College DT Impact: 658 Defensive Tackles Graded, But 113 Still Unranked

PFN Impact’s 2026 College Defensive Tackle Impact Rankings list 658 graded defensive tackles, according to www.profootballnetwork.com. Of those 658, 113 are not ranked yet because they have played under 20% of the busiest player’s snaps per game — under 51 snaps, per the source.

The rankings were updated Oct 4, with 1–50 shown on page 1 of 14, per PFN Impact. The DT+ grade is a single-number season grade from PFN’s college model, combining interior disruption through pressures, sacks, QB hits, tackles for loss and run stops.

The source does not specify which 113 players are unranked or their exact snap counts.

Every player is graded — but the bar keeps a three-snap cameo off the top of the board, according to PFN Impact. A “Non-Qualifiers” tick option exists to include those players in the display.

WHAT DT+ MEASURES

DT+ is not a highlight reel or a subjective eye-test grade. Per PFN, the College Defensive Tackle Impact model scores interior disruption by combining pressures, sacks, QB hits, tackles for loss and run stops into a single-number grade.

That means a tackle who collapses the pocket without finishing the sack still gets credit, as does one who plugs the run before the back reaches the line. The grade is built from what happens on the snap, not from reputation or recruiting stars.

The 2026 season grade updates as games are played, so it is shown on its own and left out of the pooled all-time ranking, per the source. A player’s current form is tracked separately from his career body of work, which keeps the live number clean.

A toggle on the rankings page allows comparison of two DT seasons, letting fans line up a player’s 2026 campaign against his own past production or against another tackle’s year, per PFN Impact.

The full methodology is linked from the rankings page, according to www.profootballnetwork.com. The source does not provide the exact weighting of each stat in the DT+ formula, so how much a sack outweighs a tackle for loss is part of the model’s internal math — not confirmed publicly.