Projecting X 2.0 – How To Create Your Own Fantasy Baseball Projections

NOTE: I originally wrote this several years ago when I first came across “Projecting X” (version 1.0). What follows is my story of how I read that book and ultimately developed an Excel spreadsheet that greatly improves the process and time it takes to project player performance. Projecting X 2.0 has since been released and I’ve worked with Mike Podhorzer to make an even better and more powerful Excel template.

Projecting X 2.0 Cover - 3D 300x381

Making your own fantasy baseball projections is a lot easier than you might think.  And I’m not talking about eyeballing players and saying, “I think he’ll hit about .280 and have 27 HR.”

You can create in-depth-advanced-statistic-driven fantasy projections for any player (is that too many adjectives strung together with dashes?).  I’m talking, “Mike Trout will have 700 plate appearances, a 15% walk rate, 18% strikeout rate, a BABIP of .360, a 43%/21%/36% groundball/linedrive/flyball batted ball profile, and an 18% HR/FB rate, and that will lead to him hitting .324, 116 R, 91 RBI, 30 HR, and 37 SB.”

A little better than eyeballing projections, no?  And I repeat, YOU CAN DO THIS YOURSELF.  EASILY.  All you need is some time, Microsoft Excel, and about $15.

Here’s How I Did it

“There has to be a better way”, I thought to myself.  I am not going to gain a competitive advantage over others in my league just by using the free cheat sheets and sleeper lists, widely available to everyone, from ESPN’s fantasy baseball homepage.

Rather than simply relying on someone else’s rankings (that couldn’t possibly take into account my league rules, tendencies, and keeper situations), I had to formulate my own rankings.  Then I took the plunge and started using the free projections offered at sites like CBS, Fangraphs, and ESPN.  I would then feed these projections into my own ranking system.

This gave me a little sense that I was developing an edge over my competition.  I had figured out the statistics necessary to win the league.  I had obtained projections of players and ranked them based upon that information. < Now I could use this information to compose a team to accumulate the statistics needed to win.

But in the end I was still using a resource freely available to anyone else.  And what if I disagreed with the projection system?  What if Player X is projected for a full 600 plate appearances and I think he’ll only reach 400?  Or what if I think Player Y was a fluke last year but the projection system gives him a favorable outlook?

Simply relying upon someone else’s projections is not the SFBB way.  It was time to get my hands dirty.

Then The Realization Hit Me

If I wanted to truly get an edge, to deeply familiarize myself with the player pool, and to strengthen my understanding of baseball statistics, I had to create my own projections.

But How?

Click here if you're interested in purchasing Projecting X 2.0.
Click here if you’re interested in purchasing Projecting X 2.0.

The task was daunting.  I didn’t know where to begin.  There is a lot of free fantasy advice available on the interwebs, but not much guidance about creating baseball projections.  Any explanation I found was old, overly complicated, and intimidating.

And then I came across the original “Projecting X”, by Mike Podhorzer (click here if you’re interested in purchasing the newest version of the book “Projecting X 2.0”).

I’m a huge believer in the book.  I’ve used it to create my own projections, and I highly recommend it.

What I LikeD About The Book

  • It’s concise and to the point.  After reading the 50-page book, you’ll quickly be on your way to creating your own projections.  We’re not talking about nights and nights of reading before you’re up and running.
  • It’s actionable.  In addition to information about how to develop the projections, Podhorzer gives you step-by-step instructions on how to create your own Microsoft Excel projection spreadsheet (the formulas outlined in the book do require Microsoft Excel).
  • The instructions are very clear.  Things like the exact cell to type a formula in and the specific formula to enter in each cell.  Here’s an example, with a real screenshot from the book:PROJECTINGX_FORMULA
  • The projections are driven by sabermetric statistics like BB%, K%, BABIP, GB%, FB%, and HR/FB%.  Each statistic contains a short write up in the book about how predictable it is, how aging effects players, and links to other online resources to help further your understanding.
  • Each projection is dynamically linked to playing time. I know what you’re thinking, “Dynamically linked???  Stop talking like a techie geek and speak English”.  Alright, alright.  At a high level, each player’s projection is driven by two things – a playing time component (plate appearances or IP) and the skills components talked about in the last bullet.  

    Projecting X 2.0 let’s us isolate these two components. This is extremely helpful.  Let’s say a player is injured during spring training and you expect him to be out 3 months.  You can instantly cut the expected plate appearances in half and you’ll have fully updated projections in an instant.  Find out a rookie makes the team out of spring training?  No problem.  Learn that a player is mired in a platoon?  No problem.  A few key strokes and everything is easily up-to-date.

