April Mailbag: You Asked, We Dug Into the Data

Welcome to the first mailbag of the 2026 season. We got some great questions for you all. Let's get into it.

What is going on with Dylan Beavers?

Question from Vivi: "I feel like he was so much better last year. Like obviously his AVG is down a little, and his defense seems to have gotten worse, but it's the walks that concern me. I know it wasn't really possible for things to continue at the same rate they were last year, but it just feels weird that he has less somewhere between a quarter and a third of the walks that he had in '25 in only half the games so far. I really appreciated his patience last year, where'd it go?"

This is a great question, and when we dug into this, we realized this was a very astute observation. The walks are the story with Beavers, not the batting average. Let's discuss what we found.

The Surface Numbers

Here's the side-by-side comparison between Beavers' debut in August 2025 and his 2026 so far (via FanGraphs and MLB Stats):

The OBP is trending lower by 83 points. The batting average has only dropped 16 points. What's going on with that gap? Almost entirely a difference in walks. He went from a 19% walk rate, which would've been top-20 in baseball over a full season, to 10.8%, which is roughly league average. His strikeout rate actually improved slightly (this stat has stabilized). So, it's not that he's whiffing more. Something else may be changing.

Before we go further, let's talk about what we can actually trust in these numbers. Every stat has a stabilization threshold, which is the point at which we have enough data for the stat to be more signal than noise. We discuss this in our A Guide to Statistical Stabilization and Regression, and FanGraphs has published these thresholds. They matter a lot here:

His K% is reliable in both seasons: that improvement from 26.3% to 24.6% is real (although subtle). His 2025 walk rate (19%) had just barely stabilized at 137 PA, meaning it can be considered more of a genuine reflection of his approach. But his 2026 walk rate (10.8%) hasn't stabilized yet at only 65 PA, it could still move significantly in either direction. At this point, we can't firmly say this is a decline yet in 2026, but it's trending in that direction.

The batted ball rates (GB%, LD%) haven't stabilized in either year. That 54.8% ground ball rate is alarming, but it could be noisy. Then again, both years are below the threshold, so we're really comparing two unstable samples against each other. The swing data (which stabilizes quickly because it's measured per pitch, not per PA) is the most trustworthy thing we have here. And the swing data is clear.

The Swing Data Tells the Story

This is where it gets interesting. FanGraphs tracks plate discipline metrics: how often a hitter swings, where he swings, and what happens when he does. Here's the year-over-year comparison:

From this breakdown, you can see some telling stories. Beavers is swinging seven percentage points more often than he did last year. His chase rate (swings at pitches outside the zone) jumped from 19.7% to 24.7%. In 2025, he was one of the most disciplined hitters in the lineup. In 2026, he's taking a more aggressive approach and pitchers seem to be adjusting accordingly.

The Batted Ball Problem

It's not just that he's swinging more. What happens when he makes contact also seems to be changing (batted ball data via FanGraphs, Statcast metrics via Baseball Savant):

Through 25 games in 2026, there's some noticeable trends between what we saw in his debut last year and what we are seeing so far this season.

A word of caution here: as we noted in the stabilization table, ground ball rate needs about 80 balls in play to stabilize, and Beavers only has ~42 BIP in 2026. Line drive rate requires an even larger sample, it takes roughly 600 BIP to stabilize, making it one of the noisiest stats in baseball. So the specific percentages (54.8% GB, 16.7% LD) should be treated as directional, not gospel. That said, when you pair the batted ball numbers with an 8-degree drop in average launch angle, a stat that stabilizes faster, the ground-ball trend has a more weighted argument here in the early goings of 2026.

The Walk Distribution

One more thing that stands out. In 2025, Beavers drew at least one walk in 19 of 35 games (54%) and had multiple walks in 6 games. He had a 3-walk game against Toronto. He was patient in the majority of his starts.

