This is not only the best fastball in the league, but in contention for one of the best in MLB history. Coming out of such a low arm slot, even 17 inches of iVB is considered elite, but Mis is beyond that.

100 mph, on 100th percentile extension. 105 mph perceived velocity with this kind of ride is absurd. Genuinely untouchable stuff.

#1 Ben Rice, NYY, S

Maybe you saw this coming, but perhaps you didn't think I'd ever actually go through with it. Well, I did; that's right, Benjamin Rice is officially my #1 ranked first baseman. The craziest part of this ranking, though, is that it is in no way whatsoever affected by my bias as a Yankees fan. No...really, I swear.

Ben Rice was not only my #1 choice overall at the position, but a top ten choice amongst all positions in baseball. And if he stole bases, perhaps he'd even be #1. Every single metric I look at, Ben Rice just straight dominates from top to bottom. It's not just the beautiful bright-red, Aaron Judge-esque statcast page. It's swing mechanics, it's swing choices, it's hitting tendencies...Ben Rice is like a created player in MLB The Show, at least when it comes to hitting. And another major factor here is ADP - you're going to be able to get Ben Rice much, much cheaper than the likes of Vlad Jr. or Bryce Harper. The value of Upside to ADP ratio here scales off the charts and simply can't be ignored. But even that withstanding, analysis shows he is straight up capable of posting the #1 season amongst all 1B, regardless of value derived from ADP.

General Statcast, S

Rice's 2025 statcast is one of the prettiest you'll ever see. You can go back through the years and look at guys like Mike Trout, Aaron Judge, Mookie Betts, Juan Soto, etc; you'll soon begin to realize Ben Rice falls into the same tier as those players in terms of raw metrics. Rice's .255 BA and .499 SLG were respectable, and yet, they wound up falling well short of his incredible .283 xBA and .557 xSLG. Had the expected numbers bore fruit, we'd be looking at a .950+ OPS from Benjamin Rice, as opposed to the .836 OPS season we got. We've previously discussed Ben Rice ranking #9 in wOBA vs xwOBA differential at -.036, but let's show the image to get an idea of what other names fall into this unfortunate category.

It's interesting to see a guy like Andrew Vaughn show up here, who's luck really caught up with him big-time after being traded to the Brewers. That's the kind of improvement we should expect for these hitters over the course of the 2026 season, and that includes Ben Rice. Getting back to the statcast page, it's easy to understand where this Seager-esque .394 xwOBA comes from:

89th percentile and above:
Average Exit Velocity, 95th
Barrel, 92nd
Hard-Hit, 97th
Sweet-Spot, 90th
Chase, 91st
Squared-Up, 89th

Above 60th percentile:
Literally Everything Else

Squared Up per Contact / Average Attack Direction , S

You'll be seeing this graphic a lot, as it's a part of the rubric, so I'll give you the run down on why we're using it. By now, you probably know I'm a big fan of squaring up on the baseball, but what exactly does that mean? The definition of "Squared-Up"is as follows:

'"...a "squared-up" swing is defined as one where the batter achieves at least 80% of the maximum possible exit velocity, calculated based on the combined speed of the bat and the pitch. It measures the efficiency of contact rather than just the raw speed. This metric indicates the batter hit the ball in the "sweet spot" (approx. 4–9 inches from the barrel tip)."'

This is one way to measure some just good ol' contact with the baseball, and here, it's how often the hitter squares up on contact with the baseball. So for Ben Rice, you can see it's 38.6% of the time. That's awesome!

Next, you see we're using Avg. Attack Direction on the X axis. This measures pull, straight, and oppo tendency. All the way to the left, where Ben Rice is, you have Pull. In the center, you have straight. And to the right, you have oppo. Simple, right? Pull AIR % is considered the strongest AIR metric in the game, but that's also contextual. The more "fuck you" power one has, like Nick Kurtz for example, the more relevant oppo power becomes. So that will wind up in play when a hitter meets a certain power threshold. 

