Of the three ERA estimators available on FanGraphs (SIERA, xFIP, FIP), SIERA is the best at predicting future ERA, even though it was designed as a backwards-looking metric, like the other two. If you’re still using xFIP or FIP in your pitcher analysis, then stop, and immediately switch to SIERA. In a short 60 game season, focusing on SIERA, rather than ERA, is even more important when forecasting a pitcher’s future performance.

The underlying skills that drive SIERA stabilize more quickly and the metric isn’t influenced by the gyrations of the three “luck metrics” — BABIP, LOB%, and HR/FB — which don’t have enough time to settle around the pitcher’s true talent level. ERA is heavily influenced by how a pitcher performs in those three metrics, but there’s far too much randomness involved to place significant weight on them, even over a full 162 game season. Remember though, even SIERA isn’t perfect because there are pitchers who consistently underperform or outperform due to some skill or lack thereof that has been a challenge to identify.

So let’s review the pitchers who underperformed their SIERA marks most this season (minimum 40 innings pitched). I’ll identify which of the three luck metrics fueled that underperformance and discuss whether there’s a chance the pitcher underperforms again in 2021 or reverts closer to his SIERA (I’ll only discuss the fantasy relevant names).

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Yesterday, I identified and discussed the hitters whose SwStk% marks improved the most versus 2019. Today, let’s check in on the opposite end of the list. Remember that “decliner” in this context actually means these hitters’ SwStk% marks have increased, so their skill declined, but the metric we’re using to evaluate their skill has risen.

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Let’s continue on with our look at the plate discipline metrics by moving onto swinging strike percentage (SwStk%). With a strong correlation of 0.77 (qualified batters from 2015-2019), SwStk% is a good proxy for strikeout rate and the two will usually move in the same direction. Because SwStk% uses a denominator of total pitches, versus K%’s use of plate appearances as its denominator, it takes far less time for SwStk% to become meaningful. As such, the value of the metric increases in a shortened season like 2020. So let’s review the 2020 batter SwStk% improvers.

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Yesterday, I identified and discussed the hitters that improved their O-Swing% the most versus 2019. Today, I’ll check in on the other side of the ledger. While I titled this post “decliners”, what that really means is a decline in skill, assuming a lower O-Swing% is representative of greater skill. So these are the hitters whose O-Swing% increased the most versus 2019.

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The Plate Discipline stat section provides us with a lot of “underlying skill” information. Since these metrics use a denominator that grows more quickly than more traditional metrics such as strikeout and walk rates, they are more useful over small sample sizes, especially after a short season. So let’s now move on to hitter O-Swing% to learn which hitters reduced their swing rate on pitches outside the strike zone and which swung more often at such pitches. Since 2019, O-Swing% had about a -0.74 correlation with walk rate, so it’s clearly that holding back on swinging on pitches outside the zone is an excellent indicator of plate patience and current/future walk rate.

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Yesterday, I reviewed the biggest hitter Z-Contact% improvers. Today, let’s flip to the decliners.

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Let’s move along in our 2020 review of underlying skill metrics to the plate discipline rates. While the shortened season makes it difficult to evaluate many metrics, and especially counting stats, plate discipline rates don’t take as long to reach a reasonable sample size because it uses a pitch-based denominator which ends up as a larger number than most other rate denominators. From 2015 through 2019, Z-Contact% had a correlation coefficient with K% of about -0.82 when requiring a minimum of only 100 plate appearances. That’s pretty darn strong! So let’s review and discuss the Z-Contact% improvers versus 2019, that recorded at least 100 plate appearances in each season.

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Yesterday, I listed and discussed the fly ball pull percentage (FBP%) surgers versus 2019. Though the shortened 2020 season means we have far smaller samples sizes to evaluate and significantly less meaningful data, changes to batted ball type data like fly ball rates, pull rates, and fly ball pull rates, are worth noting. They could signify a real change in plate approach that could carry over to 2021. Today, let’s review the hitters whose FBP% dropped the most versus 2019.

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Since 2015, pulled fly balls have left the park 33.1%, while the HR/FB rates of balls hit to the center of the park and opposite field sat at just 8.9% and 4.4%, respectively. Clearly, if a batter is trying to hit a home run, pulling his fly balls should give him the best chance. So knowing how important pulling fly balls is to hitting home runs, let’s review the fly ball pull percentage (FBP%) surgers versus 2019. I’ll discuss the interesting and fantasy relevant names.

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A week ago, I reviewed the average fly ball distance laggards and discussed the surprising names. Today, let’s look at the decliners, those hitters who lost the most average fly ball distance (AFBD) versus 2019. There will likely be some overlap with the laggards list, so I won’t discuss the same names again. Once again, I’ll require a minimum of 10 Statcast fly balls to qualify for the list.

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