In 2026? He went his first 9 plate appearances of the season without a single walk (0.0% BB rate in March). April has been better so far, 7 walks in 56 PA. However, most of his zero-walk games are getting drowned out. The walks aren't spread evenly across games the way they were in 2025. They come in clusters now, often in the same game, instead of being a consistent part of his approach.

The Defense

Vivi mentioned the defense, and they're right there too. In 2025, Beavers posted zero Outs Above Average in left field and +2 Defensive Runs Saved in right field across about 300 innings (Baseball Savant). Solid. In 2026, he's already at -3 OAA in just 78 innings across three outfield positions (LF, CF, RF). It's a small sample, but the fact that he's being shuffled around three positions instead of settling into one isn't helping his routes or reads.

So, What's the Diagnosis?

Beavers plate discipline is trending towards a more aggressive profile so far in 2026. Is he pressing? Is this a new approach? It's still too early to tell for sure.

Was a 19% walk rate sustainable? As Vivi mentioned, probably not over a full season, though it had just barely crossed the 120 PA stabilization threshold, so it wasn't a total mirage either. But the directional swing to 10.8% is an over-correction, and at only 65 PA it hasn't stabilized yet. If he can find a middle ground, somewhere around 14-15%, the underlying contact data suggests he'll be fine. His xBA is .220 (Baseball Savant expected stats), his hard-hit rate is actually up at 35.7%, and his K% improved. The raw ability is still there. He just needs get back to taking a more patient approach at the plate.

The bottom line: Vivi's instinct was right. The walks are the whole story, and the data says it's an approach issue, not a talent issue. The patience that made him so exciting and valuable in 2025 is still in there somewhere. He just needs to trust it again.

Do the Orioles swing at too many balls after falling behind in the count?

Question from Andrew: "I'm not sure what analytics there are for swing decisions and such, but it feels like once opposing pitchers get to an 0-1 count, they don't need to throw another strike in the at bat to get Orioles hitters out. The majority of them will swing at balls and get themself out. Is there any data that can back up this observation?"

There is fortunately a lot of data out there to look at this. Another great question. And Andrew's instinct is largely correct. For this analysis, we pulled pitch-by-pitch data from Baseball Savant's Statcast Search for five American League teams and cross-referenced with FanGraphs' team plate discipline leaderboard.

The 0-1 Count Is a Trap Door

Let's start with the big picture. Using Baseball Savant's pitch-level data for the 2026 season through April 22nd:

It makes intuitive sense, but half of all Orioles plate appearances pass through an 0-1 count. 443 out of 881 total PA (50.3%). That's roughly league average. But what happens after those at-bats reach 0-1 is where Baltimore separates from the pack:

Also quite intuitive, but when Orioles hitter falls behind 0-1, the strikeout rate more than doubles compared to at-bats where they don't. A K% of 35.2% is quite high, relative to other teams we compared for this analysis. The walk rate gets cut nearly in half. And the batting average drops 18 points.

How Does That Compare to Other Teams?

I pulled the same pitch-level data from Baseball Savant for four other American League teams: the Yankees, Blue Jays, Red Sox, and Guardians over the same date range. I thought that these five would be a relatively good mixed sample of how they are performing so far in in 2026. The Yankees and Guardians off to a good start, Red Sox and Blue Jays, not so much. Here's how each team's strikeout rate changes when they go through an 0-1 count:

Every team's K% jumps after falling behind 0-1, that's expected. But the Orioles have the largest jump in this sample at 10.2 percentage points. Their overall K% is already the highest among these five teams, and it inflates the most when behind. For comparison, Toronto only sees a 5.9-point jump.

The Real Problem: 0-2 Counts

Interestingly, through a small sample size here so far in 2026, at the 0-1 pitch itself, Orioles hitters are actually less chase-happy than you might think. Their chase rate (swings at pitches outside the zone) at 0-1 is 25.4%, which below the five-team average of 30.7%.

