There are three things that go into my Analytics Top 300 NFL Draft models -- projected draft capital (essentially a film grade), athleticism, and production. I already have posted my Adjusted SPARQ athleticism scores here, so now it’s time to address how productive these defensive players are. To create my “Adjusted Production” score, I analyzed which college stats have been the most predictive for NFL success, and then adjusted those for age (being young is good) and team strength (playing on a good team is good). You’ll see the historical percentiles for the 2020 defensive draft class below. My database goes back to 2005 and is filled with drafted players from FBS colleges.
Interior Defensive Line
The key stats for the position are tackles for loss and solo tackles. Please do not use sacks, assisted tackles, total tackles, or pass deflections as evidence for or against a player. TFLs and solos are the ones worth citing.
How to read: “Derrick Brown had an 87th percentile Adjusted Production score.”
|
Player |
College |
Adjusted Production |
|
Baylor |
0.98 |
|
|
Utah |
0.88 |
|
|
Auburn |
0.87 |
|
|
LSU |
0.87 |
|
|
Texas Christian |
0.75 |
|
|
Missouri |
0.64 |
|
|
Texas A&M |
0.63 |
|
|
Nebraska |
0.62 |
|
|
NC State |
0.61 |
|
|
Carlos Davis |
Nebraska |
0.44 |
|
Michigan State |
0.42 |
|
|
Texas |
0.40 |
|
|
Broderick Washington |
Texas Tech |
0.34 |
|
Ohio State |
0.34 |
|
|
Arkansas |
0.31 |
|
|
Ole Miss |
0.30 |
|
|
South Carolina |
0.29 |
|
|
Utah |
0.27 |
|
|
Oklahoma |
0.25 |
|
|
Alabama |
0.21 |
|
|
Penn State |
0.18 |
|
|
Nebraska |
0.05 |
|
|
Ole Miss |
0.02 |
Edge Rushers
The key stats for the position are combined tackles and tackles for loss, not sacks. If a prospect has a ton of sacks, then awesome, but it’s totally fine if a prospect has a ton of TFLs and forgettable sack totals. Pass deflections also hold some predictive value.
How to read: “Chase Young had a 99th percentile Adjusted Production score.”
|
Prospect |
College |
Adjusted Production |
|
Ohio State |
0.99 |
|
|
LSU |
0.95 |
|
|
Iowa |
0.89 |
|
|
Boise State |
0.89 |
|
|
Alabama |
0.88 |
|
|
Jonathan Greenard |
Florida |
0.86 |
|
Auburn |
0.84 |
|
|
Alabama |
0.84 |
|
|
Utah |
0.82 |
|
|
Charlotte |
0.80 |
|
|
Michigan State |
0.72 |
|
|
Michigan |
0.72 |
|
|
Syracuse |
0.72 |
|
|
Wisconsin |
0.68 |
|
|
Penn State |
0.61 |
|
|
Minnesota |
0.60 |
|
|
Miami (FL) |
0.53 |
|
|
Notre Dame |
0.46 |
|
|
Tulsa |
0.42 |
|
|
Syracuse |
0.36 |
|
|
Mississippi State |
0.27 |
|
|
South Carolina |
0.23 |
|
|
Notre Dame |
0.21 |
|
|
Tennessee |
0.19 |
|
|
Stanford |
0.19 |
|
|
North Texas |
0.17 |
|
|
Miami (FL) |
0.15 |
|
|
North Carolina |
0.13 |
|
|
Tipa Galeai |
Utah State |
0.11 |
|
Florida |
0.11 |
|
|
Auburn |
0.08 |
|
|
North Dakota State |
0.07 |
|
|
North Carolina State |
0.03 |
|
|
Ole Miss |
0.00 |
Linebackers
The key stats for the position are total tackles and solo tackles. Pretty simple.
