Here are the Excel tools and books I have available for the 2018 season. You won’t find draft lists or player profiles here. But if you’re looking to build skills and to develop your own methods for ranking and valuing players, these are for you! All of the spreadsheet tools listed below have been updated for the 2018 season.
An easy-to-use Excel spreadsheet that can combine (or average) up to three different projection sets. The aggregator can use just about any well-known projection set you can find on the web (if you find one that doesn’t work, let me know!). Simply download your favorite projection sets, fill out some settings, and you’re done. No complicated formulas or VLOOKUPS for you to add.
Ever wanted to create your own rotisserie rankings? This is my instructional guide written specifically to show you how to create customized rotisserie player rankings, dollar values, and inflation dollar values, in Microsoft Excel, tailored to your own league. No more downloading rankings from the web, hoping they apply to your unique league. 10, 12, or 15-team league? $260 or $300 budget? AL-only or mixed league? 10 hitters or 14? It doesn’t matter. This book will guide you through the process of developing rankings for just about any kind of rotisserie league.
My step-by-step guide to building custom rankings, dollar values, and inflation dollar values, in Microsoft Excel, for your points league. This book will guide you through the process of developing rankings for just about any point-based scoring format.
There were some big waves in the nerdy baseball world (I’m a proud card-carrying member) last week, when Baseball-Reference.com released a redesigned website. While the improvements are very nice, especially on a mobile device, the unfortunately broke the link to the Projecting X 2.0 spreadsheet.
Unfortunately, the newly designed site doesn’t seem to allow for the web querying function that was used to extract several of the pieces of information necessary to project pitcher stats. Because of this, we’ll have to make a few small edits to your spreadsheet that will allow you to link directly to the player you are projecting so that you’re taken right to the table containing the desired information (if we can’t pull it into the file, we’ll create a link that takes you right to where the information is located).
What follows are instructions that will help create these helpful hyperlinks and add them to your spreadsheet.
It’s time! Are you getting the itch to start thinking about fantasy baseball again? Are ready to take on a new challenge this year and calculate your own rankings or create your own projections? All spreadsheet templates have been updated for the upcoming 2017 season. Take a look at the available books and tools below.
The Projecting X 2.0 Bundle comes with Mike Podhorzer’s instructional guide to creating your own baseball projections, as well as an accompanying Excel template to help save you hours and hours of time as you work through the projection process.
(NOTE: the Excel template requires you to enter certain formulas from the book, Projecting X 2.0. If you purchased the bundle prior to the 2016 season, this is being offered to save you the time of having to manually update the player names, teams, and positions in the spreadsheet in order to start projecting the 2017 season.)
An easy-to-use Excel spreadsheet that can combine (or average) up to three different projection sets. The aggregator can use just about any well known projection set you can find on the web (if you find one that doesn’t work, let me know!). Simply download your favorite projection sets, fill out some settings, and you’re done. No complicated formulas or VLOOKUPS for you to add.
Ever wanted to create your own rotisserie rankings? This is my instructional guide written specifically to show you how to create customized rotisserie player rankings, dollar values, and inflation dollar values, in Microsoft Excel, tailored to your own league. No more downloading rankings from the web, hoping they apply to your unique league. 10, 12, or 15-team league? $260 or $300 budget? AL-only or mixed league? 10 hitters or 14? It doesn’t matter. This book will guide you through the process of developing rankings for just about any kind of rotisserie league.
My step-by-step guide to building custom rankings, dollar values, and inflation dollar values, in Microsoft Excel, for your points league. This book will guide you through the process of developing rankings for just about any point-based scoring format.
Projecting X 2.0 and the Excel Template are now available!
Yes, that’s right. Mike Podhorzer has just released Projecting X 2.0. And I’m excited to announce an updated Projecting X Excel template has been upgraded to be more helpful than ever and has been updated to be consistent with all the new projection methodologies used in Projecting X 2.0.
NOTE: The Projecting X 2.0 Bundle has been updated for the upcoming 2017 MLB season.
What’s New in Projecting X 2.0?