    Adjust a pitcher’s IP and his whole stat line will adjust accordingly.
  • This is a great learning exercise.  I learned A LOT by doing this.  We learn by doing, isn’t that what everyone says?  Getting your hands dirty looking at walk rates, strikeout rates, batted ball profiles, and home run rates, you learn a lot.  You really start to see how all of these statistics mesh together to create the stat line for a player.  When you enter a player’s estimated fly ball percentage and see it lead directly to a home run projection, it’s very enlightening.
  • This understanding of how to create a projection doesn’t just come into play in the preseason.  This will also be invaluable to you during the season.   If a player is experiencing a power surge, you’ll be able to diagnose why.  Is it because they’re hitting more fly balls?  Is it because they’re getting lucky?  What effect does aging play into thing?  Going through this exercise will equip you with the skills you’ll need to make these player evaluations during the season.

What I Didn’t Like

So there is a lot to like.  But I’m here to be honest with you.  While this is the best forecasting instruction guide I’ve found, and I’ve gotten much more than $9.99 of value from my purchase, there is one big thing you should know… The process is time consuming (but if you keep reading, I have an answer for this).

The method outlined is to project an individual player at a time.  Projecting X lays out the spreadsheet and formulas you need, but then it’s up to you to locate data for each player and use your judgment to create each projection.  Once I developed an efficient system for these things (which I’ll share with you, keep reading!), I could project a player in about 2-4 minutes.  

That doesn’t sound like much, but do the math.  If you are going to project 9 hitters and 5 pitchers for each MLB team, that’s 14 players.  Multiplied by 30 teams is 420 players.  Multiplied by 3 minutes per players is 1,260 minutes, or 21 hours.  So it’s a project.  A fun project.  But it takes time.  You could very easily focus your projections at the top of the fantasy rankings, work your way toward the bottom, and maybe pick and choose some interesting sleepers for the upcoming season.  That might let you cut the time in half and still give you really valuable data to work with.

Does It Work?

I created projections for several hundred players in 2014 & 2015 and I’m already working on my 2016 projections (as I write this in January 2016).  I was very satisfied with the results the past two seasons.  And when I compare my own projections to other notable systems like Steamer and Oliver, they come out very much in line with these other systems.

It’s also worth noting that Podhorzer performed favorably in Tom Tango’s “2011 Forcaster’s Challenge”.

It works.  It’s the most detailed and well-documented approach I can find. I am very happy with the results.

The book is also available for sale on, so you don’t just have to take my word for it.  A handful of readers have taken the time to rate the book.  You can read the reviews here.

The System I Used


As I alluded to above, I think it’s important you develop an efficient system of moving through the player pool and developing projections for each player.  Projecting X 2.0 does a great job of outlining how to develop the projections, but it’s up to you to develop an efficient system.

Here’s what I mean.  For each player, you need to look at some advanced metrics for the last three seasons.  While these are very easy to locate at a site like Fangraphs, the simple acts of visiting Fangraphs and searching for a player might add 30 seconds for each player.

And if you’re creating projections for 400+ players like I was, that extra 30 seconds for each player adds another 3 1/2 hours to the process.

Further, for some other statistics you need to calculate simple averages of the last three seasons that are not readily available on the Fangraphs pages.  This could add another minute or more!

So, as you might expect, I took it upon myself to use Excel to speed this process up.

  • I used the principles from this video to go out to Fangraphs and automatically pull in the last five years of Major League Baseball statistics necessary to follow the Projecting X approach
  • Three years of Minor League Baseball statistics are also pulled into the file
  • The three-year averages are calculated for you automatically
  • I used the principles from this post and set up each player name so it is a clickable link that will go directly to the desired page on Fangraphs.
  • I added more targeted links to take you to each player’s “Standard”, “Advanced”, and “Batted Ball” section of their Fangraphs page

I Shared My Excel Template and Approach with Mike Podhorzer

And he actually tested it out.  Here’s what he had to say:

“I have been projecting players manually for over 10 years and it’s a massively time-consuming process. So I am always looking for ways to make the process more efficient and reduce the time it takes to project each individual player. Tanner’s Excel template is like a gift from the Fantasy Gods! His Excel skills are obvious and make me look like an amateur using the program. It truly takes the methods I shared in Projecting X 2.0 to the next level and makes it easier than ever to become a master baseball forecaster.” ~ Mike Podhorzer

He liked it so much he has agreed to bundle Projecting X 2.0 with the Excel template I developed and my own e-book documenting my approach, tips, and how to use the Excel template.

Now keep in mind you can always visit and purchase the book by itself for $9.99.  Or for just a few dollars more you can get the “SFBB ‘Projecting X 2.0’ Bundle“.

What’s The Benefit Of The Bundle?

