In the fifth incarnation of a time-honored tradition that recurs every 500-ish episodes, Ben Lindbergh and Meg Rowley are joined by ex-co-host Sam Miller and The Athletic’s Grant Brisbee to draft assorted things that they like about baseball.
This is a free preview of a paid episode. To hear more, please visit our Patreon.
Ben Lindbergh and Meg Rowley banter about tough times for a few EW favorites and Ben’s pre-podcast injury, then (15:00) discuss the response to Cade Cavalli telling Willson Contreras to “Sit down, boy.” After that (38:10), they cover the MLBPA’s proposals to limit certain types of transactions, a continued tightening of the leashes on starting pitchers, Paul Skenes’s recent struggles, the unlikely win-loss records of Tanner Bibee and Aaron Ashby (and an embarrassing Cooper Ingle error), Dansby Swanson and Pete Crow-Armstrong hot streaks and PCA’s newfound patience, recent swoons by the Braves and Yankees and surges by the Marlins and Rangers, what the Red Sox and Tigers should do at the deadline, and more.
It has not been a good season for Trea Turner. The two-time batting champion is in the midst of a career-worst season at the plate, hitting for a 79 wRC+ (.239/.287/.368) even after homering in three straight games, including a three-run shot off Pirates ace Paul Skenes on Wednesday night. What’s more, after breaking a streak of three straight below-average seasons at shortstop according to both Defensive Runs Saved and Fielding Run Value last year, he’s not only back in the red, but is tied for last at the position with -8 DRS, while being tied for fifth-worst with -5 FRV. All of which once again marks Turner as a fairly typical Phillies player.
Indeed, through ups and downs that have included four postseason appearances, one trip to the World Series, and two in-season managerial firings, one constant of the Dave Dombrowski era of Phillies baseball has been lousy defense. Since the start of the 2021 season, the team is 100 runs below average according to FRV (the majors’ seventh-lowest mark) and 127 below average according to DRS (fifth-lowest). It hasn’t stopped the Phillies from being competitive — or highly entertaining — though it may have cost them seeding here and there, to say nothing of the way last year’s Division Series against the Dodgers ended. But given the choice between good hitters with questionable gloves and slick fielders with subpar bats, the team has generally gone for the offensive boost and lived or died with the consequences.
Thus it was hardly a surprise that the Phillies ranked second-to-last in my recent aggregation of team defensive metrics, even with right fielder Nick Castellanos — who contributed -41 DRS and -45 FRV from 2022–25 before being released in February — no longer on the team, and Kyle Schwarber more or less a full-time designated hitter. The Phillies’ .672 Defensive Efficiency, the rate at which a team turns batted balls into outs, is lower than all but the Rockies (.669), while their -29 DRS is lower than all but the Twins’ -32. Read the rest of this entry »
After wandering for years, Jake Bauers has found himself in Milwaukee as one of the top hitters of 2026.
I first learned about Bauers because of a stat I made up sometime in 2019, around when Baseball Savant began publishing the attack region perspective of the strike zone. Rather than labeling pitches as simply in or out of the zone, Savant drew the distinction between meatballs, borderline strikes, and various distances beyond. Analysts had made similar observations for as long as PITCHf/x had been around, of course, but this was the first time (to my knowledge) the data was easily searchable, sortable, and available to download. No longer was the concept of plate discipline limited to walks and strikeouts, or even simple chase rate, but we could now look at which players were actually swinging at the right pitches within the zone, too.
At a high level, batters should only swing at pitches in the heart region. At a more granular level, this isn’t entirely true, as things like the count, situation, and swing profile change the calculus from pitch to pitch. But as a general rule, the players who swing at the right pitches are the ones who swing at heart pitches and lay off everything else. This gives us some fairly simple math: Read the rest of this entry »
FanGraphs Members may have noticed an incredible new feature over the last couple weeks, and today, we’re thrilled to officially announce it. Members now have access to Heat Maps on our leaderboards and player pages. Sean Dolinar has been hard at work for the past month or so putting this together, and now I get to walk you through this Members-exclusive feature. Read the rest of this entry »
Today at FanGraphs, we’re introducing an updated approach to prospect valuation. You can read the announcement here, and also see the new Farm System Rankings for 2026 on The Board. This post is a detailed methodological examination of how we’ve produced our new estimates. It goes over each step of the process in order, and concludes with a sensitivity analysis. If you’re interested in the broad strokes of our new approach, the introductory post will likely suffice. But if you want to see how the sausage is made, read on.
