The Economics of Fantasy Baseball: A Pre-Season Primer

Earlier this week fantasy baseball owners everywhere heard the four-word reminder that their fantasy season is right around the corner: “Pitchers and Catchers Report”. While this phrase means plenty to loyal fans around the country, it specifically means two things for Fantistics and our readers: 1) our resident mad scientist and statistician, Anthony Perri has been bunkered down at an undisclosed location (likely with no windows and padding on the walls) and rumor has it he’s been muttering BHIP%’s and Strand Rates to himself while rocking back and forth for the last month; and 2) Fantistics subscribers are secretly sneaking away from real life responsibilities to play with the draft software, most likely with the new Mock Draft module. While a sleep-deprived Anthony continues to pound away, we (the writers) will start providing more ways to prepare for the draft that are slightly less addictive than the new Mock Draft module. With that in mind, let me first take the time out to introduce myself before delving into my first article of the 2008 season, which will take a more in-depth look at how to correctly identify value on draft day within the context of your own league rules.

My name is Drew Dinkmeyer and I’ve been writing for Fantistics for 3 years now, both on the Fantasy Football and Fantasy Baseball products. I am a die-hard Chicago sports fan, who grew up far away from Wrigley Field in the warm sunshine of South Florida. I’ve been competing in fantasy leagues for over 14 years, starting by hand-calculating statistics out of the newspaper box scores and keeping tabs on the standings with a dry-erase “leader board” in my bedroom. To this day I still can’t kick the addiction, competing annually in over 15 leagues. As a writer, I’m unrefined and unfiltered. Unrefined in the sense that I’m not trained professionally as a writer, and I don’t pretend to be. Luckily for me, we do have a trained professional in Lou Blasi on the staff. I’ll defer to his expertise in eloquently painting pictures, telling stories, and captivating audiences with his words, while I’ll haphazardly stumble through some paragraphs leading up to raw statistical analysis. I’m unfiltered in the sense that I don’t believe in wavering on opinions and I don’t believe in hiding my feelings. I think in general the fantasy community, like all forms of sports reporting these days, suffers from “Groupthink”. If there is a player projection we have that I don’t agree with, I’ll write about it. If there is a player I like you’ll know about it. I intend on using this blog space often during the course of the season, and I intend on providing mostly fantasy filled content while throwing in an occasional rant about my beloved Cubs or baseball in general. As an analyst, I feel it’s my job to teach you how to fish, as the metaphor goes, rather than fish for you. I’ll read and respond to all email that comes in and give my honest opinion about any trade ideas or general strategy, in hopes of providing you with my outlook on a situation as well as learning yours. I don’t believe in “experts”, and I don’t believe I’m done learning or that I know every conceivable way to win at this game. I’ve played this game for over 14 years and each year I learn a different way to look at things or a different strategy to carry forward, so I welcome criticism and suggestions. I genuinely believe one of the things that make this site so unique is a journey that’s created by the interaction between the writers and the subscribers. So please continue to write in if you have in the past, and if you haven’t and something strikes you, queue up an email, I’ll be waiting! Now let’s get ourselves started on the path towards title-town.

With the introductions out of the way, let’s move onto the first article of the season and talk a little bit about the concept of value. The majority of the fantasy articles out there will talk about value in the context of individual players and the difference between their draft position and their actual “value” (statistical projections). While this concept is incredibly important and one that I’m sure you’ll read more about here as we head towards opening day, it’s not the type of value I’m going to focus on today. Instead I’d like to focus on understanding the dependence a player’s actual value has on your league characteristics. I think this is one of the most underrated points of analysis heading into draft day. As you comb through magazines or other articles on the web, you’ll see plenty of projections, ranking lists, $ values, etc for almost anyone that’s ever held a baseball bat. What you won’t see though, at least on other sites, are projections customized to your league, and this is a very big problem. In fact, the reason I titled this article: “The Economics of Fantasy Baseball: A Pre-Season Primer”, is because I equate this problem with conventional projections to a very basic economic lesson on currency. Think of your bundle of projections as a big sack of dollar bills. As you travel around the world with your large sack of U.S. currency, the total value of the sack continues to change with each new country you enter because your sack gets translated to the value of the currency in that country. In fantasy baseball terms if you think of each country as a different league format, you can see the parallel I’m trying to draw: projections shouldn’t be equally valued across different league formats because different league formats reward different statistics.

