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Are Hitter SGPs Directly Comparable to Pitcher SGPs?

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I recently got an e-mail from a reader of the site (thanks Brad!), asking an interesting question. He was working through creating his own standings gain points rankings and tailoring them for his custom league.

How do I bring Losses into the SGP calculation? If I do make losses a negative, how would I make the pitcher and hitter SGP numbers apples-to-apples?

You might realize that he actually has the correct answer, but it didn’t make sense at first because he wanted to keep hitter and pitcher SGP comparable.

Losses Are an Inverse Category

Losses, like ERA and WHIP, is a category where the goal is to have the lowest total. So the answer is to make the SGP factor a negative number.  If you think about how we calculate SGP factors, we’re really trying to find the slope, or line of best fit, to our historical standings data.

Stolen_Bases_SGP
Example SGP slope calculation.

Traditional categories like Ws and Ks have a line with a positive slope (slanting up and to the right on your high school math class x- and y-axis).  The higher the number of Ws on the x-axis, the more points you get in the standings on the y-axis.

The slope of a graph plotting out Losses would be downward sloping.  The more Ls on the x-axis, the lower the standings points reflected on the y-axis.

So Brad had the right answer, but he was afraid that adding in another inverse pitching category was going to destroy his ability to compare hitter and pitcher SGPs.

The Real Reason We’re Here

I realize you didn’t come here for me to take you back to basic math class.  The real question is, can you take a pitcher who is projected for 4 SGP and say he’s a better draft selection than a hitter projected for 3.8 SGP? (more…)

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Is Multiple Position Eligibility Worth Something?

Is Multiple Position Eligibility Worth Something?

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Think of players like Ben Zobrist, Martin Prado, and Matt Carpenter.

In recent seasons, players like these have been eligible to play multiple positions. The big question is, “All else equal, should you pay more for a multi-eligible player than a player only eligible at one position?”.

I think there’s a clear answer to this question. And it might surprise you.

The Argument That They Are Not Worth More

Would you pay $2 more for Player A because he’s also second base eligible?

Player A (2B / SS): .272, 10 HR, 83 R, 52 RBI, 10 SB

Player B (SS):  .275, 11 HR, 78 R, 55 RBI, 8 SB

Some very intelligent fantasy baseball minds will tell you that a player with multi-position eligibility is not worth more. For instance:

However, since playing more than one position doesn’t mean the player will produce any extra stats, he doesn’t have any greater an actual dollar value than someone who plays only one position.

~ Larry Schechter, Winning Fantasy Baseball

If you haven’t read Schechter’s book, you need to.  It is loaded with very clear and well-reasoned thoughts and strategies like this one.

When you read the book, it becomes clear that Larry has a very bottom line approach.  If a possible decision ends up adding dollar value to your team, you choose that option.  If there is no measurable benefit in dollar value, you don’t.

I love the approach.  That’s why I think everyone should create their own rankings. Attaching dollar values to players makes all decisions systematically easier to make. You no longer have to agonize over decisions like, “Should I drop player X and add player Y from the waiver wire?”.  It’s a lot easier to simply look at each player’s projected dollar value for the rest of the season and decide.

With that said, I think it’s a little short-sighted to only look at the dollar value of a player at a given point in time.

Let’s Play Cards

My wife says my analogies are horrible, but I’m going to try a few on you anyways. Before we get into specific scenarios involving fantasy baseball, let’s first consider a couple of card game examples.

Blackjack

We can probably agree that the ace is the most powerful card in blackjack. A big reason for this is that it’s a gateway to reaching the total of 21.  Without an ace you need a combination of two cards to get to 11 or 21 (2 & 9, 3 & 8, etc.). But the ace gets you there in one card.

Another huge power of the ace is its ability to act as two different cards, a 1 or an 11. It’s an insurance policy. You can behave as if it’s an 11 and quickly change it to a 1 if you bust. It lets you take risks you wouldn’t otherwise take. Keep this in mind.

I’ll end the blackjack example with a question. Assume an 8 in blackjack could be used as an 8 or a 3. You get to decide. Would that make the card more valuable to you than a card that could only be used as an 8?

Poker

I’m not a poker guru but I played my share of Texas Hold’em games in the early 2000’s just like everyone else.

In my mind, a huge decision-making factor in poker is the number of helpful cards (or “outs”) left in the deck.

For example, if you have a pair of 9s, we know there are only two helpful cards remaining (the other two 9s) to help you make three of a kind.

