In mid-February, I used my pitcher xK% equation to highlight nine pitchers that may have strikeout rate upside for 2018. The important thing to remember is that xK% is not a projection and isn’t meant to be forward-looking. Rather, it’s descriptive, or backward looking, the same way you might think about FIP/xFIP/SIERA. I have found many pitchers who consistently over/underperform their xK% marks for whatever reason, so I never blindly use previous xK% marks as my next season forecast. That said, let’s find out how the pitchers with the greatest positive divergence between 2017 K% and 2017 xK% performed in 2018.

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Let’s wrap up my 2018 Pod Projection reviews, ending with Tommy Pham. A surprise breakout in 2017, we didn’t truly know what we were going to get in 2018. A move to Tampa mid-season didn’t exactly benefit his offense as he merely went from one pitcher friendly park to another. Let’s find out how he ended up performing compared to my projection.

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Shohei Ohtani was one of the most hyped rookies in recent memory. Fueling the excitement was the fact that he came over from Japan and he was a two-way player, both pitching and hitting, and doing each well…very well. Obviously, attempting to translate performance from a foreign league to MLB is difficult, and then you have to actually forecast the upcoming season, which is far tougher than a regular run of the mill projection for an MLB veteran.

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Let’s return to reviewing my preseason Pod Projections, this time with Luis Castillo, a popular sleeper choice and breakout candidate, and for good reason. My original writeup is here.

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Yesterday, I reviewed my stolen base upside guys, after comparing my Pod Projections to Steamer projections in the preseason. Today, I’ll review my downside guys. Let’s see how they performed.

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Let’s continue reviewing my Pod vs Steamer series, pitting my preseason Pod Projections against the Steamer forecasts. Today, I’ll recap my stolen base upside picks. I used PA/SB as my ratio to account for any differences in playing time projections. Let’s see how the group performed.

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After just about a week of the season, I published a list of eight hitters whose early fly ball rates were significantly higher than their 2017 marks. I dubbed these guys as potential fly ball revolution participators. Let’s find out if they were able to maintain their FB% gains and whether it led to a home run surge.

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Yesterday, I reviewed the first preseason Pod vs Steamer projections article, beginning with the hitters I projected for home run upside. Today, we’ll flip to the other side, as I review the home run downside guys. Hopefully I perform better than my upside guys!

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A fun activity for me each preseason is comparing my Pod Projections to the Steamer projections. While the forecasts in various categories for most players are negligible, of course there are some that are wildly different. One comparison I made was looking at which hitters I projected for more homers than Steamer. However, rather than compare the raw home run total, which is greatly influenced by the at-bat projection, I computed each projection’s AB/HR ratio. So let’s find out how the guys I identified as having AB/HR upside performed.

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As has now been an annual tradition, I published a series of Pod Projections before the season begin, and then compared my projection to the rest of the systems available on the player pages. We’ll start the reviews with Whit Merrifield, who came out of nowhere in 2017 to become a fantasy stud, swatting 19 homers and stealing 34 bases. Let’s see how he performed compared to my projection and the computer systems.

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