The player value series is back again! I run this series of posts every year now. They are a mix of repeats from previous years, which are intended as a resource to help broaden the base of people that know how to run player values, and newly updated entries which provide info specific to 2018. Stay tuned throughout the preseason for the rest of the series! - HWB

Player rankings can seem mysterious at times. Auction values, even more so. How do your favorite fantasy baseball sites come up with these things? From ESPN to Yahoo to CBS, it's tempting to think they're totally arbitrary, just players and numbers thrown on a board at the author's whim. As it turns out, there are actually several player valuation systems that are commonly used to come up with player rank - these calculations, combined with your projection system of choice, allow you to directly calculate player values and rankings!

I throw around the terms "z-score", "SGP", and "Points" fairly liberally here on the Harper Wallbanger blog. Fantasy baseball loves its jargon. All of these terms describe systems used to assign player values when generating rankings or auction prices. But if you're not a hardcore spreadsheet wizard, you might be wondering what the differences actually are in how these are calculated. Especially given that the Big Board allows you to choose any of the three systems, it's time to bring some clarity to this situation! Today is part one of the 2018 Big Board Player Valuation Series: "Where do player values come from?"

A technical note before we start: the "BIGz" score used in the Big Board was originally just a z-score, hence the "z". These days, it's a catch-all term used for any of the $ values generated by the sheet, no matter the valuation system used.

There are four basic steps to the creation of BIGz $ values for players from raw projections that I'll step through and explain:

(1) Initial calculations (different for each system)

(2) Modifications (h/p split, aging, bonus PT)

(3) Replacement levels (positional adjustments)

(4) Dollar conversion



1) Initial Calculations

z-Scores

z-Score: a statistical measurement of a score's relationship to the mean in a group of scores. A z-score can be positive or negative, indicating whether it is above or below the mean and by how many standard deviations. A z-score of 0 means the score is the same as the mean, while a z-score of 1 means the score is exactly 1 standard deviation above the mean.

z-Scores are probably the most popular system for creating player rankings and dollar values, thanks to their relative simplicity. They're sometimes referred to as ‘FVARz’ for Fantasy Value Above Replacement z-scores as popularized by Zach Sanders (formerly) of Fangraphs. The first step of creating player values in this system is to calculate and sum the z-scores for every player. To do that, you need to know the average and standard deviation of every given stat used in your league. I use the past three years (2015-2017) of collected stat lines from all qualified players to do this. Here are some of the values currently used in the Big Board: