Garbage Time and Rating Systems: Why Blowouts Complicate the Picture

When a team leads by 28 points late in the second half, something changes on the field. Starters come out. Backups rotate in. Walk-on quarterbacks get snaps. Defensive schemes relax. The football being played is real, but it's no longer representative of how either team plays when the game is actually in doubt.

This is garbage time—and it creates a persistent problem for any system trying to measure team strength.

What Garbage Time Means

In GIE's framework, garbage time is defined as any snap occurring in the third or fourth quarter when the score differential reaches 28 points or more. At that threshold, the incentive structure of the game fundamentally shifts. Coaches prioritize player development, injury prevention, and clock management over competitive football. The snaps that follow tell you something about roster depth and practice-squad talent, but very little about how the team actually competes.

The problem is simple: a 40-yard pass completion by a third-string receiver in a 35-point game counts identically in raw statistics to a 40-yard completion by an All-American in a one-score game. Both are recorded. Both affect per-play averages. Both influence ratings—unless you explicitly account for context.

How GIE Handles It Today

The model does not strip garbage-time snaps from its published ratings. Instead, it tags them. Every snap in GIE's database carries a garbage_time flag, and every player accumulates a garbage_time_pct metric showing what fraction of their snaps occurred in blowouts. This allows transparency: you can see which teams and players were most affected, and by how much.

The published ratings reflect all snaps equally. This is a deliberate choice, not an oversight. It means Indiana's offense—which accumulated 1,991 garbage-time yards across 258 snaps—carries that production into its overall efficiency profile. Stetson's defense allowed 1,489 garbage-time yards. North Dakota State's defense surrendered 1,656. These yards are real, they're recorded, and they're visible in the data.

But they're also flagged. You can see them. You can account for them yourself if you want a cleaner picture.

Which Teams Shift Most

Some teams' published ratings would look substantially different if we re-rated them using only competitive snaps.

Virginia University of Lynchburg is the most extreme case: 44% of their snaps occurred in garbage time (107 of 243 total plays). Their published rating reflects a roster that includes a lot of inexperienced depth. A competitive-snaps-only rating would be more volatile and less stable, but potentially higher or lower depending on how their starters actually performed in close games.

Stetson had 303 garbage-time plays across 1,070 total snaps (28% of their offense). They accumulated 1,741 garbage yards on offense and allowed 1,489 on defense. Stripping those would materially tighten their efficiency profiles in both directions.

Davidson logged 249 garbage plays (26% of snaps) and allowed 1,654 garbage yards defensively—the second-most in the dataset. Their published defensive rating is inflated by blowout exposure.

Lincoln (CA) and Northwestern State round out the top five by garbage-time share, each with over 20% of snaps occurring in lopsided games.

On the offensive side, Indiana, Texas Tech, and Old Dominion each accumulated over 1,400 garbage-time yards. Their published offensive ratings are boosted by that production.

Why We Don't Strip It (Yet)

There are legitimate reasons to keep garbage time in the model:

Sample size: Removing snaps shrinks the dataset, especially for teams in blowout-heavy seasons. Smaller samples mean noisier estimates.
Roster reality: Garbage time is part of how teams perform. It reflects depth, conditioning, and scheme flexibility.
Consistency: Stripping snaps introduces judgment calls. Where's the line? 28 points? 21? The threshold matters, and different thresholds produce different answers.

For now, GIE's stance is transparency over adjustment: tag the snaps, publish the flags, let analysts decide whether to weight them.

Looking Forward

This is part of GIE's commitment to showing its work. You can see which teams were most affected by garbage time, which players logged snaps in blowouts, and by how much. If you want a garbage-time-stripped view of a team's strength, the data is there to build it yourself.