Prospect Classes
We began with Baseball America’s annual Top 100 prospect lists for each year from 2005-2016, plus FanGraphs’ lists for 2017 and 2018. The BA lists serve as a publicly accessible bridge to the current era of FanGraphs prospect writing, and provide a nice through line with Craig Edwards’ earlier research. We took all instances of a prospect being ranked, including duplicates of the same prospect in multiple years. We converted those ordinal rankings into Future Value grades using a two-step process. First, we separated the rankings into pitchers and hitters and created two separate ordinal lists for each year. Second, we adjusted those ordinal rankings between years by a regressed factor based on that class’ major league production. This allowed us to differentiate between classes – without some type of delineation between years, every top overall hitter would receive the same grade, which is contrary to the way we grade prospects.
This method introduces some potential bias. Judging prospects based on how they turned out inherently brings some information from the future into the mix. We decided that this was the best possible way to systematically introduce varying year-over-year quality to an otherwise ordinal-only set of values, and that it also did a good job of replicating the way that grades might have actually been assigned in the past. The top pitching prospect on the 2010 list was Stephen Strasburg. The top pitching prospect on the 2011 list was Julio Teheran. It’s important to differentiate between the likely grade that they would have received. There’s some volatility in relative value assignment at the very top end of the scale based on this methodology, which is addressed in the sensitivity analysis. Read the rest of this entry »
Jesús Made Photo: Dave Kallmann/Milwaukee Journal Sentinel/USA Today Network via Imagn Images
Seven years ago, Craig Edwards published a landmark study on prospect valuation. Craig’s work built on previous studies by Victor Wang, Scott McKinney, Kevin Creagh, Steve DiMiceli, and our own Jeff Zimmerman, as well as a few prior ad hocattempts here at FanGraphs; subsequent work on the subject was done by the team at Driveline Baseball. These studies have been hugely important both for FanGraphs’ own evaluation of prospects — among other things, Craig’s work has helped to feed the Farm System Rankings over on The Board — and for the broader public study of the minor leagues.
The reasoning behind these studies is clear and simple. If you want to evaluate a prospect-for-big-leaguer trade, you’ll need to know the expected value of the prospect in the trade. If you want to evaluate how much help is waiting in a given team’s farm system, a quantitative assessment of the talent there is necessary. Even if you’re just wondering how likely your team is to find the next big thing, again, you’ll need some type of framework to understand how often that’s happened in the past.
The previous studies of prospect valuation are still excellent, but they’re all very much of their time. Since Craig published his study in November 2018, the league has changed significantly. The COVID-abbreviated 2020 season changed minor league timelines across the board. The league contracted the number of minor league franchises significantly in 2021. A new CBA, signed before the 2022 season, changed compensation structures and competitive balance tax levels, and introduced the Prospect Promotion Incentive. The cost of a win in free agency has skyrocketed; league-wide payrolls are up more than 30%, and free agent salaries are up by more than that. Read the rest of this entry »
DEPARTMENT OVERVIEW:
Baseball Analytics is the quantitative research and data science group within Baseball Operations. We develop statistical models, machine learning algorithms, and analytical tools that support decision-making across Baseball Operations including player acquisition, player development, and player optimization. Core responsibilities include predictive modeling, applied research, experimentation, and communicating technical findings to inform baseball decisions.
POSITION OVERVIEW:
The Boston Red Sox seek a Data Scientist for the club’s Baseball Analytics department to develop, evaluate, and optimize predictive models that enhance decision-making across all aspects of Baseball Operations. Operating in a dynamic and intellectually stimulating environment, the Data Scientist will collaborate closely with the Baseball Analytics team and other Baseball Operations stakeholders to influence player personnel decisions and strategic initiatives. This role offers a unique opportunity to apply advanced statistical techniques and data science to shape the team’s future direction.
The successful candidate will possess strong analytical skills, a deep understanding of baseball, and the ability to communicate technical concepts to non-technical audiences effectively. The specific role, level, and compensation package will be tailored to the selected candidate’s qualifications and experience. Applications are encouraged from individuals with varying levels of expertise in the field.
