Experience-Adjusted College Production & Its Impact on Prospect Hit Rates (Fantasy Football)
With the NFL draft just a few days away, we are officially entering one of the most exciting times of the year: dynasty draft season. Because even after a disappointing season in which some of us did not win a #FootclanTitle, adding a new group of rookies to our rosters gives us some hope that we can turn things around and secure a dynasty championship. However, with a multitude of rookies joining the league, it can be daunting to have so many options to choose from when you are finally on the clock. After all, you might only have one first-round rookie pick to find the next Justin Jefferson or CeeDee Lamb. With that in mind, I wanted to explore the concept of Experience-Adjusted Production to highlight just how advantageous it can be in evaluating incoming rookies. In this article, we will discuss the following:
- What Is Experience-Adjusted Production?
- The Method to the Madness
- Skill Position Hit Rates
- 2020, 2021, and 2022 Prospects Review
For this article, we will be focusing on skill position players: Running Backs, Wide Receivers, and Tight Ends. Metrics used in this analysis are calculated per game and were pulled from @cfbfastR (via ESPN box scores).
What is Experience-Adjusted Production?
Simply put, Experience-Adjusted Production is a metric that highlights how productive a player was at a specific year (or years) in their collegiate career relative to other prospects. Let’s break this down further.
Experience: There are a variety of ways to conduct this analysis. But in this case, “experience” will refer to the number of years since a prospect graduated high school. For example, when I mention “Year 1,” that would refer to a player’s true freshman season (or their first year out of high school). This article will primarily highlight early-career production (Years 1 and 2) and how it affects a prospect’s likelihood of succeeding in the NFL.
Adjusted: To adjust player production, we will be referencing prospects who have recorded at least one productive fantasy season in their first three years in the NFL. Why should we focus on their first three NFL seasons? In short, I want to highlight players who returned immediate production for dynasty managers.
Naturally, the definition of a productive season will vary by position. For Running Backs and Wide Receivers, we will consider one top-24 PPR per-game season a success for fantasy purposes. For Tight Ends, since most dynasty leagues only require one in their starting lineups, we will use one TE1 season (top-12) in PPR per-game scoring as the threshold.
Production: To transform this into a production metric, we will take a player’s career average over a given time, use the career production average of a “successful” NFL prospect as a threshold, and then calculate the difference between those two numbers. To give you a broad example of an Experience-Adjusted Metric, let’s use Breece Hall’s Total Yards Per Team Play (TYPTP) in his first two seasons out of high school:
- 1.40 TYPTP as a true Freshman
- 2.12 TYPTP as a true Sophomore
- Hall’s Year 1 & 2 college average: 1.76
- Top-24 RB in the NFL: 1.21 TYPTP in Year 1 & 2 in college
- Experience-Adjusted TYPTP: +0.55 (1.76 – 1.21)
In this example, a running back who has had at least one top-24 season in their first three NFL campaigns averaged roughly 1.21 TYPTP in their first two collegiate years. And as we can see above, Hall passes that threshold by 0.55. This suggests that Hall should have a higher likelihood of returning top-24 production in the NFL due to his early dominance at Iowa State.
Method to the Madness
What’s the end goal of this analysis? By adjusting production based on those who have succeeded in the NFL, we should be able to reduce our pool of prospects and, ideally, see an improvement in our historical hit rates. To explore the validity of this theory, we will:
- Examine hit rates for all prospects drafted from 2013 to 2019
- Analyze how those hit rates change if we apply Experience-Adjusted Production
- Break down the hit rates by draft round (because draft capital matters)
Finally, as a bonus, we will also apply “early declare” status as a variable. We know that early-declare prospects have generally been more successful in the NFL. If we combine experience-adjusted production, draft capital, and declare status, how much will that improve our rookie hit rate? Let’s find out!
Running Back Hit Rates
When analyzing running back prospects, we see a strong correlation between early-career collegiate production and fantasy success at the next level, specifically in the first two years out of high school. Therefore, for this analysis, we will be using “Years 1 and 2” as the Experience Threshold. We will also leverage one of the more predictive running back metrics in Total Yards Per Team Play (TYPTP), which is calculated as Scrimmage Yards ÷ Total Offensive Plays.
At the running back position, we have seen 43 drafted prospects since 2013 produce at least one top-24 season in their first three years in the league. Those 43 prospects have averaged about 1.21 TYPTP in their first two years out of high school. If we apply this threshold, we arrive at the following top-24 hit rates.
