Tag: Standings Gain Points

How Does a Player’s Age Affect Draft Return?

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 Continue reading “How Does a Player’s Age Affect Draft Return?”

Analyzing the Last Five Years of Rotisserie Baseball Drafts

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%.

Continue reading “Analyzing the Last Five Years of Rotisserie Baseball Drafts”

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


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.

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

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 Continue reading “How Do You Account For and Value Players with Multiple Position Eligibility?”

An Even Better Positional Ranking Formula

In my last post about how to calculate positional rankings in your player spreadsheet (link), I realized a weakness in the approach I outlined.  I’m here to fix that with a slightly more complex formula. Final_Excel_Formula_Output

The Weakness In The First Approach

The problem with the first approach is that it is entirely dependent upon how the file is sorted.  If the file is sorted by dollar value or standings gain points in descending order, then the rankings work.

But if you sort the file by home runs, stolen bases, or player name, then the rankings fall apart.  The player with the most home runs (or the most stolen bases or the first name alphabetically) becomes the top ranked player.

The COUNTIFS Excel Function

Instead of the COUNTIF function, we’ll use the COUNTIFS function this time.

You might remember from the last post that the COUNTIF function will count the number of cells in a specific range that meet a specified condition (e.g. “Hey Excel, count all the players in this column that have a ‘POS’ of ‘OF’.”).

Well the COUNTIFS function counts the number of cells in a specific range that meet all of the conditions you provide (you can give multiple conditions).

In plain English, our goal is to have Excel count all the players in our list of hitters that have a “POS” of “OF” AND that have a higher projected SGP than our player being evaluated.

We’ll get into the specifics of our formula in a bit, but here’s a screenshot of the Excel formula wizard for our COUNTIFS function.COUNTIFS_FUNCTION

This formula allows for an open-ended number of arguments, but you do need to pieces of information for each set of criteria you want to specify.  Each criteria requires:

  1. Range – This is the block, column, or area of cells we want to count from.  “Excel, look in Column E and count the cells that meet this condition I’m about to tell you about in bullet #2.”
  2. Criteria – This is what we are evaluating the cells for.  “Count the cells in Column E that show ’1B’ as the position.”

If we want to specify three conditions that must be met, then we would need six arguments (three ranges and three criteria: range1, criteria1, range2, criteria2, range3, criteria3).

Step By Step Instructions

Continue reading “An Even Better Positional Ranking Formula”

How To Evaluate a Trade Using Standings Gain Points

In this video I’ll show you how to add a Trade Evaluator into your existing rankings spreadsheet.

Here’s an animated image demonstrating the finished product.  This spreadsheet will pull in all the Rest of Season projections for a player, their total SGP to be earned the rest of the season, and the player’s dollar value (provided you’ve added dollar value calculations to your sheets).

TradeEvaluator

I’ll also show you a practical example and explain a few important things to think about when considering trade offers.

The video is roughly 30 minutes long, but keep in mind that just about everything you create by following the guides on this site are long-term in nature.  With a little bit of maintenance, all of these tools can be used all season long AND into future seasons.

The Step-By-Step Process

I start with a spreadsheet that has already been updated with RoS Projections.  I then show you how to add a tab just to evaluate trades and other roster decisions.  We’ll add drop down menus that pull each player’s statistics, dollar value, and SGPs.

This information will enable you to add clarity to all your roster moves.  No more using your gut to analyze a 2-for-3 player trade involving hitters and pitchers.  You’ll be able to see exactly which side of the offer is better.

If you’re new to the site, I would suggest getting familiar with How To Create Your Rankings Using Standings Gain Points.

A Quick Suggestion

WatchVideoDoubleSpeedIf you’re looking for a way speed things up by watching them 1.5 or 2 (double)  speed, cutting down the time it takes to watch significantly.  Just adjust the settings at the bottom of the video player.  Click the cog and change the “Speed to 1.5 or 2.

I also recommend watching the videos in HD.  A lot of the detail in Excel can only be seen well in 720p or higher.