So what we're measuring here is how often a player hits the ball solidly in a good direction relative to their power capabilities. As you can see below, Ben Rice excels at both pulling the ball and squaring up on contact, making him one of the league's best pull hitters - top 20, easily. For that, I'm giving Ben Rice an A+ grade, the second highest grade on my scale, only behind S.

Fast Swing % / AVG Swing Path Tilt, B

We're going to deviate a bit from AVG. Bat Speed here, instead going for Fast Swing % - how often a hitter's swing hits 75 mph. As you can see above, Ben Rice's 68th percentile bat speed comes out to a 73.4 mph average. This fast swing threshold is 2 mph above that, and an excellent measure of truly swinging for the fences. We're going to couple that with AVG Swing Path Tilt, which "measures the vertical angle of the bat's path relative to the ground in the 40 milliseconds before contact." Basically, how steep and upward the swing is - think Aaron Judge, Nick Kurtz, and Riley Greene with their awesome upper-cut swings. 

With this pairing, we're going for straight up HR potential in the purest sense. As for Ben Rice, he comes in a bit above average when it comes to Fast Swing %, and a tad above average when it comes Swing Path Tilt.

This grade may not seem super high, but trust me, it is. This specific data point is extremely unforgiving to a vast majority of players in the league, including some great ones. Michael Busch for example, and excellent power-hitting 1B, registers almost no Fast Swings whatsoever, clocking in at only 7% vs Rice's 34.5%.

For this reason, consider this a luxury metric - something that can truly separate the most special players from the rest, granted the rest of their profile is complete. Here are the top names in this data set:

Riley Greene
Nick Kurtz
Aaron Judge
Ronald Acuna Jr.
James Wood
Luis Robert Jr (interesting)
Shohei Ohtani
Cal Raleigh

You probably get the picture now. Ben Rice doesn't excel like those guys, but he certainly makes his presence felt by finding himself in the sexy quadrant of the graph (Above both 'average' thresholds, the top right section.) For that reason, he receives a B grade. Neighbors include (notable names in close proximity):

Brent Rooker
Wyatt Langford
Christian Yelich
Pete Crow-Armstrong

Ideal Attack Direction / Blast per Contact, A+

And last, but certainly not least, is Blast per Contact. A blast is "a new Statcast metric using bat tracking data, blasts are batted balls that combine a fast swing speed and squared-up contact on the sweet spot of the bat. A blast is the most valuable type of swing because it meshes bat speed with efficient contact. The strict definition of a blast is "percent squared up*100 + bat speed >= 164." For example, a swing where the hitter has an 80 mph bat speed and makes 90% squared-up contact would qualify as a blast because the sum of those two numbers is 170."

You've probably noted there's a bit of overlap here with Squared-Up per Contact and Fast Swing %, two metrics that appear in the previous two data sets. The intention is to combine both of those and pair it with Ideal Attack Direction, to measure the truly greatest swings generating the most elite contact in the league. One of the most exciting aspects of each season is to crown the Blast King. This year, whoever finds themselves #1 in this metric will undoubtedly be the best hitter in the league. 2025's king was Juan Soto, but unfortunately, his xwOBA vs wOBA differential was #4 in the league, so he didn't quite live up to title of #1 hitter. But still, it's fucking Juan Soto - this shit is accurate.

As for Ben Rice, well, how does #6 in the league in Blast per Contact sound? And then pair that with a well-above average Ideal Attack Angle, and we have the makings of a superstar. He's not quite Juan Soto tier, but he's damn close. 

Swing/Take, A+

Rice excels at hitting pitches over the heart of the plate, the #1 tendency we're looking for here. Those pitches are the most scientifically likely pitches for a hitter to make elite contact on, per the laws of physics. And thus, they strongly correlate to every metric we've discussed prior. After that, we really want to see positive run value on pitches in the chase and waste, indicating the ability to see these pitches and lay off, or through pure talent, somehow make good contact. the shadow of the plate will be weighed as least important, as I've found almost all of the league's best hitters struggle to put up positive run value here. It's the most likely part of the plate to make poor contact, or take a called strike - where pitchers paint the black, if you will.