Or maybe you have an open-ended straight like a 4, 5, 6, and 7.  In this case there are four 3s and four 8s that would finish of your straight, for a total of eight “outs”.

Your Hand Your Goal Outs
One Pair Three of a Kind 2
Two Pair Full House 4
Inside Straight Straight 4
Open-ended Straight Straight 8
Four Flush Cards Flush 9
Straight / Flush Draw Straight / Flush 15

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How To Calculate Projected Standings For Your Draft

How To Calculate Projected Standings For Your Draft

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So you’ve got a great set of projections, rankings, and dollar values.

This is great for draft preparation. But how do you take this information and use it during the draft?  Is there a way to monitor the progress of the draft and see if you’re lacking in power compared to the others in the league?  Do you need speed?  Are you lacking in strikeouts?

You don’t need to buy draft software or a special draft spreadsheet.  You can easily add a few more things to your Excel files and have a very powerful draft tool that can help you make these assessments.

I wrote about how to track drafted players in a spreadsheet last January.  If you haven’t read that yet, please do.  The instructions that follow pick up where that post leaves off.

Here’s how to calculate projected standings during your draft.

Prerequisites

I’ll be using Excel 2013 to create the projected standings.  I think you’ll be able to follow a very similar process in Excel 2010 and Excel 2007.

Teams_DraftedAs I mentioned, this post assumes you have already added the named range and data validation drop down listing to select the team that has drafted a player.

This is how you will be tracking the draft selections during your draft.  As each player is taken, you’ll locate them on your rankings/projections lists and select the team that drafted them.

I realize it’s a little early to be thinking about draft spreadsheets, but it’s top of mind for me now because I am participating in a mock draft that was coordinated by Bryan Curley of BaseballProf.com.  I wanted to see how the draft is going and how teams stack up after the first few rounds.  Not to mention you can set this up in your spreadsheet now and have it read to roll when we finally get closer to the season.

You can see the list of those participating in the mock draft in image above.  As selections are being made in the draft, I’m marking them off in drop down I created in the “TAKEN” column.TAKEN

 

You may want to make several “fake” selections in your Excel file, just to have some data to work with.  You will want to test that your projected standings are working prior to the draft…  That’s the last thing you need to be monkeying on draft night.

Excel Functions and Features We’ll Be Using

There are a variety of ways to do this, but I’ll show you how to use a pivot table in this example.  If you’ve never created a pivot table before, don’t worry.  They’re a lot easier to work with than most think.

The pivot table will help us to quickly accumulate every team’s offensive stats (R, RBI, HR, SB, BA).  Once we have the statistics accumulated in one nice table, we’ll then use the RANK formula to calculate the standings.

Pivot Tables

Pivot tables are very useful for taking a lot of lines of data (like we have on our “Hitter Ranks” tab) and combining or summarizing that data into more easily or digestible parts.

For example, your listing of all hitters and their projections is probably hundreds of rows of information.  If you were to select 14 hitters for each of the 12-teams in your league, that would be 168 hitters.  Sorting all of those players into teams and then calculating the totals for five different categories for each team might seem like a daunting task.

The good news is that creating a pivot table can be done in only a few clicks of the mouse and within minutes you can have a table that looks just like this:

Pivot_Table_Projected_Standings

Rank (or RANK.EQ) Formula

These two formulas are essentially the same; however, RANK was discontinued in Excel 2010 and was replaced by RANK.EQ.

If you’re using Excel 2010 or later, either one should work. But if you are using Excel 2007 or earlier, you must use RANK (RANK.EQ didn’t exist then).

These formulas will interpret a list of numbers and return the ranking of a specified item in the list.  We can use this to analyze the entire list of player SGPs and give us a ranking for each player (e.g. Mike Trout is #1).

The formulas require three inputs:

RANK(Number, Ref, Order)

RANK.EQ(Number, Ref, Order)

  1. Number – This is the specific number you want ranked. If your goal is to figure out where your team ranks in total home runs, you would select the individual cell containing your team’s projected home runs.
  2. Ref – This is the range of data, or the list of data, to calculate the ranking from. Continuing with the total home runs example, you would select the entire listing (or range) of projected home runs for all teams in the league.
  3. Order – Technically this is not a required part of the formula, but using it can make our lives a little easier. If you leave this part out of the formula, Excel would return a “1” for the team with the most home runs and a “12” for the team with the least home runs. You can see we don’t really want to know our “Rank”. We’re looking for “Rotisserie Points”. We would like the top team in home runs to show a “12”. The “Order” parameter in the RANK function is looking for a zero or a one. If you leave it blank or put in a zero, the RANK function gives a “descending” ranking. This is the typical ranking where “#1” is the best or highest possible ranking. We are looking for an “ascending” ranking, where a “12” is the best result. To do this, just put a one in for this piece of the function.

