How To Calculate Custom Rankings for a Points League: Part 6 – Replacement Level and Position Scarcity

Welcome to the first part of a series in which we’ll go step-by-step through the process of using Microsoft Excel to calculate your own rankings for a fantasy baseball points league (as opposed to rotisserie or head-to-head rotisserie).

Whether you’re in a standard points league at a major site like ESPN or a more advanced Ottoneu league at Fangraphs, this process will help you develop customized rankings for your league.  These instructions can be used for a season-long points league or a weekly head-to-head points league.

If you’re looking for info on how to rank players for a roto league, look here.

I recommend going through all the parts of the series in order. If you missed an earlier part of this series, you can find it here:

smartfantasybb_3d2 - 500x635

Please note that this series has been adapted into a nine-part book that also shows you how to convert points over replacement into dollar values and how to calculate in-draft inflation. Click here if you’re interested in reading more about the conversion to dollar values.

ABOUT THESE INSTRUCTIONS

  • The projections used in this series are the Steamer 2015 preseason projections from Fangraphs.  If you see projections that you disagree with or that appear unusual, it’s likely because I began writing this series in December 2014, still early in the off-season.
  • For optimal results, you will want to be on Excel 2007 or higher.  Some of the features used were not in existence in older versions.
  • I use Excel 2013 for the screenshots included in the instructions.  There may be some subtle differences between Excel 2007, 2010, and 2013.
  • I can’t guarantee that all of formulas used in this series will work in Excel for Mac computers.  I apologize for this.  I don’t understand why Excel operates differently and has different features on different platforms.

IN PART 6

In this part of the series we will discuss the concept of replacement level, prove that it can lead to better decision making, demonstrate how it is an objective measure for making positional scarcity adjustments, and then incorporate replacement level adjustments for each position into our projected point values.

Accounting For Replacement Level

Heading in to the 2015 season, Ryan Braun is projected by Steamer to produce 82 R, 25 HR, 82 RBI, and 13 SB (or 752 points in my example league).   Buster Posey is projected for 69 R, 19 HR, 75 RBI, and 1 SB (681 points).

Braun’s raw production is clearly superior to that of Posey.  But is that all we need to look at to conclude which player is more valuable?  Don’t we need to include some measure of “replacement level” in this calculation?  Isn’t that what WAR is all about?  Wins Above Replacement?

How do I account for the fact that the day after our fantasy draft I can go out to the free agent listing and pick up an OF that would produce 61 R, 10 HR, 47 RBI, and 15 SB (478 points), or a Catcher that would produce 38 R, 9 HR, 45 RBI, and 7 SB (319 points)?

Clearly the replacement catcher is much less productive than the replacement level OF.

Using Points League Settings

You’ve been following me through the creation of a rankings file for an example league. We just finished converting projected statistics into point values for this league, so let’s take a look at comparing Braun to Alejandro De Aza (a hypothetical replacement level OF) and Posey to Christian Bethancourt (a hypothetical replacement level catcher).

Player Projected Points
Ryan Braun 752
Alejandro De Aza 478
Buster Posey 681
Christian Bethancourt 319

Braun is projected for 274 points over the replacement level outfielder and Posey is projected for 362 points more than the replacement level catcher!

That means Posey is roughly 88 points more valuable than Braun, despite having lower overall projected points.

If you’re having a hard time digesting that, think of it this way.  Let’s assume Braun and Posey represent second round draft picks (just go with it, don’t argue) and De Aza and Bethancourt will be last round draft picks (replacement level).

The team that takes Braun in the second round and Bethancourt in the last round would be projected for 1,071 points.  The team that takes Posey in the second round and De Aza in the last round would be projected for 1,159 points.  Again, that’s 88 more points than the Braun/Bethancourt combination!

This is why considering replacement level matters.

Positional Scarcity Adjustments

You have probably come across suggestions or you might have even thought to yourself that you should “bump” a player up your rankings because he plays a weak position.  But is this really appropriate?  How much do you bump him up?

Another great benefit of incorporating replacement level into your rankings is that it makes your positional scarcity adjustments for you!

You just saw how we proved Posey’s 681 points as a catcher are more valuable than Braun’s 752 from the outfield.  Rather than arbitrarily “bumping” Posey in the rankings, we can figure out exactly where he should be ranked by calculating his “Points Above Replacement”.

Let’s look at the top 15 projected hitters in my example points league.PROJECTED_TOP_15

Not a catcher to be found.  But if we presume this league has 24 starting catchers (you need to read this if you play in a two-catcher league), things change significantly when we calculate points above replacement.TOP_15_OVER_REPLACEMENT

Three catchers rocket into the top 10 while OF and 1B are devalued some.  This movement that takes place after you calculate Points Over Replacement Level IS THE POSITIONAL SCARCITY ADJUSTMENT.  Players move exactly the proper amount.  No guesswork.