And a Disclaimer

I created this video using Prince Fielder, Jose Abreu, Billy Hamilton, and Ian Kinsler in an example trade.  News that Fielder is facing season-ending surgery came out the next day!  I apologize for this glaring problem with the example, but hope you can still see the power of using a tool like this to evaluate trades and free agency acquisitions.

Here’s The Video

Thanks for Watching

Stay smart.

Questions?  Comments?  Future Video Ideas?

Let me know in the comments below.

How To Use SGP To Rank and Value Players During the Season – Part 6 – Adjust Replacement Level

Welcome to the final part of the series in which we go through the process of plugging Steamer’s Rest of Season (RoS) projections into your existing ranking/dollar value spreadsheet so you can make informed and objective roster decisions during the season.

If you register as an SFBB Insider (it’s free), you can receive the entire series in an easy-to-use e-book (also free) along with two other helpful guides.  I’ve also written a comprehensive guide on ranking players and calculating player dollar values that’s available at Amazon.

Introduction

In this sixth part of the series we will revisit the concept of replacement level and adjust replacement level for our updated RoS projections.

Reminders About Replacement Level

If you’re new to the concept of replacement level read the introduction here (don’t go into the “Step-by-Step Instructions”.  When you consider the injuries that occur in Major League Baseball, rookies being called up, players underperforming projections, and others exceeding projections, the player pool is constantly changing.

In order to make the best possible decisions and to calculate representative dollar values, it is very important that we update the estimate of replacement level.

Caution:  No Further Adjustments Necessary

When listening or reading fantasy advice, you might come across a piece of advice that goes something like this, “You really need to draft a SS early to account for the lack of depth at the position.  Go ahead and reach for that shortstop.”

Don’t listen to that advice when you’re using the approach we’re now going through.  The replacement level adjustment that follows is already calculating the effect of depth at each position.  And it does it mathematically.  There is no guesswork going on here.

DON’T MAKE ANOTHER ADJUSTMENT.

You do not need to make an arbitrary adjustment to shortstops or catchers, or any other position.  When you have added this adjustment to your rankings, each player will be ranked according the their value over the worst players at the position.  If the position is weak, that’s accounted for.  If the position is deep, it’s accounted for.

If you then decide to make arbitrary adjustments to your rankings after adding in the replacement level calculation, YOU ARE DOUBLE COUNTING.

You will be reaching for players and you will be hurting your team.  Don’t “bump” players up a list because of their position.

Step-By-Step Instructions

Continue reading “How To Use SGP To Rank and Value Players During the Season – Part 6 – Adjust Replacement Level”

How To Use SGP To Rank and Value Players During the Season – Part 5 – Update the Player ID Map

Welcome to the fifth part in a series of posts in which I’ll go through the process of plugging Steamer’s Rest of Season (RoS) projections into your existing ranking/dollar value spreadsheet so you can make informed and objective roster decisions during the season.

If you register as an SFBB Insider (it’s free), you can receive the entire series in an easy-to-use e-book (also free) along with two other helpful guides. I’ve also written a comprehensive guide on ranking players and calculating player dollar values that’s available at Amazon.

Introduction

In this fifth part of the series we discuss updating the Player ID Map to pull new players into the rankings information.

Player ID Map

The SFBB Player ID Map contains the Fangraphs, MLB, Baseball-Reference, Retrosheet, CBS, NFBC, ESPN, Baseball Prospectus, Davenport, and Yahoo player IDs for over 1,200 players.  It’s not a comprehensive list of past players by any means, but I make a concerted effort to have all current fantasy-relevant MLB players and those minor league players likely to make a fantasy impact this season.

PlayerIDMap

To give credit where credit is due, I originally downloaded the player map from Crunchtimebaseball.com and tailored it to meet my needs.  CrunchTimeBaseball is run by Tim Blaker.  He continues to maintain his own map of player IDs and generally keeps his more up-to-date than I do.  You can obtain his version here.

