles the optimistic taking part in time allocation properly, one thing we’ve examined on a number of events.
Alright, let’s get again to WAR. The FGDC projections for dwelling runs, singles, and the like are an excellent estimate of what Acuña’s statistical outcomes will appear like if he performs a full season, of that I’m certain. However WAR isn’t an on-field statistic. It’s a derived statistic we add later that relates a participant’s contributions to what a replacement-level participant would do. Throughout the season, that is easy to calculate. We take precise outcomes and use them to outline alternative degree. Everybody’s efficiency will get measured relative to that league-wide alternative degree. The system works in the way in which you’d count on. It reduces all of the completely different dimensions of efficiency right into a single foreign money of runs, compares these runs to a baseline set by taking a look at league-wide manufacturing, and turns these inputs into WAR.
Projection methods don’t have that luxurious. They don’t know what the league common outcomes will likely be in 2026. They mission a WAR determine, after all, however that’s relative to a baseline that they calculate of their fashions, based mostly on how that specific system handles taking part in time allocation. It’s solely pure: To calculate wins above alternative, you must know alternative.
On the particular person mannequin degree, that’s wonderful. However we’re not utilizing a person mannequin. We combination fashions at a per-plate look degree after which assign our personal completely different taking part in time, which is usually meaningfully completely different than what both Steamer or ZiPS used. Once more, we try this on objective. We achieve this as a result of it helps create team-level projections the way in which we would like, and helps reply the “What would this participant appear like in a full season?” query that almost all everyone seems to be asking.
How completely different would the scoring setting be if each star performed as ceaselessly as our Depth Charts taking part in time suggests? Let’s cease for an instance. Take into consideration the main league hitters who performed in 2024 and likewise in 2025. If you happen to take their 2024 outcomes and weight them by their 2025 taking part in time, you get a .311 wOBA. In different phrases, the expertise degree of the gamers who performed in 2024 and 2025, in 2024 phrases, is a .311 wOBA.
Attempt that once more with our Depth Charts projections for 2026, and also you’ll get one thing completely different. The expertise degree of the gamers who we’re projecting to seem in 2026 – their 2025 wOBA weighted by their 2026 taking part in time – comes out to a .316 mark. That’s a significant distinction, despite the fact that it sounds small. Over 600 plate appearances, that’s an additional three or so runs. Over the 193,000 or so plate appearances that the gamers coming back from 2025 to 2026 are projected to accrue, it’s extra like 800 runs. In our hypothetical 2026 world, the one which we construct by taking charge statistics from the fashions and including our personal taking part in time, the offenses are all good.
The pitching staffs are all good too, after all. However our Depth Charts rendition of expertise doesn’t measure this interplay. The hitters are projected to be actually good, as a result of their projections are towards a decrease baseline. The pitchers are additionally projected to be actually good, as a result of we do the identical sort of over-allocation of taking part in time to stars on that aspect of the ball. However since we simply take Steamer and ZiPS charge statistics relatively than doing a little sort of adjustment for opposition on our finish, we don’t dock any batters for his or her anticipated more durable competitors. The result’s a sort of Lake Weobegone projection: We predict that each batters and pitchers will likely be above common in 2026.
That sounds fairly bizarre, however it’s not an issue in terms of projecting the season. Once we run our playoff odds, we take staff runs scored and runs allowed estimates produced by our depth charts, flip that right into a profitable proportion, and thus get a measure of staff energy that doesn’t account for opposition. To simulate a sport, we simply examine the staff strengths of the 2 groups taking part in. Since everyone seems to be over-estimated and we’re solely evaluating groups comparatively, the projections nonetheless work correctly. We is likely to be projecting a way more gifted league in 2026 than in 2025, however there aren’t any additional wins to go round on the finish of the day, and since we’re measuring everybody relative to their opposition, it simply works.
There’s some bizarre math stuff right here that you must maintain in your head. There’s no manner that every one of our WAR projections could be proper. It’s actually not possible. There’s a set quantity of WAR to go round yearly. Now we have our hitters down for greater than that. If we’re truly proper about taking part in time, the baseline degree will merely be larger, and the identical quantity of offensive contribution will simply be value fewer wins above alternative.
Why then don’t we simply alter the alternative degree baseline up in our FGDC projections? It feels like that might be the best resolution. However for those who cease and give it some thought, that’s positively not the precise factor to do. If we alter the baseline larger, we’re implicitly saying one thing in regards to the worth of manufacturing in 2026. The speed stats? These projections are good, and we’re not touching them. If we alter the mapping between that offensive manufacturing and WAR, although, we’re beginning to do one thing that is not sensible.
What’s it going to appear like if Ronald Acuña Jr. performs a full season in 2026? We predict that it’ll appear like a .286/.393/.512 slash line with 31 homers. If he accrues these numbers, what do we expect his WAR will likely be? Our 5.4 estimate might be fairly good, despite the fact that the way in which we get to it appears bizarre. That’s as a result of the precise noticed expertise degree within the majors in 2026 isn’t going to be anyplace close to what our purposefully-optimistic taking part in time projections would counsel.
Right here’s the true query individuals are asking after they take a look at a WAR projection: How worthwhile will this participant be, relative to an affordable league common baseline, if he performs a complete season? If we re-centered our preseason WAR estimates across the larger common degree of competitors that we mission, we’d be answering a unique query: How worthwhile will this participant be if he and likewise each different star in baseball performs a complete season? That second query isn’t the one which’s prime of thoughts. Clearly, then, that methodology wouldn’t work.
The query we reply, the one which I believe matches what folks need, has issues of its personal. Our outcomes are not possible by nature. They gained’t be true within the combination. Happily, although, none of these issues truly matter all that a lot in the true world. Our projections nonetheless work as a result of they take a look at relative staff energy. The Depth Charts would possibly allocate an excessive amount of WAR to each staff, however it doesn’t allocate an excessive amount of WAR to any star: Every projection is that star’s baseline consequence in a wholesome season, precisely what we would like it to be.
I can inform, studying again over this text, that it’s going to be a complicated one. It’s onerous sufficient to speak about how WAR works after we’re taking a look at already-accrued outcomes; layering in projections and re-centering and allocation clouds the matter even additional. The excellent news is that the takeaways are easy. Our projections do an excellent job of determining relative staff energy. Additionally they do an excellent job of projecting participant expertise degree. They take a number of mathematical shortcuts to get there, however these shortcuts don’t intrude with both of the 2 principal issues the projections are for: answering the questions “How good will this man be?” and “Will my staff make the playoffs?”