When should you draft different positions? Should Antonio Brown be taken ahead of David Johnson? Should Kwon Alexander be grabbed ahead of Travis Kelce? Heck, where should any position be drafted as compared to any other position?
To answer that question, I’ll draw on one of the industry innovations I implemented over 15 years ago: Consistency Rankings. Let’s take a look at how consistent every position player is (excluding kickers, since many studies have proven that kickers should be drafted last, period), the range of their scoring and their relative value. In order to gauge the relative value of positions, for this data sample we’ve chosen to look only at players who would have qualified at the position (so we’re essentially looking at players who would likely be chosen in the early-to-middle rounds of most fantasy drafts). This is a departure from my previous CR methodology, which only looked at players who started more than eight games.
Table 1: Consistency Ratings (“CR”) by Year and Position
Note: The lower the CR, the more consistent the position.
A couple of things to note:
- While I don’t have the formula listed here (I’ll do so in an upcoming column), this is a statistically derived definition of consistency. Unlike some other hack fantasy football writers who define “consistency” as scoring a minimum number of points in a game or as having “good” games, I use math, folks.
- The two most “stable” positions in 2016 were quarterback (offense) and defensive back (defense) while the least stable were wide receiver and defensive lineman.
OK, so what’s next? Well, the next reasonable step would seem to be calculating the relative value of each position, incorporating the stability of each. That is, WR might be the most volatile position but it might have the highest payoff (in terms of fantasy points produced). Let’s take a look:
Table 2: Average Fantasy Scoring by Year and Position
Note: Values assume standard Point-per-Reception scoring.
Hmmm. So quarterback, on average in this sample, produces the most fantasy points. Interesting. Now let’s look at one more factor: population size. That is to say, what is the number of “draftable” players (across all the positions in this study) belonging to each position? Is there one position whose value is driven up due to the scarcity of quality at that position? Let’s take a look:
Table 3: “Draftable” Players by Year and Position
Now this is confusing … tight ends were the scarcest “draftable” position in 2016. But were tight ends really the scarcest position? To really find out, we need to look at the quirk known as roster requirements or starting lineup requirements.
Starting lineup requirements vary from league to league, but most are a takeoff of the one quarterback, two running back, three wide receiver, one tight end, two defensive linemen, three linebackers, three defensive backs and one kicker model. How does a lineup requirement affect our analysis? Let’s keep looking …
Further assuming a 12-team league, the minimum percentage of draftable players that will be required to be taken, by position, would be:
Table 4: Minimum Percentage of “Draftable” Players
So running back becomes the position that requires the highest percentage of “draftable” players (by far), as defined as in Table 3. Does that mean running backs should demand our priority on Draft Day? What about those top-producing quarterbacks? It is obvious that we need some way to weight the results of the first four tables in order to account for the information we’ve just uncovered, in order to place the proper value on each position.
To recap, we’ve tried to determine the relative value of each position in order to craft a draft strategy applicable to any situation. We’ve tried to focus on three factors:
- Consistency (how volatile is each position?)
- Relative value (how much in demand is each position?).
- Inherent value (how well does the position perform?)
In other words, we’re trying to describe each position as if we were evaluating stocks in the marketplace.
When determining a position’s worth during a draft, we’re trying to maximize value for the pick – a fantasy football version of “buy low, sell high.” This concept is nothing new; it is the central premise of Value Based Drafting (VBD), of which Joe Bryant is a big proponent. However, the flaw with VBD is that it is almost entirely dependent on an accurate prognostication of individual player performance. Think about it: if I knew for a fact what the prices of Google and Apple stock will be one year from now, I could make a ton of money by buying low and selling high … but do I really know what the price of those stocks will be a year from now? I can make an educated guess based on a slew of historical data, but that’s about it. Heck, I worked on Wall Street for years and I still have no clue about what the prices of stocks (or players) will be one year from now. So while the tangible value of VBD is highly dubious, there is value to be gained from the discipline of at least trying to assign a relative worth to your drafting of players.
Another popular method of drafting is the Average Draft Theory (AVT), first brought to our attention years ago by Wade Iuele. This is a more refined theory in that it seeks to establish a positional forecast to draft slots, using a three-year historical average of that position. For example, if the top running backs of the past three seasons scored 175, 180 and 190 points, respectively, then the AVT of an RB1 in this year’s draft can be expected to be 181.67. It is a simple and generalized approach, because it does not seek to identify the RB1. It merely says, “Assume that the best running back in this year’s draft (whoever you think that will be) will produce 181.67 points. Then compare that with every other position on your board, and draft accordingly.” We like this approach more than VBD, but it has one immediate flaw: what is the relative value of each position in relation to draft position? Again using a stock analogy, I could use this method to predict that the best stock in a sector (say, Intel in the semiconductor industry) will go up 12 percent in one year; but should I spend my first $1,000 on Netflix, or will I get a better return buying the best stock in the retail industry (say, Amazon) and then buying the third-best entertainment six months from now? In other words, how will the volatility of the market effect the timing and selection of my stock purchase?
Here’s where we feel the BDDM steps in and fills the gaps mentioned above, and it does it on two levels. On the macro level, we can tie in all three major factors (performance, volatility and availability) on a group level – as we discussed earlier in this essay. We can do this by ranking positions in order of their relative value in each component of analysis and come up with an aggregate score:
Note: The table above was derived for a league comprised of 12 teams and position requirements of one quarterback, two running backs, three wide receivers, one tight end.
We’ve done all this math and model building, what does it all mean? It means that for the league and rules listed above, we have established a relative value for every position (outside of kickers and defensive teams) such that during our draft, we’ll know that wide receivers and running backs are more valuable than quarterbacks and that all other things being equal, we should choose to stack the running back and wide receiver positions ahead of the quarterback position, and the quarterback ahead of the tight end. Note that we have not attempted to predict the value of individual players – that would take a micro-level analysis that is beyond the scope of this article.
But notice the true payoff here: after breaking far ahead of the running backs in 2015 (12 percent ahead, to be exact), wide receivers gave back some of that dominance in 2016 — they currently stand just 3 percent ahead of the running backs.