First Round Draft Prospect Rankings via Positional Value Multiplier

As Eagles fans, all of us have "top 10" players who we would like to see end up in Kelly Green. While everyone agrees that NFL teams value certain positions higher than others, nobody has yet quantified this relationship. Brent Cohen and I collaborated on an article which quantifies this relationship via a Positional Value Multiplier and then transposes these relationships onto the consensus top 32 draft prospects. This helps explain why quarterbacks go early despite being inferior BPA prospects. The post is a duplication of our original work; if you like it, please check out Brent's site. Lots of great stuff.

TL;DR VERSION: What_Paradox? & Brent Cohen's TOP 32 NFL PROSPECTS based on positional value adjustments. Findings are contained in the last spreadsheet.


What We Did:

The overall aim of this project was to apply a positional value modifier to the consensus prospect rankings, with the hopes of generating a more accurate system of ranking value. We compiled a composite prospect rating for each player (through the first couple rounds) and then adjusted for positional importance according to last seasons’ league-wide positional salary distribution.

Before we go into the How details, here is the consensus prospect ranking using ratings from Scouts Inc (ESPN), the National Football Post, and Note: NFP uses a different grading scale, so those scores were adjusted to give us an apples-to-apples rating.


That graphic alone is pretty interesting, particularly when the ratings diverge (see Ryan Nassib at the bottom), but we’ll look at that some other time.

For today’s post, we have to adjust.

How We Did It:

I mentioned earlier that no BPA ranking is complete without an adjustment for relative positional value. For example (an extreme one), if a QB and K both carry a 95 rating, you’d obviously choose the QB first. The question is, how do we measure relative importance by position?

While there is no bullet-proof method of doing so, the salary distribution in the NFL is as good a place as any to divine information from. In theory, since the NFL has a salary cap, the distribution of limited funds between positions will give us an idea of how the league, on average, values different positions in relation to each other.

We pulled salary cap information from the Guardian. It’s not perfect (reflects cap hits from last season and misses some IR guys), but in general I believe it’s as good a breakdown as any for our purposes today. After adjusting for the number of players by position, we calculated a Positional Value Multiplier ("PVM") for each major position (FB, K, P not included). We then applied that multiplier to the above consensus rankings.

Here are the multiplier values we arrived at, in order from largest to smallest:


For the most part these make a lot of sense, based on what’s "common knowledge". QBs are, by far, the most important position. However, the relative rankings of WRs and RBs certainly surprised me, though due to the noise in the data, it’s best not to get hung up on the minute differences in values above. Instead, we can see there are some clear "tiers":

Tier 1 – QBs

Tier 2 – WR, CB, DE, RB, DT

Tier 3 – OT, LB, TE, S

Tier 4 – C, G

The only thing in those rankings that immediately draws my attention is the OT position in the 3rd tier. But that data is what it is, we can debate the reasons later.

Now that we have the PVM values, we can apply it to the prospect rankings.

The Results:


Some very interesting movement. The right-most column shows the effects of the positional modifier. The AG Rank column is the pre-adjustment consensus ranking.


- Dee Milliner jumps two places to become the top overall prospect.

- Chance Warmack, though he drops 3 spots, remains a top 5 prospect, damaging my belief that a G in the top 15 picks is a very poor decision.

- QBs, as expected, benefit the most. Geno Smith jumps 11 spots to become a top ten prospect, while Nassib and Barkley move into the middle of the first round.

- The biggest jump overall comes from Tyler Wilson (20 spots), who moves from the middle of the second round to the end of the first.

- Zach Ertz (TE) and Jonathan Cyprien (S) are hurt the most, falling out of the first round, and therefore off the chart above.

One last thing: I want to be perfectly clear about the value of this analysis. The idea here is that BPA is an overly simplistic and flawed method of drafting by its current definition. For example, while Geno Smith (19th consensus) may be a worse prospect than Kenny Vaccaro (9th consensus), with lower odds of success, the potential payoff is so much greater for Smith that he becomes a better choice (at least as shown here). Hitting on a QB offers a MUCH greater reward than hitting on a S (or really any other position), so it makes complete sense that QBs are perennially “over-drafted”.

In essence, what we are showing here is that they are not, in fact, “over-drafted”. Yes, they might have greater odds of failure, but that does not make them bad picks. Remember, you have to look at both Risk AND Reward, balancing the two. The above rankings is an effort to do that in a method as simple and transparent as possible.

Over the past few months, Brent has advanced the idea that the “consensus” forecast should carry a large degree of inertia within NFL front offices. Imagine the above rankings as equivalent to a total market stock index. For anyone going against the total market index, they must believe VERY STRONGLY that they have better information or better analysis than the rest of the market. It should function in much the same way in the NFL (and all professional sports leagues). The idea is NOT that teams should blindly follow the “market”, just that they should hold their own evaluations up to very high scrutiny before acting on them, especially when they largely conflict with available data.


The original work can be found here. Thanks for reading; this is a longer article, so please rec if you like it (otherwise people tend to glaze over longer posts). I am eager to hear your thoughts on both the methodology and the outcome. Does this additional data change your subjective belief about who the Eagles should take? Are there any angles with the data that you would like to see parceled out for future posts?

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