Step-by-Step Instructions

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How to Use Excel to Determine Replacement Level

How to Use Excel to Determine Replacement Level

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Who is the replacement level shortstop in a 12-team league that starts one shortstop and one middle infield position?

We know there will be at least 12 shortstops drafted in this scenario.  But will there be 15, 16, 17, 18, or more drafted?  And where does that put the replacement level shortstop at?

This concept of replacement level has always been a little bit of a problem for me.  In my original series about ranking players, I mentioned that in this 12-team scenario, that we would have 36 combined 2B and SS drafted, and to simplify things we could assume that would be 18 second basemen and 18 shorststops.

But that’s not a precise enough answer.

If we’re trying to squeeze every drop of value from our drafts, we should determine precisely who the replacement level player is at each position.  After all, replacement level is a huge driver in the calculation of a player’s value.

So we need to get it right.

What You Can Expect

I’m going to show you a system I’ve started using that will help you identify:

  • The starters at each position (e.g. top 12 1B, top 60 OF, etc.)
  • The corner and middle infielders (the next 12 best 1B/3B and 2B/SS)
  • The 12 utility players (the next 12 best players at any position)
  • The replacement level player at each position

The system is very easy to do.  I was forced to come up with it out of necessity when I was working on my recent analysis of the past five years of draft results.  For that post I had to calculate projected and actual dollar values for each of the last five seasons. So I needed a fool-proof method for determining replacement level 10 times in a short period of time and I also wanted to be able to come back to each set of data and easily be able to tell what group each player fell into.  Thus the color coding.

Replacement_Level
Here’s a little taste of what we’re going to do. I’ll show you a process that will take you only a few minutes to color code and clearly document players into groups of Starters, CI/MI, UTIL, and Replacement Level.

Excel Features You Should Know

There are three pretty neat features of Excel that I used during this process that you may not be familiar with, and they might be able to save you a lot of time: (more…)

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How Does a Player's Age Affect Draft Return?

How Does a Player’s Age Affect Draft Return?

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A few weeks back I took a closer look and analyzed the last five years of preseason Steamer projections (what I’m using as my best approximation of the “draft value” of each player heading into the season) and compared them to the actual end of season dollar values earned by those same players.

One of the glaring omissions in that article was some kind of analysis by age.  Are there certain age groups that might be undervalued?  Better yet, are there certain age groups of hitters we can take advantage of and a separate age group of pitchers we can jump on?

If we are trying to decide between a $20 pitcher who’s 23 years old or a $20 pitcher who’s 33 years old, who should we choose?

Quick Reminders

I’d highly recommend reading the first article that started me down this road.  There’s a greater explanation of the approach used.  But for a quick reminder… the dollar values are based on a standard 12-team league using traditional rosters (2 catchers, 14 hitters, 9 pitchers) and the standings gain points approach.

I also calculate return “including losses” and “without losses”.  The best way to think about this is with a pitcher suffering a terrible injury in the first month of the season.  Being injured that early, regardless of how good the pitcher is, will result in negative earnings.  But the “benefit” of an injured pitcher is that you can immediately drop them and not suffer any of those negative earnings.

The flip side of that coin is with a struggling pitcher.  You may decide to stick with a struggling pitcher for weeks or months, hoping for them to turn it around.  In this scenario you are saddled with many of the negative earnings for that player.  So the actual “return” on players lies somewhere between the “including losses” and “without losses” results.

Draft Results By Player Age

Take a look at the “Including Losses” and “Without Losses” charts below.  Does anything jump out at you?

RETURN_BY_AGE_WITH_LOSSES (more…)

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The Effect of Batting Order on R and RBI Production

The Effect of Batting Order on R and RBI Production

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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!

Thankfully though, I stumbled upon the league splits page for the 2014 season at Baseball-Reference.com.  And it has the batting order splits already calculated for me!

Charts and Table Data

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.

PLATE_APPEARANCES_PER_GAME (more…)

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Analyzing the Last Five Years of Rotisserie Baseball Drafts

Analyzing the Last Five Years of Rotisserie Baseball Drafts

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How many of the top hitters and pitchers at the end of the year were actually drafted? How many of the top hitters and pitchers were not drafted and were picked up during the season?  Were hitters or pitchers drafted more accurately?  What is the dollar value earned by the players that were picked up during the season?  Is there a position of hitter that’s more reliable than other positions?