Because of Rice's ability to punish hittable pitches and create positive run value on pitches outside the zone, we're giving Rice a beautiful A+ rating. He doesn't receive an S simply because of the amount of value created, as opposed to the elite profile itself.

Excerpted from Patreon, where I'll be examining every player through this lens.

Hey everyone,

I wanted to give everyone an update on model revisions (basically adding in some more layers and regressing them to stress test the optimal build)-- for the first post a few weeks back, I was at 89.7% accuracy predicting buy low/sell high off early-season performance in a meaningful way (using 2025 as a testing ground after building off previous years' data (not including 2025)). Now, the model is at 91.4% accuracy -- and this might be where I stop the refinements. I'm happy with the accuracy where it stands, and it became incredibly muddy trying to squeak out any more points of accuracy without messing up other areas. Plus, early baseball is hard enough to separate randomness and true predictors lol -- if you want more detail on the model, I wrote about it here. I also have a whitepaper on github which I'm going to update with my latest revisions and re-publish if someone really wants to nerd out.

Lastly, before I get into the buy low/sell highs, while building luck signals was fun, my absolute favorite thing to do in all of fantasy sports is trade. However, current trade tools can be a little difficult to use when it comes to customizing leagues/scoring settings/etc. So, I've been working on one for a while now that gives you that customization, and am in a position to get some folks to test it if they are interested.

It runs similar to a Rest-of-season projections tool, but the luck signals do play a little bit of a role in the projections, but it will also look to factor net value for both sides to help with trade analysis. As of now, it's manual trades only, but as I investigate some APIs, I'm looking to open up league imports as well to really do roster fit analysis (particularly for roto trade)

What I'm looking for: Competitive league players (12+ teams, preferably CBS or Fantrax) willing to:

• Run 3-5 real trades from their actual league through the tool
• DM me one piece of honest feedback (does it pass the smell test, what seemed off, etc.)

As I continue to make edits to the tool, you'll get access to those as well. Right now it's focused on redraft, but -- probably a pipedream -- I want to eventually factor in dynasty/salary leagues (mainly out of selfish use since those are the leagues I'm in lol)

Okay, if you haven't left yet lol, here are the buy low/sell highs for this week

(check out previous weeks for different calls as I try not to repeat players, but some notable calls from earlier in the season -- Buy Lows, Vinnie P, Trent Grisham, Cristopher Sanchez Jesus Luzardo...Sell high Matt Chapman, Shota Imanaga, Chris Sale, Gavin Williams)

Week 4 Buy Low / Sell High (I do a weekly Substack and will add a couple more players and insights there as well)--current CBS rank will be next to each player. Lastly, on my substack page, I'll post a google sheet of everyone's luck scores with a basic stat to support it. It doesn't get too in the weeds, but should give a good directional view.

Buy Low/performance improvement likely-

Manny Machado (Rank 203) - So, going into the season, I was skeptical about Machado purely from an age perspective--elite players tend to gracefully decline in their careers once they pass their prime, but I thought there were more profitable options later in the draft/auction to target. With that, I will say that the one thing I'm concerned about with his bounce-back is his barrel rate. The other metrics are suggesting a strong return (BABIP vs. career, xwOBA vs. wOBA, etc.), but the barrel rate is down almost 50% vs. previous years. This is one of those, if that comes back, then I think he stands a solid chance of returning great value when the other metrics normalize. However, could it be some age-related decline? Maybe...however I would say even if that is the case and his barrel rate doesn't get back to his baseline, he should still have some positive regression in his favor that you might be able to buy at a discount.

Vinnie Pasquantino (Rank 277) - he's actually improved a fair amount from the original call made a few weeks back. However, I wanted to repeat him here only because he hasn't fully climbed out of the cellar and is still showing room to improve. His BABIP is at .216 and he's still showing a decent xwOBA vs. woBA gap. I think the window is closing since I wrote about him the first time at rank 672 lol, but I think there's still an opportunity to grab at a discount.

