Archive for Hitters

Yesterday, I used Statcast’s xBA calculation to discuss the hitters whose batting average’s have most underperformed and could be due for a surge over the rest of the season. Today, let’s flip over to the hitters who have most overperformed their xBA marks as calculated by Statcast. This group could suffer a batting average decline over the rest of the season, and perhaps a significant one, without a dramatic change in underlying skills, like strikeout rate.

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There is a fifth dimension beyond that which is known to fans. It is a dimension as vast as the width of two balls and as timeless as infinity. It is the middle ground between light and dark, between strike and ball, and lies between the pit of a batter’s fear and the summit of his bat’s knowledge. This is the dimension of imagination. It is an area which we call the Shadow Zone.

The entire zone can be divided into four attack zones, starting at the heart, and moving out to the shadow zone (the width of a ball on the inside and outside of the strike zone), which is followed by the chase and waste zones.

We’ll be focusing on the shadow zone, home of pitcher’s pitches and balls framed to strikes, looking first at the players who are offering at these borderline pitches the least in 2021. However, swinging less at shadow pitches doesn’t guarantee success and some hitters are better served by being more aggressive. Like most things, it’s a case-by-case situation. Read the rest of this entry »

While we know that ratios like batting average bounce around during the year, it still takes discipline to look past your hitter’s .194 average through a quarter of the season and vow to hold him, waiting patiently for the rebound you hope occurs. Sometimes, that .194 average is deserved, though that still doesn’t necessarily mean we should expect it to remain that low. Other times, a heaping of poor fortune is mostly to blame for the low average as the hitter actually deserves a higher mark. In the latter, you might have more confidence in a rebound. Let’s use Statcast’s xBA and compare it to actual BA to see which hitters have the most potential for a BA surge over the rest of the season, according to its calculation. Since Statcast isn’t recalculating a balls in play number, then this all falls onto BABIP, so I have included that mark in the below table as well. Just keep in mind that Statcast ignores anything shift-related, so on the whole, hitters most prone to grounding into the shift are going to going to underperform their xBA marks.

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Let’s continue our look into the hitters who have been starting regularly that you may not have even realized. Will their every day playing time continue, and if so, in which leagues, if any, are they worthy of your starting roster?

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Injury and poor performance results in a constant stream of new everyday starters in team lineups. It could be difficult to keep up and notice these changes unless you own the guy who no longer has a starting job. So let’s dive into some of the hitters who are now getting an opportunity to play every day and figure out whether that playing time will continue and whether there’s potential positive fantasy impact.

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Yesterday, I identified and discussed the hitters who have most underperformed their Statcast xHR totals. Today, let’s flip to the other end — those hitters who have most overperformed their Statcast xHR marks.

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It hasn’t received a whole lot of fanfare, but Statcast has its own xHR calculation. It defines xHR as Ballparks Gone At/30, though I am unable to find any explanation on how to calculate “ballparks gone at”. The leaderboard does tell us that “environmental variables (elevation/weather/wind/etc…) not factored into these values”, which is essentially an acknowledgement that the calculation isn’t perfect. Environmental factors are real and have an effect on home runs, so you could get most of the way there by ignoring them, you’ll never get all the way there. That said, this metric is seemingly the quickest and easiest way to determine which hitters who have luckiest and unluckiest in the home run department, which is important over a small sample of at-bats. So let’s dive into the biggest underperformers, those hitters whose actual home run total is most below their xHR total.

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The Is It Too Early Episode of the Beat the Shift Podcast – a baseball podcast for fantasy baseball players.

Guest: Ian Kahn

Strategy Section

• Is it too early?
  • Is it too early for individual scoring categories to matter?
  • Is it too early to play the matchups based on category standings?
  • Is it too early to punt categories or to alter your pre-season strategy?
  • Is it too early to evaluate how you did at the draft table?
  • Is it too early to cut a player that you spent meaningful draft capital on?

Hot / Cold Starts

• Cold Players
  • Patrick Corbin
  • Luis Castillo
  • Lourdes Gurriel Jr.
  • Francisco Lindor
• Hot Players
  • Cedric Mullins
  • Byron Buxton
  • Jazz Chisholm
  • Matthew Boyd
  • Danny Duffy

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Yesterday, I identified and discussed the hitters who have underperformed their xwOBA marks by the most significant margin. The list made for a good initial group of potential “buy at a discount” candidates. Today, we flip to the other end, those hitters most overperforming their xwOBA marks. The gaps here are much smaller than on the underperformer list. Once again, it is important to remember that xwOBA isn’t meant to be predictive, so don’t automatically assume these hitters will soon suffer a significant decline in wOBA to meet their xwOBA marks. Instead, it’s a backwards looking metric and would be better used to evaluate how the hitter should have performed. Just like I use SIERA instead of ERA in the early going to get an idea of how the pitcher has pitched, sans luck, I would lean toward using xwOBA instead of actual wOBA to evaluate how a hitter has performed.

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Looking at five big performances from unexpected sources to determine their staying power in the coming weeks and months.

Christian Arroyo | BOS, 2B

Arroyo has been a surprise standout for the Red Sox, hitting .302/.353/.413 in 69 PA and occasionally hitting atop the lineup. He was a top 100 prospect multiple times back when he was the Giants but has become a bit of journeyman since then moving from the San Francisco to Tampa Bay to Cleveland and finally to Boston. At the risk of being simplistic, the fast start seems almost entirely attributable to his .404 BABIP. There has been virtually zero power (.111 ISO) thanks to a massive groundball lean (62%).

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