Now, this lesson is more commonly taught in terms of $ values given by magazines and sites. They’ll reference the total salary cap that their dollar values reference, usually $260 and then make a token reference to adjust for your league’s salary cap. The typical example would be a player projection worth $30 in a $260 league, is worth about 11.5% of your budget, so in a $100 cap league the player projection would be worth roughly $11.5. While the computation isn’t difficult and is one that mathematically makes some sense the idea of a “standard” $260-cap 5 x 5 league incorporates a few other assumptions. It assumes a “standard” league size and a “standard” set of roster requirements. This is usually a 12-team league with approximately 28 players, which creates a league with 336 rostered players (24 Catchers, 12 1B, 12 2B, 12 SS, 12 3B, 12 MI, 12 CI, 12 U, 60 OF, 108 P, and 60 Reserves). The reason I map out the positional requirements is because the size of a league directly impacts that leagues positional scarcity. But what happens if your league isn’t “standard” in terms of size? The answer is: it impacts positional scarcity, which then trickles through to overall rankings. Let’s use an example to help illustrate how changes in positional scarcity can impact the value of your projections.

One of the more popular methods of discussing positional scarcity is to place players in tiers, which we do as well with our color-coding system in the draft software. A tier system of evaluating players helps the most when understanding the impacts league size and roster requirements have on positional scarcity. As a quick example, let’s take a look at a position I feel is a bit more scarce than usual this year: 3B.

16 Team League			12 Team League			8 Team League
Player	Team	VAM	Player	Team	VAM	Player	Team	VAM
Rodriguez, Alex	NYY	16.1	Rodriguez, Alex	NYY	15.2	Rodriguez, Alex	NYY	14
Cabrera, Miguel	DET	13.3	Cabrera, Miguel	DET	12.1	Cabrera, Miguel	DET	10.5
Wright, David	NYM	12.9	Wright, David	NYM	11.6	Wright, David	NYM	9.9
Braun, Ryan	MIL	10.5	Braun, Ryan	MIL	8.8	Braun, Ryan	MIL	6.7
Atkins, Garrett	COL	5.6	Atkins, Garrett	COL	3.2	Atkins, Garrett	COL	0.3
Ramirez, Aramis	CHN	4.3	Ramirez, Aramis	CHN	1.8	Ramirez, Aramis	CHN	-1.4
Zimmerman, Ryan	WAS	3.2	Zimmerman, Ryan	WAS	0.5	Zimmerman, Ryan	WAS	-2.8
Jones, Chipper	ATL	2.9	Jones, Chipper	ATL	0.1	Jones, Chipper	ATL	-3.3
Gordon, Alex	KC	0.6	Gordon, Alex	KC	-2.5	Gordon, Alex	KC	-6.2
Beltre, Adrian	SEA	0.6	Beltre, Adrian	SEA	-2.5	Beltre, Adrian	SEA	-6.3
Figgins, Chone	LAA	0.5	Figgins, Chone	LAA	-2.7	Figgins, Chone	LAA	-6.4
Lowell, Mike	BOS	0.3	Lowell, Mike	BOS	-2.9	Lowell, Mike	BOS	-6.7
Encarnacion, Edwin	CIN	-1.1	Encarnacion, Edwin	CIN	-4.4	Encarnacion, Edwin	CIN	-8.4
Longoria, Evan	TB	-2.6	Longoria, Evan	TB	-6.2	Longoria, Evan	TB	-10.4
Blalock, Hank	TEX	-2.6	Blalock, Hank	TEX	-6.2	Blalock, Hank	TEX	-10.5
Chavez, Eric	OAK	-4.1	Chavez, Eric	OAK	-7.9	Chavez, Eric	OAK	-12.4
Kouzmanoff, Kevin	SD	-4.2	Kouzmanoff, Kevin	SD	-8.1	Kouzmanoff, Kevin	SD	-12.6
Mora, Melvin	BAL	-5.8	Mora, Melvin	BAL	-9.9	Mora, Melvin	BAL	-14.7
Glaus, Troy	STL	-6	Glaus, Troy	STL	-10.1	Glaus, Troy	STL	-14.9
Reynolds, Mark	ARZ	-6	Reynolds, Mark	ARZ	-10.1	Reynolds, Mark	ARZ	-14.9