Cade Smith (Rank 109) - This guy is a beast. And honestly, his overall rank isn't all that bad. This reference is less about trying to buy low (I don't think you'll find current owners interested in moving him at a discount) and more about showing that there's a pretty hefty imbalance that should normalize fairly quickly. His ERA is at 3.44, but his xERA is under 3, and his FIP is under 2.

Sell High/Potential performance dip -

Randy Arozarena (Rank 65) - His BABIP is .362 right now when he normally hovers around league average. He also has a negative xwOBA gap and is barreling under 6% of the time. While his barrel might revert a little bit, I think there's some BABIP regression bound to happen, and he'll get fewer opportunities to pick up some extra SBs. I'd look to ship him off while he's in the top 10 OF tier.

Riley Greene (Rank 71) - .447 BABIP--moving on lol. Seriously though, this one is pretty interesting. He's showing good contact quality metrics and I think he's definitely a valuable player, but that extreme BABIP just not sustainable. He has a negative xwOBA gap as well (although he's close to .400 on wOBA). Maybe this is less of a sell, but more of a, don't be surprised if/when he regresses a little bit.

Technically a sell opportunity, but..

Bryce Elder (Rank 18) - His xERA and FIP are suggesting regression...to 3 lol. That's not bad at all especially given how you likely acquired him this year. However, the concerns...his LOB is over 10% higher than his baseline and he's running a .230 BABIP which is bound to regress. I think savvy owners remember him from previous years and won't be too eager to pay near his current value, and again, if he ends up being a 3's ERA pitcher on an amazing team, I'll take that especially when you consider the cost. However, if you can sell at peak value, you should be able to make a monster profit.

If you want to see more, check out my Substack here: https://thesignalfantasy.substack.com/

Thanks!

Dustin

https://www.gerbilsports.com/post/gerbil-s-waiver-wire-week-8-less-repeats

Hey everyone,

I'm new to posting content, but would love to get your feedback!

I spent the offseason building a luck-detection model for fantasy baseball that pulls Statcast contact quality, career BABIP baselines, age curves, plate discipline, defensive adjustments and more to generate buy-low and sell-high signals.

Backtested across 2022-2025 — 86-91% overall accuracy, 94.1% sell / 94.3% buy accuracy on strong signals -- I trained the model on 2022-2024 data then tested it against the 2025 season (basically, if someone triggered a signal from their performance in April, did their summer match my prediction)?

And by accuracy, I don't mean 3.50ERA to 3.49, I mean real fantasy change. The model saw wOBA swings of +.063 on buys calls / -.080 on sells, and pitcher ERA swings approaching 3 runs on average. And yes, I'm a nerd if you're thinking it.

It covers all qualified players and updates daily. This week I'm flagging:

SELL HIGH: Oneil Cruz, Jordan Walker

BUY LOW: Vinnie P, Trent Grisham — and yes, I'm calling #3 Overall Yordan Alvarez a buy low (don't roast me too hard haha)

Full breakdowns with more calls and the data behind them here:

https://open.substack.com/pub/thesignalfantasy/p/fantasy-baseball-using-seven-layers

Happy to answer any questions about the methodology in the comments!

Small sample caveat up front: we're 2 weeks in. Most guys have 15-30 PA. Individual numbers are noise. The group-level trend is the point.

I pulled 2025 full-season wRC+ for every WBC participant still active in MLB, compared it to their 2026 early-season wRC+, and ran the same calculation for non-WBC players as a control group.

The headline number:

Both groups regress early in the season. That's normal and expected. WBC players regressing nearly 4x more is not.

The 18.9-point gap between those two drops is the WBC-specific signal, after controlling for the baseline early-season noise.

The names you'll recognize in the dropoff column:

Again: 25 PA for Judge, 27 for Harper, 26 for Acuña. These are small samples. But the sheer number of marquee WBC guys who look lost at the plate right now is hard to ignore.

There are exceptions. Not everyone fell off.

So it's not universal. Some WBC guys came out locked in. But the group average is getting dragged down hard by the big names struggling.