The problem is what happens when they do take a strike at 0-1 and fall to 0-2. Once the count reaches 0-2:

Half of all plate appearances that reach an 0-2 count end in a strikeout. That's trending up from 43.3% at this point last year. And the chase rate at 0-2 is also trending up 8.3 percentage points year-over-year. It's still early, and the sample is small, but pitchers have may be catching on that if they can get ahead 0-2, Orioles hitters will expand the zone and swing themselves out.

What Are They Chasing?

At 0-2, pitchers throw out of the zone on roughly 70% of their pitches to Baltimore hitters. Here's what they're throwing and how the Orioles are responding:

Changeups and curveballs are the biggest bait, both are thrown out of the zone over 76% of the time at 0-2, and Orioles hitters are chasing them at nearly a 50% clip. Sliders are even more devastating when they do swing: a 55% whiff rate. The fastball is the one pitch where they're relatively disciplined (32.5% chase rate), but pitchers know this and are using it less.

The O-Contact Problem

There's a compounding issue that FanGraphs' team-level plate discipline data reveals. It's not just that Orioles hitters chase, it's that when they chase, they don't make contact.

Baltimore's O-Contact% (contact rate on swings at pitches outside the zone) is 57.9%, which ranks tied for 3rd worst in MLB. For context:

Compare that to the Rays at 72.3%. When Tampa Bay chases, they at least foul pitches off and keep the at-bat alive. When the Orioles chase, they whiff. At 0-2 specifically, Orioles hitters swinging at pitches out of the zone whiff 45.3% of the time, meaning nearly half of their chases at 0-2 are the final swing of the at-bat.

The Bottom Line

Your observation is backed up by the data, and there's even more information to show for this trend:

1. At 0-1, the Orioles are actually relatively disciplined. Their chase rate (25.4%) is below the five-team AL average.

2. But when they reach 0-2, the discipline vanishes. Their 0-2 chase rate (37.4%) is trending up 8.3 percentage points from last year, and half of all PAs that reach 0-2 end in a strikeout.

3. When they do chase, they whiff. Their O-Contact% (57.9%) ranks 3rd worst in baseball. They're not fouling pitches off and extending at-bats.

4. The 2026 team is more patient overall (BB% up, Swing% down), but the patience evaporates under two-strike pressure which is the worst possible time to lose it.

The fix isn't to stop swinging altogether after 0-1. It's to maintain the same discipline at 0-2 that they show at 0-1 (i.e. take the breaking ball in the dirt, foul off the borderline pitch, and make the pitcher throw a strike). Taylor Ward does this. Most of the rest of the lineup doesn't.

How often do infielders commit errors when placed in the outfield?

Question from Dave: "When a player is predominantly an infielder by trade how often does he commit an error when placed in the outfield for a game?"

This is a fun one to research because the answer is counterintuitive, and because the real story isn't about errors at all.

The Short Answer

Not very often. We pulled FanGraphs fielding data for all of 2025 and found 94 players who logged time at both an infield position (SS, 2B, or 3B) and an outfield position in the same season. Across 2,722 outfield games, those infielders committed just 56 errors, a rate of roughly one error every 49 games, or a 2.1% chance of committing an error in any given outfield appearance.

For comparison, pure outfielders (players who only played OF in 2025) committed errors at a rate of one every 45 games (2.2%). The rates are almost identical.

But Errors Are the Wrong Metric

More importantly: fielding percentage isn't the most effective way to measure outfield defense. It only captures balls that a fielder reaches and then mishandles. It ignores balls they never get to in the first place, i.e. the line drive that drops in front of them because they got a bad read, the gap ball they didn't cut off because their route was inefficient, the fly ball that carried over their head because they misjudged it off the bat.

Modern defensive metrics (i.e. Outs Above Average (OAA), Defensive Runs Saved (DRS), and Ultimate Zone Rating (UZR)capture this, and they paint a very different picture.

Research from The Hardball Times and FanGraphs found that infielders placed in the outfield perform roughly 12-14 runs below average per full season, about double the 6-7 run penalty that outfielders face when switching between outfield positions. The problem mainly isn't errors. It's range, routes, reads, and jumps.