EXCEL FUNCTIONS AND FORMULAS IN THIS POST

Nothing really new here.  We’ll just be using things we’ve already used in earlier parts of the series.  We will use another VLOOKUP formula, create a table, and use structured references to build some formulas.

STEP-BY-STEP INSTRUCTIONS

Continue reading “How To Calculate Custom Rankings for a Points League: Part 6 – Replacement Level and Position Scarcity”

You Need To Read This If You Play In a Two-Catcher League

In this post I’m going to demonstrate why you can’t simply rely upon the rankings information you find online.  Widely available rankings do not account for the intricacies of your league.  These differences can lead to large swings in the valuations of players.

You should be calculating your own rankings specific to your own league format, especially if you play in a two-catcher league.  There is a valuation problem waiting to be exploited in two-catcher leagues.  

Please make sure you read to the end.  I get a little carried away with examples below, but there are some important conclusions at the end.

This Is Not a Lie

When I run Steamer’s 2014 projections through my ranking system, Buster Posey and Wilin Rosario come out as top 10 players.

Let that sink in.  In all the draft preparation and rankings articles you’ve read so far, have you seen any catcher crack the top ten?

You’re a Moron.  Your Ranking System Must Be Wrong.

Before you dismiss this out of hand, let’s work through a little exercise.  As with most scenarios I outline at this site, let’s assume a 12-team mixed league using standard 5×5 rotisserie categories, 14 hitters (2 C, 1B, 2B, SS, 3B, CI, MI, 5 OF, UTIL), 9 pitchers, and no bench. This would mean 24 catchers would be drafted, 60 OF, and 168 total hitters.

So as not to pick on any one analyst, I’ll be referring to the consensus fantasy baseball hitter rankings that FantasyPros.com puts out (if you don’t use this tool, it’s pretty neat.  You can instantly average the rankings of your favorite analysts).

As of March 10th, Buster Posey comes in as the top catcher and 36th ranked hitter.  Matt Holliday comes in as the 35th ranked hitter.

Matt_Holliday_Buster_Posey

Let’s say Team A drafts Holliday and with the very next pick, Team B drafts Posey.

If a ranking system were really accurate, you would think the combined stats from Holliday (the 35th ranked player) and Team A’s final draft pick should be very similar to the combined stats of Posey (the 36th ranked player) and Team B’s final draft pick.

Let’s Take a Look

Because Team A passed on Posey, let’s assume they decide to wait until the last round of the draft to fill their second catcher slot by taking the 24th ranked catcher.  In those same consensus rankings, the 24th catcher is Welington Castillo.

Wellington_Castillo

And because Team B wasn’t able to take Holliday with their pick, they decide to wait until the last round to draft their fifth outfielder.  When the time comes, Team B selects the 60th ranked OF (12 teams * five OF per team).  The consensus rankings tell us Kole Calhoun is that guy.

Kole_Calhoun

So Team A ends up with Holliday and Castillo.  Team B ends up with Posey and Calhoun. Applying Steamer’s 2014 projections to these two teams we get:

Player AB H AVG HR R RBI SB
Holliday 530 152 .287 22 78 81 4
Castillo 365 92 .252 12 41 45 2
Total Team A 895 244 .273 34 119 126 6
Player AB H AVG HR R RBI SB
Posey 557 165 .296 20 78 84 2
Calhoun 529 141 .267 17 72 69 11
Total Team B 1,086 306 .282 37 150 153 13

Wow.

Team B wins every category.  The reason for this is the concept of the replacement level players.  The 60th (last picked) OF is still pretty productive, whereas the last catcher selected is a problem.

Maybe Posey should be ranked higher if he gives you that big of an advantage.

You Cherry Picked This Example.  No Way Does This Work Out Like This Every Time.

It is very possible Calhoun is also slanting the results.  When I run his Steamer projection through my ranking system he comes out as the 41st OF (so the consensus rankings are underrating him by ranking him the 60th OF).  I think he’s a terrific sleeper.  So let’s drop twenty three more spots down to Gerardo Parra.

Why Parra, you ask?  Well, he does come out as the 60th best OF when I run the 2014 Steamer projections through my ranking calculations.  He’s ranked the #83 OF in the FantasyPros consensus ranks.

Gerardo_Parra

It would seem that dropping 23 spots further should affect things significantly.  But let’s take a look:

Player AB H AVG HR R RBI SB
Holliday 530 152 .287 22 78 81 4
Castillo 365 92 .252 12 41 45 2
Total Team A 895 244 .273 34 119 126 6

Continue reading “You Need To Read This If You Play In a Two-Catcher League”