Hey all, I'd like to bring some discussion to the idea of Value-Based Drafting in fantasy baseball.
A quick disclaimer: This post is long, and will involve math. The spreadsheet included is free to use for anybody, but is tailored for OBP based leagues.
If you would like to skip the text and jump right into the spreadsheet, or pull it up as you read, the link is below.https://docs.google.com/file/d/0B3UnZme ... sp=sharing
On to the wall of text!The Introduction
For those unfamiliar, VBD is a commonly used strategy in fantasy football. It takes into account the baseline production expected out of each position, thus correcting for different scoring expectations; i.e. QBs typically score much higher than other positions, TEs lower etc. Value based drafting, depending on the method, will tell you how many more points a player is expected to score than the next guy at his position, or a typical player at his position. Basically, VBD is a way of quantitatively adjusting for positional scarcity.
Now, to my experience, positional scarcity in fantasy baseball is often addressed in a more qualitative way. For example, Matthew Berry's latest fantasy baseball podcast on ESPN discusses how much of a bump Buster Posey gets for being a C vs. his value as purely a first baseman. They essentially settled on 1-2 rounds "feeling" right. It's easy to see why this is. In standard H2H or roto leagues, there are 5 categories for hitters, and 5 for pitchers. In comparison, in fantasy football it's much easier to compare between positions because all production goes into the same category: points. In baseball, the same analysis will get you +/- in 5 different categories; comparing apples to oranges.The Methodology
With all that in mind, we finally get to the point. Our goal is to go from comparing apples to oranges, to comparing apples to apples. In order to do so, I took a somewhat WAR-like approach. I took ESPN's projections and put them into a spreadsheet, sorted with an overall ranking, as well as positional rankings. Using this, I calculated the average of the 2*X number of players at each position, where X is the minimum number of starters at that position in my league. This creates a baseline "replacement level" player to compare to. Next, each player has a score calculated for each category: R, HR, RBI, SB, OBP. This score is calculated using the difference between each player's projected contribution and the replacement level contribution. This number is then normalized by dividing over the league leader's contribution in said category. This lets us address differentials across categories. Instead of wondering whether you should draft player A because he provides 7 more HRs than a replacement player or player B for providing 5 more SBs, you can see what percentage of the league leader in that category each contribution is.
Each player then has a total "player value" calculated as the sum of his contribution above the replacement level at his position in each category. This leads to players having very different scores depending on where you play them. For example, Carlos Santana drops more than 6(!) rounds as 1B vs. a C. This is because the "replacement Catcher" averages 60.2 runs, 18.75 HR, 71.9 RBI, 2.65 SB and a 0.344 OBP vs. a "replacement 1B" averages of 80.87/27.43/92.03/4.3/0.360.Where I need help
Here's where you come in. I'm not a stats major. I have a solid background in math, but if I'm being honest, most of my methodology basically can be summed up as "tinker with it till it looks right". I'm looking for any pointers on where I can improve my calculations. Specifically, I'm considering taking just the average of the X number of players around the minimum players started. I feel that top catchers have been unnecessarily boosted by being compared to guys that will not see a draft board in anything less than a 15 team league. You'll also note that in the methodology segment, I did not mention how I calculated pitcher values. This is because despite using a similar system, I have no idea how to value each category in order to get an accurate comparison across pitchers and hitters. The link to my spreadsheet is given at the top of this post, as well as again below.https://docs.google.com/file/d/0B3UnZme ... sp=sharing
If anyone has the time and inclination to peruse the data and come up with suggestions they would be most appreciated. If not, enjoy the spreadsheet, I hope it's useful. I will be updating with any changes I make.
tl;dr: Just read the post, you're in fantasy baseball forum anyways