Let’s continue our search for new everyday hitters, which continue to pop up on a seemingly regular basis.

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I’m sure I’m not the only fantasy owner ravaged by injuries this year. With multiple injuries seemingly occurring every day, new players are getting opportunities for regular playing time. Of course, poor play by the incumbent may be another reason for new opportunities. Let’s discuss a bunch of these new everyday starters and determine whether they are worthy of your attention.

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Yesterday, I used Statcast’s xBA calculation to discuss the hitters whose batting average’s have most underperformed and could be due for a surge over the rest of the season. Today, let’s flip over to the hitters who have most overperformed their xBA marks as calculated by Statcast. This group could suffer a batting average decline over the rest of the season, and perhaps a significant one, without a dramatic change in underlying skills, like strikeout rate.

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While we know that ratios like batting average bounce around during the year, it still takes discipline to look past your hitter’s .194 average through a quarter of the season and vow to hold him, waiting patiently for the rebound you hope occurs. Sometimes, that .194 average is deserved, though that still doesn’t necessarily mean we should expect it to remain that low. Other times, a heaping of poor fortune is mostly to blame for the low average as the hitter actually deserves a higher mark. In the latter, you might have more confidence in a rebound. Let’s use Statcast’s xBA and compare it to actual BA to see which hitters have the most potential for a BA surge over the rest of the season, according to its calculation. Since Statcast isn’t recalculating a balls in play number, then this all falls onto BABIP, so I have included that mark in the below table as well. Just keep in mind that Statcast ignores anything shift-related, so on the whole, hitters most prone to grounding into the shift are going to going to underperform their xBA marks.

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Yesterday, I listed and discussed eight starting pitchers who have gained the most fastball velocity in May versus April. Let’s now check the flip side — those pitchers who have lost the most velocity in May compared to April. This could be the first warning sign of a reduced level of performance, or worst case scenario, injury.

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Pitchers change their underlying talent/skill levels much more frequently and quickly than hitters do. That’s because it could be as simple as gaining/losing velocity or altering their pitch mix. One way to get ahead of the crowd in identifying changing talent levels is by comparing in-season fastball velocity. So let’s find out which starting pitchers have gained the most fastball velocity in May versus April. I included their respective strikeout rates and SwStk% marks so we could see if the added velocity has already resulted in more punchouts.

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Let’s continue our look into the hitters who have been starting regularly that you may not have even realized. Will their every day playing time continue, and if so, in which leagues, if any, are they worthy of your starting roster?

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Injury and poor performance results in a constant stream of new everyday starters in team lineups. It could be difficult to keep up and notice these changes unless you own the guy who no longer has a starting job. So let’s dive into some of the hitters who are now getting an opportunity to play every day and figure out whether that playing time will continue and whether there’s potential positive fantasy impact.

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Yesterday, I identified and discussed the hitters who have most underperformed their Statcast xHR totals. Today, let’s flip to the other end — those hitters who have most overperformed their Statcast xHR marks.

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It hasn’t received a whole lot of fanfare, but Statcast has its own xHR calculation. It defines xHR as Ballparks Gone At/30, though I am unable to find any explanation on how to calculate “ballparks gone at”. The leaderboard does tell us that “environmental variables (elevation/weather/wind/etc…) not factored into these values”, which is essentially an acknowledgement that the calculation isn’t perfect. Environmental factors are real and have an effect on home runs, so you could get most of the way there by ignoring them, you’ll never get all the way there. That said, this metric is seemingly the quickest and easiest way to determine which hitters who have luckiest and unluckiest in the home run department, which is important over a small sample of at-bats. So let’s dive into the biggest underperformers, those hitters whose actual home run total is most below their xHR total.

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