Though I’m not sure there’s a particular comparison study that makes such a definitive conclusion, it certainly feels like pitchers’ underlying skills are far more volatile during the season than batters. While that usually shows up in strikeout and walk rates, we also might see it in new stats like Stuff+. So it’s worth tracking recent trends to identify pitchers whose stuff has either improved or deteriorated as that could explain recent performance and potentially predict future performance better than if using stale Stuff+ marks.

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It’s been nearly a month since I took my last look at batter xwOBA underperformers and overperformers, and a lot could change during that time. So let’s revisit the hitters who have underperformed and overperformed the most, determine whether it’s been a consistent trend, and decide if the hitter is due to perform closer to his xwOBA the rest of the way.

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Before I decided on the topic of this article, I was randomly wondering which hitters have enjoyed the largest skill gains and suffered the biggest declines. Whose skills have actually surged most and whose have collapsed? Lucky for us, we have an all-encompassing metric that accounts for the majority of underlying skills, Statcast’s xwOBA.

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Every single year, there are hitters that seemingly come out of nowhere to post fantasy seasons worthy of shallow mixed league starting rosters. Whether it’s driven by more playing time than expected or a surprise skills surge, these are the types of players that win leagues. The challenge is determining which hitters are for real and will continue delivering positive value the rest of the season, and which are merely on hot streaks that will end soon, at which point they’ll be dropped in the majority of leagues. Let’s discuss 10 such names.

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Last week, I discussed disappointing unproven hitters that would likely be easier to buy low on, if you so chose, than proven veterans. Today, let’s shift over to guys we’re really talking about when targeting buy low candidate. The caveat here is that most owners will not be willing to sell low, so it’s going to be more difficult to succeed here. Let’s now dive in and decide which names are worth pursuing.

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Similar to Stuff+’s strong correlation with strikeout rate, Pitching+ sport a -0.506 correlation with ERA among pitchers who recorded at least 100 innings from 2021 to 2025. That means the higher the Pitching+, the lower the ERA. The correlation isn’t quite as strong as Stuff+, but still quite meaningful. So let’s dive into the starting pitchers that have enjoyed the biggest Pitching+ gains and suffered the largest losses this year. We would expect ERA to move in the same direction, but that’s not always the case when lady luck is involved.

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In my recent articles, I’ve mentioned hitter flyball pull% a lot. It’s a metric I rarely see discussed, but hugely important when evaluating a hitter’s HR/FB rate potential. It’s pretty clear why:

If you want to be a home run hitter, you should pull your flies. It’s as simple as that.

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With more than a quarter of the season in the books, buy low and sell high time is in full swing. Between X posts, website articles, and podcasts, everyone is dropping names of players off to cold or hot starts that are candidates to be involved in a trade to extract maximum value. Unfortunately, it’s far easier said than done, particularly if you’re in a competitive league (like one filled with FanGraphs and RotoGraphs readers, of course!). So while it’s easy to tell your readers to buy Gunnar Henderson, Ketel Marte, Fernando Tatis Jr., and Shohei Ohtani, actually executing on such recommendations ain’t.

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Out of all the ERA estimator equations we have, SIERA does the best job at predicting future ERA. That said, they all kind of stink because luck is a meaningful factor here and it’s obviously impossible to predict the type of fortune a pitcher is going to have. Furthermore, underlying skills often change, whether it’s added or reduced velocity driving strikeout rate changes or a pitcher suddenly learning control and improving his walk rate dramatically. So for the ERA equation to be right, it requires the common “all else being equal” caveat that demands that the underlying skills to the same, and that doesn’t always happen.

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I probably wait longer than most to evaluate my team and perform research on potential trades, but with just over a month in the books, it’s definitely trading season for the vast majority. This time of year is when we dive into the underlying skills to determine what’s real and what isn’t, identify trade targets, and review which of your own players should be put on the block.

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