College First Downs per Route Run
It’s prospecting season as we pour through the statistics and film for the incoming rookie classes across the skill positions. And much like the original prospectors of the mid-19th century, we approach prospecting by attempting to arm ourselves with as much information as possible in the hopes that we can strike fantasy gold. But also much like the original 49ers, success is far from guaranteed and our pans will only produce sand and rocks more often than not.
In my first Beneath the Surface article of the 2024 offseason, I will be looking at the incoming WR rookie class and doing something for the first time in this series: Diving deep into one single metric. If you have read much of my previous work, you know my analytics view is that it takes the form of a complicated puzzle, with many pieces needing to be fit together to see a clearer picture. A picture of both what has transpired and my best effort to see as much of the future picture as possible. Focusing on only one metric, even a metric with a relatively strong signal between college and NFL football, can not only lead to an incomplete estimation of the probability of what’s to come but also creates a pathway to potential confirmation bias and not always intentionally. For example, one could cherry-pick through some common advanced metrics such as yards per route run (YPRR) or targets per route run (TPRR) to find the statistic at which their “my-guy” excelled in college, and tunnel vision their way to a stance that is less likely to come to fruition. And this goes both ways. You can also hyper-focus on one statistic a player you are fading struggled with to reinforce your fade.
However, there is a time and place to focus on single metrics. Which is what I will be doing in this article. This isn’t about any individual player takes. Curiosity drives a lot of my work and I wanted to drill down on a metric that I have not seen a deep dive on as of yet: First Downs Per Route Run (1DRR) at the college level. Specifically, I wanted to see if a college WR’s 1DRR has historically been predictive of fantasy success at the NFL level. Remember that, regardless of the indicated answer, I would never stop at one metric in my analysis of any player or position group. However, it is helpful to know which individual statistics in college have a stronger correlation with scoring fantasy points in the NFL. For instance, college receiving yards per team pass attempt (RYTPA), especially a player’s best season RYTPA, has been shown by analysts like JJ Zachariason to have relatively strong signal compared to others. This is why I use RYTPA as one of the metrics when I am analyzing incoming rookie WRs. I wanted to shed some light on whether the same can be said for 1DRR.
First Downs Per Route Run
As I presume to be the case at least some of the time with other analysts, this idea was inspired by someone else’s work. Ryan Heath recently wrote an article for Fantasy Points in which he looked at 1DRR at the NFL level.
Yards Per Route Run is a great stat.
I found a better, more predictive version of it.
This is my deep dive into First Downs per Route Run (1D/RR) – including how it can tell us when YPRR is lying.
A very exciting new addition to @FantasyPtsData!https://t.co/Jz498h0wbD
— Ryan Heath (@RyanJ_Heath) March 18, 2024
I encourage you to read Ryan’s article as it rather convincingly adds 1DRR to the metric list for players already in the NFL. Excitedly, and because I had already compiled the raw data, I joined Ryan’s conversation on X by posting the incoming WR prospects’ 1DRR.
Fantastic deep dive by @RyanJ_Heath on first downs per route run, you should read it multiple times like I did😂
Here are the 2024 WR prospects’ college 1DRR and best season 1DRR (player pool: WRs invited to the NFL Combine).
*data from @pahowdy and @PFF https://t.co/WAtWWTurU7 pic.twitter.com/zaOUyvBt2B— Scott Rinear (@MunderDifflinFF) March 19, 2024
This then spawned the question I probably should have asked myself before I posted my pretty Excel table: Is college WR first down data predictive at the next level? I am a human being. Sometimes I “post first and ask questions later,” and so here we are. Starting that same day, I dove in, compiling historical 1DRR data as far back as I could go with available college statistics. I know there are quicker and likely more efficient statistical methods to arrive at an answer to this question, but I enjoy compiling the raw data. The osmosis between by brain and external topics struggled mightily in college and still does with many subjects today, but not with football statistics. The more I see while down in the weeds (e.g. the 1DRR data for every 6th and 7th round WR pick since 2018), the larger my knowledge foundation grows. So here we go, let’s find out if college 1DRR correlates with what we all want at the end of the day: Fantasy points.
College 1DRR Historical View – Parameters
I started this research by defining the two key pieces of the study:
- I needed to select the specific 1DRR college metrics to use. I chose to look at two different 1DRR data sets:
- College career 1DRR
- Best season 1DRR
I then selected further by only including WRs with a college career 1DRR above 8%. This threshold is arbitrary but provides a nice sample size. I then selected further by only including those who had a college career 1DRR above 8%.
- Then I needed to choose a range of seasons and rookie WR classes to focus on. The NFL fantasy points input I chose to use is the average PPG (PPR) of a WR’s best two fantasy seasons over their first three years in the league, or “BF2.” This automatically caps the range at the 2021 rookie class, as that was the most recent incoming WR class that has played (or had the opportunity to play) three seasons. The other end of my range was dictated by the available data. I could only find college “routes run” data going back to 2015, so the starting point became the 2018 WR class, as the 1DRR data (especially college career 1DRR) is incomplete if you go back further. The reason I chose BF2 as the fantasy points variable is because it has been shown that, on average, a WR’s fantasy success (or lack thereof) over their first three seasons is indicative of the seasons that follow. The probability of a WR, who let’s say has averaged 4 fantasy PPG over their first three seasons, “hitting” or significantly improving after year three is low.
