A few days ago, Travis Sawchik ask me to help find some comps for the Shohei Ohtani using a 2016 Davenport translation. The list of potential hitters with similar 2018 Steamer projections was impressive (Charlie Blackmon, George Springer, Mookie Betts, Carlos Correa, Yasiel Puig, and Aaron Judge). Additionally, I found pitchers who had similar 2018 projections to his 2016 translation but the list wasn’t as impressive (Jimmy Nelson, James Paxton, Jon Gray, Luis Castillo, Luke Weaver). Thanks to Dan “The Man” Szymborski, a 2018 projection now exists and results will be a little disappointing.

First, from what I heard from most fantasy websites, Ohtani’s will be two separate draftable players. Ohtani the pitcher and Ohtani the hitter. No site, that I know of, has yet to combine the two. If they did, they will likely have to count all the hitting stats accumulated by all pitchers. I hope this doesn’t ever happen.

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I’ve finally compiled the 2017 Disabled List (DL) information. The main change from the last few seasons is the transition from the 15-day DL to 10-day DL and the subsequent increase in DL trips. With the total trips up, the number of days lost is down which makes it tough to draw any major conclusions. It’s time to dive into the numbers.

First off, I collected the information from MLB.com’s transaction list. I like to use this list because it is easy to go back and check. I waded through it and it wasn’t pretty. It took me twice as long to compile the data compared to previous seasons. I would just like to give a big thank you to ProSportsTransactions.com for having most of the missing data.

With my venting out of the way, here is how the days missed for pitchers and hitters compare over the previous 4 seasons.

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A few weeks ago, I began the process of determining an underperformance metric. In the article, I laid out the groundwork determining the drop off in plate appearances (PA) and production (wOBA). With these thresholds, I created several metrics, each with its own advantages and disadvantages. I’m not setting the values into stone yet but I’m getting closer to a solution. I’ve found a few value I like better than others.

In the original article, I found fantasy owners considered a drop in 220 PA from 600 PA (37% drop) and of 0.035 wOBA from .350 wOBA (10%) to be the thresholds. I didn’t mess with these two values. Besides the pair, I wanted to know when both occurred. Additionally, from a discussion in the comments, I found when either PA or wOBA thresholds where met and when both dropped close to, but not over, the thresholds. This value (called Minor Drop) I found to provide the most overall value.

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Unless league rules require it or an owner plays in an NL West-only league, owners don’t use their starters in Colorado. This stance may be a little extreme but the league’s aces should be the only started used in Colorado. Pitching in Colorado adds one run to pitcher’s ERA. Owners know this but visiting team must send out a starter to get sacrificed. I’m going to go over some of the pitchers affected the most by being the sacrificial lamb.

This past season, I owned Jeff Samardzija in a couple of leagues. His 4.42 ERA was just above league average (4.36 ERA). The effect on my team wasn’t that much though. There is no way I was going to start him in Coors and I missed out on his 1.94 WHIP and 11.91 ERA over 11.1 IP. With the starts removed, his ERA dropped to 3.98. While not a great ERA, it represented the true effect it had on my team.

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The Auction Calculator is now loaded with the 2017 end-of-season data along with some 2018 projections. I’m sure the preceding comment will be sufficient to keep many readers busy for a while. I’m glad some came back. While its output can lead down several different discussion paths, I’m going to analyze what I consider to be the third starting pitcher tier. I feel many 2018 leagues will be won or lost by navigating this minefield.

So far this offseason, fantasy owners have placed four starters (Kluber, Kershaw, Sale, and Scherzer) in the top tier, After those four, I believe there are a dozen or so pitchers who would make acceptable aces, especially if they can be doubled up with another pitcher from this tier.

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This was supposed to be a quick paragraph on Max Fried but it turned into a borderline Quick Look. I was doing an article on pitchers who saw their ERA balloon because of starts at Coors. His non-Colorado ERA dropped stood at 3.09 vs 3.81 which made him seem like a borderline ace. I kept digging and found additional encouraging information. Here are some of my thoughts on my first 2018 deeper sleeper.

First, here’s how industry sources graded him including his pERA grades from his short MLB stint.

Some definite disparities exist. I will examine each pitch with a video from his September 9th start against the Marlins.

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This past weekend, I was in Phoenix for Baseball HQ’s First Pitch forum. It’s an intensive few days of catching up with old friends and focusing on the upcoming fantasy baseball season. There was an underlying theme of the weekend, the fantasy baseball game is being forced to change. Some game facets have experienced some massive adjustments. The following are some of the meta-trends which have quickly popped up over the past few seasons.

Home runs are way up

A few days ago I wrote the following incorrect statement about Carlos Martinez for a 2018 player preview.

His 1.19 HR/9 will likely drop back below the league average.

It was pointed out to me, his home run rate was below league average. I was for sure it was not near 1.20 but I was wrong. Here are the recent league-wide HR/9 values.

2014: 0.86
2015: 1.02
2016: 1.17
2017: 1.27

I remember when the HR/9 hovered around 1.0. Not anymore. Some other pitching stats are feeling the effects of the jump like ERA, but the root cause is more home runs.

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Most fantasy owners expect drafted players to under and over perform some amount. When a player overperforms, the owner looks and feels great because they “knew” a breakout was coming. Owners hope they didn’t pick too many players on the other end of the spectrum. The underperformers are the ones who drag down a team and owners find as escape goats for a bad season. I’m going to start laying the groundwork to determine a hitter’s disappointment chances.

The first major step in finding a disappointing hitter is to define what is a disappointment. After owning too many fantasy teams over the years, I’ve had my share of disappointments (e.g. Brandon Webb in a 2009 first round) and feel they are just part of the game. This ambivalence doesn’t mean I shouldn’t know the breakout chances. Even small changes in the odds can make a major difference after rostering 20 or more players.

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Yesterday, the Justin Mason posted the ADP from four of the slowest drafts containing industry experts and myself. One thought I had after a handful of rounds was the lack pitching available and how the good were the available hitters. I decided to go back and examine draft results from last year and these draft to see if pitching was being taken early. While it wasn’t, some other information could be extracted.

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Last offseason, I created an individual pitch metric, pERA, which gives each pitch an ERA and prospect grade based on its ground ball nature and swing-and-miss capability. With the 2017 season over, I’ve compiled the final 2017 values. This year, I’ve added in exit velocity (EV) grades for each pitch.

The process I used for creating pERA is in the article linked above but here is a quick rundown.

• The key change is to give each pitch an ERA value (pERA) based on the pitch’s swinging strike and groundball rate. All the values are based on the average values for starting pitchers. Closers will have higher grades because their stuff plays better coming out of the bullpen.
• The pitcher’s control is determined from their walk rate which is separate from the pitch grades.
• I’ve put each pitch on the 20-80 scale with 50 being average, 80 great, and 20 horrible. For starters, target pitchers with three average or better pitches. For relievers, they just need two pitches.

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