At this point in the season, there is a lot of specific category chasing as you try to edge out every possible point en route to that championship. Here are six power bats with varying degrees of availability (hopefully something for every league type) who could deliver those key homers for you down the stretch. These are flawed players, that’s why they’re available, but you should be able to extract some value when deployed properly.

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Giancarlo Stanton has gone crazy recently, hitting 32 home runs in 48 days. Last I checked, anyhow. It could be up to 36 by now, you never know with that guy. There have been many talks about his MVP consideration, as well there should be. However, Stanton is not the only guy in that Marlins lineup who is hitting the cover off the ball. Oh no, you have Christian Yelich raking behind Stanton, and then Ozuna behind Yelich.

In the second half, Yelich is batting .295/.387/.530 with a .389 wOBA. Marcell Ozuna is batting .292/.378/.522 with a .379 wOBA. Both of these players are sitting high among the second half offensive leaderboards, Yelich 25th and Ozuna 34th. Together with Stanton, the oft forgotten Derek Dietrich, and JT Realmuto the Marlins have 5 of the top 112 batters in the second half, including 3 of the top 34 and, of course, numero uno.

This is the offensive production the Marlins expected to see throughout the course of the entire season. Unfortunately for them, it took a few months for this to gel, in large part due to the relative poor performance of Christian Yelich in the first half.

I am not saying Yelich was terrible, because he wasn’t. He was average in April and May. But Yelich isn’t on the team to be average, he is a core piece, and his performance over the past month and a half shows just how dynamic he can be for a ball club. In April and May, though, he was not hitting nearly as well as he is right now. So let’s see if we can find a reason. Read the rest of this entry »

Last Tuesday, Jeff Sullivan wrote this article on Byron Buxton’s transformation into the Twins’ most valuable player. If you haven’t read it and you’re interested enough about Buxton to read this fantasy slant, you should probably also read Jeff’s analysis on Buxton’s increasingly well-rounded real-life skill set.

Yesterday, Buxton unleashed the best game of his career to this point, singling and stealing a base in the 1st inning as a prelude to his homers in the 4th, 7th and 9th. As Jeff pointed out in his post last week, Buxton has dramatically simplified his mechanics at the plate, most noticeably ditching the inconsistent leg kick he used to constantly tinker with, and that was certainly in evidence on Sunday.

Basically everything about his swing looks better than it did earlier in the season. The toe tap he’s replaced the leg kick with is allowing him to consistently plant his front leg, which means he can better incorporate his lower body compared to the “100% arms” swing he was flailing about with at the beginning of the season.

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Over the past two years we have had many conversations about batters increasing or decreasing launch angle. Obviously, these conversations have been brought about by our brand new launch angle stats, which only recently became publicly available. However, launch angle remains a difficult concept to fully grasp. What properties determine launch angle? How do batters control it? Can the batter control it?  These are all very valid questions which I think everyone has struggled to answer, including coaching staffs, players, analysts, and fans.

Yesterday Eno Sarris put up an article touching on this topic, in which he explains his journey towards wrapping his head around the phrase “go get the ball”. In doing so he posted two images that were generated using HITfx data, and he briefly mentioned that one may use a bit of math to make a few deductions from this data. Well, that is the topic of this article. I aim to take these images, compare them to the Statcast information we have for launch angle, and reverse engineer the contact point for batters. Read the rest of this entry »

Around 11 months ago, I checked in on a player dominating in a foreign league who appeared likely to return stateside. Eric Thames ripped minor-league pitching, struggled in MLB, and then went on to dominate in KBO for three seasons before finding success back in MLB with the Brewers this season at the age of 30.

Like Thames, Wladimir Balentien ripped minor-league pitching (.283/.351/.535 with 67 homers in 1,271 plate appearances at the Triple-A level, according to Baseball-Reference), struggled in the Majors (.221/.281/.374 with a 72 wRC+, 7.9% BB% and 26.7% K% in 559 plate appearances) and found success overseas. Balentien began playing in NPB for the Yakult Swallows as a 26-year-old in 2011 and has mashed in seven seasons slashing .278/.385/.573 with 211 homers, a 14.7% BB% and 21.4% K% in 2,947 plate appearances, per Baseball-Reference. Read the rest of this entry »

We’re running out of time to improve our teams, so let’s use my xHR/FB rate equation (unadjusted for home park) to identify a handful of hitters potentially due for a home run spike over the remaining month-plus of the season.

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A few days back, I start the process of trying to find breakout hitters. I found some possible traits which point to hitters breaking out but didn’t get into the stickiness of the stats over different time frames. I’m back to see how the “breakout” stats main their values over time.

For a quick review, here are the claims I made in the previous article.

Overall, here are the rules.
• K%-BB% (plate discipline) changes by +/- 4.5%.
• Flyball rate (FB%) changes by +/- 3%.
If the above two items can’t explain the change move onto the following three points.
• Pull% change (only) by +/- 5% this value can good or bad depending on the hitter’s other traits.
• Raw power can start decline once a player reaches 30-years-old.
• BABIP changed by +/- 30 points. (A change in plate discipline can cause this change)

I will just start walking through the points comparing the results for the year after the breakout. Also, I will look for hitters breaking out in the season’s first month and how those stats carried forward.

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It’s time to speculate and to latch on to a new starter that could provide a boost to your counting stats.

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Yesterday, I shared with you a trade I made in the keeper league in which I took over for an inactive team a couple of months ago. It was a classic dump deal, with me acquiring who I considered one of the top two keepers in the league — super prospect Yoan Moncada. We’re still in the middle of August, so we’ll have another month and a half worth of Major League stats with which to evaluate Moncada and put together a 2018 projection. But I don’t want to wait a month and a half and you probably don’t either. So let’s take a stab at an early 2018 projection, along with a dollar value for that stat line.

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Quickly identifying legitimate breakout hitters is tough. Is the hot streak just that, a streak or is something more? With pitchers, it is easier to find the breakout’s cause. New pitch. Added velocity. Improved control. These traits can be seen in a single start after facing 25+ batters. A hitter has only about five plate appearances a game to display a new skill. It’s a different world with them. Today, I am going to try to find a simple process with a few key stats to focus on.

With hitters, their data contains so much noise, especially once the ball is put into play. To get rid of some of this noise, I started to find with the following stats:

• Power: Hard%, HR/FB
• Plate Discipline: BB%, K%, O-Swing%, Contact%
• Batted Ball Distribution: Pull%, Flyball%

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