In late April, after about a month of the season was in the books, I compared starting pitcher Stuff+ grades to their marks from the 2024 season, identifying the risers and fallers. Just like with any other metric, could pitcher go on a stuff hot streak or suffer through a slump? Or does such changes early on tend to stick? Let’s review the names to see how they finished the season in both Stuff+ and strikeout rate, which correlates strongly with the former.

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The preseason and early season reviews continue! Today, I’m going to review the early starting pitcher velocity changes to find out if the gainers held onto their gains and if the decliners suffered their losses all year. Since we know that fastball velocity positively correlates with strikeout rate, I’ve included the change from 2024 to 2025 as well to see if both moved in the same direction.

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At the beginning of April, I took a super early look at hitter maxEV gainers. Obviously, a hitter had all season to record that maximum exit velocity, so a lower maxEV than the previous year at the time was not a cause for concern. However, if a hitter had already posted a meaningfully higher maxEV than the previous season, did that turn out to be an early indicator of a power breakout? Let’s review the names and find out.

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At the end of March, I dove into the hitter average bat speed risers and fallers. I realized afterward that although the metric stabilizes rather quickly, it was still simply too early to conclude anything. So I then discussed risers and fallers again with two posts back-to-back in mid-May. Let’s find out if these hitters maintained their mid-May levels, and if so, if it impacted their performance in the same direction as the bat speed change.

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Yesterday, I reviewed my $14 NFBC offense, filled with 14 hitters with an average auction value of $1 in late February when I published my imaginary roster. Today, let’s now flip over to reviewing my fake $9 pitching staff. I would imagine it’s easier to hit on some big wins from the crop of $1 pitchers than $1 hitters, so let’s see if that was the case this year. As a reminder, I rostered three true hits on the hitting side, composing just over 21% of my team. Did I do better on the pitching side?

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One of the most enjoyable things I’ve been doing over the last couple of years is creating imaginary NFBC teams based on their average auction values (AAV). It’s a fun way to identify potentially undervalued players since I’m using actual market values and not just speculating. Today, let’s review my $14 NFBC offense, which is comprised of, you guessed it, only players with an AAV of $1.

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In early February, I compared 2024 actual wOBA to xwOBA to identify players who might be in for a wOBA surge or decline in 2025, based on the gap between to the two metrics. Let’s now review these lists to find out how the players actually performed. Did the potential surgers actually surge and did the decliners actually suffer declines?

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This year, a new projection system called OOPSY by Jordan Rosenblum joined our preseason forecasts. I decided to put it to the test by comparing its wOBA projections to those of our Depth Charts to identify the hitters it was most bullish and bearish on. With the final numbers now in the books, let’s see which system more accurately forecasted these players’ wOBA marks.

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Last week, I reviewed my preseason top 40 first base rankings. There were some glaring omissions from that post for two reasons. First, there are always going to be hitters who gain eligibility at a new position that won’t be ranked there during the preseason. Second, there are usually going to be some surprise names off most radars who end up in the top 40, but failed to be ranked there. So today, let’s discuss the 12 hitters who finished among the top 40 first basemen, but were unranked.

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Preseason article review season continues! Today, let’s look back on a 2025 preview post where I identified potential HR/FB rate surgers and decliners. While I used to use my own xHR/FB rate equation when I projected a player’s HR/FB rate for the upcoming season, I decided to simplify things for this exercise. Instead, I used a metric I came up with called Barrels/(FB+LD) to help me come up with a list of names on both ends of the spectrum. So with the background out of the way, let’s review how these hitters ended up performing.

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