While I would not consider version 2.0 to be a complete re-write of the original Projecting X, it’s certainly an improvement of the process, methods, and formulas used in the original book.
Don’t get me wrong, I love the Projecting X approach. But I did feel there were a couple of methods in the original version that I thought had room for improvement. For example, I’ve come to learn that using K% is superior to using K/9. And I thought the approach to projecting runs and RBI was too subjective.
Well, Podhorzer has addressed all of those issues, improved upon several of his methods, and even introduced new ones.
My favorite changes to the process are:
A much improved and more scientific methodology for projecting Runs and RBI
Switching from K/9 and BB/9 to K% and BB%
A method for projecting quality starts (I get asked about QS projections all the time!!!)
Addition of metrics like strike percentage (STR%), looking strikes (L/STR), and swinging strikes (S/STR) to pitcher projections, and
Revisions to the projection of stolen base frequency
What’s New in the Excel Template
The Excel template has been updated to be 100% consistent with all the new methodologies and formulas used in Projecting X 2.0. Take a look.
If you’re a user of the Projecting X 1.0 Excel template, the biggest improvements in the file are:
Addition of career stats
Addition of a customizable three-year weighted average
New team hitting and pitching totals that sum as you project
More league average information
New links to Baseball Savant, Brooks Baseball, and RosterResource.com
It’s now easier to add a new player to the spreadsheet
The Player ID Map is now easily refresh-able so that when I add new players or change player teams, this information updates in your spreadsheet too
Download the Updated Bundle Today
The updated book and spreadsheet are available for the bundled price of $17.99 (they separately sell for $9.99 each). Click the Add to Cart button below to begin the checkout process.
Click here to create your own player projections.Going through the process of projecting individual players is one of my favorite parts of the year. I started creating my own projections two seasons ago, using Mike Podhorzer’s book Projecting X.
There are parts of the projection process I feel very comfortable with. I can look at a player’s recent plate discipline, batted ball mix, and power ratios to arrive at an accurate projection for most of that player’s stat line…
But when it comes to projecting playing time, I feel like I’m throwing darts with a blindfold on. How can I realistically make a determination between 675 PAs and 690 PAs?
Until now, I’ve really just relied upon a player’s recent seasons and used qualitative information about injuries, role on the team, and playing time competitions to come up with an estimate for total plate appearances.
Thankfully, a reader of the site recently commented on a post I wrote about the effect of batting order on runs and RBI, and his question helped me arrive at the much more sound approach for projecting playing time I’m about to share with you. Here’s his question:
Interesting stuff. In your research, I am wondering if you happened to look at Team Runs/Plate Appearances on a per game basis?
That is, if a team scores Y runs in a game, what would you predict their Team PAs to be. Something like Y = Ax + B.
~DMM
That question got the wheels turning in my rapidly deteriorating middle-aged brain… There have to be better ways to think about playing time. And I certainly need to take the team’s overall run scoring into account.
Then I created a scatter plot in Excel by graphing team runs against team plate appearances.
I’ve mentioned it many times on the site already. I’m no statistician. I don’t play one on TV. And I’m not pretending to be one on the internet. I am squarely in the area of having enough knowledge about statistics to offer no help but to only be dangerous. With that amazing qualifier I’ll try to explain what you see in that chart above.
Each of the blue dots represents one team’s season in the last 10 years (2006-2015). For example, the dot in the top right corner is the 2007 Yankees, who scored 968 runs (holy crap, A-ROD!).
The dotted red line represents a trend line or line of best fit. It’s the best estimate of the relationship between team runs scored and team plate appearances. The equation on the graph is the formula used to chart out the red line and is the exact answer to reader DMM’s question (where x is team runs scored and y is team plate appearances).
y=1.141x+5375.6
I suppose that could be helpful at the daily game level too. That equation would become y=0.007x+33.18 if you were trying to project a team’s plate appearances in an individual game (where x is runs per game, not season-long runs).
Projecting Individual Plate Appearances
That answers the original question. But I still wasn’t quite satisfied with stopping there.
