​How Much Does NFL Draft Position Affect IDP Fantasy Value?

With all the dust of the NFL Draft, NFL Combine, and pro days now settled, we have a much fuller picture of the newest members of the league and what they could do for us on the virtual gridiron.

For many folks in the NFL, Draft Weekend is a milestone -- the end result of a lot of effort, time, and emotion. For me, this event is more so another wellspring of data that we get to add to our evaluations of players for fantasy football purposes; for them, it’s a finish line, but for many fantasy prospectors, it’s a springboard.

One now-common concept in fantasy football came out of these post-draft data influxes. Fantasy evaluators have shown repeatedly that offensive players who get selected higher in the NFL Draft are often better bets than their peers who go later to pan out as fantasy players. Whether better talent is able to be acquired at higher picks, or the greater draft capital spent encourages a sunk-cost fallacy, or teams simply assume that a former early-round pick was an early-round pick for a reason, on offense, we know that players picked high by the league should largely be picked high in your leagues.

But what about for defense? Does the same maxim hold true for Individual Defensive Players (IDP)? How much is a high NFL Draft selection correlated to future fantasy value for a defensive player?

Methodology

Since most NFL players’ careers are relatively short -- on average, three years or fewer depending on the position played -- I decided that the best way to study fantasy value for an IDP player was to look at their first three years of production. Any more than that and we start getting noise in the data due to careers being cut short due to injury and other unpredictable situations. You can think of this flukiness spectrum with former San Francisco 49ers edge rusher Aldon Smith on one end (early success then flame-out) and someone like former Pittsburgh Steelers edge rusher James Harrison (early bust then late bloom) on the other. We’re trying to find the average players in the middle of this spectrum.

To measure fantasy potential in the pros, I identified three different ways to measure success that I wanted to examine: playing time (games and snaps), production rates (to control for playing time), and fantasy production (a composite of other production). We know that if a player is on the field more, that’s better for their chances of scoring fantasy points; in addition, if a player has high production in individual stats, high fantasy scoring is very likely. The reason I chose production rates (i.e., sacks per pass rush snap) is to eliminate playing time as a factor in production; since we’re already measuring it on its own, we don’t need it also baked into another stat and muddying that info.

Finally, I simply ran Pearson’s R correlations between each of these factors as well as both draft round and overall draft pick. Unsurprisingly, overall draft pick had much higher correlations, so we are using that as the “denominator” for this study. In order to clearly outline the indicator of draft position, I also split players by position group (cornerback, defensive line, edge rusher, off-ball linebacker, and safety). Within that, however, I also broke down positions by pick ranges (1-30, 31-60, 61-100, 101-150, 151-250+) to control for any changes in draft approaches by teams within certain phases of the selection process. Finally, I removed all players who never played a single game in the NFL in an effort to help cut down on the noise and find stronger correlative signals.

Playing Time

The simplest way to measure player success for an NFL prospect is to answer whether or not they earned playing time. This is a metric that can be muddied for an individual -- if they get drafted to the same position as one of the team’s stars, if they are less “pro-ready” and more “developmental prospect,” etc. -- but for a large group of players, the solo quirks will largely be washed out.

The four ways I broke down playing time across the first three years were: total games played, total snaps played, snaps per game, and snaps per season. The table below shows the relationship for each IDP position group between overall draft slot and each of these playing time metrics.

This, as the kids would say, is a bingo. In football prospect analysis, it’s vanishingly difficult to find a correlation coefficient stronger than ±0.30; here we have every single one beyond ±0.40 and all but two north of ±0.50.

When we look at positions broken down by draft ranges, games played remains easily the weakest correlation. This is mainly due to the limitations of the stat and that a first-round pick could see 30 snaps per game as a starter but a seventh-rounder could see just a few snaps each week and still play a full season as a special-teamer. That clutters things for our purposes. Total snaps played is a stronger indicator than games, and snaps per season is frequently slightly stronger than that -- likely due to accounting for freak injuries or redshirt rookie seasons.

In addition, the second- and third-round ranges (31-60 and 61-100) were significantly weaker in terms of the relationship between playing time and overall draft selection than the first round or even the late-round ranges. This seems to indicate that NFL teams are more open to taking upside players who may not see the field early in their careers on Day 2 of the NFL Draft. The only exceptions to this are at the safety and cornerback positions, which makes sense given the ever-increasing importance of pass defenders and sub-packages in the modern game.

For playing time, the data is clear: the higher a player is drafted, the better the chances they get on the field early. For example, that’s a major reason why I’m going to value new Jacksonville Jaguars linebacker Devin Lloyd (27th overall) and even Cleveland Browns edge rusher Alex Wright (78th) more than Philadelphia Eagles linebacker Nakobe Dean (83rd) and Green Bay Packers edge rusher Kingsley Enagbare (179th) in IDP rookie drafts.

Production Rates

If finding opportunity is the most basic factor in locating fantasy scoring, production rates are the premiums that separate stars from simple stat compilers. The players who can rack up tackles, sacks, or turnovers at profane rates can take the same snap count as their peers and far outperform them in the fantasy box score.