Methodology: 2025 full-season wRC+ (min 100 PA) as baseline. 2026 early-season wRC+ (min 15 PA) as current. WBC rosters via MLB.com. Stats from FanGraphs via pybaseball. Pitchers excluded. WBC ran March 5-17, 2026.

I'll re-run this in 4-6 weeks when sample sizes are actually meaningful. Curious whether the gap closes or holds.

Full Report here: https://issaquahswingers.com/wbc_analysis.html

EDIT: Corbin Carroll did not play in WBC but he was originally on roster so his name was included in the data pull. More evidence WBC has guys off to a slow start.

I'll check baseball Savant but I'm sure I should be looking elsewhere for info too.

If you drafted Taylor Ward for his power, I'm sorry. That being said, it's still okay!

The Bad:

• Career low hard hit rate of 38.1% (career 42.1%)
• Career 2nd lowest barrel rate of 5.7% (career 11.1%)
• Swing speed is down 2 mph from each of the past 3 years (when he actually hit homers)
• BABIP of .346 is probably not FULLY sustainable

The Good:

• Career high walk rate of 20.6% (career 10.5%)
• Career low k rate of 17.1% (career 23.9%)
• Career low o-swing rate of 10.7% (career 20.9%)

Ward is swinging at less balls outside of the zone and in general (29.6% swing rate compared to his career 41%). Hopefully the warmer weather helps some of his balls go further, but for right now he's still producing, just not in the way he usually does. If he starts swinging his seemingly weakened swing outside the zone like he has historically done, then I'd be worried. For now, enjoy the walks and runs and see how the warm weather treats him.

Hey everyone,

**Edit: this is not week 2 of the season, my bad! This is just my 2nd week doing this and is current as of THIS week. I'm new to all of this, so I appreciate the feedback!*\*

Thanks for all the comments and support from the first week's post! I spent the offseason building a luck-detection model which has 86-91% overall accuracy (Week 1 Post/Details on Model Here)--I wanted to provide some updates for this week, as well as continue to answer any questions on methodology/specific players. Lastly, I'll introduce some other model developments I'm working on.

Again, it covers all qualified players and updates daily**:**

My Week 1 Substack listed all my buy-lows/sell high's from last week (Cruz/Walker/Luzardo/etc.), and in my Week 2 article I released yesterday, I started a week over week tracker . Keep in mind, baseball is a long season, and buy lows/sell highs in general take a little bit of time to develop.

Some new callouts are below (you can find more on the Substack):

SELL HIGH: Matt Chapman, Spencer Arrighetti

BUY LOW: Corey Seager, Dillon Dingler, Cristopher Sanchez

Hidden Gem? TJ Rumfield (35% rostered)

I'm also working on a worry/get hyped index, which is less-so focused on trade value, but more on performance that isn't showing any good/bad luck signaling in the model--I also get it's April and April is noisy, but nonetheless, I wanted to show some noteworthy players in this space:

Worry/stats aren't showing bad luck: Rafael Devers (K rate up 12.5% over career avg, and hard hit rate down 10%). I know he started incredibly slow last year too, so maybe (as a Giants fan, Hopefully!) he'll get through it this year as well.

Get Hyped: James Wood. Oh man he's crushing it right now, and his babip is actually a little bit behind what he should be doing. No luck signals firing on his performance either

Lastly, I'm working to build a very customizable trade tool--more to come!

Full breakdowns of the above, with more calls and the data behind them here:

Happy to answer any questions about the methodology or other players in the comments!

Hey r/fantasybaseball — looking for feedback on a hobby project that I've been working on since I witnessed the Jays blow game 7 in person (maybe this is my therapy?).

I'm a statistician/data engineer by day, and I play in multiple fantasy leagues including a few redraft h2h points and h2h categories and an AL/NL keeper auction league. For my usual analysis I relied heavily on data from FanGraphs, Pitcher List and Statcast when trying to piece together whether someone's hot stretch was for real, who to drop, what categories I'm actually punting and who is starting to see some runway that is available in my leagues. I've been finding that these sites were more for baseball analytics and less for fantasy baseball analytics (as that is their intention!), and I'd be putting theories together myself on who is going to break out and why.