With these two parameters established, I arrived at my player pool and sample size. Between 2018 and 2021, 95 WRs were drafted into the NFL with a college career 1DRR above 8%. With the BF2 fantasy PPG charted for these 95 WRs, simple scatter plot graphs are an effective way to look at the relationship between college 1DRR and NFL fantasy points.
The data used in this study came from a combination of the following sources:
- Pro Football Focus (PFF)
- College database provided by Peter Howard (@pahowdy on X)
- College database provided by David Wright (@ff_spaceman on X)
- Various college/university websites
College 1DRR Historical View – Results
This first graph shows college career 1DRR and the corresponding BF2 fantasy PPG for each WR.
Although there is a slightly positive trend line, this graph lives up to its name. These data points are largely “scattered,” indicating there is not a strong correlation between college career 1DRR and fantasy scoring in the NFL.
Looking only at the career averages could be skewing things as it is not uncommon for successful NFL WRs to have had only one or two good college seasons. Here is the same player pool, but using each WR’s “best season” 1DRR.
You can see the trendline is slightly flatter, indicating that “Best Season” 1DRR is less predictive than looking at college career 1DRR. Breaking down some of the numbers also conveys the seeming randomness (as opposed to predictability) of college 1DRR.
Last year I looked at the average PPG (PPR) of the WR1, WR2, WR3, through the WR50 between 2012 and 2022. I added in 2023 data this offseason. The average PPG threshold for a WR1 (Top 12) is 15.9 PPG, meaning over the last 12 years, the average PPG for the WR12 is 15.9. The average PPG threshold for a WR2 (Top 24) is 13.5 PPG, and the average PPG threshold for a WR3 (Top 36) is 11.4 PPG.
We can simplify by splitting the player pool into two subsets. WRs with a BF2 above 10 PPG and WRs with a BF2 below 10 PPG. Of the 95 WRs in the player pool, 28 put up a BF2 above 10 PPG. The average college career 1DRR for that group was 10.7%. Sixty-seven WRs had a BF2 below 10 PPG. The average college career 1DRR for that group was 10.2%. So, while this doesn’t get us to the technical WR3 threshold, it is close enough to get the point across: WRs showing early fantasy success in the NFL, on average, were not putting up significantly higher college 1DRR numbers than WRs who didn’t.
Even just seeing some of the names at the top of the college 1DRR leaderboards is telling. From 2018 to 2021, here are the Top 10 WRs in college career 1DRR, including their BF2 PPG:
Here is the Top 10 in “Best Season” 1DRR:
Both show a mixed bag of WR talent.
College 1DRR Historical View – Conclusion
In the fantasy football analytics version of prospecting, one of the goals with all of the puzzle piecing is to hopefully arrive at something that can provide value beyond draft capital. A scatter plot with draft capital and BF2 PPG would be much more clustered in a positive upward trend. And if you choose to just stop at draft capital (and landing spot), I have no issue with that. There is plenty of data showing the hit rates for WRs and RBs for Day 1, 2, and 3 players. But I choose to look deeper than that. But we can use draft capital in this research to throw a little more dirt on college 1DRR, on its own, as a predictive metric. Using the same subset as above:
- Average Draft Round for WRs with a BF2 above 10 PPG: 2.2
- Average Draft Round for WRs with a BF2 below 10 PPG: 4.3
And if you just look at the WRs with a BF2 above 15 PPG (Justin Jefferson, Amon-Ra St. Brown, Ja’Marr Chase, AJ Brown, Calving Ridley, CeeDee Lamb, Deebo Samuel, Tee Higgins, and Jaylen Waddle), the average Draft Round is 1.7. This is not surprising. However, if you look through the 1DRR lense:
- Average Draft Round for WRs with a “Best Season” 1DRR above 13%: 3.7
- Average Draft Round for WRs with a “Best Season” 1DRR below 13%: 3.6
And those studly studs with a BF2 above 15 PPG?
- Average “Best Season” 1DRR for WRs with BF2 above 15 PPG: 13.1%
- Average “Best Season” 1DRR for the entire 95-WR player pool: 12.8%
All this being said, speaking qualitatively, the track record for WRs at the bottom of the college 1DRR has not been good. Remember I chose to set a lower threshold of 8% for the 1DRR data. So, while I don’t have the same numbers to back this up, the eye test for the players in this group makes me fairly confident that there is a corner of predictiveness in the downward direction of college 1DRR. Here are the WRs, from the 2018 to the 2023 rookie classes, who had college career 1DRR below 8%.
In analytical terms, yucky (with Metcalf and McLaurin as non-yucky outliers).
Thanks for reading! If you have any questions about the data used in this article or about fantasy football in general, feel free to hit me up on X. Since this article included very little information about specific players, I will leave you with the data tables, showing each WR class comprising the 95-WR player pool, including each player’s Draft Round, college career 1DRR, Best Season 1DRR, and BF2 fantasy PPG. Each table is sorted by BF2 PPG.
