Yesterday saw some fantasy applicable free agent signing occur which deserve a discussion.

A.J. Pollock signs with the Dodgers

I can’t quit Pollock, almost to a fault. I keep latching onto his 2015 season even though he hasn’t played over 113 games since then because of injuries. Now, he is going to a team notorious for limiting playing time thereby making his value is tough to unwrap.

He was productive during his stretch of limited playing time. Prorating his three-year stats down to 600 PA, he would have 88 Runs, 23 HR, 73 RBI, 23 SB and a .261 average. It’s tough to find a player with similar 2019 projection but here are a few. Ronald Acuna is at 28 HR, 24 SB, and .276 AVG. Braun at 25 HR, 13 SB, .265 AVG. Tim Anderson with 17 HR, 21 SB, .252 AVG. If playing a full season, he’s a top-50 hitter.

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The 2018 season opened my eyes to the risk of young players losing playing time because of massive platoon splits. Usually, it’s the established major league veterans like Matt Adams who get platooned. Manual Margot was such a player who usually led off against lefties but was dropped in the batting order or even to the bench against righties. Those lost plate appearances can add up over the course of a season whittling away a hitter’s value. Today, I’m going focus the most talented hitters who are most like to be platooned.

For Tanner’s and my book, The Process, Steamer projections were kind enough to include every hitter’s projected OPS versus right and left-handed pitchers. From the book’s research, we found teams have historically started platooning hitters when one side of the platoon’s OPS drops below .650 and definitely at .600. Here are some the hitters who may end up in a platoon situation if their team decides to go that route. Besides the risk of sitting out games, some teams move these players up and down the lineup based platoon differences. I’m likely going to give some of these hitters a playing time adjustment.

Note: The projected platoon OPS are league and ballpark neutral and may seem off compared to the current projected OPS.

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It’s time to get nerdy. Very nerdy. While I’m going to post some auction values end the article’s end (I just lost 99% of the readers), the focus of the words is to concentrate on setting a pitcher-hitter split by just using Standings Gain Points (SGP). It’s not going to work with every league type. Not even close but it’s a theoretical solution which can help an owner the best chance to get the most value out of every draft pick or auction dollar. It’s definitely a better option when trying to set in-season values.

The following process is definitely ripe for discussion and argument. While writing The Process, Tanner and I debated this idea and even brought in others to determine if the pitcher-hitter split can be done by using SGP values. We published without including the concept as we were still ironing it out. We are still not in 100% agreement but here is the idea.

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Catchers … what a dumpster fire for a fantasy position. I can’t remember it being worse. It probably was at some point but with the increased knowledge of pitch framing, more horrible hitting catchers are accumulating plate appearances. Today, I’m going to go through the natural catcher tiers for various league types and show where owners need to buy for the best values.

Before I go any further, I need to explain a few concepts. I’m going to be using Standing Gain Points (SGP) to differentiate the various players. The main reason I like to use SGP is it takes all of player’s Roto stats and combine them into a single value. This important with differentiating the value of a speedster leading off or a middle of the lineup slugger. Additionally, I’m using The Process’s 15-team, two-catcher formula for all the following comparisons. It may not be the perfect formula when comparing different league types but it will provide a nice baseline.

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It’s time to start discussing pitcher rankings and fantasy managers need to know it’s a new landscape for two reasons. First, the idea of every team having one or two 200-inning starters is *over*. The top arms are putting up similar stats to the past. The change now is with the floor. It has just fallen. Starters are just not going as long and the Wins and Strikeouts they accumulate are gone. Second, many bullpens are now going to more of a committee approach where there aren’t 30 set closers but more like 20. The lack of Saves in a concentrated few closers boost their value and the overall value of every Save.

It’s time to get to the rankings. I used the 15-team Standings Gain Points (SGP) Formula from The Process to create these rankings. I used FanGraphs Depth Chart projections (stats in the table) along with three other sources (not to be named). I ranked them by the average SGP value and also included the standard deviation in all the values.

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A couple of days ago, I released some hitter rankings and now I’m going to dive into some players with the biggest value divergence. By going through the most different players, the value averaging makes any effects of an outlier less meaningful. Also, remember that these are the most divisive projections. Other player projections involve less disagreement.

It’s not always one projection being “wrong”. Each one as some instance of diverging. By using several projections, the faults of one are lessened.

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It’s time to really get for the 2019 fantasy season and start and release out a set of hitter rankings to nitpick. In all fairness, some of the following projections need to be blown up. Normally, I just average several projections and use them for my fantasy values with great success. With a ‘wisdom of the crowd’ approach, I usually make sure one extreme value, high or low, doesn’t dominate my decision.

Some people get on me for just following these projections. Generally, I do follow them but just as a starting point. As I’ve shown this last week, I add in my own adjustments as I see fit into the baseline values. While Steamer has been out for a few months, other projections are now becoming available. Today, I just wanted to compare them to see who are some of the more divisive players.

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My last few articles have been deep dives on hitters who I felt may need their projection adjusted. Today, I’m going through the last few. Remember, this analysis is focused on the player’s talent projection changing and not on playing time.

Kyle Tucker (220nd in NFBC ADP)

I knew Tucker would make this list before the list ever existed. The 22-year-old flew through the minors and just destroyed AAA with a .332/.400/.590 triple slash line last season. Once he got the majors, the results stunk with him hitting .141/.236 /.203 in just 72 plate appearances.

And now the xStats come to his rescue since he was extremely unlucky with his batted balls. Here are his various actual and expected values.

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A few days ago, I did a deep dive on several hitters I felt that I needed to personally adjust their projection. Today, I’m going through a few more. This analysis is focused on the player’s talent profile changing and not on playing time.

Paul DeJong (NFBC ADP of 191st)

The reason Dejong popped up on my radar was his broken hand from mid-May to early July. It seems like he may have returned a little too early and his results suffered.

Month: OPS
Apr: .866
May: .728
June: DNP
July: .589
Aug: .726
Sep: .777

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Since the end of the regular season, I’ve been helping various publications write player previews for the upcoming season. During the process, I kept a list of hitters who I felt there may be reasons to adjust their talent projections. I’ve found that even when I normally deep dive into hitters, I come up close to the standard projection and wasted my time. I found I’m better off focusing my effort on pitchers. I can’t afford to ignore hitters, though. I’m now going to analyze these few in detail over a series of articles to see if their projection holds up or do I need to adjust it.

For some of the hitters, the reason behind the talent change (e.g. injury) is obvious. For others, I don’t remember the exact reason. Oops. I’m going to start working my way through them starting with the ones with the highest ADP.

Note: I’m only dealing with the player’s talent. Projecting playing time is an entire separate fiasco.

Justin Turner (109th in NFBC ADP)

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