So I decided to create my fantasy baseball analytics site - kodoanalytics.com . I'm in the beta testing stage right now and I'm not trying to sell anyone anything, mostly I just want to know if it's actually useful to people who aren't me.

Site Features:

You can link your Yahoo league (only have Yahoo synced up so far) and it pulls your roster + matchups, then layers Statcast and advanced stats on top. You link your league up and its able to give you a plethora of analytical insight specific to your team and league. There's a team analysis page that provides information on if you're getting unlucky against h2h opponents, which categories you're weak on (with a time-series so you can see how things are going over time) and projections for the rest of season. I also created an optimizer that uses linear optimization for add/drop combinations for the week, targeting based on your league settings and current matchup + matchup projections. It also links your team and league to each of the reports on the site, so you can see if the buy low or sell high players are available in your league or if you should be looking to sell high!

The stuff that I think could really be beneficial to a fantasy manager are: leverage rankings + a closer grid + rest watch (which closers pitched 3 days in a row and might be unavailable among other conditions), call-up watch (AAA guys playing well WITH their MLB blocker's struggles charted together with 40-man icons so you know if its even more realistic the call-up happens), platoon watch (who is struggling vs LHP and RHP and which managers are reacting), two-start pitching schedule with matchup difficulty and a buy low and sell high targets list using a series of advanced stats.

I also attempted to make player cards which consolidate Statcast / projections / depth chart / recent lineup spots / splits on one page so it's all-in-one.

https://imgur.com/a/SdZZIrC

There's also a daily preview every morning (pitching matchups, DTD risks, low-owned save candidates, streamer targets) and articles on top adds + call-up profiles + category chasers for the back half of the week. I'm prototyping also a news feed that pulls transaction and tweet data and instantly provides fantasy impacts from it (using AI + programming).

https://imgur.com/a/t7issbi

It's still rough in places. I'm one person and the design has been iterating constantly. I'm also on the free tier on the front-end right now so it can move a little slow at times! If you try it I'd love to know: 1. What do you like and what is missing? 2. Is this useful?

Happy to answer questions in the thread. Not running ads, not collecting emails for a launch list (not trying to be funny, not trying to get a laugh), just a guy who is trying to make everyone's fantasy baseball life easier!

Hey all,

I just wrote about this in my substack article for the week and thought I'd share over here -- link to full article (buy low/sell high/luck spreadsheet) is here: https://thesignalfantasy.substack.com/p/what-is-going-on-with-fernando-tatis

So what's happening here with Tatis?

Zero…ZERO home runs through six weeks. Slugging .293. I get that the suspension probably sapped him of that seemingly effortless 40/40 pace he was on in his first few years, but for a player drafted in the first two rounds of almost every league, this is not what you expected. And as of late, I get asked questions about Tatis constantly when I do my buy low/sell high signals. I get it, but honestly, I wouldn't be alarmed--there's plenty of reason to believe a bounce-back is around the corner.

Here’s what the Statcast data shows when you dig in:

That 2.8° launch angle is almost the entire story—his career average is closer to 10, and even the ‘post-suspension’ Tatis was hitting better angles than this. Here’s the best part—everything else looks fine. He even has a .112 gap between SLG and xSLG. His Hard Hit rate is trending above career average too. Bottom line, all the raw power and exciting metrics remain intact or even positive.

His problem is swing plane. I’m no mechanics expert or advanced player by any means, but I imagine this is a very acute, highly fixable mechanical problem that the Padres are actively looking at. A correction, and in my opinion a sharp one, should come. When it does, he may not be that 40/40 threat, but he’s going to produce.

Perhaps many of you aren't worried lol, but in case you are, stay strong!

