Let’s return to reviewing my Pod Projections, this time diving into popular preseason sleeper, Taijuan Walker. Though he posted a poor 4.56 ERA in 2015, he had been a heavily hyped prospect and averaged over 94 mph with his fastball. So that made him a favorite target with serious breakout potential in 2016. In April, he made his newly minted owners proud, as he posted a microscopic 1.44 ERA and 2.69 xFIP. But then the wheels fell apart and he ended up missing time due to a foot injury. Sadly, the strong April wasn’t enough to keep his ERA from finishing above 4.00, and now he gets to start 2017 on a new team and in a new league. Let’s what what I projected for 2016 and how it compared to his actual results.

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Let’s take a short break from my Pod Projection recaps (only two left!) to review another Steamer and I, where I identify players I’m far more bullish or bearish on than Steamer is. Carlos Rodon was a heavily hyped prospect after being selected as the third overall pick in the 2014 June Amateur Draft. He jetted through the minors so quickly, you would swear he never actually made an appearance. In fact, he recorded a total of just 34.2 minor league innings before making his Major League debut in 2015. It was an excellent debut, at least from an ERA perspective, so expectations were high.

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Hyun Soo Kim signed with the Orioles before last season on a two-year deal. He struggled mightily in spring training and because of the nature of his contract, the major league team was forced to roster him. After just 17 plate appearances in April, he became a decent semi-regular in the lineup. The left-handed hitter got on the strong side of a platoon with Joey Rickard or Nolan Reimold being the other half.

He became a decent fantasy option in daily transaction leagues by posting a .329/.410/.454 in until July 10th when he went on the DL with a hamstring injury. After the injury, he hit only .275/.353/.386. The second half numbers are decent numbers, but not as good as before the injury.

With the new StatCast data, I examined it to determine if there was a drop in Kim’s exit velocity around the time of the injury. Using a 10-day rolling average, the available data may not look like it but the rolling average generally stays around 7 mph of the overall average. Additionally, there was  no huge pattern change around the time of the injury.

The problem is that StatCast is not able to collect all the available data as documented at FanGraphs and The Hardball Times. The missing data is normal weak groundballs or high infield popups. I am not going to regurgitate the reasons and the exact details from the previous articles but I am going to take a step forward in accounting for the missing data.

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Jose Ramirez: 2017 Projection

Jose Ramirez was an afterthought for most people coming into the 2016 season. He had struggled early in 2015 (.176/.243/.235 in the first half) and was demoted and Francisco Lindor got called up. He came back in the season’s 2nd half and has been a different hitter ever since. His second half improvement went unnoticed because of the bad first half stats bringing down his value.

I read back through news reports to see if he was dealing with an injury or a change in approach while in the minors and could not find anything. Instead, I will throw out a bunch of stats showing the change without knowing the reason. First, here is his 2015 average exit velocity from baseballsavant.com.

Before getting demoted, his average batted velocity was below league average (84.8 mph) and after coming back it hovered around league average (87.9 mph). Besides hitting the ball harder, he went to a more line drive approach with his swing.

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At last, we come to our final outfielder Steamer and I review. Today, I’ll recap my Steamer and I battle over Michael Conforto, which pit my Pod Projection against the Steamer projection system. I was surprised to learn that I was significantly more bullish on Conforto than Steamer was, as I felt he was actually overvalued in fantasy leagues, though mostly due to his expected lineup slot toward the bottom of the Mets order. Let’s see what we expected versus what actually transpired.

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Onward and forward we move with the Steamer and I series recaps, pitting my Pod Projection against Steamer! Today, I’ll review how we forecasted Yoenis Cespedes. Unlike Mike Trout and Yasiel Puig who I previously recapped, I was actually significantly more bullish than Steamer on Cespedes. Let’s find out exactly what each system was projecting versus how Cespedes actually fared.

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Let’s continue with the outfielder Steamer and I reviews by checking in on an amusing player — Yasiel Puig. I was significantly more bearish on Puig than Steamer was, and while we know now that Puig has continued his offensive slide, let’s dive into exactly what we expected versus how he actually performed.

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Today, I start my reviews of my Steamer and I series that happened to cover mainly outfielders (not by design). The series compared my Pod Projection to the Steamer projection, as I discussed the players I was either significantly more bullish or bearish on compared to the system. We start with Mike Trout, who I was far more bearish on than Steamer. It was an interesting exercise for me since I had no idea I was in that position to begin with. Diving it to determine why was an enlightening activity.

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Miguel Sano: 2017 Projection

Trevor Plouffe has elected for free agency which means Miguel Sano is slated to be the Twins starting third baseman. Sano has positive defense metrics for third base, unlike the outfield where he has been a subpar defender. This move has really opened up the playing time Sano which will help with his uninspiring fantasy value.

Sano’s game can be summed up as “trying to hit the ball hard”. When the 23-year-old makes contact, he can really hit it hard has seen by his career 23% HR/FB rate, .240 ISO, and .354 BABIP (good for a slow guy).

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Right now I am in the middle of writing preseason player profiles for several publications. Like most people, I examine a player’s stat page for most of the information. Additionally, I have access to our database and have created some cheat sheets to help with looking for possible changes in a hitter’s profile to help explain stat changes like a significant bump in home runs. Today, I’ll start with making my hitter sheet available and go over a few players with the information.

I find hitters to be the tougher than pitchers to determine if changes in production are from a new approach or from just plain luck. To help find such changes in approach, I determine changes in several metrics which would point to an overall talent adjustment. The stats I examine are:

Swing based
Pull%
GB%
Hard%

Eye base
BB%
K%

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