Yesterday, I identified and discussed the hitters who have underperformed their xwOBA marks by the most significant margin. The list made for a good initial group of potential “buy at a discount” candidates. Today, we flip to the other end, those hitters most overperforming their xwOBA marks. The gaps here are much smaller than on the underperformer list. Once again, it is important to remember that xwOBA isn’t meant to be predictive, so don’t automatically assume these hitters will soon suffer a significant decline in wOBA to meet their xwOBA marks. Instead, it’s a backwards looking metric and would be better used to evaluate how the hitter should have performed. Just like I use SIERA instead of ERA in the early going to get an idea of how the pitcher has pitched, sans luck, I would lean toward using xwOBA instead of actual wOBA to evaluate how a hitter has performed.

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We’re about one sixth of the way through the season now, so while the sample sizes of performance and advanced underlying metrics remain small, they aren’t completely meaningless like they were a week or two into the season. So let’s begin evaluating surface results on the hitting side by looking at Statcast’s xwOBA and comparing it to actual wOBA. As a reminder, xwOBA is not a predictive metric. It’s backwards looking and should be used the same way you might use SIERA for evaluate pitching performance. It’s more of a “how should the hitter have performed”, rather than a “how will the hitter perform”. That’s because it assumes all the underlying metrics driving xwOBA, like walk rate, strikeout rate, launch angle, exit velocity, etc, are all sustainable skills, which certainly isn’t true for all players and all metrics.

So don’t read this table and automatically believe these hitters will match or come close to matching their xwOBA marks over the rest of the season. That’s not how it works. However, do figure these batters have been “unlucky” and should perform significantly better the rest of the way, assuming their underlying skills don’t dramatically change. As a result, this could be your initial acquisition target list before diving deeper.

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Yesterday, I listed and discussed the starting pitchers whose GB% marks of risen by at least 10% versus last season. The caveats here were — even though batted ball profiles stabilize more quickly than most other underlying metrics, the sample size still remains small, and an increased GB% isn’t necessarily “good”, but will likely change the shape of the pitcher’s performance and results. Let’s now move on to the GB% decliners and review those whose marks have declined by at least 10%.

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Over the last two days, I identified and discussed the hitters whose FB% has surged and those whose FB% has declined versus 2020. Today, let’s move over to starting pitchers. Unlike for hitters where depending on the type of hitter they are, the optimal batted ball profile is easier to determine, it’s not as straightforward for pitchers. So this isn’t necessarily a “good” list to be on, but it could change the shape of the pitcher’s performance. More grounders should result in fewer homers, but likely more hits allowed and a higher BABIP. So let’s get to the names of those that have increased their GB% by at least 10%. Of course, remember we remain well into small sample size territory.

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Yesterday, I listed and discussed the hitters who had raised their FB% marks by at least 10% versus 2020. Let’s now switch gears to those hitters who have seen their FB% marks decline by at least 10%. Remember these are still very small sample sizes, so the odds are the majority of these hitters return to their normal batted ball distributions by the end of the season. Still, it’s worth monitoring these names as FB% changes could have a big impact on a hitter’s fantasy value.

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There still isn’t a whole lot to evaluate just about two and a half weeks into the season, but batted ball profiles are one of the few that could signal a change in plate approach that lasts all year. As one of the primary drivers of hitting home runs, let’s look to fly ball rate to see who has increased their marks versus 2020 so far. All else being equal, a higher fly ball rate will result in more homers, so paying attention to a hitter’s batted ball profile is important.

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Today marks the final installment of this season’s wacky small sample rate discussion. Let’s finish things off by sticking with starting pitchers, but moving along to the plate discipline metrics.

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Over the last two days, I have shared the wacky rates hitters have posted over the small sample early season so far. Let’s now jump to starting pitchers. Only a handful of starters have made three starts so far, while the rest are sitting on just one or two. So these rates are not very meaningful, but are fun to look at.

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Yesterday, I discussed a whole bunch of hitting metrics and who currently leads and lags the league. Things be crazy this early in a season. I didn’t quite finish diving into all the metrics I wanted to, so today I’ll check in on the batted ball type related metrics. Let’s find out who is part of the weird and wonderful today.

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What I love about the first couple of weeks of the baseball season is all the crazy rates players are posting. In small samples, the range recorded in all metrics is much wider than over a larger sample. Obviously, the larger the sample, the more a player’s performance will revert toward his true talent level. In only eight to nine games, anything goes! So for fun, let’s take a gander at some of the weird and wonderful rates that have been posted by hitters so far.

So there’s at least some care given to sample size, I limited my dive to hitters who have recorded at least 30 plate appearances.

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