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Fake Teams Consensus Rankings - Projections Approach Part II (Hitters)

As a follow-up to his general projection approach yesterday (z-scores, positional scarcity adjustment and $ values), Dan presents his hitter projection approach.

Freddie Freeman & the Runs Produced, AVG and HR/FB Approach
Freddie Freeman & the Runs Produced, AVG and HR/FB Approach
Stephen Dunn

Prior/during/after this post, make sure you check out my general ranking approach (using z-scores), how I adjust for position scarcity (through fantasy replacement value at each position) and the auction value association formula (from Zach Sanders' Fantasy Value Above Replacement series on FanGraphs). All of this is to support Fake Teams Consensus Position Rankings that you can find in Ray's schedule.

This post will focus on my hitter projections with the use of my bullish mancrush, Freddie Freeman. I'll post my pitcher approach on Thursday morning. Let's start with per plate appearance/at-bat related projections:

PA/AB; Runs, RBI’s and SB projections:

For the sake of this post, I’ll focus on my projections for the 5x5 categories (R,HR,RBI,SB and AVG). If you want to banter on the approach, you can register (for free) for my Fantasy Baseball Forum. First up are plate appearances. I simply look at the PA/Games trend of a player and adjust if needed based on a confirmed lineup change/team transition using a percentage of PA increase by lineup position. I do not use a consistent PA per lineup position…it’s based first on the historic PA/G trend. AB naturally come about from starting with the PA total and then subtracting out BB and SAC-related factors.

At this point for Runs and RBI’s, I attend to R/PA (incorporating OBP) and RBI/AB (incorporating SLG) historical data and again manually adjust if needed based on team/lineup transitions. Example: Freddie Freeman. I know I’m bullish on him relative to many other projection outputs - I have him at 90 runs and 110 RBI, but if we use his R/PA*OBP rate from 2013 and RBI/AB*SLG rate from 2012 (which are the worser outputs from the previous 2 years) that would actually lead us to 97+ runs and 107+ RBI's. I don’t think the Braves will be worse offensively than last year around Freeman (think BJ Upton & Dan Uggla; others missing less time and naturally developing). Although Freeman had an elevated BABIP last year, it was driven by better contact/more line drives (less flyballs and less popups), increased homerun and flyball distance (from 76th in 2012 to 35th in 2013) and SLG with a more aggressive swinging approach while actually increasing his BB rate.

Similar to R/PA, for SB, I’ll focus on their SB attempt/success rates by PA, incorporating OBP.

Homerun Projections:

FanGraphs attempted to land on a HR/FB ratio formula…I believe to no sure-thing avail. The process was arduous but insightful if you eventually want to go through their 5+ part series. If you don’t mind, I’ll simply post their final summary (always incorporating regression to the mean):

-players tend to lose distance and when players have a big change, lost distance is more likely to stick than gained distance.

- the player will lose some of their distance. How much they lose depends on two things – how much they gained in the past year and how old they are.

I simply look at career/trending HR/(FB-IFFB) ratios and attend to Jeff Zimmerman’s Baseball Heat Maps Homerun and Flyball Average Distance Leaderboard. A bit of a manual process, I’ll look at 5-10 players within a similar average distance to the player in mind. I’ll exclude players that might not compare well for one reason or another i.e. player type and/or handed park factors that are very distinguishable. Sticking with Freddie Freeman (whose only 24 next year/could continue rising in average distance)…excluding 2010 as a 20 year old in limited AB’s (although he had a 16.7% HR/FB ratio), he’s posted the following HR/FB Rates in order: 14.0% (4.7% IFFB rate) à 14.8% (7.7% IFFB rate) à 15.0% (2.6% IFFB rate). For 2014, I landed on another relatively large jump à 15.75% (with a slightly regressed 4% IFFB rate). I believe the next 2-3 years we’ll see max distance from Freddie. His BABIP might not be as elevated next year, but a gorgeous line drive rate and additional contact should lead to a HR total between 26 and 30 and a batting average between .290 and .305 which leads us to our next segment.

Batting Average Projections:

Last week, I posted this on Rotobanter - Expected Batting Average vs. Projected Batting Average. It provides a very short explanation on BABIP and xBABIP (expected batting average on balls in play):

((GB – IFH ) * (GB-IFH constant) + (FB-HR-IFFB) * (OFFB Constant) + LD * (LD Constant) + IFH + BUH ) / (GB + FB + LD + BU + – HR – SH)

Approach 1) xBABIP can be used in the xAVG (expected batting average) formula: HR+xBABIP*(AB-K-HR+SF))/AB. This approach gives us the following xAVG for Freddie Freeman: .2937.

Approach 2) Infinitely more arduous, I look at historical babip and average on each individual balls in play type (GB, FB and LD). While you won’t be able to see this entire approach on my website I’ll describe it here…

Again, using Freddie Freeman as my example, we have our at-bat total as 577. We then incorporate his projected K-rate of 18.9% (calling for another improvement next year at 24) yielding a quantity of balls in play of 451. This total gets broken down into groundballs and flyballs based on his projected balls in play mix: 38.5% GB (174 Groundballs), 36.3% FB (163 Flyballs) and an associated 25.3% LD rate (114 linedrives), which I’m projecting to be top 5 in baseball next year. Last year it was a 26.7% LD rate and 26% the year prior. As a player matures, he learns to lift the ball more. Therefore we increased the FB%, but we regressed the LD% rate (basically swapping them for some GB%). If this doesn’t happen, then there’s no reason not to expect a .305+ AVG again. By looking at his BABIP and AVG on each balls in play type (regressing and/or trending) the data, I wound up on 23% of his GB’s turning into hits, 29% of his flyballs turning into hits and 73% of his linedrives falling for hits. For comparison-sake, on average the major league breakdown is something like 23%, 22% and 72% respectively so nothing out of hand here except maybe his flyball-hit percentage, but he is hitting the ball with increasing authority and had a top-35 Homerun and Flyball average distance as we noted earlier. Now we’re at 40 groundball hits, 47 flyball hits and 83 linedrive hits or 170 hits total/AB = .2951 batting average (it’s actually .2946 if you did the math but that’s because I’m excluding the values beyond the decimal points).

*This compares pretty closely with his xAVG value in approach 1, however this is often not the case for many player like Edwin Encarnacion, which is why I do both approaches (to catch big xBABIP/xAVG differentials). Next year, to streamline the process, I’ll only use the xAVG approach but will filter by xBABIP/xAVG differentials relative to their career average so I can do manual adjustments if needed. I actually spoke with Mike Podhorzer (of Projecting X via FanGraphs) on this subject and while he found the value in the 2nd approach, it’s not necessarily more reliable and it adds a boatload of time. If you're interested in purchasing his Projecting X for your mobile device or on PDF, you can go to and click on any of the links on the right-hand margin.

*Again, if you have any questions on the approach, follow Dan on Twitter @Rotobanter or banter with him and his contributors on their Rotobanter Fantasy Baseball Forum.