Just like any other metric we monitor, like average exit velocity, pitch velocity, etc, a hitter’s bat speed fluctuates throughout the year. As exciting as it is to see your favorite breakout pick to raise his bat speed during the first month of the season, it might be just as disappointing to discover he was unable to sustain the jump during the season’s second month. So let’s find out which hitters have gained and lost the most bad speed in May compared to the period through the end of the April.

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In 12-team mixed leagues and shallower, you’re generally ignoring relievers that aren’t closing games or potentially will be given the incumbent’s missteps. That’s not true in 15-team+ mixed and, especially, mono leagues. In such deeper formats, replacement level for starting pitchers is poor. You’re essentially choosing between a 4.50 ERA, 1.35 WHIP, but with perhaps 10 wins and 120 strikeouts, starting pitcher, or a middle reliever with superior ratios, but fewer wins and strikeouts. Typically, the latter is actually more valuable even if he doesn’t record a single save all season. So let’s dive into some of the most dominant non-closing middle relievers this year who might be a better option than your worst starter.

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Yesterday, I reviewed a handful of hitters whose actual AB/HR marks are significantly different from what ATC had projected during the preseason. What was driving the discrepancy between actual and projected? That was the question I was determined to answer. Since there are a lot of breakouts and busts from an AB/HR perspective, plus a number of names on yesterday’s lists had low home run totals, in which a difference in AB/HR would result in an insignificant change in home run total versus expectations, I’m going to do this again.

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We’re almost a quarter of the way through the regular season, and we still find some surprising names among the home run leaders, while others are mysteriously sitting toward the bottom. Since there are a number of components that drive a hitter’s home run total, I like to understand what’s providing the fuel. Identifying the changes in inputs will give us a better idea of whether the current performance is sustainable or we could expect a reversion back to what the hitter had been projected to do all along. So with that in mind, let’s review the AB/HR breakouts and busts.

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Yesterday, I discussed the hitter average bat speed risers and fallers. Thanks to frequent commenter Anon, I discovered that I must have kept the default “Qualified” filter on, which resulted in lots of interesting names being missed. So in today’s review, I’ll discuss the names that would have appeared in yesterday’s list, but were left off. Note that there are lots of bat speed changes, so I’ve kept these posts to changes of at least two miles per hour. Also note that since I relaxed the swing minimum, the lists are now more hand-picked based on fantasy relevance.

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Only a couple of days into the season, I shared the super early hitter average bat speed risers and fallers. Though bat speed does stabilize quickly, it’s still subject to small sample caveats. Now nearly a month and a half later, let’s revisit the metric, as the numbers now will give us a much better idea of which hitters have enjoyed sustainable bat speed increases or suffered from losses.

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We’re just over a fifth of the way through the season, which feels like prime time to start making trade offers. I typically use this time to identify my team’s overperformers and underperforming targets on my leaguemates’ teams and then send out a flurry of offers. You never know how other owners value your overperforming players or whether they have become impatient with their own underperformers. So it’s worth finding out by engaging in trade talks. Today, I’ll review the top underperformers and overperformers by comparing wOBA versus Statcast’s xwOBA. We know the latter isn’t perfect, but it’s the best metric we currently have to evaluate expected performance to-date.

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Last week, I shared that from 2021 to 2024, there has been about a 0.70 correlation between pitcher strikeout rate and Stuff+ grade for those who have recorded at least 100 innings. So then it follows that just like SwStk% and then years later, CSW%, Stuff+ should make for a pretty good proxy of what a pitcher’s strikeout rate should be. Remember, it’s backwards looking so don’t mistake Stuff+ to be predictive, though you would assume if a pitcher currently owns a high/low mark, he’ll continue to maintain that level. So let’s dive into the current starting pitcher Stuff+ leaders and laggards and see if we could identify any who may be in line for an increased or reduced strikeout rate if they maintain the quality of their repertoire.

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Yesterday, I reviewed the starting pitcher risers and fallers in the Stuff+ metric compared to last season. Those lists are super insightful in highlighting pitchers who have seen improvements and declines in the quality of their pitch repertoires. However, a number of pitchers failed to meet my minimum innings requirement last season and were therefore not compared. So today, let’s review 10 pitchers that missed my list due to injury last year or are rookies this season. We can compare the injury returnees to their 2023 numbers and evaluate the rookie marks on their own.

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From 2021 to 2024, there has been about a 0.70 correlation between pitcher strikeout rate and Stuff+ grade for those who have recorded at least 100 innings. That’s pretty significant! It means we have a nice proxy for strikeout rate without having to worry as much about sample size, as strikeout rate could fluctuate wildly after over just a couple of games. I would imagine Stuff+ stabilizes much more quickly. So it’s worth monitoring changes in Stuff+ or newly established marks for rookie pitchers to quickly get a rough idea of strikeout potential. So let’s check in on the starting pitchers who have experienced the greatest gains and losses in Stuff+ compared to last year.

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