Sure, it’s helpful to know that if I think Angels will score 700 runs that I should project that whole team for about 6,175 plate appearances (5,375.6 + 1.141 * 700 = 6,174.3). But what does that mean to Mike Trout if I think he will bat second in the lineup? And what if I think he’ll bat third?
Is there a way to add a third variable to the chart above? So we can see how leadoff hitters on teams scoring 700 runs have fared? Or how cleanup hitters on teams scoring 800 runs have performed?
The Data
Baseball-Reference has a really interesting split table that shows the hitting stats each team had from each spot in the lineup (click here to see Kansas City’s 2015 team split).
I downloaded that split table for all 30 teams for each of the last 10 seasons (300 CSV files!). You can see all the raw data here. Again, thanks to Baseball-Reference for making this data available.
Then I grouped the data by team runs scored, putting teams into categories of 500-549, 550-599, 600-649, 650-699, 700-749, 750-799, 800-849, 850-899, 900-949, and 950-999 runs. Here’s a table showing the number of teams in each of these categories for the AL and NL:
If an average hitter is bumped from the sixth spot in the batting order to the two-hole, how much of a bump in performance can we expect?
I’ve written a little about this before. Mostly just suggesting that this is something to keep in mind when you’re looking for hidden value. And I always had in the back of my mind that when I finally got around to downloading all the retrosheet game logs for each season AND learned SQL that I could figure out exactly how much of a benefit this would represent.
Then my five-year old daughter starts playing soccer and is bringing homework back from kindergarten, my sister and twin sister-in-laws all decide to get married in a two-year period, work gets in the way… and before I know it those plans of teaching myself how to process game logs are out the window!
I have taken the 2014 data from Baseball Reference tweaked it some. You will first see a series of charts depicting the batting order splits for 2014. Then after the charts you will see tables showing the MLB, AL-only, and NL-only data.
I’ve added calculations for Plate Appearances per Game, Runs per Plate Appearance, and RBI per Plate Appearance.
These measures are all important inputs when I’m projecting a player’s performance (side note, if you are interested in projecting stats here is the approach I use). Knowing (or estimating) where a player will bat in the order affects the number of times they’ll come to the plate during the season. That spot in the order also affects their run scoring and run driving productivity. You’re more likely to score batting in front of the 3- and 4-hitter than you are batting seventh.
Plate Appearances
The graph below shows that for every spot a player drops in the lineup, they can expect to see about 0.10 or 0.11 fewer plate appearances per game. Over the course of a 162 game season that is about 16 plate appearances. Fall from second in the order to 7th, you’re looking at 80 less plate appearances.
Notice that there’s really not much of a difference between the AL and NL in terms of plate appearances for any spot in the lineup.
For those that have purchased the SFBB Projecting X Bundle (click here to read about the Bundle or here if you’re interested in purchasing), I have compiled expected runs per game metrics from around the web and put them into a format that you can drop into your Projecting X spreadsheet.
In Projecting X, Mike Podhorzer refers to Baseball Prospectus, Clay Davenport, and Replacement Level Yankees as the resources he uses for his expected RPG metric (this is an input into estimating pitcher wins). I was able to locate the BP and Davenport information, but from what I can tell, Replacement Level Yankees has not published the projection. If you can locate it, please feel free to link to it in the comments below this post.
Fangraphs also provides projected standings, and so I included them as the third input.
You can download this file below through the buttons at the bottom of the web part, or possibly even copy and paste from here into your own spreadsheet.
You’ll notice that I removed the 2013 information that was the best guess for 2014 runs per game at the time the bundle was created and released.
“The Process”, My Latest Book, with Jeff Zimmerman
The 2024 edition of The Process, by Jeff Zimmerman and Tanner Bell, is now available! Click here to read what folks like John Pausma, Phil Dussault, Eno Sarris, Clay Link, Rob Silver, Rudy Gamble, and others have to say about the book.
The Process is your one-stop resource for better drafting, in-season management, and developing strategies to become a better manager. The book is loaded with unique studies, tips, and strategies you won't find anywhere else. Click here for more details.
