Archive for Hitters

My Tout Wars prep continues. I have already examined the league’s historical aspects which I have used to create initial auction values and a draft outline. With the initial projections out of the way, I am refining them. One step in this process is to find the replacement level player and adjust players who will miss time accordingly.

The concept behind the replacement level player is fairly simple. If a good player is expected to miss significant time, his fantasy value is based on just the games he is expected to play. For the games he misses, some lesser player (replacement level player) will fill. The better player’s total value will be both his and the replacement player’s contribution.

For example, I don’t expect Yoan Moncada to get called any earlier than the Super Two deadline around June 1st. For the months he’s in the minors, a less talent replacement level player will be subbing in for him. The same idea works with pitchers. Tyson Ross is expected to miss at least a couple of months so a replacement is needed until he gets healthy.

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Finally, after unmasking the newest version of xBABIP that accounts for shifts, it’s time to get to the names…you know, the kind of list you could actually use for your fantasy leagues this year! So let’s identify and discuss the fantasy relevant hitters whose xBABIP marks were significantly above their actual BABIP marks. These ten hitters should enjoy a BABIP rebound in 2017, assuming their BABIP-related skills remain stable.

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It’s xBABIP week and on Monday, I unveiled the latest incarnation of my equation, this time incorporating shift data. Then yesterday, I analyzed leaguewide shift data trends and unearthed some interesting tidbits. Today, it’s finally time to talk some names. We’ll begin by looking at the players that enjoyed the biggest gains using the new xBABIP equation versus Alex Chamberlain’s 2015 version that I had been using as my primary go-to, and also the biggest losers.

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So far in my Tout Wars preparation series, I’ve documented the league’s draft tendencies and the stats needed to win. Today, I’ll create the framework for player pricing. Along the way, I will show how there is no position scarcity except with catcher. At least for this league

Completing this step brings the preparation is laborious, but necessary. Once it’s done, I can spend most of my time evaluating players and their projected playing time.

For evaluating players, I utilize the Standings Gain Points (SGP) method. I previously outlined the procedure and it‘s the same method Larry Schechter recommends in his book, Winning Fantasy Baseball. Normally, this procedure is fairly straight forward since I’ve historically used three-year average values. Last year’s offensive explosion complicates the math. With more offense available, home runs, Runs, and RBIs become less important. Predicting 2017’s run scoring environment is impossible so I won’t for now. I feel I need to use a weighted average system with 2016 getting the most weight but I am just not sure how much to weight them. To get the process started, I will use the average standings from 2014 to 2016 for this work.

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On Monday, I introduced my new Statcast fueled batter xHR/FB rate, adjusted for home park, and then yesterday, I shared a list of six batters with significant HR/FB rate upside for 2017, given the gap between their 2016 xHR/FB rate and actual HR/FB rate. Today I’ll discuss 10 hitters with major downside.

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On Monday, I introduced my new Statcast fueled batter xHR/FB rate, adjusted for home park. Let’s finally get to the part you have been eagerly awaiting — the potential 2017 home run surgers. These are the guys whose xHR/FB rates far exceeded their actual HR/FB rates.

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Yesterday, I introduced you to the new Statcast fueled xHR/FB rate equation I developed during my recent xMetric frenzy. It’s simple to use, requiring just a couple of variables, and its components are easily accessible. So now armed with all the data that led to the equation, let’s dive in, explore, and have a little fun.

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Nearly three years ago, I developed and published the original batter xHR/FB rate equation. While I used it during the season to analyze players, it was unfortunately behind the FG+ pay wall and shrouded in mystery. Then almost exactly two years ago, I unmasked the equation and shared it with the entire world. The equation used three components compiled by Jeff Zimmerman and did a fairly solid job of estimating what a hitter’s HR/FB rate should have been (adjusted R-squared of 0.649). Sadly, the data fueling the equation is no longer available, so naturally I decided to create a new equation. A Statcast charged one.

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Power often comes with punch outs. When homers aren’t tied to strikeouts, that’s usually the profile of an elite hitter. In 2016, only six players with more than 250 plate appearances recorded a Hard% north of 40% and a K% south of 20%. One of those six players, David Ortiz, is now retired. Joining Big Papi in that group of hitters was Josh Donaldson, Miguel Cabrera, Matt Carpenter, Jose Bautista and Kendrys Morales.

Using the NFBC ADP data, Donaldson and Cabrera require roughly a top-15 pick for their services with the former carrying an 11.16 ADP and the latter sitting at 15.58. Carpenter has an ADP of 70.58 and Bautista’s ADP is 118.16 after a down year. Lagging way behind this group is Morales with an ADP of 178.21, a minimum pick of 116 and a maximum pick of 213. Yes, Morales’ utility only eligibility at most fantasy sports sites is less than ideal and should be baked into his ADP, but it looks like there’s plenty of wiggle room for a profit. Read the rest of this entry »

This season, I was lucky enough for a couple print publications, Lindy’s and The Fantasy Baseball Guide, asked me to contribute their fantasy preview magazines.  While the quality of both magazines is top notch, print publications have limited room for explanations and no ability for back-and-forth discussions. Today, I am going to go over my contributions which I feel could use more explanation and will answer any questions on my thought process.

Lindy’s

For Lindy’s, I participated in their 12-team mock draft ( standard team except 1 C, 4 OF, 8P) and I picked out of the 3rd position. Here is my team

Position – Name (Round Drafted)
C – Buster Posey (3)
1B – Hanley Ramirez (7)
2B – Rougned Odor (2)
3B – Adrian Beltre (4)
SS – Marcus Semien (12)
MI – Jung Ho Kang (17)
CI – Albert Pujols (10)
OF – Andrew McCutchen (5)
OF – Mark Trumbo (9)
OF – Marcell Ozuna (14)
OF – Matt Holliday (16)
Util – Mike Moustakas (18)
P – Clayton Kershaw (1)
P – Chris Archer (6)
P – Rich Hill (11)
P – James Paxton (13)
P – Michael Pineda (19)
P – Jharel Cotton (20)
P – Andrew Miller (8)
P – Shawn Kelley (15)

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