FanGraphs' positional adjustment system quantifies this gap. The defensive spectrum values each position per 162 games:

The gap between shortstop (+7.5) and a corner outfield spot (-7.5) is 15 runs per full season. That's the difference between having a Gold Glove-caliber defender and a below-average one at the same position.

Case Studies: The Good and the Bad

The cautionary tale: Oneil Cruz. The Pirates moved their 6'7" shortstop to center field in 2025. In his first 17 games, he posted -8 DRS (worst among all outfielders), 4 errors (twice as many as any other outfielder), and ranked 62nd of 67 qualified outfielders in jump metrics. He eventually adjusted, posting +3 DRS over his next 48 games (FanGraphs), but the early weeks were rough.

The success story: Fernando Tatis Jr. Moved from shortstop to right field and won a Gold Glove and Platinum Glove in his first full outfield season (2023). In 2025, he posted +5 OAA, the best among all MLB right fielders. Elite athleticism can overcome the learning curve.

The legend: Alex Gordon. A struggling third baseman who moved to left field and became one of the best outfielders in Royals history, 8 Gold Gloves after the conversion. His OPS also jumped 200+ points, suggesting the move freed him up offensively as well.

What About the Orioles?

This question feels relevant to the 2025 and 2026 Orioles, who have frequently shuffled infielders to the outfield. Here's how some of them fared in the OF in 2025:

In 2025, Jackson was the most-used infielder-turned-outfielder on the team, making 34 starts in right field. He committed just one error in 250 innings, a perfectly respectable .985 fielding percentage. Mateo had one error in limited CF/LF time, and Alexander was error-free in 7 OF appearances.

But again, errors don't tell the full story. Did we as O's fans feel comfortable with Jorge Mateo out in center field last season? Not really.

The Bottom Line

To directly answer your question: an infielder placed in the outfield for a game has about a 2% chance of committing an error, essentially the same rate as a regular outfielder. If you're watching an Orioles game and Blaze Alexander or Jeremiah Jackson gets moved to right field, the odds are overwhelmingly in favor of a clean defensive game.

But errors are just the tip of the iceberg. The real cost of playing an infielder in the outfield shows up in the plays that don't get made, the balls that fall for hits because of a slow read, a bad route, or a hesitant first step. Modern metrics estimate that cost at roughly 12-14 runs over a full season, about double the penalty of moving an outfielder between OF spots. It's not that infielders can't play the outfield, it's that the outfield is a deceptively difficult position that rewards instincts built over years of reps.

The occasional spot start? Usually, not a big deal. A full-time position switch? That's a much bigger ask, and the data shows that only the most athletic players (Tatis, Gordon, Cruz after adjustment) can pull it off without costing their team significant defensive value.

Why does your model project the Orioles lower than FanGraphs?

Question from Teddy: "Why are the Orioles projected so much lower in your model than in other projections like FanGraphs? It feels like the national sites are way more optimistic."

Great question, and one that was submitted to us right around Opening Day (so the pre-season hype about the 2026 Orioles was at an all-time high). The short answer is: our model uses a fundamentally different approach than FanGraphs, and so far this season, that approach has been slightly more accurate, especially on the Orioles.

Two Philosophies of Projection

FanGraphs' Depth Charts projection system works bottom-up: it projects every individual player's performance using a blend of the Steamer and ZiPS projection systems, then assembles those players projections into a team forecast. It sees the Orioles' roster: Gunnar Henderson, Adley Rutschman, Pete Alonso, Zach Eflin and projects what each player should produce based on talent.

Our ELO model works top-down: it tracks each team's historical performance through a rolling rating system, then simulates the remaining schedule 10,000 times. It doesn't care about individual rosters. It cares about what the team has actually done on the field. The Orioles' ELO entering 2026 was lower because the team underperformed expectations in 2025. The model demands proof on the field before boosting a team's rating.