To help locate these premier producers, I identified six rates to track that factor into most fantasy scoring systems: tackle opportunity, tackle success, pressure, sack conversion, defeat, and passes defended. To quickly define these metrics:

• - Tackle opportunity: the percent of snaps where the player had a chance to make a tackle (essentially, being around the ballcarrier), calculated as tackles, assists, and missed tackles divided by total snaps
• - Tackle success: How frequently the player converts a tackle chance, calculated as total tackles divided by tackle opportunities
• - Pressure: How often are they getting to the quarterback, calculated as total pressures divided by pass-rush snaps
• - Sack conversion: How often pressures are converted into sacks, calculated by sacks divided by pressures
• - Defeat: How often they stop the ballcarrier behind the line of scrimmage, calculated as sacks and tackles for a loss divided by total tackles
• - Passes defended: How often the player disrupts the passing game, calculated as passes defended, batted passes, and interceptions divided by coverage snaps

The table below shows the correlation coefficients for these metrics with overall draft position.

There are definitely not as many strong relationships here. Tackle opportunity rate has basically nothing to latch onto, and tackle success rate appears meaningful for only cornerbacks and edge rushers. Similarly, defeat rate seems to be correlated to just draft slot for edge defenders. In addition, the production rates for safeties seem to have basically no overall correlation to draft results.

Though it seems odd on the surface, linebackers and defensive linemen seem to have the highest correlation with passes defended rate. This is likely due to higher athleticism at those positions at the top of the draft, whereas bigger and less agile defenders are more readily available later on.

For cornerbacks, defensive linemen, and edge rushers, there are interesting coefficients for pressure rate, suggesting that high draft picks tend to come with better pass-rush potential (which makes sense). Add linebacker into the mix, and each position outside of safety has a meaningful mark in the sack conversion rate column.

Even when we look at draft ranges to bucket these positions with like-rated prospects, there isn’t much we can take away outside of pass-rushing prowess. What this means is that it’s incredibly hard to say that high draft picks at any specific position do any one thing better than their later-drafted peers. The draft capital spent on them isn’t to necessarily attain a singular higher-end skill; instead, teams are looking fairly holistically at each position group and each player in order to determine their valuation.

Fantasy Scoring

Finally, fantasy scoring is the reason we are here. IDP is a fantasy football format after all, so we should get down to the crux of the question in this piece. That is -- how does NFL draft position affect IDP fantasy success?

The three ways I’m parsing fantasy scoring for these purposes are total fantasy points (again, over the first three career seasons), fantasy points per game, and fantasy points per snap. I’m using a three-to-one balanced IDP scoring system for this purpose, which means big plays like sacks, tackles for a loss, and interceptions are all scored at three points, while tackles are scored at one point. The table below shows the correlation between these three fantasy scoring metrics and overall NFL draft position.

It’s no coincidence that strong correlations between draft slot and playing time should also lead to strong correlations between draft slot and fantasy points. Just like with offensive fantasy football, playing time is the strongest indicator of potential fantasy success; the more you’re on the field, the better your chances of making an impact.

What is surprising here is how much stronger total fantasy points and fantasy points per game are over fantasy points per snap. Total fantasy points does have some noise due to intrinsically having playing time baked into it; with a strong correlation between draft position and playing time, therefore, it makes sense that total fantasy points would also carry a strong correlation to draft position. When controlling for snap count, however, there is basically nothing there. It seems reasonable to assume that players available earlier in the draft would also produce higher-quality results on a moment-to-moment basis, but either the difference isn’t that drastic between players in that granular of a timeframe or perhaps we’re statistically slicing the data too thin here.

Regardless, if we want to control for playing time and still have strong correlations, fantasy points per game is well and fully into the “statistically significant” zone for our purposes. The benefits of this seem to be controlling for some of the fluke injuries or absences while not reducing things to such a microscopic view that the data can’t capture the change.

Conclusion

Just like with offensive fantasy football prospects, an earlier draft pick means more confidence from NFL teams that a defensive player will end up producing. By looking at correlation coefficients of draft position and a variety of metrics, we can see this supposition confirmed repeatedly -- though the relationship tends to disappear when we slice player profiles (i.e., narrowing down to individual stats, basing fantasy production on snap count) too narrowly and start losing the full picture of the players.

There’s no guarantee that an early-drafted player will outproduce a middle- or later-round selection, but these kinds of studies help us to see that it is more likely that they will. We can then take that into account during our rookie drafts, and structure our board more sensibly, maybe making exceptions for only players with immense talent who fell because of off-field or medical issues (for instance, the aforementioned Nakobe Dean). Even then, we should be careful of convincing ourselves that NFL decision-makers got something so wrong that we ­­-- amateur and semi-pro talent evaluators at best -- should be betting against them.

Even in terms of “bust rate” -- the percentage of players who never set foot on an NFL field -- there hasn’t been one first-round pick since 2015 to totally flame out, and few second-rounders have either.

NFL Draft results are not the be-all, end-all of prospecting, but they are a very efficient and indicative tool that you should use in both your offensive and IDP format rookie drafts. I'm not saying your rookie draft should be identical to the NFL's; instead, I'm asking you to be careful about the Channing Tindalls and Chad Mumas of the IDP world when there could be a Quay Walker right in front of you.