We don’t need to wait for the trade deadline to pass to analyze a slew of players who have recently come into regular playing time. So let’s continue our dive into new everyday starters.

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It’s been a while since running a series of New Everyday Starters posts and man, do we have a slew of them right now. Between injury replacements and minor league call-ups, it might be easier than ever to find a replacement for your injured starter. Let’s discuss five of those new regulars and determine if they have a place on your roster.

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It seems like the Rays always have a logjam of hitters and rotations at most positions, and that has now gotten even more logjammy with their acquisition of DH Nelson Cruz. Cruz hasn’t played in the field since 2018, which means for as long as he is starting, the DH slot is going to be filled. That’s bad news for many of their hitters who will likely see a playing time cut, albeit not a significant one since it will likely be a different player on the bench each day. The logjam is likely to worsen again once Manuel Margot returns from the IL. Alas, this isn’t an article on the rest of the Rays hitters, it’s about Cruz’s move from Minnesota to Tampa. From a strictly ballpark change perspective, how might this switch in home venue affect his performance? Let’s consult the park factors.

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Yesterday, I discussed six starting pitchers who had seen their strikeout rates surge the most over the last 30 days compared to the rest of the season to date. Today, we’re going to review the starting pitchers on the opposite end — those whose strikeout rates have declined the most over the last 30 days.

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Pitchers sometimes change rapidly. Whether it’s gaining or losing velocity, altering their pitch mix, changing their delivery, moving on the rubber, or something else, it’s important to pay attention to trends in their underlying skills as it could be very telling. So let’s review the strikeout rate surgers over the last 30 days compared to what these pitchers posted for the season heading into this period.

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The top prospects just keep on coming! On Friday when baseball returned after the all-star break, the Red Sox recalled their third best prospect and 55th overall ranked prospect, Jarren Duran. Then on Sunday, the Angels recalled their top prospect and ninth overall ranked prospect, Brandon Marsh. Let’s dive into each of their statistical records and investigate their chances of fantasy success this year.

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With five of the top 50 preseason top prospects now in the Majors, let’s review their performances and discuss their rest of season outlooks.

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Yesterday, I asked you to vote on which group of pitchers you expect to post a better ERA over the rest of the season. One group was composed of the 10 biggest SIERA overperformers, while the other included the underperformers. For the first time, I’m going to take the same polling idea and use it for hitters. So let’s follow the same concept and compare two groups of hitters based on xwOBA overperformance and underperformance. We know that xwOBA isn’t perfect. Neither is SIERA. In fact, no estimated/expected/forecasted equation is going to be perfect because there will always be a player or multiples that figure out how to do something we have a difficult time quantifying or there’s simply bound to be players each year that fall into either end of the extremes for no reason at all except for randomness. So let’s keep that in mind when reviewing these two groups.

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Since 2013, I have polled you dashingly attractive readers on which group of pitchers you think will post the better aggregate ERA post all-star break. The two groups were determined based on ERA-SIERA disparity, pitting the overperformers versus the underperformers during the pre-all-star break period.

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Last week, I quickly introduced my updated hitter xK% equation thanks to commenter suggestions. Let’s now put the new equation into action and update my potential hitter K% regressor list. The original list used the earlier version of this equation and can be found here. As you might have expected, many of the same names made this new list. The xK% equation is updated, but the result isn’t dramatically different than it had been. So I won’t be discussing the names I did last week, just the new ones.

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