Time.  The bundle will save you hours and hours of time.  The Excel template automatically pulls all the data you need to projected a player and it performs calculations for you.  It links directly to each player’s Fangraphs, Baseball-Reference, BrooksBaseball, and Baseball Savant pages. Not to mention links to injury history and the projected lineup for the player’s team according to Roster Resource.

Not to mention this is a projection model you can use every season for the rest of your fantasy baseball career.  You’ll save time every season, giving you more time to focus on fine tuning your projections, rankings, and other draft preparation.

Here’s a Closer Look at the Bundle

The specific materials and features included are:

  • Projecting X 2.0, by Mike Podhorzer
  • The Projecting X 2.0 Excel Template, which comes with:
    • Over 1,000 pre-loaded player names
    • Quickly view each player’s last five MLB seasons, last 10 MiLB stints, 3-year simple average, 3-years weighted average, and career statistics
    • Clickable links that go directly to the necessary player pages at Fangraphs, Baseball-Reference, ProSportsTransactions, Brooks Baseball, and Roster Resource to make your projection process as efficient as possible
    • Automatic calculation of averages necessary for Projecting X 2.0
  • A detailed instruction manual to walk you through the process and how to use the Excel file

Click here to read even more about the SFBB Projecting X 2.0 Bundle.

Or Buy It Now For $17.99!

The Excel file requires at least Microsoft Excel 2007 for Windows.

Sorry Excel 2003 users and Excel for Mac users.

PDF (recommended) Buy Now
AZW3 (Kindle) Buy Now
EPUB (Nook, Apple iPad/iBooks, Sony Reader, Kobo) Buy Now
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*Note: The download comes in a Zip file format and includes an Excel file, so it is not immediately usable if downloaded directly on an iPad or many phones. If you would like to read the contents on those devices, download the Zip file to a computer and simply email the book files to yourself and open them on your iPad or phone.

Happy Projecting!

Thanks for reading.  Stay smart.


9 Responses

  1. Paul H.
    Paul H. at | | Reply

    Was just about to hit purchase when I saw this last line “Sorry Excel 2003 users and Excel for Mac users.”

    What is it about the template that keeps it from working in Excel for Mac 2011?

  2. Tanner
    Tanner at | | Reply

    Hi Paul,

    Yes, this is very unfortunate. For some reason Excel for Mac and Excel for Windows seem to be very different programs. When you use the file on Excel for Mac the web querying (the process that pulls the data from Fangraphs and Baseball-Reference) is extremely slow compared to what you see in Windows, if it works at all.

    I have access to Excel 2011 and I tested it again this morning just to double check. I couldn’t get the web querying to work at all this morning.

    My theory behind this is that web querying probably somehow uses Internet Explorer to do its work, and they had to come up with another way to do it in the Mac environment.


  3. Kyle Stephens
    Kyle Stephens at | | Reply

    How does this system work for playing daily fantasy baseball like Draftkings? Is this for season long projections or can it work for single game projections?

  4. Larry
    Larry at | | Reply

    I apparantly didn’t read the fine print either. Any way to get to this work on a mac?

    1. Tanner
      Tanner at | | Reply

      Hi Larry, sorry for the confusion. I’ve tried to get this to work on Excel for Mac, but I can’t seem to pull it off. The web querying that makes the Excel file so great doesn’t work at all on a Mac. I’ve even tried to develop a separate version of the spreadsheet for a Mac, but even that doesn’t work. I’ll e-mail you about how we can clear things up and take care of the problem for you.



  5. Robert
    Robert at | | Reply

    Can this system be used to make point projections for DFS? Namely Draftkings..

  6. sanga collins
    sanga collins at | | Reply

    I used this for DFS projections last year. It worked very very well. I was able to boil it down to Plate appearances and Innings Pitched being the key values that you had to project each day. It is possible to make a complex formula to obtain these on a day by day basis, but I just used baseball monster to prvent my CPU from melting under the weight of computations.

    I stored the last 3 years stats in Access database. This allowed me to use queries to create a table with all the rates (yellow fields) with a players splits eg: AB/2b vs Hand of SP for that day.

    I used a 2nd excel to import updated players stats from fangraphs daily. These were also combined with the history in the access database based on weights from step 5 on the sheets first tab. This was the only way i could figure out to get data from web to access database :(

    ended up with a good system but very CPU intensive (2x Excel + 1Access open to make it work).

    I’ve learned some new tricks and believe it can be replicated in google sheets now that they support iterative formulas. I am also trying to do something similar in Rstudio with data pulled from stattleship but I am still learning both baseball and coding so it is long ways from complete.

    how the stats looked
    Brandon Drury NL ARI 3B/OF 4 4.38 1 1 0 0 0 1 1 0 0 1 0 0 0 0
    Justin Turner NL LAD 3B 4 4.44 1 1 0 0 0 1 1 0 0 1 0 0 0 0

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