Last season, I introduced the concept of adjusting college productivity based on the level of competition a player faced. In my article, Team Adjusted Dominator and the College Productivity Score, I implemented two simple methods to illustrate the value of this process. Yardage earned in the SEC is worth more than yardage earned in the Pac-12, so player stats were modified according to conference play. This gave a significant boost to the correlative value of yards earned in college and their relationship to NFL productivity. I also modified Dominator Rating according to a team's end-of-season rank based on the same premise: market share earned on a good team is worth more than market share earned on a bad team.
There are two layers of competition under evaluation:
Internal Touch Competition - The quality of the teammates that the WR had to beat out for touches
External Defensive Competition - The quality of the defenses the WR played against
This year, I've added to the fabric of both layers. The concept is no longer a prototype.
The Teammate Score
Teammate Score evaluates the other wide receivers on a prospect's team. Previously, this was accomplished using end-of-season rank for the entire team. Top teams typically carry top recruits and high-end talent. The level of competition a player faces in an Alabama or Ohio State practice is more than what any MAC football player will see before they reach the NFL. Team quality often correlates to NFL prospect quality. This season, I've upgraded the differentiation of this process by implementing College Football Reference's Simple Rating System (SRS). The table below displays the Top 20 college teams in the SRS since 2003.
In addition to the SRS, we can get more specific by evaluating the specific members of each team's wide receiver corps. The Teammate Score gets particularly interesting when valuing players from these big programs who don't breakout as early as they would at a small school. This is where the added value shows up.
The 2017-2020 Alabama WR Corps provides us with the most extreme example of cutthroat competition reducing collegiate productivity. Alabama's 2017-2018 National Championship roster was led by junior WR Calvin Ridley and supported by a trio of young freshmen talents: Henry Ruggs, Jerry Jeudy, and overtime hero, Devonta Smith.
Calvin Ridley (3), Devonta Smith (6), and Jerry Jeudy (4) celebrate during the 2017-2018 National Championship game.
Many great college players fail to become anything at the next level, so I use Draft Capital to measure the value of each of the wide receivers in the locker room. NFL investment is a perfectly good indicator of the NFL's valuation of a college prospect, so that number will determine the value of the players in the Teammate Score model.
To determine how much each draft pick is worth, I use a regression comparing average fantasy points to draft pick and apply that equation across each player in the dataset.
Calvin Ridley was the 26th pick of the 2018 draft. On average, the 26th pick scores 9.4 fantasy PPG in the NFL, so that Pick Value is assigned to Ridley. Likewise, Jerry Jeudy was the 15th pick, so he scores a Pick Value of 10.2, and so on.
The Pick Values of all drafted teammates 2 years prior and 1 year afterward are added to create the Teammate Score. A junior beating a freshman for targets doesn't prove that the junior is anything special. But a freshman earning targets with other NFL caliber talent on his college roster is a significant event.
During the 2017-2018 Alabama Championship season, 22-year-old junior, Calvin Ridley commanded a 26% market share. 18-year-old freshman, Henry Ruggs, took 14% while fellow freshmen Jerry Jeudy and Devonta Smith each took 8%. The value of those freshmen market shares is not obvious when looking at raw data, but when we consider that all four of those receivers ended up being first-round NFL picks, the value of that 8% or 14% should be recognized. The Teammate Score gives us a way to modify those market share values.
The table above displays the depth of talent at Alabama: FIVE 1st round picks in a 3-year window and possibly a sixth player to be added to that list next season. We can see the Teammate Score at work here. The lone factor in Calvin Ridley's Teammate Score is Ardarius Stewart (2017 3rd round pick), so Ridley scores a 6.2. He does not get points for earning volume over freshmen. Jeudy and Ruggs each played with 4 other first-round receivers (Ridley - two years prior, Smith & Waddle one year after) so their scores hit 41.5 and 41.2 respectively. Devonta Smith carries the largest benefit from the Teammate Score having played with all 4 Bama studs AND John Metchie whose status as a 2022 late first/early second-round pick earns him a Pick Value of 8 points.
A list of the top Teammate Scores shows that the score provides texture to the SRS and identifies which players played with the most talent.
Adding the power of Team Adjustment to a stat like College Dominator (or Receiving Market Share) amplifies its value. College Dominator alone possesses an R^2 correlation value of 0.128 (left chart). When Teammate Score and SRS are integrated, the value of that data rises to 0.200 (right chart).
This correlative value of Team Adjusted Dominator is just as good as the well-respected Age Adjusted Dominator (R^2 = 0.194). But the real value starts to hit when combining both Age and Team Adjustment together. This elevates the value of Dominator Rating all the way up to an R^2 of 0.247 (right chart below).
The top players of the combined Team & Age Adjusted Dominator:
Using the Teammate Score to adjust Dominator Rating is just my first instinct. Hopefully others will be able to test it with other metrics and implement it into their own models. Please feel free to copy/download the Teammate Score data for your own use.
Production Model and the 2021 Class
My final Production Model is the combination of Team & Age Adjusted Market Share with Conference Adjusted College Average PPR Points - the blend of Internal AND External Productivity Evaluation.
The Top 11 Production Scores in the class:
DeVonta Smith (98th percentile)
Ja'Marr Chase (97th percentile)
Elijah Moore (90th percentile)
Rashod Bateman (86th percentile)
Seth Williams (85th percentile)
Jaylen Waddle (84th percentile)
Amon-Ra St Brown (81st percentile)
Rondale Moore (80th percentile)
Tutu Atwell (80th percentile)
Dyami Brown (75th percentile)
Anthony Schwartz (75th percentile)
Other Day 1 & 2 Draft Picks:
Terrace Marshall (69th percentile)
Nico Collins (51st percentile)
Amari Rodgers (51st percentile)
Kadarius Toney (51st percentile)
Josh Palmer (35th percentile)
D'Wayne Eskridge (19th percentile)
Adding my Athleticism Score (R^2 of 0.16) to the Production Score (R^2 of 0.27) brings my Pre-Draft Model correlation to the same level as the NFL (draft pick R^2 is 0.36). The resulting Post-Draft Model (incorporating Athleticism, College Production, and Draft Capital) boasts a final R^2 of 0.438.