Yesterday, I listed and discussed the top 20 starting pitcher SIERA leaders. Since the entire season represents a small sample size, you should be far more inclined to focus on a pitcher’s SIERA, driven by his underlying skills, than the ratios that actually count in your fantasy leagues, ERA and WHIP. The underlying metrics fueling SIERA stabilize far quicker and account for skills pitchers have more control over. It therefore makes for a significantly better rest of season projection, even though SIERA is meant to be backwards looking, not forward looking. With that said, let’s check in on the bottom 20 pitchers in SIERA and discuss the interesting names. As a reminder, just because a pitcher finds his name here doesn’t mean you should drop him or trade him away, as the pitcher could improve his skills, pushing his SIERA down into more attractive territory.

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Even though we are about halfway through the season, the league leader in innings pitched sits at just 40.2 innings. That’s far too small a sample size to find much meaning in traditional surface statistics such as ERA and WHIP (plus LD%, HR/FB, BABIP, etc). The results that feed into ERA take significantly longer to stabilize, so it makes more sense to focus on the underlying skills that pitchers have more control over. Luckily, we have a metric that takes all those underlying skills, throws them into a blender, and spits out a skills-based ERA. Of course, I’m describing SIERA, and it’s what I exclusively look at early in the season to forecast future performance, as it’s far better than ERA itself. So with that said, let’s take a gander at the top 20 qualified starting pitchers in SIERA and discuss any surprises.

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With a mid-to-high 90s fastball that has touched as high as 101 MPH and an elite splitter that has generated a SwStk% over 20% every season of his career, a lot has been expected of Kevin Gausman. You figured that with a two-pitch foundation like that, he would be racking up the strikeouts and rank as one of the better pitchers in baseball on an annual basis. And while he’s posted a couple of seasons of sub-4.00 ERAs, the underlying skills just haven’t been super impressive, and he sports a career ERA of 4.31. That’s perfectly serviceable, especially in a hitter friendly home park for most of his career in the American League. Sure enough, his career ERA- stands at an almost perfectly league average 101. So he’s been fine, but not what fantasy owners hoped for.

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Yesterday, I identified and discussed the hitting leaders in Max Exit Velocity (MEV). While acknowledging that MEV doesn’t tell the entire story you want it to, it’s always a positive to see a higher MEV versus a lower one. Today, let’s check in on the laggards. Naturally, a lot of these are obvious, so I’ll discuss the interesting names.

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Let’s continue perusing our new Statcast leaderboards by checking in on the Max EV (MEV) leaders. This metric is fairly simple to understand — it’s the maximum exit velocity the hitter has recorded on a batted ball this season. Just like I shared when discussing HardHit%, there are caveats for this metric. We don’t know what batted ball type the MEV was achieved. The hope is that it’s a fly ball, so the metric could hint at a batter’s HR/FB rate potential, but that isn’t necessarily the case. We also don’t know how out of character the MEV — is the batter consistently hitting balls nearly as hard, or is this particular EV a clear outlier with the rest of his EV values? Anyhow, clearly all else being equal, hitting the ball harder is better. So with all those caveats and questions out of the way, let’s check out the leaders and discuss the interesting names.

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Yesterday, I shared and discussed the top 10 hitters in Statcast’s HardHit%, a metric now available right here on FanGraphs. Once again, a breakdown of HardHit% (HH%) by batted ball type would be ideal, so this is not a complete analysis. But an overall HH% tells us most of what we want to know, even if it could deceive here and there. So let’s check in on the bottom group in HH%. I want to highlight the surprises, the hitters you would expect to rank much better, and will ignore the guys we expect to be near the bottom.

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Statcast metrics have arrived! So let’s dive right in, starting with the HardHit% (HH%) leaders. As per Statcast, a batter’s hard hit rate is the percentage of batted balls that were hit at 95 MPH or more. While this data would be even more useful if broken up by batted ball type (we care far more about hard hit fly balls than hard hit pop-ups or grounders), the metric still gets us most of the way there. So let’s check out the top 10 leaders and see if we find any surprises.

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Yesterday, I identified and discussed the starting pitcher leaders in Z-Contact%, which is in-zone contact rate. Today, let’s look at the laggards in the metric. I’ll stick with the pitchers who have posted a rate of at least 90%.

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It’s up for debate which one metric best describes a pitcher’s level of dominance. One of those metrics that doesn’t get as much press is Z-Contact%, which is defined as “percentage of times a batter makes contact with the ball when swinging at pitches thrown inside the strike zone”. In fewer words, it’s simply in-zone contact rate. Since all else being equal, a pitch thrown inside the strike zone is easier to make contact with then pitches thrown outside the zone, then one measure of absolute dominance is how often a pitcher generates a swing and miss on pitches thrown inside the zone. If a pitcher’s strikes can’t be hit, how are batters going to hit their balls (unintentional comedy scale: 10/10)?! So let’s look at and discuss the early starting pitcher Z-Contact% leaders. All these pitchers have posted marks below 80% versus a league average of 84.6%.

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Yesterday, I identified and discussed the hitters who have increased their FB% by at least 10% compared to last season. That’s a good thing for the hitters’ home run potential, assuming all their other metrics remain stable. Today, we’ll look at the decliners, those hitters whose FB% marks have fallen the most versus last season. While this might raise their BABIP expectations, it’s bad news for their home run potential, unless their FB% reverts back to previous levels.

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