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Following on from the hitters chart, we now look at how pitchers have performed so far this year against their OOPSY rest-of-season (RoS) projections.

Continuing with the framework of the hitters’ piece, this will first look at those with projected ERA rises, then at those with projected ERA drops. Just as we identified BABIP and ISO as the major determining factors in the hitters’ RoS outlooks, we will identify a similar through line here: for pitchers, it is largely strand rate.

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As we enter the heat of the post-All-Star break summer, it is a natural point for both reflection and action for our fantasy squads moving forward. This chart plots first-half wOBA against OOPSY’s rest-of-season projection (RoS); the pitching chart will be coming soon. It is a useful way to see the discrepancy between how some hitters have performed and what OOPSY expects for the rest of the season, and to discuss why regression is being projected, and in some cases why it isn’t, across the league.

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Building on the bat speed piece from last week, I wanted to explore some deep-cut young finds based on swing length, blast contact rates, and all the rest. It turns out that if you swing fast, swing fast often, and make consistent contact, you are already highly valued, not just in fantasy but in baseball. Sorting these different metrics gives you a pretty similar list of names at the top of a chart.

For the first piece, I intentionally stuck to bat tracking metrics as much as possible, rather than outcomes, to compare the mechanical profiles of young hitters and to see whether we can use that on its own to predict future success. The problem is that the swing data on its own cannot tell the difference between an MVP candidate and a prospect who has been overmatched. Pete Crow-Armstrong sits in the same neighborhood as Marcelo Mayer, and no amount of bat speed or blast rate separates them.

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Right now, the Major League level seems about as full of young talent as it ever has been. High-profile prospects are more prepared than ever to make the leap, skipping past the slow grind of the minor leagues to make an immediate impact at the big-league level. This season, Kevin McGonigle and JJ Wetherholt have proven it: the former made the All-Star roster, and the latter absolutely should have been included.

Of course, bat speed is not a guarantee of success. The two examples I gave, McGonigle and Wetherholt, have both had great success without elite bat speed, sitting right around league average in the metric. But as indicators go, it can be a useful one. As we can see from the top end of this chart, bat speed can give you a strong platform to build on.

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Every off-season, we hear about pitchers tinkering with their pitch mix, whether that’s simply trying a new grip shown by a teammate, reimplementing old pitches, or reshaping their arsenal. It is always interesting to track new pitching trends to see what sticks in a given season. So I wanted to look at a few pitchers who have made meaningful changes to their arsenal so far in 2026, and how it has impacted their value moving forward.

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Stuff and location have become key parts of pitcher analysis in recent years. It is something I have used a lot in my writing, and I believe it can be a great indicator of success when applied correctly. This can be particularly useful in fantasy when looking to identify pick-ups or diagnose regression.

The relationship between stuff and location is symbiotic, but not exactly equal. To understand this correlation, we can look at how 2026 starting pitchers have performed across metrics and what we can learn through a macro lens when building our pitching staffs across formats. In this chart, we have Stuff+ on the y-axis and Location+ on the x-axis. The higher the pitcher, the more ‘Stuff’ they have, and the further to the right of the chart they are, the better they are at locating their pitches. If you hover over or tap a dot, you can also see how many innings they pitched and their xERA for 2026.

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Having now identified the three hitters who may have suffered the most bad luck so far this season, while still holding real fantasy value and possibly being available in your leagues, it’s time to dig into why.

Through the process of elimination in the In Search of Some Luck piece, we were able to land on three names, which we will break down in this piece. Trent Grisham, JJ Bleday, and Max Muncy.

These three names provide a wide scope of ways a hitter can underperform their expected output, giving not only three potential additions to your fantasy roster, but a wider methodology to consider when looking at why some hitters don’t perform to their expected offensive output.

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Moving on from looking at players who potentially might run out of luck in the previous piece, we now look to the other end of the chart, and some hitters who may be due some good fortune.

While identifying the hitters I thought had potential regression was easy, with plenty of highly-rostered bats in the top region of the chart with interesting data as to why they were outperforming their xwOBA in terms of BABIP, finding who to highlight at the other end was more challenging.

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