Running Back Hit Rates (2013 to 2019)
+1 Top-24 Seasons in Years 1 – 3 in the NFL
*ED = Early Declare Prospect *EP = Early Producers As you can see above, the hit rate for day 1 running backs is already fairly high at 77.8%. In fact, of the 9 running backs drafted in the first round, the only two prospects who did not produce a top-24 season were Sony Michel and Rashaad Penny. However, when we focus on “early collegiate producers” who meet the TYPTP threshold I mentioned above, the hit rate improves to 83.3%! While this isn’t a drastic improvement, we do see the correlation to early production. Of the seven first-round running backs that produced a top-24 season in this timespan, 5 of them met the “early production” threshold above. And if we also apply an early-declare filter (prospects who entered the draft 3 years after high school), we see an extremely impressive hit rate of 100%. That isolates our pool of prospects to: We see a similar trend for running backs drafted in Rounds 2 to 3 with an 8.75 percentage point increase if we apply the production threshold. That hit rate improves even further to 75% if we only look at early-declare prospects – a group highlighted by Giovani Bernard, Dalvin Cook, and David Montgomery. Finally, perhaps the more interesting result is the 15 percentage point increase for Day 3 prospects. This tells me that isolating our pool of running backs to early producers can improve our chances of finding those “late-round dynasty sleepers” such as Aaron Jones and Chris Carson – both of whom passed the production threshold. Above are all the 2020 and 2021 prospects who averaged at least 1.21 Total Yards Per Team Play in their first two years out of high school. A couple of notes: Lastly, here are the 2022 prospects that meet that same early production threshold. My analysis for wide receivers will be very similar to the one above, except I will be using the metric Receiving Yards per Team Pass Attempt (RYPTPA), which is calculated as Receiving Yards ÷ Team Pass Attempt. Since 2013, we have seen 33 wide receiver prospects hit the top-24 threshold at least once early on in their NFL career. These prospects averaged 1.76 RYPTPA in their first two years out of high school, which will be our threshold for this analysis. Draft Day Early Producers *ED = Early Declare Prospect *EP = Early Producers First off, we see that wide receiver hit rates are significantly lower compared to running backs. However, applying an early-production threshold seems to have a more significant impact, improving the hit rate by nearly 36 percentage points for first-round prospects. In fact, of the 11 first-round prospects that produced one top-24 season, 8 of them met the RYPTPA threshold I outlined above. Furthermore, all 8 of them declared early. Who are those wide receivers? It is also worth noting that one of the “early producers” that never achieved a top-24 season is the infamous Corey Davis, who happens to destroy every comp list for every wide receiver. Applying an early-declare filter removes Davis from the sample size, and in turn, improves our hit rate. In addition, there is a similar trend for day 2 WRs. Applying both thresholds leaves us with a productive group of prospects headlined by Davante Adams, A.J. Brown, and Allen Robinson. And while the hit rate is only at 54.55%, one of the misses is Robert Woods who eventually produced multiple top-24 seasons later in his career. Lastly, the odds of finding the next Stefon Diggs are clearly very low. However, Diggs did pass both the early-declare and early production thresholds. And as we can see above, that gives us the best hit rate for Day 3 wide receivers. This list includes all drafted prospects from 2020 and 2021 who met the early-career production threshold of 1.76 RYPTPA. A few notes: Finally, let’s take a look at all 2022 WR prospects who hit our production threshold: Analyzing Tight Ends is trickier than the other positions. While producing early is certainly a plus, the correlation between Year 1 collegiate production and a prospect’s likelihood of succeeding in the NFL is fairly low. Where we see the strongest correlation is in years 2 and 3. Therefore, we will use that as our experience threshold, along with the metric Receiving Yards Per Team Pass Attempt (RYPTPA). As mentioned earlier, we will take look at all TE prospects drafted since 2013 who achieved at least one top-12 season. In years 2 and 3 out of high school, those prospects averaged about 1.19 RYPTPA, which becomes our experience-adjusted threshold for the analysis below. *ED = Early Declare Prospect Surprisingly, the first-round hit rates are very high for Tight Ends, with 6 of the 8 players in the sample size producing at least one top-12 season to start their careers. If we filter on players who exceeded 1.19 RYPTPA in years 2 and 3, the hit rate improves to 85.71% with David Njoku being the only prospect who did not achieve a TE1 season. Interestingly, we do not see a similar trend for day 2 prospects even if we apply our production threshold, which is heavily driven by the multitude of outliers in this range. Some of those players include Travis Kelce, Jordan Reed, and Dallas Goedert – a group of older prospects who did not produce until later in their collegiate careers. However, we do see a sizable improvement in our hit rate if we include the early-declare filter, improving to 50% for day 2 prospects. Lastly, banking on a day 3 TE will likely leave you disappointed with George Kittle and Will Dissly being the only prospects in this sample size (out of 52) to produce a top-12 season. Listed above are all the TE prospects who hit the 1.19 RYPTPA threshold and were drafted on days 1 and 2 (because day 3 TEs are essentially irrelevant): Finally, above are all eligible 2022 TEs who hit the production threshold we outlined earlier: While this was a longer article, hopefully you found this helpful as you approach your upcoming rookie drafts. Keep in mind that experience-adjusted production is only one piece of the puzzle. Applying multiple layers to our analysis (career production, draft capital, athleticism, etc.) only improves our rookie evaluations. In short, here are my key takeaways: If you have any questions, reach out on Twitter @FF_MarvinE.
Draft Day
Total
Early Producers
ED + EP
1
77.78%
83.33%
100.00%
2
60.00%
68.75%
75.00%
3
12.37%
27.27%
25.00%
Running Back Prospect Review: 2020 – 2022
Wide Receiver Hit Rates
Wide Receiver Hit Rates (2013 to 2019)
+1 Top-24 Seasons in Years 1 – 3 in the NFL
Total
ED + EP
1
44.00%
80.00%
88.89%
2
29.51%
38.89%
54.55%
3
3.28%
6.67%
12.50%
Wide Receiver Prospect Review: 2020 – 2022
Tight End Hit Rates
Tight End Hit Rates (2013 – 2019)
+1 Top-12 Seasons in Years 1-3 in the NFL
Draft Day
Total
Early Producers (Years 2 – 3)
ED + EP
1
75.00%
85.71%
75.00%
2
32.26%
31.25%
50.00%
3
3.85%
0.00%
0.00%
*EP = Early Producers (Years 2 – 3)Tight End Prospect Review: 2020 – 2022
Major Takeaways