Let’s get back to discussing those non-closing middle relievers, the ones you generally ignore in 12-team mixed leagues and shallower, but deliver real value in deep mixed and mono leagues, despite the lack of saves.
It’s been nearly a month and a half since I last reviewed the starting pitchers who sported the greatest gap between their ERA and xERA marks. So let’s revisit these lists as they could provide you with a quick group of buy low and sell high candidates.
Statcast has enough toys to keep us nerds busy for months going down rabbit holes and digging into various metrics and numbers galore. One of the expected metrics I’ve rarely used and haven’t reach much about is xHR. It’s exactly what it sounds like, Statcast’s equation that calculates an “expected” home run total.
It’s been just over a month since I last reviewed the hitters that had most underperformed and overperformed their xwOBA marks. I’m not going to review how they have performed since, as the idea is for rest of season production, not just the next month.
Yesterday, I dove into the new Statcast bat tracking metrics to learn whether the metrics are any better at predicting HR/FB rate than what we already have, namely Barrel%. Sadly, the answer was no. However, that doesn’t mean these new metrics are useless, of course. As we collect more and more data and sample size issues go away, we’ll be able to investigate more with significantly greater confidence in the results.
You should all know by now that Statcast recently made their bat tracking data public. This is a big deal! Our own Ben Clemens made some early observations and also shared what the data does and doesn’t tell us, which included a correlation table between the new metrics and the familiar.
Yesterday, I reviewed the seven rookie hitters who had recorded the highest plate appearance total so far this season. Let’s continue on down the PA column for a final six.
We’re about a quarter of the way through the season (sheesh, that went fast!), so now is as good a time as any to review the performances of the rookie hitters. Today we’ll start with about half the crop I ultimately want to discuss, and we’ll do the rest of the freshmen tomorrow.
Like discussed with hitters yesterday and last week, a pitcher’s batted ball type profile is important and helps drive their BABIP and HR/9 rate. More grounders and line drives allowed usually result in a higher BABIP, while more fly balls allowed usually result in a higher HR/9 rate. So with that in mind, it follows that changes to a pitcher’s profile could change the shape of their performance. Let’s review the five starting pitchers that have raised their GB% the most, along with those who have suffered the biggest declines.
Last week, I identified and discussed the 10 hitters who have raised their fly ball percentage marks by the greatest amount compared to last year. This is important because home runs are a category in the vast majority (all?) of fantasy leagues, and all else being equal, more fly balls results in more home runs. Today, we’ll review the other side of the coin — the hitters who have suffered the most significant declines compared to last year. As a reminder, the odds are the majority of these hitters revert to previous season batted ball type distributions over the rest of the season. However, it’s still a good idea to monitor these rates moving forward as it’s always possible there’s a legit change in approach and these changes stick. If nothing else, the declines here could help explain a disappointing home run total so far.
