In early May, I identified and discussed 17 hitters who had boosted their fly ball rates by at least ten percentage points (30% to 40%, for example) through May 5th. With the fly ball revolution in full swing, these were potentially the newest members. For high HR/FB rate guys, more fly balls is probably a good thing as it will increase homers and runs scored, and probably runs batted in, which should be enough to offset a decline in batting average. Did these hitters maintain their early increased FB% marks or did they experience regression back to 2018 levels over the rest of the way?

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A couple of weeks ago, I devised a deserved barrel rate (where barrel rate is calculated as a percentage of batted ball events, or Barrel/BBE) based exclusively on a hitter’s average exit velocity (EV) and average launch angle (LA). To employ such a simple model, I made a broad but accurate assumption: the average hitter’s average EV (or LA) has a distribution of EVs (or LAs) centered around it, and this distribution does not differ dramatically from other hitters’ distributions.

In layman’s terms, the typical hitter’s average launch angle is his — he owns it, and it reflects his swing plane and mechanics — but he is no better than any other typical hitter in repeating his average launch angle. He, like everyone else, will likely vary from the mean by a certain margin of error. I make the same assumption of exit velocity as well. The two variables bear almost zero correlation to each other. In light of this assumption, the best thing a hitter can do is maximize his exit velocity and hopes it coincides with an optimal launch angle.

(Some folks have suggested I include the percentage of balls hit 95+ mph to refine deserved barrels. The notion intrigues me. However, to illustrate a point: if you have two hitters with identical average EVs, would you expect their distribution of EVs to be dramatically different? Probably not. The inclusion of hard-hit rate accepts as fact that one hitter might be better at hitting 95+ mph more frequently — which would also suggest he hits more softly more frequently as well, and with certainty. This doesn’t stand out to me as a repeatable, let alone necessarily desirable, trait.)

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The best part of small sample stats are the enjoyment we get from finding the weird and the extreme. This year at the beginning of May, I discussed a variety of players riding on one side of the bell curve. Let’s revisit these players and stats and find out how they performed the rest of the way.

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Yesterday, I reviewed the 11 hitters I identified back in late April who my xHR/FB rate suggested had deserved dramatically better actual xHR/FB rates. Today, we flip to the overperformers, those who my equation suggested deserved significantly lower HR/FB rates over that first month. While the equation isn’t meant to be used for predictive purposes, a forecast would likely account for that apparent overperformance and project a lower HR/FB rate the rest of the way. Let’s see what ended up transpiring.

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A hitter doesn’t have to be selective in order to produce, but it certainly helps. Alex Bregman, Mike Trout, Mookie Betts, George Springer, Marcus Semien and Anthony Rendon were all among the top 10 percent of qualified hitters in terms of O-Swing% this season. In other words, they were among the choosiest hitters, swinging at pitches outside of the strike zone at exceedingly low rates.

Eddie Rosario, Tim Anderson, Javier Báez, Jeff McNeil, Nicholas Castellanos, Eduardo Escobar and Rafael Devers were in the bottom 10 percent for O-Swing%, proving that you can still be valuable in fantasy (and in real, actual baseball) without having even decent plate discipline. Some members of this group are simply good bad-ball hitters. Rosario, McNeil, Escobar and Devers were well above average at making contact with out-of-zone pitches. McNeil also made relatively high-quality contact on those offerings, posting an xwOBA (.314) that was 16 points above the average on out-of-zone pitches for hitters who saw at least 1,000 pitches this season.
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At the end of April, I calculated hitter xHR/FB rate using my equation to determine who had most underperformed at the time. I identified and discussed 11 of those hitters. Let’s see how many of these hitters actually did improve their HR/FB rates over the rest of the season and how close they came to their xHR/FB marks. Remember that xHR/FB isn’t meant to be predictive, but descriptive. The difference being that xHR/FB rate helps us determine what should have happened, rather than what will happen in the future. It attempts to strip out luck, like the majority of our expected/deserved metrics.

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If, at this time a year ago, I had told you that between Manny Machado and Marcus Semien, one was going to finish sixth among shortstop-eligible players in 5×5 Roto value and one was going to finish 16th, there would have been no question about which player was going to rank where. But all of us (except for the most prescient) would have been wrong. Semien trailed only Alex Bregman, Trevor Story, Xander Bogaerts, Ketel Marte and Jonathan Villar, while Machado — who played in all but six of the Padres’ games — amassed less value than either Elvis Andrus or Amed Rosario.
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There is no need to beat around the bush with an intro full of cliches and examples. Simply does playing in the postseason wear down a player enough to effect their next season’s production?

Simple answer: Not really.

Less simple answer: Some with hitters, not at all with pitchers.

Complex answer: Danger math.

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You know the third base pool is loaded at the top when there are three players at the position who returned more value than Alex Bregman did in 2019 5×5 Roto leagues. Yet, on draft day 2020, owners are likely to at least consider making the Astros’ 25-year-old the first third baseman taken, ahead of Rafael Devers, Anthony Rendon and Nolan Arenado. To this point, in the currently-under-way Pitcher List Experts Mocks, Bregman is the only third base-eligible player to be taken within the first 14 picks in all three drafts.

It’s not hard to see why. This season, he maintained his elite contact and plate discipline skills while tacking on 10 home runs, nine RBIs and 17 runs to his 2018 totals. In 2020, he would appear to be primed for another batting average around .290, and with a spot in the heart of the Astros’ order, he could clear the hurdles of 110-plus RBIs and runs yet again.
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I continue reviewing my pre-season, and now in-season, articles and this is one of my favorite topics. Even though we know (or should!) that any random two week stretch of performance has little to no predictive value, fantasy owners will never stop allowing results from such a short period cloud their evaluation of a player. The most common time for player evaluation clouding is the beginning of the season, when those are the only stats currently in the book. But the funny thing is, by the end of the season, we typically forgot who those slow starters were, especially if they completely rebounded and ended up earning what we paid for them after all. So let’s take a look back at the slow starting hitters I discussed in Mid-April, and checking in on their stats at that point and over the rest of the season.

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