The salary range for this position is $75,000–$100,000, based on relevant experience and internal equity. Our full-time employees also receive a comprehensive benefits package, including healthcare, retirement plans, paid time off, and more.
RESPONSIBILITIES:
Design and maintain robust predictive models and data pipelines to generate insights for player evaluation, acquisition, development, and performance optimization.
Craft compelling written reports and data visualizations to effectively communicate complex analyses to diverse audiences, including both technical specialists and Baseball Operations leadership.
Partner with the Baseball Systems team to seamlessly integrate new analytical findings into team applications and proactively identify and address data quality issues.
Continuously monitor and evaluate cutting-edge analytics and research from public and academic spaces to recommend innovative ideas, methodologies, and technologies that can enhance on-field performance.
COMPETENCIES:
Understanding of modern statistical and machine learning methods and an advanced proficiency with popular data science languages and libraries.
Practical understanding of how to approach research questions to drive actionable insights.
Able to visualize, present and disseminate analyses to a diverse group of stakeholders (leadership, coaches, players, scouts, etc.) in a clean, intuitive, and engaging way.
ADDITIONAL QUALIFICATIONS:
PhD or master’s degree in a quantitative field (such as statistics, engineering, applied mathematics, physics, quantitative social sciences, computer science, computer vision, or operations research) or equivalent professional experience.
Proficiency in SQL and programming languages such as R or Python.
A passion for baseball and a strong desire to contribute to building a championship-winning team.
In addition to the above requirements, all roles within Baseball Operations are expected to effectively demonstrate our universal competencies related to problem solving, teamwork, clarity of communication, and time management, along with embodying our culture of honesty, humility, relentlessness, and commitment to DEIB.
At the Boston Red Sox we go beyond embracing diversity. We’re committed to living by our values, strengthening our community, and creating a workplace where people genuinely feel like they belong.
Too often, job seekers don’t apply to positions because they don’t meet every qualification. If you love this role and are great at what you do, we encourage you to apply. Your unique skills and experiences might just be what we’ve been looking for.
Prospective employees will receive consideration without discrimination based on race, religious creed, color, sex, age, national origin, handicap, disability, military/veteran status, ancestry, sexual orientation, gender identity/expression or protected genetic information.
DEPARTMENT OVERVIEW:
Baseball Analytics is the quantitative research and data science group within Baseball Operations. We develop statistical models, machine learning algorithms, and analytical tools that support decision-making across Baseball Operations including player acquisition, player development, and player optimization. Core responsibilities include predictive modeling, applied research, experimentation, and communicating technical findings to inform baseball decisions.
POSITION OVERVIEW:
The Boston Red Sox seek a Senior Data Scientist for the club’s Baseball Analytics department to develop, evaluate, and optimize predictive models that enhance decision-making across all aspects of Baseball Operations. The Senior Data Scientist will collaborate closely with the Baseball Analytics team and other Baseball Operations stakeholders to influence player personnel decisions and strategic initiatives. As a senior member of the team, the Senior Data Scientist will help shape the data strategy of the department, influencing team growth and keeping the group on the cutting edge of predictive data science. This role offers a unique opportunity to apply advanced statistical techniques and data science to shape the team’s future direction.
The successful candidate will possess excellent analytical skills, a deep understanding of baseball, and the ability to communicate technical concepts to non-technical audiences effectively. The specific role, level, and compensation package will be tailored to the selected candidate’s qualifications and experience.
The salary range for this position is $100,000–$140,000, based on relevant experience and internal equity. Our full-time employees also receive a comprehensive benefits package, including healthcare, retirement plans, paid time off, and more.
RESPONSIBILITIES:
Design and maintain robust predictive models and data pipelines to generate insights for player evaluation, acquisition, development, and performance optimization.
Craft compelling written reports and data visualizations to effectively communicate complex analyses to diverse audiences, including both technical specialists and Baseball Operations leadership.
Partner with the Baseball Systems team to seamlessly integrate new analytical findings into team applications and proactively identify and address data quality issues.
Take an active role in evaluating cutting-edge analytics and research from public and academic spaces to drive innovative ideas and methodologies to help continuously improve the department.
Introduce creative and novel methodologies to improve existing processes and enhance departmental decision making
COMPETENCIES:
Advanced understanding of modern statistical and machine learning methods and an advanced proficiency with popular data science languages and libraries.
