There are still a number of hitting metrics to review the extreme cases, so let’s continue the weird and the wonderful on the batting side before moving over to the pitching side.
Today is Statcast day, so I’ll review hitters at the extremes of the various Statcast metrics we share on FanGraphs.
Yesterday, I reviewed some of the early 2023 outliers in various hitting metrics. Since there are so many metrics, we’ll continue on the fun. Yesterday, the focus was on strikeout and walk rates. Let’s now flip over to batted ball metrics.
In past years, I have reviewed some of the most extreme performers in various categories after around a week of play. Though not necessarily actionable, it was fun to see the players and stats that stood at the top and bottom of the leaderboards. It’s a bit later than I have normally reviewed the weird and the wonderful historically, but that doesn’t mean there isn’t any wackiness going on! So let’s review some of the outliers a couple of weeks into the season.
Yesterday, I identified and discussed the starting pitchers with at least 20 IP this season and last who have raised their SwStk% marks most. Today, let’s now look at the decliners, the pitchers who have suffered the largest SwSk% declines. We’re still in small sample size territory, but such significant declines are still worrisome, especially if paired with a velocity drop.
It’s still quite early to evaluate outcomes like strikeout and walk rates, so let’s stick with underlying drivers of those metrics, like SwStk%. Typically, the higher a pitcher’s SwStk%, the better the pitcher and the lower the ERA, though obviously that’s not going to be the case 100% of the time since we’re ignoring walk rate. But SwStk% gains are almost always a good thing, as that should result in a higher strikeout rate, which means fewer balls in play and therefore fewer hits allowed. So let’s dig into the starting pitchers (with at least 20 innings pitched both this season and last season) that have raised their SwStk% most.
Yesterday, I reviewed the hitters who have most underperformed their xwOBA marks so far, which included a number of names that would make for good trade targets. Today, let’s flip over to the overperformers. I hesitate to make a blanket statement that these guys should be sold high if possible, as each deserves their own evaluation. So let’s dive in.
We’re about two and a half weeks into the season, which means impatient fantasy owners are going to start cutting or selling low on their slow starting hitters. Before making such rash decisions, it pays to check out the hitter’s Statcast xMetrics. While the metrics have their flaws, it’s the best data we currently have to determine a hitter’s expected performance given their actual batted balls. So let’s review the hitters who have most underperformed their xwOBA marks. This could be your early trade target list if you don’t own these names, and if you do own them, perhaps it’s a reminder to hold strong.
Let’s jump back over to the relief pitcher fastball velocity gainers. The sample sizes here are even smaller than for starting pitchers, so I arbitrarily required a minimum of five innings pitched this year since velocities will fluctuate from outing to outing. A reminder that if I’ve already discussed the pitcher in my first review, I will not be posting comments about the pitcher again as nothing will have changed. Instead, just celebrate that the pitcher is still on the gainer list and hasn’t fallen off of it if you’re an owner!
It’s been about a week since I last reviewed the starting pitcher fastball velocity gainers, so let’s take another look. Velocity does fluctuate from start to start, so even though it’s far more meaningful in one game than a pitcher’s walk rate in that game, it’s still subject to the same small sample size caveats as any other metric. So with a bunch more innings in the books, let’s revisit the fastball velocity gainers. It’s also important to check the game logs and see if the velocity has been consistent, or if the average was inflated by just one outing. Finally, it’s helpful to check the maxVel, because a pitcher might not actually be throwing harder, but instead the smaller sample has reduced his lower velocity fastballs that over a season would bring down his average.
With only around 7% of the season in the books, it’s still far too early to evaluate the majority of performance metrics. But we still want to analyze something, so let’s review the hitter SwStk% improvers versus last year. I chose SwStk% instead of strikeout rate, as the former has a 0.76 correlation with the latter from 2018 to 2022. There’s less noise in SwStk% than strikeout rate, so it’s a better skill metric to evaluate this early, rather than an outcome statistic. Remember, the sample sizes here are small and contact ability could fluctuate throughout the season. But hitters improve their strikeout rates all the time, which could lead to a breakout given the additional balls in play. Cutting down on swings and misses could be an early sign that such improvement will either continue or occur soon.
