Welcome back to the deep league waiver wire. You must have missed my weekly Wednesday recommendations oh so dearly. This week, we focus on being proactive with a hitter and reactive with a new closer.
Yesterday, I used my xHR/FB rate equation to identify and discuss eight hitters whose marks suggest an imminent surge in their actual HR/FB rates. Today, let’s check in on seven fantasy relevant hitters on the other side of the coin — those whose xHR/FB rates are well below their actual marks, suggesting near-term downside.
It’s been a while since I calculated my xHR/FB rate equation and compared its results to each hitter’s actual marks. So let’s discuss eight names, plus two bonus names, with HR/FB rates that fall most short of their xHR/FB rate marks. While there are no guarantees in life, especially baseball, there’s a strong chance that each one of these hitters raises their HR/FB rates the rest of the season, assuming they can maintain the underlying skills driving the marks.
It seems like it’s been a decade that we’ve been waiting for a Kyle Gibson breakout. But, this is only his sixth MLB season. Surprisingly, to me at least, he’s actually already 30 years old. It’s not often that a 30 year old pitcher with six seasons under his belt suddenly breaks out.
Who needs a catcher? We all do! Find your new one here. In addition, jettison your 5.00 starter for this studly middle reliever.
Back from Portugal! Thankfully, technology is amazing and I haven’t missed a baseball beat. Before I left, I listed and discussed the starting pitchers who had posted significantly worse wOBA against marks than their Statcast xwOBA marks. So today I’ll look at the pitchers on the other side of the coin, those who have most outperformed their xwOBA marks, and therefore may be in for some serious regression.
Earlier this week, I looked at Statcast’s expected metrics to identify hitters who may improve or decline from their current ISO marks. Today, let’s talk pitchers. I’m simply going to sort the Expected Stats leaderboard by difference between wOBA and xwOBA and discuss the fantasy relevant starting pitchers with the biggest negative gaps between wOBA and xwOBA (higher wOBA than xwOBA). Remember that xwOBA fails to account for home ballpark, defensive support, quality and opposition, and perhaps other factors I’m not able to come up with at the moment. It’s why I stick to the extremes, as even with all factors accounted for, it’s highly likely these guys are still due for the same directional move in wOBA, though perhaps not to the same degree.
After many years in AL Tout Wars, I finally discovered one of the major keys to success – anticipation. Picking up players before their call up who may have a significant fantasy impact is a wise move. I had written down the names of two of these players last week, but unfortunately I once again forgot that we had moved the FAAB deadline to 1 PM from midnight and therefore failed to make any bids. Naturally, both players were bid on, but it probably didn’t matter for me as I likely would have been outbid.
Yesterday, I used the Statcast expected metrics to calculate player xISO marks, then comparing them to actuals. I began by looking at those hitters who have posted ISO marks most below their xISO marks, suggesting the potential for significant upside in the near future. Today, let’s discuss hitters whose actual ISO marks have most exceeded their xISO marks, suggesting possible downside.
This year, the Baseball Savant pages at MLB.com have shared even more data, as new metrics are being calculated and published for our analytic pleasure. The Expected Statistics page calculates a hitter’s expected batting average, slugging percentage, and wOBA. Sweet! Though I can’t recall any exhaustive research studies on the predictive power of their expected metrics, I know the Statcast guys are top notch and trust they have done a good job.