Practical understanding of how to approach research questions to drive actionable insights.
Able to visualize, present and disseminate analyses to a diverse group of stakeholders (leadership, coaches, players, scouts, etc.) in a clean, intuitive, and engaging way.
ADDITIONAL QUALIFICATIONS:
PhD in a quantitative field (such as statistics, engineering, applied mathematics, physics, quantitative social sciences, computer science, computer vision, or operations research) or equivalent professional experience.
Expert proficiency in SQL and programming languages such as R or Python.
A passion for baseball and a strong desire to contribute to building a championship-winning team.
In addition to the above requirements, all roles within Baseball Operations are expected to effectively demonstrate our universal competencies related to problem solving, teamwork, clarity of communication, and time management, along with embodying our culture of honesty, humility, relentlessness, and commitment to DEIB.
Bryce Harper started out as a catcher. By the time he was old enough to drive, though, everyone knew his catching days were numbered. When the Nationals drafted him in 2010, they stamped that nonsense out, because no one who can mash like Bryce Harper is allowed to waste their energy and their knees behind the dish. Harper moved to the outfield, and those of us who were there in 2012 will recall that for a short while, he was fantastic out there. He played with his hair on fire, he had a rifle arm that slotted in nicely alongside Rick Ankiel’s cannon, and in those first couple years before Statcast appeared, he was downright fast. It didn’t last too long, though. Harper decided to beef up, arriving in Florida each spring with more and more muscle mass and less and less footspeed. Also, he ran into walls a lot. For most of his career, Harper was a poor outfielder, and then in 2023, he returned from Tommy John surgery as a first baseman, initially on a temporary basis. He has not played in the outfield since.
So far this season, according to Statcast’s Fielding Runs Value, Harper has been the fourth-worst fielder in baseball. He’s at -7 FRV, ahead of only Willy Adames and Logan O’Hoppe at -10, and Owen Caissie at -8. According to our defensive numbers, which include a positional adjustment, Harper has been worth -12.3 runs, making him the worst defender in baseball by a substantial margin. So that’s bad. Nobody wants to be at the very bottom of the leaderboard. I mean, I suppose once you sort the leaderboard upside down, it shouldn’t be called a leaderboard anymore. It should really be called a trailerboard. Or maybe the shame list. I’m spitballing here. The point is that’s not where Harper wants to be. And it gets worse.
Statcast has FRV values dating back to 2016. Here’s the single-season trailerboard for that entire 11-year period:
So the worst total ever recorded is -9 FRV. Harper is already at -7, and he’s still got half a season left to move beyond 1,250th place. He’s on pace for -13 FRV and -23.2 defensive runs, which would absolutely boat race the worst defensive seasons of the Statcast era. On the bright side, he’s no longer running into walls.
So is Harper one of the worst defensive first basemen in recent history? The other defensive metrics don’t think so. (As a matter of fact, they’re formulas, so they don’t think at all, but you get the point.) Harper is at -1 Defensive Runs Saved this season, an improvement over the -3 he put up in 2025. Deserved Runs Prevented, the flagship defensive metric of Baseball Prospectus, is much more conservative than the others, so Harper’s -0.3 mark makes him the fourth-worst first baseman this season. That’s very bad, but it’s not historic or anything. Last season, he was at a positive 0.3 DRP. In other words, we’re seeing a sudden drop-off according to two metrics, while the other metric thinks Harper has gotten very slightly better.
Harper also graded out fantastically at first base as recently as 2024. That was his first full season at the position, and he nailed it. He was worth 5 DRS, 5 FRV, 0.9 DRP. You can take my word for it (along with the absence of minus signs) that all of those numbers are good. Two years ago, Harper was a good first baseman and all the computers thought so. This season, one of them thinks he’s meh, one thinks he’s terrible, and one thinks he’s bordering on the worst ever to do it.
Now it’s time for the big caveat you’ve been waiting for. Defensive metrics are far from perfect, and they take a long time to stabilize. In fact, when I started writing this article yesterday, Harper was at -8 FRV. Then last night, he made a couple great plays — one of which you can watch below — and knocked it down to -7. That’s the thing about small sample sizes.