Here's what each model projected for season wins for the AL East on Opening Day (FanGraphs power rankings, March 25th):

Both models had Baltimore 4th in the AL East on Opening Day. But there's a key difference in separation. FanGraphs saw a tight division with only 3 wins separating 1st from 4th. Our model saw a 7-win gap between NYY and BAL. That separation is why our playoff odds (33.4% on Opening Day) were so much lower than what FanGraphs implied: in a tight division, Baltimore has more paths to the postseason; in a spread-out division, they have to overcome a much larger deficit.

The Caveat

Here's the honest disclaimer: we're 25 games into a 162-game season. Current win paces are noisy. A 3-game losing streak can swing your pace by a few wins. FanGraphs' talent-based approach could absolutely end up more accurate by October. Depth Charts projections are designed to be right over full seasons, not 15% samples.

But that's exactly the point of our model. We're not trying to project what the Orioles should be based on their roster. We're tracking what they are based on their results and updating every day. Right now, the data says the Orioles are a ~80-win team fighting for a wild card spot. That might change. But the model will adjust when it does and not a moment sooner.

Thanks for your submissions

And that concludes our first mailbag! We appreciate all of the really great questions. We'll be doing a mailbag each month, so please do go over to our mailbag form to submit more of your thoughts about what you are seeing on our site and/or out on the field!

Sources

Q1: Dylan Beavers

• Batting stats (AVG/OBP/SLG/OPS): MLB Stats API and FanGraphs player page

• Plate discipline (Swing%, O-Swing%, Z-Swing%, F-Strike%): FanGraphs plate discipline

• Batted ball data (GB%, FB%, LD%): FanGraphs batted ball

• Statcast metrics (exit velo, launch angle, barrel%, xBA, xSLG, xwOBA): Baseball Savant

• Defensive metrics (OAA, DRS): Baseball Savant fielding

• Stabilization thresholds: FanGraphs — Sample Size

• Walk distribution and game logs: MLB Stats API game logs

Q2: Swing Decisions After 0-1

• Pitch-level count analysis (K%, BB%, chase rates, zone rates by count): Baseball Savant Statcast Search — pitch-by-pitch CSV data for BAL, NYY, TOR, BOS, and CLE batters, 2025-2026 seasons through April 22

• Team plate discipline rankings (O-Contact%, O-Swing%, K%, BB%): FanGraphs team leaderboard — plate discipline

• Year-over-year BAL team comparison: FanGraphs — BAL 2025-2026

• Individual player count splits: Derived from Baseball Savant pitch-level data, grouped by batter and count state

Q3: Infielders in the Outfield

• 2025 fielding data (94 dual-position players, error rates, fielding%): FanGraphs fielding leaderboard

• 12-14 run penalty research: The Hardball Times — Re-Examining WAR's Defensive Spectrum

• Positional adjustments: FanGraphs — Positional Adjustment

• Oneil Cruz transition: FanGraphs — Cruz Isn't a Center Fielder Yet and FanGraphs — Cruz Looks Like a Center Fielder Now

• Fernando Tatis Jr. OAA: Baseball Savant

• Notable position conversions (Gordon, Tatis, Murphy, Yount): MLB.com — Players Who Moved from Infield to Outfield

• Orioles fielding data (Jackson, Mateo, Alexander): FanGraphs — BAL fielding

Q4: Model Projections vs FanGraphs

• FanGraphs Opening Day projections: FanGraphs Power Rankings — Opening Day 2026 (published March 25, 2026)

• FanGraphs current Depth Charts projections: FanGraphs — Projected Standings (accessed April 22, 2026)

• Our ELO model preseason projections: Birdland Metrics — Schedule Leverage, derived from preseason ELO simulation (10,000 season simulations, March 27, 2026)

• Current AL standings: MLB Stats API, accessed April 22, 2026

• 162-game win paces: Calculated from current W-L records as of April 22

All data current as of April 22, 2026.