Preparing for your fantasy baseball draft requires using the best data available. If you use bad data then you’ll make bad draft decisions. It’s as simple as that. The core piece of data behind any good fantasy baseball draft prep is the type of projections that you use. I’ll do a rundown soon about which of the available projections are most accurate (I gave you a hint in my recent tweet here) but, first, I’m releasing my 2017 projections out into the world.
The thing that is unique about these projections is that they pull from a variety of other free projections sources that are available and strategically combine them into a super projection. Back in my early days of doing fantasy baseball research, I quickly found that averaging the available projections each year will result in a very accurate projection model. I later found that some projections were better than others at certain things. This resulted in an experiment with combining the projections but providing certain weights to the source for each individual stat, based on which projection was best at projecting it.
For instance, ZiPS has historically done the best job of projecting stolen bases and CAIRO has done the worst at it. So, for 2017, I took all of the stolen base projections out there then put the highest weight on the ZiPS stolen base projection while lower weights on Steamer and Clay Davenport’s projections and leaving out CAIRO altogether. When all is said and done, these weightings generated my optimized stolen base projections for 2017. I then moved on to the next stat and kept going until I’ve projected all of the stats for hitters and pitchers.
I’ve found that this way of combining the projections has been very accurate and much more accurate than simply combining the projections without weights. Each year, I learn a bit more about what works and what doesn’t. After four years of weighting projections in this way, I continue to adjust and improve. For instance, this year I’ve decided to start incorporating previous year stats and x-stats into weightings this year. They are used sparingly but still have value in increasing the projection accuracy at times.
In the 2017 version, when all was said and done, the following sources are used:
- Clay Davenport
- Fangraphs Fans
- Fangraphs Depth Charts
- 2016 xStats
- 2016 Actual Stats
If those sources did not exist, my Special Blend would not exist so many thanks to them for all of their hard work in generating their initial projections.
The 2017 Projections
I’ve embedded the list of 2017 projections below but you can see a full view of them by accessing them through the Google Doc here. From the Google Doc, you can also download them and do whatever crazy things you want with them. When looking through these, keep in mind that there’s a separate tab for Pitchers and Hitters. There’s also columns for the calculated WERTH roto value of a player based on a standard 5×5 roto league format. The WERTH value is a z-score that calculates how far above or below average a player is in the main roto stats. If you want custom WERTH values for your specific league settings, check out my Excel cheatsheet where you can input your league settings.
Frequently Asked Questions To Address!
YES, there are some players missing from here. Carlos Carassco comes to mind and many closers too. If any of the six main projection sources are missing a projection for a player then I will be too. The source that has the least amount of projections is the Fangraphs Fans (so go there and add your own projections maybe so I can have more projections!).
YES, I will be continuing to update these until Opening Day.
YES, I like piña coladas and getting caught in the rain.
Anyway, let’s get on with it!
Projections last updated on 03/28/2017
Luke is better known as Mr. Cheatsheet despite his last name not being Cheatsheet. He makes spreadsheets, writes blog posts and his rankings were in the top 10 accuracy among FantasyPros experts in 2014, 2016 and 2017. When he's not doing fantasy baseball things, he can be found playing board games or rating beer.