Half a season of an ugly FRV does not the worst defender ever make. Still, numbers this extreme definitely mean something, and the nice thing about Statcast is that it gets very specific. Here’s why the fancy cameras dislike Harper:
Bryce Harper’s Directional OAA
Year
In
To Right
To Left
Back
2024
0
5
3
0
2025
3
-4
2
0
2026
2
-8
-2
1
First basemen don’t really go back on the ball too much, so we can mostly ignore that last column. Charging the ball isn’t Harper’s problem either. Hit the ball right at him, and he’ll probably be just fine. The problem is on the sides. In 2024, Statcast says Harper was great going both to his right (toward second base) and to his left (toward first base). In 2025, he stopped being good to his right side. This year, he stopped being good to his left side, too. He has now officially run out of sides.
With this data in hand, I hit the tape. Here’s another big caveat: Every player is going to look bad if you’re going into your film session looking for the things they’re doing wrong. It’s just human nature. However, I did my best to look at every single ball hit Harper’s way, not just the ones that got by him. Moreover, I’m here to help. I did notice a few clear issues, and I’ve prescribed some simple fixes.
The first problem is that Harper isn’t great at diving for the ball. That’s unfortunate, because although first base isn’t the hot corner, the position is still awfully close to home plate and involves a lot of plays that don’t provide much in the way of reaction time. Harper has had a lot of plays this year where he only has time for a step and a dive. I suspect that a fielder with better instincts and a quicker first step wouldn’t have to dive quite as often, but there’s only so much I can do to quantify that. That’s what Statcast is particularly good at, because it knows every player’s starting point and how much time they have to make each play. For right now, what I noticed is that Harper rarely seems to come up with the ball when he dives for a grounder. On nearly every play in the supercut below, he is within range of the ball, but he doesn’t get his glove down in time, or he dives too late, or the ball deflects off him, or he just doesn’t get extended.
All of these clips are just from the first half of this season, so this is happening pretty regularly. I don’t really know how you fix that. Harper didn’t grow up playing the infield. He spent almost no time on the dirt until he turned 30. It might just be too late for him to develop that particular skill, and it would be lunacy to risk an injury to such a valuable hitter by making him practice hurling himself to the ground over and over again. So that part’s going to be tough. Just to make Phillies fans feel better about this one, here’s a video of Harper making a diving play:
There, that’s nice. Now, I don’t mean to say there’s nothing Harper can do to fix this problem. I don’t know how you get him better specifically at making the play once he’s diving for the ball, but I do think there are a few things he could do to avoid having to dive in the first place. I’m sure that working on his instincts and his first step is already a part of his daily infield routine, but beyond that, there are a couple of ways for him to get in a position to make a few more plays.
I would argue that Harper should play a bit deeper to buy himself more time. This season, when lefties are at the plate with no one on, the league’s first basemen have average depths ranging 120 feet and 130 feet. Harper is right in the middle at 125. When righties are up, he averages 111 feet, a bit shallower than average. If you recall the table at the top of this article, Harper has always been good, maybe even great, at coming in on the ball, so why not push him back just a couple feet? He still wouldn’t be the deepest first baseman out there, but he would get a little bit more of the reaction time that he needs.
The next issue I noticed also has a pretty simple fix. As I watched ball after ball sneak past a diving Harper, I noticed something simple. When he’s holding a runner on first base, he tends not to get back into a good fielding position. When you’re holding the runner on first, you’re all the way on the edge of the field, which drastically reduces your range, since all of the area to your left is foul territory. Once the pitcher commits to home, first basemen usually shuffle toward their right in order to get back into a more useful fielding position. Harper is not great at that. In fact, he sometimes seems to forget to do it altogether.
According to the Statcast data, Harper actually grades out in the middle of the pack in terms of positioning when there’s a runner on first. His average angle is 41 degrees, and some players are as high as 43 (standing directly on the foul line would be a 45 degree angle). However, that data gets measured when the pitcher releases the ball, not when it crosses the plate, and at that point, most first basemen would only be a step or two into their shuffle. Harper often doesn’t seem to shuffle at all, and ball after ball leaks by his right side, even balls that are within the cutout of the infield grass. Believe me when I tell you that the video above could have been longer. At a certain point, I stopped pulling videos, because there were just too many, so here’s a sample of screenshots that show just how close he is to the bag:
He’s flat-footed in all of these shots. No wonder the numbers say that he doesn’t have good range going to his right. He’s starting as far to the left as it’s possible to get, and he doesn’t seem particularly interested in correcting that. Again, the Statcast numbers say that Harper is not the most egregious offender on this particular count, but he is a player whose range could really use some help, and making sure he remembers to take a shuffle or two in order to get into a better position seems like it would be pretty easy.
