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.
More than most, starting pitchers are creatures of habit and comfort. Certain parks, weather conditions, and opposing teams can have a great impact on performance. Pitching at home in particular can offer a level of comfort. But try telling that to the Athletics pitching staff, who had to go from a minor league park to pitching on the moon in Las Vegas in their miniseries earlier this month.
The reality is that pitchers are individual beasts who each react in their own way to the conditions they perform in, some more than others. In fantasy, we can use this to our advantage, as the gap between performances for some starters, whether at home or on the road, can diverge greatly. Below are the starters with the biggest differential between home and away:
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.
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.
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.
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.
At this stage of the season, the impact of luck, or lack thereof, starts to take form and become a meaningful predictor for the rest of the year.
But BABIP can be a noisy stat in isolation. I wanted to identify which hitters were getting lucky when putting balls in play, but also wanted to add a layer that allows us to assess that luck relative to fantasy value and overall offensive production.
The idea for this piece actually came from a curiosity around one specific hitter, which I will come to later, but it is a useful exercise to get a broader sense of the BABIP landscape as we enter the summer months.
So which hitters are potentially providing an unsustainable output, and which could be worth buying low on or holding onto?
Some teams would call it an embarrassment of riches, but the rise of Emerson Hancock in the absence of Bryce Miller early in the season has left the Mariners in a bit of a bind from a roster construction point of view.
With not enough starts to go around for six starters, Jerry Dipoto, Dan Wilson, and company opted to piggyback Bryce Miller and Luis Castillo. While the results spoke for themselves, it certainly did not look great off the field.
Whether that be Castillo launching his glove and jacket into the benches of Sutter Health Stadium, or Miller himself, very uncharacteristically for a starting pitcher, giving his thoughts rather candidly on the situation.
“This setup is not very comfortable.”
He stated awkwardly, in his post-game interview in Sacramento, before reverting to the usual newspeak we have come to expect from MLB players.
For both Castillo and Miller, there is only one way to remove yourself from any ideas of future piggybacking: pitch so well they don’t remove you.
That is exactly what Miller (and Castillo to a lesser extent, to his credit) has done, so far, since Operation Piggyback began.
So this will be more of a collective analysis of the rough groupings and what stands out from the composite rating, and whether any deeper stats can further support or provide additional context for fantasy purposes.
The composite z-score rating has provided a solid framework for assessing this group of rookies, and most have now logged enough innings to draw early conclusions from the metrics. It is these pitchers who will receive the bulk of the analysis in this piece, while Gage Jump has looked enticing in his two starts — 12 innings is not quite enough for meaningful metric analysis just yet, but well worth keeping a close eye on.
This crop of rookies has now had some time to get adjusted to the big leagues, and this piece will look to check in on how they have measured up so far through the season. Less of a prediction of things to come, but more so of how much we can rely on them at this stage of their young careers. But of course, this is fantasy. So there will be a natural eye on what could be… are some guys getting the rough end of the stick, and are some getting away with it a little?
I wanted to establish a composite rating that accounted for metrics that provided a balanced view of their profile as a pitcher, balanced against their xERA. These metrics were then weighted to favor those I felt were more important and those I want to see in a pitcher. This will be split into two pieces: this one sets up the methodology, so to speak, and the reasoning behind the metrics used for the ranking. The next piece will dive into more of the nuances and any interesting cases the data throws up.
Since 2021, Vladimir Guerrero Jr. has been one of the best hitters in the league. As we enter June, he has just three home runs and his worst power numbers for several years. At this pace, he will finish with nine homers — the same as he managed in the shortened 60-game season in 2020. His top-20 average ADP has resulted in returns that barely put him in the top 20 at first base, and that poses the question: Can this regression be explained?