Why Update the Player ID Map

April inevitably brings us players that were never intended to be fantasy relevant; minor leaguers that were not anticipated to make the jump, role players thrust into starting jobs, and more.  As the summer rolls on, impact rookies begin to get called up that may not have been in the preseason Player ID Map.  When September arrives there will be more of the same.

While it is possible to add individual players to the player ID map, it can be inefficient to add more than a handful.  Updating the entire list is probably easier.

Step-By-Step Instructions

Continue reading “How To Use SGP To Rank and Value Players During the Season – Part 5 – Update the Player ID Map”

How To Use SGP To Rank and Value Players During the Season – Part 4 – Add the IFERROR Formula

Welcome to the fourth part in a series of posts in which I’ll go through the process of plugging Steamer’s Rest of Season (RoS) projections into your existing ranking/dollar value spreadsheet so you can make informed and objective roster decisions during the season.

If you register as an SFBB Insider (it’s free), you can receive the entire series in an easy-to-use e-book (also free) along with two other helpful guides. I’ve also written a comprehensive guide on ranking players and calculating player dollar values that’s available at Amazon.

Introduction

In the fourth part of the series we’ll introduce a new Excel formula to help remove lookup errors, like those shown above, from our spreadsheets.  These occur when we have instructed Excel to do a VLOOKUP to find a player’s RoS projections and Excel is unable to find the player ID within the projection data.

Often times a player will stop appearing in the RoS projections.  This might be because they’ve suffered a season-ending injury, they’ve retired, or they’re an unsigned free agent. If that player remains in the list of hitters or pitchers rankings, no projection can be found for that player.  I’ve realized that the rankings and dollar value formulas I previously used did not handle these situations very well, so it’s necessary to adjust these formulas slightly.

Adding this formula to your spreadsheet is a one-time fix.  You won’t need to go through this part when you download updated RoS projections in the future.

Excel Functions in Part 4

IFERROR

The IFFERROR function allows us to control what happens when another function being used is calculating an error.  The image below is a great example of this.  On our “Hitter Ranks” tab we have a series of VLOOKUP formulas that instruct excel to go find Kendrys Morales’ player ID (moralke01) in the “Steamer Projections” tab.  During the 2014 season Morales is likely not included in the RoS projections because he remains unsigned by any Major League team.

IFERROR-Excel-Formula

The IFFERROR function will allow us to replace the error message with any value of our choice.  It essentially works by telling Excel, “If this other formula I’m using comes back with an error, use this instead”.

The formula requires two inputs:

IFERROR(value,value_if_error)

  1. Value – This represents the formula or calculation we want Excel to perform.  In our example above it will be the same VLOOKUP formula we already have entered.
  2. Value_if_error – This represents the value or message we want Excel to return if the first argument, “Value”, returns an error.  In our example above we don’t want the default “#N/A” error message that turns up if Excel cannot locate Kendrys Morales in the RoS projections.  Instead, we could just ask for Excel to return zeroes for his projected stats.

Step-By-Step Instructions

Continue reading “How To Use SGP To Rank and Value Players During the Season – Part 4 – Add the IFERROR Formula”

How To Use SGP To Rank and Value Players During the Season – Part 3 – Delete Old Info and Insert New RoS Projections

Welcome to the third part in a series of posts in which I’ll go through the process of plugging Steamer’s Rest of Season (RoS) projections into your existing ranking/dollar value spreadsheet so you can make informed and objective roster decisions during the season.

If you register as an SFBB Insider (it’s free), you can receive the entire series in an easy-to-use e-book (also free) along with two other helpful guides. I’ve also written a comprehensive guide on ranking players and calculating player dollar values that’s available at Amazon.

Introduction

In this third part of the series we will remove the old (preseason) projections from our spreadsheet and paste in the new information.  It sounds simple, but there are a few tricks to be aware of.

Step-By-Step Instructions

Continue reading “How To Use SGP To Rank and Value Players During the Season – Part 3 – Delete Old Info and Insert New RoS Projections”