The last issue I noticed specifically about balls to Harper’s right is that he has a tendency to get greedy. You can’t run into that many walls as a first baseman, but you can go steal grounders away from your second baseman. I love that Harper is aggressive. You want your first baseman to go get the ball. And sometimes, like on these plays, it works out just fine.
Those ended up as outs. That’s great. But we all saw the second baseman behind Harper, ready to field the ball, right? Sometimes it doesn’t work out that great.
The good news is that this should be at least somewhat fixable. I’m sure every infield coach has a drill where they hit tweeners toward their first basemen in order to help them practice making the split-second decision to go after the ball or cover the bag. Let’s make that a regular part of Harper’s pregame warmups.
I have one last complaint. I think Harper is genuinely great at starting the 3-6-1 double play and the 3-6 double play where the first baseman steps on the bag and the shortstop tags the lead runner. His turns are smooth and his throws are strong and accurate. That’s why Statcast thinks he’s great coming in on the ball. Those are often balls where he has to charge and make a good throw, and he’s excellent at it. However, I think Harper doesn’t charge the ball hard enough, specifically on routine plays. He’s often happy to wait back even on softly hit balls, which means that he won’t have time to step on first base himself, which means his pitcher has to cover and catch a flip. Now, Harper’s good at making that flip, but you’d still much rather have your first baseman make that play himself. A lot of things can go wrong on those flips plays: errors, sprained ankles, collisions. Here’s a glaring example:
This ball was an easy grounder hit at 49 mph, but Harper still chose to wait back and field it 15 feet behind the bag. Even then, he still had plenty of time to make the play himself. The runner wasn’t even halfway to first when he flipped the ball to the pitcher. This was a low stakes play, and about as easy a flip play as you’ll see, but it was also a play that did not necessitate a flip at all. Harper just decided early on that he was going to flip it; that’s why he didn’t charge the ball, and that’s why he didn’t keep it even after the runner gave up on the play. Here’s a higher stakes example:
This is a very easy play that Harper turned into a hard one. That’s Cy Young candidate Cristopher Sánchez on the mound. The Phillies should be protecting his ankles at all costs! Not only was Harper the closest player to first base when he fielded this ball, but also, look at where everybody else was when he fielded it.
The batter is barely out of the box. Sánchez is still on the mound, and he has to bust it over to first. Watch that clip again and look how hard he hits the bag. This is egregious. It hasn’t really come back to bite Harper just yet, but turning easy plays into hard ones is not a great habit.
So that’s my critique of Harper’s first base defense. Just a quick 2,400 words. I should once again close by noting that we’re talking about small sample sizes, and that Harper is probably not quite as bad as Statcast makes him out to be, if for no other reason than the fact that no first baseman has ever graded out as badly for a whole season as he has in the first half of this one. However, I need to bring up one more thing.
Just a few days ago, Tom Tango wrote a blog post revealing that Statcast will soon be incorporating data about how first basemen handle throws. It’s an exciting development, and I recommend reading the whole post, but we’re interested in one specific part. Naturally, Tango mentioned a couple players who stand out: “For the 2021-present (thru June 27, 2026), Matt Olson and Freddie Freeman are tied at +25 receiving outs above average. Yuli Gurriel is at +12 at half the playing time. On the flip side is Bryce Harper at -13.” Harper is the worst at this stat even though he’s only been playing first base since late 2023. As Tango was quick to mention, Harper is a converted first baseman. Because we don’t have a year-by-year breakdown, it’s entirely possible that he’s fine at this particular skill now, and that he racked up all that negative value when he was a newbie at the position. I asked a couple smart Phillies fans (though I left Michael Baumann alone because he’s on vacation) what they thought of Harper’s receiving. One said they hadn’t noticed it much one way or another, and one said they thought he’s pretty good at it. So maybe this is merely old news or nothing at all. Or maybe Statcast is about to hate Bryce Harper even more.
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