Market Principles of Dynasty (Part III): Don't Let Perfect be the Enemy of the Good
Stop Chasing Diminishing Returns on your Dynasty Rosters
This will likely be my last “theory” focused edition of the newsletter prior to the NFL draft. On a life-note, my exam period (I’m in my last of law school) is April 12-26th, after which the NFL draft exists, and I move into a new apartment May 1st.
So here’s a (subject to change) expectation of what you’ll be seeing from the newsletter over the next two months:
TODAY: Market Principles of Dynasty Part 3
Within Days after the NFL Draft:
Rookie Draft Tiers + Rankings with brief notes on each player
A Rookie Draft “Strategic Guide” outlining value sweet spots and trade ideas
[possibly] some more in depth write ups of a couple major targets
Time permitting between exams, I may have some rookie content for you pre-draft as well.
As we get back into the summer with less pressing news, I will dive back into the theoretical, but I hope today’s post draws a partial conclusion of the first branch of my Market Principles Series.
In Part 1, we talked about humility and anti-fragility in probabilistic gaming, and introduced the macro-goal of our strategies: those which maximize the benefit of good luck, and minimize the detriment of bad luck. We also discussed the unique ways in which Dynasty as a format rewards both conservative and aggressive game play in a seemingly contradictory fashion.
In Part 2, we talked about the three forms of currency that make up the buying power of your roster: picks, EYR value, and productive value. We talked about the uniquely strong investment that draft picks provide, the fragility of EYR value, and outlined a goal to build competitive rosters while retaining a surplus of draft picks.
Today I will bring these elements together. I will examine four common models of dynasty team building, and apply the concept of diminishing returns and what it teaches us about efficient roster construction.
If you missed the last edition; smash that link below!
I hope today’s far-reaching blend of economics, political theory, and probability is more than enough to chew on for the ‘dark’ period of my content-less exam window.
Models of Team Construction
Let’s begin today’s article with a broad summary of structural approaches to team-construction. Certainly these models do not take into account all teams in any league, nor do most teams fall only within one.
To generalize; there are four models of team-construction (ignoring the fifth and clearly best model of “picking the best players.”)
The Window Model: This is the most commonly referenced approach to dynasty team building. You alternate between competing and rebuilding windows and play to the extremes on both ends. Ideally, an all-out approach increases your win equity in your competing window enough to out-weigh your lost equity in rebuilding years. On the flip side, aggressively tanking in the rebuild window will yield surplus value quickly enough to shift back to contention shortly.
The Productive Struggle: Coined by the great Ryan McDowell, this approach calls for investment in youth and draft picks from the startup, and banking surplus value through a year 1 tank. Ideally, you will have created so much value while tanking that when you shift to contention you can sustain a long-term competing window
The Point Rental Model: This is a term I adopted to describe teams which invest the bulk of their buying power in young players. The goal is to mobilize the majority of your buying power into players rather than picks, and sustain long-term competitiveness by trading players away before the age-apex. When done successfully, this allows you to “rent” the production from these younger players and sell them at a similar value to when they were purchased.
The Conveyor Belt Model: This is a term I adopted to describe a team built primarily around veterans and draft picks. It is the exact opposite of the above. The goal is to sustain long-term competitiveness through surplus rookie picks, while remaining competitive short-term by maximizing the productive value of your remaining buying power through investment in older players.
Let’s relate these models back to our discussion of currency types from last article.
The Windows model alternates between being carrying disproportionately high Productive Value when competing, and then converting to EYR value and picks when rebuilding.
The Productive Struggle begins over-weight on EYR value and picks, and shifts into a plausibly balanced construction over time.
The Point rental model carries a high proportion of EYR value at the expense of picks and, to some extent, productive value. Inversely, the Conveyor Belt minimizes reliance on EYR value and places excess value on picks and productive value.
Renewable Constructions vs. Credit Constructions
Another difference between these models is whether they are “renewable” or “credit-based” constructions.
The first two - Productive Struggle and Windows - are what I call “Credit constructions.” In the competing portion of a Window model, you are often creating excess production value by trading youth and picks for “win-now” production. Effectively, you are putting more points in your lineup than you can reasonably sustain with your team’s buying power and doing it by sacrificing the future. You are in a state of ‘Credit Card Contention.’
On the flip side, the productive struggle is deemed as the more responsible, prudent approach. But you are actually making a similar choice; just in reverse order.
The Risk of Productive Struggles
Under this model, you are likely to accrue excess buying power over the first year(s) of the league because you are not allocating any of your buying power to point purchasing. By chasing future buying power alone, you are playing a parallel game on a parallel timeline compared to the rest of your league. Naturally, you are likely to succeed in this goal.
But while you are not racking up credit card debt in terms of draft picks and future value, you are literally racking up debt in cold, hard cash. By tanking the first year, or potentially the first two years, you need to substantially outperform the win equity you’d naturally expect to have based on your league size in order to generate positive expected value over the long run.
The below diagram illustrates this point.
The Blue line shows the cumulative win equity you would compile in a 12 person league over six years if each championship is awarded at random.
(1/12 = 0.0833 * 6 = 0.50)
The Yellow line shows the corresponding base win equity for each year (8.33-percent).
The red line illustrates the requisite win equity each competing year to reach equilibrium after a one-year tank. Based on a 0-percent year one, you would need 16.67-percent to reach equilibrium in year 2, and 12.5-percent in years 2 and 3 to reach equilibrium by year 3. As the timeline elongates the red line gets closer to the yellow line (base equity) each year as the effect of the initial punt year wears off but will never truly touch it.
The green illustrates the same effect as the red line but regarding a two-year productive struggle.
What you see with this graph is that a productive struggle takes on risk in two ways. First, it presumes your eventual edge in win equity will outpace the win equity knowingly sacrificed. Second, it presumes the league will last long enough in order for your edge to be realized. The latter points is of course subjective but ought to be a legitimate factor of analysis!
While it won’t show up on a graph in such a linear form, the same effect applies to any window-based approach. A strategy which involves proactively punting win equity in any given year places significant pressure on your ability to maintain a win equity advantage in other years, and to actually realize it within a compressed sample of contending years.
This is not to say productive struggles are always bad, or even that they are bad more often. Ultimately, the deciding factor on how successful a productive struggle strategy is, emanates from the degree of win equity advantage enjoyed in post-struggle years, and how much of that edge was derived from the choice to not compete from the outset.
In plain language, How much better chance do you have to win vs. everyone else? And assuming it’s a lot, how much of that is because you tanked?
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