Have you ever asked yourself draft analysis questions like these?

What follows is a five year analysis (with colorful graphs and an enormous Excel file!) of how accurately our projections in the preseason depict what has actually happened at the end of the season. How well we drafted.  What positions yield the best returns.  What positions offer the most free loot.  And more.

Assumptions You Should Know

A number of the graphs depend on dollar value earnings for the “top 168” projected hitters or “top 108” projected pitchers.  The dollar values are calculated using the approach documented in “Using Standings Gain Points to Rank and Value Fantasy Baseball Players” assuming a 12-team league, $260 team budget, 14 hitters (C, C, 1B, 2B, SS, 3B, CI, MI, OF, OF, OF, OF, OF, UTIL), 9 pitchers, and a 70%-30% hitter-to-pitcher allocation.  That’s a total of 168 hitters and 108 pitchers.

These top projected players in the preseason were determined using Steamer’s preseason projections for that season (I downloaded the historical projections here).

I suppose using ADP results or expert rankings from the given year might give a better picture of the players that were actually drafted, but then you get into the question of what’s good ADP data, where to get it, what experts to use, league differences, lineup differences, etc.

To Be Clear…  The Goal of this Study

The goal of this is not to measure the accuracy of particular experts.  It is to determine which positions can we draft and get the most return on our investment.  To some extent this is a review of Steamer’s accuracy, but that’s also not my intent.  It’s my understanding (tell me if I’m wrong) that there are not significant differences between the top projections systems.  So whether we were looking at PECOTA, Steamer, or Marcel projections, we would see similar results.

How Much of a Return Do We Get For Drafting HItters vs. Pitchers?

People have long been telling us to, “Load up on hitters early in the draft”.

“Don’t overspend on pitching.”

“Wait on pitching until most teams already have one.”

I’ve always heard these things.  They sounded right.  But I can’t say I’ve ever seen the data to support it.

In looking at the chart below it is very clear that we are much better at identifying the top hitters than the top pitchers.  The top 168 hitters in the preseason provide about 70% of the dollars earned at the end of the season.  For pitchers, it’s more in the neighborhood of 40%.

With results like that it’s very easy to see why the hitter-pitcher split is not 50-50.

Hitters are safer investments than pitchers.  We’ve always been told this, but now you can see it.  And things have not changed in the new era of pitching that we’ve been seeing the last few years.  If anything, the gap seems to have widened.

Hitter-Pitcher-Draft-Returns-With-Losses
In a draft and hold environment, the return on investment for drafting hitters fluctuates between 65% and 80%. The return on pitchers is much lower, falling roughly between 30% and 50%.

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Now in Amazon – Using Standings Gain Points To Rank and Value Players

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The Kindle edition of “Using Standings Gain Points to Rank and Value Fantasy Baseball Players: A Step-by-Step Guide Using Microsoft Excel” is now available at Amazon.com.

Want an edge in your league?  Click here to get started on creating customized rankings and dollar values tailored specifically to your league.

The book contains 150+ pages of detailed instructions, over 200 screenshots of how to build this powerful Excel spreadsheet, and links to download 10 example files.

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Is There a Hitting / Pitching Split for a Points League?

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I recently started working on my next book looking at how to create customized rankings and dollar values for a points league.  For the most part, much of the same principles followed for ranking players in a rotisserie league still apply.  But then I stumbled upon a major difference, one that I can’t find guidance on anywhere.

Points Leagues Cut Right To The Chase

One really nice thing about points leagues is that the goal is much more straightforward than in a roto league.  Instead of trying to compose a balanced team in the 10 different categories of a rotisserie league, you’re really just competing in one category… total points.

Because of this, we can cut through some of the exercises we have to do for ranking a roto league.  We don’t have to mess around with league history, determine Standings Gain Points for each category, and don’t have to convert each player’s projections into SGP.

We Just Have To Calculate Projected Points For Each Player, Right?

This is the biggest task, for sure.  Make sure to build in a replacement level calculation, too.

I think that’s what most people would do and just stop there.  But if you want an edge, I think we can dig a little deeper.

Quickly, Here’s How I Would Calculate Projected Points

I’m going to go into much more detail in the finished guide and include screenshots, tips, and tricks to make this a spreadsheet you can use into the future.  But here’s the high level:

  1. Download a set of reliable projections
  2. Document your league’s scoring settings (e.g. 10 points for a HR, 2 for SB, etc.)
  3. Multiply the projected stats by your scoring settings
  4. Determine and adjust for replacement level

Follow these steps and you’ll end up with the total number of “useful” or “draftable” points.