How to read: “Isaiah Simmons had a 98th percentile Adjusted Production score.”
|
Prospect |
College |
Adjusted Production |
|
California |
0.99 |
|
|
Clemson |
0.98 |
|
|
Oklahoma |
0.97 |
|
|
LSU |
0.96 |
|
|
LSU |
0.95 |
|
|
Utah State |
0.86 |
|
|
Texas Tech |
0.86 |
|
|
Ohio State |
0.85 |
|
|
Miami |
0.83 |
|
|
Michigan State |
0.78 |
|
|
Colorado |
0.74 |
|
|
Michael Divinity Jr. |
LSU |
0.71 |
|
Appalachian State |
0.69 |
|
|
Baylor |
0.67 |
|
|
Miami (FL) |
0.64 |
|
|
Minnesota |
0.63 |
|
|
Michigan |
0.62 |
|
|
Missouri |
0.61 |
|
|
Cameron Brown |
Penn State |
0.53 |
|
Tennessee |
0.46 |
|
|
Wake Forest |
0.42 |
|
|
Mississippi State |
0.42 |
|
|
Virginia |
0.42 |
|
|
Oregon |
0.40 |
|
|
Arkansas |
0.40 |
|
|
Purdue |
0.32 |
|
|
Utah |
0.27 |
|
|
Logan Wilson |
Wyoming |
0.24 |
|
Montana |
0.23 |
|
|
Fresno State |
0.17 |
|
|
Temple |
0.16 |
|
|
Kansas |
0.13 |
|
|
Temple |
0.11 |
Safeties
The key stats for the position are… none! Tackles, TFLs, interceptions, and pass deflections all have minimal predictive power, so I’m paying more attention to age and team strength relative to other positions.
How to read: “Xavier McKinney had a 100th percentile Adjusted Production score.”
|
Prospect |
College |
Adjusted Production |
|
Alabama |
1.00 |
|
|
Minnesota |
0.95 |
|
|
LSU |
0.92 |
|
|
Utah |
0.90 |
|
|
Utah |
0.87 |
|
|
Iowa |
0.87 |
|
|
Notre Dame |
0.73 |
|
|
Arkansas |
0.72 |
|
|
BranDon Jones |
Texas |
0.68 |
|
Clemson |
0.62 |
|
|
Ohio State |
0.61 |
|
|
Michigan |
0.57 |
|
|
Notre Dame |
0.56 |
|
|
Chris Miller |
Baylor |
0.52 |
|
Auburn |
0.50 |
|
|
Antoine Brooks |
Maryland |
0.43 |
|
Washington |
0.41 |
|
|
Southern Illinois |
0.37 |
|
|
Georgia |
0.30 |
|
|
Southern Methodist |
0.28 |
|
|
Baylor |
0.24 |
|
|
UCF |
0.21 |
|
|
California |
0.15 |
|
|
Clemson |
0.12 |
|
|
Louisiana Tech |
0.06 |
|
|
California |
0.03 |
|
|
Lenoir-Rhyne |
0.01 |
Corners
The key stats for the position are… none! Tackles don’t matter. Neither do interceptions. I only added pass deflections to age and team strength to create this “Adjusted Production” score, but it’s predictive power is lower compared to other positions. This is a “watch the tape” position.
How to read: “Jeffrey Okudah had a 98th percentile Adjusted Production score.”
|
Prospect |
College |
Adjusted Production |
|
Ohio State |
0.98 |
|
|
Louisiana Tech |
0.97 |
|
|
LSU |
0.96 |
|
|
Florida |
0.93 |
|
|
Michigan |
0.90 |
|
|
Utah |
0.85 |
|
|
Mississippi State |
0.83 |
|
|
Auburn |
0.72 |
|
|
Alabama |
0.71 |
|
|
Wake Forest |
0.69 |
|
|
Clemson |
0.68 |
|
|
Michigan State |
0.66 |
|
|
Utah |
0.66 |
|
|
Florida State |
0.64 |
|
|
Iowa |
0.62 |
|
|
Temple |
0.57 |
|
|
Alabama |
0.57 |
|
|
UCLA |
0.57 |
|
|
Ohio State |
0.51 |
|
|
Lamar Jackson |
Nebraska |
0.51 |
|
A.J. Green |
Oklahoma State |
0.50 |
|
Miami (FL) |
0.47 |
|
|
Troy Pride Jr. |
Notre Dame |
0.42 |
|
Penn State |
0.36 |
|
|
Reggie Robinson |
Tulsa |
0.32 |
|
Texas Christian |
0.31 |
|
|
Auburn |
0.29 |
|
|
Virginia |
0.27 |
|
|
Georgia Southern |
0.16 |
|
|
Tulane |
0.14 |
|
|
Pitt |
0.14 |
|
|
Florida Atlantic |
0.10 |
|
|
Stantley Thomas-Oliver |
Florida International |
0.07 |
|
Mississippi State |
0.05 |
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