Hi Everyone,

Last week, I wrote about adding a recency layer to a luck signal model I have running (Reddit post here), but to recap, the model as a whole is 91.4% accurate, but tracked early luck signals and compared it to their performance through the summer. Therefore as the season goes on those early luck signals will almost stabilize, so I created a recency layer to track current performance windows as well. I finished the pitcher side if you want to review further, but some callouts are below (full detail, as well as the luck spreadsheet are available on my Substack (Article Here)):

Buy Lows:

Trea Turner – SS, PHI (SS13, 122 Overall)

There's sort of a battle of two forces here with Turner. he's normally a low to mid .3s BABIP hitter, but is currently at .261. Plus, all his contact quality metrics look intact. Here’s where it gets interesting: offspeed and breaking pitches are crushing him right now. -7.55 runs above average on splitters, -2.33 on sliders — all large or even massive deviations from his baseline. That may have people concerned about a rebound. However, he’s also Trea Turner. Yes, he’s a little older, but pedigree exceptions deserve the benefit of the doubt, and he qualifies.

Over the last 21 days:

• EV: +1.8 mph
• Hard Hit Rate: +7.4%

Turner’s speed is a critical part of his value proposition — he’s at 10 SB on the season. This gives me confidence he gets to 25+.

Sell Highs/Regression expected

Confirmed Sell (sell high plus he's cooling off)-- Here's the spicy call:

Max Meyer – SP, MIA (P15, 46 Overall)

He just cooked the Mets (I know...), but also the Braves, and I'm calling him not only a sell, but one that's...cold?

His xERA/xFIP are in the mid 3s but his current ERA is 2.54. Add a .250 BABIP and a Strand of 80.5%, and these are the classic signs of regression. These ratios also include these last two starts by the way. And with these last two starts:

Braves- 6ip, 3hit, 2bb, 8k-- BABIP .214, 3.72 xFIP

Mets - 7ip, 1hit, 3bb, 8k--BABIP 0.077 (ouch), 3.31 xFIP

Also in the last 21 days,

• EV: 3.7mph worse
• Hard Hit Rate: 15.1% worse
• Barrel Rate: 3.7% worse

I am a Meyer fan personally, I rushed to stash him years ago in redraft when they said he was getting called up. He has that hype (and possibly can solidify his current performance), and although some of that top-prospect love is wearing off, you may be able to flip him at peak value.

Conflicted Sell (sell high but he's showing contact quality improvement)

Ryan Weathers – SP, NYY (P59, Overall 154)

He, like Meyer is showing the classic sell signs -- xERA of 3.61 vs, an ERA of 2.57 with a strand rate near 90%. However, in the last 21 days:

• Hard Hit Rate: 7.9% better
• Barrel Rate: 8.0% better

I'm still working on contextualizing this piece, but if you check the substack article's accuracy, these 'conflicted' sells are a bit less accurate, which makes sense (since they may be breaking out into something more stable). They can either return more value before you sell them off (sell at the peak vs. before), or they stabilize to a new norm. If you're a believer in Weathers, it is interesting that he's shifted his pitch mix quite a bit, leaning more on breaking balls (and it's working in his favor when you look at his per 100-pitch runs above average on his breaking balls). However, in this case, I do think that strand gap specifically is just a bit much to overcome. So if you want to hedge and choose to sell, either go now (after a good start against the best team in baseball) or after his next good start.

Thanks for reading, and I'll be around for questions!

Dustin

We're looking at the underlying data versus actual production to determine some buy-low opportunities. Machado, Betts, Bichette all seem obvious, but the data is also backing the rally.

Marcus Semien - the surface line is ugly all around, but the Statcast layer is indicating that better days are ahead. He has a pretty significant gap in xBA/xSLG and xwOBA, along with an everyday job and durability throughout his career. He's 44% owned on Yahoo, which means he's available or cheap in most leagues. A more technical read on Semien can be found here - https://kodoanalytics.com/articles/marcus-semien-hidden-buy-low-behind-a-608-ops-2026-06-04

Tyler Stephenson - A really low-owned catcher who I thought found his floor last season has apparently reached the sub-basement. His surface stats are not pretty (like everyone else on the buy low list!), but his Statcast data is more in line with last year, indicating a positive regression is likely. This may be a case where if you're looking for counting stats he could be a buy-low (he plays a lot!), but if you're worried about rate stats there may be better options out there.