The chart above is used to show the impact of league size on tiers. In this chart we’re showing three different league sizes (using the roster requirements and salary cap restrictions described above in a “standard league”). I’ve used VAM, which is probably the most important concept used here at Fantistics to help illustrate the impacts of league size on position scarcity. (Read more here: http://www.insiderbaseball.com/VAM.htm). If you don’t have the time to read the link posted above and aren’t familiar with VAM, VAM is essentially the method Anthony Perri developed to quantify positional scarcity. In this chart you’ll see three VAM values highlighted in Red (one for each league size); these values are highlighted because they represent the last “starter” drafted in each of these formats. In the 16-team league this represents the 16th ranked 3B; in the 12-team league it represents the 12th ranked 3B, and so on. The purpose for highlighting this number is to show the impact varying league sizes have on positional scarcity. Because talent isn’t distributed in a linear fashion, pockets of depth emerge sporadically. This is, generally, why we use the tier system. Different size leagues slice through this distribution differently, which ultimately determines the scarcity of the position as a whole. 3B this year is a unique position because of the way the talent is distributed. If your goal was to wait on a 3B and draft him late, because of the talent distribution, the strategy would be more beneficial in a 12-team league than either a 16-team league or an 8-team league, as evidenced by the VAM for the 12th 3B in a 12-team league being higher than the 16th 3B in a 16-team league or the 8th 3B in an 8-team league. Essentially this illustrates that as you re-configure the total number of players being rostered at a single position, you’re impacting the scarcity at that position. If you can envision this movement happening across all positions you can see a picture shaping that creates differences in player valuations just based on the difference in the number of teams participating in your league or the number of a specific position being required. For example a league that requires two Catchers as opposed to one or a league that requires five OF’s as opposed to three will all carry differences in scarcity. As the shifts happen across positions, overall player rankings begin to move in unison. As a position becomes scarcer, the top rated players at that position become more valuable. Without the player projections ever changing, the value of the players IS changing.

This same concept not only applies to leagues of differing sizes but it applies to leagues with different scoring formats. Fantasy Baseball scoring systems have transformed so much over the last few years as providers have become more customizable with their league formats that I challenge owners to explain which league format represents the “standard” anymore? If we can’t identify a “standard” league how good are the “standard” league values we’re looking at alongside our projections? The simple answer is: not very good. As an example let’s take a look at the Top 20 overall rankings for two different league types with the same league size and roster requirements, but different scoring formats:

 

Fantasy Points Based			5 x 5 Rotisseie
Player	Team	Rank	Player	Team	Rank
Reyes, Jose	NYM	1	Rodriguez, Alex	NYY	1
Santana, Johan	NYM	2	Holliday, Matt	COL	2
Howard, Ryan	PHI	3	Reyes, Jose	NYM	3
Rodriguez, Alex	NYY	4	Santana, Johan	NYM	4
Peavy, Jake	SD	5	Ramirez, Hanley	FLA	5
Sizemore, Grady	CLE	6	Cabrera, Miguel	DET	6
Pujols, Albert	STL	7	Pujols, Albert	STL	7
Holliday, Matt	COL	8	Utley, Chase	PHI	8
Webb, Brandon	ARZ	9	Wright, David	NYM	9
Ramirez, Hanley	FLA	10	Crawford, Carl	TB	10
Wright, David	NYM	11	Peavy, Jake	SD	11
Fielder, Prince	MIL	12	Sizemore, Grady	CLE	12
Rollins, Jimmy	PHI	13	Rollins, Jimmy	PHI	13
Haren, Dan	OAK	14	Guerrero, Vlad	LAA	14
Cabrera, Miguel	DET	15	Soriano, Alfonso	CHN	15
Crawford, Carl	TB	16	Braun, Ryan	MIL	16
Utley, Chase	PHI	17	Ortiz, David	BOS	17
Dunn, Adam	CIN	18	Fielder, Prince	MIL	18
Ortiz, David	BOS	19	Webb, Brandon