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.

Read the rest of this entry »

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.

Read the rest of this entry »

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.

Read the rest of this entry »

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.

Read the rest of this entry »

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.

Read the rest of this entry »

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!

Read the rest of this entry »

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.

Read the rest of this entry »

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.

Read the rest of this entry »

As I have at the end of the first half since 2013, I grouped two sets of pitchers together and aggregated their results through the half based on the degree of SIERA outperformance and underperformance. I then asked you which group of pitchers would perform better from an ERA perspective over the second half, and which range each group’s ERA would fall into. This year’s poll and voting results are here.

Read the rest of this entry »

At the end of spring training, I identified and discussed 10 pitchers whose spring training strikeout rate was significantly higher than my Pod Projection K%. Though the vast majority of spring training stats are completely meaningless, I did find many years ago that strikeout and walk rates do hold some predictive value. So let’s see how these 10 pitchers ended up performing.

Read the rest of this entry »