In addition to the analysis I conduct using my xHR/FB rate equation, I also still look at ESPN Home Run Tracker after the season ends. As usual, I identified a group of hitters before the 2016 season that based on the Home Run Tracker data, appeared to have serious HR/FB downside. Let’s find out how these hitters performed.
Yesterday, I review the five hitters with major HR/FB rate downside. Today, I’ll recap the list of hitters that would have been more actionable and beneficial for fantasy owners — the eight guys with serious HR/FB upside. As usual, I used my xHR/FB rate equation to settle on these names. Let’s find out how they performed.
In what has become an annual tradition, today I will hold myself accountable to you the reader by publishing the results of my 2016 fantasy season.
In the 2015 version of this post, I decided I did too many leagues to give any the proper attention they deserved. Even though I whittled down my total commitments, an increase in dynasty-type formats meant I had needier children.
The 2016 preseason recaps continue and we’re going to move to hitting for the rest of this week. In late January, I used my xHR/FB rate equation (which is likely to get an overhaul this offseason) to identify five hitters with major HR/FB rate downside. Let’s find out how the group performed.
September is Head-to-Head playoffs month. Just like the major league postseason, a lot is riding on tiny little samples of performance. If your team was anchored by players like Bryce Harper, Gregory Polanco, Sandy Leon, Travis Jankowski, and Michael Saunders, you likely suffered an ignominious defeat. That quintet would have gotten you to the playoffs, but they were conspicuously absent for the month of September.
Let’s talk about the players who played hero in the final month. There’s no analytical angle here. These guys simply stepped up (for your fantasy teams) when it counted.
Let’s finish up my preseason starting pitcher strikeout rate articles by looking at those I identified as possessing significant downside, as hinted at by my xK% equation. It’s a very different list than the one generated by the upsiders, as these tend to be the pitchers with high strikeout rates with seemingly the only direction to go moving forward is down.
Let’s continue the strikeout rate theme by reviewing my list of starting pitchers my xk% equation deemed holding strikeout rate upside in 2016. In the original article, I expressed that the list of names was rather boring, so let’s see if that turned out to be the case or if any gems were uncovered.
I have a total of 28 preseason prediction type articles I need to review, so let’s get rolling! Fingers are crossed that these recaps don’t make me look like a fool. Let’s begin by reviewing my spring training starting pitchers strikeout rate surgers and breakout candidates. The idea here was that underlying skills posted during spring training do carry em>some predictive value, so perhaps those starting pitchers that enjoyed a strikeout rate spike would see a jump in rate during the regular season as well.
These were fun. I usually just say crazy things to my friends and when one of them is true, try to remind them about it and they usually don’t care because they have lives that involve things outside of baseball. Losers. Anyway, here is my initial Bold Predictions article along with my midseason review where a few of my colleagues and myself were so impatient, we had to see where we stood. My goal was to bat .300, so let’s see if I was able to hit my mark. Then laugh at all the ones I was terribly wrong on.
1.) Chris Carter will break 100 R.B.I.
This was the prediction I felt most confident about going into the midseason review and I came very close to nailing this one as Carter ended up with 94 RBI Coming into the season, I really felt strong about Carter having a strong season because of opportunity and how he closed out the 2015 season. He hit 41 HRs and had a wRC+ of 114, so I’d say his season was a success and the spirit of this prediction was pretty spot on. I didn’t account for the Brewers trading away Jonathan Lucroy, which maybe could’ve accounted for another 6 RBI? To be fair, I also didn’t think Jonathan Villar would have the type of season he did and that certainly gave Carter more RBI opportunities than anticipated.
Since I am going to be struggling to find hits with these other predictions, I am going to give myself the every-so-common half a hit. Trust me, it will not help my batting average too much.
0.5 for 1
It’s that time of year again where we look ourselves in the mirror and admit defeat. Some of these predictions are pretty ugly.
Disclaimer: these projections
arewere bold (at least they’re supposed to be), and most are made in the context of Ottoneu fantasy baseball.
1) Yangervis Solarte will outscore Rougned Odor in 2016.
From a Roto standpoint, Odor was the better player in 2016, breaking out for a .271 AVG with 33 HR and 14 SB’s. This prediction was made in the context of Ottoneu however, and it’s wOBA-weighted scoring format didn’t love Odor nearly as much. Looking back, this prediction now just appears to be poorly worded, since Odor (818 points, 150 games) outscored Solarte (570 in 109) by nearly 250 points, almost entirely with the benefit of a healthier season. Solarte (2.5 WAR, 118 wRC+, .346 wOBA) was the superior player to Odor (2.1 WAR, 106 wRC+, .336 wOBA) in almost every other advanced offensive metric, so this one was kinda close.