Why Do We Have a Rotisserie Split?

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How Do You Account For and Value Players with Multiple Position Eligibility?

How Do You Account For and Value Players with Multiple Position Eligibility?

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Zobrist_Prado_Santana_CarpenterHow do we handle the multi-position players like Ben Zobrist and Martin Prado?  When a player is eligible to be slotted at 2B, SS, and OF, how do we value that player?

This question came up in the comments of my last post on “How to Add Positional Ranking to Your Spreadsheet“, from a reader named Michael (I welcome your questions too).  In this post I’ll take a look at how I handle this and look at a more inticate approach you could take to get the information.

I must warn you that it takes a lot of new formulas and manipulation of your existing rankings spreadsheet to accommodate multiple positions.  To make sure you have something to reference, at the end of this post I’ll provide a download link to an example Excel file you can download.

Assign the Player to the Weakest Position They’re Eligible For

This is what I currently do.  For example, let’s take a player like Ben Zobrist, who in the 2014 season currently qualifies at SS, 2B, and OF.

In the Player ID Map, I attempt to classify each player at the weakest position they’re eligible for.  I do that by determining what replacement level is for a standard 12-team mixed rotisserie league.

Is the “weakest position” going to be the same for every league?  No it’s not.  It’s probably close in most leagues.  Catcher will almost surely be the weakest in any format.  Then Shortstop will generally be the next weakest, followed by 2B, 3B, 1B, and OF.  But positions might change a little in an 8-team league or a 15-team league, in an AL-only league versus a standard league.

That’s a big reason why I started this site.  It’s not always safe to give blanket advice, and I think the best approach is to calculate all of these things for your own league.  You’ll be better off for it.

How Do I Determine the Weakest Positions?

Assuming you’ve done some kind of work to create your own rankings (if not, start here), the weakest position can easily be determined by looking at the replacement level information you’ve calculated (if you want to refresh your memory on replacement level, read this).

Looking back to one of my preseason files for the 2014 season, this is the replacement level information for one of my leagues.
REPL_LEVEL_TABLE

The weaker positions are those with the lowest replacement level.  So in this league it’s C, SS, 2B, and then 1B, 3B, and OF are essentially the same.

Back to Zobrist

Going back to our example of Ben Zobrist who is eligible at SS, 2B, and OF, if we’re trying to assign him to the weakest position he’s eligible for, he would be assigned to SS.

Thinking of Martin Prado who is eligible at 2B, 3B, and OF, he would be assigned to 2B.

Carlos Santana who is eligible at 3B and C would be assigned to C.

Why Do I Only Assign a Player to One Position?

I have two reasons for this.

The main reason is because assigning players to the weakest position they are eligible for gives the player his greatest value.  I’ll demonstrate more on this in a minute.  But if you’re calculating Zobrist’s dollar value, it comes out highest when he’s classified as a SS.

Going along with this, fantasy baseball leagues are becoming more efficient market places.  As we all get better and smarter about playing fake baseball, people generally realize they’re best off putting Buster Posey at catcher and not at 1B.

This won’t always be the case, but for the most part the obvious situations like your Buster Poseys and Carlos Santanas are going to be assigned where they belong.  Because of this, it’s somewhat of a wasted effort to try calculating values for them at 1B or 3B.

The second reason is a technological one.  You run into a lot of trouble having the same player appear multiple times in one spreadsheet (on multiple rows).  Not only does it become confusing to have to remember that Zobrist’s name appears three times in your draft list, but it also greatly complicates (or eliminates) your ability to calculate dollar values.

How Much Does a Player’s Position Affect Their Value?

Is there really a big difference between a SS and an OF?  Let’s take a look.

I am running the exercise below using Steamer’s 2014 preseason projections.  The dollar values assume a 12-team standard mixed rotisserie league with 14 hitters (C, C, 1B, 2B, 3B, SS, CI, MI, OF, OF, OF, OF, OF, UTIL) and 9 pitchers.  The dollar values are calculated using standings gain points and my approach to calculating player values.

Here’s the replacement level information again:REPL_LEVEL_TABLE

Let’s start out with Zobrist.  You can see below that he was projected for 8.73 SGP before adjusting for replacement level.  When you then account for replacement level and figure out his “SGP Over Replacement Level” you see that he becomes much more valuable as a shortstop.  Over $4 more valuable than when he’s classified as an OF!

BEN_ZOBRIST_REPL_LEVEL (more…)

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