Author Archive

Joining the Fly Ball Revolution — May 2019, A Review

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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The World of the Weird and Extreme — Through May 4, 2019 Pitchers, A Review

In Early May, I dove into the world of small sample size theater to discuss some of the statistical oddities that had occurred so far on the pitching side of the ledger. Let’s review how these pitchers performed the rest of the way in the metrics highlighted.

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The World of the Weird and Extreme — Through April, a Review

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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Potential HR/FB Rate Decliners – 4/30/19 — A Review

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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Potential HR/FB Rate Surgers – 4/29/19 — A Review

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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Final 2019 Statcast Hitting Trends

Last week, I reviewed and discussed various hitting and pitching metrics and how they have trended over the past five seasons, from 2015 through 2019. After also discussing the early Statcast trends back in mid/late April, let’s take a look again with the full season now in the books.

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Final 2019 Pitching Trends

Yesterday, I shared and discussed a plethora of hitting metric trends from 2015 to 2019. More strikeouts, more fly balls, and more home run power are the obvious trends. Now let’s look at how the early 2019 pitcher trends I discussed in mid/late April ended for the season.

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Final 2019 Hitting Trends

In mid-April, I took an early look at hitting trends in a plethora of metrics since 2015. Now that the 2019 season has concluded, let’s now revisit those metrics and see what 2019 ended up bringing us. Did it continue a trend, reverse a recent trend, or begin a new one?

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Game of Groans: Slow Starting Pitchers — A Review

Today, let’s review how 10 slow-starting pitchers I first discussed in mid-April performed the rest of the way. Was it a profitable move to acquire any of these pitchers from a panicked owner? Let’s find out.

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Game of Groans: Slow Starting Hitters — A Review

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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