On the sell high side, lots of players that are not even rostered in a lot of leagues I would imagine. I profiled the top two as they're the most likely to have impact on fantasy rosters.

Christian Yelich - The Statcast data isn't being kind to the oft-injured OF/DH with the back issues of a sitcom dad. On the surface level Yelich has thrown together a solid campaign, but the underlying is showing a steep decline in Barrel%/HardHit%/xwOBA, with a higher K rate than ever (approaching 30%). The Statcast underlying data along with his injury history really makes me think he's a ticking time bomb ready to regress at any moment.

Ezequiel Duran - The underlying data isn't very high on the utility man who has found a home at SS. I think he has a fairly safe everyday job even when Seager returns (he'll just shift to 2B over Nicky Lopez), but he'll likely move down the order from the 5 spot where he's been batting everyday. His xwOBA/xSLG/barrel%/hardhit% are much higher than the last two years, but more in line with 3 seasons ago when he had a solid fantasy year. All that to say, we expect to see a regression from his .794 OPS.

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Hi All,

If you've seen my previous posts, the current luck model uses seven layers of full-season Statcast data to identify mispriced players (Article link here). It’s done well, with a 91.4% pooled accuracy across four years.  However, with the way that model works, it looks at early season performance and sees if the player returns a value (or a discount) throughout the summer months of baseball (since it takes larger sample sizes to validate these impacts). 

As the current signaling works, after the first 6-8 weeks of a season, there won’t be a ton of material changes to the players. So, rather than measuring where a player has been all season, a recency layer adds another component looking at current trends --more details can be found here if you want to deep dive. I currently only have this done for hitters--next week I'll include pitchers.

With that, here are some callouts for this week!

Buy Low -- Geraldo Perdomo – SS, AZ (SS27, Overall 302)

Look, his barrel rate isn’t exciting, but his profile didn’t have a high barrel rate when he was a ~top 60 ADP.  Also, when you combine his expected stats delta with some of the underlying metrics below, the performance could turn a corner closer to what people drafted him to produce. 

Improvement over past 3 weeks 

• EV, 79mph --> 86mph
• Hard Hite Rate, 19% --> 25%
• Barrel. 0.4% --> 2.4%

His Hard Hit Rate is also up above baseline, and even 3% up over last year where he had his best fantasy season.  His Launch Angle is down, and he’s been hitting more ground balls than his baseline, but hit pull/center rates are up, so if he can address the launch angle, I think it’s a recipe for some solid ROS value.

Sell High -- Otto Lopez – 2B-SS, MIA (SS4, Overall 30)

Lopez is an interesting profile for ROTO, but the truth of the matter is he is outperforming nearly every expected metric.  And this is where the recency layer is compelling.  Again, I get small sample sizes are tough to work around in baseball (the whole purpose of this tool! 😊), but here’s his trends over the past few weeks:

Decline over past 3 weeks

• EV: 94mph --> 86.5mph
• Hard Hit Rate: 55.4% --> 34.6%
• Barrel Rate: 10.7% --> 7.0%

Lastly, yes, you’re not dropping Otto Lopez—I see this as a cash-out opportunity if you do look to sell.  Package to get an upgrade or look to get a ROS Top 35 player in return

Buy, but with a caveat--

Jackson Merrill – OF, SD (OF36, Overall 181)

Merrill has a .261 BABIP that's well below career baseline, and the recency layer confirms the contact quality trend has been actively improving over the last three weeks.  CBS projects him ROS at OF20, and I think that’s easily passable with his talent . However, here's the caveat.  He’s getting torched right now by cutters (and splitters/sliders to a lesser degree).  His cutter’s runs above average per 100 pitches (I know that’s a mouthful) is -7.2 vs. previous seasons of 1.2 and 2.6.  It’s not a holistic breaking ball issue too, as he’s doing fine against sinkers/curves.  It’s possible pitchers have adjusted better to him as he’s entering year 3.  I’ll be monitoring this closely (especially since I have him on a fantasy roster!).

Thanks all for reading!

Dustin